Quantitative Evaluation.
\\n\\n
More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:{caption:"IntechOpen Maintains",originalUrl:"/media/original/113"}},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{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"}]},book:{item:{type:"book",id:"7695",leadTitle:null,fullTitle:"Green Energy Advances",title:"Green Energy Advances",subtitle:null,reviewType:"peer-reviewed",abstract:'This book contributes to understanding the development and application of green energy solutions. The term "green energy" is widely used today to indicate sustainable energy sources with zero or minimal environmental and economic impact, obtained from various renewable energy sources. The contents presented in this book deal with different solutions, from small-scale applications (thermoelectric energy harvesting) to energy efficiency in buildings with local renewable energy production (also in critical seismic sites), local energy systems (smart energy management of storage and complex interactions), exploitation of biomasses from agricultural wastes, and voluntary certifications associated with energy trading in large energy systems. These aspects mark a more sustainable evolution of the society with wider green energy usage.',isbn:"978-1-78984-200-5",printIsbn:"978-1-78984-199-2",pdfIsbn:"978-1-83962-051-5",doi:"10.5772/intechopen.77501",price:119,priceEur:129,priceUsd:155,slug:"green-energy-advances",numberOfPages:156,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"ca498ae0f824bac0c43f5cfb011d8e9c",bookSignature:"Diana Enescu",publishedDate:"February 20th 2019",coverURL:"https://cdn.intechopen.com/books/images_new/7695.jpg",numberOfDownloads:12876,numberOfWosCitations:50,numberOfCrossrefCitations:45,numberOfCrossrefCitationsByBook:12,numberOfDimensionsCitations:77,numberOfDimensionsCitationsByBook:16,hasAltmetrics:1,numberOfTotalCitations:172,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 25th 2018",dateEndSecondStepPublish:"May 16th 2018",dateEndThirdStepPublish:"July 15th 2018",dateEndFourthStepPublish:"October 3rd 2018",dateEndFifthStepPublish:"December 2nd 2018",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"226207",title:"Ph.D.",name:"Diana",middleName:null,surname:"Enescu",slug:"diana-enescu",fullName:"Diana Enescu",profilePictureURL:"https://mts.intechopen.com/storage/users/226207/images/system/226207.jpeg",biography:"Diana Enescu graduated in Industrial Energy Engineering at the University Politehnica of Bucharest (UPB), Romania, and holds a Master Degree in energy efficiency and economy of energy from UPB. She obtained her PhD in mechanical engineering at the Technical University of Civil Engineering of Bucharest. In 2006 she was a visiting postdoctoral researcher at Yale University, USA. She has published more than 40 papers in national and international journals and conferences, four books and three book chapters. She is a member of ASME (American Society of Mechanical Engineers) and a reviewer of many international journals. She teaches thermal engineering courses at the Valahia University of Targoviste, Romania. Her research interests include heat transfer, thermodynamics, and thermoelectric system applications.",institutionString:"Valahia University of Targoviste",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Valahia University of Targoviste",institutionURL:null,country:{name:"Romania"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"771",title:"Sustainability Science",slug:"sustainability-science"}],chapters:[{id:"65239",title:"Thermoelectric Energy Harvesting: Basic Principles and Applications",doi:"10.5772/intechopen.83495",slug:"thermoelectric-energy-harvesting-basic-principles-and-applications",totalDownloads:5442,totalCrossrefCites:33,totalDimensionsCites:56,hasAltmetrics:1,abstract:"Green energy harvesting aims to supply electricity to electric or electronic systems from one or different energy sources present in the environment without grid connection or utilisation of batteries. These energy sources are solar (photovoltaic), movements (kinetic), radio-frequencies and thermal energy (thermoelectricity). The thermoelectric energy harvesting technology exploits the Seebeck effect. This effect describes the conversion of temperature gradient into electric power at the junctions of the thermoelectric elements of a thermoelectric generator (TEG) device. This device is a robust and highly reliable energy converter, which aims to generate electricity in applications in which the heat would be otherwise dissipated. The significant request for thermoelectric energy harvesting is justified by developing new thermoelectric materials and the design of new TEG devices. Moreover, the thermoelectric energy harvesting devices are used for waste heat harvesting in microscale applications. Potential TEG applications as energy harvesting modules are used in medical devices, sensors, buildings and consumer electronics. This chapter presents an overview of the fundamental principles of thermoelectric energy harvesting and their low-power applications.",signatures:"Diana Enescu",downloadPdfUrl:"/chapter/pdf-download/65239",previewPdfUrl:"/chapter/pdf-preview/65239",authors:[{id:"226207",title:"Ph.D.",name:"Diana",surname:"Enescu",slug:"diana-enescu",fullName:"Diana Enescu"}],corrections:null},{id:"63514",title:"Definition and Design of Zero Energy Buildings",doi:"10.5772/intechopen.80708",slug:"definition-and-design-of-zero-energy-buildings",totalDownloads:1568,totalCrossrefCites:4,totalDimensionsCites:6,hasAltmetrics:0,abstract:"The wide application of renewable energy system (RES) in buildings combined with numerous financial incentives on RES paves the way for future zero energy buildings (ZEB). Although the definition of ZEB still lacks a national building code and international standards, the number of ZEB projects is still increasing worldwide which seems to be the pioneer ZEB buildings. However, due to the intermittency of the renewable resources, various uncertain parameters, and dynamic electricity price from the grid, how to select the renewable energy system for buildings is one of the challenges and therefore becomes an extensive concern for both researchers and designers. In addition, questions like how to achieve the target of zero energy for different types of buildings, should the building be designed as an independent ZEB or a group of buildings to be a ZEB cluster, and how to make building owners actively involved in installing enough RES for the building are still on the air. This chapter will present a comprehensive view on several key issues related with ZEB, that is, definition, evaluation criteria, design method, and uncertainty analysis, and the penalty cost scheme is also proposed for consideration as one policy to assist the promotion of ZEB.",signatures:"Yuehong Lu, Xiao-Ping Zhang, Zhijia Huang, Jinli Lu and Changlong Wang",downloadPdfUrl:"/chapter/pdf-download/63514",previewPdfUrl:"/chapter/pdf-preview/63514",authors:[{id:"258333",title:"Associate Prof.",name:"Yuehong",surname:"Lu",slug:"yuehong-lu",fullName:"Yuehong Lu"},{id:"269313",title:"Prof.",name:"Zhijia",surname:"Huang",slug:"zhijia-huang",fullName:"Zhijia Huang"}],corrections:null},{id:"65163",title:"Energy and Seismic Rehabilitation of RC Buildings through an Integrated Approach: An Application Case Study",doi:"10.5772/intechopen.82581",slug:"energy-and-seismic-rehabilitation-of-rc-buildings-through-an-integrated-approach-an-application-case",totalDownloads:882,totalCrossrefCites:1,totalDimensionsCites:3,hasAltmetrics:0,abstract:"The high number of existing buildings in Italy without adequate seismic and thermal performances requires the definition of integrated retrofitting techniques in order to improve the seismic performance and to reduce energy losses at the same time. On one hand, an integrated approach appears mandatory considering that improving only the energy efficiency of nonseismic buildings leads to an increase of their exposure and, therefore, of their risk in the case of seismic events. On the other hand, seismic strengthening without an adequate thermal assessment and rehabilitation could compromise living comfort and energy maintenance costs. In this context, an application of integrated approach for the rehabilitation of reinforced concrete (RC) existing buildings has been proposed referring to a case study representative of the Italian building stock. Different configurations of infill panels have been considered in order to analyze both energy and seismic performance. Monthly quasi-steady state and hourly dynamic models have been used for the calculation of the energy need of buildings located in different Italian climate and seismic zones. Seismic performances have been evaluated by means of incremental nonlinear dynamic analysis (IDA). As-built and post-retrofit performances have been compared in order to evaluate the effectiveness of the proposed intervention solutions.",signatures:"Antonio D’Angola, Vincenzo Manfredi, Angelo Masi and Marianna Mecca",downloadPdfUrl:"/chapter/pdf-download/65163",previewPdfUrl:"/chapter/pdf-preview/65163",authors:[{id:"144482",title:"PhD.",name:"Antonio",surname:"Dangola",slug:"antonio-dangola",fullName:"Antonio Dangola"},{id:"281765",title:"Prof.",name:"Angelo",surname:"Masi",slug:"angelo-masi",fullName:"Angelo Masi"},{id:"281766",title:"Dr.",name:"Vincenzo",surname:"Manfredi",slug:"vincenzo-manfredi",fullName:"Vincenzo Manfredi"},{id:"281767",title:"Ph.D.",name:"Marianna",surname:"Mecca",slug:"marianna-mecca",fullName:"Marianna Mecca"}],corrections:null},{id:"63225",title:"A Smart Battery Management System for Photovoltaic Plants in Households Based on Raw Production Forecast",doi:"10.5772/intechopen.80562",slug:"a-smart-battery-management-system-for-photovoltaic-plants-in-households-based-on-raw-production-fore",totalDownloads:1553,totalCrossrefCites:2,totalDimensionsCites:3,hasAltmetrics:0,abstract:"A basic battery management system (BMS) permits the safe charge/discharge of the batteries and the supply of loads. Batteries are protected to avoid fast degradation: the minimum and maximum state-of-charge (SOC) limits are not exceeded and fast charge/discharge cycles are not permitted. A more sophisticated BMS connected to a photovoltaic (PV) generator could also work with the double purpose of protecting storage and reducing peak demand. Peak reduction by storage generally requires the forecast of consumption and PV generation profiles to perform a provisional energy balance. To do it, it is required to have accurate information about production profiles, that is, to have at disposal accurate weather forecasts, which are not easily available. In the present work, an efficient BMS in grid-connected PV plants for residential users is described. Starting from raw 1-day ahead weather forecast and prediction of consumption, the proposed BMS preserves battery charge when it is expected high load and low PV production and performs peak shaving with a negligible reduction in self-sufficiency.",signatures:"Filippo Spertino, Alessandro Ciocia, Paolo Di Leo, Gabriele Malgaroli\nand Angela Russo",downloadPdfUrl:"/chapter/pdf-download/63225",previewPdfUrl:"/chapter/pdf-preview/63225",authors:[{id:"52199",title:"Dr.",name:"Filippo",surname:"Spertino",slug:"filippo-spertino",fullName:"Filippo Spertino"},{id:"54831",title:"Dr.",name:"Paolo",surname:"Di Leo",slug:"paolo-di-leo",fullName:"Paolo Di Leo"},{id:"198475",title:"Prof.",name:"Angela",surname:"Russo",slug:"angela-russo",fullName:"Angela Russo"},{id:"258823",title:"Dr.",name:"Alessandro",surname:"Ciocia",slug:"alessandro-ciocia",fullName:"Alessandro Ciocia"},{id:"258824",title:"MSc.",name:"Gabriele",surname:"Malgaroli",slug:"gabriele-malgaroli",fullName:"Gabriele Malgaroli"}],corrections:null},{id:"65063",title:"Integration of Advanced Technologies for Efficient Operation of Smart Grids",doi:"10.5772/intechopen.83570",slug:"integration-of-advanced-technologies-for-efficient-operation-of-smart-grids",totalDownloads:1098,totalCrossrefCites:5,totalDimensionsCites:8,hasAltmetrics:0,abstract:"The current transition of electrical power systems toward smart grids is encompassing a fundamental change in their structure, as well as operation. This is setting the path to be followed by the hardware and software embedded in electrical power systems, as well as technology adaptation to the “open-source” customers’ needs and consumption patterns. This chapter is following the evolution of energy sector, accompanied by constant improvements of technology, which is providing increasingly complex hardware, which embeds power quality improvement devices, for an efficient operation of electrical power assets. This chapter presents a comprehensive survey of continuous advances of renewable energy sources and storage technology which have started the transformation of end users into energy-efficient and clean prosumers, underlining the subsequent energy markets support of peer-to-peer energy trading through novel technologies as blockchain.",signatures:"Radu Porumb and George Serițan",downloadPdfUrl:"/chapter/pdf-download/65063",previewPdfUrl:"/chapter/pdf-preview/65063",authors:[{id:"258532",title:"Associate Prof.",name:"Radu",surname:"Porumb",slug:"radu-porumb",fullName:"Radu Porumb"},{id:"258533",title:"Prof.",name:"George",surname:"Serițan",slug:"george-seritan",fullName:"George Serițan"}],corrections:null},{id:"64335",title:"Sustainable Energy Model for the Production of Biomass Briquettes Based on Rice Husks in Peruvian Low-Income Agricultural Areas",doi:"10.5772/intechopen.81817",slug:"sustainable-energy-model-for-the-production-of-biomass-briquettes-based-on-rice-husks-in-peruvian-lo",totalDownloads:1358,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"An energy model focuses on the sustainability of environmental proposals that use clean biomass technology. In this case, briquette production seeks to generate socio-environmental development in agricultural areas contaminated by the burning of rice husks. However, this agricultural waste product has a large heating capacity and can be used as a raw material for briquette production, replacing conventional contaminant fuels such as firewood and reducing Peru’s annual energy consumption by approximately 833,000 kg of CO2 per year, considering the minimization of emissions from the felling of trees and the burning of rice husks. These rice husks are burned and generate pollutant gases, causing respiratory and pulmonary problems. Despite these negative effects, it is an agricultural waste product with great untapped energy potential and constitutes an opportunity to promote socio-environmental development based on economic valorization. The level of deforestation would decrease by approximately 2070 trees per year, 23% of a market population which consumes 10 kg of firewood per day. Unlike similar projects, briquette production sustainability may be achieved when economic, environmental and social aspects are included in energy model development, based on the application of clean technology and efficient management of energy supplies, such as husk supplies and corresponding briquettes.",signatures:"Juan Arévalo, Grimaldo Quispe and Carlos Raymundo",downloadPdfUrl:"/chapter/pdf-download/64335",previewPdfUrl:"/chapter/pdf-preview/64335",authors:[{id:"256337",title:"Ph.D.",name:"Carlos",surname:"Raymundo",slug:"carlos-raymundo",fullName:"Carlos Raymundo"},{id:"272063",title:"Mr.",name:"Juan",surname:"Arevalo",slug:"juan-arevalo",fullName:"Juan Arevalo"},{id:"272064",title:"Dr.",name:"Grimaldo",surname:"Quispe",slug:"grimaldo-quispe",fullName:"Grimaldo Quispe"}],corrections:null},{id:"63953",title:"Voluntary Certification of Carbon Emission in Brazil - The Experience of an Electricity Trader",doi:"10.5772/intechopen.81185",slug:"voluntary-certification-of-carbon-emission-in-brazil-the-experience-of-an-electricity-trader",totalDownloads:976,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Few countries in the world have such availability of natural resources as Brazil. Even so, the country records increasing greenhouse gas (GHG) emissions related to electricity, and this is due to political and economic factors. This chapter shows the experience of the largest Brazilian power trader in its pioneering effort to develop voluntary certifications (2011) in power buy and sell transactions, along with other energy efficiency actions. The initiative has accumulated 9 years’ experience with more than 1600 units in different industries, using a methodology aligned with the Paris Agreement. The chapter presents the calculation methodology and the safeguards that ensure information integrity and verification of the certified indicators. Only renewable sources are used in this methodology, such sources being qualified as incentivized by their sustainability characteristics being small-size power plants (less than 30 MW of capacity installed).",signatures:"Fernando Amaral de Almeida Prado and Edvaldo Avila",downloadPdfUrl:"/chapter/pdf-download/63953",previewPdfUrl:"/chapter/pdf-preview/63953",authors:[{id:"257274",title:"Ph.D.",name:"Fernando",surname:"Almeida Prado Jr.",slug:"fernando-almeida-prado-jr.",fullName:"Fernando Almeida Prado Jr."},{id:"259329",title:"BSc.",name:"Edvaldo",surname:"Avila",slug:"edvaldo-avila",fullName:"Edvaldo Avila"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:[{id:"23",label:"women in science book program"}]},relatedBooks:[{type:"book",id:"205",title:"Fundamental and Advanced Topics in Wind Power",subtitle:null,isOpenForSubmission:!1,hash:"b8b5955addb75d98a6bba1c94e3e7a74",slug:"fundamental-and-advanced-topics-in-wind-power",bookSignature:"Rupp Carriveau",coverURL:"https://cdn.intechopen.com/books/images_new/205.jpg",editedByType:"Edited by",editors:[{id:"22234",title:"Dr.",name:"Rupp",surname:"Carriveau",slug:"rupp-carriveau",fullName:"Rupp Carriveau"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"2706",title:"Small-Scale Energy Harvesting",subtitle:null,isOpenForSubmission:!1,hash:"63bc4c27bdf9ec1e00aa20ff6f1d804f",slug:"small-scale-energy-harvesting",bookSignature:"Mickael Lallart",coverURL:"https://cdn.intechopen.com/books/images_new/2706.jpg",editedByType:"Edited by",editors:[{id:"10041",title:"Dr.",name:"Mickaël",surname:"Lallart",slug:"mickael-lallart",fullName:"Mickaël Lallart"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"115",title:"Wind Turbines",subtitle:null,isOpenForSubmission:!1,hash:null,slug:"wind-turbines",bookSignature:"Ibrahim Al-Bahadly",coverURL:"https://cdn.intechopen.com/books/images_new/115.jpg",editedByType:"Edited by",editors:[{id:"19588",title:"Dr.",name:"Ibrahim H.",surname:"Al-Bahadly",slug:"ibrahim-h.-al-bahadly",fullName:"Ibrahim H. 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\r\n\tSupercapacitors are an important topic of research and development because they are interesting both in terms of energy and environmental aspects. Standard power storage systems are supercapacitors and rechargeable batteries. Recently, more and more attention is paid to supercapacitors as a qualitatively new type of capacitor and fuel cells as sources of electricity. A large number of teams and laboratories around the world are working on the development of supercapacitors, while their ever-improving performance allows for wider use. The goal of this book is to bring readers closer to new supercapacitor technologies that are changing the present and future of electricity storage. The big challenges are to improve the parameters of supercapacitors, primarily energy density and operating voltage, but we are also working on miniaturization, optimization, energy efficiency, and environmental friendliness. The expansion of electric cars brings a new trend in the development of supercapacitors - hybridization with batteries or a complex power supply that contains a battery, supercapacitor, and power electronics for energy management. The economic aspect must also be taken into account.
\r\n\r\n\tThe book hopes to cover the following topics: new achievements in the field of electrode and inter-electrode materials, new models and test methods, new constructions and applications, and the environmental aspect.
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He published over 350 papers (over 50 refereed full papers in Scientific Journals), 5 books, and 5 chapters. He was the project coordinator and member of working groups on many scientific and technical projects. He is also a professional in thermography (level II acc. ISO 9712).",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"30692",title:"Dr.",name:"Zoran",middleName:"M.",surname:"Stevic",slug:"zoran-stevic",fullName:"Zoran Stevic",profilePictureURL:"https://mts.intechopen.com/storage/users/30692/images/system/30692.jpg",biography:"Zoran M. Stevic (1958), zstevic@etf.rs , zstevic@tfbor.bg.ac.rs , zstevic@live.com is a full professor at the University of Belgrade, Technical Faculty in Bor and School of Electrical Engineering in Belgrade, Serbia. He received his Ph.D. degree from the School of Electrical Engineering in Belgrade, University of Belgrade. His research areas include power electronics, IR thermography, computer measurement, and process control, supercapacitors, energy efficiency, renewable energy sources, system modeling, sensors, optoelectronics, and electrochemistry. He is a member of IEEE, IBPSA, SMEITS, and SCS. He published over 350 papers (over 50 refereed full papers in Scientific Journals), 5 books, and 5 chapters. Also, he was the project coordinator and member of working groups on many scientific and technical projects. He is a professional in thermography (level II acc. 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In fact, it would appear that many of these skills will center on the challenge of interacting with humans, rather than with machine parts or other robots. To this end, modern-day roboticists are actively studying the problem of human-robot interaction – how best to create robots that can interact with humans, usually in a social setting. Among the many problems of human robot interaction, one of the most interesting is the problem of
As grandiose as this claim may sound, we believe that this understanding of intent recognition is quite reasonable; it is this interpretation that we seek to justify in the following pages.
\n\t\t\tEvery day, humans observe one another and on the basis of their observations “read people’s minds,” correctly inferring the intentions of others. Moreover, this ability is regarded not as remarkable, but as entirely ordinary and effortless. If we hope to build robots that are similarly capable of successfully interacting with people in a social setting, we must endow our robots with an ability to understand humans\' intentions.
\n\t\t\tIn this paper, we review the intent recognition problem, and provide as an example a system we have been developing to recognize human intentions. Our approach is ultimately based on psychological and neuroscientific evidence for a theory of mind (Premack & Woodruff, 1978), which suggests that the ease with which humans recognize the intentions of others is the result of an innate mechanism for representing, interpreting, and predicting other\'s actions. The mechanism relies on taking the perspective of others (Gopnick & Moore, 1994), which allows humans to correctly infer intentions.
\n\t\t\tAlthough this process is innate to humans, it does not take place in a vacuum. Intuitively, it would seem that our understanding of others\' intentions depend heavily on the contexts in which we find ourselves and those we observe. This intuition is supported by neuroscientific results (Iacobini et al., 2005), which suggest that the context of an activity plays an important and sometimes decisive role in correctly inferring underlying intentions.
\n\t\t\tBefore considering this process in detail, we first look at some of the related work on the problem of intent recognition. After that, we reconsider the problem of intent recognition, looking at it from a new perspective that will shed light on how the process is accomplished. After looking at this re-framing of the problem, we consider some more general questions related to intent recognition, before moving on to describe a specific example system. We describe the architecture of our system, as well as experimental results we have obtained during validation of our system. We move on to describe some of the challenges facing future intent recognition systems, including planning based on recognized intentions, complexity of recognition, and the incorporation of novel sources of information for intent recognition systems. We then conclude with a summary of the central issues in the field of intent recognition.
\n\t\tWhenever one wants to perform statistical classification in a system that is evolving over time, hidden Markov models may be appropriate (Duda et al., 2000). Such models have been very successfully used in problems involving speech recognition (Rabiner, 1989). Recently, there has been some indication that hidden Markov models may be just as useful in modelling activities and intentions. For example, HMMs have been used by robots to perform a number of manipulation tasks (Pook and Ballard, 93), (Hovland et al., 96), (Ogawara et al., 2002). These approaches all have the crucial problem that they only allow the robot to detect that a goal has been achieved
The use of HMMs in intent recognition (emphasizing the prediction element of the intent recognition problem) was first suggested in (Tavakkoli et al., 2007). That paper also elaborates on the connection between the HMM approach and theory of mind. However, the system proposed there has shortcomings that the present work seeks to overcome.
\n\t\t\tThe problem of intent recognition is also of great interest to researchers in neuroscience. Recent research in that field informs us that the mirror neuron system may play a role in intent recognition, and that contextual information is employed by the brain when ascribing intentions to others (Iacobini et al., 2005).
\n\t\tAlthough some researchers consider the problems of activity recognition and intent recognition to be essentially the same, a much more common claim is that intent recognition differs from activity recognition in that intent recognition has a predictive component: by determining an agent\'s intentions, we are in effect making a judgment about what we believe are the likely actions of the agent in the immediate or near future. Emphasizing the predictive component of intent recognition is important, but may not reveal all of the significant facets of the problem.
\n\t\t\tIn contrast with the more traditional view of intent recognition, we contend that
For an example of intent recognition as disambiguation, consider an agent playing chess. When the agent reaches for a chess piece, we can observe that activity and ascribe to the agent any number of possible intentions. Before the game, an agent reaching for a chess piece may putting the piece into its initial position; during the game, the agent may be making a move using that piece; and after the game, the agent may be cleaning up and putting the piece away. In each of these cases, it is entirely possible (if not likely) that the activity of reaching for the piece will appear identical to the other cases. It is only the intentional component of each action that distinguishes it from the others. Moreover, this component is determined by the context of agent\'s activity: before, during, or after the game. Notice that we need to infer the agent\'s intention in this example even when we are not interested in making any predictions. Disambiguation in such circumstances is essential to even a basic understanding of the agent\'s actions.
\n\t\tWe provide a set of vision-based perceptual capabilities for our robotic system that facilitate the modelling and recognition of actions carried out by other agents. As the appearance of these agents is generally not known a priori, the only visual cue that can be used for detecting and tracking them is image motion. Although it is possible to perform segmentation from an image sequence that contains global motion, such approaches -- typically based on optical flow estimation (Efros et al., 2003) -- are not very robust and are time consuming. Therefore, our approach uses more efficient and reliable techniques from real-time surveillance, based on background modelling and segmentation:
\n\t\t\tDuring the
During the
\n\t\t\t\tFig. 1 shows the block diagram of the proposed object tracking frameworks.
\n\t\t\tWe propose an efficient Spatio-Spectral Tracking module (SST) to detect objects of interest and track them in the video sequence. The major assumption is that the observer robot is static. However, we do not make any further restrictions on the background composition, thus allowing for local changes in the background such as fluctuating lights, water fountains, waving tree branches, etc.
\n\t\t\t\tThe two object tracking frameworks for (a)
The proposed system models the background pixel changes using an Incremental Support Vector Data Description module. The background model is then used to detect foreground regions in new frames. The foreground regions are processed further by employing a connected component processing in conjunction with a blob detection module to find objects of interest. These objects are tracked by their corresponding statistical models that are built from the objects\' spectral (color) information. A laser-based range finder is used to extract the objects\' trajectories and relative angles from their 2-D tracking trajectories and their depth in the scene. However, the spatio-spectral coherency of tracked objects may be violated in cases when two or more objects occlude each other.
\n\t\t\t\tA collision resolution mechanism is devised to address the issue of occlusion of objects of interest. This mechanism uses the spatial object properties such as their size, the relative location of their center of mass, and their relative orientations to predict the occlusion (collision).
\n\t\t\tBackground modelling is one of the most effective and widely used techniques to detect moving objects in videos with a quasi-stationary background. In these scenarios, despite the presence of a static camera, the background is not completely stationary due to inherent changes, such as water fountains, waving flags, etc. Statistical modelling approaches estimate the probability density function of the background pixel values. If the data is not drawn from a mixture of normal distributions the parametric density estimation techniques may not be useful. As an alternative, non-parametric density estimation approaches can be used to estimate the probability of a given sample belonging to the same distribution function as the data set (Tavakkoli et al., 2006). However, the memory requirements of the non-parametric approach and its computational costs are high since they require the evaluation of a kernel function for all data samples.
\n\t\t\t\tSupport Vector Data Description (SVDD) is a technique that uses support vectors in order to model a data set (Tax & Duin, 2004). The SVDD represents one class of known data samples in such a way that for a given test sample it can be recognized as known, or rejected as novel. Training of SVDDs is a quadratic programming optimization problem. This optimization converges by optimizing only on two data points with a specific condition (Platt, 1998) which requires at least one of the data points to violate the KKT conditions – the conditions by which the classification requirements are satisfied (Osuna et al., 1997). Our experimental results show that our SVDD training achieves higher speed and require less memory than the online and the canonical training (Tax & Duin, 2004).
\n\t\t\tIn the blob detection module, the system uses a spatial connected component processing to label foreground regions from the previous stage. However, to label objects of interest a blob refinement framework is used to compensate for inaccuracies in physical appearance of the detected blobs due to unintended region split and merge, inaccurate foreground detection, and small foreground regions. A list of objects of interest corresponding to each detected blob is created and maintained to further process and track each object individually. This raw list of blobs corresponding to objects of interest is called the spatial connected component list.
\n\t\t\t\tSpatial properties about each blob such as its center and size are kept in the spatial connected component list. The list does not incorporate individual objects\' appearances and thus is not solely useful for tracking purposes. The process of tracking individual objects based on their appearance in conjunction with their corresponding spatial features is carried out in the spatio-spectral tracking mechanism.
\n\t\t\tA system that can track moving objects (i.e. humans) requires a model for individual objects. These appearance models are employed to search for correspondences among the pool of objects detected in new frames. Once the target for each individual has been found in the new frame they are assigned a unique ID. In the update stage the new location, geometric and photometric information for each visible individual are updated. This helps recognize the objects and recover their new location in future frames.
\n\t\t\t\tOur proposed appearance modelling module represents an object with two sets of histograms, for the lower and upper half of the body. In the spatio-spectral tracking module a list of known objects of interest is maintained. This list represents each individual object and its corresponding spatial and color information along with its unique ID. During the tracking process the system uses the raw spatial connected component list as the list of observed objects and uses a statistical correspondence matching to maintain the ordered objects list and track each object individually. The tracking module is composed of three components:
\n\t\t\t\t\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
In order for the system to be robust to collisions -- when individuals get too close so that one occludes the other-- the models for the occluded individual may not reliable for tracking purposes. Our method uses the distance of detected objects and uses that as a means of detecting a collision. After a collision is detected we match each of the individual models with their corresponding representatives. The one with the smallest matching score is considered to be occluded. The occluded object\'s model will not be updated but its new position is predicted by a Kalman filter. The position of the occluding agent is updated and tracked by a well-known mean-shift algorithm. After the collision is over the spatio-spectral tracker resumes its normal process for these objects.
\n\t\t\tAs mentioned above, our system uses HMMs to model activities that consist of a number of parts that have intentional significance. Recall that a hidden Markov model consists of a set of
As an example, consider the activity of
We train our HMMs by having our robot perform the activity that it later will recognize. As it performs the activity, it records the changes in the parameters of interest for the activity, and uses those to generate sequences of observable states representing the activity. These are then used with the Baum-Welch algorithm (Rabiner, 1989) to train the models, whose topologies have been determined by a human operator in advance.
\n\t\t\t\tDuring recognition, the stationary robot observes a number of individuals interacting with one another and with stationary objects. It tracks those individuals using the visual capabilities described above, and takes the perspective of the agents it is observing. Based on its perspective-taking and its prior understanding of the activities it has been trained to understand, the robot infers the intention of each agent in the scene. It does this using maximum likelihood estimation, calculating the most probable intention given the observation sequence that it has recorded up to the current time for each pair of interacting agents.
\n\t\t\tTo use contextual information to perform intent recognition, we must decide how we want to model the relationship between intentions and contexts. This requires that we describe what intentions and contexts
An intention model consists of two parts: first, an activity model, which is given by a particular HMM, and secondly a name. This is the minimal amount of information necessary to allow a robot to perform disambiguation. If necessary or desirable, intentions could be augmented with additional information that a robot could use to support interaction. As an example we might augment an intention model to specify an action to take in response to detecting a particular sequence of hidden states from the activity model.
\n\t\t\t\tA context model, at a minimum, must consist of a name or other identifier to distinguish it from other possible contexts in the system, as well as some method for discriminating between intentions. This method might take the form of a set of deterministic rules, or it might be a discrete probability distribution defined over the intentions about which the context is aware. In general, a context model can contain as many or as few features as are necessary to distinguish the intentions of interest. Moreover, the context can be either
A static context consists of a name for the context and a probability distribution over all possible intentions. This is the simplest approach to context-based intent recognition in our framework, and is useful for modelling context that depends on unchanging location of an observer robot (as we would see in the case of a guard or service robot that only works in a single room or building), or on time or the date.
\n\t\t\t\tA dynamic context consists of features that are inferred by the observer. This could include objects that are being manipulated by the observed agents, visually detected features of the agents, or aspects of the environment that vary in hard-to-predict ways. In general, a dynamic context consists of a name and a probability distribution over
Suppose that we have an activity model (
We can further simplify matters by noting that the denominator is independent of our choice of
This approximation suggests an algorithm for determining the most likely intention given a series of observations and a context: for each possible intention
In robotics applications, simply determining an observed agent\'s intentions may not be enough. Once a robot knows what another\'s intentions are, the robot should be able to act on its knowledge to achieve a goal. With this in mind, we developed a simple method to allow a robot to dispatch a behavior based on its intent recognition capabilities. The robot first infers the global intentions of all the agents it is tracking, and for the activity corresponding to the inferred global intention determines the most likely local intention. If the robot determines over multiple time steps that a certain local intention has the largest probability, it can dispatch a behavior in response to the situation it believes is taking place.
\n\t\t\t\tFor example, consider the activity of stealing an object. The local intentions for this activity might include “approaching the object,” “picking up the object,” and “walking off with the object.” If the robot knows that in its current context the local intention “picking up the object” is not acceptable and it infers that an agent is in fact picking up the object, it can execute a behavior, for example stopping the thief or warning another person or robot of the theft.
\n\t\t\tTo validate our approach, we performed a set of experiments using a Pioneer 3DX mobile robot, with an on-board computer, a laser rangefinder, and a Sony PTZ camera. We trained our robot to understand three basic activities:
We placed our trained robot in an indoor environment and had it observe the interactions of multiple human agents with each other, and with multiple static objects. In our experiments, we considered both the case where the robot acts as a passive observer and the case where the robot executes an action on the basis of the intentions it infers in the agents under its watch.
\n\t\t\t\tWe were particularly interested in the performance of the system in two cases. In the first case, we wanted to determine the performance of the system when a single activity could have different underlying intentions based on the current context (so that, returning to our example in Sec. 3, the activity of “moving one\'s hand toward a chess piece” could be interpreted as “making a move” during a game but as “cleaning up” after the game is over). This case deals directly with the problem that in some situations, two apparently identical activities may in fact be very different, although the difference may lie entirely in contextually determined intentional component of the activity.
\n\t\t\t\tIn our second case of interest, we sought to determine the performance of the system in disambiguating two activities that were in fact different, but due to environmental conditions appeared superficially very similar. This situation represents one of the larger stumbling blocks of systems that do not incorporate contextual awareness.
\n\t\t\t\tIn the first set of experiments, the same visual data was given to the system several times, each with different a context, to determine whether the system could use the context alone to disambiguate agents\' intentions. We considered three pairs of scenarios, which provided the context we gave to our system: leaving the building on a normal day/evacuating the building, getting a drink from a vending machine/repairing a vending machine, and going to a movie during the day/going to clean the theater at night. We would expect our intent recognition system to correctly disambiguate between each of these pairs using its knowledge of its current context.
\n\t\t\t\tThe second set of experiments was performed in a lobby, and had agents meeting each other and passing each other both with and without contextual information about which of these two activities is more likely in the context of the lobby. To the extent that meeting and passing appear to be similar, we would expect that the use of context would help to disambiguate the activities.
\n\t\t\t\tLastly, to test our intention-based control, we set up two scenarios. In the first scenario (the “theft” scenario), a human enters his office carrying a bag. As he enters, he sets his bag down by the entrance. Another human enters the room, takes the bag and leaves. Our robot was set up to observe these actions and send a signal to a “patrol robot” in the hall that a theft had occurred. The patrol robot is then supposed to follow the thief as long as possible.
\n\t\t\t\tIn the second scenario, our robot is waiting in the hall, and observes a human leaving the bag in the hallway. The robot is supposed to recognize this as a suspicious activity and follow the human who dropped the bag for as long as possible.
\n\t\t\tIn all of the scenarios considered, our robot was able to effectively observe the agents within its field of view and correctly infer the intentions of the agents that it observed.
\n\t\t\t\tTo provide a quantitative evaluation of intent recognition performance, we use two measures:
\n\t\t\t\t\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
The accuracy rate of our system is 100%: the system ultimately chose the correct intention in all of the scenarios in which it was tested. We consider the correct duration measure in more detail for each of the cases in which we were interested.
\n\t\t\t\n\t\t\t\t\tTable 1 indicates the system\'s disambiguation performance. For example, we see that in the case of the scenario
Scenario (With Context) | \n\t\t\t\t\t\t\tCorrect Duration [%] | \n\t\t\t\t\t\t
Leave Building (Normal ) | \n\t\t\t\t\t\t\t96.2 | \n\t\t\t\t\t\t
(Evacuation) | \n\t\t\t\t\t\t\t96.4 | \n\t\t\t\t\t\t
Theater (Cleanup) | \n\t\t\t\t\t\t\t87.9 | \n\t\t\t\t\t\t
Theater (Movie) | \n\t\t\t\t\t\t\t90.9 | \n\t\t\t\t\t\t
Vending (Getting a Drink) | \n\t\t\t\t\t\t\t91.1 | \n\t\t\t\t\t\t
Vending (Repair) | \n\t\t\t\t\t\t\t91.4 | \n\t\t\t\t\t\t
Quantitative Evaluation.
As we can see from Table 2, the system performs substantially better when using context than it does without contextual information. Because
Meet (No Context) - Agent 1 | \n\t\t\t\t\t\t\t65.8 | \n\t\t\t\t\t\t
Meet (No Context) - Agent 2 | \n\t\t\t\t\t\t\t74.2 | \n\t\t\t\t\t\t
Meet (Context) - Agent 1 | \n\t\t\t\t\t\t\t97.8 | \n\t\t\t\t\t\t
Meet (Context) - Agent 2 | \n\t\t\t\t\t\t\t100.0 | \n\t\t\t\t\t\t
Quantitative Evaluation.
In both the scenarios we developed to test our intention-based control, our robot correctly inferred the ground-truth intention, and correctly responded the inferred intention. In the theft scenario, the robot correctly recognized the theft and reported it to the patrol robot in the hallway, which was able to track the thief (Figure 2). In the bag drop scenario, the robot correctly recognized that dropping a bag off in a hallway is a suspicious activity, and was able to follow the suspicious agent through the hall. Both examples indicate that intention-based control using context and hidden Markov models is a feasible approach.
\n\t\t\t\tAn observer robot catches a human stealing a bag (left). The top left view shows the robot equipped with our system. The bottom right is the view of a patrol robot. The next frame (right) shows the patrol robot using vision and a map to track the thief.
In real-world applications, the number of possible intentions that a robot has to be prepared to deal with may be very large. Without effective heuristics, efficiently performing maximum likelihood estimation in such large spaces is likely to be difficult if not impossible. In each of the above scenarios, the number of possible intentions the system had to consider was reduced through the use of contextual information. In general, such information may be used as an effective heuristic for reducing the size of the space the robot has to search to classify agents\' intentions. As systems are deployed in increasingly complex situations, it is likely that heuristics of this sort will become important for the proper functioning of social robots.
\n\t\t\tIn addition to the improved performance of a context-aware system over a context-agnostic one that we see in the experimental results above, the proposed approach has a few other advantages worth mentioning. First, our approach recognizes the importance of context in recognizing intentions and activities, and can successfully operate in situations that previous intent recognition systems have had trouble with.
\n\t\t\t\tMost importantly, though, from a design perspective it makes sense to separately perform inference for activities and for contexts. By “factoring” our solution in this way, we increase modularity and create the potential for improving the system by improving its individual parts. For example, it may turn out that another classifier works better than HMMs to model activities. We could then use that superior classifier in place of HMMs, along with an unmodified context module, to obtain a better-performing system.
\n\t\t\tOur particular implementation has some shortcomings that are worth noting. First, the use of static context is inflexible. In some applications, such as surveillance using a set of stationary cameras, the use of static context may make sense. However, in the case of robots, the use of static context means that it is unlikely that the system will be able to take much advantage of one of the chief benefits of robots, namely their mobility.
\n\t\t\t\tAlong similar lines, the current design of the intention-based control mechanism is probably not flexible enough to work “in the field.” Inherent stochasticity, sensor limitations, and approximation error make it likely that a system that dispatches behaviors based only on a running count of certain HMM states is likely to run into problems with false positives and false negatives. In many situations (such as the theft scenario describe above), even a relatively small number of such errors may not be acceptable.
\n\t\t\t\tIn short, then, the system we propose faces a few substantial challenges, all centering on a lack of flexibility or robustness in the face of highly uncertain or unpredictable environments.
\n\t\t\tTo deal with the problems of flexibility and scalability, we extend the system just described in two directions. First, we introduce a new source for contextual information, the lexical digraph. These data structures provide the system with contextual knowledge from linguistic sources, and have proved thus far to be highly general and flexible.
\n\t\t\tTo deal with the problem of scalability, we introduce the
As mentioned above, our system relies on contextual information to perform intent recognition. While there are many sources of contextual information that may be useful to infer intentions, we chose to focus primarily on the information provided by object affordances, which indicate the actions that one can perform with an object. The problem, once this choice is made, is one of training and representation: given that we wish the system to infer intentions from contextual information provided by knowledge of object affordances, how do we learn and represent those affordances? We would like, for each object our system may encounter, to build a representation that contains the likelihood of all actions that can be performed on that object.
\n\t\t\tAlthough there are many possible approaches to constructing such a representation, we chose to use a representation that is based heavily on a graph-theoretic approach to natural language -- in particular, English. Specifically, we construct a graph in which the vertices are words and a labeled, weighted edge exists between two vertices if and only if the words corresponding to the vertices exist in some kind of grammatical relationship. The label indicates the nature of the relationship, and the edge weight is proportional to the frequency with which the pair of words exists in that particular relationship. For example, we may have vertices
There are a number of justifications for and consequences of the decision to take such an approach.
\n\t\t\tThe use of a linguistic approach is well motivated by human experience. Natural language is a highly effective vehicle for expressing facts about the world, including object affordances. Moreover, it is often the case that such affordances can be easily inferred directly from grammatical relationships, as in the example above.
\n\t\t\t\tFrom a computational perspective, we would prefer models that are time and space efficient, both to build and to use. If the graph we construct to represent our affordances is sufficiently sparse, then it should be space efficient. As we discuss below, the graph we use has a number of edges that is linear in the number of vertices, which is in turn linear in the number of sentences that the system “reads.” We thus attain space efficiency. Moreover, we can efficiently access the neighbors of any vertex using standard graph algorithms.
\n\t\t\t\tIn practical terms, the wide availability of texts that discuss or describe human activities and object affordances means that an approach to modelling affordances based on language can scale well beyond a system that uses another means for acquiring affordance models. The act of “reading” about the world can, with the right model, replace direct experience for the robot in many situations.
\n\t\t\t\tNote that the above discussion makes an important assumption that, although convenient, may not be accurate in all situations. Namely, we assume that for any given action-object pair, the likelihood of the edge representing that pair in the graph is at least approximately equal to the likelihood that the action takes place in the world. Or in other words, we assume that linguistic frequency well approximates action frequency. Such an assumption is intuitively reasonable. We are more likely to read a book than we are to throw a book; as it happens, this fact is represented in our graph. We are currently exploring the extent to which this assumption is valid and may be safely relied upon; at this point, though, it appears that the assumption is valid for a wide enough range of situations to allow for practical use in the field.
\n\t\t\tTo obtain our pairwise relations between words, we use the Stanford labeled dependency parser (Marneffe et al., 2006). The parser takes as input a sentence and produces the set of all pairs of words that are grammatically related in the sentence, along with a label for each pair, as in the “water” example above.
\n\t\t\t\tUsing the parser, we construct a graph
One of the greatest strengths of the dependency-grammar approach is its space efficiency: the output of the parser is either a
The number of edges in the Wikipedia graph as a function of the number of vertices during the process of graph growth.
The final Wikipedia graph we used in our experiments consists of 244,267 vertices and 2,074,578 edges. The childrens\' story graph is much smaller, being built from just a few hundred sentences: it consists of 1754 vertices and 3873 edges. This graph was built to fill in gaps in the information contained in the Wikipedia graph. The graphs were merged to create the final graph we used by taking the union of the vertex and edge sets of the graphs, adding the edge weights of any edges that appeared in both graphs.
\n\t\t\tTo test the lexical-digraph-based system, we had the robot observe an individual as he performed a number of activities involving various objects. These included books, glasses of soda, computers, bags of candy, and a fire extinguisher.
\n\t\t\t\tTo test the lexically informed system, we considered three different scenarios. In the first, the robot observed a human during a meal, eating and drinking. In the second, the human was doing homework, reading a book and taking notes on a computer. In the last scenario, the robot observed a person sitting on a couch, eating candy. A trashcan in the scene then catches on fire, and the robot observes the human using a fire extinguisher to put the fire out.
\n\t\t\t\tThe robot observer watches as a human uses a fire extinguisher to put out a trashcan fire.
Defining a ground truth for these scenarios is slightly more difficult than in the previous scenarios, since in these scenarios the observed agent performs multiple activities and the boundaries between activities in sequence are not clearly defined. However, we can still make the interesting observation that, except on the boundary between two activities, the correct duration of the system is 100%. Performance on the boundary is more variable, but it isn\'t clear that this is an avoidable phenomenon. We are currently working on carefully ground-truthed videos to allow us to better compute the accuracy rate and the correct duration for these sorts of scenarios. However, the results we have thus far obtained are encouraging.
\n\t\t\tThe first step in the recognition process is deciding what to recognize. In general, a scene may consist of many agents, interacting with each other and with objects in the environment. If the scene is sufficiently complex, approaches that don\'t first narrow down the likely interactions before using time-intensive classifiers are likely to suffer, both in terms of performance and accuracy. To avoid this problem, we introduce the
For our current system, we considered four factors that we identified as particularly relevant to identifying interaction: distance in physical space, the angle of an entity from the center of an agent\'s field of view, velocity, and acceleration. Other factors that may be important that we chose not to model include sensed communication between two agents (this would be strongly indicative of interaction between two agents), time spent in and out of an agent\'s field of view, and others. We classify agents as interacting whenever a weighted sum of these distances is less than a human-set threshold.
\n\t\t\tTo test the interaction space model, we wished to use a large number of interacting agents behaving in a predictable fashion, and compare the results of an intent recognition system that used interaction spaces against the results of a system that did not. Given these requirements, we decided that the best approach was to simulate a large number of agents interacting in pre-programmed ways. This satisfied our requirements and gave us a well-defined ground truth to compare against.
\n\t\t\t\tThe scenario we used for these experiments was very simple. The scenario consisted of
The results of the simulation experiments show that as the number of entities to be classified increases, the system that uses interaction spaces outperforms a system that does not. As we can see in Table 3, for a relatively small number of agents, the two systems have somewhat comparable performance in terms of correct duration. However, when we increase the number of agents to be classified, we see that the interaction-space approach
\n\t\t\t\t\t\t\t | 8 Agents | \n\t\t\t\t\t\t\t32 Agents | \n\t\t\t\t\t\t
System with Interaction Spaces | \n\t\t\t\t\t\t\t96% | \n\t\t\t\t\t\t\t94% | \n\t\t\t\t\t\t
Baseline System | \n\t\t\t\t\t\t\t79% | \n\t\t\t\t\t\t\t6% | \n\t\t\t\t\t\t
Simulation results – correct duration.
There is substantial room for future work in intent recognition. Generally speaking, the task moving forward will be to increase the flexibility and generality of intent recognition systems. There are a number of ways in which this can be done. First, further work should address the problem of a non-stationary robot. One might have noticed that our work assumes a robot that is not moving. While this is largely for reasons of simplicity, further work is necessary to ensure that an intent recognition system works fluidly in a highly dynamic environment.
\n\t\t\tMore importantly, further work should be done on context awareness for robots to understand people. We contend that a linguistically based system, perhaps evolved from the one described here, could provide the basis for a system that can understand behavior and intentions in a wide variety of situations.
\n\t\t\tLastly, beyond extending robots’
In this chapter, we proposed an approach to intent recognition that combines visual tracking and recognition with contextual awareness in a mobile robot. Understanding intentions in context is an essential human activity, and with high likelihood will be just as essential in any robot that must function in social domains. Our approach is based on the view that to be effective, an intent recognition system should process information from the system\'s sensors, as well as relevant social information. To encode that information, we introduced the lexical digraph data structure, and showed how such a structure can be built and used. We demonstrated the effectiveness of separating interaction identification from interaction classification for building scalable systems. We discussed the visual capabilities necessary to implement our framework, and validated our approach in simulation and on a physical robot.
\n\t\t\tWhen we view robots as autonomous agents that increasingly must exist in challenging and unpredictable human social environments, it becomes clear that robots must be able to understand and predict human behaviors. While the work discussed here is hardly the final say in the matter of how to endow robots with such capabilities, it reveals many of the challenges and suggests some of the strategies necessary to make socially intelligent machines a reality.
\n\t\tAccording to Russell Ackoff [1], a systems theorist and professor of organizational change, the content of the human mind can be classified into three categories:
IF temperature < = 0° C THEN cold = true;
Cold IF == right THEN notify personnel to remove ice from aircraft.
Indeed, knowledge is the appropriate collection of information such that it intends to be useful. Knowledge is a deterministic process. Memorization of information leads to knowledge. Knowledge represents a pattern and provides a high level of predictability regarding what is being described or will happen next.
Ex: If the humidity is very high and the temperature drops drastically, the atmosphere is unlikely to hold the humidity so that it rains.
This knowledge has a useful meaning, but its integration in a context will infer new knowledge. For example, a student memorizes or accumulates knowledge of the multiplication Table. A student can answer 2 × 2 because this knowledge is in the multiplication table. Nevertheless, when asked for 1267 × 300, he cannot answer correctly because he cannot dip into the multiplication table. To answer such a question correctly requires a real cognitive and analytical capacity that exists in the next level … comprehension. In computer jargon, most of the applications we use (modeling, simulation, etc.) use stored knowledge.
The system is an aggregated “whole” where each component interacts with at least one other component of the system. The components or parts of a system can be real or abstract.
All system components work toward a standard system goal. A system can contain several subsystems. It can be connected to other systems.
A system is a collection of elements or components that interact to achieve goals. The elements themselves and the relationships between them determine how the system works. Systems have inputs, processing mechanisms, outputs, and feedback mechanisms. A system processes the input to create the output [3].
Input is the activity of collecting and capturing data.
Processing involves the transformation of inputs into outputs such as computation, for example.
Output is about producing useful information, usually in the form of documents and reports. The output of one system can become the input of another system. For example, the output of a system, which processes sales orders, can be used as input to a customer’s billing system. Computers typically produce output to printers and display to screens. The output can also be reports and documents written by hand or produced manually.
Finally, feedback or feedback is information from the system used to modify inputs or treatments as needed.
An information system (IS) is a set of interrelated components that collect, manipulate, store and disseminate information and provide a feedback mechanism to achieve a goal. The feedback mechanism helps organizations achieve their goals by increasing profits, improving customer service [3], and supporting decision-making and control in organizations [4].
Companies use information systems to increase revenues and reduce costs.
In organizations, information systems are structured around four essential elements, proposed in the 1960s by Harold Leavitt (Figure 1). The pattern is known as the “Leavitt Diamond.”
Leavitt’s diamond: A socio-technical view of IS.
A company has systems to support the different managerial levels. These systems include transaction processing systems, management information systems, decision support systems, and dedicated business intelligence systems.
Companies use information systems so that accurate and up-to-date information is available when needed [5].
Within the same organization, executives at different hierarchy levels have very different information requirements, and different types of information systems have evolved to meet their needs. A common approach for examining the types of information systems used within organizations is to classify them according to their roles at different organizational structure levels, and this approach is called a vertical approach. Indeed, the organization is considered a management pyramid at four levels (Figure 2):
Information Systems types according to managerial level.
At the operational level, managers need systems that keep track of the organization for necessary activities and operations, such as sales and material flow in a factory. A transaction processing system is a computer system that performs and records the routine (daily) operations necessary for managing affairs, such as keeping employee records, payroll, shipping merchandise, keeping records, accounting and treasury.
At this level, the primary purpose of systems is to answer routine questions and monitor transactions flow through the organization.
At the operational level, tasks, resources, and objectives are predefined and highly structured. The decision to grant credit to a customer, for example, is made by a primary supervisor according to predefined criteria. All that needs to be determined is whether the client meets the criteria.
Middle managers need systems to help with oversight, control, decision making, and administrative activities. The main question that this type of system must answer is: is everything working correctly?
Its role is to summarize and report on essential business operations using data provided by transaction processing systems. Primary transaction data is synthesized and aggregated, and it is usually presented in reports produced regularly.
DSS supports decision-making for unusual and rapidly evolving issues, for which there are no fully predefined procedures. This type of system attempts to answer questions such as: What would impact production schedules if we were to double sales for December? What would the level of Return on investment be if the plant schedule were delayed by more than six months?
While DSSs use internal information from TPS and MIS systems, they also leverage external sources, such as stock quotes or competitor product prices. These systems use a variety of models to analyze the data. The system can answer questions such as: Considering customer’s delivery schedule and the freight rate offered, which vessel should be assigned, and what fill rate to maximize profits? What is the optimum speed at which a vessel can maximize profit while meeting its delivery schedule?
ESS helps top management make decisions. They address exceptional decisions requiring judgment, assessment, and a holistic view of the business situation because there is no procedure to be followed to resolve a given issue at this level.
ESS uses graphics and data from many sources through an interface that senior managers easily understand. ESS is designed to integrate data from the external environment, such as new taxes or competitor data, and integrate aggregate data from MIS and DSS. ESSs filter, synthesize and track critical data. Particular attention is given to displaying this data because it contributes to the rapid assimilation of these top management figures. Increasingly, these systems include business intelligence analysis tools to identify key trends and forecasts.
Decision-making in companies is often associated with top management. Today, employees at the operational level are also responsible for individual decisions since information systems make information available at all company levels.
So decisions are made at all levels of the company.
Although some of these decisions are common, routine, and frequent, the value of improving any single decision may be small, but improving hundreds or even thousands of “small” decisions can add value to the business.
Not all situations that require decisions are the same. While some decisions result in actions that significantly impact the organization and its future, others are much less important and play a relatively minor role. A decision’s impact is a criterion that can differentiate between decision situations and the degree of the decision’s structuring. Many situations are very structured, with well-defined entrances and exits. For example, it is relatively easy to determine the amount of an employee’s pay if we have the appropriate input data (for example, the number of hours worked and their hourly wage rate), and all the rules of relevant decision (for example, if the hours worked during a week are more than 40, then the overtime must be calculated), and so on. In this type of situation, it is relatively easy to develop information systems that can be used to help (or even automate) the decision.
In contrast, some decision situations are very complex and unstructured, where no specific decision rules can be easily identified. As an example, consider the following task: “Design a new vehicle that is a convertible (with a retractable hardtop), has a high safety rating, and is esthetically pleasing to a reasonably broad audience. No predefined solution to this task finalizing a design will involve many compromises and require considerable knowledge and expertise.
Examples of Types of decisions, according to managerial level, are presented in Table 1.
Decision level | Characteristics of decisions | Examples of decisions |
---|---|---|
Top Management | Unstructured | Decide whether or not to come into the market |
Approve the budget allocated to capital | ||
Decide on long-term goals | ||
Intermediate management | Semi-structured | Design a marketing plan |
Develop a departmental budget | ||
Design a website for the company | ||
Operational management | Structured | Determine the overtime hours |
Determine the rules for stock replenishment | ||
Grant credit to customers | ||
Offer special offers to customers |
Types of decisions according to managerial level.
Generally speaking, structured decisions are more common at lower levels of the organization, while unstructured problems are more common at higher business levels.
The more structured the decision, the easier it is to automate. If it is possible to derive an algorithm that can be used to make an efficient decision and the input data to the algorithm can be obtained at a reasonable cost, it generally makes sense to automate the decision.
Davenport and Harris [6] proposed a framework for the categorization of applications used for decision automation. Most of the systems they describe include some expert systems, often combined with DSS and/or EIS aspects. The categories they provided include Solution Configuration, Optimization of Performance, Routing or Segmentation of Decisions, Business Regulatory Compliance, Fraud Detection, Dynamic Forecasting, and Operational Control.
Many business decision situations are not very structured, and therefore cannot (or should not) be fully automated.
Data visualization tools allow users to see patterns and relationships in large amounts of data that would be difficult to discern if the data had been presented in tabular form, for example.
Geographic Information Systems (GIS) helps decision-makers visualize issues requiring knowledge about people’s geographic distribution or other resources. GIS software links the location data of points, lines, and areas on a map. Some GIS have modeling capabilities to modify data and simulate the impact of these modifications. For example, GIS could help the government calculate response times to natural disasters and other emergencies or help banks identify the best replacement for installing new branches or ATMs of tickets.
Geographic (or geospatial) information refers not only to things that exist (or are being planned) on specific locations on the Earth’s surface but also to events such as traffic congestion, flooding, and other events such as an open-air festival [7].
Its scope and granularity characterize this information:
Location, extent, and coverage are essential aspects of geographic information.
Granularity, for example, geometric information, can be concise or fuzzy depending on the application.
GIS is used to capture, store, analyze, and visualize data that describes part of the Earth’s surface, technical and administrative entities, and the results of geosciences, economics, and ecological applications.
It is a computer system with a database observing the spatial distribution of objects, activities, or events described by points, lines, or surfaces.
It is a comprehensive collection of tools for capturing, storing, extracting, transforming, and visualizing real-world spatial data for applications.
It is an information system containing all the data of the territory, the atmosphere, the surface of the Earth, and the lithosphere, allowing the systematic capture, the update, the manipulation, and the analysis of these data standardized reference framework.
It is a decision support system that integrates spatial data into a problem-solving environment.
Other definitions of GIS exist depending on the point of view of application [7], a GIS can be considered as
A collection of spatial data with storage and retrieval functions
A collection of algorithmic and functional tools
A set of hardware and software components necessary for processing geospatial data
A particular type of information technology
A gold mine for answers to geospatial questions
A model of spatial relations and spatial recognition.
Typically, a GIS provides functions for the storage and retrieval, interrogation and visualization, transformation, geometric and thematic analysis of information.
Indeed, geographic/geospatial information is ubiquitous, as seen on mobile devices such as cell phones, maps, satellite images, positioning and routing services, and even 3D simulations, gaining popularity from increasingly essential segments of the consumers.
Technological advances in recent years have transformed classical GIS into new forms of geospatial analysis tools, namely:
Web-based and service-oriented approaches have led to a client–server architecture.
Mobile technology has made GIS ubiquitous in smartphones, tablets, and laptops (opening up new markets).
IS applications cover functional areas and focus on the execution of business processes across the enterprise, including all management levels.
There are several categories of business applications: Enterprise Resource Planning (ERP), Supply Chain Management systems (SCM), Customer Relationship Management systems (CRM), electronic commerce or e-commerce, Knowledge Management systems or KM, and Business Intelligence or BI. The categories of business applications dealt with in this section cover all managerial levels since KMS are mainly intended for top management (ESS), SCMs, CRMs, and BI for mid-level management (MIS and DSS), ERP and e-commerce dedicated to the transactional level (TPS or basic or operational).
However, it is useful to specify that some ERP systems, such as the global giant SAP, offer versions of its software package covering these different categories, including SCM and CRM.
ERPs allow business processes related to production, finance and accounting, sales and marketing, and human resources to be integrated into a single software system. Information that was previously fragmented across many different systems is integrated into a single system with a single, comprehensive database that multiple business stakeholders can use.
An ERP system centralizes an organization’s data, and the processes it applies are the processes that the organization must adopt [8]. When an ERP provider designs a module, it must implement the rules of the associated business processes. ERP systems apply best management practices. In other words, when an organization implements ERP, it also improves its management as part of ERP integration. For many organizations, implementing an ERP system is an excellent opportunity to improve their business practices and upgrade their software simultaneously. Nevertheless, integrating an ERP represents a real challenge: Are the processes integrated into the ERP better than those currently used? Furthermore, if the integration is booming, and the organization operates the same as its competitors, how do you differentiate yourself?
ERPs are configurable according to the specificities of each organization. For organizations that want to continue using their processes or even design new ones, ERP systems provide means for customizing these processes. However, the burden of maintenance falls on the organizations themselves in the case of ERP customization.
Organizations will need to consider the following decision carefully: should they accept the best practice processes embedded in the ERP system or develop their processes? If the choice is ERP, process customization should only concern processes essential to its competitive advantage.
Electronic commerce is playing an increasingly important role in organizations with their customers.
E-commerce enables market expansion with minimal capital investment, improves the supply and marketing of products and services. Nevertheless, there is still a need for universally accepted standards to ensure the quality and security of information and sufficient telecommunications bandwidth.
The three main categories of e-commerce are Business-to-Consumer (B2C), Business-to-Business (B2B), and Consumer-to-Consumer (C2C).
Business-to-Consumer (B2C) e-commerce involves the retailing of products and services to individual customers. Amazon, which sells books, software, and music to individual consumers, is an example of B2C e-commerce.
Business-to-Business (B2B), e-commerce involves the sale of goods and services between businesses. The ChemConnect website for buying and selling chemicals and plastics is an example of B2B e-commerce.
Consumer-to-Consumer (C2C), this type of e-commerce involves consumers selling directly to consumers. For example, eBay, the giant web-based auction site, allows individuals to sell their products to other consumers by auctioning their goods, either to the highest bidder or through a fixed price.
Information systems for the management of the supply chain or SCM make it possible to manage its suppliers’ relations. These systems help suppliers and distributors share information about orders, production, inventory levels, and delivery of products and services so that they can source, produce and deliver goods and services efficiently.
The ultimate goal is to get the right amount of products from their suppliers at a lower cost and time. Additionally, these systems improve profitability by enabling managers to optimize scheduling decisions for procurement, production, and distribution.
Anomalies in the supply chain, such as parts shortages, underutilized storage areas, prolonged storage of finished products, or high transportation cost, are caused by inaccurate or premature information. For example, manufacturers may stock an excessive amount of parts because they do not know precisely the dates of upcoming deliveries from suppliers. Alternatively, conversely, the manufacturer may order a small number of raw materials because they do not have precise information about their needs. These supply chain inefficiencies squander up to 25 percent of the company’s operating costs.
If a manufacturer has precise information on the exact number of units of the product demanded by customers, on what date, and its exact production rate, it would be possible to implement a successful strategy called “just in time” (just-in-time strategy). Raw materials would be received precisely when production needed them, and finished products would be shipped off the assembly line with no need for storage.
However, there are always uncertainties in a supply chain because many events cannot be predicted, such as late deliveries from suppliers, defective parts or non-conforming raw materials, or even breakdowns in the production process. To cope with these kinds of contingencies and keep their customers happy, manufacturers often deal with these uncertainties by stocking more materials or products than they need. The safety stock acts as a buffer against probable supply chain anomalies. While managing excess inventory is expensive, a low stock fill rate is also costly because orders can be canceled.
CRM aims to manage customer relationships by coordinating all business processes that deal with customers’ sales and marketing. The goal is to optimize revenue, customer satisfaction, and customer loyalty. This collected information helps companies identify, attract and retain the most profitable customers, and provide better service to existing customers and increase sales.
The CRM captures and integrates the data of the company’s customers. It consolidates data, analyzes it, and distributes the results to different systems and customer touchpoints throughout the company. A point of contact (touchpoint, contact point) is a means of interaction with the customer, such as telephone, e-mail, customer service, conventional mail, website, or even a sales store, by retail.
Well-designed CRM systems provide a single view of the company’s customers, which is useful for improving sales and customer service quality. Such systems also provide customers with a single view of the business regardless of their contact point or usage.
CRM systems provide data and analytical tools to answer these types of questions: “What is the value of a customer to the business” “Who are the most loyal customers?” “Who are the most profitable customers” and “What products are profitable customers buying?”
Businesses use the answers to these questions to acquire new customers, improve service quality, support existing customers, tailor offerings to customer preferences, and deliver escalating services to retain profitable customers.
Some companies perform better than others because they know how to create, produce, and deliver products and services. This business knowledge is difficult to emulate, is unique, and can be leveraged and deliver long-term strategic benefits. Knowledge Management Systems or KMS enable organizations to manage processes better to collect and apply knowledge and expertise. These systems collect all the relevant knowledge and experiences in the company and make them available to everyone to improve business processes and decision management.
Knowledge management systems can take many different forms, but the primary goals are: 1) facilitating communication between knowledge workers within an organization, and 2) to make explicit the expertise of a few and make it available to many.
Consider an international consulting firm, for example. The company employs thousands of consultants across many countries. The consultancy team in Spain may be trying to resolve a client’s problem, very similar to a consultancy team in Singapore that has already been solved. Rather than reinventing the solution, it would be much more useful for the Spain team to use the Singapore team’s knowledge.
One way to remedy this situation is to store case histories from which employees worldwide can access (via the Internet) and search for cases (using a search engine) according to their respective needs. If the case documentation is of good quality (accurate, timely, complete), the consultants will share and benefit from each other’s experiences, and the knowledge gained.
Unfortunately, it is often difficult to get employees to contribute meaningfully to the knowledge base (as they are probably more concerned with moving forward on their next engagements with customers rather than documenting their past experiences). For such systems to have any chance of success, the work organization must change, such as establishing a reward system for cases captured and well documented.
The term Business Intelligence (BI) is generally used to describe a type of information system designed to help decision-makers learn about trends and identify relationships in large volumes of data. Typically, BI software is used in conjunction with large databases or data warehouses. While the specific capabilities of BI systems vary, most can be used for specialized reporting (e.g., aggregated data relating to multiple dimensions), ad-hoc queries, and trend analysis.
As with knowledge management systems, the value of business intelligence systems can be hampered in several ways. The quality of the data that is captured and stored is not guaranteed. Besides, the database (or data warehouse) may lack essential data (for example, ice cream sales are likely to correlate with temperature; without the temperature information, it may be difficult to identify why it is. There has been an increase or decrease in sales of ice cream). A third challenge is the lack of mastery of data analysts over the context of the organization’s operations, even if they are proficient in BI software. In contrast, a manager has mastery of the organization but does not know how to use BI software. As a result, it is common to have a team (a manager associated with a data analyst) to get the most information (and/or knowledge) from a business intelligence system.
Unlike physical assets, the information does not necessarily disappear when it has been stolen. If an organization holds confidential information such as a new manufacturing process, it may be uploaded by an unauthorized person and remain available to the organization.
Exposing information to unauthorized personnel constitutes a breach of confidentiality.
Another type of system failure happens when the integrity of information is no longer guaranteed. In other words, rather than unauthorized exposure of information, there are unauthorized changes of information. A corporate website containing documentation on how to configure or repair its products could suffer severe financial harm if an intruder could change instructions, leading to customers misconfigure or even ruin the purchased product.
Finally, the denial of access to information or the unavailability of information represents another type of information failure. For example, if a doctor is prevented from accessing a patient’s test results, the patient may suffer needlessly or even die. A commercial website could lose significant sales if its website were down for an extended period.
Understanding the potential causes of system failure enables appropriate action to be taken to avoid them. There are a wide variety of potential threats to an organization’s information systems.
Human threats are the most complicated to manage because they include a wide variety of behaviors. To illustrate how the level of detail can vary, some relevant subcategories include:
Accidental behavior by members of the organization, technical support staff, and customers of the organization
Malicious behavior by someone inside or outside the organization
Other categories of threats include:
A natural event: flood, fire, tornado, ice storm, earthquake, pandemic flu
Environmental elements: chemical spill, gas line explosion.
Technical Threat: Hardware or software failure
Operational Threat: a faulty process that unintentionally compromises the confidentiality, integrity, or availability of information. For example, an operational procedure that allows application programmers to upgrade software without test or notification system operators can result in prolonged outages.
It is possible to categorize the various checks intended to avoid a failure, such as:
Management controls management processes that identify system requirements such as confidentiality, integrity, and availability of information and provide for various management controls to ensure that these requirements are met.
Operational controls: include the day-to-day processes associated with the provision of information services.
Technical controls: concern the technical capacities integrated into the IT infrastructure to support the increased confidentiality, integrity, and availability of information services.
A widely cited Gartner research report concludes that “people directly cause 80% of downtime in critical application services. The remaining 20% are caused by technological failures, environmental failure or a natural disaster”.
Often, these failures are the result of software modifications such as adding new features or misconfiguring servers or network devices.
IT professionals should ensure that system changes are prioritized and tested and that all interested parties are notified of proposed changes.
Perceptible benefits can be quantified and assigned a monetary value. Imperceptible benefits, such as more efficient customer service or improved decision making, cannot be immediately quantified but can lead to quantifiable long-term gain [4].
System performance can be measured in different ways.
Efficiency is often referred to as “doing the things right” or doing things right. Efficiency can be defined as the ratio of output to input. In other words, a company is more efficient if it produces more with the same amount of resources or if it produces the same amount of output with a lower investment of resources, or - even better - produces more with less input. In other words, the company achieves improvements in terms of efficiency by reducing the waste of resources while maximizing Productivity.
Each time an item is sold or ordered, the manager updates the quantity of the item sold in the inventory system. The manager needs to check the sales to determine which items have been sold the most and restocked. This considerably reduces the manager’s time to manage his stock (limit input to achieve the same output). So efficiency is a measure of what is produced divided by what is consumed [3].
Effectiveness is measured based on the degree achieved in achieving system objectives. It can be calculated by dividing the objectives achieved by the total of the objectives set.
Effectiveness is denoted as “doing the right thing” or doing the things necessary or right. It is possible to define effectiveness as an organization’s ability to achieve its stated goals and objectives. Typically, a business more significant is the one that makes the best decisions and can carry them out.
For example, to better meet its various customers’ needs, an organization may create or improve its products and services founded on data collected from them and information accumulated from sales activities. In other words, information systems help organizations better understand their customers and deliver the products and services that customers desire. Collecting customer data on an individual basis will help the organization provide them with personalized service.
The manager can also ask customers what kind of products and services customers would like to buy in the future, trying to anticipate their needs. With the information gathered, the manager will order the customers’ products and stop ordering unpopular products.
In what follows, we present several formulas established to measure efficiency and effectiveness resulting from the information systems use. Indeed, the impact of an information system on an organization can be assessed using financial measures.
When the information system is implemented, management will certainly want to assess whether the system has succeeded in achieving its objectives. Often this assessment is challenging to achieve. The business can use financial metrics such as Productivity, Return On Investment (ROI), net present value, and other performance metrics explained in the following:
Return on investment, denoted as a Return rate, is a financial ratio that measures the amount gained or lost compared to the amount initially invested.
An information system with a positive return on investment indicates that this system can improve its efficiency.
The advantage of using Return on investment is that it is possible to quantify the costs and benefits of introducing an information system. Therefore, it is possible to use this metric to compare different systems and see which systems can help the organization be more efficient and/or more effective.
Developing information systems that measure Productivity and control is a crucial element for most organizations. Productivity is a measure of produced output divided by required input. A higher production level for a given entry-level means greater Productivity; a lower output level for a given entry-level means lower Productivity. Values assigned to productivity levels are not always based on hours worked. Productivity may be based on the number of raw materials used, the quality obtained, or the time to produce the goods or services. According to other parameters and with other organizations in the same industry, Productivity’s value has to mean only compared to other Productivity periods.
Another measure of the SI value is the increase in profit or the growth in realized profits. For example, a mail-order company installs an order processing system that generates 7 percent growth in profits over the previous year.
Market share is the percentage of sales of a product or service relative to the overall market. If installing a new online catalog increases sales, it could help increase the company’s market share by, for example, 20 percent.
Although customer satisfaction is difficult to quantify, many companies measure their information systems performance based on internal and external feedback. Some companies use surveys and questionnaires to determine whether investments have resulted in increased customer satisfaction.
Another way to measure the value of information systems has been developed by the Gartner Group and is called the Total Cost of Ownership (TCO). This approach allocates the total costs between acquiring the technology, technical support, and administrative costs. Other costs are added to the TCO, namely: retooling and training costs. TCO can help develop a more accurate estimate of total costs for systems ranging from small computers to large mainframe systems.
The evolution of information technologies leads to the reflection on new approaches that set up more flexible, more scalable architectures to meet its agility needs. The urbanization of information systems is one such approach.
The company’s information system’s urbanization is an IT discipline consisting of developing its information system to guarantee its consistency with its objectives and business. By taking into account its external and internal constraints while taking advantage of the opportunities of the IT state of the art.
This discipline is based on a series of concepts modeled on those of the urbanization of human habitat (organization of cities, territory), concepts that have been reused in IT to formalize or model the information system.
Town planning defines rules and a coherent, stable, and modular framework, to which the various stakeholders refer for any investment decision relating to the management of the information system.
In other words, to urbanize is to lead the information systems’ continuous transformation to simplify it and ensure its consistency.
The challenges of urbanization consist of managing complexity, communicating and federating work, considering organizational constraints, and guiding technological choices.
Define and frame the objectives of the project, define the scope, develop the schedule.
Carry out the inventory, organize the work, and present the deliverables. More precisely, list the assets and map the different layers (business, functional, application, and technical):
Business Architecture
Identify “business processes”: Who does what and why? The description of the processes is done with BPMN, EPC formalisms, etc. This step is tricky and may require the use of exploration methods. However, it does improve the overall understanding and increase the possibilities for optimization
Functional architecture
Identify the “functional block”: What do we need to carry out the business processes? Here, we are based on a classic division into zones (exchanges, core business, reference data, production data, support activities, management). This step’s difficulty lies in choosing the right level of detail and remaining consistent with business processes. However, it provides a hierarchical presentation and makes it easier to break down the work.
Application Architecture
Identify the applications: How to achieve the functionalities? This step is based on a classic N-Tiers division. However, it is not easy to provide value and solutions compared to functional architecture. This stage lays the foundations for the realization (major technological choices, etc.).
System Architecture
Identify the technical components: With what and where the applications work, it is based on a classic division into technical areas (security, storage, etc.). It is not easy to make the connection between applications and servers. This step brings concrete and structuring and is essential to assess the cost of the system.
Impact on the different layers, consideration of constraints (human, material, etc.), design of costed scenarios, and arbitration of the choice of a target.
How to organize the work, frame and then refine the budgets, design and plan projects, define the support strategy, set up an organization, contributions, roles, and responsibilities of actors.
At the end of this process, a Land Use Plan (LUP) is defined. It is a report consisting of:
Summaries of the orientations chosen as well as the justifications for the options selected.
A definition of areas, neighborhoods, and blocks.
Existing and target maps (process, functional, application, and technical mapping).
Additional documents (interview reports, list of people and organizational entities, etc.)
The goal is to identify the gaps between the existing and the principles of urbanization and establish changes by describing the actions and their corresponding cost.
In practice, the urbanization process is very cumbersome to implement. On the one hand, it requires the participation of many actors in the organization, and on the other hand, the analysis is very long. As a result, needs to change, and LUP is no longer necessarily suitable.
The reasons for a successful or unsuccessful IS implementation are complex and contested by different stakeholders and from the various perspectives involved. Developers tend to focus on the system’s technical validity in terms of execution, operation, and evolution. Other qualities are often considered, such as security, maintainability, scalability, stability, and availability. All of these criteria are considered to be signs of successful IS Development.
The failure of an IS can be defined as: either the system put in place does not meet the user’s expectations or does not function properly. The reasons for failure are as divergent as the projects.
The perspective of project management, on the other hand, tends to focus on the consumption of resources. The project delivered with the initial budget and within the allotted time is considered a successful project. Nelson [9] analyzed 99 SI projects and identified 36 classic errors. He categorized these errors into four categories: process, people, product, and technology. The last category concerns the factors leading to IS failures based on the misuse of modern technologies.
The seminal article by DeLone and McLean [10] suggested that IS success should be the preeminent dependent variable for the IS domain. These researchers proposed a taxonomy of six interdependent variables to define the IS’ success as the system’s quality, the quality of information, the IS, user satisfaction, individual impact, and organizational impact.
One of the significant extensions to this proposition is the dimension of the IT department’s quality of service [11].
Either way, the use of the system is seen as a sign of its success. The IS use level is incorporated into most IS success models [11, 12]. These models show the complexity of measuring user satisfaction because, even in the same organization, some user groups may be more or less enthusiastic than others to use the new information system.
In the current global context of the covid pandemic, it appears clear that information systems that integrate web and mobile technologies can positively contribute to the monitoring of contaminated cases and therefore minimize the risks of contamination provided that users adhere to this movement for the benefit of all [13]. A truly global, rapid, and efficient decision-making process is enabled by the integration of information systems from distributed sources [14].
To conclude this introductive chapter, we present its key ideas:
Levels of information are data, information, and knowledge.
The system is an aggregated “whole” where each component interacts with at least one other system component to achieve a goal.
An information system can be defined as a set of interconnected components that gather, process, store and dispense information to support decision making and control in an organization. An IS can be seen as a socio-technical system. The technical part includes the technology and the processes, while the social part includes the people and the structure.
The role of information systems is to solve an organization’s problems concerning its information needs
A company has systems to support the different managerial levels: transaction processing systems, management information systems, decision support systems, and systems dedicated to business intelligence.
Decisions can be operational or strategic.
There are several categories of business applications: enterprise resource planning, supply chain management systems, customer relationship management systems, knowledge management systems, and business intelligence.
Among the failures that can affect IS a violation of confidentiality, integrity, and availability of information.
The controls intended to avoid the IS’s security failures include management controls, operational controls, and technical controls.
The information system’s performance can be measured according to efficiency, effectiveness, Return on investment, Productivity, customer satisfaction, etc.
Urbanizing an information system means directing its continuous transformation to guarantee its consistency
The reasons for a successful or unsuccessful implementation of an IS are complex and contested by the various stakeholders and from the various perspectives involved.
"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges".
\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.
",metaTitle:"About Open Access",metaDescription:"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges.\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.",metaKeywords:null,canonicalURL:"about-open-access",contentRaw:'[{"type":"htmlEditorComponent","content":"The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\\n\\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\\n\\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
\\n\\n“By “open access” to [peer-reviewed research literature], we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited” (reference: http://www.budapestopenaccessinitiative.org)
\\n\\nOAI-PMH
\\n\\nAs a firm believer in the wider dissemination of knowledge, IntechOpen supports the Open Access Initiative Protocol for Metadata Harvesting (OAI-PMH Version 2.0). Read more
\\n\\nLicense
\\n\\nBook chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen upholds a very flexible Copyright Policy. There is no copyright transfer to the publisher and Authors retain exclusive copyright to their work. All Monographs/Compacts are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Read more
\\n\\nPeer Review Policies
\\n\\nAll scientific works are Peer Reviewed prior to publishing. Read more
\\n\\nOA Publishing Fees
\\n\\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
\\n\\nDigital Archiving Policy
\\n\\nIntechOpen is committed to ensuring the long-term preservation and the availability of all scholarly research we publish. We employ a variety of means to enable us to deliver on our commitments to the scientific community. Apart from preservation by the Croatian National Library (for publications prior to April 18, 2018) and the British Library (for publications after April 18, 2018), our entire catalogue is preserved in the CLOCKSS archive.
\\n\\nOpen Science is transparent and accessible knowledge that is shared and developed through collaborative networks.
\\n\\nOpen Science is about increased rigour, accountability, and reproducibility for research. It is based on the principles of inclusion, fairness, equity, and sharing, and ultimately seeks to change the way research is done, who is involved and how it is valued. It aims to make research more open to participation, review/refutation, improvement and (re)use for the world to benefit.
\\n\\nOpen Science refers to doing traditional science with more transparency involved at various stages, for example by openly sharing code and data. It implies a growing set of practices - within different disciplines - aiming at:
\\n\\nWe aim at improving the quality and availability of scholarly communication by promoting and practicing:
\\n\\n\\n"}]'},components:[{type:"htmlEditorComponent",content:'
The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\n\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\n\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
\n\n“By “open access” to [peer-reviewed research literature], we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited” (reference: http://www.budapestopenaccessinitiative.org)
\n\nOAI-PMH
\n\nAs a firm believer in the wider dissemination of knowledge, IntechOpen supports the Open Access Initiative Protocol for Metadata Harvesting (OAI-PMH Version 2.0). Read more
\n\nLicense
\n\nBook chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen upholds a very flexible Copyright Policy. There is no copyright transfer to the publisher and Authors retain exclusive copyright to their work. All Monographs/Compacts are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Read more
\n\nPeer Review Policies
\n\nAll scientific works are Peer Reviewed prior to publishing. Read more
\n\nOA Publishing Fees
\n\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
\n\nDigital Archiving Policy
\n\nIntechOpen is committed to ensuring the long-term preservation and the availability of all scholarly research we publish. We employ a variety of means to enable us to deliver on our commitments to the scientific community. Apart from preservation by the Croatian National Library (for publications prior to April 18, 2018) and the British Library (for publications after April 18, 2018), our entire catalogue is preserved in the CLOCKSS archive.
\n\nOpen Science is transparent and accessible knowledge that is shared and developed through collaborative networks.
\n\nOpen Science is about increased rigour, accountability, and reproducibility for research. It is based on the principles of inclusion, fairness, equity, and sharing, and ultimately seeks to change the way research is done, who is involved and how it is valued. It aims to make research more open to participation, review/refutation, improvement and (re)use for the world to benefit.
\n\nOpen Science refers to doing traditional science with more transparency involved at various stages, for example by openly sharing code and data. It implies a growing set of practices - within different disciplines - aiming at:
\n\nWe aim at improving the quality and availability of scholarly communication by promoting and practicing:
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This chapter considers the use of different capacitated clustering problems and models that fits better in real-life applications such as household waste collection, IT teams layout in software factories, wholesales distribution, and staff’s home collection or delivery to/from workplace. Each application is explored in its regular form as it is being developed by contractors and/or users. We consider for each application the aspects of solving the problem by the appropriate mathematical programming model and decision support methodology (using aggregated Geographical Information System and mobile technology) to hold correctly and most precisely the problems and difficulties related to instances in evaluation. The experience on these fields is here revealed in detailed form as the results obtained by using the techniques here explained.
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Other positions she has held at the university include Vice-Dean of Master Programs, Vice-Dean of the Degree in Biology and Vice-Dean for Mobility and Enterprise and Engagement at the Faculty of Science (University of Alicante). She received her Bachelor in Biology in 1998 (University of Alicante) and her PhD in 2003 (Biochemistry, University of Alicante). She undertook post-doctoral research at the University of East Anglia (Norwich, U.K. 2004-2005; 2007-2008).\nHer multidisciplinary research focuses on investigating archaea and their potential applications in biotechnology. She has an H-index of 21. She has authored one patent and has published more than 70 indexed papers and around 60 book chapters.\nShe has contributed to more than 150 national and international meetings during the last 15 years. Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",isOpenForSubmission:!0,editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. He performed post-doctoral studies at Max-Planck Institute, Germany, and University of Florence, Italy in addition to making several scientific visits abroad. He currently works as a Full Professor of Biochemistry in the Faculty of Pharmacy, Anadolu University, Turkey. Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. 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He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. 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He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. 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Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. 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She gained considerable experience in developing and validating new methodologies whose applications allowed her to determine both the amount of biomarkers (Desmosine and Isodesmosine) in the urine of patients affected by COPD, and the activity of proteolytic enzymes (HNE, Cathepsin G, Pseudomonas aeruginosa elastase) in the sputa of these patients. Simona Viglio was also involved in research dealing with the supplementation of amino acids in patients with brain injury and chronic heart failure. She is presently engaged in the development of 2-DE and LC-MS techniques for the study of proteomics in biological fluids. The aim of this research is the identification of potential biomarkers of lung diseases. 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He worked as a Executive Research & Development @ Cadila Pharmaceuticals Ltd, Ahmedabad. He received DBT-postdoc fellow @ Molecular Biophysics Unit, Indian Institute of Science, Bangalore under the supervision of Prof. P. Balaram, later he moved to NIH-postdoc researcher at Drexel University College of Medicine, Philadelphia, USA, after his return from postdoc joined NITK-Surthakal as a Adhoc faculty at department of chemistry. Since from August 2013 working as a Associate Professor, and in 2016 promoted to Profeesor in the School of Basic Sciences: Department of Chemistry and having 20 years of teaching and research experiences.",institutionString:null,institution:{name:"Rani Channamma University, Belagavi",country:{name:"India"}}},{id:"158492",title:"Prof.",name:"Yusuf",middleName:null,surname:"Tutar",slug:"yusuf-tutar",fullName:"Yusuf Tutar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/158492/images/system/158492.jpeg",biography:"Prof. Dr. Yusuf Tutar conducts his research at the Hamidiye Faculty of Pharmacy, Department of Basic Pharmaceutical Sciences, Division of Biochemistry, University of Health Sciences, Turkey. He is also a faculty member in the Molecular Oncology Program. He obtained his MSc and Ph.D. at Oregon State University and Texas Tech University, respectively. He pursued his postdoctoral studies at Rutgers University Medical School and the National Institutes of Health (NIH/NIDDK), USA. His research focuses on biochemistry, biophysics, genetics, molecular biology, and molecular medicine with specialization in the fields of drug design, protein structure-function, protein folding, prions, microRNA, pseudogenes, molecular cancer, epigenetics, metabolites, proteomics, genomics, protein expression, and characterization by spectroscopic and calorimetric methods.",institutionString:"University of Health Sciences",institution:null},{id:"180528",title:"Dr.",name:"Hiroyuki",middleName:null,surname:"Kagechika",slug:"hiroyuki-kagechika",fullName:"Hiroyuki Kagechika",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/180528/images/system/180528.jpg",biography:"Hiroyuki Kagechika received his bachelor’s degree and Ph.D. in Pharmaceutical Sciences from the University of Tokyo, Japan, where he served as an associate professor until 2004. He is currently a professor at the Institute of Biomaterials and Bioengineering (IBB), Tokyo Medical and Dental University (TMDU). From 2010 to 2012, he was the dean of the Graduate School of Biomedical Science. Since 2012, he has served as the vice dean of the Graduate School of Medical and Dental Sciences. He has been the director of the IBB since 2020. Dr. Kagechika’s major research interests are the medicinal chemistry of retinoids, vitamins D/K, and nuclear receptors. 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He received his post-doctoral training in oncology and cancer proteomics for two years at the Cancer Research Institute of Human Medical University in China. In 2001, he went to the University of Tennessee Health Science Center (UTHSC) in USA, where he was a post-doctoral researcher and focused on mass spectrometry and cancer proteomics. Then, he was appointed as an Assistant Professor of Neurology, UTHSC in 2005. He moved to the Cleveland Clinic in USA as a Project Scientist/Staff in 2006 where he focused on the studies of eye disease proteomics and biomarkers. He returned to UTHSC as an Assistant Professor of Neurology in the end of 2007, engaging in proteomics and biomarker studies of lung diseases and brain tumors, and initiating the studies of predictive, preventive, and personalized medicine (PPPM) in cancer. In 2010, he was promoted to Associate Professor of Neurology, UTHSC. Currently, he is a Professor at Xiangya Hospital of Central South University in China, Fellow of Royal Society of Medicine (FRSM), the European EPMA National Representative in China, Regular Member of American Association for the Advancement of Science (AAAS), European Cooperation of Science and Technology (e-COST) grant evaluator, Associate Editors of BMC Genomics, BMC Medical Genomics, EPMA Journal, and Frontiers in Endocrinology, Executive Editor-in-Chief of Med One. He has\npublished 116 peer-reviewed research articles, 16 book chapters, 2 books, and 2 US patents. His current main research interest focuses on the studies of cancer proteomics and biomarkers, and the use of modern omics techniques and systems biology for PPPM in cancer, and on the development and use of 2DE-LC/MS for the large-scale study of human proteoforms.",institutionString:null,institution:{name:"Xiangya Hospital Central South University",country:{name:"China"}}},{id:"40482",title:null,name:"Rizwan",middleName:null,surname:"Ahmad",slug:"rizwan-ahmad",fullName:"Rizwan Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/40482/images/system/40482.jpeg",biography:"Dr. Rizwan Ahmad is a University Professor and Coordinator, Quality and Development, College of Medicine, Imam Abdulrahman bin Faisal University, Saudi Arabia. Previously, he was Associate Professor of Human Function, Oman Medical College, Oman, and SBS University, Dehradun. Dr. Ahmad completed his education at Aligarh Muslim University, Aligarh. He has published several articles in peer-reviewed journals, chapters, and edited books. His area of specialization is free radical biochemistry and autoimmune diseases.",institutionString:"Imam Abdulrahman Bin Faisal University",institution:{name:"Imam Abdulrahman Bin Faisal University",country:{name:"Saudi Arabia"}}},{id:"41865",title:"Prof.",name:"Farid A.",middleName:null,surname:"Badria",slug:"farid-a.-badria",fullName:"Farid A. Badria",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/41865/images/system/41865.jpg",biography:"Farid A. Badria, Ph.D., is the recipient of several awards, including The World Academy of Sciences (TWAS) Prize for Public Understanding of Science; the World Intellectual Property Organization (WIPO) Gold Medal for best invention; Outstanding Arab Scholar, Kuwait; and the Khwarizmi International Award, Iran. He has 250 publications, 12 books, 20 patents, and several marketed pharmaceutical products to his credit. He continues to lead research projects on developing new therapies for liver, skin disorders, and cancer. Dr. Badria was listed among the world’s top 2% of scientists in medicinal and biomolecular chemistry in 2019 and 2020. He is a member of the Arab Development Fund, Kuwait; International Cell Research Organization–United Nations Educational, Scientific and Cultural Organization (ICRO–UNESCO), Chile; and UNESCO Biotechnology France",institutionString:"Mansoura University",institution:{name:"Mansoura University",country:{name:"Egypt"}}},{id:"329385",title:"Dr.",name:"Rajesh K.",middleName:"Kumar",surname:"Singh",slug:"rajesh-k.-singh",fullName:"Rajesh K. Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329385/images/system/329385.png",biography:"Dr. Singh received a BPharm (2003) and MPharm (2005) from Panjab University, Chandigarh, India, and a Ph.D. (2013) from Punjab Technical University (PTU), Jalandhar, India. He has more than sixteen years of teaching experience and has supervised numerous postgraduate and Ph.D. students. He has to his credit more than seventy papers in SCI- and SCOPUS-indexed journals, fifty-five conference proceedings, four books, six Best Paper Awards, and five projects from different government agencies. He is currently an editorial board member of eight international journals and a reviewer for more than fifty scientific journals. He received Top Reviewer and Excellent Peer Reviewer Awards from Publons in 2016 and 2017, respectively. He is also on the panel of The International Reviewer for reviewing research proposals for grants from the Royal Society. He also serves as a Publons Academy mentor and Bentham brand ambassador.",institutionString:"Punjab Technical University",institution:{name:"Punjab Technical University",country:{name:"India"}}},{id:"142388",title:"Dr.",name:"Thiago",middleName:"Gomes",surname:"Gomes Heck",slug:"thiago-gomes-heck",fullName:"Thiago Gomes Heck",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/142388/images/7259_n.jpg",biography:null,institutionString:null,institution:{name:"Universidade Regional do Noroeste do Estado do Rio Grande do Sul",country:{name:"Brazil"}}},{id:"336273",title:"Assistant Prof.",name:"Janja",middleName:null,surname:"Zupan",slug:"janja-zupan",fullName:"Janja Zupan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/336273/images/14853_n.jpeg",biography:"Janja Zupan graduated in 2005 at the Department of Clinical Biochemistry (superviser prof. dr. Janja Marc) in the field of genetics of osteoporosis. Since November 2009 she is working as a Teaching Assistant at the Faculty of Pharmacy, Department of Clinical Biochemistry. In 2011 she completed part of her research and PhD work at Institute of Genetics and Molecular Medicine, University of Edinburgh. She finished her PhD entitled The influence of the proinflammatory cytokines on the RANK/RANKL/OPG in bone tissue of osteoporotic and osteoarthritic patients in 2012. From 2014-2016 she worked at the Institute of Biomedical Sciences, University of Aberdeen as a postdoctoral research fellow on UK Arthritis research project where she gained knowledge in mesenchymal stem cells and regenerative medicine. She returned back to University of Ljubljana, Faculty of Pharmacy in 2016. She is currently leading project entitled Mesenchymal stem cells-the keepers of tissue endogenous regenerative capacity facing up to aging of the musculoskeletal system funded by Slovenian Research Agency.",institutionString:null,institution:{name:"University of Ljubljana",country:{name:"Slovenia"}}},{id:"357453",title:"Dr.",name:"Radheshyam",middleName:null,surname:"Maurya",slug:"radheshyam-maurya",fullName:"Radheshyam Maurya",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/357453/images/16535_n.jpg",biography:null,institutionString:null,institution:{name:"University of Hyderabad",country:{name:"India"}}},{id:"418340",title:"Dr.",name:"Jyotirmoi",middleName:null,surname:"Aich",slug:"jyotirmoi-aich",fullName:"Jyotirmoi Aich",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038Ugi5QAC/Profile_Picture_2022-04-15T07:48:28.png",biography:"Biotechnologist with 15 years of research including 6 years of teaching experience. Demonstrated record of scientific achievements through consistent publication record (H index = 13, with 874 citations) in high impact journals such as Nature Communications, Oncotarget, Annals of Oncology, PNAS, and AJRCCM, etc. Strong research professional with a post-doctorate from ACTREC where I gained experimental oncology experience in clinical settings and a doctorate from IGIB where I gained expertise in asthma pathophysiology. A well-trained biotechnologist with diverse experience on the bench across different research themes ranging from asthma to cancer and other infectious diseases. An individual with a strong commitment and innovative mindset. Have the ability to work on diverse projects such as regenerative and molecular medicine with an overall mindset of improving healthcare.",institutionString:"DY Patil Deemed to Be University",institution:null},{id:"349288",title:"Prof.",name:"Soumya",middleName:null,surname:"Basu",slug:"soumya-basu",fullName:"Soumya Basu",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035QxIDQA0/Profile_Picture_2022-04-15T07:47:01.jpg",biography:"Soumya Basu, Ph.D., is currently working as an Associate Professor at Dr. D. Y. Patil Biotechnology and Bioinformatics Institute, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India. With 16+ years of trans-disciplinary research experience in Drug Design, development, and pre-clinical validation; 20+ research article publications in journals of repute, 9+ years of teaching experience, trained with cross-disciplinary education, Dr. Basu is a life-long learner and always thrives for new challenges.\r\nHer research area is the design and synthesis of small molecule partial agonists of PPAR-γ in lung cancer. She is also using artificial intelligence and deep learning methods to understand the exosomal miRNA’s role in cancer metastasis. Dr. Basu is the recipient of many awards including the Early Career Research Award from the Department of Science and Technology, Govt. of India. She is a reviewer of many journals like Molecular Biology Reports, Frontiers in Oncology, RSC Advances, PLOS ONE, Journal of Biomolecular Structure & Dynamics, Journal of Molecular Graphics and Modelling, etc. She has edited and authored/co-authored 21 journal papers, 3 book chapters, and 15 abstracts. She is a Board of Studies member at her university. She is a life member of 'The Cytometry Society”-in India and 'All India Cell Biology Society”- in India.",institutionString:"Dr. D.Y. Patil Vidyapeeth, Pune",institution:{name:"Dr. D.Y. 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He pursued post-doctoral research at College of Pharmacy, Health Science Center, Texas A & M University and was involved in another postdoctoral research at Department of Translational Neurosciences and Neurotherapeutics, John Wayne Cancer Institute, Santa Monica, California. In 2015, he worked in Harvard-MIT Health Sciences & Technology as a visiting scientist. He has substantial experience in nanotechnology-based formulation development and successfully served various Indian organizations to develop pharmaceuticals and nutraceutical products. He is an inventor in many US patents and an author in many peer-reviewed articles, book chapters and books published in various media of international repute. Dr. Mukherjee is currently serving as Principal Scientist, R&D at Esperer Onco Nutrition (EON) Pvt. 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Graduated in Pharmacy, specialization in Cosmetology and Cosmeceuticals applied to aesthetics, specialization in Aesthetic and Cosmetic Health, and a doctorate in Pharmaceutical Nanotechnology. Teaching experience in Pharmacy and Aesthetics and Cosmetics courses. She works mainly on the following subjects: nanotechnology, cosmetology, pharmaceutical technology, aesthetics.",institutionString:"Universidade Federal de Juiz de Fora",institution:{name:"Universidade Federal de Juiz de Fora",country:{name:"Brazil"}}},{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",slug:"abdulsamed-kukurt",fullName:"Abdulsamed Kükürt",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",biography:"Dr. Kükürt graduated from Uludağ University in Turkey. He started his academic career as a Research Assistant in the Department of Biochemistry at Kafkas University. In 2019, he completed his Ph.D. program in the Department of Biochemistry at the Institute of Health Sciences. He is currently working at the Department of Biochemistry, Kafkas University. He has 27 published research articles in academic journals, 11 book chapters, and 37 papers. He took part in 10 academic projects. He served as a reviewer for many articles. He still serves as a member of the review board in many academic journals. 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He has 60 articles published in scientific journals and 20 poster presentations in scientific congresses. His research interests include physiology, endocrine system, cancer, diabetes, cardiovascular system diseases, and isolated organ bath system studies.",institutionString:"Kafkas University",institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"418963",title:"Dr.",name:"Augustine Ododo",middleName:"Augustine",surname:"Osagie",slug:"augustine-ododo-osagie",fullName:"Augustine Ododo Osagie",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/418963/images/16900_n.jpg",biography:"Born into the family of Osagie, a prince of the Benin Kingdom. I am currently an academic in the Department of Medical Biochemistry, University of Benin. 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She is a fellow member of the Royal Society of Chemistry UK and the American Chemical Society of the United States.",institutionString:"King Saud University",institution:{name:"King Saud University",country:{name:"Saudi Arabia"}}},{id:"49848",title:"Dr.",name:"Wen-Long",middleName:null,surname:"Hu",slug:"wen-long-hu",fullName:"Wen-Long Hu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49848/images/system/49848.jpg",biography:"Wen-Long Hu is Chief of the Division of Acupuncture, Department of Chinese Medicine at Kaohsiung Chang Gung Memorial Hospital, as well as an adjunct associate professor at Fooyin University and Kaohsiung Medical University. Wen-Long is President of Taiwan Traditional Chinese Medicine Medical Association. He has 28 years of experience in clinical practice in laser acupuncture therapy and 34 years in acupuncture. He is an invited speaker for lectures and workshops in laser acupuncture at many symposiums held by medical associations. He owns the patent for herbal preparation and producing, and for the supercritical fluid-treated needle. Dr. Hu has published three books, 12 book chapters, and more than 30 papers in reputed journals, besides serving as an editorial board member of repute.",institutionString:"Kaohsiung Chang Gung Memorial Hospital",institution:{name:"Kaohsiung Chang Gung Memorial Hospital",country:{name:"Taiwan"}}},{id:"298472",title:"Prof.",name:"Andrey V.",middleName:null,surname:"Grechko",slug:"andrey-v.-grechko",fullName:"Andrey V. Grechko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/298472/images/system/298472.png",biography:"Andrey Vyacheslavovich Grechko, Ph.D., Professor, is a Corresponding Member of the Russian Academy of Sciences. He graduated from the Semashko Moscow Medical Institute (Semashko National Research Institute of Public Health) with a degree in Medicine (1998), the Clinical Department of Dermatovenerology (2000), and received a second higher education in Psychology (2009). Professor A.V. Grechko held the position of Сhief Physician of the Central Clinical Hospital in Moscow. He worked as a professor at the faculty and was engaged in scientific research at the Medical University. Starting in 2013, he has been the initiator of the creation of the Federal Scientific and Clinical Center for Intensive Care and Rehabilitology, Moscow, Russian Federation, where he also serves as Director since 2015. He has many years of experience in research and teaching in various fields of medicine, is an author/co-author of more than 200 scientific publications, 13 patents, 15 medical books/chapters, including Chapter in Book «Metabolomics», IntechOpen, 2020 «Metabolomic Discovery of Microbiota Dysfunction as the Cause of Pathology».",institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"199461",title:"Prof.",name:"Natalia V.",middleName:null,surname:"Beloborodova",slug:"natalia-v.-beloborodova",fullName:"Natalia V. Beloborodova",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/199461/images/system/199461.jpg",biography:'Natalia Vladimirovna Beloborodova was educated at the Pirogov Russian National Research Medical University, with a degree in pediatrics in 1980, a Ph.D. in 1987, and a specialization in Clinical Microbiology from First Moscow State Medical University in 2004. She has been a Professor since 1996. Currently, she is the Head of the Laboratory of Metabolism, a division of the Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russian Federation. N.V. Beloborodova has many years of clinical experience in the field of intensive care and surgery. She studies infectious complications and sepsis. She initiated a series of interdisciplinary clinical and experimental studies based on the concept of integrating human metabolism and its microbiota. Her scientific achievements are widely known: she is the recipient of the Marie E. Coates Award \\"Best lecturer-scientist\\" Gustafsson Fund, Karolinska Institutes, Stockholm, Sweden, and the International Sepsis Forum Award, Pasteur Institute, Paris, France (2014), etc. Professor N.V. Beloborodova wrote 210 papers, five books, 10 chapters and has edited four books.',institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"354260",title:"Ph.D.",name:"Tércio Elyan",middleName:"Azevedo",surname:"Azevedo Martins",slug:"tercio-elyan-azevedo-martins",fullName:"Tércio Elyan Azevedo Martins",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/354260/images/16241_n.jpg",biography:"Graduated in Pharmacy from the Federal University of Ceará with the modality in Industrial Pharmacy, Specialist in Production and Control of Medicines from the University of São Paulo (USP), Master in Pharmaceuticals and Medicines from the University of São Paulo (USP) and Doctor of Science in the program of Pharmaceuticals and Medicines by the University of São Paulo. Professor at Universidade Paulista (UNIP) in the areas of chemistry, cosmetology and trichology. 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He has experience teaching DPharm, Pharm.D, BPharm, and MPharm students. He has more than five publications in reputed journals to his credit. Dr. Faheem’s research area is the development and characterization of nanoformulation for the delivery of drugs to various organs.",institutionString:"Integral University",institution:{name:"Integral University",country:{name:"India"}}},{id:"329795",title:"Dr.",name:"Mohd Aftab",middleName:"Aftab",surname:"Siddiqui",slug:"mohd-aftab-siddiqui",fullName:"Mohd Aftab Siddiqui",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329795/images/system/329795.png",biography:"Dr. Mohd Aftab Siddiqui is an assistant professor in the Faculty of Pharmacy, Integral University, Lucknow, India, where he obtained a Ph.D. in Pharmacology in 2020. He also obtained a BPharm and MPharm from the same university in 2013 and 2015, respectively. 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