Projected natural gas demand in India [in MMSCMD].
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"1310",leadTitle:null,fullTitle:"Topics in Cancer Survivorship",title:"Topics in Cancer Survivorship",subtitle:null,reviewType:"peer-reviewed",abstract:"Cancer is now the leading cause of death in the world. 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He later used similar methods in Virginia, to evaluate the quality of life of patients who had knee arthritis, and subsequently of patients before and after treatment of localized prostate cancer. \nDr. Mohan’s research has been published in over 35 high-impact factor peer-reviewed journals and he has also contributed to chapters in five books.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"3",institution:null}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1075",title:"Breast Oncology",slug:"breast-oncology"}],chapters:[{id:"26732",title:"Living With and Beyond Cancer: New Challenges",doi:"10.5772/24959",slug:"living-with-and-beyond-cancer-new-challenges",totalDownloads:1746,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:null,signatures:"Neel Bhuva, Sonia P. 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His technical feasibility study [1] had originally been an attachment to the science fiction story of a journey to Mars, which he wrote during his postwar internment [2]. In his story, he makes the crew members go through a 1-month isolation prior to their flight to Mars, in order to let this character screening test verify their ability to manage psychological distress [3]. When he modified this story for Collier’s magazine edition, he writes about how states of tension and hatred appear among the crew members after several months, which could even have led to murder [2]. At this time, researchers were not only interested in physiological questions anymore but also in psychological aspects of extraatmospheric flights [4]. In the years 1956–1958, the first simulations of a stay in a cosmic cockpit took place, which included not only physiological but also psychological monitoring [5]. During one of these experiments, a decline in performance and mood was observed. Due to displays of hatred toward the researchers, the question arose whether to prematurely end the week-long isolation study [6]. The founding of the National Aeronautics and Space Administration (NASA) in 1958 allowed the extension of the experimental research program, including psychosocial aspects of long-term space flights. The psychological prerequisites for managing a cosmic flight were also considered important during the selection of the first astronauts in the Mercury project—besides an interview, as well as personality and performance psychological testing, candidates were sociometrically questioned, including whom of their colleagues they would commission to fly if they themselves could not and with whom they would most like to undertake the flight if the crew only had two members [5]. In his summarizing study, Christensen [7] reverted to the progress and results of this selection, to the existing interpersonal antagonisms, as well as to other findings. In explicit relation to the preparation for a flight to Mars, Christensen wrote about the need to research the impacts of cosmic flights on human behavior. Chambers [8] reached the conclusion in his summarizing study that psychological variables have a greater impact on the progress of simulated flights than physiological variables do. He also concluded that over time, motivation may decrease and that some crew members may become more irritable, even hostile. According to him, this can be prevented not only through a selection of suitable, i.e., stress-resistant, individuals, but also through training, which should include the team’s isolation before the flight. In 1963, the Institute of Biomedical Problems (IMBP) was founded in the Soviet Union, whose purpose was to deal, among other things, with the research of the conditions of a flight to Mars [9]. In 1964, the first experiment took place in the IMBP—a 120-day-long stay of a three-member crew in a module imitating a spaceship designed for a flight to Mars [10, 11]. Following up, an experiment of a 1-year isolation of a three-member crew took place in 1967–1968 [11]. As one of the participants of this 1-year experiment later indicated [12], it turned out that “the problem of the crew’s psychological tolerance is one of the key problems of the medicinally psychological assurance of lengthy cosmic flights.” Fraser [13] analyzed 60 confinement studies and also reached the conclusion that feelings of anger and animosity, directed either at other crew members or at the researchers and other outside persons they communicate with, occur frequently. Haythorn [14] indicated in his summarizing study that interpersonal relationships do not always alleviate stress but can also produce it. Furthermore, he notes that little is known about the behavior of isolated groups in stress situations, due to the lack of longitudinal studies. As Suedfeld [15] later pointed out, it is possible to deduce, to a certain extent, the behavior of people on long-term cosmic missions from early terrestrial and marine exploration voyages, which also illustrate the importance and vulnerability of mutual interpersonal relationships. Kanas and Fedderson [16] conducted their review bearing in mind the fact that the mission to Mars will be a long-term one. Among other things, they point out that in the longer term, restrictions of interpersonal contact may appear. Like other similarly oriented research, they recommend reducing the risks with a suitable selection of people and with activities compensating the monotony and sensory deprivation. Vinograd’s work [17] was a synoptical summarization in its time, comprised of 14 studies simulating cosmic flights but also of comparable studies of submarine crew members, teams in arctic or military environments, or in other situations of isolation. An analysis of individual studies reveals not only the importance of mutual relationships but also the lack of tools for a continuous (quantitative) capturing of their changes. In 1975, the newly founded European Space Agency (ESA) joined the other research institutions in their coverage of cosmic research (including psychosocial questions).
During the 1970s, it was proven during real cosmic flights that relationship and communication issues can have grave consequences. In 1974, the first cosmic strike of a crew led by William Pogue took place, who reasons in his autobiography [18] that the strike happened due to the demanding work program, which did not include time for rest. The exhaustion culminated in a conflict between the control center and the astronauts, to which the astronauts reacted with a 24-hour silence. In 1975, the astronauts themselves pointed out the importance of the psychological aspect of space flights [19]. In 1976, a premature abortion of the mission of the two-member crew of Volynov and Zholobov occurred, which was later attributed to the demanding work conditions, the worsening psychological state of the crew, but also to the serious conflicts between the two astronauts [20, 21]. Almost 10 years later, Harrison and Connors [22] suggested lowering the psychological and interpersonal vulnerability of the team not only by a suitable selection of crew members but also through training in group dynamics and by offering psychological support. They request that the anecdotal testimonies of the importance of these factors be examined by systematic scientific research. In cooperation with the IMBP, the Štola 88 experiment was conducted in the former Czechoslovakia, in which the comparison of two teams simulating a flight to Mars showed how differently the communication can develop during isolation depending on the composition of the team and leadership type [23, 24, 25]. In this 23-day experiment (structured for the crew as thirty 18-hour days), it was shown, among other things, that part of the tension manifested itself in a deterioration of the communication with the control center [24, 25]. In a later debriefing, the presence of a woman in one of the teams was mentioned as positive [26]. Related to the renewed considerations of a journey of six (or more) astronauts to Mars, Kanas [27] points to the possible impact of psychological, psychiatric, and interpersonal factors on the safety and success of such a mission. He mentioned interpersonal tension, a continuously decreasing team cohesiveness, the need for privacy, and the leadership’s contradicting focus on the task and on emotions. In the 1990s, under the tutelage of the European Space Agency, a 30-day experiment with a six-member crew, Isolation Study for European Manned Space Infrastructure (ISEMSI-90), was carried out [28], as well as a 60-day experiment with a four-member crew, Experimental Campaign for the European Manned Space Infrastructure (EXEMSI-92) [29]. To capture the relationship dynamics, the Systematic Multiple Level Observation of Groups (SYMLOG) method [30, 31] was utilized, for example, as well as an analysis of spatial behavior [32, 33] and an analysis of the communication with the control center [34, 35]. During a summary of the EXEMSI experiment’s results [36], it was noted that while no conflicts occurred within the team, this came at the expense of suppressing affection and a more rigid functioning of the team. Cazes and his colleagues believe that it was possible to maintain such a communication thanks to the experiment’s relatively short duration and to the absence of any real risk. They consider this type of behavior inadequate (even dangerous) for a real space flight. They also point out that the team’s cohesiveness was maintained by using the management as a scapegoat, as demonstrated by the criticism of the ground crew during crisis situations. For this reason, Cazes et al. [36] have doubts whether the harmony presented in sociometric tests was real or apparent. An important stimulus for the research of communication in the 1990s was the analyses proving that a majority of accidents in aviation are caused by human factors [37]. As it later turned out, after the introduction of standardized communication rules (the crew management system), accidents caused by human factors decreased significantly [38]. In 1994, a joint project between the ESA and IMBP was carried out, the Human Behavior in Extended Spaceflight (HUBES) experiment, in which a 30-member crew was isolated for 135 days. In this experiment, physiological variables were observed in addition to the crew’s communication. Sociometric tests were included, as well. The sociomapping method, which had been tested for a year on military units of the Czech army [39], supplemented the data collection and will be presented in more depth in the following chapter. In 1996, a 30-day stay of a four-member crew took place as part of the Lunar-Mars Life Support Test Project [40]. Even though the team dynamic was evaluated as ideal during the debriefing of this experiment, one of the recommendations was for the teams to be briefed more and sensitized to the psychological aspects of the experiments. In the summary of the subsequent 91-day experiment that took place in the Lunar-Mars Life Support Test Project in 1997, its leader mentions that in the early phases of the project, miscommunications occurred between the control center and the crew [41], to which it was necessary to react with an increased emphasis of the “overall team-integration approach,” which also included members of the management. Holland a Curtis [42] pointed out in their summary of the results of NASA studies within the Lunar-Mars Life Support Test Project that extending the length of the mission increases the significance of psychological factors and thus psychological activities, as well, which are meant to ensure the success of the mission [43]. Among those, they mention training, briefing, in-mission tracking, and prospective interventions. They also allude to the importance of communication with the family and other close people outside of the crew. As Galarza and Holland [44] propose, the fact that teamwork and the ability to get along with the team are critical competencies for long-term flights should be reflected in the development of tools and procedures for the selection of people but also in their trainings and in-flight support. Despite the knowledge that tensions may rise during periods of isolation and partial communication isolations of certain team members may occur, the next experiment conducted in the IMBP, Simulation of Flight of International Crew on Space Station (SFINCSS), was carried out without a continuous monitoring of the communication. Furthermore, it utilized subjective evaluation scales and did not provide an appropriate training on group dynamics, which would include cultural and gender aspects, too (a woman took part in the experiment, unlike the previous HUBES and EKOPSY experiments). The experiment had to be terminated prematurely due to an argument between two astronauts, resulting in a physical altercation, an allegation of harassment, and due to the explicit request of a Japanese crew member to be able to leave the shuttle [45, 46]. Despite its failure, this experiment was useful, as it pointed out what consequences an underestimation of a continuous monitoring of communication and its subsequent interventions can have. It also demonstrated that it is necessary to pay attention to linguistic and cultural aspects. Morphew [47] refers to personal conversations with astronauts Jdanov and Atkov to point out that the astronauts themselves consider psychological and psychosocial aspects among the most critical problems of long-term flights, based on their own experience. Among the most significant psychosocial stress factors, Morphew mentions the high demands on team coordination, tensions between the crew members and control center, the forced contact with other crew members, the lack of contact with the family, cultural differences, and other factors, such as differences in gender, personalities, and others. Other non-psychosocial factors, such as high or low workloads, lack of privacy, space adaptation sickness, and of course the permanent life-threatening dangerous environment, must be considered, as well. Morphew [47] concludes that the US cosmic program considers psychological factors critical for increasing the safety and ensuring the success of the mission. In 2004, Manzey states that the research on human behavior during long-term missions is still insufficient to estimate and reduce specific risks associated with a long-term journey to Mars. In this context, he mentions that it is necessary to pay attention not only to an individual adaptation and performance but also to the interactions among the crew members and methods of psychological measures [48, 49].
The sociomapping method allows to visually express mutual proximities (and distances) between individual teammates, military units, and crews [39, 50, 51, 52]. From a mathematical perspective, proximity is the degree of membership into the fuzzy set of people close to a specific member of the team. Various operational definitions are being used for the degree of membership, depending on the situation. Mutual proximity can be defined by the time spent on joint conversations, the volume of text or information, the average physical proximity, and many other characteristics. Most commonly, scales evaluating the mutual communication or cooperation in a given timeframe from a quantity and quality standpoint are used [52]. Such operationalized values of mutual proximity do not have to be symmetrical for two team members. Data about the validity, reliability, and time dependability is known and constantly being supplemented [52, 53, 54, 55]. During the creation of sociomaps, the order of the closest to the furthest colleague is correlated for each team member in terms of the spatial distance ranked by the closest to the furthest according to the degree of membership. The final sociomap is created by maximizing the average Spearman correlation coefficients calculated for each team member [51, 52, 56]. During sociomapping, the average values of the scales are being monitored using the control chart method, which allows to capture significant deviations over time [52, 57, 58]. In the HUBES experiment, it turned out [23] that sociometric tests were not sensitive enough, whereas the scales evaluating the cooperation allowed to capture the gradual development, which consisted in one crew member separating from the other two with a simultaneous decrease in communication (substantiated by analyses of actual communication). The aggregated score expressing the degree of subjectively and physiologically captured stress grew over time, particularly in the final quarter of the experiment [23, 50]. As (not only) the HUBES experiment showed, traditional sociometrical procedures consisting in the selection of the remaining crew members are not very suitable due to their lack of sensitivity to continuous changes, which is particularly important in long-term missions. For this reason, sociomapping was also used in the 90-day experiment ECOPSY-95, in which a three-member crew was expanded by another three-member crew over the course of the experiment. Thanks to sociomapping, it was possible to capture how both crews interconnected from a communication standpoint, particularly thanks to the communication between the two crew leaders [51, 59]. After the departure of the second crew, the original three-member crew returned to the initial composition, while one of the members remained relatively separated from the communication perspective. In the Mars-105 experiment, a flight to Mars was simulated throughout a 105-day stay of a six-member crew in a module of the MIR ship [52]. To monitor the communication, subjective scales were used again, including a five-point evaluation of changes in the communication frequency with individual crew members, for example, the communication in the last previous weeks decreased significantly – decreased slightly – stayed the same – increased slightly – increased significantly. In addition, it included a five-point evaluation of the required optimal change in communication frequency (a wish for a significant decrease – slight decrease – maintenance of the current state – slight increase – significant increase), a percentage evaluation of the quality of cooperation with individual team members (0–100% scale), as well as an overall assessment of the team’s performance and atmosphere (0–100% scale). The scales were supplemented by a question about the frequency of misunderstandings. All questions concerned the period from the previous measurement (i.e., approximately the prior 2 weeks). The following graph indicates the average values of the five-point scales of the perceived communication changes converted to the interval <0;1> for seven specific dates indicated by the administration (the whole experiment took place between March 31, 2009, and July 14, 2009). The value of 0.5 corresponds to constant, or stabilized, in terms of communication frequency (Figure 1).
Average change in frequency of communications.
Even though the communication frequency stabilized throughout the experiment, it is possible to capture significant changes in the percentage scales of the assessment of the mutual communication’s quality, which match the fluctuations of the average percentage scales of the overall evaluation of the team’s performance and atmosphere (Figure 2).
Average quality of cooperation.
In the mutual assessment of the communication quality and in the overall evaluation of the team’s performance and atmosphere, the minimum was reached in the administration on June 13, 2009, i.e., about two thirds into the experiment. The assessment of the performance and quality of communication were even lower at this point than it had been during the first administration. Furthermore, for this period, the highest number of misunderstandings was reported (only two out of six people indicated that no misunderstandings occurred in this period). In a personal account, the crew’s leader commented on the worsening atmosphere, performance, and quality of communication. Among other factors, he considered fatigue, as well as the suggested improvement measures, which the crew submitted to the control center and which were not accepted according to their expectations, to have played a role. The deterioration of communication quality, captured on multiple levels, proves that it is possible to detect significant changes using a scaled assessment, even though the scales are test–retest reliable. The median of the test–retest correlation in this experiment was 0.8 [52]. While the average scale values may point to the fact that the communication overall is deviating from its norm, the sociomaps offer insight on an individual team member level. The following figures show sociomaps of the crew (including the displayed position of the control center) dated May 2, 2009, and May 9, 2009 (in this case, the time passed between the administration was only 7 days) (Figures 3 and 4).
Sociomap of Mars-105 crew (May 2, 2009).
Sociomap of Mars-105 crew (May 9, 2009).
As the description of sociomapping above implies, the closer two crew members are to each other, the more they communicate together. The whole team can be divided into subsets according to their mutual adhesion [50, 51, 52]. The blue arrows indicate a desired increase in communication (compared to the current level), while red arrows signify a wish for the decrease of communication. Colors stand for the average frequency of current communication for each crew member and control center (CC).
The situation changed over the course of 7 days—person P2 is more connected with persons P3 and P4. The basis of the second subgroup is primarily the close relationship between P5 and P6, the only foreign (non-Russian) crew members. Following the Mars-105 experiment, the longest experiment to date took place, lasting 520 days—Mars-500, during which communication was also continuously monitored. Mars-500 simulated a flight to Mars in the full scale of its estimated 520-day duration [57, 60]. Sociomaps were continuously sent to the control center. The option of notifying the center about unusual or unexpected situations for possible intervention purposes was not utilized in this case, as the communication was relatively stable throughout the experiment, both in terms of quantity and quality. The entire communication progress may be viewed dynamically based on individual sociomaps created in regular 14-day intervals (36 administrations in total). The simulated landing on Mars occurred in February 2011, when the team was separated into two subteams—a landing and orbital team. Control center is included (Video 1 can be viewed at https://bit.ly/2ENYzja).
Even though the average correlation between the values of subsequently occurring sections was high (the average scale value of the test–retest 14-day correlation was 0.785 for the current communication and 0.843 for the optimal communication), a decrease could be observed in some cases. The test–retest correlations for the 16th and 17th collection, which took place before and after the landing, were −0.005 and 0.117, respectively [60]. Since each of the six crew members expressed their opinion about the remaining five members in the relational questions, 30 values were gathered in total in the individual collections. The following graph (Figure 5) shows the differences in absolute values between the actual degree of communication expressed on a five-point scale and the optimal communication value.
Differences between current and optimal communication in Mars-500 experiment.
The most visible change occurred during the landing period. The occurrence of misunderstandings negatively correlated with the overall level of current communication (r = −0.33), while it positively correlated with the expressed wish for a communication change (r = 0.42). Besides creating partial sociomaps, it is possible to aggregate the sociomap data, as well as that from the derived sociomap, for an extended period. That way, it is even possible to aggregate all 36 data collections into one sociomap expressing the interconnectedness of the individual crew members (Figure 6).
Aggregated sociomap of Mars-500 experiment.
The main linking factor among the crew members is person U, who is closer with pair R and S. The triplet U, R, and S, as well as G, E, and N, forms the Russian and non-Russian team subgroup, respectively. Communication within these subgroups is statistically higher than communication between (people from) both subgroups (p = 0.002, d = 1.28), which accentuates the importance of understanding linguistic and cultural aspects of communication and cooperation in crews. The Mars-500 experiment showed that this way of monitoring is sensitive enough (despite the high test–retest reliability of the scales) and that the crew can handle communication even in such long isolation periods without long-term deterioration. Based on our experience and research, we assume that monitoring alone can sensitize the crew to the importance of communication and instigate possible attempts to change this communication.
The advantages of monitoring communication using sociomapping continue to be examined in other experiments simulating space flights [61, 62, 63]. The interventions’ success is being researched experimentally and quasi-experimentally within work teams [53, 64, 65, 66, 67, 68]. The main source of our findings is all work teams we supported with sociomapping, some of which were being examined over the course of more than 3 years [52]. The second significant source is the usage of sociomaps in the Czech Army, where this method has been used in combat teams for 25 years [69].
From the experiments to date, which directly or indirectly simulate a flight to Mars, it can be deduced that psychosocial factors are critically important and their underestimation may even lead to a failure of the whole mission. Besides selecting suitable, stress-resistant individuals during the preflight phase, it is recommendable for the crew members to meet well in advance and for them to spend some time together in isolation before the actual flight. During this phase, it would be appropriate for the crew to be briefed with the issue at hand and with the usual development of the group dynamic, the methods that will help them capture it, and with the subsequent procedures of formulating a contract about what can be improved based on this data. We also recommend paying attention to a sensitization on cultural, linguistic, and gender aspects during the training and briefing prior to the actual flight. We also suggest for the team to familiarize itself with the way of conducting the debriefing, which improves its communication and performance. This is based not only on the meta-analysis, which showed a significant increase of the performance of teams that conduct debriefings [70], but also from the derived recommendations aimed specifically at space flights [71]. In the view of the communication delay between Earth and Mars, it is necessary to support the teams by leading them to conduct the debriefing based on an automated, structured protocol. For example, this could be sociomapping followed by a debate about how the communication is going and how it might be continuously improved. Throughout the mission, we recommend a regular monitoring of the communication with a possible discussion on improvement options. From time to time, the team “on Earth” should be included in such a discussion, so that this intervention can help strengthen the mutual ties and reduce the risks of possible displacement. Besides a debriefing, providing support or an intervention may also be considered in more difficult times. We also unequivocally suggest that the contact with close friends and relatives be available, which will decrease the sense of isolation. Monitoring communication using the sociomapping method will continue to be a part of the experiment in the Sirius project. After the Sirius 2017 [72] and Sirius 2019 experiments, the utilization of sociomapping is planned in the Sirius 2020 and 2021 experiments, as well. The team led by Kateřina Bernardová is now preparing not only a methodology of the measurement itself but also a methodology of team dynamic training and subsequent interventions similarly to the way the Czech Army has been using the system for the last 20 years [69].
I would like to thank the pioneer of Czech space research, military pilot, and sociologist Col. PhDr. Jaroslav Sýkora, as well as psychologist Col. PhDr. Kateřina Bernardová, founder of the Department of Psychosocial Services in the Czech Army, with whom I had the honor to collaborate for over 25 years. Col. PhDr Kateřina Bernardová was using sociomapping for interventions in combat units for over 20 years and now is leading Sirius project. I would like to thank PhDr. Eva Rozehnalová, PhD, for the collaboration on psychometric research of sociomapping, and RNDr. Cyril Höschl, PhD, for translating the idea of sociomapping into functioning algorithms and programs.
India commits to addressing climate change without compromising economic growth. It continues to expand its energy basket and reduce over-dependence on coal and oil. India is on the right path to managing its energy transition. It aims to increase the share of natural gas to 15% by 2030 [1] from 6.5% at present. Experts believe that India must go through multiple phases of the energy transition. In this context, many believe that natural gas could play the role of a transition fuel. However, we believe that natural gas has a more prominent role than just a bridge fuel. The government firmly pushes the adoption of natural gas as a clean fuel. In line with the United Nation’s sustainable development goal # 7 [2], natural gas offers a solution to ensure modern and clean energy is accessible to millions of customers at an affordable price in India. Further, natural gas is a viable and affordable solution to reduce pollution in cities and industries. The transport sector, one of the biggest CO2 emitters, stands to benefit from the higher penetration of natural gas in the country.
India’s natural gas market is at a growth stage. Its demand for natural gas has been growing steadily. India’s unsaturated market has the potential to expand gas demand at a faster rate. This section highlights natural gas reserves, domestic production, consumption, deficit, and import.
At the end of 2020, India’s proven natural gas reserves stood at 1.32 trillion cubic meters (TCM) compared to just 0.731 TCM in 2000, 80.5% growth in 20 years. Despite India’s rising natural gas reserves, its share is just 0.7% of the global reserves. Asia-Pacific, the world’s most populous region holds 8.8% of the global reserves. In this region, China leads the table with a 4.5% share followed by Australia, India, Indonesia, and others. Global natural gas resources are quite unevenly distributed. Russia, Iran, and Qatar hold 19.9%, 17.1%, and 13.1% of the global reserves, respectively. These three countries collectively controlled 50% of the global natural gas reserves of 188 TCM in 2020 (Figure 1).
Proven natural gas reserves in India. Source: prepared by the authors using Statistical Review of World Energy 2021.
India’s natural gas production has been a cause of concern for the government and the operating companies. The consuming industries, especially the power and fertilizer producers are at the receiving end. The falling natural gas production has severely impacted the power and fertilizer producers. If India continues to produce at the current rate the reserve to production ratio (R/P) suggests that natural gas can last for 56 years. However, the production rate is bound to increase in the future (Figure 2), thereby the R/P ratio will fall.
India’s domestic natural gas production.
Petroleum and Natural Gas Regulatory Board (PNGRB), India had commissioned an industry study in 2011 to assess the realistic demand of natural gas by 2029–2030. The purpose was to advise the government about the development of related infrastructure for making the natural gas available, transport, creating re-gasification plants, and supply to various sectors. The industry group submitted its report in 2013. PNGRB projected that the demand for natural gas to expand up to 746 million standard cubic meters per day (MMSCMD) (Table 1) in 2029–2030 from the actual consumption of 176 MMSCMD in 2010–2011.
Consuming industry/sector | 2021–2022 | 2026–2027 | 2029–2030 |
---|---|---|---|
Power | 238.88 | 308.88 | 353.88 |
Fertilizer | 107.85 | 110.05 | 110.05 |
City gas distribution | 46.25 | 67.96 | 85.61 |
Industrial | 37.00 | 52.06 | 63.91 |
Petchem/refineries/Int. Cons | 81.99 | 103.41 | 118.85 |
Sponge iron/steel | 10.00 | 12.19 | 13.73 |
Total realistic demand | 516.97 | 654.55 | 746.03 |
Petroleum Planning and Analysis Cell (PPAC) records suggest that the average consumption of natural gas in the first 4 months of the financial year (FY) 2021–2022 was around 171 MMSCMD, which was 316 MMSCMD lower than the PNGRB projections. In fact, from the year 2012–2013 till 2020–2021, the trend of consumption of natural gas had been significantly lower than PNGRB’s projections. India achieved about 34% of the natural gas demand projections for the FY 2020–2021 compared to 65% achievement in 2012–2013 (Table 2). During the said period, consumption of natural gas increased marginally but the actual consumption was markedly lower than the projections. The widening gap between projected demand and actual consumption could be due to sluggish natural gas demand in the industries and transport sector. The reasons for sluggish demand and slow penetration of natural gas could be ascribed to a combination of factors including lower domestic natural gas production, high import price, and infrastructure bottlenecks.
Year | Projection | Actual consumption | Achievement against projections | ||
---|---|---|---|---|---|
Domestic | Import | Total | |||
2012–2013 | 242.66 | 108.91 | 48.26 | 157.17 | 64.8% |
2013–2014 | 265.33 | 94.72 | 48.77 | 143.49 | 54.1% |
2014–2015 | 289.52 | 89.57 | 50.98 | 140.55 | 48.5% |
2015–2016 | 326.16 | 85.29 | 58.60 | 143.89 | 44.1% |
2016–2017 | 378.06 | 84.51 | 68.08 | 152.59 | 40.4% |
2017–2018 | 409.05 | 86.93 | 75.18 | 162.11 | 39.6% |
2018–2019 | 438.02 | 87.83 | 78.74 | 166.57 | 38.0% |
2019–2020 | 465.19 | 82.90 | 92.84 | 175.74 | 37.8% |
2020–2021 | 490.76 | 76.12 | 90.03 | 166.15 | 33.9% |
Natural gas consumption in India (MMSCMD).
Source: prepared by the authors based on projections of PNGRB [3] and actual consumption data of PPAC.
Arguably, the natural gas market development was slower than expectations. The natural gas market development was largely dependent on the ample supply of domestic natural gas at affordable prices [4]. The user of natural gas in power plants, fertilizer plants, cement plants, ceramic industries, refineries, and petrochemical plants were expected to strongly drive natural gas market development, which did not happen.
The gas-based power plants expected domestic gas to address their long-standing supply concerns. Unfortunately, falling domestic natural gas production aggravated their pain points. The natural gas consumption by power plants declined from 22,628 MMSCM in 2011–2012 to 11,020 MMSCM in 2019–202020. The share of natural gas consumption by power plants fell from 35% in 2011–2012 to 17% in 2019–20. During the period, natural gas consumption in refineries, fertilizer plants, and the city gas distribution (CGD) network improved (Figure 3). The government prioritized natural gas allocation to the CGD network, especially for the domestic and transport segments, which resulted in higher consumption.
Natural gas consumption by selected sectors in India [
It is evident from Table 2 that domestic supply shrank from approximately 109 MMSCMD in 2012–2013 to 76 MMSCMD. Consequently, during the same period, liquefied natural gas (LNG) import increased from 48 MMSCMD to 90 MMSCMD. LNG import registered 88.5% growth to maintain the share of natural gas and meet rising natural gas demand.
The higher contribution of natural gas in India’s primary energy basket will be severely constrained without boosting demand in the industries, especially power and fertilizer plants. The refineries, petrochemical plants, and CGD network will continue to augment natural gas consumption. CARE Ratings—a leading credit rating agency [6] indicated that higher urea production will foster demand for natural gas. However, the fertilizer plants will need natural gas supply at a competitive price, supply of domestic natural gas will be desirable.
India’s natural gas domestic production has been lower than consumption. It is evident from Figure 4 that natural gas consumption has been fluctuating. The slack domestic natural gas production failed to meet the demand, therefore, the deficit kept widening. So, India’s dependence on natural gas imports continued to rise. Due to a lack of import options through a pipeline, India primarily relied on the import of liquefied natural gas (LNG).
India’s widening natural gas deficit. Source: prepared by the authors using PPAC data [
Globally LNG trade registered a strong improvement over the previous decade. By December 2020, global LNG trade reached 350 million tons. By February 2021, the global LNG regasification capacity in 39 markets hit 850 million tons per annum (MMTPA). According to the International Gas Union Report (2021), the leading natural gas deficit countries like Japan, China, South Korea, India, and Spain depended on LNG imports. The rising demand of LNG in the Asia-pacific region resulted in the liquefaction capacity addition in the middle east, Russia, and Australia.
Due to India’s rising natural gas deficit the import of LNG escalated from 18 billion cubic meters (BCM) in 2012 to 33.8 BCM in 2020 (Figure 5). Owing to severe Covid-19 linked disruptions including national and state lockdowns, natural gas consumption slowed down in 2020–2021. As a result, the import of LNG was marginally lower than the previous year. India largely depended on Qatar for its LNG import. However, newer import destinations like Russia and USA offered an opportunity to reduce over-dependence on any single-sourcing country.
LNG import in India. Source: prepared by the authors using data available on the PPAC website [
India’s LNG import would continue to increase in the near and long term. Recently Petronet LNG CEO stated that “India needed to increase its LNG import capacity to 155 MMTPA considering 80% utilization to enhance the use of the cleaner fuel” [8]. The capacity expansion will depend on pipeline connectivity for evacuating re-gasified LNG (R-LNG), the price of imported LNG, and acceptance of R-LNG at the price point by the consuming industries. High LNG price often hampers buyer acceptance; therefore, it slows down LNG infrastructure development. However, investment in LNG infrastructure is long-term in nature, so temporary LNG price fluctuations should not deter LNG infrastructure build-up.
India aspires to raise natural gas’s share to 15% by 2030 from 6.5% in 2020, which necessitates the development of associated infrastructure. Often the natural consumption centers are away from production centers, so pipeline connectivity or virtual pipelines are critical to meet the demand. India’s natural gas grid would expand to 32,559 km from the existing operational network of 17,016 km (Table 3).
Pipeline | Authorized length (km) | Authorized capacity (MMSCMD) | |
---|---|---|---|
1 | Operational natural gas pipelines | 12,654 | 337.3 |
2 | Natural gas pipelines partly commissioned# | 13,680 | 406.5 |
3 | Natural gas pipelines under construction | 6225 | 180.9 |
Total | 32,559 | 924.7 |
India’s natural gas grid (as on June 30, 2020).
Commissioned length 4362 km.
Source: compiled from published sources [9].
India’s plan for creating an interconnected “National Gas Grid” shall support the wider supply and distribution of R-LNG throughout the nation. Indian natural gas pipeline network is less penetrated compared to the developed countries. At present, for every million population only about 12.3 km of natural gas pipeline exists in India. India’s 17,016 km of natural pipeline network is insufficient to connect all demand centers. Therefore, the government wants to develop a pan-India natural gas grid of 32,559 km, which can address the existing regional disparities of the natural gas pipeline network. A fully functional national gas grid will improve natural gas accessibility throughout India.
As per the data available on the Petroleum Planning and Analysis Cell website the average capacity utilization of natural gas pipelines stood at 54% during 2018–2019. Only nine pipelines had capacity utilization above 50% and Dahej-Vijaipur (DVPL)-Vijaipur-Dadri (GREP) pipeline had a capacity utilization of 67% and Dabhol-Bengaluru Pipeline (Including spur) had 8% capacity utilization. Most of the existing pipelines are underutilized and the operators are trying to enhance the productivity of the pipelines. Pipeline Infrastructure Limited, now the owner of East-West Pipeline has decided to inject green hydrogen into its pipeline, which will help improving the capacity utilization of the pipeline.
Natural gas consumption should expand from 165–170 MMSCMD to 640–700 MMSCMD by 2030 to reach 15% of primary energy consumption. Given the fact that domestic production may not go beyond 100 MMCMD from the current levels of 75 MMSCMD, the gap shall have to be filled with the import of LNG for which adequate regasification terminals should be created. At end of 2020, India had six operational LNG terminals with a cumulative capacity of 42.5 MMTPA (Table 4). Petronet LNG Limited operated the largest LNG terminal at Dahej, Gujarat with a capacity of 17.5 MMTPA. The Petronet LNG Limited was the largest operator with 54% of the total commissioned LNG terminal capacity. The Dahej and Kochi terminals handled 254 and 14 LNG cargoes respectively in the financial year 2020–2021. Utilization of Kochi terminal improved due to commissioning of Mangalore section of GAIL’s Kochi Mangalore pipeline in 2020–2021.
Sl. no. | Place | State | Developer(s) | Year of commissioning | Annual capacity (MMTPA) |
---|---|---|---|---|---|
Commissioned | |||||
1 | Dahej | Gujarat | Petronet LNG Limited (PLL) | 2004 | 17.5 |
2 | Hazira | Gujarat | Shell Energy India | 2005 | 5 |
3 | Dabhol | Maharashtra | GAIL (India) Limited | 2013 | 5 |
4 | Kochi | Kerala | PLL | 2013 | 5 |
5 | Ennore | Tamil Nadu | Indian Oil Corporation | 2019 | 5 |
6 | Mundra | Gujarat | GSPC LNG | 2020 | 5 |
Total commissioned | 42.5 | ||||
Under construction | |||||
7 | Jaigarh | Maharashtra | Western Concessions Private Limited | 2021* | 5 |
8 | Dhamra | Odisha | Adani-Total | 2022* | 5 |
9 | Jafrabad | Gujarat | Swan LNG | 2022* | 5 |
10 | Chhara | Gujarat | HPCL & Shapoorji Pallonji Group | 2022* | 5 |
Total under construction | 20 | ||||
Grand total | 62.5 |
Upcoming LNG terminals in Jaigarh (Floating Storage and Regasification Unit), Dhamra, Jafrabad (Floating Storage Regasification Unit), and Chhara will strengthen India’s LNG infrastructure. Especially, the LNG terminal in Dhamra, Odisha will augment natural gas supply in eastern India and enhance natural gas penetration in the underpenetrated demand centers. Dhamra LNG terminal can expand its capacity up to 10 MMTPA. Dhamra will bolster the CGD network development in Odisha, West Bengal, and Bihar. LNG infrastructure development now spreads across the coastal states in the country, which was not the case earlier. Even then the share of LNG infrastructure is still concentrated in the west coast of India. Well-developed ports, natural gas pipeline connectivity, and early adoption of natural gas in Gujarat, and Maharashtra supported LNG infrastructure in the west coast. On the contrary, despite the strong coastal presence, the eastern and southern states like Odisha, West Bengal, Andhra Pradesh, and Tamil Nadu remained less attractive for developing LNG terminals.
In the coming years, LNG will have greater use, especially LNG as a transport fuel, which will create a market for LNG. Considering the emerging market scenario, LNG has significant growth potential. The new and upcoming consumption centers will create additional demand for LNG.
The existing capacity of LNG regasification terminals will not meet the rising demand. Therefore, the existing LNG infrastructure requires much-needed augmentation to address the supply concerns. So, there is an urgent requirement of creating additional LNG regasification capacity to the tune of 75–80 MMTPA.
Apart from the anchor customers like the power/fertilizer/petrochemical plants, and the refineries, the City Gas Distribution would remain the other most important sector. The government wanted to boost clean fuel adoption in the transport, domestic, and transport sectors, so PNGRB granted 136 authorizations to CGD entities under the 9th and 10th rounds of bidding. This has the potential to cover 53% of the geographical area (GA) of the country and 70% of the population. The number of compressed natural gas (CNG) stations will increase from existing 1838 to over 10,000. In the same way, the number of domestic PNG connections is proposed to be increased from 5.5 million to 40 million. The CGD sector will need investment in the range of Rs. 900–1200 billion by 2030.
The CGD networks growth has taken off only in the last 5–6 years. The historical progress of the award of CGD networks is given in Table 5.
Category | Year | Category-wise % area of India | Cumulative | Category-wise population coverage (%) | Cumulative population coverage (%) | Category-wise GA | Cumulative GA | |
---|---|---|---|---|---|---|---|---|
1 | Pre-PNGRB | 3.02 | 3.02 | 9.67 | 9.67 | 31 | 31 | |
2 | Round 1 | 2008 | 0.03 | 3.05 | 0.33 | 10.00 | 6 | 37 |
3 | Round 2 | 2009 | 0.03 | 3.08 | 0.23 | 10.23 | 3 | 40 |
4 | Round 3 | 2010 | 1.21 | 4.29 | 0.77 | 11.00 | 6 | 46 |
5 | Round 4 | 2013 | 1.29 | 5.58 | 2.27 | 13.27 | 9 | 55 |
6 | Round 5 | 2015 | 1.82 | 7.40 | 2.04 | 15.31 | 8 | 63 |
7 | Round 6 | 2015 | 2.02 | 9.42 | 2.07 | 17.38 | 18 | 81 |
8 | Round 7 | 2016 | 0.46 | 9.88 | 0.36 | 17.74 | 1 | 82 |
9 | Round 8 | 2016 | 0.57 | 10.45 | 0.94 | 18.68 | 6 | 88 |
10 | Section 42 | 0.61 | 11.06 | 1.57 | 20.25 | 6 | 94 | |
11 | Round 9 | 2018 | 23.82 | 34.88 | 26.38 | 46.63 | 86 | 180 |
12 | Round 10 | 2018 | 19.92 | 52.8 | 24.32 | 70.86 | 50 | 230 |
In addition to the above, PNGRB has already announced the 11th round of bidding under which an additional 65 geographical areas could get a CGD network. The government and the PNGRB are constantly striving to expand the CGD network in the country. The government offers the necessary push to build up CGD infrastructure across the country. However, the shift from competing fuels to natural gas will take place only when it becomes cost-competitive. Customers are primarily concerned about the economics of natural gas vs. the competing fuels [16, 17], therefore availability of domestic natural gas or imported LNG at a competitive price will improve the adoption of natural gas.
In addition to the domestic, transport, and industrial segments, there are multiple areas where natural gas could find users. Room heating and cooling offer opportunities for use of natural gas. Higher penetration of the CGD network will facilitate the adoption of CNG for intra-city transport, especially public transport. Despite the economic advantage of CNG over competing fuel, CNG refueling stations remained a major hurdle for inter-city travel. Within the city, mobile refueling units (MRUs) could address refueling concerns as the customers can refuel at their doorstep. MRUs have been working successfully in countries like Mexico, Colombia, Peru, Indonesia, Vietnam, Russia, Korea, etc. India introduced its first MRU (CNG) in June 2021. Due to its flexibility, cost efficiency, and convenience, it has the potential to expand across the country.
The telecom service tower could shift to natural gas/LNG-based generators from diesel generators. There are over 5,20,000 such towers on a pan-India basis and growing. These generators use diesel in case of power outages. The use of natural gas/LNG will be economical as well as environment friendly. LNG use for long-distance transport, inland waterways, LNG bunkering in fishing/marine vessels offers considerable opportunities for adoption as a cleaner fuel.
In addition to the above, the CGD sector will throw open ample opportunities for equipment and spare suppliers in the areas like mechanical meters, smart meters, PNG regulators, PE pipes, online compressor, booster compressor, dispenser, and cascade, etc.
Expansion of the natural gas market will bring along several benefits like socio-economic empowerment, import-substitution, emission reduction, and green energy solutions at affordable prices. Further, natural gas shall address India’s energy security concerns to a greater extent.
The government and regulators have created a conducive environment for investment in gas market development. Consequently, large private players are involved in the entire natural gas value chain. Domestic natural gas allocation policy prioritized gas allocation to the CGD sector, which catalyzes market expansion.
The domestic gas price trends (Figure 6) suggest that the market-based pricing mechanism augurs well for the market development. The domestic natural gas price was fixed at $2.90 per million British thermal units (mbtu) for October 2021–March 2022. The ceiling price for natural gas was fixed at $6.13 per mBtu for October 2021–March 2022.
Domestic natural gas price trend in India. Source: prepared by the authors using PPAC data [
The government’s decision to develop a pan-India natural gas grid will be one of the biggest enablers for gas market growth. Less penetrated regional markets in north-east, east, and south India will get access to natural gas. The availability of natural gas will boost industrial, economic, and social progress in those regions.
For a long period impediments like insufficient infrastructure for the import of natural gas, low cross-country pipeline penetration, and lack of cost-competitiveness of natural gas hampered market growth in India. Despite rising environmental concerns and lower emphasis on polluting fuel, natural gas faces continued challenges from coal. Further, falling renewable electricity price challenges natural gas’s cost competitiveness. The high cost of imported LNG becomes a dampener for power plants to use natural gas. Insufficient availability of domestic natural gas does not offer any hope for the stranded power plants. The Standing Committee on Energy (2020–2021) in its eleventh report pointed out that change in domestic gas allocation policy adversely impacted the stranded power plants. This committee observed that the gas-based power plants which developed based on assured domestic gas supply are unviable on imported R-LNG [19]. High R-LNG price, which is at times twice the price of domestic gas is not sustainable for power plants. Therefore, most of the natural gas-stranded power plants are stressed assets.
The ministry of power stated that the unit cost of power produced from imported R-LNG was around Rs.7/kWh [19], which was expensive compared to coal and renewable power. Solar-based power cost has declined to a record low of Rs 2/kWh, which is comparable to coal-based electricity cost.
Natural gas has been kept outside the purview of goods & services tax (GST), which is an impediment for growth of the sector. Various industry bodies including the Federation of Indian Petroleum Industry recommend bringing natural gas under the ambit of GST [20]. The current tax regime allows states to levy varying amounts of value-added tax, which goes against “one nation one tax” philosophy. Further, buyers of natural gas do not get input credit, consequently, it adds up to the production cost of the industrial customer.
Lack of sufficient cross-country pipeline network remains a major impediment for natural gas market development. The pipeline network has better connectivity in the west coast compared to eastern and north-eastern India. However, the government has taken several steps to build pan-India natural gas pipeline network.
The government has been pushing for expansion of the natural gas market with a heightened focus on increasing city gas distribution network penetration including CNG at retail outlets across the country. Further, the government emphasizes building cross country pipeline networks to remove the supply bottleneck. The government offers viability gap funding for the infrastructure build-up. For instance, the government committed 60% viability gap funding for Northeast Gas Grid with an estimated project cost of Rs 92.65 billion [21]. The Indradhanush Gas Grid Limited shall connect eight north-eastern states with a 1656 km natural gas pipeline. The government encourages investors to develop LNG terminals for import of LNG and regasification of LNG. In addition, it aspires for developing 1000 LNG refueling stations across all the major “highways, industrial corridors, and mining areas”. LNG refueling stations development would attract investment of Rs. 100 billion soon. The first 50 LNG refueling outlets shall be along the golden quadrilateral and major national highways [22]. Ministry of Petroleum and Natural Gas must strongly push for including natural gas in the GST regime. Such a move will bring tax rationality and benefit customers across the country.
The presence of an active and independent regulator in the form Petroleum and Natural Gas Regulatory Board serves as an enabler for faster progress of the natural gas market in India [4]. The regulator brings transparency and establishes fair competition.
India’s under-penetrated natural gas market will expand till it saturates. There are plenty of scopes for expansion in the north-east, eastern, and southern India. City gas distribution will be a prime driver for natural gas market growth. The existing infrastructure including LNG importing terminals, pipelines, and refueling stations needs a boost. Despite the emergence of multiple green energy options, the share of natural gas will increase. The government’s progressive policies including viability gap funding for cross-country pipeline and promotion of LNG/hydrogen-CNG as transport fuels will spur natural gas market developments. Additionally, the government is committed to removing the bottlenecks to enhance penetration of natural in the country. Natural gas will play a critical role in developing India’s green economy.
Authors are thankful to the editors and anonymous reviewers for their comments and observations.
The authors declare no conflict of interest.
Btu | British thermal unit |
BCM | billion cubic meter |
CGD | city gas distribution |
CNG | compressed natural gas |
LNG | liquefied petroleum gas |
MMTPA | million tons per annum |
MMSCMD | million standard cubic meter per day |
PNGRB | Petroleum and Natural Gas Regulatory Board |
Rs. | Indian rupee |
TCM | trillion cubic meter |
CARE | Credit Analysis & Research Ltd |
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. 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. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. His current research interests are in the fields of intelligent control and robotics.",institutionString:null,institution:{name:"Technical University of Sofia",country:{name:"Bulgaria"}}},{id:"585",title:"Prof.",name:"Munir",middleName:null,surname:"Merdan",slug:"munir-merdan",fullName:"Munir Merdan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/585/images/system/585.jpg",biography:"Munir Merdan received the M.Sc. degree in mechanical engineering from the Technical University of Sarajevo, Bosnia and Herzegovina, in 2001, and the Ph.D. degree in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 2009.Since 2005, he has been at the Automation and Control Institute, Vienna University of Technology, where he is currently a Senior Researcher. His research interests include the application of agent technology for achieving agile control in the manufacturing environment.",institutionString:null,institution:null},{id:"605",title:"Prof",name:"Dil",middleName:null,surname:"Hussain",slug:"dil-hussain",fullName:"Dil Hussain",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/605/images/system/605.jpg",biography:"Dr. Dil Muhammad Akbar Hussain is a professor of Electronics Engineering & Computer Science at the Department of Energy Technology, Aalborg University Denmark. Professor Akbar has a Master degree in Digital Electronics from Govt. College University, Lahore Pakistan and a P-hD degree in Control Engineering from the School of Engineering and Applied Sciences, University of Sussex United Kingdom. Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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Oxidative stress has been considered a major contributory factor to the diseases. They are mainly derived from oxygen (reactive oxygen species (ROS)) and nitrogen (reactive nitrogen species (RNS)) and are generated in our body by various endogenous systems and exposure to different physicochemical conditions or pathophysiological states. Free radical damage to protein can result in loss of enzyme activity. There are epidemiological evidences correlating higher intake of components/foods with antioxidant abilities to lower incidence of various human morbidities or mortalities. The sources and origin of antioxidants which include fruits and vegetables, meats, poultry, and fish were treated in this study. The classification and characteristics of antioxidant, its measurements and level in food and free radicals, were also documented. The chemistry of antioxidants which includes chain reactions, molecular structures, food antioxidants and reaction mechanisms, biochemical activity, therapeutic properties, and future choice of antioxidants was reported in this review.",book:{id:"8323",slug:"traditional-and-complementary-medicine",title:"Traditional and Complementary Medicine",fullTitle:"Traditional and Complementary Medicine"},signatures:"Arun Rasheed and Rinshana Fathima Abdul Azeez",authors:[{id:"277345",title:"Dr.",name:"Arun",middleName:null,surname:"Rasheed",slug:"arun-rasheed",fullName:"Arun Rasheed"}]},{id:"66587",title:"Introductory Chapter: Plant Extracts",slug:"introductory-chapter-plant-extracts",totalDownloads:1773,totalCrossrefCites:3,totalDimensionsCites:3,abstract:null,book:{id:"8593",slug:"plant-extracts",title:"Plant Extracts",fullTitle:"Plant Extracts"},signatures:"Aman Dekebo",authors:[{id:"191684",title:"Dr.",name:"Aman",middleName:null,surname:"Dekebo",slug:"aman-dekebo",fullName:"Aman Dekebo"}]}],onlineFirstChaptersFilter:{topicId:"199",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:31,numberOfPublishedChapters:314,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:11,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:105,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:17,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:14,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"June 11th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). 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He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,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. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:19,paginationItems:[{id:"82196",title:"Multi-Features Assisted Age Invariant Face Recognition and Retrieval Using CNN with Scale Invariant Heat Kernel Signature",doi:"10.5772/intechopen.104944",signatures:"Kamarajugadda Kishore Kumar and Movva Pavani",slug:"multi-features-assisted-age-invariant-face-recognition-and-retrieval-using-cnn-with-scale-invariant-",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"82063",title:"Evaluating Similarities and Differences between Machine Learning and Traditional Statistical Modeling in Healthcare Analytics",doi:"10.5772/intechopen.105116",signatures:"Michele Bennett, Ewa J. Kleczyk, Karin Hayes and Rajesh Mehta",slug:"evaluating-similarities-and-differences-between-machine-learning-and-traditional-statistical-modelin",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Machine Learning and Data Mining - Annual Volume 2022",coverURL:"https://cdn.intechopen.com/books/images_new/11422.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"81791",title:"Self-Supervised Contrastive Representation Learning in Computer Vision",doi:"10.5772/intechopen.104785",signatures:"Yalin Bastanlar and Semih Orhan",slug:"self-supervised-contrastive-representation-learning-in-computer-vision",totalDownloads:23,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"79345",title:"Application of Jump Diffusion Models in Insurance Claim Estimation",doi:"10.5772/intechopen.99853",signatures:"Leonard Mushunje, Chiedza Elvina Mashiri, Edina Chandiwana and Maxwell Mashasha",slug:"application-of-jump-diffusion-models-in-insurance-claim-estimation-1",totalDownloads:8,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Data Clustering",coverURL:"https://cdn.intechopen.com/books/images_new/10820.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}}]},overviewPagePublishedBooks:{paginationCount:9,paginationItems:[{type:"book",id:"7723",title:"Artificial Intelligence",subtitle:"Applications in Medicine and Biology",coverURL:"https://cdn.intechopen.com/books/images_new/7723.jpg",slug:"artificial-intelligence-applications-in-medicine-and-biology",publishedDate:"July 31st 2019",editedByType:"Edited by",bookSignature:"Marco Antonio Aceves-Fernandez",hash:"a3852659e727f95c98c740ed98146011",volumeInSeries:1,fullTitle:"Artificial Intelligence - Applications in Medicine and Biology",editors:[{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}}]},{type:"book",id:"7726",title:"Swarm Intelligence",subtitle:"Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/7726.jpg",slug:"swarm-intelligence-recent-advances-new-perspectives-and-applications",publishedDate:"December 4th 2019",editedByType:"Edited by",bookSignature:"Javier Del Ser, Esther Villar and Eneko Osaba",hash:"e7ea7e74ce7a7a8e5359629e07c68d31",volumeInSeries:2,fullTitle:"Swarm Intelligence - Recent Advances, New Perspectives and Applications",editors:[{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",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. 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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. 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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. 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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:"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:"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"}}}]}},subseries:{item:{id:"40",type:"subseries",title:"Ecosystems and Biodiversity",keywords:"Ecosystems, Biodiversity, Fauna, Taxonomy, Invasive species, Destruction of habitats, Overexploitation of natural resources, Pollution, Global warming, Conservation of natural spaces, Bioremediation",scope:"