IntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\\n\\n
By listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
All three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\\n\\n
"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\\n\\n
"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\\n\\n
In conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\\n\\n
“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\\n\\n
We invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\\n\\n
Feel free to share this news on social media and help us mark this memorable moment!
After years of being acknowledged as the world's leading publisher of Open Access books, today, we are proud to announce we’ve successfully launched a portfolio of Open Science journals covering rapidly expanding areas of interdisciplinary research.
\n\n\n\n
IntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\n\n
By listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
All three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\n\n
"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\n\n
"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\n\n
In conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\n\n
“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\n\n
We invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\n\n
Feel free to share this news on social media and help us mark this memorable moment!
\n\n
\n'}],latestNews:[{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"},{slug:"intechopen-identified-as-one-of-the-most-significant-contributor-to-oa-book-growth-in-doab-20210809",title:"IntechOpen Identified as One of the Most Significant Contributors to OA Book Growth in DOAB"}]},book:{item:{type:"book",id:"4655",leadTitle:null,fullTitle:"Applications of Digital Signal Processing through Practical Approach",title:"Applications of Digital Signal Processing through Practical Approach",subtitle:null,reviewType:"peer-reviewed",abstract:"This book is recommended to readers who can ponder on the collection of chapters authored/co-authored by various researchers as well as to researchers around the world covering the field of digital signal processing. This book highlights current research in the digital signal processing area such as communication engineering, image processing and power conversion system. The entire work available in the book mainly focusses on researchers who can do quality research in the area of digital signal processing and related fields. Each chapter is an independent research, which will definitely motivate young researchers to further study the subject. These six chapters divided into three sections will be an eye-opener for all those engaged in systematic research in these fields.",isbn:null,printIsbn:"978-953-51-2190-9",pdfIsbn:"978-953-51-5764-9",doi:"10.5772/59529",price:119,priceEur:129,priceUsd:155,slug:"applications-of-digital-signal-processing-through-practical-approach",numberOfPages:198,isOpenForSubmission:!1,isInWos:1,isInBkci:!1,hash:"b20308efd28e8a487949997c8d673fb8",bookSignature:"Sudhakar Radhakrishnan",publishedDate:"October 28th 2015",coverURL:"https://cdn.intechopen.com/books/images_new/4655.jpg",numberOfDownloads:13338,numberOfWosCitations:5,numberOfCrossrefCitations:5,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:6,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:16,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 23rd 2014",dateEndSecondStepPublish:"November 13th 2014",dateEndThirdStepPublish:"February 17th 2015",dateEndFourthStepPublish:"May 18th 2015",dateEndFifthStepPublish:"June 17th 2015",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"26327",title:"Dr.",name:"Sudhakar",middleName:null,surname:"Radhakrishnan",slug:"sudhakar-radhakrishnan",fullName:"Sudhakar Radhakrishnan",profilePictureURL:"https://mts.intechopen.com/storage/users/26327/images/system/26327.png",biography:"Dr. R. Sudhakar is a professor and head of the Department of Electronics and Communication Engineering, Dr. Mahalingam College of Engineering and Technology, Pollachi, India. He is also an associate editor for IEEE Access, from which he received the Outstanding Associate Editor Award in 2019. He is a reviewer of sixteen international journals, including IEEE Transactions on Systems, Man, and Cybernetics: Systems, International Arab Journal of Information Technology, and International Journal of Computer and Electrical Engineering, among others. He has published 110 papers in international, and national journals and conference proceedings. His areas of research include digital image processing, image analysis, wavelet transforms, and digital signal processing.",institutionString:"Dr. Mahalingam College of Engineering and Technology",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"5",institution:null}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"561",title:"Signal Processing",slug:"computer-science-and-engineering-signal-processing"}],chapters:[{id:"49358",title:"Optical Signal Processing for High-Order Quadrature- Amplitude Modulation Formats",doi:"10.5772/61681",slug:"optical-signal-processing-for-high-order-quadrature-amplitude-modulation-formats",totalDownloads:1969,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In this book chapter, optical signal processing technology, including optical wavelength conversion, wavelength exchange and wavelength multicasting, for phase-noise-sensitive high-order quadrature-amplitude modulation (QAM) signals will be discussed. Due to the susceptibility of high-order QAM signals against phase noise, it is imperative to avoid the phase noise in the optical signal processing subsystems. To design high-performance optical signal processing subsystems, both linear and nonlinear phase noise and distortions are the main concerns in the system design. We will first investigate the effective monitoring approach to optimize the performance of wavelength conversion for avoiding undesired nonlinear phase noise and distortions, and then propose coherent pumping scheme to eliminate the linear phase noise from local pumps in order to realize pump-phase-noise-free wavelength conversion, wavelength exchange and multicasting for high-order QAM signals. All of the discussions are based on experimental investigation.",signatures:"Guo-Wei Lu",downloadPdfUrl:"/chapter/pdf-download/49358",previewPdfUrl:"/chapter/pdf-preview/49358",authors:[{id:"174507",title:"Associate Prof.",name:"Guo-Wei",surname:"Lu",slug:"guo-wei-lu",fullName:"Guo-Wei Lu"}],corrections:null},{id:"49240",title:"High-Base Optical Signal Proccessing",doi:"10.5772/61504",slug:"high-base-optical-signal-proccessing",totalDownloads:1810,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:1,abstract:"Optical signal processing is a promising technique to enable fast data information processing in the optical domain. Traditional optical signal processing functions pay more attention to binary modulation formats (i.e., binary numbers) with single-bit information contained in one symbol. The ever-growing data traffic has propelled great success in high-speed optical signal transmission by using advanced multilevel modulation formats (i.e., high-base numbers), which encode multiple-bit information in one symbol with resultant enhanced transmission capacity and efficient spectrum usage. A valuable challenge would be to perform various optical signal processing functions for multilevel modulation formats, i.e., high-base optical signal processing. In this chapter, we review recent research works on high-base optical signal processing for multilevel modulation formats by exploiting degenerate and nondegenerate four-wave mixing in highly nonlinear fibers or silicon photonic devices. Grooming high-base optical signal processing functions including high-base wavelength conversion, high-base data exchange, high-base optical computing, and high-base optical coding/decoding are demonstrated. High-base optical signal processing may facilitate advanced data management and superior network performance.",signatures:"Jian Wang and Alan E. Willner",downloadPdfUrl:"/chapter/pdf-download/49240",previewPdfUrl:"/chapter/pdf-preview/49240",authors:[{id:"174233",title:"Prof.",name:"Jian",surname:"Wang",slug:"jian-wang",fullName:"Jian Wang"},{id:"174665",title:"Prof.",name:"Alan",surname:"Willner",slug:"alan-willner",fullName:"Alan Willner"}],corrections:null},{id:"48732",title:"Multitones’ Performance for Ultra Wideband Software Defined Radar",doi:"10.5772/60804",slug:"multitones-performance-for-ultra-wideband-software-defined-radar",totalDownloads:2118,totalCrossrefCites:3,totalDimensionsCites:3,hasAltmetrics:0,abstract:"This chapter proposes and tests an approach for an unbiased study of radar waveforms’ performances. Through an empirical performance analysis, the performances of Chirp and Multitones are compared with both simulations and measurements. An ultra wideband software defined radar prototype was designed and the prototype has performances comparable to the state of the art in software defined radar. The study looks at peak-to-mean-envelope power ratio, spectrum efficiency, and pulse compression as independent waveform criteria. The experimental results are consistent with the simulations. The study shows that a minimum of 10 bits resolution for the AD/DA converters is required to obtain near-optimum performances.",signatures:"Julien Le Kernec and Olivier Romain",downloadPdfUrl:"/chapter/pdf-download/48732",previewPdfUrl:"/chapter/pdf-preview/48732",authors:[{id:"174716",title:"Prof.",name:"Olivier",surname:"Romain",slug:"olivier-romain",fullName:"Olivier Romain"},{id:"174717",title:"Dr.",name:"Julien",surname:"Le Kernec",slug:"julien-le-kernec",fullName:"Julien Le Kernec"}],corrections:null},{id:"49264",title:"Application of DSP Concept for Ultrasound Doppler Image Processing System",doi:"10.5772/61164",slug:"application-of-dsp-concept-for-ultrasound-doppler-image-processing-system",totalDownloads:2149,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Blood-flow measurements using Doppler ultrasound system are popular in ultrasonic diagnoses. But the blood-flow measurement inside the heart is difficult. There are many reasons behind it. The deep range and fast blood-flow are difficult to measure because of limitation of acoustic velocity. Moreover, strong heart valve signals mix into the blood-flow signal. Against such difficulties, the statistics mathematical model was applied to analyze many clinical data sets. The system identification method based on the mathematical model could realize a new blood-flow measurement system that has ultrasound Doppler information as input and electrocardiogram as output.",signatures:"Baba Tatsuro",downloadPdfUrl:"/chapter/pdf-download/49264",previewPdfUrl:"/chapter/pdf-preview/49264",authors:[{id:"65121",title:"Dr.",name:"Baba",surname:"Tatsuro",slug:"baba-tatsuro",fullName:"Baba Tatsuro"}],corrections:null},{id:"49098",title:"Lossy-to-Lossless Compression of Biomedical Images Based on Image Decomposition",doi:"10.5772/60650",slug:"lossy-to-lossless-compression-of-biomedical-images-based-on-image-decomposition",totalDownloads:2077,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The use of medical imaging has increased in the last years, especially with magnetic resonance imaging (MRI) and computed tomography (CT). Microarray imaging and images that can be extracted from RNA interference (RNAi) experiments also play an important role for large-scale gene sequence and gene expression analysis, allowing the study of gene function, regulation, and interaction across a large number of genes and even across an entire genome. These types of medical image modalities produce huge amounts of data that, for several reasons, need to be stored or transmitted at the highest possible fidelity between various hospitals, medical organizations, or research units.",signatures:"Luís M. O. Matos, António J. R. Neves and Armando J. Pinho",downloadPdfUrl:"/chapter/pdf-download/49098",previewPdfUrl:"/chapter/pdf-preview/49098",authors:[{id:"1177",title:"Prof.",name:"Antonio",surname:"Neves",slug:"antonio-neves",fullName:"Antonio Neves"}],corrections:null},{id:"48835",title:"Application of DSP in Power Conversion Systems — A Practical Approach for Multiphase Drives",doi:"10.5772/60450",slug:"application-of-dsp-in-power-conversion-systems-a-practical-approach-for-multiphase-drives",totalDownloads:3216,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Digital Signal Processing is not a recent research field, but has become a powerful technology to solve engineering problems in the last few decades due to the introduction by Texas Instruments in 1982 of the Digital Signal Processor. Fast digital signal processors have quickly become a cornerstone of high-performance electrical drives, where power electronic conversion systems have heavy online computation burdens and must be controlled using complex control algorithms. In this sense, multiphase drives represent a particularly interesting case of study, where the computational cost highly increases with each extra phase. This technology has been recognized in recent times as an attractive electrical drive due to its usefulness in traction, more-electric aircraft applications and wind power generation systems. However, the complexity of the required control algorithms and signal processing techniques notably increases in relation with conventional three-phase drives. This chapter makes a revision of the necessities of a high-performance multiphase drive from the digital signal processing perspective. One of the most powerful Texas Instruments’ digital signal processor (TMS320F28335) is used, and specific control algorithms, electronic circuits and acquisition processing methods are designed, implemented and analyzed to show its interest in the development of a high-performance multiphase drive.",signatures:"Hugo Guzman, Mario Bermúdez, Cristina Martín, Federico Barrero\nand Mario Durán",downloadPdfUrl:"/chapter/pdf-download/48835",previewPdfUrl:"/chapter/pdf-preview/48835",authors:[{id:"174330",title:"Dr.",name:"Hugo",surname:"Guzmán",slug:"hugo-guzman",fullName:"Hugo Guzmán"},{id:"174607",title:"Dr.",name:"Federico",surname:"Barrero",slug:"federico-barrero",fullName:"Federico Barrero"},{id:"174608",title:"Dr.",name:"Mario",surname:"Durán",slug:"mario-duran",fullName:"Mario Durán"},{id:"175630",title:"Mr.",name:"Mario",surname:"Bermúdez",slug:"mario-bermudez",fullName:"Mario Bermúdez"},{id:"175631",title:"Ms.",name:"Cristina",surname:"Martín",slug:"cristina-martin",fullName:"Cristina Martín"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"112",title:"Effective Video Coding for Multimedia Applications",subtitle:null,isOpenForSubmission:!1,hash:"09a9826a6f8e7d58cf8516c609b4fa05",slug:"effective-video-coding-for-multimedia-applications",bookSignature:"Sudhakar Radhakrishnan",coverURL:"https://cdn.intechopen.com/books/images_new/112.jpg",editedByType:"Edited by",editors:[{id:"26327",title:"Dr.",name:"Sudhakar",surname:"Radhakrishnan",slug:"sudhakar-radhakrishnan",fullName:"Sudhakar Radhakrishnan"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5364",title:"Recent Advances in Image and Video Coding",subtitle:null,isOpenForSubmission:!1,hash:"fda66fbfe658c4c51b5c45c7cd5f3f59",slug:"recent-advances-in-image-and-video-coding",bookSignature:"Sudhakar Radhakrishnan",coverURL:"https://cdn.intechopen.com/books/images_new/5364.jpg",editedByType:"Edited by",editors:[{id:"26327",title:"Dr.",name:"Sudhakar",surname:"Radhakrishnan",slug:"sudhakar-radhakrishnan",fullName:"Sudhakar Radhakrishnan"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6547",title:"Wavelet Theory and Its Applications",subtitle:null,isOpenForSubmission:!1,hash:"18c8eeba76232a47936f09f42fc739e6",slug:"wavelet-theory-and-its-applications",bookSignature:"Sudhakar Radhakrishnan",coverURL:"https://cdn.intechopen.com/books/images_new/6547.jpg",editedByType:"Edited by",editors:[{id:"26327",title:"Dr.",name:"Sudhakar",surname:"Radhakrishnan",slug:"sudhakar-radhakrishnan",fullName:"Sudhakar Radhakrishnan"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"7623",title:"Coding Theory",subtitle:null,isOpenForSubmission:!1,hash:"db1156342e3a1a46ff74cad035a3886b",slug:"coding-theory",bookSignature:"Sudhakar Radhakrishnan and Muhammad Sarfraz",coverURL:"https://cdn.intechopen.com/books/images_new/7623.jpg",editedByType:"Edited by",editors:[{id:"26327",title:"Dr.",name:"Sudhakar",surname:"Radhakrishnan",slug:"sudhakar-radhakrishnan",fullName:"Sudhakar Radhakrishnan"}],equalEditorOne:{id:"215610",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sarfraz",slug:"muhammad-sarfraz",fullName:"Muhammad Sarfraz",profilePictureURL:"https://mts.intechopen.com/storage/users/215610/images/system/215610.jpeg",biography:"Muhammad Sarfraz is a professor in the Department of Information Science, Kuwait University, Kuwait. 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\r\n\tOrganic electronics can impact healthcare, sports, and national security through inventions such as real-time biosensing and drug-delivery, stretchable and flexible sport track gear, and the electronic- nose and tongue. Organic semiconductors, based on carbon and hydrogen, two of the most abundant and low cost materials, can transduce ionic and electronic carriers into quantifiable data paving the way for multi-functional applications that are not easy to create with other material systems and often go beyond the working principle of the conventional field-effect transistor. We will begin our review with a general overview of the current state of OFETs focusing on complex architectures, materials and fabrication processes. We will discuss the device physics and explain the doping mechanisms that can exist in organic semiconducting channel materials. Then we will focus on exciting applications that include the electronic- nose and tongue, myriad biosensing applications for preventive, point-of-care testing and real-time drug delivery, emerging physico-chemical low cost sensing applications, and the well known flexible, stretchable electronics.
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1. Introduction
Nowadays, research activity in the field of automotive industry receives a strong influence due to necessity to reduce the emissions of polluting gasses in the atmosphere. Hence, replacing the classical internal combustion engines with electric propulsion systems that are non-polluting became a hot topic in research labs all over the world [1]. Different electrical machine structures, their power electronics and supply units are continuously developed and tested, aiming the goal of high efficiency at as low costs as possible. Induction machines and permanent magnet machines are now implemented on Tesla and Toyota electric vehicles. However, their design and building costs are higher compared with other machine topologies, such as the switched reluctance machine (SRM). The latter has the main drawback of more complex power electronics and complex control. However, with the advance of the semiconductors and processors, it became possible to develop reduced price electronics and their applied control for SRMs.
Another feature of the SRM is the ability to continuously operate even in faulted conditions and if added to the original topology, structural modifications one can reach a highly fault tolerant propulsion machine [2].
Designing an SR machine is not too complicated, however, it is important to establish during sizing process, proper flux density values in the magnetic core. Too low values have the outcome of an unsaturated machine and by this, poor power density and too high values will limit the developed power and cause core heating [3]. Proper sizing of the air-gap is having huge performance influence; hence, a compromise must be considered between low values and building costs that are increasing drastically for values smaller than 0.5 mm.
Choosing and designing the proper architecture for the power electronics for an SR machine is crucial from the point of view regarding costs and ability to perform torque linearization control. If no such dedicated control is required, only classical hysteresis one is engaged, there are simple power converters that can be used with minimal number of transistors. However, if one desires to develop and use torque smoothening procedures, topologies that allow these are mandatory to be used, based on complete or half-H bridge designs, with independent switch control. Moreover, the driver that turns on/off the power switches must be able to maintain the state of the switch for an unlimited time [4].
A serious drawback of the SRM is the increased torque ripples that are caused due to the working principle of the machine to switch the current from one phase to the next one that encounters the lowest magnetic reluctance. By this, the rotor moves from unaligned to aligned rotor to stator poles, the movement being characterized by a sudden instantaneous torque variation. Part of the torque ripple minimization can be handled during the design phase [5], shaping correctly the rotor poles function of the stator ones. However, this is limited up to an extent that is still considered too much for automotive applications. The main method for decreasing as much as possible the torque ripples that create mechanical stress, noise and vibrations is to engage direct instantaneous torque control (DITC) of current profiling based on torque sharing functions (TSF). For both, as mentioned in the previous paragraph, it is necessary to have certain electronics that allow their operation. Following the details presented in this chapter, one can see that the toque characteristic of the SRM can reach a shape just like that of an induction or synchronous motor, yet using a much cheaper and more simple machine structure.
To be more comprehensive when designing such a machine, it is more transparent if one considers a specific application. For this case, the application will be a light electric vehicle designed for people with physical disabilities. Based on an existing DC machine mounted on such a vehicle, the main parameters that will be the start-up for the design process are: the required output power (P2N) 1.2 kW, the supply voltage (UN) of 24 V, shaft speed (nN) of 3400 rpm and electromagnetic required torque (T) of 3.4 Nm. Besides these considerations, it is mandatory that the machine needs to fit in the place of the existing DC machine. Hence, the maximum dimensions allowed are as follows: for the outer diameter 115 mm and for the active stack length 150 mm.
2. Design of the switched reluctance machine
Based on the specifications detailed in the introduction part, one can start sizing the SRM. Before that the stator (QS) and rotor (QR) pole numbers must be imposed. Usually, three-phase SRMs are cheaper both in electronics and machine building, but encounter high torque ripples, while five- or six-phase machine with low torque ripples reach increased development costs. Hence, the best compromise is to develop a four-phase machine, with a QS/QR ratio of 8/6 [6]. Another parameter that must be imposed is the flux density toward the air-gap (Bgmax) at 1.9 T. The current computed function of the supply voltage and the machine’s requested power, considering an efficiency of 0.65 (low power SRMs have quite poor efficiency) is I = 80 A. The design process is an iterative one, as this will be explained later. Hence, the air-gap was set to a low value of g = 0.1 mm, this is due to the dimension limitations of the outer machine diameter.
The most influential parameter of the machine is the mean diameter [7] (Dg).
Dg=P2N⋅Qs⋅kσQR⋅π2⋅kL⋅nN60⋅Bgmax⋅(1−1Kcr)⋅AS3E1
In Eq. (1), kσ and kL coefficients are the leakage flux factors, chosen between 0.75 and 0.95, respectively, the aspect factor, which can be calculated from the rotor pole number using Eq. (2).
kL=π2⋅1QR3E2
It should be mentioned that for this particular design, as the active stack length is given in the specifications, one does not need to compute it any more. The term As represents the electrical loading that is chosen in the range 25,000–100,000 A/m, where higher values correspond to smaller dimensions [8]. Carter’s factor (KCR) considers the flux path’s distortion due to the shape of the salient poles. Its value ranges between 1.4 and 2. The ratio of the mean diameter with respect to the aspect factor will give an estimate of the active stack length of the machine (lS), but as mentioned for this design, this is a known value.
The stator and rotor pole pitch is computed as ratio between the mean diameter and the number of the poles, using Eq. (3).
τS,R=π⋅DgQS,RE3
The width of the stator and rotor poles (bpS and bpR) can be calculated by using the pole pitch values, considered about 0.1–1.3 of it. The values chosen for stator and rotor were, respectively, 0.8 and 1.15 to reach as low torque ripples as possible [6]. Using these values, the yokes of the stator and rotor can be computed considered in the range of 0.5–1 of the pole width. Smaller values will reach proper saturation in the magnetic cores [5, 9] which will help to extract the energy from the coils when the phase is turned off. However, too low values will saturate the core too much resulting in the overheating of machine.
The slot openings are used to determine function of the stator and rotor pole widths and the pole pitch values computed with Eq. (3).
bcS,cR=τS,R−bpS,pRE4
Using a catalogue value for the shaft (dax) one can now finalize the sizing process that regards the SRM’s rotor. The rotor pole height, meaning the dimension from the airgap to the rotor yoke, and the inner rotor diameter will be computed using Eqs. (5) and (6), both function of the rotor yoke height (hjR).
hpR=Dg−g2−hjR−dax2E5
DiR=Dg−g−hjR−hpRE6
To finalize the sizing process with regard to the stator; firstly, it is necessary to size the coils of the machine, because these influence the height of the stator poles. This process starts from the magnetomotive force (mmf). There are several methods to compute it, but one efficient and simple way is to take advantage of the known parameters, such as the air-gap length (g) and its flux density value (Bgmax), the saturation factor, the flux leakage factor (kρ) and the relative permeability of the air (µ0).
Θ=g⋅ksat⋅Bgmaxkρ⋅μ0E7
Now a round value of the number of turns can be established as a function of the magnetomotive force and the phase current (I) of the SRM.
Nf=round(ΘI)E8
Next, sizing the cross-section of the wire has handled function of the current density (Jc) in the range of 2.5–8 A/cm2.
Scond=IrmsJcE9
In Eq. (9), it is seen the rms value of the current (Irms) is used instead of its rated value. The reason is that the current is switched from one phase to another, and the machine has four phases; one phase will be energized for only ¼ of the entire period. Hence, the rms current will be computed as the function of the number of phases (Nphase) like in AC supply systems, based on Eq. (10).
Irms=INphaseE10
The used wire diameter can be computed as the function of the cross-section in Eq. (9). This value will be used for arranging the turns inside the stator slots, as it will be presented as follows. The total number of turns is placed in several layers. Each layer will have a certain number of turns (Nsp_strat), computed function of the slot opening (bcS), its insulation (giz) and the actual wire diameter.
Nsp_strat=round(lbob−2⋅giz1.05⋅d)E11
The number of layers (nstrat) is found by dividing the total number of turns by the number of turns in a layer. Now, the height of the coil can be used to find the function of the number of layers, the wire diameter and the isolation of each wire (giz_strat), using Eq. (12).
hbob=nstrat⋅(d+giz_strat)+2⋅gizE12
The area inside the stator slot occupied by the coil is used to compute function of the number of turns, the cross-section of the wire and a factor (ku) ranged between 0.5 and 0.85 that considers the wire surface imperfections.
Abob=Nf⋅ScondkuE13
The term Abob is used for only half of the stator slot. In one slot, two such areas need to fit as two phases sharing the same slot. Hence, the total slot area will be computed using Eq. (14).
Ac=1.1⋅2⋅AbobE14
The term ‘1.1’ is added as a safety caution because there are other imperfections of the coils that cannot be taken into calculation every time. Having these dimensions fixed, one can compute the height of the coil using Eq. (15).
hcS=round(AcbcS)E15
Usually for simplifying the cutting process, round values are imposed. At this point, it is easy to find the height of the stator pole (hpS), adding to the height of the coil the height of a nonmagnetic displacer (hlim) used to fix the coil into the slot.
hpS=hcS+hlimE16
At this point, having all the required dimensions, it is possible to compute the outer diameter of the machine, for this project, to check if this does not exceed the imposed value.
DM=Dg+g+2⋅hpS+2⋅hjSE17
To be able to compute the resistance of one phase winding, it is necessary to know the wire length function of the machine dimensions.
linf=2⋅Nf⋅(lS+hjS)E18
Finally, the resistance is given by Eq. (19) considering the cross-section and the material properties.
R=ρCu⋅linfScondE19
2.1. Analytic calculation of losses and torque in SR machines
To calculate the efficiency of the newly designed SR machine, different methods for losses approximation can be used [7, 10]. Preliminary, it is mandatory to compute the frequency of the flux density variation in the magnetic core, both for the stator and the rotor.
fjS=QS2⋅nN60fjR=QR2⋅nN60E20
The specific losses in the machine’s core, computed for standard values measured for 50 Hz and 1 T are calculated using Eq. (21), where BjS and BjR are the stator and rotor yoke flux densities.
pFeS=pFesp⋅BjS⋅fjSpFeR=pFesp⋅BjR⋅fjRE21
To calculate the losses in the machine and function of its dimensions, one needs to compute the weight of the assemblies of the core function of the used material’s properties.
The losses in the winding have computed function of the internal resistance and the phase current.
Pj=R⋅I2E23
The mechanical losses are estimated approximately 0.5% of the machine’s output power.
PM=0.005⋅P2NE24
Finally, the total losses of the machine will be the sum of the above calculated ones:
PT=Pj+PFe+PME25
Hence the efficiency will be
ηSRM=PoutPout+PTE26
The developed torque can be used to compute function of the mmf created in the machine and its main dimensions using Eq. (29).
TSRM=2⋅(Nf⋅I2)⋅Dg2⋅μ0⋅lS2gE27
The term 2g (twice the air-gap) in Eq. (29) stands because always two diametrically opposed poles contribute to the torque development, hence, the air-gap length is considered double along the flux path.
Starting from the requirements detailed at the beginning of the chapter and using the above presented breviary, an SRM designed for light electric vehicle was obtained with the main dimensions which are depicted in Figure 1.
Figure 1.
The resulted SRM dimensions: (a) the entire machine, (b) details of the stator and (c) details of the rotor.
To certify that the machine meets the requirements of developing at 80 A, a torque of 3.4 Nm at 3400 rpm, in finite element analysis (FEA) model was created in Cedrat Flux 2D software. The current in the windings was handled using hysteresis controller referenced at 80 A as depicted in Figure 2a. At rated current the mean torque reaches the value of 3.4 Nm, but, despite attempts to reduce the torque ripple by design, these are still quite high. In such cases, the SRM cannot be used for electric propulsion systems as those ripples create high noise and vibration in the mechanical transmission and the car’s body itself.
Figure 2.
The simulation results of the designed SRM: (a) the phase currents and (b) the developed torque.
3. Torque linearization control strategies for the SRM
The results shown in Figure 2 indicate that the operational skills of the SRM, but more, it is also proved that the torque ripples are too high compared to the requirements of an electric vehicle propulsion unit. The structure recorded a success up to an extent. However, the torque ripples need to be further reduce to fit the machine in the EV requirements. For this purpose, special control procedures are engaged, such as direct instantaneous torque control (DITC) [11, 12] or current profiling based on torque sharing functions (TSF) [13].
Before detailing each of the above-mentioned methods, some requirements regarding their implementation must be highlighted. Besides a good knowledge about the parameters of the machine, of the power converter and of the controller’s sampling frequency, each of the two methods is based on inserting into the control model look-up-tables (LUT). For DITC, the LUT must contain information of the variation of the torque versus current and rotor position, as depicted in Figure 3a. Usually the content of this LUT is fetched from the FEA model of the machine. If the laboratory facility permits it, it is better to record this data from experimental measurements. However, as its name mentions it, DITC is an instantaneous torque control; hence, at each computation sample, the controller must have precise information of the torque values. This information can be extracted from the LUT, knowing precisely the shaft position and the measured phase current.
Figure 3.
The look-up-table used for the DITC (a) and TSF (b).
The second control strategy, the current profiling based on TSF, requires a reversed structure of the LUT depicted in Figure 3a, having the variation of the current versus torque and rotor position. The data can be obtained proceeding for a reversed interpolation of the torque versus current and rotor position, with respect to the phase current. This LUT is depicted in Figure 3b.
3.1. Direct instantaneous torque control (DITC)
The DITC (see Figure 4a) method [14] invokes a procedure of torque smoothening based on the control of instantaneous torque developed by the machine, using a hysteresis band. The main advantage of this procedure is that it does not require any PI (proportional integral) or PID (proportional integral derivate). The actual shape of the torque is regulated based on a double-layered hysteresis band. The comparison of the torque with the hysteresis band returns directly the gate signals for the power switches. As the torque is not measured directly from the machine, but it is estimated from the LUT, the setup does not require an instantaneous torque transducer which usually costs too much.
Figure 4.
The DITC control scheme (a), the instantaneous torque (b), voltage of adjacent phases and (c) the phase torque (d).
Practically, the DITC is implemented using two hysteresis bands, one larger than the other. The controller divides these into three regions, two of them form the torque reference to the upper and lower extremities and the main one is placed in the middle as depicted in Figure 4a.
During single phase conduction, the torque is regulated inside the limits of the main (inner) band (as shown in Figure 4b). In Figure 4c, with blue the voltage of the outgoing phase is depicted, while with red the voltage of the incoming one is represented. With the same colors, in Figure 4d, with blue the torque of the outgoing phase is represented while with red the torque of the incoming one is shown. The main involvement of the DITC is reflected during phase commutation. During phase commutation, the torque is regulated by the incoming phase, on one hand, to maintain it inside the inner hysteresis band, and on the other hand, by the outgoing one that becomes energized just enough to increase the torque when it falls and reaches the lower limit of the outer band. On increasing the torque, this will be re-established inside the inner band. At this point, the current increases close to maximum value, hence the torque tends to increase fast. To compensate this issue, the outgoing phase is again energized but with negative voltage (Figure 4c) to force fast-fall of the torque to maintain it in the desired band. From the moment when the incoming phase is energized, despite the times when the torque gets out of the inner hysteresis band, the outgoing phase is kept at zero voltage. Hence, the phase torque is regulated precisely during phase commutation, as seen in Figure 4c, time interval when usually the increased ripples appear.
3.2. Torque sharing functions (TSF)
Despite DITC, there are control methods that are more precise based on shaping the current and by this, automatically modifying the torque profile to become close to the linear one. The torque sharing function (TSF) is engaged mainly in the region of phase switching. The outgoing and incoming phase currents are profiled based on specific functions in order to compensate the ripples in the torque characteristic. One important issue that needs to be controlled for this strategy is the overlap angle [15] that needs to be precisely 15 mechanical degrees θov:
θov≤θrot2−θoffE28
In Eq. (30), θrot denotes the period of the rotor and θoff the turn off angle; with θon the turn on angle of the phase is denoted for all the following equations. A general rule for engaging the TSF of the rotor position described in Eq. (31) is valid for all the following analysed cases [16, 17]. As it can be seen there are five levels of the control based on the rotor position. While the machine phase is in non-conducting region, the TSF is null. During the increase and decrease of the current, the slopes are described by functions finc(θ) and fdec(θ). If the region of the phase is in full conduction (neither increase nor decrease of the current), the TSF becomes equal with the reference torque. As it can be seen that the profile of the current is obtained using the LUT data depicted in Figure 3b.
In total, there are four different types of TSF named after the mathematical operator that describes them: linear, sinusoidal, exponential and cubic.
The linear TSF refers to the fact that the instantaneous torque during phase commutation follows a linear variation with the rotor position. The function that describes this variation is detailed in Eq. (32) for the increasing and decreasing slopes.
It has to be noted that during phase commutation the incoming and outgoing phases of the machine are both active.
Using sinusoidal TSF implies using functions with sinusoidal or co-sinusoidal evolution of the TFS during phase commutation. The model that refers to such variations is detailed in Eq. (33).
In Ref. [11], the functions detailed in Eq. (33) are presented only function of the on and off angles of the phase. Here, in order to improve the functionality, the overlap angle is also introduced.
The third model, the exponential TSF, considers the on and off angles, the actual rotor position and the overlap angle too, as detailed in Eq. (34).
Cubic TSF is the last involved method, described as third degree polynomial functions for both increasing and decreasing slopes, as explained in Eq. (35).
Plotting in Figure 5, all the four functions superimposed for comparison some important remarks can be underlined.
Figure 5.
The variation of the TSFs used in the SRM controller.
As depicted in Figure 5a, the TSF for the cubic and sinusoidal evolutions nearly overlap and for a better comparison in Figure 5b, a zoomed plot of the rising slopes of the functions is depicted.
The exponential one has the largest deviation from the linear one, the latter being considered for reference. Another important remark to be mentioned is that the machine’s geometry or its parameters do not have an important significance over the effectiveness of the TSFs. Main modifications regard changing the stator to rotor pole ratio. However, it is possible to invoke optimization regarding the losses and the torque variation [17], together with the on and off switching angles.
3.3. Testing the control strategies for torque linearization
As already stated, and depicted in Figure 2, the torque ripples of the SRM with ‘natural‘ hysteresis control strategy are too high to be used in EV propulsion systems [18]. However, applying the control procedures detailed in Section 3.2, this drawback can be compensated to reach a torque characteristic close to a linear one, comparable with the one of a permanent magnet synchronous or induction machine. To test the control strategies, a Matlab/Simulink model was created for the SRM based on a hybrid model based on equations and on data both fetched from the FEA model.
In Figure 6a and b, the simulation results for the DITC are depicted for an imposed speed of 1000 rpm testing at 1 and 3 Nm. The phase currents and the phase torques provide information of the contribution of each of them to the total electromechanical torque development. The latter, as seen, reaches a quite linear characteristic, which is maintained inside the hysteresis bands. One important mention that needs to be expressed is that for such simulation or real control, the computation step time must be imposed to values that allow at least 5–10 steps inside the hysteresis band. Another important issue is that the width of the bands automatically increases the switching frequency of the transistors. Hence, a compromise between the latter and the type of power switch used must be considered when sizing the bands.
Figure 6.
Simulated results for: (a) DITC @1 Nm, (b) DITC @ 3 Nm, (c) linear TSF @1 Nm and (d) linear TSF @3 Nm.
Plotting the results for the linear TSF was accomplished in Figure 6c and d for the same conditions as for the DITC. There are similarities between them; however, the results for the linear TSF are smoother than those obtained with DITC. The variation of the phase torque during phase switching is quite linear, as expected for this method. Both for the DITC and the linear TSF tests were performed at low and rated torque to prove the operational skills in extreme conditions. As Figure 6 shows that the expectations are reached in all the cases. Tests were performed ranging the rotor speed from low to rated one and still the controller responded well, linearizing the torque as expected.
The other three TSF strategies, the exponential, cubic and sinusoidal ones were tested for 1000 rpm at 3 Nm and are depicted in Figure 7. As seen, these too can linearize the shape of the instantaneous torque.
Figure 7.
Simulated results for exponential, cubic and sinusoidal TSF @3 Nm.
However, the lowest ripple is yelled by the exponential TSF while for the cubic and sinusoidal, during phase commutation there are some spikes that are visible in the plots. However, as global conclusion, the DITC and all the four TSFs can move the SRM from the point of high torque ripples to the point where these are neutralized by obtaining a linear characteristic. By this, the SRM becomes a candidate with serious advantages for the field of electric vehicle propulsion systems, combining low costs, high efficiency, fault tolerance and linear torque, over the entire range of speed and torque values.
4. Custom made SRM electronic converter architecture
In SRM-drive application, the 48 V input voltage seems to present some advantages in comparison with the 24 V systems. For application where the 48 V is not available, as for the designed SRM, this section is presenting a possible solution regarding the electronics that can enhance the performances of SRM in 24 V systems. One way to boost the input voltage by means of a front-end converter is increasing the voltage up to 48 V. For this, numerous electronic circuits can be implemented [19]. Usually, these converters are using an inductance that can increase the size of the converter, but also its price.
In this section, based on a derived C-dump topology [20], a low-cost SRM electronic circuit is presented which can add a boost voltage to a regular asymmetrical converter, increasing the overall performances of the drive system. The present circuit is fed from a 24-V power supply, as designed, and can perform in some situations like the classic SRM converter with 48 V input voltage. This is achieved, as depicted in Figure 8, by adding the transistor Q and the capacitor C to a regular asymmetrical SRM drive. Moreover, the input diode D is needed for proper control of the power flow. This diode is adding some losses to the circuit, but the auxiliary feature obtained by adding protection in revered polarizations is an important characteristic for automotive electronics. The auxiliary circuit is boosting the voltage across the capacitor C, by recovering the energy from the motor during de-fluxing. The voltage across C can be higher than the input voltage and this energy can be re-used to drive the motor when needed. Thus, with proper control, the motor can be fed in this situation with a higher voltage then the input voltage. If the voltage across C is regulated to a 48 V, the drive can act in some working modes like a 48-V drive system.
Figure 8.
Proposed SRM boost converter.
The energy recovered from the motor is not high enough to fed the motor all the time, but if we consider that the high voltage is strongly needed only in some particularly situations like the beginning of the phase energizing, the stored energy in the capacitor C could be sufficient.
The circuit is presented in Figure 8, while Figure 9 highlights the main working modes for one phase. In the first two figures (Figure 9a and b), the phase fluxing is presented, while Figure 9c and d highlights de-fluxing possible working modes.
Figure 9.
Operation points for the investigated converter topology; one phase is considered; (a and b) phase energising; (c and d) phase de-fluxing.
In the followings, two comparison situations will be presented to highlight the advantages obtained by using the presented topology in correlation with the regular asymmetrical SRM converter, applied on a 48-V SRM. In Figure 10 and 11, the instantaneous toque, the phase current and the phase voltage are presented at 800 and 1000 rpm, for the analyzed converter topologies.
Figure 10.
Waveforms for the proposed converter (a) and regular asymmetrical SRM converter (b) at 1000 rpm.
Figure 11.
Waveforms for the proposed converter (a) and regular asymmetrical SRM converter (b) at 800 rpm.
This circuit is working with different voltage levels, thus the control of the T1 switch should be correlated with the working speed. At low speed, the energy needed to obtained the 48 V across the C is easily obtained, thus the excess energy is used during normal phase operation, or correlated with special control algorithms that can be used for smoothing the torque ripple at low speeds. At high speeds, the energy recovered in the capacitor C is just high enough for full or partial first energising of the phase coil.
If the energy recovered in the capacitor C is managed in the right way, the drive converter can act almost like a 48-V converter. This is boosting the performance of the drive system, by adding flexibility regarding the torque control, extend the working range and is expected to add 3–5% on the system efficiency. Moreover, the presented converter topology can be used to enhance the performances also in 12 V systems.
Comparing the results in Figure 10 and 11, a first remark regards the slope of the energized coil. It can be observed that due to boosted voltage, the slope of the current is faster than in the case of non-boosted one. On the other hand, if comparing the mean torque, developed by the machine for all cases, at 1000 rpm this value reaches 3.36 Nm for the boosted case, instead of 3.18 Nm for the regular converter. For the second case of analysis, the mean torque in the case of the modified converter yells for 3.65 Nm while for the regular one reaches only 3.55 Nm.
Implying such changes, one can express that with low cost modifications of a classical asymmetrical converter structure, higher performances can be obtained. It is true that the gain is not extremely high, but considering that the subject is dedicated to electric propulsion systems, each step forward in increasing the autonomy of the vehicle is an addition to the actual progress of science in this field of high interest nowadays.
5. Conclusions
The goal of the chapter is to offer a solution as a complete development tool for the reader to be able to design an SRM, design an increased performance power converter for it and create smart control strategies to reach linear torque characteristics as requirement for electric propulsions. Combining analytical models of the design with finite element analysis-based validation can reach in a properly design machine. Usually, a backtracking concept is engaged, performing changes at the level of design and observe performance modifications during FEA simulations. Once the machine fits in the designer’s expectations, adding an electronic power converter and torque smoothening strategies becomes the second and third steps in the design of the system.
The issues detailed in the chapter points out that an SRM can be used easily in the field of electric propulsion. Placing it in the list of serious candidates for the automotive industry, adds to the actual status of research focused on PMSMs or AC machines, with a low cost, robust and simple solution. Comparing the SRM with the above-mentioned machines, it can be stated that all need precise rotor position measurement, performed by a resolver, all need power electronics and a main electronic digital controller. However, the price of electronics nowadays decreased a lot due to fast advance. Hence, the battle on financial level is now dictated by the architecture of the machine, the materials used and the complexity of its geometry. Regarding the magnetic cores, the windings, the use of permanent magnets, etc., a comparative analysis of the ac machines with the SRM points strongly for higher costs and more complex manufacturing process.
Worldwide, there are already several companies that invest in development of SR machines for propulsion systems, both for light and heavy electrical vehicles.
\n',keywords:"switched reluctance machine (SRM), design breviary, power electronics, torque smoothening, light electric vehicle",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/55557.pdf",chapterXML:"https://mts.intechopen.com/source/xml/55557.xml",downloadPdfUrl:"/chapter/pdf-download/55557",previewPdfUrl:"/chapter/pdf-preview/55557",totalDownloads:1736,totalViews:428,totalCrossrefCites:0,totalDimensionsCites:0,totalAltmetricsMentions:0,impactScore:0,impactScorePercentile:50,impactScoreQuartile:2,hasAltmetrics:0,dateSubmitted:"November 15th 2016",dateReviewed:"April 18th 2017",datePrePublished:null,datePublished:"June 21st 2017",dateFinished:"May 24th 2017",readingETA:"0",abstract:"In the last decade, increased tendency in the field of automotive industry was focused on the development of highly efficient and low-cost electric propulsion systems to replace the existing internal combustion solutions. The aim is to reduce the pollution due to carbon dioxide emissions into the air. Several electric machine topologies with their power electronics, control and supply units are continuously in the development process to reach the desired goal. One such machine is the switched reluctance machine (SRM), reaching increased power density, low cost and possibility of continuous operation despite fault occurrence. Designing the machine, choosing its power electronics and controlling the machine to diminish the negative effect of the torque ripples are key points in reaching the proper propulsion system. The main topics presented in detail in this chapter are managing the reader’s skills with an analytic design breviary, presenting the machine’s control strategies for instantaneous torque linearization and finally, showing a power converter topology with increased performances in low voltage applications. To be more close to such an application, the exampled machine is developed for a light electric vehicle for people with physical disabilities. Operational skills of the machine will be validated based on complex simulations.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/55557",risUrl:"/chapter/ris/55557",book:{id:"6017",slug:"switched-reluctance-motor-concept-control-and-applications"},signatures:"Mircea Ruba and Petre Dorel Teodosescu",authors:[{id:"190371",title:"Dr.",name:"Mircea",middleName:null,surname:"Ruba",fullName:"Mircea Ruba",slug:"mircea-ruba",email:"mircea.ruba@emd.utcluj.ro",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/190371/images/system/190371.png",institution:{name:"Technical University of Cluj-Napoca",institutionURL:null,country:{name:"Romania"}}},{id:"195867",title:"Dr.",name:"Petre",middleName:"Dorel",surname:"Teodosescu",fullName:"Petre Teodosescu",slug:"petre-teodosescu",email:"petre.teodosescu@emd.utcluj.ro",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Technical University of Cluj-Napoca",institutionURL:null,country:{name:"Romania"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Design of the switched reluctance machine",level:"1"},{id:"sec_2_2",title:"2.1. Analytic calculation of losses and torque in SR machines",level:"2"},{id:"sec_4",title:"3. Torque linearization control strategies for the SRM",level:"1"},{id:"sec_4_2",title:"3.1. Direct instantaneous torque control (DITC)",level:"2"},{id:"sec_5_2",title:"3.2. Torque sharing functions (TSF)",level:"2"},{id:"sec_6_2",title:"3.3. Testing the control strategies for torque linearization",level:"2"},{id:"sec_8",title:"4. Custom made SRM electronic converter architecture",level:"1"},{id:"sec_9",title:"5. Conclusions",level:"1"}],chapterReferences:[{id:"B1",body:'Vrazic M, Vuljaj D, Pavasovic A, Paukovic H. Study of a vehicle conversion from internal combustion engine to electric drive. In: IEEE International Energy Conference, Croatia; 13-16 May 2014. pp. 1544–1548. ISBN: 978-1-4799-2449-3'},{id:"B2",body:'Ruba M, Viorel IA, Szabó L. 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In: 2016 IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR; 19th-21st May 2016; Cluj Napoca, Romania. ISBN: 978-1-4673-8691-3'},{id:"B19",body:'Tomaszuk A, Krupa A. High efficiency high step-up DC/DC Converters a Review. Bulletin of the Polish Academy of Sciences Technical Sciences. 2011;59(4):475–483. ISSN: 2300-1917'},{id:"B20",body:'Lee TW, Yoon YH, Yuen-Chung Kim, Lee BK, Won CY. Control of c-dump converters fed switched reluctance motor on an automotive application. Electric Power Systems Research. 2007;77(7):804–812. ISSN 0378-7796'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Mircea Ruba",address:"mircea.ruba@emd.utcluj.ro",affiliation:'
Technical University of Cluj Napoca, Cluj, Romania
Technical University of Cluj Napoca, Cluj, Romania
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1. Introduction
1.1 History of computing
Evolution in one region of science and technology leads to the discovery of a new one. In less than a century, research and development of functional computing technologies have renovated science, technology, and nation massively. The first practical computer around the 20th century was not capable of doing mathematical computations, on its own. Practical devices need a solid physical implementation of theoretical concepts. Nowadays, computers are solving problems instantly and accurately provided the input is relevant, and a set of instructions given are favorable. It all started from World War II when Alan Turing created a real general-purpose computer with a storable program model and is known as the ‘Universal Turing Machine’. It was redesigned by Von Neumann and is now the most important architecture for almost every computer. The computers and their physical parts kept improving with time in terms of performance and their strengths. And gradually, the industry of computers became larger than the military department which initiated it. The advancement in control and understanding of humans over nature and physical systems has given us the latest electronic devices we are utilizing today [1].
2. A new kind of computing
Today’s computers are smaller, cheaper, faster, greatly efficient, and even more powerful as compared to early computers that used to be huge, costly, and more power-consuming. It becomes possible due to improvements in architecture, hardware components, and software running on them. Electronic circuits used in computers are getting smaller and smaller day by day. Transistors are small semiconductor devices that are used to amplify and also switch electric or electronic signals. They were used to be fabricated on a piece of silicon. The circuit was made by connecting these transistors together into a single silicon surface. The shape of circuits in an IC was printed together in all layers of silicon at the same time. This process takes the same amount of time even if the number of transistors in the circuit was increased. The cost of production of IC was decided by the size of silicon and not the number of transistors. This reduced the price of products due to which manufacturing and selling of IC increased and thus benefits and sales also. From the idea of connecting individual transistors to the collection of these transistors (Logic Gates) and finally, the collection of these Logic Gates used to get connected into a single integrated circuit (IC). Nowadays, a single IC can even integrate small computers onto it.
Gordon Moore, co-founder of Intel, in 1965, discovered that the number of transistors on a silicon microprocessor chip had made twice as much every year while the prices were reduced to half since their invention. This is known as Moore’s Law. Moore’s Law is considerable because it means that computers and their computing power get smaller and faster over time. Though this law is putting the brakes on now and consequently, the improvement in classical computers is not like before it used to be [2].
This leads to the idea of the smallest computer by reducing the size of the circuit up to the size of an atom. But then these circuits will not be able to act as a switch as electrons inside an atom can become invisible from one side of a barrier and appear on another side, i.e. they can exist in more than one place at the same time. This is due to the teleporting phenomena in quantum mechanics called “Quantum Tunneling”. It shows that the size of the circuits of the classical computer after 5–7 nanometers has reached their limit. The representation and processing of these computers can be illustrated by the law of classical physics that gives us an only deterministic justification of the Universe. But it fails to forecast all noticeable phenomena occurring in nature and this led to the discovery of quantum mechanics, the biggest changeover in physics. Thus, there is a need for new computing other than current classical computing to put its state into some physical information rather than a circuit. Since the quantum phenomena are bringing up more constraints on the design of the computers. It changes the basic building blocks of a computer that not only expects new type of hardware creation but also a new design, software, and layers of abstraction to facilitate the designers to create and exploit these systems even if their complexities scale over time. The design of the hardware components has to be governed by quantum properties [3].
Quantum Computing is a new kind of computing based on Quantum mechanics that deals with the physical world that is probabilistic and unpredictable in nature. Quantum mechanics being a more general model of physics than classical mechanics give rise to a more general model of computing- quantum computing that has more potential to solve problems that cannot be solved by classical ones. To store and manipulate the information, they use their own quantum bits also called ‘Qubits’ unlike other classical computers which are based on classical computing that uses binary bits 0 and 1 individually. The computers using such type of computing are known as ‘Quantum Computers’. In such small computers, circuits with transistors, logic gates, and Integrated Circuits are not possible. Hence, it uses the subatomic particles like atoms, electrons, photons, and ions as their bits along with their information of spins and states. They can be superposed and can give more combinations. Therefore, they can run in parallel using memory efficiently and hence is more powerful. Quantum computing is the only model that could disobey the Church-Turing thesis and thus quantum computers can perform exponentially faster than classical computers.
3. Need for quantum computers
Quantum computers can solve any computational problem that any classical computer can. According to the Church-Turing thesis, the converse is also true that classical computers can solve all the problems of quantum computers too. It means they provide no extra benefit over classical computers in terms of computability but there are some complex and impossible problems that cannot be solved by today’s conventional computers in a practical amount of time. It needs more computational power. Quantum computers can solve such problems in reasonably and exponentially lower time complexities, also known as “Quantum Supremacy” [4].
Peter Shor in 1993 showed that Quantum computers can help to solve these problems considerably more efficiently like in seconds without getting overheated. He developed algorithms for factoring large numbers quickly. Since their calculations are based on the probability of an atom’s state before it is actually known. These are having the potential to process data in an exponentially huge quantity. It also explains that a practical quantum computer could break the cryptographic secret codes. It can risk the security of encrypted data and communication. It can expose private and protected secret information. But the advantages of quantum computers are also kept in mind that is significantly more than its flaws. Hence, they are still needed and further research is going towards a brighter future.
4. Fundamentals of quantum computing
While designing the conventional computer, it was kept in mind that transistors’ performance especially when getting smaller, will be affected by noise if any type of quantum phenomenon takes place. They tried to avoid quantum phenomena completely for their circuits. But the quantum computer adapts a different technique instead of using classical bits and even works on the quantum phenomenon itself. It uses quantum bits that are analogous to classical bits and have two quantum states where it can be either 0 or 1 except it follows some quantum properties where it can have both values simultaneously leading to a concept of superposed bits.
5. Where the concept of bits came from?
Transistors are the fundamental construction blocks for an IC which are connected through wires in a circuit. They conduct electric signals between devices. The communication between transistors within an IC takes place through electric signals. The behavior of the signals is analog in nature. Therefore, their values are real numbers that change smoothly between 0 and 1. These electric signals can also interact with the environment resulting in noise. Therefore, a little change from 0 to 0.1 due to temperature or vibrations from the environment can drastically change the system’s behavior. There are two types of noise present in the environment. The first type of noise results from energy instabilities occurring suddenly within the object like temperature above absolute zero Kelvin. These are fundamental in nature. Other types of noise are the consequences of signal interactions. This type of noise could have corrected or designed. But neither of them got designed nor corrected or maybe left intentionally uncorrected at the hardware layer. They are systematic in nature [5].
To overcome these noises in analog circuits, the IC is built with transistors in such a way that it could work on digital signals (binary bits) instead of analog signals. These circuits are called ‘Logic Gates’. They perceive the electric signals containing values of real numbers as a binary digit or ‘bit’ of either 0 (low voltage) or 1 (high voltage). Registers are another type of Gate which stores a bit or the number of bits present in an input value to process further. Gates can remove noise from a signal by limiting the set of values a signal can hold. Constructing IC using logic gates rather than transistors simplifies the designing by creating a powerful circuit that is not sensitive to design and fabrication issues and facilitates abstraction to designers so that they can focus only on gate functions (Boolean functions) rather than circuit issues. Boolean functions are defined by the rules of Boolean algebra. They can use an automated design tool for mapping the required logic gates. A standard library containing a set of tested logic gates is integrated into the silicon chip design with the help of their manufacturing technology. Negligible error rates can be achieved using digital logic and standard libraries. This helps in making the design robust. Also, the data is encoded by adding some redundant bits in the memory using an error correction code. This code is checked at regular intervals to detect the error. It also helps in other traits of design like testing and debugging.
Quantum Bit or Qubit is the fundamental unit of quantum information that represents subatomic particles such as atoms, electrons, etc. as a computer’s memory while their control mechanisms work as a computer’s processor. It can take the value of 0, 1, or both simultaneously. It is a million times more powerful than today’s strongest supercomputers. Production and management of qubits are tremendous challenges in the field of engineering. They acquire both, digital as well as analog nature which gives the quantum computer their computational power. Their analog nature indicates that quantum gates have no noise limit and their digital nature provides a norm to recover from this serious weakness. Therefore, the approach of logic gates and abstractions created for classical computing is of no use in quantum computing. Quantum computing may adopt ideas only from classical computing. But this computing needs its own method to overcome the variations of processing and any type of noise. It also needs its own strategy to debug errors and handle defects in design.
Qubit has two quantum states similar to the classical binary states. The qubit can be in either state as well as in the superposed state of both states simultaneously. There is a representation of these quantum states also known as Dirac notation [6].
In this notation, the state label is kept between two symbols | and ⟩. Therefore, states are written as |0⟩ and |1⟩ which are literally having analog values and both are participating to give any value between 0 and 1 given that sum of probability of occurrence of each state must be 1. Thus any quantum bit wave function can be expressed as a two-state linear combination each with its own complex coefficient i.e. |w⟩ = x |0⟩ + y |1⟩ where x and y are coefficients of both the states. The probability of the state is directly proportional to the square of the magnitude of its coefficient. |x|2 is the probability of identifying the qubit state 0 and |y|2 is the probability of identifying the qubit state 1. These probabilities when summed up must give a total of 1 or say 100% mathematically, i.e. |x|2 + |y|2 = 1.
6. Properties of quantum computing
In quantum physics, the quantum object does not exist in an entirely determined state. It looks like a particle but behaves like a wave when not being observed. This dual nature of particles leads to interesting physical phenomena. The state of any quantum object is expressed as a sum of possible participating states or a wave-function. Such states are coherent due to the interference of all the participating states either in a constructive or a destructive manner. Observation of quantum objects when they interact with some larger physical system results in the extraction of information. Such observation of quantum objects is called quantum measurement. Measurement can also result in the loss of information by disrupting the quantum state. These are some of the properties of quantum objects. Quantum objects referred here are the qubits in the case of quantum computing. The progress of any quantum system is regulated by Schrodinger’s equation that tells us about the change in the wave-function of the system due to the energy environment. This environment is the system Hamiltonian which is a mathematical description of energies experiencing from all forces felt by all components of the system. To control any quantum system, there is a need to control this environment by isolating the system from the forces of the universe that cannot be controlled easily and by assigning energy within this isolated area only. A system cannot be completely isolated. However, energy and information exchanges can be minimized. This interaction with the outside environment can lead to loss of coherence and can result in “Decoherence” [7].
The properties are the conceptual rules and mathematical manifestations that describe the behavior of the particles. Quantum computers use three fundamental properties of quantum mechanics to store, represent, and perform operations on data in such a way so that it can compute exponentially faster than any classical computer. The three properties are given as follows [8]:
Superposition
Superposition in quantum mechanics states that any two quantum states can be summed up (superposed) resulting in another valid quantum state. It is a fundamental principle of quantum mechanics. Oppositely we can say that any quantum state is the sum of two or more than two other unique states.
Superposition in quantum computing refers to the ability of a quantum system where quantum particle or qubit can exist in two different positions or say, in multiple states at the same time. It provides high-speed parallel processing in an unbelievable way and is very different from their classical equivalents that have binary constraints. The quantum computer system holds the information that exists in two states simultaneously. Qubits are brought into a superposition by influencing them with the help of lasers so that it can simultaneously store 0 and 1 at the same time. In classical computing, if there are 2 bits, the total possible values after combining we get are 4, out of which only 1 value is possible at any instant. But on the other hand, if there are 2 qubits in the quantum computer. The total possible values after combination are 4 and all are possible at once. It looks like unthinkable because it is not like gravity that can be proved easily just by looking at the falling of an apple. The laws of classical physics fail here because superposition only exists in the territory of quantum particles.
For example, when solving a puzzle-like maze, a quantum particle can decide to take the various paths at the same time using superposition. This process matches the function of the parallel computer. Due to this property, the qubit is able to navigate the maze in exponentially less time than a classical bit
Entanglement
Entanglement in quantum mechanics is a physical phenomenon where two or more quantum objects are inherently linked such that measurement of one rules the possible measurement of another. In other words, a pair or a group of particles interacts or share spatial locality such that the quantum state of each particle cannot be characterized independently of the other particle’s state in the same group even when they are separated by a large distance.
Entanglement is one of the important properties of quantum computing. It refers to the strong correlation existing between two quantum particles (physical properties of systems) or qubits. Qubits are linked together in a perfect instantaneous connection, even if they are isolated at any large distances such as located at the opposite ends of the Universe. They are entangled or defined with reference to each other. The fact is that the state of one particle influences the state of the other. It creates strong communication between qubits. Once they got entangled, they will stay connected even after separated at any distance. In classical computers, if bits are doubled, computational power also gets doubled. But in the case of Entanglement, adding extra bits to a quantum computer can increase its computational power exponentially. Quantum computer uses this property in a sort of quantum daisy chain.
Some examples of entanglement can be seen in nature such as electrons separated from each other at some distance inside an electron cloud are massively entangled with one another. If one electron is at both the states of spin-up and spin-down with each state having a probability of ½, a similar case is with the other electron.
Interference
The property of interference in quantum computers is similar to wave interference in classical physics. Wave interference happens when two waves interact with each other in the same medium. It forms a resultant wave with either their amplitudes added together when they are aligned in the same direction known as constructive interference or a resultant wave with their amplitudes canceled out when waves are in opposite direction known as destructive interference. The net wave can be bigger or smaller than the original wave depending on the type of interference. Since all subatomic particles along with light pose dual nature, i.e. particle and wave nature both. The quantum particle may experience interference. If each particle goes through both the slits (Young’s double-slit experiment) simultaneously due to superposition, they can cross its own path interfering with the path direction. The idea of interference allows us to intentionally bias the content of the qubit towards the needed state. However, it can also result in a quantum computer to combine its various computations into one making it more error-prone [9].
7. The topography of quantum technology
The quantum phenomena are not limited to just quantum computing but they apply to other technologies also including quantum information science, quantum communication, and quantum metrology. The progresses of all these technologies are mutually dependent on each other and can control as well as transform the entire quantum system. They share the same theory of physics, common hardware and related methods [10].
Quantum Information Science seeks the methods of encoding the information in a quantum system. It includes statistics of quantum mechanics along with their limitations. It provides a core for all other applications such as quantum computing, communications, networking, sensing and metrology.
Quantum Communication and networking concentrates on the conversation or exchange of information by encoding it into a quantum system to facilitate communication between quantum computers. Quantum cryptography is the subset of quantum communication in which quantum properties help to design the secure communication system.
Quantum sensing and metrology is the study and development of quantum systems. The drastic sensitivity of such a system to environmental nuisances can be utilized in order to measure important physical properties (e.g. electric and magnetic fields, temperature, etc.) more accurately than classical systems. Quantum sensors are based on qubits and are carried out using the experimental quantum systems.
Quantum computing is the central focus of this research which exploits the quantum mechanical properties of superposition, entanglement and interference to enact computations. In common, a quantum computer is a physical system that comprises a collection of qubits that must be isolated from the environment for their quantum state to stay coherent until it performs the computation. These qubits are organized and manipulated in order to enforce an algorithm and to achieve a result with high probability from the measurement of its final state.
Difference between classical computers and quantum computers [11].
Comparison key
Classical computer
Quantum computer
Basis of computing
Large scale integrated multipurpose computer based on classical physics
High speed parallel computer based on quantum mechanics
Information storage
Bit based information storage using voltage/ charge
Quantum bit (qubit) based information storage using electron spin
Bit values
Bits having a value of either 0 or 1 and can have a single value at any instant
Qubits having a value of 0,1 or sometimes negative and can have both values at the same time
Number of possible states
The number of possible states is 2 which is either 0 or 1
The number of possible states is infinite since it can hold combinations of 0 or 1 along with some complex information
Output
Deterministic- (repetition of computation on the same input gives the same output)
Probabilistic- (repetition of computation on superposed states gives probabilistic answers)
Gates used for processing
Logic gates process the information sequentially, i.e. AND, OR, NOT, etc.
Quantum logic gates process the information parallel
Scope of possible solutions
Defined and limited answers due to the algorithm’s design
probabilistic and multiple answers are considered due to superposition and entanglement properties
Operations
Operations use Boolean Algebra
Operations use linear algebra and are represented with unitary matrices.
Circuit implementation
Circuits implemented in macroscopic technologies (e.g. CMOS) that are fast and scalable
Circuits implemented in microscopic technologies (e.g. nuclear magnetic resonance) that are slow and delicate
8. The architecture of quantum computer
Architecture can be seen as a blueprint. The architecture of the quantum computer is a combination of classical and quantum parts and can be divided into 5 layers where each layer is represented as the functional part of the computer (Figure 1).
Application Layer- It is not a part of a quantum computer. It is used for representing a user interface, the operating system for a quantum computer, coding environment, etc. that are needed for formulating suitable quantum algorithms. It is hardware-independent.
Classical Layer- It optimizes and compiles the quantum algorithm into microinstructions. It also processes quantum-state measurement returned back from hardware in the below layers and gives it to a classical algorithm to produce results.
Digital Layer- It interprets microinstructions into signals (pulses) needed by qubit which act as quantum logic gates. It is the digital description of the required analog pulses in the below layers. It also gives quantum measurement as feedback to the above classical layer for merging the quantum outcomes to the final result.
Analog Layer- It creates voltage signals which are having a phase and amplitude modulations like in wave, for sending it to the below layer so that qubit operations can be executed.
Quantum Layer- It is integrated with the digital and the analog processing layer onto the same chip. It is used for holding qubits and is kept at room temperature (absolute). Error correction is handled here. This layer determines how well the computer performs.
Quantum Processing Unit (QPU) is made up of three layers including the digital processing layer, analog processing layer, and quantum processing layer. QPU and classical layer together constitute the Quantum Computer. Digital and Analog layers operate at room temperature.
Figure 1.
The architecture of a practical quantum computer. It can be divided into five layers, each performing different types of processing [12].
9. Hardware and software of quantum computers
There should be an interface between the quantum computer and conventional computers for tasks related to data, networks, and users. In order to function usefully, the quantum qubit system needs organized control that can be managed by a conventional computer. The necessary hardware components for analog quantum computers are designed in 4 conceptual layers. First is the “quantum data plane” where qubit is present. Second is the “control and measurement plane” which is liable for performing operations and measurement on qubits as needed. The third is the “control processor plane” which defines the sequence of those operations and measurement outcomes to inform successive quantum operations required by the algorithm. And the last one is “host processor” which is a classical computer running a conventional operating system that handles user interfaces, network access, and big storage data structures. The processor is controlled using a high bandwidth connection that it provides [13].
A functional Quantum computer also requires software components in addition to the hardware. It is comparable to classical computers. Various new tools including programming languages are needed to substantiate quantum operations so that programmers can formulate algorithms, compilers that can map them to the hardware used by quantum computers and some other supports which can evaluate, optimize, debug and test programs. The programming language must be designed for any targeting quantum architecture. Some preparatory tools have been developed to support quantum computers and are accessible on the web [14]. These tools must be designed in an abstract way so that software developers can think more algorithmically without much concern for details of quantum mechanics. This software must be flexible enough to adapt to the changes in hardware and algorithms. This is one of the biggest challenges in quantum computing to develop complete software architecture. Other than programming languages, there must be simulation tools for modeling quantum operations and tracking quantum states and optimization tools for evaluating needed qubit resources so that it can perform different quantum algorithms in an efficient manner. The main goal is to minimize the number of qubits and the operations required for the hardware [15].
10. What is quantum algorithm?
An algorithm is a sequence of instructions or a set of rules to be followed to perform any task or calculation. It is a step-by-step process for solving a problem, especially by a computer. Any algorithm that can be executed on a quantum computer is called the Quantum algorithm. Generally, it is possible to execute all classical algorithms on quantum computers. However, the algorithms should contain at least one unique quantum step due to the property of either superposition or entanglement to be called a Quantum algorithm.
Quantum algorithms are characterized by a quantum circuit. A quantum circuit is a prototype for quantum computation that includes each step of the quantum algorithm as a quantum gate. A quantum gate is an operation that can be performed on any number of qubits. It changes the quantum state of the qubit. It can be divided into a single-qubit or multi-qubit gate, depending on the number of qubits on which it is applied at the same time. A quantum circuit is determined with qubit measurement [16].
An algorithm executing on a simulator rather than hardware is very profitable in terms of execution time by replacing the measurement overhead at the end of the algorithm. It is also known as simulation optimization. A quantum algorithm is always reversible when compared to the classical algorithm. It implies that if the measurement is not considered, a quantum circuit can be traversed back which can undo all the operations done by a forward traversing of the circuit. According to the undecidability problem, all problems that are unsolvable by a classical algorithm cannot be solved by quantum algorithms too. But these algorithms can solve problems significantly faster than classical algorithms. Some examples of the quantum algorithm are Shor’s algorithm and Grover’s algorithm. The Shor’s algorithm can do factorization of very large numbers in exponentially faster than best-known classical algorithms [17], whereas, Grover’s algorithm is used for searching large unordered list or unstructured databases that is four times faster than the classic algorithm [18].
There are various quantum algorithms available so far are as follows [19]:
Fourier transform-based quantum algorithms
Amplitude amplification-based quantum algorithms
Quantum walks based algorithm
BQP-complete problems
Hybrid quantum/classical algorithms
11. Design limitations of quantum computer
The exponential computing power of quantum computers can be accomplished by assessing and rectifying any kind of design limitation which helps to avoid their quality degradation. There are four major design limitations. The first limitation is that the number of coefficients in Dirac notation that defines the state of a quantum computer rise exponentially with the rise in the number of qubits, only when all the qubits get entangled with each other. To obtain the full potential of quantum computing, qubits must follow the property of entanglement where the state of any qubit must be linked with states of other qubits. It cannot be achieved directly since it is hard to generate a direct relation between qubits. But it can be decomposed into a number of simple fundamental operations directly aided by the hardware. One can also perform indirect coupling which is known to be an overhead in machines in classical computing and is crucial at the early stages of development especially when qubits and gate operations are confined.
The second limitation is that it is impossible to copy an entire quantum system because of a principle called a no-cloning principle [20]. There is a risk of deletion of arbitrary information from the original qubits since the state of qubits or set of qubits are moved to another set of qubits rather than being copied. The generation and storage of copies of intermediate states or partial outcomes in memory is a necessary aspect of classical computing. But quantum computers need a different strategy. There are quantum algorithms that help to access classical bits from the storage so that it can be known which bits are loaded and being queried into the memory of the quantum system to perform its task successfully.
The third limitation is due to the absence of noise protection of qubit operations. The small deformities in gate operations or input signals are collected over time disturbing the state of the system because they are not discarded by the fundamental gate operations. This can highly affect the calculation preciseness, measurements and coherence of the quantum systems and lessen the qubit operations integrity [21].
The final limitation is the incapability of the quantum machine to identify its full state even after it has finished its operation. Assume quantum computer has introduced an initial set of qubits with the superposition of all states combination. After applying a function to this state, the new quantum state will have information about the function value for each possible input and measuring this quantum system will not give this information. Therefore, a successful quantum algorithm can be achieved by manipulating the system in such a way so that states after finishing the operations have a higher probability of getting measured than any other probable result.
12. Approaches to quantum computing
If we can design each gate slightly different from others, then the generated electric signals on communicating with each other produce periodic noise in each other. Thus, the noise immunity of gates used will be adequate to cancel the impact of various noise origins. Therefore, the concluding system will produce the same outcome as the logical gate model, even with millions of gates operating in parallel. The goal of the design is to minimize the noise in qubit that can prevent the qubit state to pass through noisy channels. The qubit state can be changed by changing its physical energy environment.
Thus, it leads to 2 approaches to quantum computing. In the first approach, the energy environment representing Hamiltonian is frequently changed smoothly as qubits operations are analog in nature and smoothly changes from 0 to 1 which cannot be completely corrected. It initializes the quantum state and then uses Hamiltonian directly to develop the quantum state. This is known as ‘Analog Quantum Computing’. It includes quantum annealing, quantum simulation and adiabatic quantum computers.
The second approach is similar to the classical computer approach where the problem is decomposed into a sequence of fundamental operations or gates. These gates have adequately defined digital outcomes for some input states. The set of fundamental operations of quantum computing is different from that of classical computing. This approach is referred to as ‘Gate-based quantum computing’.
13. Different categories of quantum computer
13.1 Analog quantum computer
This type of system performs its operation by manipulating the analog values in the Hamiltonian representation. It does not use quantum gates. It includes quantum annealing, quantum simulation and adiabatic quantum computing. The quantum annealing is done using some initial set of qubits that gradually changes the energy encountered by the system until the problem parameters are defined by Hamiltonian. This is done in order to get the highest probability final state of the qubits that corresponds to the solution of that problem. The adiabatic quantum computer performs computation using some initial set of qubits in the Hamiltonian ground state and then Hamiltonian is changed slowly enough such that it stays in its ground state or lowest possible energy while the process takes place. It has processing power similar to a gate-based computer but still cannot perform full error correction.
There are three basic types of analog quantum computing. These are divided on the basis of the required amount of processing power (number of qubits) and time to become practically and commercially available.
Quantum Annealing
A basic rule of physics is that everything inclines towards a minimum energy state of a problem. This behavior is also true in the world of quantum physics. Quantum annealing is naturally used for real low-energy solutions such as optimization problems [22]. It is useful where the best solution is needed out of all possible solutions available. However, it is least powerful among all the types available. An example of this demonstrates an experiment to optimize traffic flows in a crowded city. Such an algorithm could successfully decrease traffic by choosing a convenient path. Volkswagen performs this with Google and D-wave system partnership. Such an experiment can be applied on a universal scale for all to get the cost-productive travel. This method can be applied to a collection of industry problems. For example, optimization of the flight route, petroleum price, weather and temperature information and passenger details, developing commercial aircraft.
Quantum annealing is also used for digital modeling, sampling problems and other science fields. This will take only a couple of hours to model all the individual atoms of air flowing over an airplane’s wing at every tilts and speeds to formulate an optimized wing design. Using a sampling problem from energy-based distribution, the shape of energy can be characterized and is useful in machine learning problems. The samples improve the model using information about the state of the model for the given parameters.
Quantum Simulation
Quantum simulations examine certain problems in quantum mechanics that are beyond classical physics. Simulating quantum phenomena that are complex in nature is one of the most important applications of quantum computing such as quantum chemistry. It includes modeling of chemical reactions on a large number of quantum subatomic particles. Quantum simulators can be used to simulate the misfolded protein structure [23]. Diseases like Alzheimer’s are caused by misfolded proteins. Using random computer simulation, researchers test new treatment drugs and learn reactions. To achieve correctly folded protein structure and study all drug-induced effects, sequential sampling is done which could take more than a million years. Quantum computers can help evaluate it for making more effective treatments and medicines and it would be a significant healthcare improvement. In the future, quantum simulations will facilitate quick drug designing and testing by evaluating every possible drug combinations of protein.
Adiabatic Quantum Computing
Adiabatic quantum computing is the most dominant, commonly applicable and hardest to create. A truly adiabatic quantum computer will use over a million of qubits. The maximum qubits we can access is less than 128 today. The basic idea behind this is that the machine can be directed at any complex calculation and obtain an immediate solution. This comprises analyzing the annealing equations, quantum phenomena simulation, etc. [24]. At least fifty unique algorithms other than Shor’s and Grover’s algorithm have been formulated to run on this quantum computer.
There is a possibility that quantum computers could revolutionize the area of artificial intelligence and machine learning. Some work has been done on algorithms that would operate as building blocks of machine learning but the hardware and software for quantum AI are still not practically accessible.
13.2 NISQ gate-based computer
NISQ stands for Noisy Intermediate-Scale Quantum. It is also known as the Digital NISQ computer. These type of systems are gate-based and operates on a collection of qubits without full error correction and cannot restrict all the errors. The computations must be designed in a way so that they remain practical on a quantum system with little noise and can be finished in fewer and sufficient steps so that Decoherence and gate errors do not hide the outcomes [25].
13.3 Gate-based quantum computer with full error correction
Such computers also perform gate-based operations on a set of qubits with the implementation of the Quantum Error Correction algorithm. It reduces or corrects the noise in the system occurring during the computation period. Errors may include inadequate signals, device forgery or undesired bonding of qubits to the environment or with each other. The error is reduced to such a limit that the system seems valid and precise for all computations. Such quantum computers can have various realizations and they must fulfill some conditions such as there must be an availability of a well-defined two-level system that can be used as qubits, a potential to initialize those qubits, a sufficiently extended amount of Decoherence time which can perform error correction and computation, quantum gates (a set of quantum operations) common for every quantum computation and a capability of measuring each quantum bit individually without bothering others [26]. The analog quantum computers and digital NISQ computers are in progress while the gate-based computers with full error corrections are much more difficult and demanding.
14. Advantages of quantum computing
According to researchers, quantum computers will be able to solve those complex mathematical problems that traditional computers find impossible to solve in a practical timeframe.
It provides that computing power which can sufficiently process excessively large amounts of data (2.5 Exabyte daily i.e. equal to 5 million laptops) created all around the world to extract meaning from it.
Due to the teleportation phenomenon known as ‘quantum tunneling,’ it can work in parallel and use less amount of electricity, hence, reducing the power consumption up to 100 to 1000 times.
A general quantum computer is “thousands of times” faster than any classical computer. For example, Google has made a quantum computer [27] that is 100 million times faster than any classical computer present in its lab.
It can solve complex problems without being overheated since for its stability it kept cold up to 0.2 Kelvin inside the quantum system.
It can easily solve optimization problems such as finding the best route and scheduling trains and flights. It would also be able to compute 1 trillion moves in chess per second. Quantum computers will be able to crack the highest security unbreakable encryption techniques. However, it would also build hack-proof alternates.
It can bring up revolution from drugs to petroleum industries. The invention of new drugs will become possible. The marketable algorithms of financial organizations can be improved. The field of artificial intelligence can be improved soon.
15. Disadvantages of quantum computing
Due to advancements in quantum computers, the security of the existing Internet of Things (IoT) would fall down. Cryptographic techniques, Databases of government and private large organizations, banks, and defense systems can be hacked. Considering these facts, quantum computers can be terrible for our future.
The Quantum Computer will work as a different device and cannot replace classical computers entirely. Since, classical computers are better at some chores than quantum computers like email, excel, etc.
It has not been invented completely yet as only parts are being implemented and people are still imagining how it would look.
It is very delicate and error-prone. Any kind of vibrations affects subatomic particles like atoms and electrons. Due to which noise, faults, and even failures are possible. It leads to “Decoherence” which is a loss of coherence in quantum.
Quantum processors are very unstable and are very hard to test even. For the stability of the quantum computer, it is kept at 0.2 Kelvin (absolute Kelvin) which is nearly below the universe temperature [28]. It is very hard to maintain and regulate such temperature. The main problem is to really develop it as a personal computer with the price range in the budget of consumers. They will be firstly accessible to large scale industry then come to retail markets.
16. Applications of quantum computing
Many quantum algorithms have been evolved for quantum computers that deliver speedup which is a result of some fundamental mathematical methods like Fourier transform, Hamiltonian simulation, etc. Most algorithms require a large number of qubits of the best quality and some error correction to provide useful functionalities. These algorithms are formed in blocks rather than as a whole combined application since it is not practical. Therefore, it is a great challenge to create quantum applications that are really practically useful along with providing speedup with no error. The potential utility or say useful application of a quantum computer is an area of ongoing research. It is predicted that those applications require fewer qubits and can be carried out with a lesser amount of codes. It is possible to build algorithms that can run faster on quantum computers because of the distinct features of the qubit. Below are some of the primary applications that we will see soon in the upcoming era:
Cryptography
Many important elements of IT security and online security such as e-commerce and electronic secrecy depend on encryption and mathematical algorithms which are difficult to break such as factoring very huge numbers into primes (RSA technique). It is done by traversing through every possible factor using conventional computers which takes a significant amount of time. Also, some modern algorithms other than RSA like AES, ECDSA, etc. cannot be cracked using even high computing power. It makes it costly and cracking them even less practical. Quantum computers can do all these kinds of stuff in exponentially less amount of time. New quantum algorithms (e.g. Shor’s algorithm) are able to do it and more unique algorithms will develop [29]. But before that, new encryption techniques are being made to resist the quantum ones. Since the already running techniques and digital applications security are at greater risks.
Optimization Problems
Optimizing a problem implies finding the best solution to that problem out of all the possible solutions. It can be done by minimizing the error and even minimizing the steps available. Quantum computers are best in solving optimization problems. There are a lot of quantum algorithms out of which quantum optimization algorithms might improve the already existing optimization problems which are solved using conventional computers currently. Some of them are quantum semi-definite programming, quantum data fitting, and quantum combinatorial optimization. Some of the examples include simulating the molecular model like protein behavior for medical research which can lead to the new discovery of drugs for serious diseases like cancer, lung disease, etc. Another example is the Simulation of the cellular structure of batteries for improving battery power and life in electric vehicles. It could also solve travel-related problems in real traffic just like traveling salesman problems to find the shortest path between many cities, going to each city once and returning back, modeling the entire finance market, and many more. Traveling optimization is the major work under Volkswagen recently [30].
Artificial Intelligence
Artificial Intelligence counts on processing large and complex datasets. It is responsible for learning, inferring, and understanding. It learns until it stops mistaking and making errors in its task. It takes a significant amount of time in learning too. But quantum computing can make it easy and more accurate. Since conventional computers are only training the learning model from a specific size of the dataset to restrict the computation time. Quantum computers can train these models over a huge dataset without sticking into the exponential time. The more data it uses to train, the more accurate it will be. Generative models generate output such as image, audio, etc. that can be fed to quantum computers to improve its quality and accuracy. Natural Language processing is another example that can understand complete sentences. Quantum computers can make it understand all the phrases and speech in real-time with improved quality, which is computationally costly with today’s computer.
Quantum Simulation
It is an important utility in the field of quantum chemistry and material science [31]. This problem needs solving ground state energies of electrons and their wave functions, with or without the presence of some external electric or magnetic field. From the structure of atoms and electrons in chemistry to the rate at which chemical reactions are taking place, everything can be simulated very well. The classical computer when applied to this problem often fails to reach the level of precision needed to predict the rate of the chemical reaction.
It could also have commercial applications in areas such as medical and healthcare fields, chemical catalysts, storage of energy, pharmaceutical advancement and device displays.
17. Major challenges in quantum computing
The good news is that at any instant of time, the quantum state with the same number of quantum bits can stretch over all possible states as compared to classical computers and thus works in an exponentially massive space. However, to be able to use this space requires all qubits to remain interconnected. Even after such progress, improvements are still needed. The bad news is that making new and high-quality qubits does not guarantee the creation and efficient use of fault-tolerant quantum computers and is still having challenges in its path [32].
Qubits cannot naturally ignore the noise. Hence, the quantum system is more error-prone. It suffers from Decoherence. The biggest challenge is how it can handle any undesirable deviations or noise in quantum computers. Classical computers can produce clean noise-free outcomes by simply putting its state as off or ‘0’, which is not possible for quantum computers where errors occur in physical circuits. Qubits will gradually lose its information as well as interconnection (entanglement) between each other. The error rate is seen as a design parameter for such systems which should be improved in large qubit systems also. However, to make the qubits stable and error-free, they are being insulated from the outside environment in super-refrigerated fridges or vacuum chambers and accurately handled [33].
Qubits are neither completely binary nor digital. It is having analog properties also. Gate can reject noise by dealing with the input signal value of 0.8 and treating it as 1. But in the analog signal, every value between 0 and 1 is permitted since they have their meanings. Signals cannot be checked for any kind of noise or corruption. Since 0.8 can be 1 with some error or 0.8 without error. Presuming the error as 0 like Gates do or taking some noise value even if it was not present there can affect the adherence of the resulting quantum computation. Hence, there is a need for algorithms like quantum error correction similar to the logical error correction in classical computers. These algorithms can be run on a noisy gate-based quantum computer to eliminate the errors and noises present in them [34].
It is possible to employ a Quantum Error Correction algorithm on a quantum system. But quantum error correction requires dealing with the overhead such as a large number of qubits and their fundamental operations and generally needs more resources. Also, problems with large data inputs require a large amount of time to create the input quantum state that would monopolize the computation time lessening the quantum benefits.
Quantum algorithm development is another challenge since achieving quantum speedup expects entirely new types of algorithm design as the speed of computation depends on the design of the algorithm. The design of the algorithm should be corresponding to the number of qubits used.
Further development of software tools in addition to hardware, is required to create and debug quantum systems to help explain unknown issues and push towards designs.
Debugging quantum hardware and software is of utmost importance which depends on memory and intermediate machine states in classical computers. But in the case of quantum computing, states cannot be copied directly for later evaluation, and directly measuring intermediate state can bring it to halt. Hence, new strategies for debugging are essential for their development.
18. Importance of quantum computing
It is clearly possible to build a quantum computer that could perform computations that would run a lifetime on a classical computer. Practical applications of quantum computing need controlling the quantum phenomena and thus the quantum world to an exceptional level. This job requires substantial engineering and research to build, manage and employ a noiseless quantum system. The experiment with quantum supremacy is an important test of the theory of quantum mechanics that will help to improve the support of quantum theory and leads to unexpected discoveries. The development of aspects and components of quantum information technology and computing has already started to influence the area of physics. The quantum error correction theory to attain the fault-tolerant quantum system has proven important. The quantum information theory is practically useful to study physics and dynamics of multibody systems like a massive number of quantum subatomic particles and even in blackhole and related concepts. Advancement in this area is important for an accurate understanding of various physical structures. It has contributed to many other engineering fields like physics, mathematics, chemistry, computer science, material science, etc. It has also advanced classical computing. Strategies to develop a quantum computing algorithm have helped in improving the classical computing algorithm also. Research in the quantum algorithm has answered many questions in the computer science area. It can help to evaluate the safety of cryptographic systems, clarifying the limitations of physical computational and advancing computational methods. It will help to advance the human’s understanding of the universe. The qubits that are recently being used in quantum computing is also used for building sensors, precision clocks, and other applications. Quantum communication is used for communicating two quantum systems at distance. There is an increased risk of asymmetric cryptography as well as the entire security system. Hence, the actions are being taken towards new quantum cryptography. The development of quantum information, science, technology and computing is a global area now.
19. Future scope of quantum computing
A significant amount of struggle is remaining before a practical quantum computer can be launched. There are some future advancements that are needed. Some of the future needs are enabling a Quantum Error Correction algorithm that requires low overhead and decreases the error rates in qubits, developing more algorithms with lesser qubits for solving problems, reducing circuit thickness so that NISQ computers can be operated, the advancement of methods which can verify, debug, and simulate the quantum computers, scaling the number of qubits per processor in such a way so that error rate is maintained or can be improved if possible, interleaving of operations in a qubit, recognizing more algorithms that can reduce the computation time and creating input–output for the quantum processor.
Such ‘Quantum games’ are predicted in the future that will give unexpected situations and results that a player can experience because quantum computers will take all the possible operations and throws them into the game randomly due to its quantum properties like superpositioning and entanglement of qubits. It will be a never-ending experience.
‘Quantum computing in Cloud’ has the potential to overtake business initiatives like in other emerging technologies such as cryptography and artificial Intelligence. Since the classical simulation of fifty qubits is equal to the memory of one Petabyte that doubles with every single qubit added [35], the memory required should also be large enough to provide an environment for application development and testing for multiple developers to simulate quantum computers using suitable shared resources.
AI and machine learning problems could be solved in a practical amount of time that can be reduced from hundreds of thousands of years to seconds. Several quantum algorithms have been developed such as Grover’s algorithm for searching and Shor’s algorithm for factoring large numbers. More quantum algorithms are coming soon. Google has also declared that it would produce a workable quantum computer in the following 5 years with a 50-qubit quantum computer and will achieve quantum supremacy. IBM is also offering commercial quantum computers soon.
The progress of development in the field of quantum computers depends on many factors. Interest and financial support from the private sector can help developing commercial applications for NISQ computers. It depends on the progress of quantum algorithm development, availability of enough investment in the quantum technology field from government and the exchange of ideas within researchers, scientists and engineers [36]. To illuminate the limitations of quantum technology, a defensive result is also beneficial. It can help in overcoming those negative results which can lead to a new discovery.
\n',keywords:"quantum computing, real-time systems, program processors",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/73811.pdf",chapterXML:"https://mts.intechopen.com/source/xml/73811.xml",downloadPdfUrl:"/chapter/pdf-download/73811",previewPdfUrl:"/chapter/pdf-preview/73811",totalDownloads:1145,totalViews:0,totalCrossrefCites:3,dateSubmitted:"August 23rd 2020",dateReviewed:"September 18th 2020",datePrePublished:"October 29th 2020",datePublished:"February 23rd 2022",dateFinished:"October 29th 2020",readingETA:"0",abstract:"Quantum computing is a modern way of computing that is based on the science of quantum mechanics and its unbelievable phenomena. It is a beautiful combination of physics, mathematics, computer science and information theory. It provides high computational power, less energy consumption and exponential speed over classical computers by controlling the behavior of small physical objects i.e. microscopic particles like atoms, electrons, photons, etc. Here, we present an introduction to the fundamental concepts and some ideas of quantum computing. This paper starts with the origin of traditional computing and discusses all the improvements and transformations that have been done due to their limitations until now. Then it moves on to the basic working of quantum computing and the quantum properties it follows like superposition, entanglement and interference. To understand the full potentials and challenges of a practical quantum computer that can be launched commercially, the paper covers the architecture, hardware, software, design, types and algorithms that are specifically required by the quantum computers. It uncovers the capability of quantum computers that can impact our lives in various viewpoints like cyber security, traffic optimization, medicines, artificial intelligence and many more. At last, we concluded all the importance, advantages and disadvantages of quantum computers. Small-scale quantum computers are being developed recently. This development is heading towards a great future due to their high potential capabilities and advancements in ongoing research. Before focusing on the significances of a general-purpose quantum computer and exploring the power of the new arising technology, it is better to review the origin, potentials, and limitations of the existing traditional computing. This information helps us in understanding the possible challenges in developing exotic and competitive technology. It will also give us an insight into the ongoing progress in this field.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/73811",risUrl:"/chapter/ris/73811",signatures:"Surya Teja Marella and Hemanth Sai Kumar Parisa",book:{id:"10209",type:"book",title:"Quantum Computing and Communications",subtitle:null,fullTitle:"Quantum Computing and Communications",slug:"quantum-computing-and-communications",publishedDate:"February 23rd 2022",bookSignature:"Yongli Zhao",coverURL:"https://cdn.intechopen.com/books/images_new/10209.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83968-134-9",printIsbn:"978-1-83968-133-2",pdfIsbn:"978-1-83968-135-6",isAvailableForWebshopOrdering:!0,editors:[{id:"199527",title:"Associate Prof.",name:"Yongli",middleName:null,surname:"Zhao",slug:"yongli-zhao",fullName:"Yongli Zhao"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"297632",title:"Mr.",name:"Surya Teja",middleName:null,surname:"Marella",fullName:"Surya Teja Marella",slug:"surya-teja-marella",email:"suryatejamarella@gmail.com",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/297632/images/9335_n.jpg",institution:{name:"Western Michigan University",institutionURL:null,country:{name:"United States of America"}}},{id:"336267",title:"Mr.",name:"Hemanth Sai Kumar",middleName:null,surname:"Parisa",fullName:"Hemanth Sai Kumar Parisa",slug:"hemanth-sai-kumar-parisa",email:"hemanthsaikumargoud@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Leicester",institutionURL:null,country:{name:"United Kingdom"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_1_2",title:"1.1 History of computing",level:"2"},{id:"sec_3",title:"2. A new kind of computing",level:"1"},{id:"sec_4",title:"3. Need for quantum computers",level:"1"},{id:"sec_5",title:"4. Fundamentals of quantum computing",level:"1"},{id:"sec_6",title:"5. Where the concept of bits came from?",level:"1"},{id:"sec_7",title:"6. Properties of quantum computing",level:"1"},{id:"sec_8",title:"7. The topography of quantum technology",level:"1"},{id:"sec_9",title:"8. The architecture of quantum computer",level:"1"},{id:"sec_10",title:"9. Hardware and software of quantum computers",level:"1"},{id:"sec_11",title:"10. What is quantum algorithm?",level:"1"},{id:"sec_12",title:"11. Design limitations of quantum computer",level:"1"},{id:"sec_13",title:"12. Approaches to quantum computing",level:"1"},{id:"sec_14",title:"13. Different categories of quantum computer",level:"1"},{id:"sec_14_2",title:"13.1 Analog quantum computer",level:"2"},{id:"sec_15_2",title:"13.2 NISQ gate-based computer",level:"2"},{id:"sec_16_2",title:"13.3 Gate-based quantum computer with full error correction",level:"2"},{id:"sec_18",title:"14. Advantages of quantum computing",level:"1"},{id:"sec_19",title:"15. Disadvantages of quantum computing",level:"1"},{id:"sec_20",title:"16. Applications of quantum computing",level:"1"},{id:"sec_21",title:"17. Major challenges in quantum computing",level:"1"},{id:"sec_22",title:"18. Importance of quantum computing",level:"1"},{id:"sec_23",title:"19. Future scope of quantum computing",level:"1"}],chapterReferences:[{id:"B1",body:'Copeland, B. J. (2000). The modern history of computing, https://plato.stanford.edu/entries/computing-history/'},{id:"B2",body:'Theis, T. N., & Wong, H. S. P. (2017). The end of moore’s law: A new beginning for information technology. 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Nesteroff, 2009, Decoherence in adiabatic quantum computation, Physical Review A 79(2):022107'},{id:"B8",body:'Scott Amyx (2017), “quantum-computing-series-part-4-superposition-in-quantum-mechanics-381b98180f62”, https://medium.com/@ScottAmyx/quantum-computing-series-part-4-superposition-in-quantum-mechanics-381b98180f62'},{id:"B9",body:'Margaret Rouse (2011), “Quantum Intereference”, WhatIs.com, Tech Target https://whatis.techtarget.com/definition/quantum-interference'},{id:"B10",body:'J. Preskill, 2018, “Quantum Computing in the NISQ Era and Beyond,” arXiv:1801.00862'},{id:"B11",body:'Rajprasath Subramanian (2017), “10 Differences between Classical computing and Quantum computing,” Medium, https://medium.com/@prasathbhuvana89/10-difference-between-classical-computing-and-quantum-computing-5e1777aa590d'},{id:"B12",body:'Versluis, Richard (2020, March), ‘Here’s a Blueprint for a Practical Quantum Computer’, IEEE Spectrum, https://spectrum.ieee.org/computing/hardware/heres-a-blueprint-for-a-practical-quantum-computer'},{id:"B13",body:'Emily Grumbling and Mark Horowitz (2019), “5Essential Hardware Components of a Quantum Computer,” Quantum Computing: Progress and Prospects, ISBN 978-0-309-47969-1 | DOI 10.17226/25196'},{id:"B14",body:'For example, QISKit and OpenQASM from IBM (https://www.qiskit.org/) and Forest from Rigetti (https://www.rigetti.com/forest)'},{id:"B15",body:'Emily Grumbling and Mark Horowitz (2019),“6Essential Software Components of a scalable Quantum Computer,” Quantum Computing: Progress and Prospects, ISBN 978-0-309-47969-1 | DOI 10.17226/25196'},{id:"B16",body:'Mosca, M. (2008). “Quantum Algorithms”. arXiv:0808.0369 [quant-ph]'},{id:"B17",body:'P. Shor, 1994, “Algorithms for Quantum Computation: Discrete Logarithms and Factoring,” pp. 124-134 in 35th Annual Symposium on Foundations of Computer Science, 1994 Proceedings, https://ieeexplore.ieee.org'},{id:"B18",body:'L.K. Grover, 1996, “A Fast Quantum Mechanical Algorithm for Database Search,” pp. 212-219 in Proceedings of the Twenty-Eighth Annual ACM Symposium on Theory of Computing, https://dl.acm.org/proceedings.cfm'},{id:"B19",body:'“Quantum Algorithm,” https://en.m.wikipedia.org/wiki/Quantum_algorithm'},{id:"B20",body:'W.K. Wootters and W.H. Zurek (1982), “A single quantum cannot be cloned”, Nature 299(5886):802-803'},{id:"B21",body:'T.P. Harty, D.T.C. Allcock, C.J. Ballance, L. Guidoni, H.A. Janacek, N.M. Linke, D.N. Stacey, and D.M. Lucas, 2014, High-fidelity preparation, gates, memory, and readout of a trapped-ion quantum bit, Physical Review Letters 113:220501'},{id:"B22",body:'Fiona H (2018), “What is Quantum Annealing?”, D wave Leap, https://support.dwavesys.com/hc/en-us/articles/360003680954-What-is-Quantum-Annealing-#:~:text=Quantum%20annealing%20is%20a%20heuristic,represent%20solutions%20to%20a%20problem'},{id:"B23",body:'Vineeth Veeramachaneni (2018), “Protein Folding: How Quantum Computing can help”, Medium, https://medium.com/@veevinn/protein-folding-how-quantum-computing-can-help-6086b2456fb#:~:text=Protein%20folding%20is%20a%20problem,more%20quickly%2C%20and%20without%20limitations'},{id:"B24",body:'A. Mizel, 2014, “Fault-Tolerant, Universal Adiabatic Quantum Computation,” https://arxiv.org/abs/1403.7694'},{id:"B25",body:'J. Preskill, 2018, “Quantum Computing in the NISQ Era and Beyond,” arXiv:1801.00862'},{id:"B26",body:'D.P. DiVincenzo, 2000, The physical implementation of quantum computation, Fortschritte der Physik 48:771-783'},{id:"B27",body:'David Nield (2015), “Google’s Quantum Computer Is 100 Million Times Faster Than Your Laptop”, Science Alert, https://www.sciencealert.com/google-s-quantum-computer-is-100-million-times-faster-than-your-laptop'},{id:"B28",body:'R. Barends, J. Kelly, A. Megrant, A. Veitia, D. Sank, E. Jeffrey, T.C. White, et al., 2014, Logic gates at the surface code threshold: Supercomputing qubits poised for faulttolerant quantum computing, Nature 508:500-503'},{id:"B29",body:'Katwala, Amit (5 March 2020). “Quantum computers will change the world (if they work)”. Wired UK'},{id:"B30",body:'Vella, H. (2019). Quantum transforms travel. Engineering & Technology, 14(4), 50-53'},{id:"B31",body:'Norton, Quinn (2007-02-15). “The Father of Quantum Computing”. Wired'},{id:"B32",body:'Franklin, Diana; Chong, Frederic T. (2004). “Challenges in Reliable Quantum Computing”. Nano, Quantum and Molecular Computing. pp. 247-266. doi:10.1007/1-4020-8068-9_8. ISBN 1-4020-8067-0'},{id:"B33",body:'M. Joseph, K. Elleithy and M. Mohamed, “A new Quantum Processor Architecture,” 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York City, NY, USA, 2019, pp. 0483-0487. doi: 10.1109/UEMCON47517.2019.8992935'},{id:"B34",body:'A. Kandala, K. Temme, A.D. Corcoles, A. Mezzacapo, J.M. Chow, and J.M. Gambetta, 2018, “Extending the Computational Reach of a Noisy Superconducting Quantum Processor,” arXiv:1805.04492'},{id:"B35",body:'“Multiple Qubits (2017),”Microsoft Quantum docs, https://docs.microsoft.com/en-us/quantum/concepts/multiple-qubits'},{id:"B36",body:'Office of Science and Technology Policy, 2018, National Strategic Overview for Quantum Information Science, https://www.whitehouse.gov/wp-content/uploads/2018/09/ National-Strategic-Overview-for-Quantum-Information-Science.pdf'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Surya Teja Marella",address:"suryatejamarella@gmail.com",affiliation:'
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\r\n\tTransforming our World: the 2030 Agenda for Sustainable Development endorsed by United Nations and 193 Member States, came into effect on Jan 1, 2016, to guide decision making and actions to the year 2030 and beyond. Central to this Agenda are 17 Goals, 169 associated targets and over 230 indicators that are reviewed annually. The vision envisaged in the implementation of the SDGs is centered on the five Ps: People, Planet, Prosperity, Peace and Partnership. This call for renewed focused efforts ensure we have a safe and healthy planet for current and future generations.
\r\n
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\r\n
\r\n\tThis Series focuses on covering research and applied research involving the five Ps through the following topics:
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\r\n\t
\r\n
\r\n\t1. Sustainable Economy and Fair Society that relates to SDG 1 on No Poverty, SDG 2 on Zero Hunger, SDG 8 on Decent Work and Economic Growth, SDG 10 on Reduced Inequalities, SDG 12 on Responsible Consumption and Production, and SDG 17 Partnership for the Goals
\r\n
\r\n\t
\r\n
\r\n\t2. Health and Wellbeing focusing on SDG 3 on Good Health and Wellbeing and SDG 6 on Clean Water and Sanitation
\r\n
\r\n\t
\r\n
\r\n\t3. Inclusivity and Social Equality involving SDG 4 on Quality Education, SDG 5 on Gender Equality, and SDG 16 on Peace, Justice and Strong Institutions
\r\n
\r\n\t
\r\n
\r\n\t4. Climate Change and Environmental Sustainability comprising SDG 13 on Climate Action, SDG 14 on Life Below Water, and SDG 15 on Life on Land
\r\n
\r\n\t
\r\n
\r\n\t5. Urban Planning and Environmental Management embracing SDG 7 on Affordable Clean Energy, SDG 9 on Industry, Innovation and Infrastructure, and SDG 11 on Sustainable Cities and Communities.
\r\n
\r\n\t
\r\n
\r\n\tThe series also seeks to support the use of cross cutting SDGs, as many of the goals listed above, targets and indicators are all interconnected to impact our lives and the decisions we make on a daily basis, making them impossible to tie to a single topic.
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Later, he completed his postdoctoral research at the Center of Molecular Biosciences, University of the Ryukyus, Japan, as a recipient of the Japan Society for the Promotion of Science (JSPS) postdoctoral fellowship. He was also the recipient of the Australian Government Endeavour Research Fellowship for postdoctoral research as an adjunct senior researcher at the University of Tasmania, Australia. Dr. Hasanuzzaman’s current work is focused on the physiological and molecular mechanisms of environmental stress tolerance. Dr. Hasanuzzaman has published more than 150 articles in peer-reviewed journals. He has edited ten books and written more than forty book chapters on important aspects of plant physiology, plant stress tolerance, and crop production. According to Scopus, Dr. Hasanuzzaman’s publications have received more than 10,500 citations with an h-index of 53. He has been named a Highly Cited Researcher by Clarivate. He is an editor and reviewer for more than fifty peer-reviewed international journals and was a recipient of the “Publons Peer Review Award” in 2017, 2018, and 2019. He has been honored by different authorities for his outstanding performance in various fields like research and education, and he has received the World Academy of Science Young Scientist Award (2014) and the University Grants Commission (UGC) Award 2018. He is a fellow of the Bangladesh Academy of Sciences (BAS) and the Royal Society of Biology.",institutionString:"Sher-e-Bangla Agricultural University",institution:{name:"Sher-e-Bangla Agricultural University",country:{name:"Bangladesh"}}},{id:"187859",title:"Prof.",name:"Kusal",middleName:"K.",surname:"Das",slug:"kusal-das",fullName:"Kusal Das",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBDeQAO/Profile_Picture_1623411145568",biography:"Kusal K. Das is a Distinguished Chair Professor of Physiology, Shri B. M. Patil Medical College and Director, Centre for Advanced Medical Research (CAMR), BLDE (Deemed to be University), Vijayapur, Karnataka, India. Dr. Das did his M.S. and Ph.D. in Human Physiology from the University of Calcutta, Kolkata. His area of research is focused on understanding of molecular mechanisms of heavy metal activated low oxygen sensing pathways in vascular pathophysiology. He has invented a new method of estimation of serum vitamin E. His expertise in critical experimental protocols on vascular functions in experimental animals was well documented by his quality of publications. He was a Visiting Professor of Medicine at University of Leeds, United Kingdom (2014-2016) and Tulane University, New Orleans, USA (2017). For his immense contribution in medical research Ministry of Science and Technology, Government of India conferred him 'G.P. Chatterjee Memorial Research Prize-2019” and he is also the recipient of 'Dr.Raja Ramanna State Scientist Award 2015” by Government of Karnataka. He is a Fellow of the Royal Society of Biology (FRSB), London and Honorary Fellow of Karnataka Science and Technology Academy, Department of Science and Technology, Government of Karnataka.",institutionString:"BLDE (Deemed to be University), India",institution:null},{id:"243660",title:"Dr.",name:"Mallanagouda Shivanagouda",middleName:null,surname:"Biradar",slug:"mallanagouda-shivanagouda-biradar",fullName:"Mallanagouda Shivanagouda Biradar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243660/images/system/243660.jpeg",biography:"M. S. Biradar is Vice Chancellor and Professor of Medicine of\nBLDE (Deemed to be University), Vijayapura, Karnataka, India.\nHe obtained his MD with a gold medal in General Medicine and\nhas devoted himself to medical teaching, research, and administrations. He has also immensely contributed to medical research\non vascular medicine, which is reflected by his numerous publications including books and book chapters. Professor Biradar was\nalso Visiting Professor at Tulane University School of Medicine, New Orleans, USA.",institutionString:"BLDE (Deemed to be University)",institution:{name:"BLDE University",country:{name:"India"}}},{id:"289796",title:"Dr.",name:"Swastika",middleName:null,surname:"Das",slug:"swastika-das",fullName:"Swastika Das",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/289796/images/system/289796.jpeg",biography:"Swastika N. Das is Professor of Chemistry at the V. P. Dr. P. G.\nHalakatti College of Engineering and Technology, BLDE (Deemed\nto be University), Vijayapura, Karnataka, India. She obtained an\nMSc, MPhil, and PhD in Chemistry from Sambalpur University,\nOdisha, India. Her areas of research interest are medicinal chemistry, chemical kinetics, and free radical chemistry. She is a member\nof the investigators who invented a new modified method of estimation of serum vitamin E. She has authored numerous publications including book\nchapters and is a mentor of doctoral curriculum at her university.",institutionString:"BLDEA’s V.P.Dr.P.G.Halakatti College of Engineering & Technology",institution:{name:"BLDE University",country:{name:"India"}}},{id:"248459",title:"Dr.",name:"Akikazu",middleName:null,surname:"Takada",slug:"akikazu-takada",fullName:"Akikazu Takada",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/248459/images/system/248459.png",biography:"Akikazu Takada was born in Japan, 1935. After graduation from\nKeio University School of Medicine and finishing his post-graduate studies, he worked at Roswell Park Memorial Institute NY,\nUSA. He then took a professorship at Hamamatsu University\nSchool of Medicine. In thrombosis studies, he found the SK\npotentiator that enhances plasminogen activation by streptokinase. He is very much interested in simultaneous measurements\nof fatty acids, amino acids, and tryptophan degradation products. By using fatty\nacid analyses, he indicated that plasma levels of trans-fatty acids of old men were\nfar higher in the US than Japanese men. . He also showed that eicosapentaenoic acid\n(EPA) and docosahexaenoic acid (DHA) levels are higher, and arachidonic acid\nlevels are lower in Japanese than US people. By using simultaneous LC/MS analyses\nof plasma levels of tryptophan metabolites, he recently found that plasma levels of\nserotonin, kynurenine, or 5-HIAA were higher in patients of mono- and bipolar\ndepression, which are significantly different from observations reported before. In\nview of recent reports that plasma tryptophan metabolites are mainly produced by\nmicrobiota. He is now working on the relationships between microbiota and depression or autism.",institutionString:"Hamamatsu University School of Medicine",institution:{name:"Hamamatsu University School of Medicine",country:{name:"Japan"}}},{id:"137240",title:"Prof.",name:"Mohammed",middleName:null,surname:"Khalid",slug:"mohammed-khalid",fullName:"Mohammed Khalid",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/137240/images/system/137240.png",biography:"Mohammed Khalid received his B.S. degree in chemistry in 2000 and Ph.D. degree in physical chemistry in 2007 from the University of Khartoum, Sudan. He moved to School of Chemistry, Faculty of Science, University of Sydney, Australia in 2009 and joined Dr. Ron Clarke as a postdoctoral fellow where he worked on the interaction of ATP with the phosphoenzyme of the Na+/K+-ATPase and dual mechanisms of allosteric acceleration of the Na+/K+-ATPase by ATP; then he went back to Department of Chemistry, University of Khartoum as an assistant professor, and in 2014 he was promoted as an associate professor. In 2011, he joined the staff of Department of Chemistry at Taif University, Saudi Arabia, where he is currently an assistant professor. His research interests include the following: P-Type ATPase enzyme kinetics and mechanisms, kinetics and mechanisms of redox reactions, autocatalytic reactions, computational enzyme kinetics, allosteric acceleration of P-type ATPases by ATP, exploring of allosteric sites of ATPases, and interaction of ATP with ATPases located in cell membranes.",institutionString:"Taif University",institution:{name:"Taif University",country:{name:"Saudi Arabia"}}},{id:"63810",title:"Prof.",name:"Jorge",middleName:null,surname:"Morales-Montor",slug:"jorge-morales-montor",fullName:"Jorge Morales-Montor",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/63810/images/system/63810.png",biography:"Dr. Jorge Morales-Montor was recognized with the Lola and Igo Flisser PUIS Award for best graduate thesis at the national level in the field of parasitology. He received a fellowship from the Fogarty Foundation to perform postdoctoral research stay at the University of Georgia. He has 153 journal articles to his credit. He has also edited several books and published more than fifty-five book chapters. He is a member of the Mexican Academy of Sciences, Latin American Academy of Sciences, and the National Academy of Medicine. He has received more than thirty-five awards and has supervised numerous bachelor’s, master’s, and Ph.D. students. Dr. Morales-Montor is the past president of the Mexican Society of Parasitology.",institutionString:"National Autonomous University of Mexico",institution:{name:"National Autonomous University of Mexico",country:{name:"Mexico"}}},{id:"217215",title:"Dr.",name:"Palash",middleName:null,surname:"Mandal",slug:"palash-mandal",fullName:"Palash Mandal",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/217215/images/system/217215.jpeg",biography:null,institutionString:"Charusat University",institution:null},{id:"49739",title:"Dr.",name:"Leszek",middleName:null,surname:"Szablewski",slug:"leszek-szablewski",fullName:"Leszek Szablewski",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49739/images/system/49739.jpg",biography:"Leszek Szablewski is a professor of medical sciences. He received his M.S. in the Faculty of Biology from the University of Warsaw and his PhD degree from the Institute of Experimental Biology Polish Academy of Sciences. He habilitated in the Medical University of Warsaw, and he obtained his degree of Professor from the President of Poland. Professor Szablewski is the Head of Chair and Department of General Biology and Parasitology, Medical University of Warsaw. Professor Szablewski has published over 80 peer-reviewed papers in journals such as Journal of Alzheimer’s Disease, Biochim. Biophys. Acta Reviews of Cancer, Biol. Chem., J. Biomed. Sci., and Diabetes/Metabol. Res. Rev, Endocrine. He is the author of two books and four book chapters. He has edited four books, written 15 scripts for students, is the ad hoc reviewer of over 30 peer-reviewed journals, and editorial member of peer-reviewed journals. Prof. Szablewski’s research focuses on cell physiology, genetics, and pathophysiology. He works on the damage caused by lack of glucose homeostasis and changes in the expression and/or function of glucose transporters due to various diseases. He has given lectures, seminars, and exercises for students at the Medical University.",institutionString:"Medical University of Warsaw",institution:{name:"Medical University of Warsaw",country:{name:"Poland"}}},{id:"173123",title:"Dr.",name:"Maitham",middleName:null,surname:"Khajah",slug:"maitham-khajah",fullName:"Maitham Khajah",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/173123/images/system/173123.jpeg",biography:"Dr. Maitham A. Khajah received his degree in Pharmacy from Faculty of Pharmacy, Kuwait University, in 2003 and obtained his PhD degree in December 2009 from the University of Calgary, Canada (Gastrointestinal Science and Immunology). Since January 2010 he has been assistant professor in Kuwait University, Faculty of Pharmacy, Department of Pharmacology and Therapeutics. His research interest are molecular targets for the treatment of inflammatory bowel disease (IBD) and the mechanisms responsible for immune cell chemotaxis. He cosupervised many students for the MSc Molecular Biology Program, College of Graduate Studies, Kuwait University. Ever since joining Kuwait University in 2010, he got various grants as PI and Co-I. He was awarded the Best Young Researcher Award by Kuwait University, Research Sector, for the Year 2013–2014. He was a member in the organizing committee for three conferences organized by Kuwait University, Faculty of Pharmacy, as cochair and a member in the scientific committee (the 3rd, 4th, and 5th Kuwait International Pharmacy Conference).",institutionString:"Kuwait University",institution:{name:"Kuwait University",country:{name:"Kuwait"}}},{id:"195136",title:"Dr.",name:"Aya",middleName:null,surname:"Adel",slug:"aya-adel",fullName:"Aya Adel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/195136/images/system/195136.jpg",biography:"Dr. Adel works as an Assistant Lecturer in the unit of Phoniatrics, Department of Otolaryngology, Ain Shams University in Cairo, Egypt. Dr. Adel is especially interested in joint attention and its impairment in autism spectrum disorder",institutionString:"Ain Shams University",institution:{name:"Ain Shams University",country:{name:"Egypt"}}},{id:"94911",title:"Dr.",name:"Boulenouar",middleName:null,surname:"Mesraoua",slug:"boulenouar-mesraoua",fullName:"Boulenouar Mesraoua",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94911/images/system/94911.png",biography:"Dr Boulenouar Mesraoua is the Associate Professor of Clinical Neurology at Weill Cornell Medical College-Qatar and a Consultant Neurologist at Hamad Medical Corporation at the Neuroscience Department; He graduated as a Medical Doctor from the University of Oran, Algeria; he then moved to Belgium, the City of Liege, for a Residency in Internal Medicine and Neurology at Liege University; after getting the Belgian Board of Neurology (with high marks), he went to the National Hospital for Nervous Diseases, Queen Square, London, United Kingdom for a fellowship in Clinical Neurophysiology, under Pr Willison ; Dr Mesraoua had also further training in Epilepsy and Continuous EEG Monitoring for two years (from 2001-2003) in the Neurophysiology department of Zurich University, Switzerland, under late Pr Hans Gregor Wieser ,an internationally known epileptologist expert. \n\nDr B. Mesraoua is the Director of the Neurology Fellowship Program at the Neurology Section and an active member of the newly created Comprehensive Epilepsy Program at Hamad General Hospital, Doha, Qatar; he is also Assistant Director of the Residency Program at the Qatar Medical School. \nDr B. Mesraoua's main interests are Epilepsy, Multiple Sclerosis, and Clinical Neurology; He is the Chairman and the Organizer of the well known Qatar Epilepsy Symposium, he is running yearly for the past 14 years and which is considered a landmark in the Gulf region; He has also started last year , together with other epileptologists from Qatar, the region and elsewhere, a yearly International Epilepsy School Course, which was attended by many neurologists from the Area.\n\nInternationally, Dr Mesraoua is an active and elected member of the Commission on Eastern Mediterranean Region (EMR ) , a regional branch of the International League Against Epilepsy (ILAE), where he represents the Middle East and North Africa(MENA ) and where he holds the position of chief of the Epilepsy Epidemiology Section; Dr Mesraoua is a member of the American Academy of Neurology, the Europeen Academy of Neurology and the American Epilepsy Society.\n\nDr Mesraoua's main objectives are to encourage frequent gathering of the epileptologists/neurologists from the MENA region and the rest of the world, promote Epilepsy Teaching in the MENA Region, and encourage multicenter studies involving neurologists and epileptologists in the MENA region, particularly epilepsy epidemiological studies. \n\nDr. Mesraoua is the recipient of two research Grants, as the Lead Principal Investigator (750.000 USD and 250.000 USD) from the Qatar National Research Fund (QNRF) and the Hamad Hospital Internal Research Grant (IRGC), on the following topics : “Continuous EEG Monitoring in the ICU “ and on “Alpha-lactoalbumin , proof of concept in the treatment of epilepsy” .Dr Mesraoua is a reviewer for the journal \"seizures\" (Europeen Epilepsy Journal ) as well as dove journals ; Dr Mesraoua is the author and co-author of many peer reviewed publications and four book chapters in the field of Epilepsy and Clinical Neurology",institutionString:"Weill Cornell Medical College in Qatar",institution:{name:"Weill Cornell Medical College in Qatar",country:{name:"Qatar"}}},{id:"282429",title:"Prof.",name:"Covanis",middleName:null,surname:"Athanasios",slug:"covanis-athanasios",fullName:"Covanis Athanasios",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/282429/images/system/282429.jpg",biography:null,institutionString:"Neurology-Neurophysiology Department of the Children Hospital Agia Sophia",institution:null},{id:"190980",title:"Prof.",name:"Marwa",middleName:null,surname:"Mahmoud Saleh",slug:"marwa-mahmoud-saleh",fullName:"Marwa Mahmoud Saleh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/190980/images/system/190980.jpg",biography:"Professor Marwa Mahmoud Saleh is a doctor of medicine and currently works in the unit of Phoniatrics, Department of Otolaryngology, Ain Shams University in Cairo, Egypt. She got her doctoral degree in 1991 and her doctoral thesis was accomplished in the University of Iowa, United States. Her publications covered a multitude of topics as videokymography, cochlear implants, stuttering, and dysphagia. She has lectured Egyptian phonology for many years. Her recent research interest is joint attention in autism.",institutionString:"Ain Shams University",institution:{name:"Ain Shams University",country:{name:"Egypt"}}},{id:"259190",title:"Dr.",name:"Syed Ali Raza",middleName:null,surname:"Naqvi",slug:"syed-ali-raza-naqvi",fullName:"Syed Ali Raza Naqvi",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259190/images/system/259190.png",biography:"Dr. Naqvi is a radioanalytical chemist and is working as an associate professor of analytical chemistry in the Department of Chemistry, Government College University, Faisalabad, Pakistan. Advance separation techniques, nuclear analytical techniques and radiopharmaceutical analysis are the main courses that he is teaching to graduate and post-graduate students. In the research area, he is focusing on the development of organic- and biomolecule-based radiopharmaceuticals for diagnosis and therapy of infectious and cancerous diseases. Under the supervision of Dr. Naqvi, three students have completed their Ph.D. degrees and 41 students have completed their MS degrees. He has completed three research projects and is currently working on 2 projects entitled “Radiolabeling of fluoroquinolone derivatives for the diagnosis of deep-seated bacterial infections” and “Radiolabeled minigastrin peptides for diagnosis and therapy of NETs”. He has published about 100 research articles in international reputed journals and 7 book chapters. Pakistan Institute of Nuclear Science & Technology (PINSTECH) Islamabad, Punjab Institute of Nuclear Medicine (PINM), Faisalabad and Institute of Nuclear Medicine and Radiology (INOR) Abbottabad are the main collaborating institutes.",institutionString:"Government College University",institution:{name:"Government College University, Faisalabad",country:{name:"Pakistan"}}},{id:"58390",title:"Dr.",name:"Gyula",middleName:null,surname:"Mozsik",slug:"gyula-mozsik",fullName:"Gyula Mozsik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/58390/images/system/58390.png",biography:"Gyula Mózsik MD, Ph.D., ScD (med), is an emeritus professor of Medicine at the First Department of Medicine, Univesity of Pécs, Hungary. He was head of this department from 1993 to 2003. His specializations are medicine, gastroenterology, clinical pharmacology, clinical nutrition, and dietetics. His research fields are biochemical pharmacological examinations in the human gastrointestinal (GI) mucosa, mechanisms of retinoids, drugs, capsaicin-sensitive afferent nerves, and innovative pharmacological, pharmaceutical, and nutritional (dietary) research in humans. He has published about 360 peer-reviewed papers, 197 book chapters, 692 abstracts, 19 monographs, and has edited 37 books. He has given about 1120 regular and review lectures. He has organized thirty-eight national and international congresses and symposia. He is the founder of the International Conference on Ulcer Research (ICUR); International Union of Pharmacology, Gastrointestinal Section (IUPHAR-GI); Brain-Gut Society symposiums, and gastrointestinal cytoprotective symposiums. He received the Andre Robert Award from IUPHAR-GI in 2014. Fifteen of his students have been appointed as full professors in Egypt, Cuba, and Hungary.",institutionString:"University of Pécs",institution:{name:"University of Pecs",country:{name:"Hungary"}}},{id:"277367",title:"M.Sc.",name:"Daniel",middleName:"Martin",surname:"Márquez López",slug:"daniel-marquez-lopez",fullName:"Daniel Márquez López",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/277367/images/7909_n.jpg",biography:"Msc Daniel Martin Márquez López has a bachelor degree in Industrial Chemical Engineering, a Master of science degree in the same área and he is a PhD candidate for the Instituto Politécnico Nacional. His Works are realted to the Green chemistry field, biolubricants, biodiesel, transesterification reactions for biodiesel production and the manipulation of oils for therapeutic purposes.",institutionString:null,institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"196544",title:"Prof.",name:"Angel",middleName:null,surname:"Catala",slug:"angel-catala",fullName:"Angel Catala",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/196544/images/system/196544.jpg",biography:"Angel Catalá studied chemistry at Universidad Nacional de La Plata, Argentina, where he received a Ph.D. in Chemistry (Biological Branch) in 1965. From 1964 to 1974, he worked as an Assistant in Biochemistry at the School of Medicine at the same university. From 1974 to 1976, he was a fellow of the National Institutes of Health (NIH) at the University of Connecticut, Health Center, USA. From 1985 to 2004, he served as a Full Professor of Biochemistry at the Universidad Nacional de La Plata. He is a member of the National Research Council (CONICET), Argentina, and the Argentine Society for Biochemistry and Molecular Biology (SAIB). His laboratory has been interested for many years in the lipid peroxidation of biological membranes from various tissues and different species. Dr. Catalá has directed twelve doctoral theses, published more than 100 papers in peer-reviewed journals, several chapters in books, and edited twelve books. He received awards at the 40th International Conference Biochemistry of Lipids 1999 in Dijon, France. He is the winner of the Bimbo Pan-American Nutrition, Food Science and Technology Award 2006 and 2012, South America, Human Nutrition, Professional Category. In 2006, he won the Bernardo Houssay award in pharmacology, in recognition of his meritorious works of research. Dr. Catalá belongs to the editorial board of several journals including Journal of Lipids; International Review of Biophysical Chemistry; Frontiers in Membrane Physiology and Biophysics; World Journal of Experimental Medicine and Biochemistry Research International; World Journal of Biological Chemistry, Diabetes, and the Pancreas; International Journal of Chronic Diseases & Therapy; and International Journal of Nutrition. He is the co-editor of The Open Biology Journal and associate editor for Oxidative Medicine and Cellular Longevity.",institutionString:"Universidad Nacional de La Plata",institution:{name:"National University of La Plata",country:{name:"Argentina"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",slug:"francisco-javier-martin-romero",fullName:"Francisco Javier Martin-Romero",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",biography:"Francisco Javier Martín-Romero (Javier) is a Professor of Biochemistry and Molecular Biology at the University of Extremadura, Spain. He is also a group leader at the Biomarkers Institute of Molecular Pathology. Javier received his Ph.D. in 1998 in Biochemistry and Biophysics. At the National Cancer Institute (National Institute of Health, Bethesda, MD) he worked as a research associate on the molecular biology of selenium and its role in health and disease. After postdoctoral collaborations with Carlos Gutierrez-Merino (University of Extremadura, Spain) and Dario Alessi (University of Dundee, UK), he established his own laboratory in 2008. The interest of Javier's lab is the study of cell signaling with a special focus on Ca2+ signaling, and how Ca2+ transport modulates the cytoskeleton, migration, differentiation, cell death, etc. He is especially interested in the study of Ca2+ channels, and the role of STIM1 in the initiation of pathological events.",institutionString:null,institution:{name:"University of Extremadura",country:{name:"Spain"}}},{id:"217323",title:"Prof.",name:"Guang-Jer",middleName:null,surname:"Wu",slug:"guang-jer-wu",fullName:"Guang-Jer Wu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/217323/images/8027_n.jpg",biography:null,institutionString:null,institution:null},{id:"148546",title:"Dr.",name:"Norma Francenia",middleName:null,surname:"Santos-Sánchez",slug:"norma-francenia-santos-sanchez",fullName:"Norma Francenia Santos-Sánchez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/148546/images/4640_n.jpg",biography:null,institutionString:null,institution:null},{id:"272889",title:"Dr.",name:"Narendra",middleName:null,surname:"Maddu",slug:"narendra-maddu",fullName:"Narendra Maddu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/272889/images/10758_n.jpg",biography:null,institutionString:null,institution:null},{id:"242491",title:"Prof.",name:"Angelica",middleName:null,surname:"Rueda",slug:"angelica-rueda",fullName:"Angelica Rueda",position:"Investigador Cinvestav 3B",profilePictureURL:"https://mts.intechopen.com/storage/users/242491/images/6765_n.jpg",biography:null,institutionString:null,institution:null},{id:"88631",title:"Dr.",name:"Ivan",middleName:null,surname:"Petyaev",slug:"ivan-petyaev",fullName:"Ivan Petyaev",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Lycotec (United Kingdom)",country:{name:"United Kingdom"}}},{id:"423869",title:"Ms.",name:"Smita",middleName:null,surname:"Rai",slug:"smita-rai",fullName:"Smita Rai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Integral University",country:{name:"India"}}},{id:"424024",title:"Prof.",name:"Swati",middleName:null,surname:"Sharma",slug:"swati-sharma",fullName:"Swati Sharma",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Integral University",country:{name:"India"}}},{id:"439112",title:"MSc.",name:"Touseef",middleName:null,surname:"Fatima",slug:"touseef-fatima",fullName:"Touseef Fatima",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Integral University",country:{name:"India"}}},{id:"424836",title:"Dr.",name:"Orsolya",middleName:null,surname:"Borsai",slug:"orsolya-borsai",fullName:"Orsolya Borsai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca",country:{name:"Romania"}}},{id:"422262",title:"Ph.D.",name:"Paola Andrea",middleName:null,surname:"Palmeros-Suárez",slug:"paola-andrea-palmeros-suarez",fullName:"Paola Andrea Palmeros-Suárez",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Guadalajara",country:{name:"Mexico"}}}]}},subseries:{item:{id:"93",type:"subseries",title:"Inclusivity and Social Equity",keywords:"Social contract, SDG, Human rights, Inclusiveness, Equity, Democracy, Personal learning, Collaboration, Glocalization",scope:"
\r\n\tThis topic is dedicated to the efforts and promotion of UNESCO SDG4, the UNESCO initiative on the future of education, and the need for a new social contract for education. It aims to disseminate knowledge on policies, strategies, methods, and technologies that increase the resilience and sustainability of the development of the future of education and the new social contract for education. It will also consider the global challenges such as globalization, demographic change, digital transformation, climate change, environment and the social pillars of sustainable development.
\r\n
\r\n\tResponses to the pandemic and the widespread discontent that preceded it must be based on a new social contract and a New Global Deal for education that ensures equal opportunities for all and respects all people’s rights and freedoms (UNESCO; 2021). Such a new social contract, as proposed by UNESCO, must be based on the general principles underlying human rights - inclusion and equality, cooperation and solidarity, and collective responsibility and interconnectedness - and be guided by the following fundamental principle: Ensure that everyone has access to quality education throughout their lives.
\r\n
\r\n\tWe face the dual challenge of delivering on the unfulfilled promise of ensuring the right to quality education for every child, youth, and adult, as well as fully realizing the transformative potential of education as a pathway to a more sustainable collective future. To achieve this, we need a new social contract for education that eliminates inequities while transforming the future. This new social contract must be based on human rights and the principles of non-discrimination, social justice, respect for life, human dignity, and cultural diversity. It must include an ethic of care, reciprocity and solidarity. The new social contract builds on inclusiveness, equity, lifelong learning, SDG, collaboration and personal learning in a global context for democracy.
\r\n
\r\n\tAt an international level, the adoption of the Open Educational Resources recommendation and the Open Science recommendation represents an important step towards building more open and inclusive knowledge societies as well as the achievement of the UN 2030 Agenda. Indeed, implementing the recommendations will help to achieve at least five more Sustainable Development Goals (SDGs) that are intertwined with the topic of this book series, namely SDG 5 (Gender equality), SDG 9 (Industry, innovation and infrastructure), SDG 10 (Reduced inequalities within and across countries), SDG 16 (Peace, justice and strong institutions) and SDG 17 (Partnerships for the goals).
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Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. 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Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. 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