Commercial sorghum parent lines and accessions.
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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:"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"},{slug:"intechopen-identified-as-one-of-the-most-significant-contributor-to-oa-book-growth-in-doab-20210809",title:"IntechOpen Identified as One of the Most Significant Contributors to OA Book Growth in DOAB"}]},book:{item:{type:"book",id:"9685",leadTitle:null,fullTitle:"Agroecosystems – Very Complex Environmental Systems",title:"Agroecosystems",subtitle:"Very Complex Environmental Systems",reviewType:"peer-reviewed",abstract:"This book, “Agroecosystems – Very Complex Environmental Systems”, aims to present an update on different aspects associated with the importance of sustainable agriculture. It was our intention to gather information from diverse sources in this volume and to give some real-life examples, extending the appreciation of the complexity of this subject in a way that may stimulate new approaches in relevant fields.",isbn:"978-1-83880-528-9",printIsbn:"978-1-83880-384-1",pdfIsbn:"978-1-83880-529-6",doi:"10.5772/intechopen.87489",price:119,priceEur:129,priceUsd:155,slug:"agroecosystems-very-complex-environmental-systems",numberOfPages:162,isOpenForSubmission:!1,isInWos:1,isInBkci:!1,hash:"c44f7b43a9f9610c243dc32300d37df6",bookSignature:"Marcelo L. Larramendy and Sonia Soloneski",publishedDate:"April 7th 2021",coverURL:"https://cdn.intechopen.com/books/images_new/9685.jpg",numberOfDownloads:3747,numberOfWosCitations:2,numberOfCrossrefCitations:4,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:5,numberOfDimensionsCitationsByBook:0,hasAltmetrics:0,numberOfTotalCitations:11,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 15th 2019",dateEndSecondStepPublish:"March 5th 2020",dateEndThirdStepPublish:"May 4th 2020",dateEndFourthStepPublish:"July 23rd 2020",dateEndFifthStepPublish:"September 21st 2020",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"14764",title:"Dr.",name:"Marcelo L.",middleName:null,surname:"Larramendy",slug:"marcelo-l.-larramendy",fullName:"Marcelo L. Larramendy",profilePictureURL:"https://mts.intechopen.com/storage/users/14764/images/system/14764.jpg",biography:"Marcelo L. Larramendy, Ph.D., serves as Professor of Molecular Cell Biology at the School of Natural Sciences and Museum (National University of La Plata, Argentina). Appointed Senior Researcher of the National Scientific and Technological Research Council of Argentina. Former Member of the Executive Committee of the Latin American Association of Environmental Mutagenesis, Teratogenesis and Carcinogenesis. Author of more than 450 contributions, including scientific publications, research communications and conferences worldwide. Recipient of several national and international awards. Prof. Larramendy is a regular Lecturer at the international A. Hollaender Courses organized by the IAEMS and former guest scientist at NIH (USA) and the University of Helsinki, (Finland). He is an expert in Genetic Toxicology and is, or has been, referee for more than 20 international scientific journals. Member of the International Panel of Experts at the International Agency for Research on Cancer (IARC, WHO, Lyon, France) in 2015 for the evaluation of DDT, 2,4-D and Lindane. Presently, Prof. Dr. Larramendy is Head of the Laboratory of Molecular Cytogenetics and Genotoxicology at the UNLP.",institutionString:"National University of La Plata",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"20",institution:{name:"National University of La Plata",institutionURL:null,country:{name:"Argentina"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"14863",title:"Dr.",name:"Sonia",middleName:null,surname:"Soloneski",slug:"sonia-soloneski",fullName:"Sonia Soloneski",profilePictureURL:"https://mts.intechopen.com/storage/users/14863/images/system/14863.jpg",biography:"Sonia Soloneski has a Ph.D. in Natural Sciences and is Assistant Professor of Molecular Cell Biology at the School of Natural Sciences and Museum of La Plata, National University of La Plata, Argentina. She is a member of the National Scientific and Technological Research Council (CONICET) of Argentina in the Genetic Toxicology field, the Latin American Association of Environmental Mutagenesis, Teratogenesis and Carcinogenesis (ALAMCTA), the Argentinean Society of Toxicology (ATA), the Argentinean Society of Biology (SAB) and the Society of Environmental Toxicology and Chemistry (SETAC). She has authored more than 380 contributions in the field, including scientific publications in peer-reviewed journals and research communications. She has served as a review member for more than 30 scientific international journals. She has been a plenary speaker in scientific conferences and a member of scientific committees. She is a specialist in issues related to Genetic Toxicology, Mutagenesis, and Ecotoxicology.",institutionString:"National University of La Plata",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"7",institution:{name:"National University of La Plata",institutionURL:null,country:{name:"Argentina"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"307",title:"Agroecology",slug:"agroecology"}],chapters:[{id:"71812",title:"Fungal Endophytes: Australian Terrestrial Orchids",doi:"10.5772/intechopen.91976",slug:"fungal-endophytes-australian-terrestrial-orchids",totalDownloads:570,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Orchids are unique as they lack a functional rooting system and share an obligate relationship with their fungal symbionts. This relationship supports their host’s nutritional demands from seed germination to its later development. The orchid fungal endophytes explore large areas in the soil as, to which orchid roots have no access, and thus acquire both organic and inorganic nutrients beyond the depletion zone at low carbon cost. Both ‘autotrophic’ (green) and ‘mycoheterotrophic’ species occur in the Orchidaceae, but the term ‘mixotrophic’ is possibly a truer description of the carbon economy of many green orchids. Some of the major ecological threats of an Australian landscape are habitat destruction and fragmentation. There is little known about the nutritional sources and saprophytic ability of orchid mycorrhizal fungi (OMF) and their role in providing nutrition to orchids. However, several integrated approaches have been developed for the conservation, management and restoration of these plants in wild but there is an urgent need to set appropriate conservation priorities to prevent the loss of habitats for these endangered species in terms of their fungal endophytes. This chapter focuses on the protection of these endangered Australian orchid species by understanding the nutritional behavior of their endophytes.",signatures:"Shalika Mehra",downloadPdfUrl:"/chapter/pdf-download/71812",previewPdfUrl:"/chapter/pdf-preview/71812",authors:[{id:"315183",title:"Dr.",name:"Shalika",surname:"Mehra",slug:"shalika-mehra",fullName:"Shalika Mehra"}],corrections:null},{id:"72341",title:"Impact Brassinolide on Two Fig Varieties",doi:"10.5772/intechopen.92655",slug:"impact-brassinolide-on-two-fig-varieties",totalDownloads:313,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Brassinolide (BL) is a plant hormone showing wide occurrence in the plant kingdom with unique biological effects on growth and physiological traits. The fig varieties, Improved Brown Turkey (IBT) and Masui Dauphine (MD), are commonly found in Indonesia and Malaysia. There is limited information on exogenous brassinolide application on these varieties. In this chapter, we present the effect of different concentration of exogenous application of BL on growth and physiological changes of fig. Increasing BL concentration (50, 100, and 200 ml.L−1) caused some differences in growth and physiological changes of fig, but the differences were not consistent and most of the changes happened only in first or second month. Cultivar IBT showed higher growth and physiological changes than cultivar MD after receiving brassinolide treatment. There was significant effect of interaction between brassinolide and variety on growth and physiological changes of fig except in plant height and total dry biomass.",signatures:"Zulias Mardinata, Mardaleni and Tengku Edy Sabli",downloadPdfUrl:"/chapter/pdf-download/72341",previewPdfUrl:"/chapter/pdf-preview/72341",authors:[{id:"318963",title:"Dr.",name:"Zulias",surname:"Mardinata Zulkarnaini",slug:"zulias-mardinata-zulkarnaini",fullName:"Zulias Mardinata Zulkarnaini"},{id:"346266",title:"Dr.",name:"Mardaleni",surname:null,slug:"mardaleni",fullName:"Mardaleni null"},{id:"346267",title:"Dr.",name:"Tengku Edy",surname:"Sabli",slug:"tengku-edy-sabli",fullName:"Tengku Edy Sabli"}],corrections:null},{id:"73090",title:"The Creation of Resistant Berries’ Agrobiocenosis",doi:"10.5772/intechopen.92698",slug:"the-creation-of-resistant-berries-agrobiocenosis",totalDownloads:252,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In conditions of increasing differences in the hydrothermal regime of the environment, all known adaptation mechanisms should be used fully, as at the level of individual varieties and at agrobiocenosis in general. The modern gardener needs high-productive, adapted to the growing conditions varieties of the Fragária × ananássa Durh. The resistant varieties of the Fragária × ananássa Durh. to negative environmental conditions is a basic characteristic, which shows an economic value and the effectiveness of their cultivation in an actual zone. The main physiological and biochemical indicators of resistance during autumn hardening and after temperature stress in winter are changes in the antioxidant system, interruptions of the protein-carbohydrate complex, accumulation products of membran’s lipoperoxidation, and changes in the fractional composition of water in leaves. The Fragária × ananássa Durh. production process is characterized by the following physiological parameters: pigment analysis, photochemical activity of isolated chloroplasts, respiration, and net photosynthesis productivity. Studies of physiological and biochemical resources of resistance to abiotic stress factors and productivity of Fragária × ananássa Durh. are shown. As a result of the carried studies, perspective variety of the Fragária × ananássa Durh. (“Tzaritza”) was identified for the creation of resistance berries’ agrobiocenosis.",signatures:"Zoya Evgenievna Ozherelieva, Pavel Sergeevich Prudnikov, Diana Aleksandrovna Krivushina, Marina Ivanovna Zubkova and Anna Androsova",downloadPdfUrl:"/chapter/pdf-download/73090",previewPdfUrl:"/chapter/pdf-preview/73090",authors:[{id:"319385",title:"Dr.",name:"Zoya",surname:"Ozherelieva",slug:"zoya-ozherelieva",fullName:"Zoya Ozherelieva"},{id:"319387",title:"Dr.",name:"Pavel",surname:"Prudnikov",slug:"pavel-prudnikov",fullName:"Pavel Prudnikov"},{id:"319388",title:"MSc.",name:"Diana",surname:"Krivushina",slug:"diana-krivushina",fullName:"Diana Krivushina"},{id:"319389",title:"Ms.",name:"Marina",surname:"Zubkova",slug:"marina-zubkova",fullName:"Marina Zubkova"},{id:"319390",title:"MSc.",name:"Anna",surname:"Androsova",slug:"anna-androsova",fullName:"Anna Androsova"}],corrections:null},{id:"72423",title:"Castor (Ricinus communis): An Underutilized Oil Crop in the South East Asia",doi:"10.5772/intechopen.92746",slug:"castor-em-ricinus-communis-em-an-underutilized-oil-crop-in-the-south-east-asia",totalDownloads:658,totalCrossrefCites:0,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Castor belongs to a monotypic genus Ricinus and subtribe Ricininae. It is one of the oldest plants, getting importance as an agricultural crop for subtropical and tropical countries in the world. Castor is a hardy plant, requires low input, tolerates marginal soils, is easy to establish in the field, is resistant to drought, and gives yield 350–900 kg oil per hectare. Castor oil shows great functional value in energy sector, industry, and pharmaceutical. In recent years, it received increasing demand in the international market for its more than 700 uses, ranging from medicine and cosmetics to biodiesel, plastic, and lubricants. The oil is significant for many industrial uses compared with other oils from plant sources because of its high and low temperature-tolerant properties. This chapter has been written to provide botanical descriptions, ecology, agro-technology, and versatile industrial uses.",signatures:"Swapan Chakrabarty, Abul Kalam Mohammad Aminul Islam, Zahira Yaakob and Abul Kalam Mohammad Mominul Islam",downloadPdfUrl:"/chapter/pdf-download/72423",previewPdfUrl:"/chapter/pdf-preview/72423",authors:[{id:"77958",title:"Prof.",name:"Zahira",surname:"Yaakob",slug:"zahira-yaakob",fullName:"Zahira Yaakob"},{id:"191072",title:"Prof.",name:"A. K. M. Aminul",surname:"Islam",slug:"a.-k.-m.-aminul-islam",fullName:"A. K. M. Aminul Islam"},{id:"234696",title:"Prof.",name:"A. K. M. Mominul",surname:"Islam",slug:"a.-k.-m.-mominul-islam",fullName:"A. K. M. Mominul Islam"},{id:"320653",title:"Mr.",name:"Swapan",surname:"Chakrabarty",slug:"swapan-chakrabarty",fullName:"Swapan Chakrabarty"}],corrections:null},{id:"71485",title:"Dangerous Risk Factors to be Considered for Proper Management of Agroecosystems",doi:"10.5772/intechopen.91824",slug:"dangerous-risk-factors-to-be-considered-for-proper-management-of-agroecosystems",totalDownloads:572,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Our work aims to identify the main risks existing in the agroecosystems of southern Italy, providing, at the same time, information about innovative and fast methodologies. The goal is to understand the magnitude of the phenomena that could compromise them if no action is taken for water and soil matrices. Regarding the former we will consider plant protection product residues in water bodies and the importance of agroecosystems as source of microplastic pollution and their role as a vector of pollutants; regarding the latter, we will present a rapid and low-cost methodology to detect asbestos-containing materials and significantly transformed areas. Furthermore, indications are provided on how to implement effective monitoring plans in order to certainly identify the problem affecting one or more matrices and provide practical instructions to the administrators to implement the appropriate remediation strategies.",signatures:"Carmine Massarelli, Claudia Campanale and Vito Felice Uricchio",downloadPdfUrl:"/chapter/pdf-download/71485",previewPdfUrl:"/chapter/pdf-preview/71485",authors:[{id:"315689",title:"Dr.",name:"Carmine",surname:"Massarelli",slug:"carmine-massarelli",fullName:"Carmine Massarelli"},{id:"315745",title:"Dr.",name:"Claudia",surname:"Campanale",slug:"claudia-campanale",fullName:"Claudia Campanale"},{id:"315746",title:"Dr.",name:"Vito Felice",surname:"Uricchio",slug:"vito-felice-uricchio",fullName:"Vito Felice Uricchio"}],corrections:null},{id:"72409",title:"Use of Deep Eutectic Solvents in the Treatment of Agro-Industrial Lignocellulosic Wastes for Bioactive Compounds",doi:"10.5772/intechopen.92747",slug:"use-of-deep-eutectic-solvents-in-the-treatment-of-agro-industrial-lignocellulosic-wastes-for-bioacti",totalDownloads:784,totalCrossrefCites:4,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Lignocellulose is the most abundant component in nature since it refers to plant material. Beyond the enormous utilization of lignocellulose by human being, unignorable amount of waste is also formed simultaneously. Agro-industrial lignocellulosic wastes can cause environmental pollutions if not processed before discharged. An innovative approach for lowering the detrimental influences of lignocellulosic wastes is to consider them as a source of useful products rather than a waste to be decontaminated. Beyond the conventional techniques for evaluation of the wastes, new emerging techniques and the use of new solvents have drawn attention recently. Among new generation solvents, deep eutectic solvents (DESs) have been increasingly used in the treatment of lignocellulosics to produce value-added products such as biofuels, chemicals, and solvents and also used for the recovery of bioactive phenolic compounds. DESs are used extensively for fractionation of lignocellulosic wastes, often in combination with enzymatic hydrolysis of the biomass. On the other hand, extraction and recovery of bioactive compounds are also under research using DESs. This mini review summarizes the very recent literature reports on the use of DESs in treating agro-industrial wastes within the concept of valorization of biomass.",signatures:"Ayşe Ezgi Ünlü and Serpil Takaç",downloadPdfUrl:"/chapter/pdf-download/72409",previewPdfUrl:"/chapter/pdf-preview/72409",authors:[{id:"315816",title:"Dr.",name:"Ayşe Ezgi",surname:"Ünlü",slug:"ayse-ezgi-unlu",fullName:"Ayşe Ezgi Ünlü"},{id:"316243",title:"Prof.",name:"Serpil",surname:"Takaç",slug:"serpil-takac",fullName:"Serpil Takaç"}],corrections:null},{id:"72566",title:"Formulations of BGA for Paddy Crop",doi:"10.5772/intechopen.92821",slug:"formulations-of-bga-for-paddy-crop",totalDownloads:599,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Blue green algae (BGA) are prokaryotic phototrophic organisms that can fix the atmospheric nitrogen biologically, and were directly applied as a biofertilizers in agricultural fields specifically Paddy field. Since they are having the ability to fix nitrogen, they are formulated with various adsorbents for the purpose of enhancing the crop growth along with maintaining the soil fertility and other soil factors responsible for productivity. The present study revealed that the formulations of blue green algae isolated from paddy fields of southern districts with different adsorbents like alluvial soil, sand, charcoal, and powdered paddy straw. All the adsorbents mixed with blue green algae showed significant growth when compared to the control plant. This determined that the adsorbent formulated mixed blue green algae enhanced the paddy plant growth under greenhouse condition.",signatures:"Bagampriyal Selvaraj and Sadhana Balasubramanian",downloadPdfUrl:"/chapter/pdf-download/72566",previewPdfUrl:"/chapter/pdf-preview/72566",authors:[{id:"316222",title:"Dr.",name:"Sadhana",surname:"Balasubramanian",slug:"sadhana-balasubramanian",fullName:"Sadhana Balasubramanian"},{id:"316448",title:"Mrs.",name:"Bagampriyal",surname:"Selvaraj",slug:"bagampriyal-selvaraj",fullName:"Bagampriyal Selvaraj"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"923",title:"Herbicides",subtitle:"Theory and Applications",isOpenForSubmission:!1,hash:"54a8eb808c05a5fe01c676e7047d4576",slug:"herbicides-theory-and-applications",bookSignature:"Sonia Soloneski and Marcelo L. 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October 18, 2018.
\n“There is no use trying” said Alice, “we cannot believe impossible things.”—Lewis Carroll
\nFew organizations combine the institutional benefits of longevity and tradition with the disruptive startup advantages of novelty and suspension of path dependent behavior. This chapter provides a case study of Toyota Corporation, an organization with an explicit philosophy that embodies “…standardized work and kaizen (that) are two sides of the same coin. Standardized work provides a consistent basis for maintaining productivity, quality and safety at high levels. Kaizen furnishes the dynamics of continuing improvement and the very human motivation of encouraging individuals to take part in designing and managing their own jobs” ([1], p. 38). Toyota’s philosophy, combining a model that is “stable and paranoid, systematic experimental, formal and frank” [2], often called the Toyota Way, evolved from the founding of Toyoda Automatic Loom Works, founded in 1911, setting up an auto division in 1933, and Toyota Motor Company in 1937 [3].
\nWhat is unique about Toyota and its pioneering lean production, described colloquially as just-in-time (JIT), embraces a deliberative philosophy that establishes a corporate identity for safety, quality, and aspirational performance goals. Going forward, with plants and distribution centers around the world, Toyota cultivates a direct involvement of employees, suppliers, and other organizations, called the Toyota Group, as a network identity that extends boundary members of the firm’s eco-system that also embodies detailed performance measures to strengthen and reinforce identity enhancement. These identity attributes creating novel and seemingly contradictory configurations, both at home and now in global markets. Toyota provides a framework to link identity as a cohesive attribute for problem-solving with explicit, data-driven benchmarks, a DNA that encompasses observation, analysis, hypothesis testing from the shop floor to the executive suite [3, 4].
\nThe concept of
Despite the growing literature on organization identity, encompassing diverse constructs and methodologies [6, 7], often at different organizational levels (individuals, groups and senior management), has limited empirical study linking individual and group identity both to corporate strategy and corporate performance. Various accounts of social experiences, concentrating on a sense of insider and outsider to frame a mutual identity mindset that shapes organizational identity, apply personal histories and narratives, but leave open the distinction between corporate identity and organizational identity [10]. Identity producing mechanisms flowing from purposeful actions vary by context, such as universities and faith-based organizations to technology and engineering organizations with complicated role activities grounded in socio-technical design [11]. Compelling cases of identity as a tool for organizational integration, or the impact of cleavage and conflict owing to human diversity policies, personality characteristics of key actors, and sub-unit identity images advance understanding of behavior within organizations, but often ignores how both strategic choice and external forces impact these internal mindsets. Many scholars associate internal identity issues to external stakeholders using sundry communication tools (e.g., [12]) but the literature has few studies that explain what organizational identity features are truly different and give a competitive advantage in contested markets over time. To advance hypothesis testing and to encourage conceptual development in both theory and practice, there must be a linkage to identity as a construct that provides insights to an organization’s competitive advantage.
\nThis chapter addresses the issues linking strategic choices and capabilities to Toyota’s identity as a case study. Toyota’s strategic positioning and high-performance outcomes amplify identity tools at three levels, its employees (both in Japan and its factories overseas), its suppliers, and its customers. Depicted as a best practice company [13], Toyota is seen as a model to emulate in sectors as diverse as hospitals and retailing. This chapter has three objectives: first, by examining Toyota’s transformation as a leading domestic producer to a top global company, the firm’s core identity has changed little despite numerous internal and external changes; second, Toyota as a case study illustrates the capacity to have multiple images in different contexts, without sacrificing its core identity; and third, the chapter offers recommendations for empirical studies of organizational identity.
\nIn their seminal article, Stuart and Whetten [5] put forward the concept of organizational identity constituting a set of “claims” and specified what was central, distinctive and enduring, but recognizing that organizations can have multiple identities and claims that can be contradictory, ambiguous, or even unrelated. While some authors have attempted to provide more clarity, Pratt addresses the construct of identity and its generality, stating it was “often overused and under specified” beyond general statements about “who are we?” and “who do we want to become?”
\nHistorically, identity and identification are described in classical writings focusing on societies, social systems, and their constituent parts. Such examples as Adam Smith in economics on the division of labor, Babbage on the division of work tasks, Marx on division of social class, Max Weber on the division of status and occupation, and Durkheim on differentiated social structures, each contributed to current views of how individuals, groups, and teams become a cohesive collective in a complex organization. More specifically, Durkheim’s [14] analysis of the division of labor and differentiated social structures with distinct socio-psychological values and impacts required variations in role homogeneity in sub-systems.1 His views influenced subsequent writers as diverse as Freud in psychiatry and Harold Laswell in political theory, whose study of world politics includes a chapter entitled “Nations and Classes: The Symbols of Identification.”
\nSimon [15] introduced identification to organization theory, describing it as follows: “the process of identification permits the broad organizational arrangements to govern the decisions of the persons who participate in the structure” (p. 102). More specifically, “a person identifies himself with a group when, in making a decision, he evaluates the several alternatives of choice in terms of their consequences for the specified group” in contrast to personal motivation, where “his evaluation is based upon an identification with himself or his family” ([16], p. 206). Both the fault lines of identity, based on status, perverse incentives, class or occupation, as well as group identification [17] impact organizational performance by variations in shared goals and preferences, as well as forms of interaction and feedback, often enhanced or lessoned by recruitment patterns and work rules and incentives.
\nIdentity and identification as reference points in organizations also flow from the configuration of roles, role structures, and “clusters of activities” where “a person has an occupational self-identity and is motivated to behave in ways which affirm and enhance the value attributes of that identity” ([18], p. 179). Theories of social identity assume individual identity is partitioned into ingroups and outgroups is social situations and organizational life, often with an implicit cost–benefit calculation, but acts of altruistic behavior, where behavioral norms benefit the welfare of others, often seen in “collectivist societies,” strengthens organizational identity [19]. Other approaches take a social constructionist approach, emphasizing social and cultural perspectives [20], where sense-making comes from stories and narratives of everyday experience [21], thereby, “…in linking identity and narrative in an individual, we link an individual [career] story to a particular cultural and historical narrative of a group” [22]. Going further, Dutton et al. [23] speculate that organizational identification is a process of self-categorization cultivated by distinctive, central, and enduring attributes that get reflected in corporate image, reputation, or strategic vision. Alvesson [24] describes the need for identity alignment: “…by strengthening the organization’s identity—its experienced distinctiveness, consistency, and stability—it can be assumed that individual identities and identification will be strengthen with what they are supposed to be doing at their work place.”
\nWhile some studies [25] purport to focus on managerial strategies that project images as a tool to shape distinctive identities with stakeholders, the reality is that organizational identities without corresponding integration of individual, sub-unit, or group identification may lead to behavioral frictions, and detachment via lower compliance and cues of detachment. Conflict and cleavages affect group-binding identification, often persisting as conformity of opinion, forms of social interaction, and group loyalties, as well as enhancing internal legitimacy for desired outcomes. While both individuals and groups may have multiple and loosely connected identities, there remains lingering organizations dysfunctions that exacerbate cleavage and conflict, such as hypocrisy, selective amnesia, or disloyalty [18]. Psychological exit comes from unsatisfactory outcomes, a form of weakening organizational identity and strengthening group identity to give voice for remedial actions [26]. In the extreme, such sub-identities found in groups and sub-units compete with other forms of identification and may lead to organizational dysfunctions [17].
\nAkerlof and Kranton [27] view organizational identity, with emphasis on why firms must transform workers from outsiders to insiders, as a form of motivational capital. In short, a distinctive identity is a distinctive competence. To quote Likert [28]. “the favorable attitudes towards the organization and the work are not those of easy complacency but are the attitudes of identification with the organization and its objectives and a high sense of involvement in achieving them” (p. 98). Other theorists suggest variations in organizational identity impact sense-making and interpretative processes [29], internalization of learning [10] and processes linking shared values and modes of performance [30].
\nIdentity and identification cues, viewed as the mental perceptions of individual self-awareness, social interactions and experiences, and self-esteem have many antecedents, such as social class [31], demographic factors like age, race, religion, or sex [32], and national culture and identity [33]. Studies emphasizing social construction perspectives stem from individual accounts, often defined in social narratives, histories, and biographies rooted in time and place [34]. As Hammack [22] emphasizes, “…in linking identity and narrative in an individual, we link an individual story to a particular cultural and historical narrative of a group” (p. 230). At a general level, organizational culture depicts the set of norms and values that are widely shared and strongly held throughout the organization [35], and refers to the “unspoken code of communication among members of an organization” [36] and aids and supplements task coordination and group identity. In this way, individual employees better understand the premises of decision choices in problem solving at the organizational level. In complex organizations, identity is linked to the strategic capacity of choice opportunities and implementation dynamics of priorities and preferences. As Thoenig and Paradieise [37] emphasize, “strategic capacity lies to a great extent in how much its internal subunits … shape its identity, define its priorities approve its positions, prepare the way for general agreement to be adopted on its roadmap and provide a framework for the decisions and acts of all its components” (p. 299).
\nSuch diverse views leave open how organizational identity, or shared central vision, confers competitive advantage in contested spaces. As a starting hypothesis, a shared identity strengthens coordination across diverse groups applying common norms, codes and protocols, hence improving shared learning skills. In a similar vein, individual cleavages and loyalties are lessoned by shared interactions and information sharing that mobilize learning tools. Further, organizational identity strengthens individual identities via performance success that promotes a shared set of preferences, expectation, and habits of rule setting.
\nBy any standards—shareholder value, product innovation, employee satisfaction measured by low turnover and lack of strike action, market capitalization—Toyota has been astonishingly successful, both against rival incumbents in the auto sector, but as a organizational pioneer in transportation with just-in-time thinking. Against existing rivals at home, or in an industry with firms pursuing growth by alliances and acquisition (Renault-Nissan-Mitsubishi, VW-Porsche), facing receivership and saved by public funding (GM and Chrysler), exiting as a going concern (British Leyland) or new startups (Tesla). Toyota’s performance is unrivaled. Toyota remains a firm committed to organic development, steady and consistent market share in all key international markets, and cultivating a shared identity within its eco-system around measurable outcomes of product safety, quality, and consumer value.
\nAs shown in Figure 1, despite many forms of competitive advantages, such as size, high domestic market share, being part of a larger group, or diversification, there are many times when the side expected to win actually is less profitable and may actually lose. Toyota’s growth and expansion, despite the turbulent 2009 recall and temporary retreats [38, 39], comes with consistent profitability and market share growth. In this organizational transformation, Toyota has replicated its identity of “safety, quality, and value” outside its home market, often depicted by foreigners as “inscrutable,” closed, and Japan Inc. [40]. Strategically, this organizational identity framework is multipurpose, allowing shared alignment of identities with domestic employees, suppliers and supervisors, but also incorporating these identity attributes first to foreign operations in North America and subsequently to Europe and Asia. Toyota management considers the firm as a learning organization, where learning symmetries take place at all levels, vertically and horizontally.
\nOperating Profits versus Firm Revenues in the Auto Sector.
Unlike many corporate design models of multinationals, where foreign subsidiaries passively replicate the production systems of the home market (a miniature replica effect) or seek out decision-attention from head-quarters [41] Toyota is evolving as a global enterprise. In this model, Toyota’s foreign subsidies and trade blocks (e.g., NAFTA and Europe), solve key problems and translate the protocols for headquarters and its global network of factories, distribution outlets, and service and maintenance dealerships. In this way, Toyota’s training protocols, network learning systems, and using foreign subsidies to develop new technologies (e.g., Toyota Canada pioneering cold weather technologies for ignitions engineering), i.e., a learning chain that mobilizes employee identity to network identity, including its global supply chain collaboration [42, 43, 44, 45].
\nTo illustrate the complexity of contemporary auto production and the need to evolve both organizational design around supply chains, and the nature of complementarities in production, firms like Toyota must realign engineering and technological systems to novel role configurations for a diverse workforce. A car (or truck) has over 5000 parts, components, and sub-assemblies, where factories are linked to diverse supply chains with tightly-knit communications and transport linkages, often across national boundaries, to produce a factory production cycle of 1 minute per vehicle, or even less. Parts or components like steel, for instance, are not commodities, undifferentiated only by price, and Japanese steel producers produced the high carbon steel that was more resistant to water, hence rust. This production cycle demands very high quality and safety of each part and component, plus the precision engineering processes to assemble them. This alignment determines not only the standards of quality and safety of the finished vehicle but the image and reputation of the company, plus an indispensable need to retain price value of the brand in the aftermarket sales cycle.
\nTo this contemporary production system, reshaped and refined since Toyota first introduced in 1956 what Womack et al. [46] termed “the machine that changed the world,” auto production now faces a steady, relentless, and inexorable technology disruption. This shift in engines and fuel consumption technologies, away from diesel and gasoline-powered vehicles, to new dominant technologies, such as electric vehicles, fuel-cells, battery, hydrogen, or hybrid, each requiring massive changes to traditional parts and components suppliers, and the layout of factory assembly. Successful firms thus require forward-looking strategic intent and novel organizational configurations both to exploit existing systems based on gasoline vehicles, or novel organizational systems to explore new technologies and processes. Strategies differ widely. Tesla as a new startup has dedicated factories and labs using lithium battery technology. To gain equivalent scale of Toyota, GM, and Volkswagen, i.e., over 10 million vehicles per year, Nissan and Renault joined with Mitsubishi as a new alliances and equity investment partner.
\nBy contrast, both Ford and GM are retreating from large markets like Europe, Japan, or India with direct-foreign investment strategies. Even more intrusive to existing production programs and protocols are new demands for data analytics, artificial intelligence, robotic and associated Internet and social media technologies. Both incumbent firms, new startups, and suppliers are developing futuristic technologies in drivers’ facial recognition, driving habits, and consumer disabilities, from wheel chairs to hearing that impact cars of the future, and impose threats to existing distinctive competences and corporate identity. Not all firms can manage simultaneously the processes of exploitation of existing organizational programs, and the exploration of product innovation and assembly [47]. Toyota is an exception.
\nThe Toyota production system is transformational, an organizational philosophy around two core ideas,
Strategies of corporate retreat in key markets (GM in Europe, GM and Ford in India, Ford in Japan), suggest home market advantages are the new testing ground for first-mover disadvantage [48] when firms face massive technology disruption. To cite an example, during the 1990s, four major automakers, Toyota, GM, Honda, and Ford, took the lead in the development of hybrid technologies, with GM the leader with 23 patents in hybrid vehicles (vs. 17 for Toyota, 16 for Ford, and 8 for Honda). By 2000, however, Honda and Toyota were the clear leaders, with Honda had filed 170 patents, and Toyota with 166 in hybrid drivetrain technology, far ahead pf Ford with 85 and GM at 56. Today, Fords’ hybrid is a license from Toyota.
\nThe auto sector symbolizes the development of post-war multinationals largely based on firm-specific capabilities and proprietary advantages. This organizational evolution includes changing work mechanisms characterized as machine theory by management [49], a catch-all phrase to describe scientific management techniques espoused by Frederick Taylor from his 1911 book with that title. He first learned time management at Philips Executer Academy and became an early practitioner of what became known as
Taylor’s disciples in the engineering profession spread his message beyond America, to Europe, as well as to Japan and Russia, where even Lenin and Trotsky developed an interest after the Revolution of 1917. In appearances before Congressional committees, and in other forums, Taylor’s theories faced withering criticisms and great resistance by American union movement a “dehumanizing of the worker” and a tool for profits at the expense of the worker. [50, 52]. In Japan, however, Taylorism and scientific management had wide acceptance, starting with Yukinori Hoshino’s translation of
After 1945 in Japan, given the wartime devastation of Japan’s industrial capacity, resource scarcity—food, building supplies, raw materials of all sorts, electric power—had a profound and lasting impact on Japanese society, even more so when the American military supervised the Occupation and displayed abundance of everyday goods—big cars, no shortage of food, long leisure hours, and consumer spending using American dollars. As Japanese firms slowly rebuilt, the corporate ethos promoted efficient use of everything, and waste became a watchword for inefficiency. Japanese executives visited US factories, the Japanese media documented US success stories. American management practices were widely emulated, and US consultants—notably Peter Drucker, W. Juran, and W. Edwards Deming—had an immense following and their books, papers and personal appearances were publicized, translated and widely-read, even by high school students. While American firms emphasized a marketing philosophy where the customer is king, Japanese firms remained committed to production, helped in part by trading firms, led by the nine giant
Japan industrial firms, by contrast, cultivated three features of management-worker relations. The first was life time employment—once hired, the employee stayed in the firm until retirement. Second, wages and compensation were determined by seniority—young workers received lower wages and bonus compensation, just as older workers were paid more relative to their actual productivity. And third, firms had enterprise unions, as distinct from industry unions in the US and Europe (e.g., unions autoworkers, coal workers or shipbuilders). All three characteristics greatly extended the psychological linkages between employee identity and the firm’s identity, and the employee’s career success was directly tied to the firm’s success. In Japan, with very low turnover, but high screening processes, firms hired the best graduates, and training was on-going and formed part of the job description, with little layoffs, firing, or absenteeism. Additionally, there was little employee fear of adopting new technologies. Abegglen and Stalk [54] describe the implication of technological diffusion as follows: “…it is the relatively close identification of the interests of
Okika [56] describes the implications of the evolving Japanese model of labor-management relations in the firm:
\nJapanese enterprises made their decisions by gaining an overall consensus through repeated discussions starting from the bottom and working up … making it easier for workers to accept technical innovation flexibly. For a start, that sense of identity with the firm is strong and they are aware that the firm’s development is to their own advantage, so they tend to improve the efficiency of its production system and strengthens its competitiveness (p. 22).
\nAcross Japan, industrial firms, from Sony to Canon, recruited workers from rural areas, executives read US textbooks, and many visited US factories to study management practices. The production focus of Japanese firms, in a competitive environment of limited slack, hence the need for managerial improvisation and what the French call
The advance of industrialization involved new methods of energy, raw materials, dominant technologies, and organizational configurations [58] but relatively little to consideration actual production systems, especially after Henry Ford introduced mass production using interchangeable parts. As foreign executives visited Ford’s assembly lines, there were dissenting opinions, such as Czech entrepreneur Thomas Bata and S. Toyoda who worked a year in Detroit. How could three core concepts be integrated—craft skills of custom-made products like a
Toyota’s introduction of the lean production system has been widely studied,2 including its the origins in the 1950s by Ohno [62], when visiting America and adopting ideas from super market chains, and had strong views on scientific management’s focus on the total production system, and Japanese concepts of
Core concepts of lean production is the desire to maximize capacity utilization, by reducing production variability and minimize excess inventories with a view to eradicating waste [54]. But other factors are critical, such as supplying high quality workmanship of craft production, reducing per unit costs via mass production using interchangeable parts, and high capacity utilization of continuous flow production, typically seen as three distinct systems. The ingrained ethos of resource scarcity in Japanese society, demonstrating that low slack in organizations encourage search behavior [63], and these requirements required pooling of efforts as an organizational philosophy (Figure 2).
\nContrasts Between Traditional Technical Design and Toyota’s Model.
To perfect the system over time, starting in the 1960s, Toyota accelerated the adoption of high work commitment by organizing workers in teams, reducing the number of job classifications, seeking suggestions from employees, and investing in training of new workers, 47–48 days per worker, compared to less than 5–6 days for US plants, 21–22 days for European plants [3]. The focus on production as an integrated system, using hardware ideas like quick die change equipment, robots, and advanced computer-aided design, also meant removing traditional tasks that are noisy, hard on the eyes, or dangerous to allow employees to concentrate on tasks like quality assessment, and allowing a worker to stop the entire production line, known as
Einstein once said, “Make everything as simple as possible, but no simpler.” Simplicity became a watchword in the evolution of Toyota’s lean production system, a contrast to the complicated vertical integration model adopted in Detroit. Toyota adopted a highly focused structural design, becoming a systems assembler and sourcing from dedicated suppliers, each with core competences in specialized domains and technologies. Production engineering—e.g., craft, mass assembly or process systems—became central features as organizational configuration, choosing from the strengths of each but discarding the perceived weaknesses. Stress was place on the worker, avoiding the monotonous routines of a moving assembly line, by including job rotation and special training to apply quality management circles within a group structure. The advantages of process manufacturing as high capacity utilization came from high initial overhead of equipment and overhead, including IT investments, but allowing flexibility in machine set up, such as quick die change that reduced the need to stop the line for product variability from 3 months, to 3 weeks, to 3 minutes, to less than 3 seconds. The internal factory layout, an S shape configuration, changed the sequencing of tasks, the forms of supervisor-employee interactions, and the speed and timing of interdependencies between the production operations and external suppliers of parts, delivering “just in time.”
\nIn some cases, the interactions involve the core production system and independent suppliers serving as complementarities3 where the competitive advantage of one is augmented by the presence of the other [45]. Early examples included Ford’s cooperation with Firestone to produce tires, or Renault’s links to Michelin to produce radial tires. Complementarities allow synergistic advantages, a contrast to additive, discrete features [64], and allow two immediate effects: knowledge spillovers at differing stages of production, including process learning impacts, and complimentary and coordinated changes in activities and programs across the value chain, such as process benchmarks for product design, scheduling, inspection, and time cycles of production. Toyota cultivates complementarity attributes but instituted a revised activity sequence, discarding production based on estimated demand forecasts, and turning finished production of cars and trucks to car lots for ultimate sale. The pull system starts with customer demands, allowing novel design using the advantages of the need for high capacity utilization of smaller actual output demands, to manufacture outputs with shorter time for product delivery.
\nToyota’s lean production both reconfigures the boundaries of the firm by incorporating the supply chain as an integrated, cooperative network with collective competences and capabilities across the network value chain and incorporates decision processes for learning and knowledge sharing that shifts subunit identities to a collective identity. Lean production requires these system-wide processes to address inoperability issues like buffer stocks, time delays, peak demand, or product defects. Deep collaboration across sub-units needs robust methods to design, evaluate, and verify data gathering and data feedback. Unlike economic models of transaction costs, or contractual relations, lean production emphasizes symmetrical collaboration to optimize outcome effectiveness for the total eco-system organization, not sub-optimize for only certain members, sub-units, or component firms. Toyota’s collective identity is a notable corporate example that combines both superb operational performance but also long-term, forward looking innovation through its complex ecosystem of Tier I and Tier II supplier system. As depicted in Figure 3, Toyota aligns its supply system both domestically and overseas with knowledge systems, including standards of precision and quality, including using internal staffing and consultants to assure optimum outcomes against agreed benchmarks.
\nToyota’s Knowledge Diffusion and Sharing Approaches.
By replacing asymmetric contractual relations based on cost, Toyota shifts the locus of corporate risk to the total eco-system, involving Toyota at the center, the Tier I and Tier II suppliers, and their Tier I and Tier II suppliers. The lean “pull” of production control is a connectivity to calibrate inventory at each stage, starting with the final assembly and preceding to each preceding stage without delay. Unlike the push model, where the early steps of sub-assembly is sequential to subsequent stages and require buffer inventory to lesson delays, Toyota’s lean system of ‘pulling’ requires training and upgrading skills employed at different work stations, and close communications across the total supply chain system. To make this system work, economic transaction costs are discarded, and replaced by a currency of cooperation using preventive tools and benchmarks to meet high standards of reliability where Tier II firms meet rigorous standards of price, quality, and delivery. Suppliers are battle-tested, i.e., they must conform to agreed specifications and their products are accepted only after years of testing. Tier I suppliers, on the other hand, meet the exacting standards of Tier II suppliers but they form part of the design, research, and testing of new products, markets, and technological innovations. Tier II suppliers can “graduate” to being Tier I suppliers if they meet benchmark performance over time, thus demanding intense deep collaboration at Level 4 (Figure 4).
\nLevels of Value Chain Collaboration: Toyota as Level 4.
Less coordinated systems of structure, processes, and executive decision-making inhibit eco-system operability. Three integrating systems are vital: (1) technical systems, including IT, software, and data; (2) organizational tools of coordination, like dedication teams supported by specialists and intense data sharing; and (3) collaborative executive decision processes that champion novelty, innovation, and feedback [65, 66]. Inoperability can come from seemingly mundane tasks, like loading supplies on a truck with different invoices, manifest requirements, and delivery times. Separate and differing organizational processes inhibit deep collaboration. Inoperability arises from silo information flows and compartmentalization. Even with aspirational targets of decision-making, organizations acting alone fail to develop and improve competencies and capabilities to manage this integrated system via experiential learning, feedback, and criticism [67, 68, 69].
\nDeep collaboration needs robust methods to design, evaluate, and verify data gathering and data feedback to optimize effectiveness for the total eco-system organization, not sub-optimize for only certain members, sub-parts, or component firms [70]. Toyota’s lean production now has both a language and a vocabulary to remove task ambiguities and increase identity among workers, sub-units, and factories in the global network, but requiring a learning process to perfect clear meanings and defined protocols. Words like
Training programs—internships, formal courses, apprenticeships—build organizational capabilities and mitigates risks from operating with incomplete knowledge, inexperience, understanding operating rules and procedures. Deep collaboration illustrates the need for similar training approaches to know, understand, and apply knowledge across the entire system. Toyota gains three network advantages: positional, where individual managers and subsidiaries access tools and protocols for high performance processes and benchmarks that create learning; structural, where communication connections strengthen the effectiveness and acuity of information flows to attend to emerging problems; agility, by strengthening interactions between individuals and teams, and embedding the new benchmarks across the entire network of factories, sales offices, and supplier organizations.
\nBy the early 1980s, Toyota, like many leading Japanese corporations such as Sony, Komatsu, Canon, Matsushita, and Hitachi, were making deep inroads in the American market via exports. The auto sector was singled out, as 500,000 American autoworkers were laid off, a new President, Ronald Reagan faced pressure from Congress to take legislative action, and firms like Ford applied to the American International Trade Commission for temporary relief, following similar action by the powerful auto union, the UAW. Further, Japan’s emphasis on direct export sales stood in contrast to American strategies of direct investment in foreign markets, often by acquisition of local companies [8, 45, 72] .4 For firms like Toyota, growing high dependence on exports meant that larger total volumes (domestic + exports) strengthened their product capacity and cost position at home, including that of their supplier base. Japan’s auto exports to the US reached 6.6 million vehicles in 1981, up from a million units 10 years earlier, 566,042, accounted for almost 20% of total Japanese auto exports.
\nThe imposition of Japan’s export restraints, formalized in June 1981, coincided a $1.5b loan guarantee to Chrysler, indefinite layoffs of over 30,000 auto workers, and sectors like steel facing declining market share. Pressed by firms like Ford for Congressional actions, MITI imposed export quotas on each Japanese company, a form of “administrative guidance” designed to accommodate political goals in each country but was in fact a “cartel” solution aimed to appease the US government [3, 74]. The percentage breakdown for each of the five biggest exporters, calculated mainly by US exports in the previous 2 years, was as follows: Toyota (30.75), Nissan (27.15), Honda (20.75), Mazda (9.48), and Mitsubishi (6.7). The impact for each company in the brutally competitive Japanese market varied: Honda was the first to begin direct investment, opening its first plant in Ohio and then Ontario; while Toyota kept to its quota by exports but strengthened domestic operations to build up a commanding market share lead, over 50%. For the Japanese auto sector, as Summerville notes [74], “investment in local production was also a crucial way to insulate oneself from further export cutbacks, and of course to get away from the thumb of the Japanese state” (p. 395). Toyota illustrates the complexity to manage very fast growth in foreign markets, while transferring its corporate identity to a network identity of safety, quality, and value [43], even though the knowledge sharing processes that are now taken for granted at home, including quality standards of suppliers, may not exist in foreign countries [75, 76, 77, 78].
\nThe massive recall in 1999, where Toyota accepted responsibility to service over 8.5 million vehicles, the President appearing before Congress, and sundry lawsuits launched in a litigious environment against a foreign-owned firm, have been analyzed and studied5 in the media, the automotive press, and by academic studies, with mixed conclusions. The reality, despite paying fines, accepting responsibility, apologizing to the American public, and accepting the huge financial costs of the recall, Toyota refused to play the blame game, or take easy solutions, like importing more parts from Canada or Japan, or shifting American production to Canada or Mexico. Toyota took the difficult decision, true to its identity, of fixing the core problem, raising the quality standards of its American-own parts supplier, devoting more resources to training, and accepting short-term risks to financial performance, particularly when leading automakers from Europe, Korea, and Japan were investing in the US market. The Detroit Big 3 received temporary relief, a massive bailout after bankruptcy from the US and Canadian government, and a 25% tariff on imported trucks, one of the most profitable segments for American producers. Toyota quietly responded about building a truck factory in Texas.
\nIn a world of disruptive corporate strategy and identity offer a refined tool for alignment of stakeholders to create competitive advantage. Corporate culture focuses on the behavioral assumptions to perceive, think, and feel in problem-solving [81] within the organization, while organizational identity is a projection of that culture to external stakeholders to align both cognitive and behavioral tools for growth and innovation. Individual and sub-unit identities can lead to cleavage and discord, especially where environmental forces make knowledge and information asymmetric, so special attention and sense-making requires an adaptive alignment to improve performance (Figure 5).
\nOrganizational Strategy and Identity Linkages.
Increasing, all organizations face four separate but related challenges that impact overall performance but also survival as independent entities. Clearly, technological change imposes new challenges for internal organizational competences and capabilities, as firms scramble for mergers, takeovers, and new alliances to meet the test of size and foreign market penetration, or a retreat approach or even drift. Decision uncertainty influences the nature of internal competencies, learning barriers, and the sustainable position of existing firms. The third challenge with disruption is the growing complexity of the firm’s ecosystem, and what is the optimal scale of a firm’s future business case, based on potential changes to customer markets across multiple countries?
\nThe fourth challenge relates to the first three but is subtler. That challenge concerns what might be called the Galapagos trap, namely designing an ecosystem that is suitable for one market that is unsuitable for global markets and allows little transfer of knowledge or engineering knowhow to other markets with a separate eco-system, including the supplier system. Recent examples include Japan’s unique wireless standards that did not apply in foreign markets systems, or American big car gas guzzlers with limited fuel mileage that did not meet foreign market regulations. Toyota’s development of hydrogen fuel powered vehicles, based on new chemical technologies, is a case in point, where existing infrastructure lacks the necessary technical requirements for even limited mass appeal. In all four of these development challenges, the competitive race is to avoid the lessons of the computer industry, where new smart phone technologies displaced existing incumbents, lowered entry barriers for new startups, and shifted the main suppliers and their location.
\nSuch fundamental changes pose difficult questions for firms’ missions, corporate identity, and framing long term employee loyalty. As Simon [76] warned decades ago, “organizational identification…implies absorption of strategic plans into the minds of organizational members where they can have direct effect upon the entire decision-process, starting with the identification of problems…” (p. 141).
\nThe domestication of Sorghum (
Sorghum evolved after splitting from the shared ancestors with rice in Africa 50–70 million years ago, but diffusion into other regions and the widespread cultivation led to high natural genetic diversity within sorghum nowadays [1], which has resulted in distinct phenotypic variance defined by their floral architecture and seed characteristics [6, 21]. Sorghum is a diploid C4 grass with 10 chromosomes and a genome of approximately 800 Mbp [22, 23]. A first reference genome was reported in 2009 [8]. The reference genome of sorghum is derived from the inbred ‘BTx623,’ a genotype with reduced height and early maturation, which is primarily used for production of grain. The phenotype of this reference genotype is very distinct from the tall, late maturing sorghums, which are usually grown for sugars or high biomass yield [1]. Commercial production systems in Argentina, Australia, Brazil, Mexico or USA utilize sorghum hybrids. However, subsistence agriculture mainly plants sorghum inbred lines for their livelihood. The preference of both consumers and regulators for non-GM sorghum has focused significantly on identifying and utilizing the natural genetic variation of sorghum to improve yield and quality. Currently, Sorghum breeding focusses on tackling abiotic and biotic stresses such as drought, acid soils, and insect and fungal pests [4]. The genetic resources that are largely created by public research are important to understand crop physiology to improve crop performance and production. It is aided by genome-wide map of SNP variation that will accelerate marker-assisted breeding. The adaptability and stress tolerance found in sorghum accessions allows to study the genotype–phenotype relationship as well as dissect genotype-by-environment (G x E x M) interactions for complex, quantitative traits [24] permitting future insights in drought tolerance and thereby mitigating the impacts of climate change. Especially, the exploration of the unknown and unexplored genetic potential taking advantage for the improvement of other cereals, especially maize.
The origin in Africa, distribution to other ecosystems, and agricultural practices is reflected in the phenotypic variation [21] ranging from traditional varieties across Africa and Asia to modern germplasm in China, Australia, and the Americas. This provides a wide variance of morphological and physiological traits for crop improvement [3, 7, 25]. Rainy periods are long and erratic in parts of West Africa, and subsequently, open panicle guinea types are preferred to reduce yield penalties such as grain mold and insect damage. In contrast, other parts of South and East Africa, where rainy seasons are relatively short and predictable, dense panicle kafir and durra types are preferred to increase grain yield per plant [4]. Further selection has occurred in the United States in the last 150 years as temperate and tropical sorghum from Africa and Asia has been bred for commercial agriculture [26].
While research on climate change impact on sorghum is limited, the importance of its root system has been highlighted. Modelling studies have shown that sorghum root systems have a relative adaptive advantage over maize in water-limited conditions [27]. The differences between maize and sorghum root system might facilitate adaptation to drought-prone regions with erratic precipitation. Maize and sorghum differed in root development at the seedling stage for both the number of seminal roots and the timing of nodal root appearance [28]. After germination, sorghum produced a single primary root and a coleoptile, by day 7 the two leaves stage was reached and the primary root had started to form lateral branches. In contrast to maize, no nodal or seminal roots had formed by day 7 (see also Figure 1). Sorghum produced only one primary root from seed and nodal roots emerged at the 4th–5th leaf stage, whereas maize produced 3–7 roots from the seed and nodal roots emerged at the 2nd leaf stage [28]. The differences in root development and the adaptation to different environmental and agricultural practices of sorghum root systems might explain the better performance of sorghum in drought-prone regions with erratic precipitation when compared with maize. Increased access to water can be achieved either by better water acquisition from the soil exploring an increased soil volume, which could be achieved by deeper rooting or greater lateral spread [29, 30]. A relationship between drought adaptation and nodal root angle was reported, which further supports the role of below-ground biomass traits in sorghum production under water stress [31]. Furthermore, QTLs were mapped for nodal root angle in sorghum at the 6-leaf stage and evaluated the relevance of the trait for improving drought adaptation via marker-assisted selection. All four nodal root angle QTLs in sorghum identified co-located with previously identified QTLs for stay-green loci [31]. The grain yield benefit of the stay-green phenotype under drought was found to be a result of reduced vegetative biomass and water uptake during the pre-flowering growth stages [32]. Under artificial conditions, sorghum root length during the seedling stage was found to be a major factor in drought tolerance [33].
The root system of
The parasitic plants,
Root growth is impeded by aluminum, the third most abundant element in the Earth’s crust. A major physiological mechanism facilitating plant aluminum tolerance is aluminum exclusion from root apices based on organic acid release forming stable, nontoxic Al3+-complexes in the rhizosphere. Quantitative RT-PCR analysis showed that the responsible gene (
To exemplify what degree of variation can be expected by sorghum varieties, a set of European sorghum lines was grown under sterile conditions in filter paper and in soil-filled rhizotrons. Grown in filter paper, the primary root and its lateral roots were identified easily, while no seminal roots were observed (Figure 1). In agreement with [28] 14 and 21 days after sowing (DAS), no seminal roots were observed in any of the varieties grown, while a varying number of crown roots was found. All root types of all the tested sorghum varieties did have root hairs and all those hairs were excreting sorgoleone, visible as droplets on each root hair tip. On soil-grown roots no sorgoleone was observed, but that might have been absorbed by the surrounding soil or washed away during the washing procedures at harvest.
30 diverse sorghum genotypes, selected for variation in origin and breeding status, including physiological traits such as drought tolerance, and flowering time, (summarized in Table 1) were grown in soil-filled rhizotrons and their roots and shoots non-invasively phenotyped over three weeks. Although genotypic variation was large for most traits, the mean shoot height over all genotypes followed a linear increase (Figure 2) and its variation was stable in the last week of growth. Both, shoot height as well as shoot dry weight had a variation of ~2x and ~ 4x, meaning the largest genotype had a dry weight or shoot height twice or four times as large as the smallest genotype. At harvest, 21 DAS, the most contrasting lines had 35 cm compared to 60 cm high shoots and 0.23 g compared to 0.82 g shoot dry matter. Among the varieties with largest shoot height were ‘Mace Da Kunya’, ‘SC35’, and ‘Mota Maradi‘, landraces described either as drought tolerant, post-flowering or pre-flowering drought tolerant, respectively. The shortest three varieties were ‘Tx430’, ‘Tx631’, and ‘Tx436’, all American feed-grade hybrids. Genotypes with large shoot height tended to also have higher shoot dry mass compared to genotypes with shorter shoots. A higher variation in shoot biomass compared to shoot height implicated additional factors influencing the first independent of the latter, such as leaf number, width and thickness. Given the highly diverse origin of these selected genotypes (Table 1) a high phenotypic variation above- and below ground was expected.
ID | Pedigree | Description | Origin |
---|---|---|---|
1 | T × 430 | Feed-grade hybrid pollinator-parent | USA |
2 | T × 2752 | Feed-grade hybrid seed-parent | USA |
3 | T × 631 | Food-grade hybrid seed-parent | USA |
4 | T × ARG1 | Food-grade hybrid seed-parent | USA |
5 | T × 436 | Food-grade hybrid pollinator-parent | USA |
6 | B N223 | Food-grade hybrid seed-parent | Niger |
7 | SC599 | Post-flowering drought tolerant accession | USA |
8 | SC35 | Post-flowering drought tolerant accession | USA |
9 | Kuyuma | Improved, open pollinated variety | Zambia |
10 | Sepon82 | Improved, open pollinated variety | Niger |
11 | SK 5912 Short Kaura | Improved, open pollinated variety | Nigeria |
12 | Ajabsido | Drought tolerant landrace | Sudan |
13 | CE-151-262-A1 | Improved, open pollinated variety | Senegal |
14 | CSM-63 | Drought tolerant landrace | Mali |
15 | Mota Maradi | Pre-flowering drought tolerant landrace | Niger |
16 | Koro Kollo | Pre-flowering drought tolerant landrace | Sudan |
17 | Feterita Gishesh | Pre-flowering drought tolerant landrace | Sudan |
18 | Segeolane | Pre-flowering drought tolerant landrace | Botswana |
19 | PI609567 | Post-flowering drought tolerant accession | Mali |
20 | MR732 | Elite, food-grade, hybrid pollinator-parent | Niger |
21 | Wassa | Improved, open pollinated variety | Mali |
22 | Seguetana | Improved, open pollinated variety | Mali |
23 | El Mota - S241 | Pre-flowering drought tolerant landrace | Niger |
24 | Honey Drip | Sweet-stem sorghum | USA |
25 | Theis | Sweet-stem sorghum | USA |
26 | Framida | Improved, Striga-resistant variety | Burkina Faso |
27 | ICSV1049 | Improved, Striga-resistant variety | Burkina Faso |
28 | Sariaso 14 | Improved, Striga-resistant variety | Burkina Faso |
29 | Grinkan | Improved, open pollinated variety | Mali |
30 | Mace Da Kunya | Drought tolerant landrace | Niger |
Commercial sorghum parent lines and accessions.
Variation in growth of 30
In contrast to the relatively small above ground variation in the rhizotron-grown sorghum lines, root dry matter varied much more after three weeks of growth- almost 7x between the most extreme genotypes (Figure 2). At harvest the root dry weight varied between 0.22 g and 1.4 g. Again, the three largest root biomass varieties were observed as drought tolerant landraces (‘Ajabsido’, ‘Segeolane’, ‘Mace Da Kunya’), while improved and hybrid varieties had lower root biomass (‘Tx430’, ‘SC599’, ‘Wassa’). A similar wide range of variation (6-7x) was found for root length of all separated types- the primary root, nodal roots, and lateral roots (Figure 3), but it changed over time. One week after sowing the first emerging primary root showed the highest length and variation while crown and lateral roots were almost not detected. Primary root length reached a plateau between 14 and 17 DAS, both due to the physical rhizotron constraints and the limited number of one primary root per plant. Two weeks after sowing, nodal root length varied from not detected to close to primary root length (50 cm), and just three days later their length doubled, and more than doubled again at harvest, 21 DAS. Lateral root length showed an even stronger increase in length over time, the genotype with the longest LRs had 1,400 cm LR length at harvest, while the most contrasting genotype on the other end had only 250 cm LR length. With increase in NR and LR length over time, their variation among the tested genotypes also increased both in absolute and relative values. Although the genotypic ranking per investigated root type varied slightly, also over time, a general trend of stable ranking became visible. Since these plants were grown without nutritional, water, light, or biological stress this expresses their genetic potential to either form rather small or large root systems, often also with higher numbers of main axis. In all three root types, ‘Tx436’, a food-grade hybrid pollinator parent, and ‘SC599’ (Figure 3D), a post-flowering drought tolerant accession, were among the lowest ranking genotypes. Among the largest root systems were ‘Mota Maradi’ (Figure 3E), a pre-flowering drought tolerant landrace, and ‘SK5912’ and short ‘Kaura’, an improved open pollinated variety. Thus, previously drought tolerant described varieties did not show comparable root system developments in contrast to their early shoot development.
Variation in root growth of 30
To gain more detailed knowledge about root morphology of these 30 sorghum genotypes, microscopic analyses were performed. Per root type (PR, NR, LRs) root diameter, root hair length, and root hair density were measured (Figure 4). When root hair density was plotted against root hair length per root type, a dependency became visible: roughly the more root hairs the longer they were (Figure 4A). All root types except for nodal roots showed significant correlations of root hair length and density. On all root types the genotypes ‘Tx430’, ‘Tx631’, ‘Tx436’, and ‘Mace Da Kunya’ formed the shortest and fewest root hairs. As root hairs are known to be instrumental for water und nutrient uptake [59] it is surprising to find ‘Mace Da Kunya’ in this list as it was also producing high root and shoot biomass. It should be noted that without nutrient and water limitation short and fewer root hairs were shown to be sufficient for plant growth [60, 61]. The longest and most root hairs were formed on roots of ‘Segeolane’, ‘MR732’, and ‘Mota Maradi’. Since the latter, a pre-flowering drought tolerant landrace, also had the largest root system, it overall has the highest root surface area leading to the most soil contact for water and nutrient uptake. Like ‘Mota Maradi’, the genotypes with most root hairs also have the potential to excrete more sorgoleone into their soil environment compared to varieties with smaller root systems and fewer root hairs. Nodal roots had longer root hairs compared to all other root types, followed by primary roots, but their lateral roots did not differ from each other. Overall these soil-grown roots did produce many, but short root hairs of ~150 μm length; similar ranges of root hair formation have been reported for soil-grown rice varieties [60]. On the other hand, field-grown barley genotypes were reported to form longer root hairs from 400 μm [62] up to 700 μm [61]. Root hair formation in these studies varied with environmental conditions, be it nutrient or water supply, or other soil properties, therefore it is likely that sorghum root hairs could be longer in less optimal conditions then the one they were grown in here. Studies on rice root type-dependent root hair formation also showed a high dependency on the growth media used [63, 64].
Root morphology of 30
The rhizotron-grown 30 genotypes showed root type-specific separation of root diameters (Figure 4B). For every genotype, nodal roots were not only thicker than primary roots, they did separate clearly with PRs ranging from ~300–550 μm and NRs from ~700–1,050 μm thickness. In contrast, their lateral roots had similar diameters, and both main roots (NR & PR) had ‘thin’ and ‘thick’ lateral roots, the first with ~100 μm diameter and little variation, the latter with higher variation from ~150–300 μm. In rice, distinct classes of lateral roots, S-type (thin) and L-type (thick) have been identified that are distinguishable by their diameter, but also branching ability [65, 66]. Recently those LR types have also been indicated to have different functions in water and nutrient uptake and transport [67, 68]. If these different diameters do also indicate different LR functions in Sorghum would be interesting to investigate in future experiments, especially with resource limited conditions. Interestingly, while the primary root diameter did significantly correlate with the diameter of its lateral roots, this was not found for nodal roots and nodal root lateral roots. This may be due to the higher variation in lateral root diameter on nodal roots. The genotypes ‘Tx436’, ‘Koro Kollo’, and ‘Tx631’ had thin roots, while ‘CSM-63’, ‘Feterita Gishesh’, and ‘Framida’ were among the biggest root types. Interestingly, ‘Kuyuma’ had very thick PR and NRs, but very thin lateral roots, especially on NRs, while ‘Ajabsido’ behaved contrastingly. Overall, the thicker the root, the longer root hairs were measured (Figure 4), a trend that has also been observed in maize [69] and in rice [63].
Already, sorghum is grown in regions where maize production might fail due to adverse drought conditions. One difference between maize and sorghum lies in their root systems. The phenotypic and genotypic variation within
For demonstration images (Figure 1) three different European sorghum genotypes were grown, WL08–713 and Zerberus from Germany, and SOR19 from Portugal. In the larger rhizotron screening 30 genotypes were grown, selected for variation in several physiological traits, including drought tolerance, flowering time, and origin (summarized in Table 1).
Fungicide-coated seeds were sown either in between sheets of moist (DI water) white filter paper, placed in square petri dishes wrapped with parafilm or placed in moist brown filter paper which was rolled and placed standing upright in a 5 l container with 1 l DI water. After 10 (white) and 14 (brown) days in a greenhouse chamber with 22°C day (16 h) and 18°C night (8 h) sorghum roots were observed for root system structure, sorgoleone production and root hair formation using a stereomicroscope (MX12.5, Leica).
Fungicide-coated seeds of 30 selected genotypes (Table 1) were sown in sheets of moist white filter paper, placed in a square petri dish and wrapped with parafilm. After two days a single germinated seed was placed into a rhizotron, four rhizotrons per genotype. The rhizotrons were 30x60 cm large and filled with 3 kg soil substrate (dried & sieved field soil 50:50 (v/v) mixed with dried organic soil low in nutrients “Nullerde”). Groups of six rhizotrons were grouped into a larger container, inclined to ~45° and covered to reduce light falling onto the transparent plexiglas side used for root imaging. The 30 genotypes in each replicate were randomized and grown in a greenhouse compartment at 24°C during the day (16 h, 70% humidity) and 20°C during nights (8 h, 90% humidity). After 7, 14, 18, and 21 DAS non-invasive phenotyping, and after 21 DAS invasive measurements were performed.
Seedlings grown in filter paper were unwrapped gently without removing them from the paper. Roots were photographed with a digital camera and primary and their branched lateral roots imaged under a stereomicroscope (MX12.5, Leica) to evaluate sorgoleone production, root diameter, and root hair formation (length and density).
For rhizotron-grown plants, at the given time points, roots and shoots of the 30 genotypes were non-invasively measured. Shoot length was measured until the tip of the youngest elongated leaf. The root systems of rhizotron-grown plants were imaged using a photo-station equipped with a digital camera. The PaintRhizo software (FZJ) was used to mark and track primary, lateral, and nodal roots separately over time.
At harvest, 21 DAS and following the last non-invasive measurements, shoots were cut off, dried for seven days in a 60°C oven and then weighted to determine total shoot dry weight. After shoot removal, rhizotrons were opened and the soil was gently removed by washing using running tap water. The primary root as well as the longest crown root were gently separated from the remaining root system. From these roots several 1 cm segments (at 5, 10, 20, 30, 40 cm from the root tip) were cut and transferred to 50% ethanol (p.a.) for subsequent root morphological analyses. The remaining root system was dried for seven days in 60°C and then weighted for root dry weight determination.
All root segments were imaged using a stereomicroscope (MX12.5, Leica) followed by analysis using the image J software (Fiji). Per root segment four images were taken; per image root diameter and ten root hairs were measured in length, while sorgoleone production was noted as presence or absence. Root hair density was scored following the procedure described in [63]. Distinguished were the primary root and the longest nodal root as well as their daughter roots, separated as ‘thick’ and ‘thin’ lateral roots.
The experimental data were analyzed with Excel (version 2019, Microsoft) and R (Rstudio, version 4.0.3). Genotypic variation per time point was analyzed by a one-way ANOVA followed by Tukey’s Honest Significant Difference (HSD) and the LSD (Least Significant Difference). Linear correlations over all plants was calculated as Pearson’s correlation.
We thank Andreas Neuwohner for technical support. We thank Professor Dr. Mitchell R. Tuinstra for selection and generous provision of seeds of the 30 diverse sorghum genotypes. JK was funded by a Feodor-Lynen-Return Fellowship of the Alexander-von-Humboldt Foundation (DEU/1151987). The authors acknowledge institutional funding by the Helmholtz Association (POF III Program – Key Technologies for the Bioeconomy).
The authors declare no conflict of interest.
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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. 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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 received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. 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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. 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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:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"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:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}},{id:"351158",title:"Prof.",name:"David W.",middleName:null,surname:"Anderson",slug:"david-w.-anderson",fullName:"David W. Anderson",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}},{id:"351159",title:"BSc.",name:"Kalum J.",middleName:null,surname:"Ost",slug:"kalum-j.-ost",fullName:"Kalum J. Ost",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}},{id:"325029",title:"Dr.",name:"Prem Chand",middleName:null,surname:"Jain",slug:"prem-chand-jain",fullName:"Prem Chand Jain",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Shiv Nadar University",country:{name:"India"}}},{id:"357275",title:"Dr.",name:"Thomas",middleName:null,surname:"Mih",slug:"thomas-mih",fullName:"Thomas Mih",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Buea",country:{name:"Cameroon"}}},{id:"305305",title:"Dr.",name:"Arturo Yosimar",middleName:null,surname:"Jaen-Cuellar",slug:"arturo-yosimar-jaen-cuellar",fullName:"Arturo Yosimar Jaen-Cuellar",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}},{id:"305315",title:"Dr.",name:"David Alejandro",middleName:null,surname:"Elvira-Ortiz",slug:"david-alejandro-elvira-ortiz",fullName:"David Alejandro Elvira-Ortiz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}},{id:"344374",title:"Dr.",name:"Manuel",middleName:null,surname:"Toledano-Ayala",slug:"manuel-toledano-ayala",fullName:"Manuel Toledano-Ayala",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}}]}},subseries:{item:{id:"8",type:"subseries",title:"Bioinspired Technology and Biomechanics",keywords:"Bioinspired Systems, Biomechanics, Assistive Technology, Rehabilitation",scope:'Bioinspired technologies take advantage of understanding the actual biological system to provide solutions to problems in several areas. Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. Possible contributions can address (but are not limited to) the following research topics: Bioinspired design and control of exoskeletons, orthoses, and prostheses; Experimental evaluation of the effect of assistive devices (e.g., influence on gait, balance, and neuromuscular system); Bioinspired technologies for rehabilitation, including clinical studies reporting evaluations; Application of neuromuscular and biomechanical models to the development of bioinspired technology.',coverUrl:"https://cdn.intechopen.com/series_topics/covers/8.jpg",hasOnlineFirst:!1,hasPublishedBooks:!0,annualVolume:11404,editor:{id:"144937",title:"Prof.",name:"Adriano",middleName:"De Oliveira",surname:"Andrade",slug:"adriano-andrade",fullName:"Adriano Andrade",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRC8QQAW/Profile_Picture_1625219101815",biography:"Dr. Adriano de Oliveira Andrade graduated in Electrical Engineering at the Federal University of Goiás (Brazil) in 1997. He received his MSc and PhD in Biomedical Engineering respectively from the Federal University of Uberlândia (UFU, Brazil) in 2000 and from the University of Reading (UK) in 2005. He completed a one-year Post-Doctoral Fellowship awarded by the DFAIT (Foreign Affairs and International Trade Canada) at the Institute of Biomedical Engineering of the University of New Brunswick (Canada) in 2010. Currently, he is Professor in the Faculty of Electrical Engineering (UFU). He has authored and co-authored more than 200 peer-reviewed publications in Biomedical Engineering. He has been a researcher of The National Council for Scientific and Technological Development (CNPq-Brazil) since 2009. He has served as an ad-hoc consultant for CNPq, CAPES (Coordination for the Improvement of Higher Education Personnel), FINEP (Brazilian Innovation Agency), and other funding bodies on several occasions. He was the Secretary of the Brazilian Society of Biomedical Engineering (SBEB) from 2015 to 2016, President of SBEB (2017-2018) and Vice-President of SBEB (2019-2020). He was the head of the undergraduate program in Biomedical Engineering of the Federal University of Uberlândia (2015 - June/2019) and the head of the Centre for Innovation and Technology Assessment in Health (NIATS/UFU) since 2010. He is the head of the Postgraduate Program in Biomedical Engineering (UFU, July/2019 - to date). He was the secretary of the Parkinson's Disease Association of Uberlândia (2018-2019). Dr. Andrade's primary area of research is focused towards getting information from the neuromuscular system to understand its strategies of organization, adaptation and controlling in the context of motor neuron diseases. His research interests include Biomedical Signal Processing and Modelling, Assistive Technology, Rehabilitation Engineering, Neuroengineering and Parkinson's Disease.",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,series:{id:"7",title:"Biomedical Engineering",doi:"10.5772/intechopen.71985",issn:"2631-5343"},editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",slug:"hitoshi-tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",slug:"marcus-vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",slug:"ramana-vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},onlineFirstChapters:{paginationCount:7,paginationItems:[{id:"79909",title:"Cryopreservation Methods and Frontiers in the Art of Freezing Life in Animal Models",doi:"10.5772/intechopen.101750",signatures:"Feda S. 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Moreover, in the field of machine learning, evolutionary computation has carved out a significant niche both in the generation of learning models and in the automatic design and optimization of hyperparameters in deep learning models. This collection aims to include quality volumes on various topics related to evolutionary algorithms and, alternatively, other metaheuristics of interest inspired by nature. For example, some of the issues of interest could be the following: Advances in evolutionary computation (Genetic algorithms, Genetic programming, Bio-inspired metaheuristics, Hybrid metaheuristics, Parallel ECs); Applications of evolutionary algorithms (Machine learning and Data Mining with EAs, Search-Based Software Engineering, Scheduling, and Planning Applications, Smart Transport Applications, Applications to Games, Image Analysis, Signal Processing and Pattern Recognition, Applications to Sustainability).",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",keywords:"Genetic Algorithms, Genetic Programming, Evolutionary Programming, Evolution Strategies, Hybrid Algorithms, Bioinspired Metaheuristics, Ant Colony Optimization, Evolutionary Learning, Hyperparameter Optimization"},{id:"26",title:"Machine Learning and Data Mining",scope:"The scope of machine learning and data mining is immense and is growing every day. It has become a massive part of our daily lives, making predictions based on experience, making this a fascinating area that solves problems that otherwise would not be possible or easy to solve. This topic aims to encompass algorithms that learn from experience (supervised and unsupervised), improve their performance over time and enable machines to make data-driven decisions. It is not limited to any particular applications, but contributions are encouraged from all disciplines.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",keywords:"Intelligent Systems, Machine Learning, Data Science, Data Mining, Artificial Intelligence"},{id:"27",title:"Multi-Agent Systems",scope:"Multi-agent systems are recognised as a state of the art field in Artificial Intelligence studies, which is popular due to the usefulness in facilitation capabilities to handle real-world problem-solving in a distributed fashion. 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We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",keywords:"Collaborative Intelligence, Learning, Distributed Control System, Swarm Robotics, Decision Science, Software Engineering"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:{title:"Artificial Intelligence",id:"14"},selectedSubseries:null},seriesLanding:{item:{id:"7",title:"Biomedical Engineering",doi:"10.5772/intechopen.71985",issn:"2631-5343",scope:"Biomedical Engineering is one of the fastest-growing interdisciplinary branches of science and industry. 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Dr. Koprowski has authored more than a hundred research papers with dozens in impact factor (IF) journals and has authored or co-authored six books. Additionally, he is the author of several national and international patents in the field of biomedical devices and imaging. Since 2011, he has been a reviewer of grants and projects (including EU projects) in biomedical engineering.",institutionString:null,institution:{name:"University of Silesia",institutionURL:null,country:{name:"Poland"}}},subseries:[{id:"7",title:"Bioinformatics and Medical Informatics",keywords:"Biomedical Data, Drug Discovery, Clinical Diagnostics, Decoding Human Genome, AI in Personalized Medicine, Disease-prevention Strategies, Big Data Analysis in Medicine",scope:"Bioinformatics aims to help understand the functioning of the mechanisms of living organisms through the construction and use of quantitative tools. The applications of this research cover many related fields, such as biotechnology and medicine, where, for example, Bioinformatics contributes to faster drug design, DNA analysis in forensics, and DNA sequence analysis in the field of personalized medicine. Personalized medicine is a type of medical care in which treatment is customized individually for each patient. Personalized medicine enables more effective therapy, reduces the costs of therapy and clinical trials, and also minimizes the risk of side effects. Nevertheless, advances in personalized medicine would not have been possible without bioinformatics, which can analyze the human genome and other vast amounts of biomedical data, especially in genetics. The rapid growth of information technology enabled the development of new tools to decode human genomes, large-scale studies of genetic variations and medical informatics. 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Recently, bioinspired systems have been successfully employing biomechanics to develop and improve assistive technology and rehabilitation devices. The research topic "Bioinspired Technology and Biomechanics" welcomes studies reporting recent advances in bioinspired technologies that contribute to individuals\' health, inclusion, and rehabilitation. 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We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics can include but are not limited to: Biotechnology such as biotechnological products and process engineering; Biotechnologically relevant enzymes and proteins; Bioenergy and biofuels; Applied genetics and molecular biotechnology; Genomics, transcriptomics, proteomics; Applied microbial and cell physiology; Environmental biotechnology; Methods and protocols. Moreover, topics in biosensor technology, like sensors that incorporate enzymes, antibodies, nucleic acids, whole cells, tissues and organelles, and other biological or biologically inspired components will be considered, and topics exploring transducers, including those based on electrochemical and optical piezoelectric, thermal, magnetic, and micromechanical elements. Chapters exploring biomaterial approaches such as polymer synthesis and characterization, drug and gene vector design, biocompatibility, immunology and toxicology, and self-assembly at the nanoscale, are welcome. 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