Weight of fever.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"3092",leadTitle:null,fullTitle:"Anopheles mosquitoes - New insights into malaria vectors",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",reviewType:"peer-reviewed",abstract:"Anopheles mosquitoes are highly important insects due to their involvement in the transmission of human malaria and its devastating consequences in endemic countries worldwide. In 2010 alone, malaria was responsible for an estimated 660,000 deaths. As the study of Anopheles species and populations is a key element for reaching the goal of malaria elimination, an enormous amount of information has accumulated over the past century, and together in recent decades with the advent of novel technologies the acquisition of new knowledge has accelerated even further. The originality of this book is to offer the latest compilation on various research, new concepts, paradigms and innovative approaches for the control of anophelines using state-of-the-art methodologies and analysis. The 24 chapters, written by internationally recognized experts from 5 continents, cover the rich landscape for the understanding of Anopheles mosquitoes and the development of more effective weapons to control the vector of malaria.",isbn:null,printIsbn:"978-953-51-1188-7",pdfIsbn:"978-953-51-4244-7",doi:"10.5772/3392",price:169,priceEur:185,priceUsd:219,slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",numberOfPages:830,isOpenForSubmission:!1,isInWos:1,isInBkci:!0,hash:"c9e622485316d5e296288bf24d2b0d64",bookSignature:"Sylvie Manguin",publishedDate:"July 24th 2013",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",numberOfDownloads:90613,numberOfWosCitations:545,numberOfCrossrefCitations:315,numberOfCrossrefCitationsByBook:29,numberOfDimensionsCitations:744,numberOfDimensionsCitationsByBook:37,hasAltmetrics:1,numberOfTotalCitations:1604,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 7th 2012",dateEndSecondStepPublish:"March 28th 2012",dateEndThirdStepPublish:"November 1st 2012",dateEndFourthStepPublish:"September 30th 2012",dateEndFifthStepPublish:"February 27th 2013",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,8,9,10",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"50017",title:"Prof.",name:"Sylvie",middleName:null,surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin",profilePictureURL:"https://mts.intechopen.com/storage/users/50017/images/3936_n.png",biography:"Sylvie Manguin is a Full Research Professor at the Institute of Research for Development (IRD), based at the University of Montpellier, France. She is a leading medical entomologist and academician researcher whose main interest concerns mosquitoes and vector-borne diseases such as malaria and dengue. She has developed studies on Anopheles mosquitoes from three continents (Asia, Africa, Americas) including molecular species identification, population genetics, phylogenetic, vectorial capacities, spatial surveillance, midgut microbiota biodiversity, salivary immunological markers and vector control approaches. She is the author of 90 indexed publications, six book chapters, three books including “Anopheles mosquitoes: New insights into malaria vectors” for which she is the Editor (InTech Open Access) and “Biodiversity of malaria in the World” (John Libbey Ed.), respectively published in 2013 and 2008. She is also the Secretary General of the International Federation of Tropical Medicine (IFTM) http://www.iftm-hp.org/board.html, member of the Editorial Boards of the Malaria Journal and Acta Tropica and she serves as reviewer in several international institutions and more than 20 scientific journals.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"Institut de Recherche pour le Développement",institutionURL:null,country:{name:"France"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1046",title:"Infectious Diseases",slug:"infectious-diseases"}],chapters:[{id:"41407",title:"The Phylogeny and Classification of Anopheles",doi:"10.5772/54695",slug:"the-phylogeny-and-classification-of-anopheles",totalDownloads:4834,totalCrossrefCites:31,totalDimensionsCites:69,hasAltmetrics:0,abstract:null,signatures:"Ralph E. 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Akyar"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},onlineFirst:{chapter:{type:"chapter",id:"74830",title:"Fuzzy Multi-Attribute Decision Making (FMADM) Application on Decision Support Systems (SPK) to Diagnose a Type of Disease",doi:"10.5772/intechopen.94614",slug:"fuzzy-multi-attribute-decision-making-fmadm-application-on-decision-support-systems-spk-to-diagnose-",body:'Decision making is a problem solving process that produces a goal of factors such as subjectivity and linguistics which tend to be presented in real life to a lower or greater level [1]. Difficulties are often encountered when a problem involves several alternatives and the factors that influence it (criteria), to overcome this problem, it is able to use the Multi-Attribute Decison Making (MADM) method. The results of these methods still contain uncertainty so that in this case fuzzy logic plays an important role in overcoming problems that contain uncertainty. Fuzzy logic is the basis of a system that can implement a problem and solve sharp problems [2]. However, Fuzzy MADM is only able to solve the problem of uncertainty in the data presented and numbers of diverse attributes is usually conflicting, thus to make a decision there needs to be a classic MADM method, so that decisions are more precise and more accurate [3], besides this method can also be used to provide input to the doctor so that there is no mistake in diagnosing dengue disease. One of the classic MADM methods that can be used is Simple Additive Weighting.
Simple Additive Weighting is often referred as a method with weighted sum. The basic concept of SAW method is to find a weighted sum of performance branches on each alternative of all attributes [4]. One of the problems that can be solved by this method is the misdiagnosis of DHF. DHF is a type of infectious disease caused by the degue virus which is transmitted through the bite of the
The data used are primary and secondary data, primary data obtained from the results of doctor interviews and secondary data is data on patients with DHF, secondary data will be used to validate the system. Completion of cases of dengue diagnosis will be through SAW method then the results of SAW method are used in the FDM method.
The first method will use one crisp value with 1 degree membership and use preference weight multiplication while the second method uses 3 crisp values namely right boundary, left boundary and crisp value with 1 membership degree which will later go through the aggregation process and total integral value.
Completion using the FMADM method with SAW:
Alternative (Ai) is a1 = Morbili, a2 = DBD, a3 = ARI, a4 = Typoid fever, a5 = Acute pharyngitis, a6 = Ensafalitis. Ci criteria are c1 = Fever, c2 = Spots, c3 = Bleeding gum, c4 = Nausea, c5 = Headache, c6 = Defecation Disorders
The weight of the criteria is obtained from triangular fuzzy numbers which are then converted into the form of crisp.
The author defines the universal value for the criteria for fever is [0,1] and divides it into 5 categories of fuzzy triangle sets, which are normal (N), low fever (DR), moderate fever (DS), high fever (DT), very high fever (DST).
By using the concept of the Likert scale and the defuzzy method, Large of Maximum, Table 1 is obtained as the weight of the criteria for fever.
Fever | Fuzzy Set | Crisp Value (weight) |
---|---|---|
36°C-37,5°C | Normal (N) | |
37,5–38°C | Low Fever (DR) | |
38°C-39,5 °C | Moderate Fever (DS) | |
39,5–40°C | High Fever (DT) | |
>40°C | Very High Fever (DST) |
Weight of fever.
The author defines the universal value for the criteria of spots is [0,1] and divides them into 5 categories of fuzzy triangle sets which are none (TA), few (SDK), somewhat a lot (ABYK) many (BYK), very much (SBYK). By using the concept of the Likert scale and the defuzzy method, Large of Maximum, the Table 2 is obtained as the weight of the criteria for spots:
Spots | Fuzzy Set | Crisp Value (weight) |
---|---|---|
0–10 spots | None (TA) | |
10–20 spots | few (SDK) | |
20–30 spots | Somewhat a lot (ABYK) | |
30–50 spots | Many (BYK) | |
>50 spots | Very Much (SBYK) |
Weigth of spots.
We are defines the universal value for bleeding gum criteria is [0,1] and divides it into 2 fuzzy triangle set categories namely never (TP), ever (P). By using the concept of the Likert scale and the defuzzy method, Large Of Maximum, the Table 3 is obtained as the weight of the bleeding gum criteria.
Bleeding Gums | Fuzzy Sets | Crisp Value (weight) |
---|---|---|
0 No | Never (TP) | 0 |
Once or More | Ever (P) | 1 |
Weight of bleeding gum.
The author defines the universe value for the nausea criteria is [0.1] and divides it into 4 fuzzy triangle set categories namely never (TP), ever (P), rare (J) and often (S). By using the concept of the Likert scale and the defuzzy method, Large of Maximum, Table 4 is obtained as the weight of the criteria for nausea.
Nausea | Fuzzy Sets | Crisp Value (weight) |
---|---|---|
0 | Never (TP) | |
1 time a day | Ever (P) | |
2–3 times a day | Rare (J) | |
>3 times a day | Often (S) |
Weigth of nausea.
The author defines the universal value for the headache criteria is [0,1] and divides it into 4 fuzzy triangle set categories namely never (TP), ever (P), rarely (J) and often (S). By using the concept of the Likert scale and the defuzzy method, namely Large Of Maximum, Table 5 is obtained as the weight of the headache criteria.
Headache | Fuzzy Set | Crisp Value (weight) |
---|---|---|
0 | Never (TA) | |
1 time a day | Ever (P) | |
3–4 times a day | Rare (J) | |
4–5 times a day | Often (S) |
Weight of headache.
The author defines the universal value for the criteria for defecation disorder is [0,1] and divides it into 3 categories of fuzzy triangles, namely normal (N), difficult to do defecation (SB) and diarrhea (D). By using the concept of the Likert scale and the defuzzy method, Large of Maximum, Table 6 is obtained as the weight of the criteria for BAB defects.
Defecation Disorder | Fuzzy Set | Crisp Value (weight) |
---|---|---|
1–2 times a day | Normal (N) | |
1–2 days unable to do defecation | Hard to do Defecation (SB) | |
>3 times a day | Diarrhea (D) |
Defecation disorder weight.
Interview results from an expert (doctor) on Table 7.
c1 | c2 | c3 | c4 | c5 | c6 | |
---|---|---|---|---|---|---|
a1 | DT | SDK | TP | J | P | SB |
a2 | DT | SBYK | P | J | J | D |
a3 | DT | TA | TP | T | J | N |
a4 | DST | SDK | TP | P | S | D |
a5 | DS | TA | TP | S | P | N |
a6 | DST | TA | TP | J | S | SB |
Linguistics data.
From the Table 8, the match rating value is obtained as follows:
c1 | c2 | c3 | c4 | c5 | c6 | |
---|---|---|---|---|---|---|
a1 | 0.75 | 0.25 | 0 | 0.5 | 0.25 | 1 |
a2 | 0.75 | 1 | 1 | 0.5 | 0.5 | 0.75 |
a3 | 0.75 | 0.25 | 0 | 0 | 0.5 | 0.5 |
a4 | 1 | 0 | 0 | 0.75 | 0.75 | 0.75 |
a5 | 0.5 | 0 | 0 | 0.5 | 0.25 | 0.5 |
a6 | 1 | 0 | 0 | 0.5 | 0.75 | 1 |
Match rating value.
The compatibility rating in this method is also called the decision matrix which will be normalized.
The determination of the preference weight is stated in Table 9 as follows:
c1 | c2 | c3 | c4 | c5 | c6 | Total |
---|---|---|---|---|---|---|
30% | 30% | 10% | 10% | 10% | 10% | 100% |
0.3 | 0.3 | 0.1 | 0.1 | 0.1 | 0.1 | 1 |
Preference weight (W).
To find a matrix you can use the following formula:
The results of the calculation are shown in Table 10 as follows.
(Morbili) | |||||
---|---|---|---|---|---|
0.5 | 0.83 | 0.42 | 0.58 | 0.30 | 0.57 |
Rank 4 | Rank 1 | Rank 6 | Rank 2 | Rank 5 | Rank 3 |
Preference value.
The highest value achieved by the second alternative (
In this case, SAW method is not appropriate if it is used to make a decision support system thus the author tries to use a method developed by Joo (2004) [6], namely the FMADM method with development or FDM.
Consists of 3 stages, namely:
Objective Identification
The purpose of this decision is to determine or diagnose an illness that is suffered based on the initial symptoms experienced.
Identification of Criteria and Alternatives.
The criteria used are still 6 types of diseases and 6 criteria (symptoms).
The hierarchical structure that determines the disease is shown in the Figure 1.
Hierarchy Structure.
Consists of 4 stages, namely:
a. Selecting the set of ratings for the criteria weights. There are two things that must be done, namely determining the degree of importance and determining the degree of compatibility. T (importance) W = {
The parameters of each level of interest are as follows:
The degree of compatibility of each decision criteria as follows:
Based on this, the degree of compatibility of each alternative is obtained to the decision criteria in Table 11 and the branch of interest for the decision criteria in Table 12.
c1 | c2 | c3 | c4 | c5 | c6 | |
---|---|---|---|---|---|---|
a1 | T | R | SR | C | R | ST |
a2 | T | ST | R | C | C | T |
a3 | T | ST | SR | SR | C | C |
a4 | ST | R | SR | T | T | T |
a5 | C | SR | SR | C | C | C |
a6 | ST | SR | SR | C | T | ST |
The degree of compatibility of each alternative to the decision criteria.
Fever | Spot | Bleeding gum | Nausea | Headache | Defecation Disorder |
---|---|---|---|---|---|
High | Very Much | Ever | Rare | Rare | Diarrhea |
(0.5,0.75, 1) | (0.75,1, 1) | (0, 1, 1) | (0.25, 0.5, 0.75) | (0.25, 0.5, 0.75) | (0.5, 0.75, 1) |
Branch of interest for decision criteria.
b. Aggregate the weight of criteria and the degree of compatibility of each alternative with its criteria, using the following equation:
The result is compatibility index obtained from the aggregation of the weight of the criteria and the degree of compatibility of each alternative with its criteria that’s shown in Table 13.
Alternative | Compatibility Rate | Fuzzy Compatibility Index | |||||||
---|---|---|---|---|---|---|---|---|---|
c1 | c2 | c3 | c4 | c5 | c6 | Yi | Qi | Zi | |
a1 | T | R | SR | C | R | ST | 0.1146 | 0.3229 | 0.6146 |
a2 | T | ST | R | C | C | T | 0.1979 | 0.4792 | 0.7708 |
a3 | T | ST | SR | SR | C | C | 0.1667 | 0.3646 | 0.6250 |
a4 | ST | R | SR | T | T | T | 0.1458 | 0.3854 | 0.7083 |
a5 | C | SR | SR | C | C | C | 0.0625 | 0.2083 | 0.5208 |
a6 | ST | SR | SR | C | T | ST | 0.1563 | 0.3542 | 0.6354 |
Compatibility index.
Prioritizing decision alternatives based on aggregation results by substituting the fuzzy match index value into the following equation:
By taking optimism degree (α), namely: α = 0 (not optimistic), α = 0.5 (optimistic) and α = 1 (very optimistic). The following results are obtained on Table 14.
Alternative | Integral Total Value | ||
---|---|---|---|
α = 0 | α = 0.5 | α = 1 | |
a1 | 0.22 | 0.34 | 0.47 |
a2 | 0.34 | 0.48 | 0.63 |
a3 | 0.27 | 0.38 | 0.49 |
a4 | 0.27 | 0.47 | 0.55 |
a5 | 0.14 | 0.25 | 0.36 |
a6 | 0.26 | 0.37 | 0.49 |
Integral total value.
Based on the results above, it can be seen that regardless of the degree of optimism, the alternative a2 is that DHF has the greatest value compared to other alternatives.
The following figure (Figure 2) is a flowchart that shows how decision support system works.
Decision Support System Algorithm.
Based on the
View of GUI (Opening).
Figure 4 is the appearance of the two
GUI Display (Form Filling).
Following are the steps to diagnose a type of disease: Fill in the biodata form and symptoms, then click the diagnosis button then click the save button. The results of the diagnosis are obtained as follows like what’s shown in Figure 5.
GUI Display (Diagnose Result).
The storage results are displayed in a form of what’s shown in Figure 6.
GUI Display (Data Base).
The accuracy of the FMADM decision support system with MAPE obtained the following equation
Obtained from 30 data is as follows:
Based on the method in the first stage, the FMADM method with SAW rank 1 was obtained in the second alternative
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Bouallègue, J. Haggège and M. Benrejeb",authors:[{id:"141915",title:"Dr.",name:"Soufiene",middleName:null,surname:"Bouallegue",slug:"soufiene-bouallegue",fullName:"Soufiene Bouallegue"}]},{id:"39435",doi:"10.5772/48529",title:"Fuzzy Control Systems: LMI-Based Design",slug:"fuzzy-control-systems-lmi-based-design",totalDownloads:4663,totalCrossrefCites:6,totalDimensionsCites:7,abstract:null,book:{id:"2229",slug:"fuzzy-controllers-recent-advances-in-theory-and-applications",title:"Fuzzy Controllers",fullTitle:"Fuzzy Controllers - Recent Advances in Theory and Applications"},signatures:"Morteza Seidi, Marzieh Hajiaghamemar and Bruce Segee",authors:[{id:"145408",title:"Mr.",name:"Morteza",middleName:null,surname:"Seidi",slug:"morteza-seidi",fullName:"Morteza Seidi"},{id:"147329",title:"Ms.",name:"Marzieh",middleName:null,surname:"Hajiaghamemar",slug:"marzieh-hajiaghamemar",fullName:"Marzieh Hajiaghamemar"},{id:"155198",title:"Dr.",name:"Bruce",middleName:null,surname:"Segee",slug:"bruce-segee",fullName:"Bruce Segee"}]},{id:"39429",doi:"10.5772/47798",title:"A Type-2 Fuzzy Model Based on Three Dimensional Membership Functions for Smart Thresholding in Control Systems",slug:"a-type-2-fuzzy-model-based-on-three-dimensional-membership-functions-for-smart-thresholding-in-contr",totalDownloads:3329,totalCrossrefCites:2,totalDimensionsCites:6,abstract:null,book:{id:"2229",slug:"fuzzy-controllers-recent-advances-in-theory-and-applications",title:"Fuzzy Controllers",fullTitle:"Fuzzy Controllers - Recent Advances in Theory and Applications"},signatures:"M.H. Fazel Zarandi, Fereidoon Moghadas Nejad and H. Zakeri",authors:[{id:"142009",title:"Prof.",name:"Mohammad Hossein",middleName:null,surname:"Fazel Zarandi",slug:"mohammad-hossein-fazel-zarandi",fullName:"Mohammad Hossein Fazel Zarandi"},{id:"160785",title:"Ph.D.",name:"H",middleName:null,surname:"Zakeri",slug:"h-zakeri",fullName:"H Zakeri"},{id:"160872",title:"Prof.",name:"Freeidon",middleName:null,surname:"Moghadas Nejad",slug:"freeidon-moghadas-nejad",fullName:"Freeidon Moghadas Nejad"}]},{id:"52178",doi:"10.5772/64951",title:"Adaptive Building Envelope: An Integral Approach to Indoor Environment Control in Buildings",slug:"adaptive-building-envelope-an-integral-approach-to-indoor-environment-control-in-buildings",totalDownloads:2091,totalCrossrefCites:5,totalDimensionsCites:4,abstract:"The problem of energy consumption of buildings is complex and multidimensional, as it is a cross section of building envelope performance, indoor environmental conditions and user demands and preferences. In order to fulfil the EU goal stated in the 2020 climate and energy package and beyond, the implementation of high-performance buildings is crucial. Part of the solution is properly designed, flexible and adequately controlled building envelope that can contribute to reduced energy consumption and to increased occupancy comfort. In the presented chapter first, a structured treatment of the indoor environment formation is proposed that can be used in order to define appropriate fields of interventions when designing building automation systems. Furthermore, interaction between adaptive building envelope elements, indoor and exterior environment is discussed and elaborated. Second, the conventional and artificial intelligence control approaches used in building automation are discussed and commented, whereas advantages and disadvantages of each group are discussed. At the end, an example of building automation system designed on the principles of a holistic treatment of indoor environment in buildings is presented. The discussed system was designed at the Faculty of Civil and Geodetic Engineering using a combination of conventional and artificial intelligence control methods.",book:{id:"5238",slug:"automation-and-control-trends",title:"Automation and Control Trends",fullTitle:"Automation and Control Trends"},signatures:"Mitja Košir",authors:[{id:"182476",title:"Dr.",name:"Mitja",middleName:null,surname:"Košir",slug:"mitja-kosir",fullName:"Mitja Košir"}]}],mostDownloadedChaptersLast30Days:[{id:"39423",title:"Output Tracking Control for Fuzzy Systems via Static-Output Feedback Design",slug:"output-tracking-control-for-fuzzy-systems-via-static-output-feedback-design",totalDownloads:2310,totalCrossrefCites:1,totalDimensionsCites:2,abstract:null,book:{id:"2229",slug:"fuzzy-controllers-recent-advances-in-theory-and-applications",title:"Fuzzy Controllers",fullTitle:"Fuzzy Controllers - Recent Advances in Theory and Applications"},signatures:"Meriem Nachidi and Ahmed El Hajjaji",authors:[{id:"25659",title:"Prof.",name:"Ahmed",middleName:null,surname:"El Hajjaji",slug:"ahmed-el-hajjaji",fullName:"Ahmed El Hajjaji"},{id:"141360",title:"Dr.",name:"Meriem",middleName:null,surname:"Nachidi",slug:"meriem-nachidi",fullName:"Meriem Nachidi"}]},{id:"51207",title:"Human Movement Control",slug:"human-movement-control",totalDownloads:2103,totalCrossrefCites:0,totalDimensionsCites:2,abstract:"Control theory is used to design automatic systems, which are able to maintain a desired behaviour despite of the disturbances. It is present in different machines we use every day; in fact, technical systems in our homes and all the industries are hard to imagine today without these concepts. Moreover, the same theories can be used for modelling life processes as a collection of inputs, outputs, plants and control loops. Feedback is one of the main concepts behind control; in particular, several examples of physiological control mechanisms for regulating life aspects can be found in the human anatomy, for example, blood pressure, cholesterol levels, body movements, the equilibrium, etc. Those processes can be damaged by the aging effects, diseases, accidents or when the mechanism has been broken and cannot be recovered naturally; consequently, it will be required external assistance. A relative new field in control theory is related with developing technology for helping with physiological and medicals problems. However, in comparison with machines, those physiological processes are highly nonlinear, with delays and slow responses. Another problem is when human becomes the operators using their capacities of decision making to close the control loop, as they are prone to errors and mistakes. For those reasons, the biomedical system needs to be carefully designed and several aspects have to be considered. This chapter gives a small review of some internal and external control processes within the human body and discusses how to interact with them for designing biomedical devices. Under this design scheme, a practical application of a smart electric wheelchair for assisting persons with strong disabilities is presented. These assistive robotic systems are in close contact with the user, and thus, it is determinant to have a user-friendly relation between the human and the interface. Therefore, intuitive interfaces were included in the design and an intelligent navigation assistant to guarantee a collision-free path.",book:{id:"5238",slug:"automation-and-control-trends",title:"Automation and Control Trends",fullTitle:"Automation and Control Trends"},signatures:"David Balderas and Mario Rojas",authors:[{id:"183076",title:"M.Sc.",name:"David",middleName:null,surname:"Balderas Silva",slug:"david-balderas-silva",fullName:"David Balderas Silva"},{id:"184877",title:"MSc.",name:"Mario",middleName:null,surname:"Rojas",slug:"mario-rojas",fullName:"Mario Rojas"}]},{id:"51070",title:"Fuzzy PD Controller in NAO System's Platform",slug:"fuzzy-pd-controller-in-nao-system-s-platform",totalDownloads:1565,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"Humanoid robotic platforms rarely achieve the desire trajectory because of the deviation generated during the robot walking. This problem is due to different circumstances such as robot manufacturing, wear and tear of mechanic parts, or variations of floor flatness. Currently, one of the humanoid robots on the market is the robotic platform developed by Aldebaran Robotics called NAO robot, and it is used for different purposes where the robot needs to navigate into controlled spaces. NAO presents the issue of deviation during walking; therefore, a Fuzzy PD Controller is developed and implemented for this platform to reduce the orientation error and to ensure reliability during navigation. Inertial sensors are used to get the orientation reference and for feedback of the closed-loop control. Consequently, a robust control was implemented and tested in different conditions of floor and velocity during the robot’s navigation such as robot races and maze resolution. Experimental results show that fuzzy controller achieves significant improvements in the trajectories of NAO.",book:{id:"5238",slug:"automation-and-control-trends",title:"Automation and Control Trends",fullTitle:"Automation and Control Trends"},signatures:"Edgar Omar López‐Caudana and César Daniel González Gutiérrez",authors:[{id:"26464",title:"Dr.",name:"Edgar",middleName:"Omar",surname:"Lopez-Caudana",slug:"edgar-lopez-caudana",fullName:"Edgar Lopez-Caudana"},{id:"185936",title:"Mr.",name:"César Daniel",middleName:null,surname:"González Gutiérrez",slug:"cesar-daniel-gonzalez-gutierrez",fullName:"César Daniel González Gutiérrez"}]},{id:"51186",title:"Aircraft Landing Control Using the H-inf Control and the Dynamic Inversion Technique",slug:"aircraft-landing-control-using-the-h-inf-control-and-the-dynamic-inversion-technique",totalDownloads:1604,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"The chapter presents the automatic control of aircraft during landing, taking into account the sensor errors and the wind shears. Both planes—longitudinal and lateral-directional—are treated; the new obtained automatic landing system (ALS) will consists of two subsystems—the first one controls aircraft motion in longitudinal plane, while the second one is for the control of aircraft motion in lateral-directional plane. These two systems can be treated separately, but in the same time, these can be put together to control all the parameters which interfere in the dynamics of aircraft landing. The two new ALSs are designed by using the H-inf control, the dynamic inversion, optimal observers, and reference models. To validate the new obtained ALS, one uses the dynamics associated to the landing of a Boeing 747, software implements the theoretical results and analyzes the accuracy of the results and the precision standards' achievement with respect to the requirements of the Federal Aviation Administration (FAA).",book:{id:"5238",slug:"automation-and-control-trends",title:"Automation and Control Trends",fullTitle:"Automation and Control Trends"},signatures:"Romulus Lungu and Mihai Lungu",authors:[{id:"181904",title:"Prof.",name:"Romulus",middleName:null,surname:"Lungu",slug:"romulus-lungu",fullName:"Romulus Lungu"}]},{id:"51936",title:"Models for the Reliability Analysis of Digital Instrumentation and Control Systems for Nuclear Power Plants",slug:"models-for-the-reliability-analysis-of-digital-instrumentation-and-control-systems-for-nuclear-power",totalDownloads:1779,totalCrossrefCites:3,totalDimensionsCites:3,abstract:"The objective of this chapter is to discuss two approaches for reliability analysis of digital instrumentation and control systems in nuclear power plants taking into account the regulatory side. Dynamic Flowgraph Methodology (DFM) and Markov/Cell-to-Cell Mapping Technique (CCMT) are discussed and case studies developed are presented. These case studies involve simplified control systems for a steam generator and a pressurizer of a Pressurized Water Reactor (PWR) plant for the purpose of evaluating each method. Advantages and limitations of each approach are addressed. For the DFM approach, three concerns in the literature are addressed: modeling of the system itself, incorporation of the methodology results into existing Probabilistic Safety Assessments (PSA), and identification of software failures. The Markov/CCMT, which has been used in dynamic probabilistic safety assessments, is approached by means of a simplified digitally controlled water volume control system. The Markov/CCMT methodology results in detailed data of the system reliability behavior in relation to time. However, it demands a higher computational effort than usual as the complexity (i.e., number of components and failure states) of the system increases. As a regulatory research conclusion, the methodologies presented can be used on PSA risk informed assessment, contributing to the regulatory side.",book:{id:"5238",slug:"automation-and-control-trends",title:"Automation and Control Trends",fullTitle:"Automation and Control Trends"},signatures:"Jonathan M. O. Pinto, Ian B. Gomes, Pedro L. C. Saldanha, Eustério\nB. Furieri and Paulo F. F. e Melo",authors:[{id:"26628",title:"Prof.",name:"Paulo",middleName:null,surname:"Frutuoso e Melo",slug:"paulo-frutuoso-e-melo",fullName:"Paulo Frutuoso e Melo"},{id:"30429",title:"Dr.",name:"Pedro Luiz da C.",middleName:null,surname:"Saldanha",slug:"pedro-luiz-da-c.-saldanha",fullName:"Pedro Luiz da C. 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The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"25",title:"Environmental Sciences",doi:"10.5772/intechopen.100362",issn:"2754-6713",scope:"\r\n\tScientists have long researched to understand the environment and man’s place in it. The search for this knowledge grows in importance as rapid increases in population and economic development intensify humans’ stresses on ecosystems. Fortunately, rapid increases in multiple scientific areas are advancing our understanding of environmental sciences. Breakthroughs in computing, molecular biology, ecology, and sustainability science are enhancing our ability to utilize environmental sciences to address real-world problems.
\r\n\tThe four topics of this book series - Pollution; Environmental Resilience and Management; Ecosystems and Biodiversity; and Water Science - will address important areas of advancement in the environmental sciences. They will represent an excellent initial grouping of published works on these critical topics.