Meaning of notations used in this section.
\\n\\n
More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:{caption:"IntechOpen Maintains",originalUrl:"/media/original/113"}},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
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As a result of increasing industrialization and urbanization, cities around the world have experienced growing populations and as a result increasing number of vehicles. This trend is growing exponentially. Many predictors of urban population have indicated that by 2050, it is expected that 70% of the world population will be living in cities [1]. This implies that the number of vehicles will also see exponential growth as people work and study in cities. However, while the parking spaces are expanded, it does not meet the demands of growing populations. The shortage of parking spaces exerts more pressure on congested roads, which affects the travel time of motorists. This congestion of traffic leads to increase in costs in terms of fuel consumption, as well as an increase in accidents. The traffic authorities cannot cope with this burgeoning problem since it requires re-designing the parking infrastructure to make it more futuristic, so as to cater for rapid development and exponential growth in the number of motor vehicles [2]. In congested roads, the search for parking space consumes a lot of time and this negatively impacts on the economy, as people spend chunks of time waiting for limited parking spaces. This time would be well spent doing beneficial work. Moreover, the economy is also affected with respect to the environment as more carbon emissions are produced in the course of searching for parking [3]. This adds more strain on the economy as it has to deal with the effects of carbon pollution. The barrels of oil that are consumed everyday as a result of parking search are estimated at about one million rand [4]. Motorists also become fatigued from this tiring exercise of waiting and looking for parking, which affects productivity and overall health of people. Although many approaches have been proposed to tackle this problem [5], more intelligent mechanisms are needed to solve this critical problem, especially given its complexity and scalability. In many cities, parking attendants are ubiquitous as they guide motorists to empty parking bays. However, these manual controls are not efficient and do not optimize the available parking space. They are also expensive since these attendants expect a monetary reward for their services, and in many cases, they demand high charges for their unsolicited and informal services [6]. This is in addition to the formal fee that motorists pay for parking. If the informal attendants are not paid, they might damage the car or slash the tires, which creates a security risk to the motorists. As a result of this car parking problem, a safety hazard is created as carjackers and other robbers disguise themselves as parking attendants and end up inflicting harm on innocent motorists that are desperate for parking space. Due to the far-reaching impact of this problem, policymakers in some cities have attempted to introduce measures of dealing with the issue, by creating more off-street parking spaces and increasing the charges for on-street parking [7]. However, these measures have not created the desired effect as determined from many surveys; most motorists prefer on-street parking [8]. This is due to convenience and proximity of parking space to the intended destination. A long walk to the destination might impel the motorist to jostle and wait for on-street parking space. Therefore, the solution is not to walk away from reality on the off chance that creating more off-street parking would ameliorate the problem, but to face the problem and find smarter ways of optimizing the on-street parking. It is from that premise that the idea of a hybrid optimization method is proposed in this chapter. The method applies memetic algorithm, which is a blend of two algorithms. These are genetic algorithm that is used to optimize the global search based on the natural evolutionary process of generating new offspring using a set of parameters [9] and tabu search (TS) that is a metaheuristic that is used to diversify the search space by conducting neighborhood search of the individual solutions with a view to improve their fitness [10]. Unlike other heuristics, TS is memory based, such that each found solution in the course of the iteration is stored in a tabu list, so as to keep track of solutions and avoid duplicates. Its adaptive memory makes it suitable for highly dynamic problems [11], such as the street parking problem (SPP). In order to generate an optimal solution for the SPP, the synergy of these algorithms is harnessed to attain intensification and diversification search processes and enable the search reach optimum without premature convergence. The remainder of this chapter is structured as follows: related work is presented in Section 2, problem definition is talked about in Section 3, methodology is discussed in Section 4, results and discussion make Section 5, and the article concludes in Section 6.
A number of evolutionary algorithms have been advanced in the literature in an effort to solve the street parking problem (SPP). The review of these approaches provides an insight into what has been done and the potential impact and utility of the proposed approach in the current body of related knowledge.
Thomas and Kovoor [12] applied genetic algorithm to create an autonomous system for parking vehicles. The approach used the roulette wheel selection method for selection of mating individuals and then used genetic operators, such as crossover and mutation to optimize fitness and produce offspring. The same principle was used by Aydin et al. [13] to develop a parking system for a smart city. Based on Internet of Things, data is transmitted across the Internet through devices. The genetic algorithm generates a vacant parking slot, which can be navigated for reservation by the motorist. This process can be done on a mobile device, which is similar to the intelligent parking system that operates on android platform [14]. In order to automate the parking guide process, a mobile robot was designed to optimize parking space using fuzzy logic [15]. The intelligent mobile robot automatically guides the motorist toward free parking space. Based on genetic algorithm, the robot is able to detect free parking space and map it to the vehicle. It also checks the dimensions of the parking bay to ensure an appropriate vehicle is assigned the bay. The deep learning of the robot system creates patterns that can be used for prediction; for example, Camero et al. [16] applied neural networks to predict the occupancy of the parking, so as to output the possible free parking spaces available through an optimization process. Han et al. [17] optimized the selection of the parking lot and route by use of Dijkstra’s algorithm. The outcome of the optimization process in terms of path and parking lot is sent to the cell phone of the driver. The travel and walking distances are considered before the automatic assignment of parking.
Dong et al. [18] hybridized the chaotic dynamics with the particle swarm optimization (PSO) to optimize the parking space. In order to avoid premature convergence, there is a constant update of the rules with a view to increase diversity and expand the search. This technique was also applied by Abidi et al. [19] whereby parking space is assigned to groups of drivers using a hybrid genetic algorithm. However, with the changing optima in the current problems related to car parking, a dynamic application of the search operators would make the methods more adaptive, so as to perform well despite the complexity and nonstationary nature of the car parking problem. Researchers have resorted to combining several algorithms to match the inherent difficulty of the problem. For example, Kantenti et al. [20] combined sensor technology with the Internet of Things. The barricade to the parking area is sensor enabled, so as to capture the details of the car including number plate and keep track of the vehicles, as well as both allocated and unallocated parking spaces. The nearest parking space is allocated to the vehicle. Sensors that are triggered when a vehicle enters or exits the parking lot include Arduino, ultrasonic sensor, and optical character recognition, among others. In order for the vehicle to be allocated the nearest parking space, a swarm intelligence mechanism was applied by Moorthy and Pabitha [21], whereby the route generator and allocator are infused into the PSO algorithm, so as to have source and destination routes generated and allocated to vehicles searching for parking space. Motorists request for parking through a request handler function that then sends the information to the route generator. The storage of this information is done by the route repository, and this information can be useful for prediction; for example, Rad et al. [22] use the data collected on vehicles for traffic flow prediction. The approach combines genetic algorithm with neural fuzzy technique for reservation of parking space. The most optimal parking space is generated using a multi-objective function that simultaneously applies genetic and fuzzy operators to the search optimization process with a view to minimize the waiting time and cost that motorists can spend on the parking space. The advent of electric cars has added another layer of difficulty to the parking space problem not only due to increase in cars but also waiting time concerns, as it affects the depletion of the battery power. Amini et al. [23] proposed a power distribution system to support parking lots for electric cars. Genetic algorithm is hybridized with particle swarm optimization algorithm to minimize loss of distribution network and optimize the allocation of parking space. The searching time for parking space can also be minimized through application of a bi-level genetic algorithm that was presented by Shen et al. [24]. The approach finds inter alia, free parking space, fees, and location, which are defined at different levels of the problem. For example, the location is produced by the upper level, while waiting and travel costs are generated by the lower level. The method aims to minimize the costs associated with obtaining the parking space.
The problem in this section is defined as an on-street parking optimization problem based on linear programming. This implies that subject to a set of constraints, the best solution is obtained from a set of feasible solutions [25] with regard to parking space. The objective function is used to calibrate the outcome of the optimization process according to the desired objective or target as per the problem features, such as maximizing or minimizing based on the decision variables and coefficients (Table 1).
Notation | Denotation |
---|---|
Car entity: | |
Space entity: | |
Cost of assigning car | |
Distance between car | |
Time it takes to assign car | |
Parking space capacity |
Meaning of notations used in this section.
Minimize:
Subject to:
The objective of the function defined in Eq. (1) is to minimize the following:
The cost of assigning a car to an empty parking space
Distance between intended destination and parking
Time it takes to assign car to an empty parking space, as well as to find empty space and map it onto the waiting car
Vehicle waiting time
In order to find the optimal solution, the objective function is defined with inequality constraints. The constraint in Eq. (2) indicates that the total number of assigned cars must not exceed the size or capacity of the available parking space. The vehicle cannot be assigned parking unless there is an empty parking space, as defined in Eq. (3). In order to make it easy for the proposed hybrid algorithm to solve this problem, a penalty function is applied [26]. The function in Eq. (1) is converted into unconstrained optimization problem.
Minimize:
A constant penalty is applied to individuals or solutions in the population sample that have violated the constraints. The penalty factors are defined by
where
Unlike genetic algorithms (GAs), MAs combine two evolutionary processes to solve problems. These include the natural process where genes are transmitted from one entity to the other through mating and the cultural process where memes are transmitted through meeting and interactions with one another [27] (Figure 1).
Memetic algorithms.
These steps are followed in the implementation of the proposed algorithm. The algorithm represents a hybridized structure of evolutionary method and the local search. Memetic operators such as recombination and mutation are applied, so as to re-create new solutions through interactions between each other and the environment with a view to generate a better offspring. The local search expands the search space, which increases population diversity. The presence of multiple memes provides an opportunity for fitness comparisons, so that the best outcome is returned by the algorithm [28]. Whereas most approaches use tournament and roulette selection methods for parent individuals in the population, a random selection mechanism is used in this work [29]. The random selection of parents is conducted with a view to give each individual an equal chance for selection. The memetic operators are then applied to produce offspring. MAs are considered one of the best evolutionary methods that can solve today’s increasingly complex and dynamic problems and because of this, they have been extensively applied to solve real-life problems [30, 31].
In this work, TS metaheuristic is used to perform the exploitation procedure or search the local neighborhood for better solutions. TS comprises in its structure the ability to store solutions in the course of iterations [11]. Based on its memory function, TS prevents duplication of solutions by creating a sequential tabu list of solutions. The solution is added on condition that it is better than the existing previous solution [32]. The feasibility of the solutions is maintained by penalizing the infeasible solutions and concentrating the search in promising areas of the search space. The TS helps to control the search, given that it is easier to know which areas contain feasible solutions or otherwise based on the tabu list; the search can then be directed to areas of high feasibility value with a view to obtain the best solutions. The optimal parking space for the vehicle is thus obtained through search intensification and diversification. An adaptive memory configuration for TS is considered in this work. This allows automatic adjustment of the tabu list as the search progresses. The search moves that were already made or the solutions that were visited are forbidden, so as to ensure that all areas are visited during the search [33]. Swap moves are employed to focus search attention to areas that do not feature in the tabu search list. A swap move is conducted if it will yield the highest move gain [34]. The variables cannot change their status once they have been included in the tabu list, but if the search leads to a potentially better solution, then a swap move is performed. These measures enable the local neighborhood search to converge to solutions of good quality [35]. The local search technique implementation in this chapter follows the steps in Figure 2.
Search technique.
The efficiency of the proposed method, adaptive memetic algorithm (AMA), was evaluated against the existing optimization techniques in the literature with a view to investigate the performance of each method over the same set of data and defined with similar settings. The optimization techniques implemented in this work include simulated annealing (SA) [36], genetic algorithm (GA) [37], ant colony optimization (ACO) [38], and particle swarm optimization (PSO) [39]. MATLAB environment was used for the experiments in this section. The case study was taken from the city of Durban in South Africa which has an on-street parking problem (OPP) due to limited parking spaces. Anton Lembede street and Prince street are the two busy streets in Durban city that were selected for this study, and the global positioning system (GPS) data are drawn from the geographical information system of Google Maps, including the parking space coordinates. Thirty individuals are considered for the population sample size (Figures 3 and 4).
Satellite view of the Anton Lembede street in Durban city.
Satellite view of the Prince Street in Durban city.
Crossover and mutation probabilities are set at 25 and 75%, respectively. The performance is measured based on the average waiting time, utilization of the parking space, and allocation of appropriate parking space to the car.
The proposed AMA demonstrates the ability to explore and exploit the search better in search of higher fitness individuals during the search process, for most of the instances as shown in Figure 5.
Fitness comparisons between the proposed AMA and existing algorithms.
The results indicate that parking space wastage is minimized when memetic algorithm is employed in optimization of parking space. Also, the proposed method, AMA, produces a faster convergence for most iterations as shown in Figure 6. This is due to the local search technique that adaptively conducts a neighborhood search for better solutions. Ultimately, the AMA ensures that an appropriate parking space is allocated to the car.
Convergence comparisons between different techniques.
In this chapter, an adaptive memetic algorithm was employed to solve the on-street parking problem (OPP). The proposed method combined genetic algorithm (GA) and tabu search (TS) to generate the optimal solution. The method was applied to a real life problem in Durban city of South Africa whose limited parking space is under the control of eThekwini municipality. TS was used to perform neighborhood search to improve the solutions with a view to prevent premature convergence of the search process. The proposed algorithm optimized the parking space search and allocation by reducing the waiting time, cost of allocating vehicle to parking space, and enhancing parking space utilization through appropriate allocations. Given the difficulty of finding and allocating an on-street parking space, the proposed algorithm implemented the memetic operators adaptively, so as to deal with nonstationary optima. The proposed method was compared with existing algorithms, such as SA, GA, ACO, and PSO in solving the same problem, OPP, and as shown in the experiments, the proposed algorithm outperformed all algorithms on several iterations.
The utilization of quasi-interpolation methods has been advanced in several fields of numerical analysis. This method can yield directly to solutions and does not require the solution of any linear system. In general, quasi-interpolation methods have attracted much attention because of their potential for solving partial differential equations [1, 2, 3], curve and surface fitting, integration, differentiation, and so on. In [2], Foucher and Sablonnière developed some collocation methods based on quadratic spline quasi-interpolants for solving the elliptic boundary value problems. In [4], Bouhiri et al. have used the cubic spline collocation method to solve a two-dimensional convection-diffusion equation. Generally, the problems involving Burger’s equation arise in several important applications throughout science and engineering, including fluid motion, gas dynamics, [5] transfer and number theory [6].
In literature, recent developments in the resolution of the nonlinear Burger’s-Fisher equation have been achieved. In a recent study [7], Mohammadi developed a stable and accurate numerical method, based on the exponential spline and finite difference approximations, to solve the generalized Burgers’-Fisher equation. The main advantage of the last method is its simplicity. Kaya et al. [8] presented numerical simulation and explicit solutions of the generalized Burgers-Fisher. Ismail et al. [9] used the Adomian decomposition method for the solutions of Burger-Huxley and Burgers-Fisher equations. In [10] Mickens proposed a non-standard finite difference scheme for the Burgers-Fisher equation. A compact finite difference method for the generalized Burgers-Fisher equation was proposed by Sari et al. [11]. Khattak [12] presented a computational radial basis function method for the Burgers-Fisher equation and some various powerful mathematical methods such as factorization method [13], tanh function methods [6, 14], spectral collocation method [15, 16] and variational iteration method [17]. In [18], the fractional-order Burgers-Fisher and generalized Fisher’s equations have been solved by using the Haar wavelet method. Recently, in Ref. [19] discontinuous Legendre wavelet Galerkin method is presented for the numerical solution of the Burgers-Fisher and generalized Burgers-Fisher equations. It consists to combines both the discontinuous Galerkin and the Legendre wavelet Galerkin methods. In [20], Zhu and Kang presented a numerical scheme to solve the hyperbolic conservation laws equation based on cubic B-spline quasi-interpolation. Nonlinear partial differential equations are encountered in a variety of domains of science. Burgers- Fisher equation is a well nonlinear equation because it combines the reaction, convection and diffusion mechanisms. The sticky tag of this equation is called Burgers-Fisher because it gathers the properties of the convective phenomenon from the Burgers equation and the diffusion transport as well as the reaction mechanism from the Fisher equation. This equation shows an exemplary model to express the interaction between the reaction mechanisms, convection effect and diffusion transport. For current applications, Burgers-Fisher equation is much known in financial mathematics, physics, applied mathematics.
In this work, we consider the generalized Burger’s-Fisher equation ([9]) of the form:
with the initial condition
and the boundary conditions
and
The exact solution of Eq. (1) (presented in [9]) is given by:
Our main purpose in this chapter is to use the univariate quasi-interpolant associated with the algebraic hyperbolic B-spline of order
The chapter is organized as follows. Section 2 is dedicated to the description of the quasi-interpolation of the algebraic hyperbolic splines. Afterward, Section 3 is devoted to the presentation of numerical techniques to solve the Burger’s-Fisher equation. The stability of the scheme has been studied in Section 4. In Section 5, two examples of the Burger’s-Fisher equation are illustrated and compared to those obtained with some previous results. Finally, our conclusion is presented in Section 6.
In this section, we recall the results on hyperbolic spline quasi-interpolation that we will use to establish the numerical method (see [21]). Let
For
and for
We apply the recursion formula (8) to get the algebraic hyperbolic B-spline of order
According to [21], the univariate Quasi-Interpolant associated to the algebraic hyperbolic B-spline of order
where
The error associated with the quadrature formula based on
Theorem 1 There exists a constant
with
For approximate derivatives of
and
The values of
and
By using Eq. (10), the first derivative of algebraic hyperbolic spline quasi-interpolation at
That is to say
and the second derivative of algebraic hyperbolic spline quasi-interpolation at
That is to say
with
Discretizing (1) in time we get
where
Assume that
From the initial conditions ((3), (4)) and boundary conditions (2), we can compute the numerical solution of (1) step by step using the scheme (20) and formulas ((17), (19)).
According to (17), (19) and (21). the scheme (20) can be rewritten as
with
This scheme is called the algebraic hyperbolic quasi-interpolation (AHQI) scheme.
Sharma and Singh provided a method to study the stability of the nonlinear partial equation in [25], which we used in this section to study the stability of our scheme.
If we set
If we move to the L-infinity norm then we obtain
If we set
It implies that the scheme is stable if
with
In this section, the proposed quasi-interpolation splines collocation methods are tested for their validity for solving the generalized Burgers-Fisher equation with the initial condition (2) and the boundary conditions (3). Two different examples for the Burgers-Fisher equation are solved and the obtained results are compared with those presented in [22, 25]. To verify the accuracy and reliability of the present method in this article, we select two examples to conduct numerical experiments and compare them with the calculated results in the existing literature. That’s why we divided this section into two subsections, in each subsection we compared our scheme (AHQI scheme) to each example by comparing their maximum error which is defined by
In the first example, we compared the maximum error of AHQI scheme with MCN scheme proposed in [22]. In Table 1 we showed the maximum error of each scheme with different values of
x | N = 10 | N = 100 | N = 1000 | |||
---|---|---|---|---|---|---|
AHQI | MCN | AHQI | MCN | AHQI | MCN | |
1 | 1 | 1 | 1 | 1 | ||
0.1 | 0.0442 | 0.0987 | 0.0248 | 0.0865 | 0.0128 | 0.2880 |
0.2 | 0.0923 | 0.1269 | 0.0760 | 0.1153 | 0.0384 | 0.2834 |
0.3 | 0.1399 | 0.1352 | 0.1225 | 0.1232 | 0.0727 | 0.2060 |
0.4 | 0.1869 | 0.1376 | 0.1662 | 0.1250 | 0.1293 | 0.1419 |
0.5 | 0.2329 | 0.1383 | 0.2064 | 0.1253 | 0.2180 | 0.1158 |
0.6 | 0.2778 | 0.1379 | 0.2394 | 0.1251 | 0.3439 | 0.1315 |
0.7 | 0.3213 | 0.1359 | 0.2595 | 0.1235 | 0.4929 | 0.1836 |
0.8 | 0.3633 | 0.1287 | 0.2458 | 0.1162 | 0.5740 | 0.2489 |
0.9 | 0.4037 | 0.2489 | 0.1225 | 0.0882 | 0.3241 | 0.2516 |
Values of errors by AHQI and MCN.
The behavior of numerical results of equation
For the second example, we compared our scheme to BSQI scheme proposed in [25] for different values of
The absolute errors for
t | ||||||
---|---|---|---|---|---|---|
AHQI | BSQI | AHQI | BSQI | AHQI | BSQI | |
0.001 | 2.22044 | 4.44089 | 2.88657 | 9.76996 | 2.37587 | 3.37508 |
0.005 | 3.88578 | 1.55431 | 1.26565 | 4.17888 | 1.16573 | 1.66422 |
0.010 | 6.66133 | 1.83187 | 2.45359 | 9.18154 | 2.32702 | 3.25628 |
0.500 | 1.19904 | 3.81917 | 2.12041 | 1.07303 | 2.12041 | 3.88234 |
1.000 | 5.10702 | 3.04201 | 2.17048 | 1.08047 | 2.12352 | 3.91087 |
Error for various values of
t | ||||||
---|---|---|---|---|---|---|
AHQI | BSQI | AHQI | BSQI | AHQI | BSQI | |
0.2 | 3.99146 | 5.55746 | 1.26606 | 2.56108 | 1.76174 | 1.76161 |
0.4 | 7.94950 | 9.05507 | 1.74941 | 4.24308 | 1.82135 | 4.17351 |
0.6 | 1.76244 | 2.18808 | 2.71508 | 3.56848 | 1.32793 | 2.42401 |
0.8 | 2.34913 | 2.93314 | 3.79941 | 1.46518 | 7.62594 | 2.35757 |
1 | 2.47511 | 3.01455 | 3.98493 | 5.54230 | 3.79941 | 1.44350 |
Error for various values of
In this work, a numerical scheme to solve the nonlinear Burgers -Fisher equation has been proposed using algebraic hyperbolic spline quasi-interpolation. The numerical scheme stability was well established. The scheme efficiency, as well as its accuracy, are justified by treating well-known examples in the literature, for each case the error is reported. We conclude that the scheme with algebraic hyperbolic spline quasi-interpolation can solve Burgers-Fisher equations since it produces reasonably good results, with high convergence with very small errors.
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Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. 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Saxena",hash:"d92a4085627bab25ddc7942fbf44cf05",volumeInSeries:2,fullTitle:"Current Perspectives in Human Papillomavirus",editors:[{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",slug:"shailendra-k.-saxena",fullName:"Shailendra K. Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},subseriesFiltersForPublishedBooks:[{group:"subseries",caption:"Bacterial Infectious Diseases",value:3,count:2},{group:"subseries",caption:"Parasitic Infectious Diseases",value:5,count:4},{group:"subseries",caption:"Viral Infectious Diseases",value:6,count:7}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:2},{group:"publicationYear",caption:"2021",value:2021,count:4},{group:"publicationYear",caption:"2020",value:2020,count:3},{group:"publicationYear",caption:"2019",value:2019,count:3},{group:"publicationYear",caption:"2018",value:2018,count:1}],authors:{paginationCount:148,paginationItems:[{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. 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:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{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:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{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:'"Politechnica" University Timişoara',institution:null},{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:{name:"Tecnalia",country:{name:"Spain"}}},{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:"426586",title:"Dr.",name:"Oladunni A.",middleName:null,surname:"Daramola",slug:"oladunni-a.-daramola",fullName:"Oladunni A. 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The area covers many techniques that offer solutions to emerging problems in robotics and enterprise-level software systems. Collaborative intelligence is highly and effectively achieved with multi-agent systems. Areas of application include swarms of robots, flocks of UAVs, collaborative software management. Given the level of technological enhancements, the popularity of machine learning in use has opened a new chapter in multi-agent studies alongside the practical challenges and long-lasting collaboration issues in the field. It has increased the urgency and the need for further studies in this field. We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",hasOnlineFirst:!0,hasPublishedBooks:!1,annualVolume:11423,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. 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mechanisms of living organisms through the construction and use of quantitative tools. The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. The considerable development of technology, including the computing power of computers, is also conducive to the development of bioinformatics, including personalized medicine. In an era of rapidly growing data volumes and ever lower costs of generating, storing and computing data, personalized medicine holds great promises. Modern computational methods used as bioinformatics tools can integrate multi-scale, multi-modal and longitudinal patient data to create even more effective and safer therapy and disease prevention methods. Main aspects of the topic are: Applying bioinformatics in drug discovery and development; Bioinformatics in clinical diagnostics (genetic variants that act as markers for a condition or a disease); Blockchain and Artificial Intelligence/Machine Learning in personalized medicine; Customize disease-prevention strategies in personalized medicine; Big data analysis in personalized medicine; Translating stratification algorithms into clinical practice of personalized medicine.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/7.jpg",keywords:"Biomedical Data, Drug Discovery, Clinical Diagnostics, Decoding Human Genome, AI in Personalized Medicine, Disease-prevention Strategies, Big Data Analysis in Medicine"},{id:"8",title:"Bioinspired Technology and Biomechanics",scope:'Bioinspired technologies take advantage of understanding the actual biological system to provide solutions to problems in several areas. Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",keywords:"Bioinspired Systems, Biomechanics, Assistive Technology, Rehabilitation"},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:null,selectedSubseries:null},seriesLanding:{item:{id:"7",title:"Biomedical Engineering",doi:"10.5772/intechopen.71985",issn:"2631-5343",scope:"Biomedical Engineering is one of the fastest-growing interdisciplinary branches of science and industry. The combination of electronics and computer science with biology and medicine has improved patient diagnosis, reduced rehabilitation time, and helped to facilitate a better quality of life. Nowadays, all medical imaging devices, medical instruments, or new laboratory techniques result from the cooperation of specialists in various fields. The series of Biomedical Engineering books covers such areas of knowledge as chemistry, physics, electronics, medicine, and biology. This series is intended for doctors, engineers, and scientists involved in biomedical engineering or those wanting to start working in this field.",coverUrl:"https://cdn.intechopen.com/series/covers/7.jpg",latestPublicationDate:"August 3rd, 2022",hasOnlineFirst:!0,numberOfOpenTopics:3,numberOfPublishedChapters:107,numberOfPublishedBooks:12,editor:{id:"50150",title:"Prof.",name:"Robert",middleName:null,surname:"Koprowski",fullName:"Robert Koprowski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTYNQA4/Profile_Picture_1630478535317",biography:"Robert Koprowski, MD (1997), PhD (2003), Habilitation (2015), is an employee of the University of Silesia, Poland, Institute of Computer Science, Department of Biomedical Computer Systems. For 20 years, he has studied the analysis and processing of biomedical images, emphasizing the full automation of measurement for a large inter-individual variability of patients. Dr. Koprowski has authored more than a hundred research papers with dozens in impact factor (IF) journals and has authored or co-authored six books. Additionally, he is the author of several national and international patents in the field of biomedical devices and imaging. Since 2011, he has been a reviewer of grants and projects (including EU projects) in biomedical engineering.",institutionString:null,institution:{name:"University of Silesia",institutionURL:null,country:{name:"Poland"}}},subseries:[{id:"7",title:"Bioinformatics and Medical Informatics",keywords:"Biomedical Data, Drug Discovery, Clinical Diagnostics, Decoding Human Genome, AI in Personalized Medicine, Disease-prevention Strategies, Big Data Analysis in Medicine",scope:"Bioinformatics aims to help understand the functioning of the mechanisms of living organisms through the construction and use of quantitative tools. The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. The considerable development of technology, including the computing power of computers, is also conducive to the development of bioinformatics, including personalized medicine. In an era of rapidly growing data volumes and ever lower costs of generating, storing and computing data, personalized medicine holds great promises. Modern computational methods used as bioinformatics tools can integrate multi-scale, multi-modal and longitudinal patient data to create even more effective and safer therapy and disease prevention methods. Main aspects of the topic are: Applying bioinformatics in drug discovery and development; Bioinformatics in clinical diagnostics (genetic variants that act as markers for a condition or a disease); Blockchain and Artificial Intelligence/Machine Learning in personalized medicine; Customize disease-prevention strategies in personalized medicine; Big data analysis in personalized medicine; Translating stratification algorithms into clinical practice of personalized medicine.",annualVolume:11403,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/7.jpg",editor:{id:"351533",title:"Dr.",name:"Slawomir",middleName:null,surname:"Wilczynski",fullName:"Slawomir Wilczynski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035U1loQAC/Profile_Picture_1630074514792",institutionString:null,institution:{name:"Medical University of Silesia",institutionURL:null,country:{name:"Poland"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"5886",title:"Dr.",name:"Alexandros",middleName:"T.",surname:"Tzallas",fullName:"Alexandros Tzallas",profilePictureURL:"https://mts.intechopen.com/storage/users/5886/images/system/5886.png",institutionString:"University of Ioannina, Greece & Imperial College London",institution:{name:"University of Ioannina",institutionURL:null,country:{name:"Greece"}}},{id:"257388",title:"Distinguished Prof.",name:"Lulu",middleName:null,surname:"Wang",fullName:"Lulu Wang",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRX6kQAG/Profile_Picture_1630329584194",institutionString:"Shenzhen Technology University",institution:{name:"Shenzhen Technology University",institutionURL:null,country:{name:"China"}}},{id:"225387",title:"Prof.",name:"Reda R.",middleName:"R.",surname:"Gharieb",fullName:"Reda R. Gharieb",profilePictureURL:"https://mts.intechopen.com/storage/users/225387/images/system/225387.jpg",institutionString:"Assiut University",institution:{name:"Assiut University",institutionURL:null,country:{name:"Egypt"}}}]},{id:"8",title:"Bioinspired Technology and Biomechanics",keywords:"Bioinspired Systems, Biomechanics, Assistive Technology, Rehabilitation",scope:'Bioinspired technologies take advantage of understanding the actual biological system to provide solutions to problems in several areas. Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',annualVolume:11404,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",keywords:"Biotechnology, Biosensors, Biomaterials, Tissue Engineering",scope:"The Biotechnology - Biosensors, Biomaterials and Tissue Engineering topic within the Biomedical Engineering Series aims to rapidly publish contributions on all aspects of biotechnology, biosensors, biomaterial and tissue engineering. We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. Finally, the tissue engineering subcategory will support topics such as the fundamentals of stem cells and progenitor cells and their proliferation, differentiation, bioreactors for three-dimensional culture and studies of phenotypic changes, stem and progenitor cells, both short and long term, ex vivo and in vivo implantation both in preclinical models and also in clinical trials.",annualVolume:11405,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",institutionString:null,institution:{name:"Autonomous University of Baja California",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"35539",title:"Dr.",name:"Cecilia",middleName:null,surname:"Cristea",fullName:"Cecilia Cristea",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYQ65QAG/Profile_Picture_1621007741527",institutionString:null,institution:{name:"Iuliu Hațieganu University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"40735",title:"Dr.",name:"Gil",middleName:"Alberto Batista",surname:"Gonçalves",fullName:"Gil Gonçalves",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYRLGQA4/Profile_Picture_1628492612759",institutionString:null,institution:{name:"University of Aveiro",institutionURL:null,country:{name:"Portugal"}}},{id:"211725",title:"Associate Prof.",name:"Johann F.",middleName:null,surname:"Osma",fullName:"Johann F. 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