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Collins",authors:[{id:"47952",title:"Dr.",name:"Amaya",middleName:null,surname:"Azqueta",fullName:"Amaya Azqueta",slug:"amaya-azqueta"},{id:"57813",title:"Dr.",name:"Sergey",middleName:null,surname:"Shaposhnikov",fullName:"Sergey Shaposhnikov",slug:"sergey-shaposhnikov"},{id:"57814",title:"Prof.",name:"Andrew R",middleName:null,surname:"Collins",fullName:"Andrew R Collins",slug:"andrew-r-collins"}]}]}],publishedBooks:[{type:"book",id:"7204",title:"Gene Expression and Regulation in Mammalian Cells",subtitle:"Transcription Toward the Establishment of Novel Therapeutics",isOpenForSubmission:!1,hash:"10030057b2e2dee7d800ff27658c3a69",slug:"gene-expression-and-regulation-in-mammalian-cells-transcription-toward-the-establishment-of-novel-therapeutics",bookSignature:"Fumiaki Uchiumi",coverURL:"https://cdn.intechopen.com/books/images_new/7204.jpg",editedByType:"Edited by",editors:[{id:"47235",title:"Dr.",name:"Fumiaki",surname:"Uchiumi",slug:"fumiaki-uchiumi",fullName:"Fumiaki Uchiumi"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"267",title:"DNA Replication",subtitle:"Current Advances",isOpenForSubmission:!1,hash:"7098366ef9c3671e3699a9528f8a310c",slug:"dna-replication-current-advances",bookSignature:"Herve Seligmann",coverURL:"https://cdn.intechopen.com/books/images_new/267.jpg",editedByType:"Edited by",editors:[{id:"118814",title:"Dr.",name:"Herve",surname:"Seligmann",slug:"herve-seligmann",fullName:"Herve Seligmann"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"309",title:"RNA Processing",subtitle:null,isOpenForSubmission:!1,hash:"2a9bd91e201c38a107495de18f8883b0",slug:"rna-processing",bookSignature:"Paula Grabowski",coverURL:"https://cdn.intechopen.com/books/images_new/309.jpg",editedByType:"Edited by",editors:[{id:"62212",title:"Prof.",name:"Paula",surname:"Grabowski",slug:"paula-grabowski",fullName:"Paula Grabowski"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"342",title:"Genetic Transformation",subtitle:null,isOpenForSubmission:!1,hash:"458f41f1953f32c1ada346898c78b031",slug:"genetic-transformation",bookSignature:"María Alvarez",coverURL:"https://cdn.intechopen.com/books/images_new/342.jpg",editedByType:"Edited by",editors:[{id:"62781",title:"Prof.",name:"María",surname:"Alvarez",slug:"maria-alvarez",fullName:"María Alvarez"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"346",title:"DNA Repair",subtitle:"On the Pathways to Fixing DNA Damage and Errors",isOpenForSubmission:!1,hash:"962f1357bb182c3d5e01b7cac964f529",slug:"dna-repair-on-the-pathways-to-fixing-dna-damage-and-errors",bookSignature:"Francesca Storici",coverURL:"https://cdn.intechopen.com/books/images_new/346.jpg",editedByType:"Edited by",editors:[{id:"40385",title:"Dr.",name:"Francesca",surname:"Storici",slug:"francesca-storici",fullName:"Francesca Storici"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],publishedBooksByAuthor:[{type:"book",id:"1967",title:"Molecular Interactions",subtitle:null,isOpenForSubmission:!1,hash:"522b62bf32423a57eeceb0bf150e5a66",slug:"molecular-interactions",bookSignature:"Aurelia Meghea",coverURL:"https://cdn.intechopen.com/books/images_new/1967.jpg",editedByType:"Edited by",editors:[{id:"104880",title:"Prof.",name:"Aurelia",surname:"Meghea",slug:"aurelia-meghea",fullName:"Aurelia Meghea"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},onlineFirst:{chapter:{type:"chapter",id:"79228",title:"Preisach Hysteresis Model. Some Applications in Electrical Engineering",doi:"10.5772/intechopen.99590",slug:"preisach-hysteresis-model-some-applications-in-electrical-engineering",body:'Hysteresis is a very complex nonlinear behavior affecting many physical phenomena. Systems affected by this behavior are characterized by the fact that the way they evolve in response to a stimulus depends not only on the cause of the stimulus, but also on the preceding states of the system. Thus, the same instantaneous values of the input can give different outputs depending on the history of the input applied, which gives rise to a relationship that is not only nonlinear but also multivalued, making it very difficult to model and control. This memory-based property is found in various areas of science and engineering such as mechanics, biology, economics and multiphase flow in porous media or magnetism, among others. It was precisely in the latter that the term was initially coined since most ferromagnetic materials exhibit hysteresis [1]. This means that when the material is subjected to the application of a magnetic field, the magnetic induction reached at each point of the material depends not only on the intensity of the applied field at a given instant of time, but also on its previous magnetic history. Despite the difficulties involved in its study, having a good hysteresis model is essential in a multitude of applications in the field of electrical engineering; an example of this is the estimation of energy losses in electrical machines.
The variety of systems with hysteresis is very broad and there is a large amount of bibliography devoted to hysteresis models in different communities of physicists, engineers, and mathematicians, where great efforts have been devoted to their development and analysis. As a result, nowadays there are several hysteresis models, ranging from simple to complex, each of them valid in some specific situation; see, e.g., the monographs and reviews [2, 3, 4, 5].
The mathematical approach tries to deal with this phenomenon under a common mathematical framework, but this is not always possible. We highlight the monograph by Krasnosel’ski
Hysteresis models can be classified into two main classes according to whether or not the system response depends on the input velocity. In
The so-called classical Preisach operator [10] is a rate-independent model originally designed to model hysteresis of ferromagnetic materials which is based on physical assumptions derived from the concept of magnetic domains [8, 9, 11, 12]. It is suitable for modeling scalar hysteresis and for this purpose, the magnetic field strength H is used as the input variable while the magnetization M (or the magnetic flux density strength, B) acts as the output variable. Its main advantage is the ability to describe not only the major hysteresis loop, but also inner loops and other complex characteristics of the magnetization processes. There are several extensions of this model that consider the rate of change of the stimulus to be able to consider phenomena where this factor influences the magnetization. These are generically referred to as
Currently, the Preisach-type operators [18] are used not only in the area of magnetism, but also to describe hysteresis phenomena in other fields as diverse as fluid flow in porous media [19], elastoplasticity [20], solid phase transitions [7], shape memory alloys [21], or biology [22], to name a few.
The mathematical and numerical treatment of PDEs with hysteresis operators is a challenging issue because, despite the importance of the topic, still few results are available. Due to the strong interdisciplinary character of hysteresis phenomena, the interest for their study is continuously increasing in a great variety of applications. During the last few years, the authors of this chapter have been working on the mathematical modeling, numerical analysis and computation of PDE hysteresis-related problems motivated by real applications, with special emphasis on the hysteresis of ferromagnetic materials. This work is a survey of previous co-authored studies [17, 23, 24, 25], where we have intended to provide original steps into the mathematical and numerical treatment of parabolic problems with hysteresis. In all of them, the Preisach model was considered as hysteresis operator. The problems were addressed in different aspects: mathematical analysis, numerical methods, until convergence of approximate solutions and computational results to confirm the theory and to compare with experimental data. The rigorous mathematical framework or the numerical analysis are not included here, and we will be concerned with the results obtained for different industrial problems.
The chapter is organized as follows. In Section 2, we start by recalling the basic properties of the hysteresis operators. The well-known Preisach hysteresis model, both in the rate-independent and rate-dependent cases, is introduced in Section 3. Finally, in Section 4 we show some examples of the applications of the Preisach model in electrical engineering. These examples include the computation of hysteresis losses, the numerical simulation of magnetization and demagnetization processes in ferromagnetic workpieces and the simulation of batteries for electric vehicles.
In this section, we summarize the basic knowledge of scalar hysteresis operators based on the description given in [6].
Most systems experiencing hysteresis phenomena display
Hysteresis loop (left) and rate independence example (right).
According to Ref. [6], two main characteristics of hysteresis phenomena can be distinguished:
We notice that, even in the most typical hysteresis phenomena, like plasticity, ferroelectricity or ferromagnetism, the memory effect is not completely rate-independent, since viscous-type effects are coupled with hysteresis. However, in the applications presented in the following sections, this effect is neglected, so that the rate-independent component prevails.
To provide a functional setting for hysteresis operators, we first notice that, at any instant
In the case of partial differential equations, it is necessary to define an operator
We notice that operator
The general setting that we have discussed so far, and the majority of the hysteresis models proposed in the literature, are scalar. Thus, they can be applied only to model unidirectional inputs. However, in many applications, the hysteresis is characterized by a vector input
The Preisach model [31] is the most common and probably the most important model to represent magnetic hysteresis phenomenona in the literature. It was originally proposed by the physicist F. Preisach [10] in 1935 in the context of ferromagnetism and later the formalism was more broadly generalized to describe hysteretic behaviors in different fields [6, 8]. Nowadays, it is recognized as a fundamental tool for describing hysteretic systems with complex behaviors.
To describe the hysteresis, the classical Preisach model assumes that each particle of the material has an associated elementary hysteresis operator, called
where
In this model, the elementary relay operator is represented by a rectangular loop in the input–output plane with “up” and “down” switching values (see Figure 2 for an example). Each elemental relay, here denoted by
Scalar relay.
Formally, for any continuous function
Then, for any
If
When working with ferromagnetic materials, this initial configuration results in zero magnetic induction; thus, the material is often said to be “demagnetized” or in a “virginal” state. We remark that, in this situation,
where we recall that variable
The integral in (7) is calculated in the so-called
An arbitrary input
being
(see Figure 3). The interface
Staircase line
Then, the Preisach operator (7) can be equivalently expressed as
which can be readily calculated once
From (10), is clear that
From the description above, we conclude that three basic steps characterize the model application:
Identification, from experimental data, of the Preisach density
At each time step the set
The value of
The first and third steps, namely, the identification of the Preisach function and the output calculation are difficult issues. To obtain an efficient procedure for the computation of
In [14, 32], Bertotti introduces a rate-dependent generalization of the classical Preisach model, aiming to take into account the rate of change of the input
Contrary to the classical relay operator, where only the two states
Input function
In a formal manner, and inspired by [14], for a fixed
In the expressions above, the standard notations
Next, we consider two examples aiming to give an idea of the dynamic curve
On the left panel, input function
From previous considerations, the dynamic Preisach operator
Notice that, if
Input function
In [8], Mayergoyz developed an approach for the computation of the Preisach model that does not require the Preisach density function
Left – First order reversal curves (solid line) and major loop (dashed line). Right – Triangle
where the integration domain
Taking into account that the integral on a generic triangle
where
In this section we present some applications of hysteresis modeling in electrical engineering. The first two are motivated by the hysteresis observed when modeling the BH curve of a ferromagnetic material. The third one has to do with the hysteresis present in the State of Charge (SoC)-Open Circuit Voltage (OCV) mapping of Li-ion batteries.
For the performance analysis of electrical machines, an important factor to be considered is the power losses that occur in the ferromagnetic materials that make up the core of the machine. These losses, usually known as iron losses, can generally be divided into eddy current, hysteresis and excess losses. Eddy current losses are resistive losses due to the currents induced in the magnetic material by the time varying magnetic induction; its magnitude strongly depend on the size of the continuous conductive regions. That is why the core of the machine is usually assembled from thin steel sheets, insulated from each other by a non-conductive coating on the surface.
The hysteresis and excess losses are essentially related to the microscopic properties of ferromagnetic materials. These consist of small magnetic domains, which tend to align along the external (time – varying) applied magnetic field. As a consequence of the molecular friction produced in this continuous movement, heat losses, generally referred to as magnetic hysteresis losses, are produced. Given a material point
Nevertheless, these losses are especially difficult to compute, since for ferromagnetic materials, the magnetic induction in each point depends on the intensity of the present magnetic field to which it is exposed, and also on previous exposures to magnetic field intensity of each volume element. This causes differences in the magnetization curve under increasing and decreasing fields; therefore, hysteresis loops arise as the one illustrated in Figure 9 (left).
Toroidal laminated media (left) and its meridian section (center); hysteresis loop measured and approached (right).
In the literature there are several simplified analytical expressions that are used to approximate the different components of the losses, such as those proposed by Bertotti [14], which are among the most widely used. However, the assumptions under which it is possible to apply these formulas are not met in most practical situations. In this context, numerical simulation is a viable option to overcome these limitations.
As an example, we consider an application consisting of the computation of hysteresis and eddy current losses in a laminated medium with toroidal geometry, as sketched in Figure 9. It consists of
As shown in [24], in this situation, it is possible to reduce the computational domain to the meridian section of one single sheet for which it is necessary to derive appropriate boundary conditions. More precisely, the axisymmetric transient eddy current problem to be solved reads:
where
where
The energy losses can be evaluated by computing the magnetic field and magnetic induction solutions to (19)–(22) with appropriate numerical techniques, such as Finite-Difference Time-Domain (FDTD) [33, 34] or Finite-Element method (FEM) (see, for instance [35, 36, 37, 38, 39, 40, 41, 42] where scalar and vector hysteresis models are considered, respectively). In particular, we have applied the latter and a fixed-point iteration (see [24], Section 3) and also [43, 44] for different fixed point iteratios applied to hysteresis models).
In order to compute the losses, we consider the energy balance in the axisymmetric setting, which reads [24]:
In this expression, the terms
The measurements reported in Table 1 were performed on an Epstein frame considering a material sheet of width 30 mm and thickness 0.5 mm. The sheet is subjected to sinusoidal flux excitation with peak induction levels
Total (exp.)a | Error 1(%)b | Error 2(%)c | ||||||
25 | 9.91 | 126.23 | 136.14 | 134.60 | 121.26 | 12.27 | 11.00 | |
32.77 | 269.50 | 302.27 | 300.32 | 300.25 | 0.67 | 0.02 | ||
91.37 | 585.73 | 677.10 | 676.60 | 638.93 | 5.97 | 5.90 | ||
150 | 48.25 | 146.10 | 194.34 | 186.49 | 167.55 | 15.10 | 11.30 | |
178.53 | 282.28 | 460.81 | 4570.42 | 459.16 | 0.36 | 0.46 | ||
506.40 | 588.19 | 1094.58 | 1095.70 | 1090.18 | 0.40 | 0.51 |
Total losses. Numerical versus experimental results (J/
Total losses computed experimentally.
Relative error between experimental losses and
Relative error between experimental losses and
This table shows that the computed losses are close to the losses measured in the experiments. The largest differences are obtained for
The technique known as Magnetic Particle Inspection (usually MPI for its acronym in English) is a non-destructive method for detecting flaws located on or near the surface of ferromagnetic parts. It exploits the fact that when a ferromagnetic sample is exposed to the influence of a magnetic field, the induced magnetic flux density accumulates inside the material. Then, if there is a crack, the magnetic field will be distorted, causing local magnetic leakage around the defect. Therefore, if fluorescent magnetic particles are sprayed on the magnetized sheet, they will concentrate on the cracks and produce deposits that are easy to identify under ultraviolet light. The purpose of MPI is to find faults in any direction. Because the breakings are easier to detect when orientated perpendicular to the specimen’s magnetic field, it is common to apply the magnetization in two orthogonal orientations, such as circular and longitudinal orientation (see Figure 10, left). Most times, after inspection, the workpieces must be demagnetized since residual magnetism could interfere with later processing.
Field lines in circular (left) and longitudinal (center) magnetization. Computational domain used in tests (right).
In [25], the authors introduced two models for the numerical simulation of the entire magnetization and demagnetization procedures entailed in an MPI test. In particular, the remanent flux density in specimens with cylindrical symmetry is computed. The method is based on scalar models that include magnetic hysteresis and is carried out in three steps: long-term magnetization, circular magnetization and final demagnetization. To achieve circular magnetization (and demagnetization), the workpiece is clamped between two electrical contacts between which an electric current is circulated (see Figure 10). For modeling purposes, all fields are assumed to be
For the longitudinal magnetization and demagnetization processes, the piece is placed inside a conducting coil carrying an alternating current in the azimuthal direction (see Figure 10). To avoid the use of a vector hysteresis law, an infinitely thin conducting surface
where
It is worth noting that when solving (32)–(35), the effective computation of the inverse of the hysteresis operator is avoided by using an iterative algorithm of a fixed point type, based on the properties of the Yosida regularization for maximal monotone operators (see [45]). Moreover, the fields
For the sake of brevity, only the numerical results corresponding to the circular case are included. The ferromagnetic piece is characterized by the initial magnetization curve and the major hysteresis loop, as shown in Figure 11, which was obtained by using an artificial weight function
Left – Major hysteresis loop and (blue) and initial magnetization curve (red). Center – Demagnetizing source. Right – Circular demagnetization. Remanent flux density at
It is well-known that hysteresis has a significant impact on the ability to monitor battery performance since it affects the voltage during charging and discharging cycles for different battery chemistries. Therefore, it must be considered for diagnosis algorithms that use the so-called open circuit voltage (OCV) as a measure of the state of charge (SoC) of the battery. SoC indicates the residual charge of the battery with respect to its maximum nominal and it is usually expressed as a percentage of the battery capacity. Since the SoC provides a measure of the available energy of the battery, as well as of its instantaneous power capacity, an accurate estimate is important to monitor battery performance. Unfortunately, it cannot be directly measured but must be estimated from other battery quantities (see, for instance [46, 47, 48, 49, 50], to mention some recent works). However, the non-linear electrochemical reactions involved in the battery system, the effects of temperature, aging and, specially, hysteresis effects make this task especially difficult.
For a battery cell, hysteresis means that the battery cell reaches different OCV values at the same SoC value and temperature between charge and discharge, depending on the previous charge–discharge history. In particular, from experiments it is shown that, after discharging, the OCV always relaxes below the OCV after charging for the same SoC (see Figure 12, left). As a consequence, the SoC-OCV relation is a bundle of curves enclosed in a major loop. The loop consists of two SoC-OCV curves obtained by fully charging and discharging the battery, first to minimum voltage and then to maximum voltage while recording the battery voltage and accumulated ampere hours, for a complete battery cycle. Minor loops lying inside the major SoC-OCV loop can be obtained by conducting similar experiments but with partial cycles (see Figure 12, right). A simple approach is to compute the average of the major loop and to relate the battery’s OCV with its SoC through this average single-valued curve (see Figure 12, left), but usually this approximation suffers from significant errors in the real SoC estimation.
Measurements along the major loop and the approximation given by the Preisach model (left). Experimental inner loops and approximation of the Preisach model for different SoC values (right).
Based on the work [51], in this section we consider a Preisach-type hysteresis model to approximate the SoC-OCV hysteresis loop (see [52, 53, 54] for different approaches to handle hysteresis in batteries). The battery dynamics is modeled by using an equivalent circuit model (ECM) as extensively used in the literature [55]. In particular, we consider a general
Sketch of the 2RC model and parameters values.
From a macroscopic standpoint, the SoC-OCV hysteresis relation can be considered rate-independent; this implies that the OCV depends on the SoC history and not on the velocity (battery current rate) of SoC. Our aim is now to apply a hysteresis model to a lithium-iron-phosphate (LFP) cell. It is known that the classical Preisach operator cannot be directly applied to model the SoC-OCV hysteresis loop. Thus, the hysteretic behavior is modeled with a modified Preisach operator in which the SoC is assumed to be the independent variable. In particular we consider
where
Next, we consider a realistic vehicle driving profile to quantify the accuracy of the ECM with hysteresis. We have solved (36)–(39) and compared the computed voltage (40) with the experimental values. The values of OCV are obtained with the average open circuit voltage curve (see Figure 12, left) and with the Preisach hysteresis model (cf. (41)). Figure 14 shows the results obtained when a second-order circuit model (2RC) is considered. More precisely, this figure shows, on the left, the measured voltage and on the right the error between the experimental voltage and the voltage computed with the average curve (in red) and the Preisach model (in blue), respectively. The result has been excellent when the Preisach model is considered, having a relative error of
Percentage error in the voltage approximation (left). Measured and computed voltage with ECM and Preisach model (right).
In this chapter we summarize some applications of the hysteresis Preisach model in electrical engineering. First, we have introduced the classical or rate-independent Preisach hysteresis model and the rate-dependent extension of this model, the so-called dynamic Preisach model. Moreover, the identification of this operator based on the Everett function is explained. Finally, we provide some examples of application of the Preisach model in electrical engineering which highlight the importance of having a good hysteresis model in those processes that are characterized by this complex behavior.
Work partially founded by FONDECYT-Chile project 1211030, by Xunta de Galicia project GI-1563 ED431C 2021/15 and by FEDER, Ministerio de Economía, Industria y Competitividad-AEI under grant project MTM2017-86459-R.
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\n\nAvoidance Measures for Academic Editors of Conflicts of Interest:
\n\nFor manuscripts submitted by the Academic Editor (or a scientific advisor), an appropriate person will be appointed to handle and evaluate the manuscript. The appointed handling Editor's identity will not be disclosed to the Author in order to maintain impartiality and anonymity of the review.
\n\nIf a manuscript is submitted by an Author who is a member of an Academic Editor's family or is personally or professionally related to the Academic Editor in any way, either as a friend, colleague, student or mentor, the work will be handled by a different Academic Editor who is not in any way connected to the Author.
\n\nCONFLICT OF INTEREST - REVIEWER
\n\nAll Reviewers are required to declare possible Conflicts of Interest at the beginning of the evaluation process. If a Reviewer feels he or she might have any material, financial or any other conflict of interest with regards to the manuscript being reviewed, he or she is required to declare such concern and, if necessary, request exclusion from any further involvement in the evaluation process. A Reviewer's potential Conflicts of Interest are declared in the review report and presented to the Academic Editor, who then assesses whether or not the declared potential or actual Conflicts of Interest had, or could be perceived to have had, any significant impact on the review itself.
\n\nEXAMPLES OF CONFLICTS OF INTEREST:
\n\nFINANCIAL AND MATERIAL
\n\nNON-FINANCIAL
\n\nAuthors are required to declare all potentially relevant non-financial, financial and material Conflicts of Interest that may have had an influence on their scientific work.
\n\nAcademic Editors and Reviewers are required to declare any non-financial, financial and material Conflicts of Interest that could influence their fair and balanced evaluation of manuscripts. If such conflict exists with regards to a submitted manuscript, Academic Editors and Reviewers should exclude themselves from handling it.
\n\nAll Authors, Academic Editors, and Reviewers are required to declare all possible financial and material Conflicts of Interest in the last five years, although it is advisable to declare less recent Conflicts of Interest as well.
\n\nEXAMPLES:
\n\nAuthors should declare if they were or they still are Academic Editors of the publications in which they wish to publish their work.
\n\nAuthors should declare if they are board members of an organization that could benefit financially or materially from the publication of their work.
\n\nAcademic Editors should declare if they were coauthors or they have worked on the research project with the Author who has submitted a manuscript.
\n\nAcademic Editors should declare if the Author of a submitted manuscript is affiliated with the same department, faculty, institute, or company as they are.
\n\nPolicy last updated: 2016-06-09
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He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). 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. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. 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. Anderson",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}}]}},subseries:{item:{id:"17",type:"subseries",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. 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