Materials used for making thermo-TDR sensors.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{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"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"6285",leadTitle:null,fullTitle:"Proton Exchange Membrane Fuel Cell",title:"Proton Exchange Membrane Fuel Cell",subtitle:null,reviewType:"peer-reviewed",abstract:'The main idea of this study is to scrutinize the performance efficiency and enhancement of modelling and simulations of PEM fuel cell. Besides, the research of PEM fuel cell performance can figure out many critical issues for an alternative resource energy. The chapters collected in the book are contributions by invited researchers with a long-standing experience in different research areas. I hope that the material presented here is understandable to a wide audience, not only energy engineers but also scientists from various disciplines. The book contains nine chapters in three sections: (1) "General Information About PEM Fuel Cell", (2) "PEM Fuel Cell Technology" and (3) "Many Different Applications of PEM Fuel Cell". This book presents detailed and up-to-date evaluations in different areas and was written by academics with experience in their field. It is anticipated that this book will make a scientific contribution to PEM fuel cell and other alternative energy resource workers, researchers, academics, PhD students and other scientists both in the present and in the future.',isbn:"978-1-78923-067-3",printIsbn:"978-1-78923-066-6",pdfIsbn:"978-1-83881-378-9",doi:"10.5772/intechopen.69180",price:119,priceEur:129,priceUsd:155,slug:"proton-exchange-membrane-fuel-cell",numberOfPages:212,isOpenForSubmission:!1,isInWos:1,isInBkci:!1,hash:"ed010c881a38d577f89ccb714c17f785",bookSignature:"Tolga Taner",publishedDate:"May 9th 2018",coverURL:"https://cdn.intechopen.com/books/images_new/6285.jpg",numberOfDownloads:12655,numberOfWosCitations:17,numberOfCrossrefCitations:10,numberOfCrossrefCitationsByBook:1,numberOfDimensionsCitations:25,numberOfDimensionsCitationsByBook:1,hasAltmetrics:1,numberOfTotalCitations:52,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 3rd 2017",dateEndSecondStepPublish:"May 24th 2017",dateEndThirdStepPublish:"August 20th 2017",dateEndFourthStepPublish:"November 18th 2017",dateEndFifthStepPublish:"January 17th 2018",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"197240",title:"Associate Prof.",name:"Tolga",middleName:null,surname:"Taner",slug:"tolga-taner",fullName:"Tolga Taner",profilePictureURL:"https://mts.intechopen.com/storage/users/197240/images/system/197240.jpg",biography:"Dr. Tolga Taner is the head of the Department of Motor Vehicles and Transportation Technology at Aksaray University, Turkey. He received a BS in Mechanical Engineering in 1998; an MS in Mechanical Engineering from Pamukkale University, Denizli, Turkey, in 2002; and a Ph.D. in Mechanical Engineering from the Gazi University of Engineering Faculty, Ankara, Turkey, in 2013. In 2018, he received the title of Associate Professor from the Inter-University Council (UAK). He also worked as a part-time lecturer in the Department of Technical Programs, Middle East Technical University, Turkey, from 2003 to 2006. His current research interests include exergy, renewable energy, and PEM fuel cells. He has published many scientific and conference papers and books. In addition, Dr. Taner has been a manager and researcher for many research projects.",institutionString:"Aksaray University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"4",totalChapterViews:"0",totalEditedBooks:"5",institution:{name:"Aksaray University",institutionURL:null,country:{name:"Turkey"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"765",title:"Electrical Engineering",slug:"electrical-engineering"}],chapters:[{id:"57548",title:"Introductory Chapter: An Overview of PEM Fuel Cell Technology",doi:"10.5772/intechopen.71544",slug:"introductory-chapter-an-overview-of-pem-fuel-cell-technology",totalDownloads:1829,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:null,signatures:"Tolga Taner",downloadPdfUrl:"/chapter/pdf-download/57548",previewPdfUrl:"/chapter/pdf-preview/57548",authors:[{id:"197240",title:"Associate Prof.",name:"Tolga",surname:"Taner",slug:"tolga-taner",fullName:"Tolga Taner"}],corrections:null},{id:"58733",title:"Improving the Performance of PEM Fuel Cell",doi:"10.5772/intechopen.71928",slug:"improving-the-performance-of-pem-fuel-cell",totalDownloads:1129,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"In order to develop a novel proton exchange membrane fuel cell (PEMFC), new materials were investigated in order to increase the water uptake of the membrane known commercially as “Nafion” by casting it with zirconium metal organic frameworks (MOFs) (i.e., MOF 801 and 808) to form a composite using sol-gel method. It was found that the water uptake of the composite membrane (NAF-MOF) was increased in a significant way, and ion exchange capacity was improved in comparison with the commercial membrane at various temperatures. Actual runs using PEM fuel cell at 80°C and Naf-MOF (801 and 808) membranes were performed to assure the efficiency of using these membranes.",signatures:"Farqad Al-Hadeethi",downloadPdfUrl:"/chapter/pdf-download/58733",previewPdfUrl:"/chapter/pdf-preview/58733",authors:[{id:"210871",title:"Prof.",name:"Farqad",surname:"Al-Hadeethi",slug:"farqad-al-hadeethi",fullName:"Farqad Al-Hadeethi"}],corrections:null},{id:"57505",title:"Robotic Technologies for Proton Exchange Membrane Fuel Cell Assembly",doi:"10.5772/intechopen.71470",slug:"robotic-technologies-for-proton-exchange-membrane-fuel-cell-assembly",totalDownloads:1338,totalCrossrefCites:2,totalDimensionsCites:3,hasAltmetrics:0,abstract:"Proton exchange membrane fuel cell (PEMFC) stacks and their components are currently being manufactured using laboratory fabrication methods. While in recent years these methods have been scaled up in size, they do not incorporate high-volume manufacturing methods. In this context, manufacturing R&D is necessary to prepare advanced manufacturing and assembly technologies that are required for low-cost, high-volume fuel cell power plant production. U.S. Department of Energy (DOE) has identified high-priority manufacturing R&D needs for PEMFCs. Along with efforts to develop technologies for high-speed manufacturing of fuel cell components, DOE identified the need for demonstrating automated assembly processes for fuel cell stacks. The scope of this chapter is to review current manufacturing R&D efforts in the area of automated processes for assembling PEMFC stacks, to present the current state of development, successful demonstrations, related technological challenges and the technical solutions used to overcome them. An emphasis of this review is on the design of tools used for robotic grasping, handling and inserting fuel cell components in the stack and on the use of design for manufacture and assembly (DFMA) strategies that enable the automated assembly process.",signatures:"Vladimir Gurau, Devin Fowler and Daniel Cox",downloadPdfUrl:"/chapter/pdf-download/57505",previewPdfUrl:"/chapter/pdf-preview/57505",authors:[{id:"219399",title:"Dr.",name:"Vladimir",surname:"Gurau",slug:"vladimir-gurau",fullName:"Vladimir Gurau"},{id:"220252",title:"MSc.",name:"Devin",surname:"Fowler",slug:"devin-fowler",fullName:"Devin Fowler"},{id:"222195",title:"Prof.",name:"Daniel",surname:"Cox",slug:"daniel-cox",fullName:"Daniel Cox"}],corrections:null},{id:"57432",title:"Perspective Non-Fluorinated and Partially Fluorinated Polymers for Low-Temperature PEM FC",doi:"10.5772/intechopen.71250",slug:"perspective-non-fluorinated-and-partially-fluorinated-polymers-for-low-temperature-pem-fc",totalDownloads:1378,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The main requirement to the materials used to make membranes polymer electrolyte membrane fuel cells (PEM FC) is the combination of high proton conductivity and resistance to the FC operation conditions. Thus, the search for inexpensive and high-performance non-fluorinated or partially fluorinated materials for use as FC membranes is an actual task today, since the use of membranes based on perfluorosulfonate acid has a number of disadvantages limiting their application. The aim of this study is the investigation of sulfonated polyimide (SPI) and materials for use as FC membranes. The relevance of research stems from the fact that the use of the SPI will allow to increase the resistance of the membrane to the constantly changing environment in which PEM operates. The objects of research are sulfonated polyimides. SPIs, especially aromatic SPIs, are attractive to researchers, because of the possibility of obtaining a wide variety of chemical structures and also due to their excellent thermal, mechanical properties and high resistance to aggressive media. The results of this study will be methods of obtaining and evaluating the advantages and disadvantages of SPI-based materials. For the first time, special attention will be paid to advanced development based on SPI with the addition of crown-ether fragments.",signatures:"Vitaly Ivanov, Anton Yegorov, Alena Wozniak, Ol’ga Zhdanovich,\nMarina Bogdanovskaya and Elena Averina",downloadPdfUrl:"/chapter/pdf-download/57432",previewPdfUrl:"/chapter/pdf-preview/57432",authors:[{id:"211848",title:"Mr.",name:"Anton",surname:"Yegorov",slug:"anton-yegorov",fullName:"Anton Yegorov"},{id:"211885",title:"Mr.",name:"Vitaly",surname:"Ivanov",slug:"vitaly-ivanov",fullName:"Vitaly Ivanov"},{id:"211886",title:"Ms.",name:"Alena",surname:"Wozniak",slug:"alena-wozniak",fullName:"Alena Wozniak"},{id:"211887",title:"Dr.",name:"Olga",surname:"Zhdanovich",slug:"olga-zhdanovich",fullName:"Olga Zhdanovich"},{id:"211888",title:"Ms.",name:"Marina",surname:"Bogdanovskaya",slug:"marina-bogdanovskaya",fullName:"Marina Bogdanovskaya"},{id:"211889",title:"Ms.",name:"Elena",surname:"Averina",slug:"elena-averina",fullName:"Elena Averina"}],corrections:null},{id:"58665",title:"Degradation in PEM Fuel Cells and Mitigation Strategies Using System Design and Control",doi:"10.5772/intechopen.72208",slug:"degradation-in-pem-fuel-cells-and-mitigation-strategies-using-system-design-and-control",totalDownloads:1586,totalCrossrefCites:3,totalDimensionsCites:7,hasAltmetrics:1,abstract:"The rapid miniaturization of electronics, sensors, and actuators has reduced the cost of field sensor networks and enabled more functionality in ever smaller packages. Networks of field sensors have emerging applications in environmental monitoring, in disaster monitoring, security, and agriculture. Batteries limit potential applications due to their low specific energy. A promising alternative is photovoltaics. Photovoltaics require large, bulky panels and are impacted by daily and seasonal variation in solar insolation that requires coupling to a backup power source. Polymer electrolyte membrane (PEM) fuel cells are a promising alternative, because they are clean, quiet, and operate at high efficiencies. However, challenges remain in achieving long lives due to catalyst degradation and hydrogen storage. In this chapter, we present a design framework for high-energy fuel cell power supplies applied to field sensor networks. The aim is to achieve long operational lives by controlling degradation and utilizing high-energy density fuels such as lithium hydride to produce hydrogen. Lithium hydride in combination with fuel-cell wastewater or ambient humidity can achieve fuel specific energy of 5000 Wh/kg. The results of the study show that the PEM hybrid system fueled using lithium hydride offers a three- to fivefold reduction in mass compared to state-of-the-art batteries.",signatures:"Jekan Thangavelautham",downloadPdfUrl:"/chapter/pdf-download/58665",previewPdfUrl:"/chapter/pdf-preview/58665",authors:[{id:"210571",title:"Prof.",name:"Jekan",surname:"Thangavelautham",slug:"jekan-thangavelautham",fullName:"Jekan Thangavelautham"}],corrections:null},{id:"58423",title:"Chalcogenides and Carbon Nanostructures: Great Applications for PEM Fuel Cells",doi:"10.5772/intechopen.71994",slug:"chalcogenides-and-carbon-nanostructures-great-applications-for-pem-fuel-cells",totalDownloads:1016,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Nanostructured metal chalcogenides (NMCs) and carbon nanostructures (CNS) are attracting significant attention due to their features such as high stability in an acidic environment, especially if they have a significant oxygen reduction activity and remarkable superconducting properties. The broad range of CNS exhibits novel physicochemical properties, and thus it is triggering intense research about carbon nanoscience with numerous applications. In this context, new synthesis routes are designed under moderate conditions, which are definitely needed in order to simplify the process, reduce costs, and allow the production of NMCs at lower temperatures and CNS whose size and shape can be controlled. Some related studies about Pt based on sulfides and selenides, transition metal chalcogenides (TMCs), and carbon nanostructures (nanotubes and graphene) are revealed here; however, they show promise for fuel cells that these NMCs, CNS, or even NMC-CNS materials have been applied for other energy devices. Until now, a good response for cathodic reactions is employing TMCs based on tungsten and CNS without metal. According to experimental results and in terms of catalytic activity, durability, and chemical/electrochemical stability, much more research is required to produce commercially valid non-noble catalysts, electrocatalysts, or supports; however, one approach on this field is metal-free CNS.",signatures:"Yadira Gochi-Ponce, Gabriel Alonso-Núñez, Nicolás Alonso-Vante\nand Mercedes Teresita Oropeza-Guzmán",downloadPdfUrl:"/chapter/pdf-download/58423",previewPdfUrl:"/chapter/pdf-preview/58423",authors:[{id:"104665",title:"Dr.",name:"Gabriel",surname:"Alonso-Nuñez",slug:"gabriel-alonso-nunez",fullName:"Gabriel Alonso-Nuñez"},{id:"211953",title:"Dr.",name:"Yadira",surname:"Gochi Ponce",slug:"yadira-gochi-ponce",fullName:"Yadira Gochi Ponce"},{id:"213630",title:"Dr.",name:"N.",surname:"Alonso-Vante",slug:"n.-alonso-vante",fullName:"N. Alonso-Vante"}],corrections:null},{id:"57938",title:"Fundamentals of Electrochemistry with Application to Direct Alcohol Fuel Cell Modeling",doi:"10.5772/intechopen.71635",slug:"fundamentals-of-electrochemistry-with-application-to-direct-alcohol-fuel-cell-modeling",totalDownloads:1349,totalCrossrefCites:1,totalDimensionsCites:6,hasAltmetrics:0,abstract:"Fuel cell modeling is an inherently multiphysics problem. As a result, scientists and engineers trained in different areas are required to work together in this field to address the complex physicochemical phenomena involved in the design and optimization of fuel cell systems. This multidisciplinary approach forces researchers to become accustomed to new concepts. Electrochemical processes, for example, constitute the heart of a fuel cell. Accurate modeling of electrochemical reactions is therefore essential to successfully predict the performance of these devices. However, becoming familiar with the complex concepts of electrochemistry can be an arduous task for those who approach the study of fuel cells from fields other than chemical engineering. This process can extend over time and requires careful reading of many textbooks and papers, the most illuminating ones being hidden to the newcomer in a plethora of recent publications on the subject. The authors, who engaged in the study of fuel cells coming from the field of mechanical engineering, had to travel this road once and, with this contribution, would like to make the journey easier for those who come behind. As an illustrative example, the thermodynamic and electrochemical principles reviewed in this chapter are applied to a complex electrochemical system, the direct ethanol fuel cell (DEFC), reviewing recent work on this problem and suggesting future research directions.",signatures:"Juan Sánchez-Monreal, Marcos Vera and Pablo A. García-Salaberri",downloadPdfUrl:"/chapter/pdf-download/57938",previewPdfUrl:"/chapter/pdf-preview/57938",authors:[{id:"176049",title:"Dr.",name:"Marcos",surname:"Vera",slug:"marcos-vera",fullName:"Marcos Vera"},{id:"213212",title:"Dr.",name:"Juan",surname:"Sánchez-Monreal",slug:"juan-sanchez-monreal",fullName:"Juan Sánchez-Monreal"},{id:"213213",title:"Dr.",name:"Pablo A.",surname:"García-Salaberri",slug:"pablo-a.-garcia-salaberri",fullName:"Pablo A. García-Salaberri"}],corrections:null},{id:"58686",title:"PEM-Less Microbial Fuel Cells",doi:"10.5772/intechopen.71479",slug:"pem-less-microbial-fuel-cells",totalDownloads:1401,totalCrossrefCites:1,totalDimensionsCites:3,hasAltmetrics:0,abstract:"Microbial fuel cells (MFCs) are comparatively new technique of simultaneously generating electricity from bio-waste while degrading the organic waste. The use of microbes to generate electricity is an uninterrupted process in MFCs since the bacteria replicate and continue to produce power indefinitely as long as there is enough food source to nurture the bacteria. Besides, MFCs have the potential to produce hydrogen for fuel cells, desalinate sea water, and provide sustainable energy sources for remote areas. Factors like type of electrodes used in the cells, partitioning of cells, oxygen complement and configurations are important factors that affect the performance of MFCs. The fabrication of microbial fuel cells of different configurations and the relationship between the factors affecting the efficiency of single chambered (SC-MFCs) and double chambered (DC-MFCs) will be presented. The experimental data on observations made on the effects of these materials on the MFCs characteristics, electricity generation and wastewater treatment have also been included. The main aim of this study is to find out whether a nonconventional inexpensive clay could be used as an ion-exchange medium alternative to the conventional expensive PEM in the fabrication of MFCs. The results obtained on power generation, current density, open circuit voltage, etc., clearly show that PEM-less MFCs can be used as practical devices for sustainable energy generation.",signatures:"Reuben Y. Tamakloe",downloadPdfUrl:"/chapter/pdf-download/58686",previewPdfUrl:"/chapter/pdf-preview/58686",authors:[{id:"211009",title:"Dr.",name:"Reuben",surname:"Tamakloe",slug:"reuben-tamakloe",fullName:"Reuben Tamakloe"}],corrections:null},{id:"57392",title:"Advanced Supporting Materials for Polymer Electrolyte Membrane Fuel Cells",doi:"10.5772/intechopen.71314",slug:"advanced-supporting-materials-for-polymer-electrolyte-membrane-fuel-cells",totalDownloads:1636,totalCrossrefCites:0,totalDimensionsCites:2,hasAltmetrics:1,abstract:"Among the various kinds of fuel cell, polymer electrolyte membrane fuel cell (PEMFC) is the most prominent energy conversion device for portable applications. The catalyst-supporting materials provide active triple phase boundary for electrochemical reactions where the reactant molecules can easily interact with the catalyst surface. Catalysts play a vital role for improving the overall efficiency of the fuel cells through the advancement in the catalyst and their supporting materials for cathodic oxygen reduction reaction (ORR) in PEMFCs. The supporting materials mainly contribute to increase the electrocatalytic activity of the catalysts by providing more active surface area and extended life-time. The major roles of supporting materials are (i) they act as electron source with improved conductivity; (ii) they hold the metal nanoparticles; (iii) they possess higher surface area and (iv) they should have better stability under operating conditions. In this chapter, the various supporting materials were reviewed carefully based on their nature and performance toward the electrochemical reduction of oxygen for PEMFCs. They are classified into three major categories as (i) carbon supports; (ii) carbon-free supports, and (iii) polymer nanocomposites. In summary, the overall view on support materials and their role on electrocatalysis for fuel cell reactions is provided.",signatures:"Narayanamoorthy Bhuvanendran",downloadPdfUrl:"/chapter/pdf-download/57392",previewPdfUrl:"/chapter/pdf-preview/57392",authors:[{id:"210500",title:"Dr.",name:"Narayanamoorthy",surname:"Bhuvanendran",slug:"narayanamoorthy-bhuvanendran",fullName:"Narayanamoorthy Bhuvanendran"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"6469",title:"Application of Exergy",subtitle:null,isOpenForSubmission:!1,hash:"0836749bb350a373d5e2628c73539698",slug:"application-of-exergy",bookSignature:"Tolga Taner",coverURL:"https://cdn.intechopen.com/books/images_new/6469.jpg",editedByType:"Edited by",editors:[{id:"197240",title:"Associate Prof.",name:"Tolga",surname:"Taner",slug:"tolga-taner",fullName:"Tolga Taner"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9385",title:"Renewable Energy",subtitle:"Technologies and Applications",isOpenForSubmission:!1,hash:"a6b446d19166f17f313008e6c056f3d8",slug:"renewable-energy-technologies-and-applications",bookSignature:"Tolga Taner, Archana Tiwari and Taha Selim Ustun",coverURL:"https://cdn.intechopen.com/books/images_new/9385.jpg",editedByType:"Edited by",editors:[{id:"197240",title:"Associate Prof.",name:"Tolga",surname:"Taner",slug:"tolga-taner",fullName:"Tolga Taner"}],equalEditorOne:{id:"186791",title:"Dr.",name:"Archana",middleName:null,surname:"Tiwari",slug:"archana-tiwari",fullName:"Archana Tiwari",profilePictureURL:"https://mts.intechopen.com/storage/users/186791/images/system/186791.jpg",biography:"Dr. Archana Tiwari is Associate Professor at Amity University, India. Her research interests include renewable sources of energy from microalgae and further utilizing the residual biomass for the generation of value-added products, bioremediation through microalgae and microbial consortium, antioxidative enzymes and stress, and nutraceuticals from microalgae. She has been working on algal biotechnology for the last two decades. She has published her research in many international journals and has authored many books and chapters with renowned publishing houses. She has also delivered talks as an invited speaker at many national and international conferences. 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Thermo-TDR Sensors for Soil Physical Measurements",doi:"10.5772/intechopen.100285",slug:"applications-of-thermo-tdr-sensors-for-soil-physical-measurements",body:'Dynamic, in situ measurements of soil temperature (
In this chapter, the theories, methodologies and applications of the thermo-TDR technique are presented.
The heat pulse technique can measure soil volumetric heat capacity (
Thermo-TDR technique estimates soil thermal properties from the temperature change-by-time data at the sensing probes (heat pulse signals) based on line-source heat transfer models. The most widely known model is based on the infinite line source (ILS) theory considering an instantaneous or pulsed heating scheme, which assumes the heating probe as a line heat source with zero diameter and infinite length [9, 14, 15, 16]. For an isothermal and homogeneous soil with a uniform initial temperature distribution, the solution of the Fourier radial equation for heat conduction of a short-duration heat-pulse away from an infinite line source was developed by [17] further analyzed by [15, 16]. The temperature distributions in a cylindrical system are as follows:
where.
in which
where
Ignoring the finite heat pulse probe properties (finite radius and finite heat capacity) can be a significant source of error when estimating soil thermal properties with the ILS theory, especially when there is a large contrast between the physical properties of probes and soil [18, 19]. Peng et al. [8] showed that finite probe effects on temperature rise with time curves were most significant in dry soils, and faded with increasing θ; the ILS theory can cause about 6% relative error in dry soil thermal property estimates [20]. Knight et al. proposed a semi-analytical solution of the cylindrical perfect conductors (CPC) theory, accounting for the finite probe radius and finite probe heat capacity [18]. The CPC theory was successfully applied in various studies [19, 21, 22]. This is especially true for the large sensor designs, in which the CPC theory reduces the error due to the finite probe effects. The theories and applications of CPC theory can be found in [20].
Figure 1 shows typical heat pulse signals (temperature change-by-time data) in two sensing probes of a thermo-TDR measurement on a loamy sand soil with water content of 0.15 m3 m−3. Generally, soil temperature starts to increase when the heat pulse is initiated and then decreases with time after the heat pulse ceases. The heating rate
The temperature change-by-time data (circles) measured by two sensing probes with the large thermo-TDR sensor on a loamy sand soil. The lines represent the nonlinear curve fitting results for the CPC solution to the measured data. The heating duration (t0) and the heating power (q) are listed.
Soil θ and σ measurements are determined from the TDR waveforms obtained with the reflectometer device. Figure 2 presents a typical TDR waveform generated with the TDR200 device (Campbell Scientific Inc., Logan, UT). The TDR technique determines
A TDR waveform from the thermo-TDR sensor immersed in distilled water. v0 is the amplitude of the incident voltage waveform generated by cable tester, and v∞ is final voltage amplitude in the transmission line after all multiple reflections have ceased. Part of the waveform framed in gray is used for water content calculation. L1 and L2 are the first and second reflection points on a TDR waveform (from [
where
Typically,
The magnitude of soil σ depends on the transmission line impedance
where
where
Following Heimovaara et al.
where
in which
The design of the thermo-TDR sensor must meet several criteria to achieve the requirements of line-source heat-pulse theory to measure soil thermal properties and TDR principles to derive soil water content and electrical conductivity [1, 22]. The key parameters are probe diameter (
Various configurations have been proposed for the thermo-TDR sensor. The original sensor design consisted of three parallel probes with 40-mm length, 1.3-mm diameter, and 6-mm probe-to-probe spacing [1] (Figure 3). The middle probe acted as a heater that introduced a heat pulse into soil, while the two outer needles acted as the sensing probes that measured the soil temperature at a known distance (e.g., ∼6 mm) from the heating probe.
Schematic view of the thermo-TDR sensor configuration in [
Newer versions of thermo-TDR sensor designs, with various probe sizes and configurations (i.e.,
The small sensing volume of the Ren et al. sensor design made it suitable for fine-scale measurements, but the short probes somewhat restricted the accuracy of TDR measurements [1, 38]. Recently Peng et al. introduced a large-size thermo-TDR with a probe length of 70 mm, and a probe-to-probe spacing of 10-mm, a diameter of 2.38 mm for the heater probe, and a diameter of 2 mm for the sensing probe (Figure 4) [22]. As a result, this sensing volume was three times larger than that of the Ren et al. [1] sensor, and greater accuracy was achieved with TDR θ measurement accuracy due to the reduction of the superimposed reflections. Peng et al. also integrated updated algorithms to determine soil thermal and dielectric properties in order to produce accurate θ, ρb and porosity values [22].
Schematic view of the thermo-TDR sensor configuration from [
Thermo-TDR sensors are not readily commercially available. One may be able to make special order sensors from some companies, but in most cases the sensors are constructed in soil physics research laboratories. As shown in Figure 3, a thermo-TDR sensor usually consists of three probes that house the heating wire and temperature sensors (thermocouples or thermistors), an epoxy base that fixes the probes in place, extension wires for the heater and temperature sensors, and a coaxial cable for TDR measurement. The stainless-steel tubes that serve as housings for heating and sensing probes, can be custom made or produced from hypodermic needles with the specified diameter and length.
The heating probe is constructed by threading an enameled resistance heater wire (e.g., 38-gauge Nichrome 80 Alley), through the heating needle two or four times for a total resistance of about 888 Ω m−1. The sensing probes are typically constructed by positioning a thermocouple or a thermistor enclosed at the midpoint of each probe (Figure 3). More than one thermocouple (Type E, chromel-constantan, 40 American wire gauge [AWG]) can be also used to detect soil temperatures at several locations along the probe to enable in situ corrections of
For TDR measurements, a 75-Ω coaxial cable is connected to the sensor by soldering the inner conductor to the central probe and the shield to the outer probes. The thermocouple wires are extended by connecting them to longer extension wires of the same type (e.g., Type E, chromel-constantan, 36 American wire gauge [AWG]). The extension thermocouple and resistance wires are kept within 5 m to avoid signal losses in long wires. Finally, the three probes and wires are kept in place with a mold and casting resin.
Table 1 lists the key materials and specifications used in [1, 22] for making the thermo-TDR sensors.
Materials | Specifications |
---|---|
Thermocouple | Type E, chromel-constantan, 40 AWG, OMEGA Engineering, CT |
Thermocouple extension wire | Type E, chromel-constantan, 36 AWG, OMEGA Engineering, CT |
Thermistor | Model 10K3MCD1, 0.46-mm diam., 10 kΩ at 25°C; Betatherm Corp., Shrewsbury, MA |
Resistance wire | 79-μm diameter, 40 AWG, enameled, 205 Ω m−1, Nichrome 80 Alloy, Pelican Wire Co., Naples, FL |
Stainless-steel tube | Ren et al. : 1.27-mm o.d. and 0.84-mm i.d for both heating and sensing probes [1]. Peng et al. : 2.38-mm o.d., 0.71-mm wall thickness for heating probe, 2.00-mm o.d., 0.25-mm wall thickness for sensing probes [22]. |
Coaxial cable | 75 Ω coaxial cable, RG 187 A/U, Newark Electronics |
Epoxy inside probes | High thermal conductivity, Omegabond 101, Omega Engineering, Stamford, CT |
Casting resin for sensor body | Water proof, Cr600 Casting Resin, Micro-Mark, Berkeley Heights, NJ |
Materials used for making thermo-TDR sensors.
The operation of a thermo-TDR sensor requires a setup to generate the heat pulses, a TDR device that generates a fast-rise-time electromagnetic pulse, samples and digitizes the resulting reflection waveform, and data acquisition and control systems (Figure 3). For the TDR part, a coaxial cable tester (e.g., model 1502B, Tektronix Inc., Beaverton, OR) or a TDR200 reflectometer system (Campbell Scientific Inc., Logan, UT) generates the reflection waveform for analysis or storage. Simultaneous and automatic collection of multiple TDR measurements can be achieved with compatible multiplexers connected to a datalogger (e.g., model CR1000x or CR3000, Campbell Scientific Inc., Logan, UT) that retrieves TDR waveforms or dielectric constants for further analysis of θ or σ.
The experiment setup commonly used for a heat pulse measurement, which consists of a datalogger, a circuit, and a DC power (Figure 5). The circuit consists of a relay and a 1-Ω precision resistor, which is controlled by the datalogger. A DC power supply or a 12-volt battery applies a constant current for a fixed time to the heater wires to generate the heat pulse. The extension wires of thermocouples/thermistors are connected to a datalogger for temperature measurements. A switch to control the heat pulse is through a relay embedded in the circuit that can be activated by the datalogger. The resistance wire is heated for a controlled amount of time (typically 8–20 s for small sensors and 15–30 s for large sensors). During the heat pulse process, the current in the heater wire is determined automatically by measuring the voltage drop across a 1-Ω precision resistor which is in series with the heater wire.
Experiment setup for a typical thermo-TDR measurement.
Once the measurement is initiated, the current in the resistance wire and soil temperatures of the sensing probes are recorded at a 1-s interval for about 100–300 s with a datalogger (e.g., model CR1000x or CR3000, Campbell Scientific Inc., Logan, UT). The total measurement time can be set to be longer than 300 s, especially when the background soil temperature varies significantly with time under the field conditions. In this case, a linear temperature correction procedure is needed for the soil thermal property calculations [39, 40]. The heating intensity should be carefully controlled to achieve a clear heat pulse signals at the sensing probe and to avoid potential heat induced moisture redistributions at the same time. Normally, the heat pulse duration is set to make sure that the temperature changes at the sensing probes typically fall in the range of 0.5–1.0°C.
The thermo-TDR sensor can be placed horizontally or vertically in a soil profile, depending on the application objectives. Special care is required to avoid needle deflection and to keep good soil-probe contact during installation. It is recommended to install the sensor under moist conditions when probe deflection is less likely to occur [2].
Accurate information about parameters
Wen et al. designed a probe-spacing-correction thermo-TDR sensor with 6-cm long sensing probe, each enclosed with three thermistors at different distances away from the sensor base [36]. This enabled the calculation of probe deflection angles to estimate actual in situ
For
where
For TDR-σ measurements with the thermo-TDR sensor,
The thermo-TDR technique permits routine measurements of soil thermal properties, water content and electrical conductivity on repacked soil columns and in situ field measurements. Figure 6 presents the results of soil thermal properties on a repacked sand soil, showing typical trends of
Thermo-TDR determined thermal properties of a sand at bulk density of 1.47 Mg m−3 as a function of water content.
Figure 7 shows measured apparent σ values for sand wetted by various salt solution concentrations to θ ranging from 0.08 to 0.25 m3 m−3. It is clear that the increases in salt concentrations lead to significant increases in σ, and σ also increases with θ. Soluble salt ions in soil solution can enhance the electric conductivity of bulk soil. For salt affected soils, the Peng et al. [8] thermo-TDR sensor can measure σ values as large as 22.5 dS m−1. Thus, important observations of solute, heat and water properties in soil are possible with thermo-TDR sensors.
Thermo-TDR measured bulk electrical conductivity of a sand soil as a function of KCl salt concentrations used to wet the soil to four selected water contents.
The thermo-TDR technique soil thermal property and water content data can be used to estimate soil structure changes [43, 48, 49]. The thermo-TDR technique can be applied to determine in situ ρb,
Thermo-TDR determinations of ρb depend on the de Vries
From Eq. (11), ρb is derived as,
where cs is the specific heat of soil solids (kJ kg−1 K−1), ρw is the density of water (1.0 g cm−3), and cw is the specific heat of water (4.18 kJ kg−1 K−1) [9]. Once soil
Because λ measurements using the heat pulse technique are not influenced by needle deflection, Lu et al. proposed the λ-based thermo-TDR method to determine in situ ρb [54]. An empirical equation that related λ to ρb, θ, and soil texture was used [50],
where
where
An iterative approach is used to numerically solve for ρb because there is no explicit solution for ρb from Eqs. (13)–(15). The nonlinear equation solver (
The empirical Lu et al. λ model introduced uncertainty in ρb estimates, especially for coarse soils [50]. Thus, Tian et al. proposed a simplified version of the physically-based de Vries λ model to inversely estimate ρb, and they found that their λ model performed better than the
Both
It is commonly recognized that a tilled soil layer undergoes great structural changes due to agricultural management and rainfall effects. The in situ measurements of ρb in tilled soil layers using a thermo-TDR technique indicated that soil ρb increased following tillage because rainfalls caused soil particles to settle and consolidate [48, 49]. Figure 8 shows that soil ρb increased and then leveled off, and the thermo-TDR method determined ρb values mostly matched the core sample values.
Dynamic thermo-TDR measured bulk density (ρb) values for two soil layers plotted along with independent ρb values from soil core measurements. Both error bars and gray areas represent standard errors of the measurements (figure originally published in [
With the thermo-TDR determined θ and ρb, soil
Thus, the
Fu et al. [56] showed that when applying the thermo-TDR technique in cropped soil, the influences of roots should be considered by using an extended mixing model based on Eq. (11),
where
For a bulk soil sample with a volume of
where
where
where θtotal is defined as the sum of volumetric θ values of root and soil. Fu et al. report that when the maize root density is greater than 0.037 g cm−3, Eqs. (21, 22) should be used to estimate ρb from thermo-TDR measured
Comparison of thermo-TDR soil bulk density (ρb) estimates from the original approach (
Although in-situ determination of soil ice content during freezing and thawing is challenging, a thermo-TDR technique has been developed to measure soil liquid water and ice contents in partially frozen soils. Tian et al. report that thermo-TDR determined heat capacity and liquid water content in partially frozen soil can be used to determine soil ice content [4]. According to [45], the volumetric heat capacity of a partially frozen soil can be expressed as,
where
Tian et al. reported that the heating strength of heat pulse measurements should be carefully controlled for measurements in partially frozen soil to minimize ice melting during the process [4]. Their results indicated that the heat pulse method failed to provide accurate thermal properties at soil temperatures between −5 and 0°C because of temperature field disturbances from latent heat of fusion. The optimized heating application strategy was found to be a 60-s heat duration (450 J m−1) or a 90-s heat duration (450–900 J m−1), and the
Soil temperature dynamics, thermo-TDR measured ice contents (from Eq. (30)), and TDR evaluated ice contents (θt-θu) during freezing and thawing for soil samples with a water content of 0.15 m3 m−3 on sandy loam, silt loam and silty clay loam soils. Dashed lines indicate ±0.05 m3 m−3 error. (figure originally published in [
Tian et al. reported that the
For soils experiencing seasonal or diurnal freezing and thawing cycles, Kojima et al. proposed an approach with TDR-θ determinations made before and after an imposed ice melting process caused by heating the soil surrounding the sensor [7]. The θi value was equivalent to the difference between the two TDR-θ values, which represented the liquid water content and total water content in the soil. Their method only relied on the two TDR-θ values but required long measurement intervals and a relatively large heat input to melt the ice.
The thermo-TDR method is a useful tool that can be used in laboratory and field experiments to study transient in-situ properties and processes related to coupled heat and water transfer in soil. Heitman et al. used thermo-TDR sensors in a closed soil cell with imposed transient boundary conditions to obtain non-uniform temperature, water and thermal property distributions [3]. Thermo-TDR sensors were used to obtain soil thermal conductivity during wetting and drying processes on quartz sands for geothermal applications [59, 60, 61, 62].
Significant improvements in both sensor configurations and theories have been made in fine-scale measurements of coupled water and heat transfer process in soil under field conditions, especially in near surface soils [63]. Based solely on the heat pulse function of the thermo-TDR sensor, the use of a series of such sensors aligned in a soil profile permitted the determination of soil heat fluxes, liquid water fluxes, and soil-water evaporation fluxes [64].
Based on Fourier’s law, the one-dimensional heat flux density (
A heat pulse technique based on the sensible heat balance of near-surface soil layers was able to determine in situ soil water evaporation (
An analytical solution that related soil water flux density (
Figure 11 presents a flowchart of the uses and outcomes for the thermo-TDR method. Generally, the thermo-TDR determined state variables and physical parameters can be estimated with proper models and methods. The most promising aspect of the thermo-TDR technique is the capability to determine in situ bulk density, porosity, heat flux, water flux and vapor flux. These provide opportunities to study transient heat and water processes in field soils, including water evaporation, sensible and latent heat, and liquid water fluxes [64, 68, 69, 82].
The schematic view of thermo-TDR sensor measurement for state variables and parameters. (figure originally published in [
This chapter includes descriptions of thermo-TDR sensors, methods for collecting and analyzing data, and reviews of current and potential thermo-TDR applications. The thermo-TDR sensor, which combines a heat pulse probe with a time domain reflectometry probe for soil thermal and electrical properties determinations, provides new opportunities for improved soil measurements on thermal properties, water content, bulk electrical conductivity, ice content, bulk density, air-filled porosity, heat flux, water flux, and vapor flux. The thermo-TDR technique has the potential to monitor in situ soil physical properties and processes for vadose zone soils.
This work was funded by the National Natural Science Foundation of China (41977011 and 41671223), the U.S. National Science Foundation (2037504) and USDA-NIFA Multi-State Project 4188.
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Costa"}]}],onlineFirstChaptersFilter:{topicId:"63",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"81262",title:"The Innovative Business Model for Family-Owned Firms in the Era of Digital Entrepreneurship: Evidence from Emerging Economy",slug:"the-innovative-business-model-for-family-owned-firms-in-the-era-of-digital-entrepreneurship-evidence",totalDownloads:36,totalDimensionsCites:0,doi:"10.5772/intechopen.102459",abstract:"The current Covid-19 pandemic has been changed the businesses plans. High uncertainty can compel the organization to change the business plan according to the market demand. In the current era of digitalization, organizations are needed to modify the existing business plan and innovate it through technologies. Modifying existing resources according to the market demand is challenging for the organization; employers face many challenges and obstacles. 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These results show that the Cameroonian authorities must intensify measures in favor of the formalization of enterprises to boost the potential for innovation within enterprises.",book:{id:"11258",title:"Innovation, Research and Development and Capital Evaluation",coverURL:"https://cdn.intechopen.com/books/images_new/11258.jpg"},signatures:"Martin Ndzana and Gregory Mvogo"},{id:"80595",title:"The “Lateral Transshipment” is a Cooperative Tool for Optimizing the Profitability of a Distribution System",slug:"the-lateral-transshipment-is-a-cooperative-tool-for-optimizing-the-profitability-of-a-distribution-s",totalDownloads:37,totalDimensionsCites:0,doi:"10.5772/intechopen.101992",abstract:"In this chapter, we discuss a network consisting of a distribution center (or central depot) and two retailers who serve customers. D1 andD2 represent, respectively, the demands of retailer 1 and 2. We assume that the demandDi (i = 1, 2) at retailer i follows a normal distribution with mean μi and standard deviationσi (known). This analysis makes it possible to assess the effect of emergency transshipment both at the level of the Average Global Profit and of the Average Global Desservice Rate. In this chapter, we consider a centralized one-echelon supply chain with two-retailers selling products and facing stochastic demand.",book:{id:"11258",title:"Innovation, Research and Development and Capital Evaluation",coverURL:"https://cdn.intechopen.com/books/images_new/11258.jpg"},signatures:"Elleuch Fadoi"},{id:"80382",title:"Innovation and Entrepreneurial Ecosystems",slug:"innovation-and-entrepreneurial-ecosystems",totalDownloads:107,totalDimensionsCites:0,doi:"10.5772/intechopen.102344",abstract:"Nowadays special attention is paid to ecosystem conditions that encourage innovation and entrepreneurship. This chapter provides a critical review and expands the understanding of the concepts of the innovation ecosystem and entrepreneurial ecosystem. The entrepreneurial ecosystem represents a collection of actors that interact within a geographically bound entrepreneurial environment and factors, which contribute to the development of productive entrepreneurship. Innovation ecosystems represent communities of interacting actors that support innovation processes and create technologies and innovations. The focus of the innovation ecosystem is on value creation through the creation of innovations, while the focus of the entrepreneurship ecosystem is on the development of entrepreneurship. There are differences between the two concepts, but also the relationships and interactions, which are revealed in the chapter. 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A variety of businesses may appear within a firm, in which case the value change rates must be integrated. An example is provided of a real estate firm benefiting from the growth of multiannual plants of varying age. It is found that the application of a duration-dependent reference capital return rate increases the value increment rate of juvenile stands and decreases that of mature stands, however increasing the valuation result of both.",book:{id:"11258",title:"Innovation, Research and Development and Capital Evaluation",coverURL:"https://cdn.intechopen.com/books/images_new/11258.jpg"},signatures:"Petri P. 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After almost 32 years of teaching at the University of Trás-os-Montes and Alto Douro, she recently moved to the University of Évora, Department of Veterinary Medicine, where she teaches in the field of Animal Reproduction and Clinics. Her primary research areas include the molecular markers of the endometrial cycle and the embryo–maternal interaction, including oxidative stress and the reproductive physiology and disorders of sexual development, besides the molecular determinants of male and female fertility. She often supervises students preparing their master's or doctoral theses. 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He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. 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He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. His research interests include Activity Fusion & Reasoning, Machine Learning, Context-aware Middleware, Human-Computer Interaction, etc.",institutionString:null,institution:{name:"Daegu Gyeongbuk Institute of Science and Technology",country:{name:"Korea, South"}}},{id:"262719",title:"Dr.",name:"Esma",middleName:null,surname:"Ergüner Özkoç",slug:"esma-erguner-ozkoc",fullName:"Esma Ergüner Özkoç",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Başkent University",country:{name:"Turkey"}}},{id:"346530",title:"Dr.",name:"Ibrahim",middleName:null,surname:"Kaya",slug:"ibrahim-kaya",fullName:"Ibrahim Kaya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}},{id:"351158",title:"Prof.",name:"David W.",middleName:null,surname:"Anderson",slug:"david-w.-anderson",fullName:"David W. 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A dynamic career research platform which is based on the thematic areas of comparative vertebrate physiology, stress endocrinology, reproductive endocrinology, animal health and welfare, and conservation biology. \nEdward has supervised 40 research students and published over 60 peer reviewed research.",institutionString:null,institution:{name:"University of Queensland",institutionURL:null,country:{name:"Australia"}}},editorTwo:null,editorThree:null,series:{id:"13",title:"Veterinary Medicine and Science",doi:"10.5772/intechopen.73681",issn:"2632-0517"},editorialBoard:[{id:"258334",title:"Dr.",name:"Carlos Eduardo",middleName:null,surname:"Fonseca-Alves",slug:"carlos-eduardo-fonseca-alves",fullName:"Carlos Eduardo Fonseca-Alves",profilePictureURL:"https://mts.intechopen.com/storage/users/258334/images/system/258334.jpg",institutionString:null,institution:{name:"Universidade Paulista",institutionURL:null,country:{name:"Brazil"}}},{id:"191123",title:"Dr.",name:"Juan José",middleName:null,surname:"Valdez-Alarcón",slug:"juan-jose-valdez-alarcon",fullName:"Juan José Valdez-Alarcón",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBfcQAG/Profile_Picture_1631354558068",institutionString:"Universidad Michoacana de San Nicolás de Hidalgo",institution:{name:"Universidad Michoacana de San Nicolás de Hidalgo",institutionURL:null,country:{name:"Mexico"}}},{id:"161556",title:"Dr.",name:"Maria Dos Anjos",middleName:null,surname:"Pires",slug:"maria-dos-anjos-pires",fullName:"Maria Dos Anjos Pires",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS8q2QAC/Profile_Picture_1633432838418",institutionString:null,institution:{name:"University of Trás-os-Montes and Alto Douro",institutionURL:null,country:{name:"Portugal"}}},{id:"209839",title:"Dr.",name:"Marina",middleName:null,surname:"Spinu",slug:"marina-spinu",fullName:"Marina Spinu",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRLXpQAO/Profile_Picture_1630044895475",institutionString:null,institution:{name:"University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca",institutionURL:null,country:{name:"Romania"}}},{id:"92185",title:"Dr.",name:"Sara",middleName:null,surname:"Savic",slug:"sara-savic",fullName:"Sara Savic",profilePictureURL:"https://mts.intechopen.com/storage/users/92185/images/system/92185.jfif",institutionString:'Scientific Veterinary Institute "Novi Sad"',institution:{name:'Scientific Veterinary Institute "Novi Sad"',institutionURL:null,country:{name:"Serbia"}}}]},onlineFirstChapters:{paginationCount:8,paginationItems:[{id:"81791",title:"Self-Supervised Contrastive Representation Learning in Computer Vision",doi:"10.5772/intechopen.104785",signatures:"Yalin Bastanlar and Semih Orhan",slug:"self-supervised-contrastive-representation-learning-in-computer-vision",totalDownloads:12,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"79345",title:"Application of Jump Diffusion Models in Insurance Claim Estimation",doi:"10.5772/intechopen.99853",signatures:"Leonard Mushunje, Chiedza Elvina Mashiri, Edina Chandiwana and Maxwell Mashasha",slug:"application-of-jump-diffusion-models-in-insurance-claim-estimation-1",totalDownloads:2,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Data Clustering",coverURL:"https://cdn.intechopen.com/books/images_new/10820.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"81471",title:"Semantic Map: Bringing Together Groups and Discourses",doi:"10.5772/intechopen.103818",signatures:"Theodore Chadjipadelis and Georgia Panagiotidou",slug:"semantic-map-bringing-together-groups-and-discourses",totalDownloads:12,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Data Clustering",coverURL:"https://cdn.intechopen.com/books/images_new/10820.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"79491",title:"Fuzzy Perceptron Learning for Non-Linearly Separable Patterns",doi:"10.5772/intechopen.101312",signatures:"Raja Kishor Duggirala",slug:"fuzzy-perceptron-learning-for-non-linearly-separable-patterns",totalDownloads:14,totalCrossrefCites:0,totalDimensionsCites:0,authors:[{name:"Raja Kishor",surname:"Duggirala"}],book:{title:"Data Clustering",coverURL:"https://cdn.intechopen.com/books/images_new/10820.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"81331",title:"Machine Learning Algorithm-Based Contraceptive Practice among Ever-Married Women in Bangladesh: A Hierarchical Machine Learning Classification Approach",doi:"10.5772/intechopen.103187",signatures:"Iqramul Haq, Md. 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