Sources and types of solid wastes [10].
\\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:"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:"6129",leadTitle:null,fullTitle:"Kalman Filters - Theory for Advanced Applications",title:"Kalman Filters",subtitle:"Theory for Advanced Applications",reviewType:"peer-reviewed",abstract:"This book presents recent issues on theory and practice of Kalman filters, with a comprehensive treatment of a selected number of concepts, techniques, and advanced applications. From an interdisciplinary point of view, the contents from each chapter bring together an international scientific community to discuss the state of the art on Kalman filter-based methodologies for adaptive/distributed filtering, optimal estimation, dynamic prediction, nonstationarity, robot navigation, global navigation satellite systems, moving object tracking, optical communication systems, and active power filters, among others. The theoretical and methodological foundations combined with extensive experimental explanation make this book a reference suitable for students, practicing engineers, and researchers in sciences and engineering.",isbn:"978-953-51-3828-0",printIsbn:"978-953-51-3827-3",pdfIsbn:"978-953-51-4038-2",doi:"10.5772/intechopen.68249",price:139,priceEur:155,priceUsd:179,slug:"kalman-filters-theory-for-advanced-applications",numberOfPages:314,isOpenForSubmission:!1,isInWos:1,isInBkci:!1,hash:"7341ee991eeb22a10a8b14bcd53a24b6",bookSignature:"Ginalber Luiz de Oliveira Serra",publishedDate:"February 21st 2018",coverURL:"https://cdn.intechopen.com/books/images_new/6129.jpg",numberOfDownloads:21378,numberOfWosCitations:30,numberOfCrossrefCitations:36,numberOfCrossrefCitationsByBook:7,numberOfDimensionsCitations:50,numberOfDimensionsCitationsByBook:8,hasAltmetrics:0,numberOfTotalCitations:116,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 18th 2017",dateEndSecondStepPublish:"May 9th 2017",dateEndThirdStepPublish:"August 5th 2017",dateEndFourthStepPublish:"November 3rd 2017",dateEndFifthStepPublish:"January 2nd 2018",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"11032",title:"Dr.",name:"Ginalber Luiz",middleName:"De Oliveira",surname:"Serra",slug:"ginalber-luiz-serra",fullName:"Ginalber Luiz Serra",profilePictureURL:"https://mts.intechopen.com/storage/users/11032/images/3436_n.jpg",biography:"Dr. Ginalber L. O. Serra was born in São Luis, Maranhão, Brazil, in 1976. He received the B.Sc. and M. Sc. degrees in electrical engineering from Federal University of Maranhão, Maranhão, Brazil, in 1999 and 2001, respectively. He received the Ph.D. degree in electrical engineering from State University of Campinas (UNICAMP), Campinas, Brazil, on September 2005. He has finished his Postdoctoral research on multivariable neuro-fuzzy adaptive control of nonlinear systems at the Department of Machines, Components and Intelligent Systems, State University of Campinas, Campinas, Brazil, on September 2006 and he has served as researcher with the Department of Electrical Engineering at the University of Santiago, Santiago, Chile, in 2007. Currently, Dr. Serra is with the Department of ElectroElectronics at Federl Institute of Education, Cience and Technology, São Luis, Maranhão, Brazil. Dr. Serra has served as Reviewer for many prestigious international journals, including the IEEE TRANSACTIONS ON FUZZY SYSTEMS, IEEE TRANSACTIONS ON SYSTEMS, MAN AND CYBERNETICS - PART B: CYBERNETICS, IEE CONTROL THEORY AND APPLICATIONS, and for papers from {\\\\em IEEE Conferences}. His research interests include fuzzy systems, neural networks and genetic algorithms applied to identification and control of nonlinear systems.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"Instituto Federal do Maranhão",institutionURL:null,country:{name:"Brazil"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1401",title:"Control Theory",slug:"applied-mathematics-control-theory"}],chapters:[{id:"58317",title:"A Reference Recursive Recipe for Tuning the Statistics of the Kalman Filter",doi:"10.5772/intechopen.71961",slug:"a-reference-recursive-recipe-for-tuning-the-statistics-of-the-kalman-filter",totalDownloads:1463,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:0,abstract:"The philosophy and the historical development of Kalman filter from ancient times to the present is followed by the connection between randomness, probability, statistics, random process, estimation theory, and the Kalman filter. A brief derivation of the filter is followed by its appreciation, aesthetics, beauty, truth, perspectives, competence, and variants. The menacing and notorious problem of specifying the filter initial state, measurement, and process noise covariances and the unknown parameters remains in the filter even after more than five decades of enormous applications in science and technology. Manual approaches are not general and the adaptive ones are difficult. The proposed reference recursive recipe (RRR) is simple and general. The initial state covariance is the probability matching prior between the Frequentist approach via optimization and the Bayesian filtering. The filter updates the above statistics after every pass through the data to reach statistical equilibrium within a few passes without any optimization. Further many proposed cost functions help to compare the present and earlier approaches. The efficacy of the present RRR is demonstrated by its application to a simulated spring, mass, and damper system and a real airplane flight data having a larger number of unknown parameters and statistics.",signatures:"Mudambi R Ananthasayanam",downloadPdfUrl:"/chapter/pdf-download/58317",previewPdfUrl:"/chapter/pdf-preview/58317",authors:[{id:"209685",title:"Prof.",name:"Mudambi",surname:"Ananthasayanam",slug:"mudambi-ananthasayanam",fullName:"Mudambi Ananthasayanam"}],corrections:null},{id:"58052",title:"The Error Covariance Matrix Inflation in Ensemble Kalman Filter",doi:"10.5772/intechopen.71960",slug:"the-error-covariance-matrix-inflation-in-ensemble-kalman-filter",totalDownloads:1289,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:0,abstract:"The estimation accuracy of ensemble forecast errors is crucial to the assimilation results for all ensemble-based schemes. The ensemble Kalman filter (EnKF) is a widely used scheme in land surface data assimilation, without using the adjoint of a dynamical model. In EnKF, the forecast error covariance matrix is estimated as the sampling covariance matrix of the ensemble forecast states. However, past researches on EnKF have found that it can generally lead to an underestimate of the forecast error covariance matrix, due to the limited ensemble size, as well as the poor initial perturbations and model error. This can eventually result in filter divergence. Therefore, using inflation to further adjust the forecast error covariance matrix becomes increasingly important. In this chapter, a new structure of the forecast error covariance matrix is proposed to mitigate the problems with limited ensemble size and model error. An adaptive procedure equipped with a second-order least squares method is applied to estimate the inflation factors of forecast and observational error covariance matrices. The proposed method is tested on the well-known atmosphere-like Lorenz-96 model with spatially correlated observational systems. The experiment results show that the new structure of the forecast error covariance matrix and the adaptive estimation procedure lead to improvement of the analysis states.",signatures:"Guocan Wu and Xiaogu Zheng",downloadPdfUrl:"/chapter/pdf-download/58052",previewPdfUrl:"/chapter/pdf-preview/58052",authors:[{id:"210688",title:"Dr.",name:"Guocan",surname:"Wu",slug:"guocan-wu",fullName:"Guocan Wu"}],corrections:null},{id:"57977",title:"Unscented Kalman Filter for State and Parameter Estimation in Vehicle Dynamics",doi:"10.5772/intechopen.71900",slug:"unscented-kalman-filter-for-state-and-parameter-estimation-in-vehicle-dynamics",totalDownloads:1948,totalCrossrefCites:10,totalDimensionsCites:11,hasAltmetrics:0,abstract:"Automotive research and development passed through a vast evolution during past decades. Many passive and active driver assistance systems were developed, increasing the passengers’ safety and comfort. This ongoing process is a main focus in current research and offers great potential for further systems, especially focusing on the task of autonomous and cooperative driving in the future. For that reason, information about the current stability in terms of dynamic behavior and vehicle environment are necessary for the systems to perform properly. Thus, model-based online state and parameter estimation have become important throughout the last years using a detailed vehicle model and standard sensors, gathering this information. In this chapter, state and parameter estimation in vehicle dynamics utilizing the unscented Kalman filter is presented. The estimation runs in real time based on a detailed vehicle model and standard measurements taken within the car. The results are validated using a Volkswagen Golf GTE Plug-In Hybrid for various dynamic test maneuvers and a Genesys Automotive Dynamic Motion Analyzer (ADMA) measurement unit for high-precision measurements of the vehicle’s states. Online parameter estimation is shown for friction coefficient estimation performing maneuvers on different road surfaces.",signatures:"Mark Wielitzka, Alexander Busch, Matthias Dagen and Tobias\nOrtmaier",downloadPdfUrl:"/chapter/pdf-download/57977",previewPdfUrl:"/chapter/pdf-preview/57977",authors:[{id:"122290",title:"Dr.",name:"Tobias",surname:"Ortmaier",slug:"tobias-ortmaier",fullName:"Tobias Ortmaier"},{id:"201140",title:"M.Sc.",name:"Mark",surname:"Wielitzka",slug:"mark-wielitzka",fullName:"Mark Wielitzka"},{id:"202801",title:"M.Sc.",name:"Matthias",surname:"Dagen",slug:"matthias-dagen",fullName:"Matthias Dagen"},{id:"222868",title:"MSc.",name:"Alexander",surname:"Busch",slug:"alexander-busch",fullName:"Alexander Busch"}],corrections:null},{id:"58292",title:"Sensitivity-Based Adaptive SRUKF for State, Parameter, and Covariance Estimation on Mechatronic Systems",doi:"10.5772/intechopen.72470",slug:"sensitivity-based-adaptive-srukf-for-state-parameter-and-covariance-estimation-on-mechatronic-system",totalDownloads:1340,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Since the initial developments in the state-space theory in the 1950s and 1960s, the state estimation has become an extensively researched and applied discipline. All systems that can be modelled mathematically are candidates for state estimators. The state estimators reconstruct the states that represent internal conditions and status of a system at a specific instant of time using a mathematical model and the information received from the system sensors. Moreover, the estimator can be extended for system parameter estimation. The resulting Kalman filter (KF) derivatives for state and parameter estimation also require knowledge about the noise statistics of measurements and the uncertainties of the system model. These are often unknown, and an inaccurate parameterization may lead to decreased filter performance or even divergence. Additionally, insufficient system excitation can cause parameter estimation drifts. In this chapter, a sensitivity-based adaptive square-root unscented KF (SRUKF) is presented. This filter combines a SRUKF and the recursive prediction-error method to estimate system states, parameters and covariances online. Moreover, local sensitivity analysis is performed to prevent parameter estimation drifts, while the system is not sufficiently excited. The filter is evaluated on two testbeds based on an axis serial mechanism and compared with the joint state and parameter UKF.",signatures:"Mauro Hernán Riva, Mark Wielitzka and Tobias Ortmaier",downloadPdfUrl:"/chapter/pdf-download/58292",previewPdfUrl:"/chapter/pdf-preview/58292",authors:[{id:"122290",title:"Dr.",name:"Tobias",surname:"Ortmaier",slug:"tobias-ortmaier",fullName:"Tobias Ortmaier"},{id:"201140",title:"M.Sc.",name:"Mark",surname:"Wielitzka",slug:"mark-wielitzka",fullName:"Mark Wielitzka"},{id:"210832",title:"M.Sc.",name:"Mauro",surname:"Riva",slug:"mauro-riva",fullName:"Mauro Riva"}],corrections:null},{id:"57768",title:"Kalman Filters for Parameter Estimation of Nonstationary Signals",doi:"10.5772/intechopen.71874",slug:"kalman-filters-for-parameter-estimation-of-nonstationary-signals",totalDownloads:1543,totalCrossrefCites:2,totalDimensionsCites:3,hasAltmetrics:0,abstract:"An adaptive Taylor-Kalman filter with PSO tuning for tracking nonstationary signal parameters in a noisy environment with primary focus on time-varying power signals has been presented in this piece of work. In order to deal with the dynamic envelope of the power signal, second-order Taylor expansion has been used such that the Taylor coefficients are updated with the PSO-tuned Taylor-Kalman Filter algorithm. In addition to this, for fast convergence, a self-adaptive particle swarm optimization technique has been used for obtaining the optimal values of model and measurement error covariances of the Kalman filter. The proposed algorithm is linear and therefore has less computational burden, which is easier to be implemented on a hardware platform like DSP processor or FPGA. The proposed PSO-tuned Taylor-Kalman filter exhibits robust tracking capabilities even under changing signal dynamics, immune to critical noise conditions, harmonic contaminations, and also reveals excellent convergence properties.",signatures:"Sarita Nanda",downloadPdfUrl:"/chapter/pdf-download/57768",previewPdfUrl:"/chapter/pdf-preview/57768",authors:[{id:"209587",title:"Dr.",name:"Sarita",surname:"Nanda",slug:"sarita-nanda",fullName:"Sarita Nanda"}],corrections:null},{id:"57455",title:"Kalman Filter Models for the Prediction of Individualised Thermal Work Strain",doi:"10.5772/intechopen.71205",slug:"kalman-filter-models-for-the-prediction-of-individualised-thermal-work-strain",totalDownloads:1204,totalCrossrefCites:0,totalDimensionsCites:3,hasAltmetrics:0,abstract:"It is important to monitor and assess the physiological strain of individuals working in hot environments to avoid heat illness and performance degradation. The body core temperature (Tc) is a reliable indicator of thermal work strain. However, measuring Tc is invasive and often inconvenient and impractical for real-time monitoring of workers in high heat strain environments. Seeking a better solution, the main aim of the present study was to investigate the Kalman filter method to enable the estimation of heat strain from non-invasive measurements (heart rate (HR) and chest skin temperature (ST)) obtained ‘online’ via wearable body sensors. In particular, we developed two Kalman filter models. First, an extended Kalman filter (EFK) was implemented in a cubic state space modelling framework (HR versus Tc) with a stage-wise, autoregressive exogenous model (incorporating HR and ST) as the time update model. Under the second model, the online Kalman filter (OFK) approach builds up the time update equation depending only on the initial value of Tc and the latest value of the exogenous variables. Both models were trained and validated using data from laboratory- and outfield-based heat strain profiling studies in which subjects performed a high intensity military foot march. While both the EKF and OKF models provided satisfactory estimates of Tc, the results showed an overall superior performance of the OKF model (overall root mean square error, RMSE = 0.31°C) compared to the EKF model (RMSE = 0.45°C).",signatures:"Jia Guo, Ying Chen, Weiping Priscilla Fan, Si Hui Maureen Lee,\nJunxian Ong, Poh Ling Tan, Yu Li Lydia Law, Kai Wei Jason Lee and\nKok-Yong Seng",downloadPdfUrl:"/chapter/pdf-download/57455",previewPdfUrl:"/chapter/pdf-preview/57455",authors:[{id:"171298",title:"Dr.",name:"Kok-Yong",surname:"Seng",slug:"kok-yong-seng",fullName:"Kok-Yong Seng"},{id:"209402",title:"Dr.",name:"Ying",surname:"Chen",slug:"ying-chen",fullName:"Ying Chen"},{id:"209404",title:"Dr.",name:"Jia",surname:"Guo",slug:"jia-guo",fullName:"Jia Guo"},{id:"220688",title:"Ms.",name:"Weiping Priscilla",surname:"Fan",slug:"weiping-priscilla-fan",fullName:"Weiping Priscilla Fan"},{id:"220689",title:"Ms.",name:"Si Hui Maureen",surname:"Lee",slug:"si-hui-maureen-lee",fullName:"Si Hui Maureen Lee"},{id:"220690",title:"Mr.",name:"Junxian",surname:"Ong",slug:"junxian-ong",fullName:"Junxian Ong"},{id:"220691",title:"Ms.",name:"Poh Ling",surname:"Tan",slug:"poh-ling-tan",fullName:"Poh Ling Tan"},{id:"220692",title:"Ms.",name:"Yu Li Lydia",surname:"Law",slug:"yu-li-lydia-law",fullName:"Yu Li Lydia Law"},{id:"220693",title:"Dr.",name:"Kai Wei Jason",surname:"Lee",slug:"kai-wei-jason-lee",fullName:"Kai Wei Jason Lee"}],corrections:null},{id:"57512",title:"Application of Kalman Filtering in Dynamic Prediction for Corporate Financial Distress",doi:"10.5772/intechopen.71616",slug:"application-of-kalman-filtering-in-dynamic-prediction-for-corporate-financial-distress",totalDownloads:1388,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"This chapter aims to dynamically improve the method of predicting financial distress based on Kalman filtering. Financial distress prediction (FDP) is an important study area of corporate finance. The widely used discriminant models currently for financial distress prediction have deficiencies in dynamics. Based on the state-space method, we establish two models that are used to describe the dynamic process and discriminant rules of financial distress, respectively, that is, a process model and a discriminant model. These two models collectively are called dynamic prediction models for financial distress. The operation of the dynamic prediction is achieved by Kalman filtering algorithm, and further, a general n-step-ahead prediction algorithm based on Kalman filtering is derived for prospective prediction. We also conduct an empirical study for China’s manufacturing industry, and the results have proved the accuracy and advance of predicting financial distress in such case.",signatures:"Qian Zhuang",downloadPdfUrl:"/chapter/pdf-download/57512",previewPdfUrl:"/chapter/pdf-preview/57512",authors:[{id:"209794",title:"Dr.",name:"Qian",surname:"Zhuang",slug:"qian-zhuang",fullName:"Qian Zhuang"}],corrections:null},{id:"57651",title:"Predicting Collisions in Mobile Robot Navigation by Kalman Filter",doi:"10.5772/intechopen.71653",slug:"predicting-collisions-in-mobile-robot-navigation-by-kalman-filter",totalDownloads:1116,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The growing trend of the use of robots in many areas of daily life makes it necessary to search for approaches to improve efficiency in tasks performed by robots. For that reason, we show, in this chapter, the application of the Kalman filter applied to the navigation of mobile robots, specifically the Time-to-contact (TTC) problem. We present a summary of approaches that have been taken to address the TTC problem. We use a monocular vision-based approach to detect potential obstacles and follow them over time through their apparent size change. Our approach collects information about obstacle data and models the behavior while the robot is approaching the obstacle, in order to predict collisions. We highlight some characteristics of the Kalman filter applied to our problem. Finally, we show of our results applied to sequences composed of 210 frames in different real scenarios. The results show a fast convergence of the model to the data and good fit even with noisy measures.",signatures:"Angel Sánchez, Homero Ríos, Gustavo Quintana and Antonio Marín",downloadPdfUrl:"/chapter/pdf-download/57651",previewPdfUrl:"/chapter/pdf-preview/57651",authors:[{id:"210685",title:"MSc.",name:"Angel",surname:"Sanchez Garcia",slug:"angel-sanchez-garcia",fullName:"Angel Sanchez Garcia"},{id:"211071",title:"Dr.",name:"Homero",surname:"Rios Figueroa",slug:"homero-rios-figueroa",fullName:"Homero Rios Figueroa"},{id:"211072",title:"Dr.",name:"Antonio",surname:"Marin Hernandez",slug:"antonio-marin-hernandez",fullName:"Antonio Marin Hernandez"},{id:"219509",title:"Dr.",name:"Gustavo",surname:"Quintana Carapia",slug:"gustavo-quintana-carapia",fullName:"Gustavo Quintana Carapia"}],corrections:null},{id:"59091",title:"Efficient Matrix-Free Ensemble Kalman Filter Implementations: Accounting for Localization",doi:"10.5772/intechopen.72465",slug:"efficient-matrix-free-ensemble-kalman-filter-implementations-accounting-for-localization",totalDownloads:1111,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"This chapter discusses efficient and practical matrix-free implementations of the ensemble Kalman filter (EnKF) in order to account for localization during the assimilation of observations. In the EnKF context, an ensemble of model realizations is utilized in order to estimate the moments of its underlying error distribution. Since ensemble members come at high computational costs (owing to current operational model resolutions) ensemble sizes are constrained by the hundreds while, typically, their error distributions range in the order of millions. This induces spurious correlations in estimates of prior error correlations when these are approximated via the ensemble covariance matrix. Localization methods are commonly utilized in order to counteract this effect. EnKF implementations in this context are based on a modified Cholesky decomposition. Different flavours of Cholesky-based filters are discussed in this chapter. Furthermore, the computational effort in all formulations is linear with regard to model resolutions. Experimental tests are performed making use of the Lorenz 96 model. The results reveal that, in terms of root-mean-square-errors, all formulations perform equivalently.",signatures:"Elias David Niño Ruiz, Rolando Beltrán Arrieta and Alfonso Manuel\nMancilla Herrera",downloadPdfUrl:"/chapter/pdf-download/59091",previewPdfUrl:"/chapter/pdf-preview/59091",authors:[{id:"107082",title:"Prof.",name:"Elias",surname:"Nino-Ruiz",slug:"elias-nino-ruiz",fullName:"Elias Nino-Ruiz"}],corrections:null},{id:"58238",title:"Kalman Filters for Reference Current Generation in Shunt Active Power Filter (APF)",doi:"10.5772/intechopen.72467",slug:"kalman-filters-for-reference-current-generation-in-shunt-active-power-filter-apf-",totalDownloads:1654,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Shunt active power filter (APF) method have been used by many researchers as a solution in reducing the harmonics creating by the non-liner loads. Therefore, this research is targeted to design and implement a three-phase shunt APF employing Kalman filter estimator. Conventionally, low-pass filter (LPF) is used to filter out the unwanted DC component of the non-linear load to produce the sinusoidal waveform called the reference current. However, when applying LPF it contributes with the phase shift and high transient at the supply current. Therefore, to reduce these problems, the digital Kalman filter estimator is used to replace the LPF for generating the reference current. Details on the investigation between conventional and proposed methods under simulation based on Matlab Simulink platform and experimental that are made for two types of load, namely, three-phase rectifier with RC-load and three-phase induction motor, are presented. The performance criteria of the shunt APF are determined by the supply current waveform, total harmonic distortion (THD), harmonic spectrum and power quality measurements, which were also obtained by simulation and experimental. In conclusion, by employing Kalman filter estimator for generating the reference current, it reduces the time delay and high transient current at the power supply and, thus, improved the overall THD from 0.1 to 0.42% compared to the LPF.",signatures:"Ahmad Shukri Bin Abu Hasim, Syed Mohd Fairuz Bin Syed Mohd\nDardin and Zulkifilie Bin Ibrahim",downloadPdfUrl:"/chapter/pdf-download/58238",previewPdfUrl:"/chapter/pdf-preview/58238",authors:[{id:"208972",title:"Dr.",name:"Syed Mohd Fairuz",surname:"Syed Mohd Dardin",slug:"syed-mohd-fairuz-syed-mohd-dardin",fullName:"Syed Mohd Fairuz Syed Mohd Dardin"},{id:"209475",title:"Dr.",name:"Ahmad Shukri",surname:"Abu Hasim",slug:"ahmad-shukri-abu-hasim",fullName:"Ahmad Shukri Abu Hasim"},{id:"218276",title:"Prof.",name:"Zulkifilie",surname:"Ibrahim",slug:"zulkifilie-ibrahim",fullName:"Zulkifilie Ibrahim"}],corrections:null},{id:"57692",title:"Applications of Kalman Filters for Coherent Optical Communication Systems",doi:"10.5772/intechopen.71617",slug:"applications-of-kalman-filters-for-coherent-optical-communication-systems",totalDownloads:1477,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In this chapter, we review various applications of Kalman filtering for coherent optical communication systems. First, we briefly discuss the principles of Kalman filter and its variations including extended Kalman filter (EKF) and adaptive Kalman filter (AKF). Later on, we illustrate the applicability of Kalman filters for joint tracking of several optical transmission impairments, simultaneously, by formulating the state space model (SSM) and detailing the principles. A detailed methodology is presented for the joint tracking of linear and nonlinear phase noise along with amplitude noise using EKF. Also, approaches to enhance the performance obtained by EKF by combining with other existing digital signal processing (DSP) techniques are presented. Frequency and phase offset estimation using a two stage linear Kalman filter (LKF)/EKF is also discussed. A cascaded structure of LKF and EKF by splitting the SSM to jointly mitigate the effects of polarization, phase and amplitude noise is also presented. The numerical analysis concludes that the Kalman filter based approaches outperform the conventional methods with better tracking capability and faster convergence besides offering more feasibility for real-time implementations.",signatures:"Lalitha Pakala and Bernhard Schmauss",downloadPdfUrl:"/chapter/pdf-download/57692",previewPdfUrl:"/chapter/pdf-preview/57692",authors:[{id:"210340",title:"M.Sc.",name:"Lalitha",surname:"Pakala",slug:"lalitha-pakala",fullName:"Lalitha Pakala"},{id:"210654",title:"Prof.",name:"Bernhard",surname:"Schmauss",slug:"bernhard-schmauss",fullName:"Bernhard Schmauss"}],corrections:null},{id:"57673",title:"Kalman Filter for Moving Object Tracking: Performance Analysis and Filter Design",doi:"10.5772/intechopen.71731",slug:"kalman-filter-for-moving-object-tracking-performance-analysis-and-filter-design",totalDownloads:3144,totalCrossrefCites:12,totalDimensionsCites:19,hasAltmetrics:0,abstract:"This chapter presents Kalman filters for tracking moving objects and their efficient design strategy based on steady-state performance analysis. First, a dynamic/measurement model is defined for the tracking systems, assuming both position-only and position-velocity measurements. Then, problems with the Kalman filter design in tracking systems are summarized, and an efficient steady-state performance index proposed by the author [termed the root-mean-squared error index (the RMS index)] is introduced to resolve these concerns. The analytical relationship between the proposed RMS index and the covariance matrix of the process noise is shown, leading to a proposed design strategy that is based on this relationship. Theoretical performance analysis is conducted using the performance indices to show the optimality of the design strategy. Numerical simulations show the validity of the theoretical analyses and effectiveness of the proposed strategy in realistic situations. In addition, the optimal performance of the position-only-measured and position-velocity-measured systems is analyzed and compared. This comparison shows that the position-velocity-measured Kalman filter tracking is accurate when compared with the position-only-measured filter.",signatures:"Kenshi Saho",downloadPdfUrl:"/chapter/pdf-download/57673",previewPdfUrl:"/chapter/pdf-preview/57673",authors:[{id:"209334",title:"Associate Prof.",name:"Kenshi",surname:"Saho",slug:"kenshi-saho",fullName:"Kenshi Saho"}],corrections:null},{id:"57985",title:"Distributed Kalman Filter",doi:"10.5772/intechopen.71941",slug:"distributed-kalman-filter",totalDownloads:1337,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:0,abstract:"The continuing trend toward connected sensors (“internet of things” and” ubiquitous computing”) drives a demand for powerful distributed estimation methodologies. In tracking applications, the distributed Kalman filter (DKF) provides an optimal solution under Kalman filter conditions. The optimal solution in terms of the estimation accuracy is also achieved by a centralized fusion algorithm, which receives all associated measurements. However, the centralized approach requires full communication of all measurements at each time step, whereas the DKF works at arbitrary communication rates since the calculation is fully distributed. A more recent methodology is based on ”accumulated state density” (ASD), which augments the states from multiple time instants to overcome spatial cross-correlations. This chapter explains the challenges in distributed tracking. Then, possible solutions are derived, which include the DKF and ASD approach.",signatures:"Felix Govaers",downloadPdfUrl:"/chapter/pdf-download/57985",previewPdfUrl:"/chapter/pdf-preview/57985",authors:[{id:"209490",title:"Dr.",name:"Felix",surname:"Govaers",slug:"felix-govaers",fullName:"Felix Govaers"}],corrections:null},{id:"57804",title:"Consensus-Based Distributed Filtering for GNSS",doi:"10.5772/intechopen.71138",slug:"consensus-based-distributed-filtering-for-gnss",totalDownloads:1371,totalCrossrefCites:4,totalDimensionsCites:5,hasAltmetrics:0,abstract:"Kalman filtering in its distributed information form is reviewed and applied to a network of receivers tracking Global Navigation Satellite Systems (GNSS). We show, by employing consensus-based data-fusion rules between GNSS receivers, how the consensus-based Kalman filter (CKF) of individual receivers can deliver GNSS parameter solutions that have a comparable precision performance as their network-derived, fusion center dependent counterparts. This is relevant as in the near future the proliferation of low-cost receivers will give rise to a significant increase in the number of GNSS users. With the CKF or other distributed filtering techniques, GNSS users can therefore achieve high-precision solutions without the need of relying on a centralized computing center.",signatures:"Amir Khodabandeh, Peter J.G. Teunissen and Safoora Zaminpardaz",downloadPdfUrl:"/chapter/pdf-download/57804",previewPdfUrl:"/chapter/pdf-preview/57804",authors:[{id:"116970",title:"Prof.",name:"Peter",surname:"Teunissen",slug:"peter-teunissen",fullName:"Peter Teunissen"},{id:"210691",title:"Dr.",name:"Amir",surname:"Khodabandeh",slug:"amir-khodabandeh",fullName:"Amir Khodabandeh"},{id:"210714",title:"Dr.",name:"Safoora",surname:"Zaminpardaz",slug:"safoora-zaminpardaz",fullName:"Safoora Zaminpardaz"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"2286",title:"Frontiers in Advanced Control Systems",subtitle:null,isOpenForSubmission:!1,hash:"43dae6480e55f2985ce8c4a1860e6dca",slug:"frontiers-in-advanced-control-systems",bookSignature:"Ginalber Luiz de Oliveira Serra",coverURL:"https://cdn.intechopen.com/books/images_new/2286.jpg",editedByType:"Edited by",editors:[{id:"11032",title:"Dr.",name:"Ginalber Luiz",surname:"Serra",slug:"ginalber-luiz-serra",fullName:"Ginalber Luiz Serra"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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In this sense, the chapters that make up this book should propose transdisciplinarity as an educational paradigm, to bring students closer to the social reality of which they are a part and to its problematic complexity in an integrated manner.
\r\n\r\n\tThis book will represent one of the first educational contributions to the need to consolidate an emerging research line aimed at learning by and for education for a critical, responsible, and committed citizenship with its social environment, and the acquisition of skills for democratic culture.
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Rapid growth of the global population, permanently increasing life standards, and vast technological advancement are continually increasing the variety and amount of solid waste.
\nGeneration of municipal solid waste, together with the high organic share present in solid waste and its often incorrect discarding, results in extensive ecological pollution, mainly based on the emission of gases that contribute to the greenhouse effect, such as methane (CH4) and carbon dioxide (CO2). Because of this environmental threat, municipal authorities are currently urged to implement techno-economic and political solutions of higher efficiency to manage the growing quantities of municipal solid waste [1].
\nThe lion’s share of municipal (mainly urban) solid waste consists of biodegradable matter, which plays a substantial role in greenhouse gas emissions in today’s cities all around the globe. According to the present state of knowledge, integrated solid waste management is the strategy of choice to manage this issue; such strategies, however, require improvement in order to handle the growing organic fractions of municipal solid discards. If accomplished in a smart manner, this can on the one hand contribute to the aspired reduction of greenhouse gas emissions, and, on the other hand, even potentially generate economic benefits. Hence, systems for sustainable management of municipal solid waste are auspicious and attractive objects of study to assess current consumption behavior in different global regions and to protect the natural environment.
\nGenerally, municipal solid waste gets disposed of in dumps and landfills as the most simple, convenient, inexpensive, and technologically less advanced method. Organic fractions as the major component of municipal solid waste undergo biodegradation under the anaerobic conditions prevailing in landfills, which consequently releases greenhouse gases as mentioned above [2].
\nReduction or complete abolition of environmental contamination becomes increasingly important, which intensifies the global efforts dedicated to develop novel strategies for gradually reducing the quantities of the biodegradable municipal solid wastes in landfills. The process toward reduction of organic pollution involves (i) source separated collection of organic fraction of municipal solid waste, which undergo compost production, (ii) organic waste incineration for energy production, and (iii) mechanical/biological processing to get a compostable material [3].
\nThis introduction chapter makes the reader familiar with the principles of municipal solid waste management, encompassing landfilling and recycling technologies; moreover, the composition of different types of municipal solid waste will be introduced. Based on this, the most feasible, promising, and realistic scenarios for municipal solid waste management are presented in order to provide a solid scientific background of these processes implemented or in development, and the factors needed to assess the sustainability of these processes in a critical and straightforward fashion by using innovative sustainable assessment tools [4].
\n“Municipal solid waste” is commonly understood as the waste accruing in a municipality. Most of this solid waste is generated without any segregation, and, therefore, it may be either harmful or harmless. In general, independent on the origin of municipal solid waste, its impact on the environment and different life forms affects pollution of air, water, and soil. Moreover, impact of municipal solid waste on land use, odors, and esthetic aspects has also accounted for holistic considerations of waste treatment systems.
\nIn principle, the human species is on top of any environmental pollution and consequently constitutes the major factor endangering nature’s biodiversity. Global population growth and increasing consumer demands, especially in strongly growing, emerging, and developing economies, have resulted in a large production increase worldwide. However, most industrial facilities have insufficient or completely lacking monitoring of their production processes in environmental terms, and often insufficient or inadequate facilities for management and treatment of waste. The global trend of rapid urban growth has further caused an increase of waste generation from private habitation sites and private and public service facilities; in addition, intensified construction and demolition activities are ongoing. As urban population density is generally very high all over the world, the daily consumption of goods and services is also high in urban areas. Additionally, the amounts of accruing municipal solid waste are also directly correlating with the economic status of the society in a given country [5].
\nMunicipal solid waste generation
Because of diverse shortcomings such as the lack of waste segregation already at the origin, insufficient treatment, scarce reuse, lacking recycling systems, and often inappropriate disposal, solid waste management still has various gaps in the management chain which need to be filled. Treatment of the organic waste fraction for energy and resource recovery changes its physical and chemical characteristics. In this context, the most important processing techniques encompass composting (aerobic treatment) or bio-methanogenesis (anaerobic treatment in biogas reactors). Composting through aerobic processing produces compost as a stable product, which is broadly utilized as manure and as soil fertilizer and soil conditioner.
\nDue to various reasons, composting facilities are used to a lower extent in large metropolitan cities. Prevalence of unsegregated waste and production of low-quality compost resulting in low end user acceptance are the two most important reasons for this underutilization. Bio-methanogenesis via microbiological activity under anaerobic conditions generates biogas rich in methane as the value component. In general, composting becomes feasible when a given waste contains high moisture and high organic content. Uncontrolled and arbitrary disposal of mixed waste including organic fractions that cause environmental problems such as land pollution and pollution of soil and aquatic environments due to leaching of waste components [7].
\nAn exemplary study assessing a new industrial process for mechanical-biological treatment of municipal solid waste reports that municipal solid waste received for treatment on the plant typically consists of, based on the dry mass, 9% of rejectable waste, 21% of fines (<20 mm) (mainly rejectables), 23% of paper and cardboard, and 15% of diverse plastic materials originating from petrochemistry. Such high content in plastics, paper, and cardboard is typical for the local situation (suburb of Mende, Lozère, France), where municipal solid waste is collected based only on a source separation of glass and complex residual waste, without separately collecting plastic, paper, and cardboards [8].
\nA classification of solid waste sources can be accomplished based on the following assumptions:
All solid waste produced within a municipality’s territory, independent on its physical and chemical nature and source of generation, is classified as “municipal solid waste” (Figure 1).
All economic activities create a given solid waste pattern.
Due to the fact that economic and consumers’ activities cause generation of solid waste, all these activities are considered sources of solid waste [9].
A hypothetical urban municipality and the geographic areas (1. Urban, 2. Industrial, 3. Rural) where solid waste is generated [
Private households, hotels, offices, stores, educational, and other institutions are causes of municipal solid waste generation. The lion’s share of solid waste encompasses organic (mainly food or horticulture) waste, cardboard, paper, plastics and other resins, textile rags, metal, and glass; in many cases, even demolition and construction debris is included in collected waste, in addition to certain quantities of precarious waste, such as batteries, electric light bulbs and fluorescent tubes, automotive parts, expired medicines and other pharmaceutical products, and diverse chemicals, e.g., cleaning and cosmetic products [10]. Hence, the main sources of solid waste are private households and the agricultural, industrial, construction, commercial, and institutional sectors. An assignment of different types of solid waste to their individual sources is shown in Table 1.
\nSource | \nTypical waste generators | \nTypes of solid wastes | \n
---|---|---|
Residential (private sector) | \nSingle and multifamily habitations | \nPaper, cardboard, food wastes, plastics, textile rags, leather, yard waste, glass, lignocelluloses (wood, grass, and lopping), metals, ashes (heating and tobacco products), special wastes (e.g., bulky items, white goods, electronic parts, batteries, car tires, waste oils), and diverse types of precarious household waste | \n
Industrial sector | \nLight and heavy manufacturing companies, fabrication, power and chemical plants, construction sites | \nHousekeeping waste, different packaging materials, food waste, construction and demolition materials, ashes, hazardous waste, and special waste | \n
Commercial sector | \nStores, markets, gastronomy, hotels, office buildings, etc. | \nPaper, cardboard, plastics, wood, food wastes, glass, metals, special wastes, and hazardous waste | \n
Institutional sector | \nSchools, universities, kindergartens, hospitals and other health and medical institutions, penitentiaries, government centers | \nSame as for the commercial sector | \n
Construction and demolition sector | \nNew construction sites, renovation sites, road rehabilitation, demolition of buildings | \nWood, steel, asphalt, cement, insulation materials, dirt, dust, etc. | \n
Municipal services | \nStreet cleaning, parks, landscaping, beaches, groves, playgrounds, sport facilities, other recreational areas, and wastewater treatment plants | \nStreet sweepings, landscape, tree- and bush trimmings, different waste accruing in parks, beaches, riversides, and other recreational area, sludge after flooding events | \n
Processing sector | \nHeavy and light manufacturing, chemical plants, (bio)refineries, power plants, mineral extraction and processing, joinery, and veneer works | \nIndustrial process waste, saw dust, scrap materials, off specification products, slag, and tailings | \n
All of the above should be included as “municipal solid waste” | \n||
Agro-industrial sector | \nFarms, crops, orchards, vineyards, dairies, feedlots, distilleries, rendering and animal processing industry, biodiesel industry, and bioethanol production | \nAgricultural wastes, spoiled food wastes, animal residues (slaughterhouse waste), hazardous wastes (e.g., pesticides, antibiotic residues), and crude glycerol | \n
Sources and types of solid wastes [10].
In parallel to the increase of population and economic activity, solid waste management is turning into a severe issue for almost all municipalities. Public health, odor disturbance, hazardous gas emissions, air pollution, or particulate matter formation are typical phenomena prevailing in urban regions. For smart management, municipal solid waste disposal requires proper environmental monitoring during the entire waste treatment chain from waste collection to its ultimate disposal, and, finally, a regular control of disposal sites is needed [11].
\nTo manage solid waste in an efficient fashion, the interrelationships of four functional elements have to be taken into account before a decision about an ultimate disposal strategy can be made. As reported by Shah [12], the first function element refers to the material generated at the source. Materials to which no more value is added are referred to and disposed as waste; quantity and nature of different types of waste are dependent on the waste source. The second function element encompassed the handling, separation, and storage at site of waste. In this context, waste has to be subjected toward separation before being placed into suitable storage containers. Paper, cardboard, packaging plastics, glass, ferrous metals, aluminum cans, and organic waste are those components, which typically are separated and stored individually. This step is crucial before moving to the next point. During the collection process, solid waste is picked up and placed into empty containers, which have separate compartments for recyclable materials [13]. Subsequently, the refuse collection staff collects the waste around the disposal centers manually before disposing it at the disposal sites. Figure 2 illustrates the individual steps involved from waste material generation at its source until the final functional element for ultimate waste disposal.
\nSchematic of solid waste management system [
A policy for proper waste management needs to be grounded on the principles of sustainable development, which considers the society’s refuse not only as rejects but also as a potential resource, which can undergo upgrading for potential value creation. In urban regions, appropriate solid waste management facilities are essential for, on the one hand, environmental management and protection and, on the other hand, for public health. Strategies and techniques for solving waste problems on a regional scale inevitably have a large number of possible solutions in order to be implemented in different areas, which are characterized by variable population densities, different life standard and life style, number of locations for waste management infrastructure, and number and types of protected landscape areas and other high value ecological sites. Environmentally benign waste management depends on various site-specific factors such as the composition of the waste, efficacy of waste collection at its source and of processing systems required to carry out different waste management techniques, feasibility of value-added material recovery from waste streams, emission standards to which waste management facilities are designed and operated, overall cost efficiency, and social performance of the community [7]. Due to this high complexity, municipal solid waste management has attracted a great deal of attention especially in countries with highly dynamic economic development such as India, a country that produces an estimated quantity of 50–600 million tons of municipal solid waste per year [7].
\nLife cycle assessment (LCA) is a process analytical tool recommended in many EU documents, e.g., the Directive 2008/98/EC on waste and certain other directives. LCA as a tool supports or enables the holistic consideration of the environmental impact of a new product or process already in its infancy, hence, during development [14]. As a quantitative measure, the Sustainable Process Index (SPI) allows to compare in a straightforward way the ecological footprint of products, processes, and systems based on the area required for completely embedding a process/system into the ecosphere [15]. Hence, LCA is a well-established tool, which nowadays is widely used to assess the environmental impact of product life cycles (“cradle-to-gate” or “cradle-to-grave”; the first refers only to production until the product leaving the factory’s gate, while latter involves also the waste disposal after a product’s life span), new technological processes, as well as waste management systems including waste treatment and processes for disposal, recycling, composting, or waste conversion for energy generation (biogas, thermal conversion in cogeneration plants). The evaluation of the existing situation of municipal solid waste management from an environmental, economic, and social perspective via a life cycle approach is an important first step prior to taking any decisions on the technologies to be selected, the policies to be developed, and the strategies to be followed for a nation [16].
\nThe considerable number of reported LCA computer models dedicated to municipal solid waste management, often resorting to the SPI quantification tool, emphasizes the applicability of LCA in issues related to municipal solid waste management systems. Typically, these models have been developed independently from each other and are often based on features and assumptions that are highly specific to the period, economic framework, and geographical conditions in which they were developed. This clearly emphasizes that the assessment of feasibility of a given solid waste management systems needs to be in accordance to the individually prevailing conditions in a specific city or region.
\nCardiac electrophysiology study (EPS) is helpful to assess the heart’s electrical system. This is an invasive percutaneous cardiac procedure used for the investigation and treatment of certain arrhythmias. During the examination, catheters are inserted to the appropriate position within the heart mainly via large veins to record the electrical signals of the heart and to pace from different localized areas. In this way, EPS can help evaluating the function of the conduction system, determining the mechanisms of brady- and tachyarrhythmias, and identifying areas which may be the targets of often curative catheter ablation. Many cardiac arrhythmias that previously required the use of potentially harmful antiarrhythmic drugs can now be routinely cured in the electrophysiology laboratory by means of transcatheter ablation techniques.
In this chapter, the basics of cardiac electrophysiological studies are presented.
Equipment necessary for EPS includes an operation table, fluoroscopy unit, recorders, programmable stimulator, a multichannel lead switching box, an oscilloscope, and emergency instruments. In addition, tools for vascular access and electrode catheters are also required [1]. A standard schematic set-up for typical EPS is shown in Figure 1.
Standard schematic set-up for typical electrophysiology study. Abbreviation: RF—radiofrequency.
Electrical signals from humans obtained by surface or intracardiac electrodes are <10 mV in amplitude. These electrocardiograms must be amplified and filtered before digitalization, displaying, and storage for interpretation and analysis [2]. Amplification means the increase of the signal’s amplitude. However, the signals are plagued with electrical noise, thus amplification results in increasing not only the original signals but the amplitude of noise also. For this reason, avoidance of extraneous signals is essential: all electrical tools used in EPS should be appropriately earthed and shielded. In addition, filtering is required to eliminate unnecessary components of the electrical signals. High-pass filters remove components below a given frequency, while low-pass filters eliminate high-frequency components of the electrical signal. Electrophysiological signals are often contaminated with power line noise (i.e., 60 Hz in North America and 50 Hz in Europe), thus notch filtering is often used to eliminate it [3].
Standard ECG devices run at 25 mm/s Increasing the paper output speed, subtle ECG findings hidden in the tracings become more evident. During an EPS, surface ECG leads and intracardiac electrocardiograms (IEGM) are generally displayed and interpreted at a sweep speed of 100 or 200 mm/s (Figure 2).
Same normal sinus beat at a paper speed of 25, 50, 100, and 200 mm/s.
For a standard EPS, a standard number of four catheters is necessary. Based on the operator’s decision, EPS is also feasible using only three diagnostic catheters. Diagnostic catheters have two or multiple electrodes, and for each pair of consecutive electrodes, a distinct intracardiac electrogram gets recorded. Traditionally, catheter placement is carried out under fluoroscopy guidance. In the EP lab, three main fluoroscopy projections are used: anteroposterior (AP), left anterior oblique (LAO), and right anterior oblique (RAO) views (Figure 3).
Standard catheter positions in left anterior oblique (LAO), anteroposterior (AP), and right anterior oblique (RAO) projections. Abbreviations: CS—coronary sinus decapolar catheter; HRA—high right atrium; RVa—right ventricle apex.
A diagnostic catheter is positioned from the femoral vein and contacted with the lateral wall of the right atrium at right atrium—superior vena cava junction.
The coronary sinus runs transversely in the left atrioventricular groove on the posterior side of the heart. A multielectrode catheter is inserted into the coronary sinus from femoral, jugular internal, or subclavian vein. For femoral approach, steerable catheters are used. CS catheter allows to record IEGMs coming from the left atrium and ventricle. Moreover, this position is easily reproducible and serves as a reference point during the EPS. Thus, CS catheters play an important role in EP labs.
For recording His bundle electrogram, a catheter is inserted via femoral vein to the high septal part of the right ventricle and pulled back slowly with clockwise torquing till characteristic His bundle electrogram appears.
A diagnostic catheter is advanced from femoral vein to apical right ventricle, which allows to record local ventricular IEGMs.
Generally, IEGMs mean the electrical activity between two electrodes at the tip of the catheter (bipolar recording) [4]. The main difference between surface ECG and IEGMs is that the surface ECG records a summation of the electrical activity of the heart, while in contrast, IEGMs show only the electrical activity of a localized area, i.e., IEGMs are local intracardiac electrograms. Importantly, these are displayed together on the monitor system facilitating accurate interpretations of the electrical signals (Figure 4).
Snapshot from an electrophysiology study. The upper four channels represent lead I, II, V1, and V6 of surface ECG. The paper speed is 200 mm/s. on the distal His (His d) channel, we can recognize three different wavefront characteristics of the His bundle: the first one is the A (atrial) wave (synchronous to P wave on surface ECG), the last is called V (ventricular) wave (synchronous to QRS complex on the surface ECG). In the middle, a sharp signal represents His bundle electrogram. AH interval could be measured from the beginning of A to the sharp His signal. HV interval is measured on the His bundle electrogram from the beginning of the His deflection to the earliest identified ventricular activity on the surface ECG. CS electrograms show atrial activation (synchronous to P wave on surface ECG again). Note that first activation occurs on CS 9,10 which is the proximal pair of electrodes. CS 9,10 is at the ostium of the coronary sinus, thus these electrodes are the closest to the sinus node. In the case of a correctly positioned CS catheter, CS 9,10 should be activated first during normal sinus rhythm. Finally, a local ventricular electrogram can be easily identified on the catheter at RVa position. Asterix represents PA interval.
After catheter placement, a routine EPS starts with the measurement of basic intervals [4]. Ideally basic intervals should be measured during sinus rhythm.
The PA interval represents the interval between the earliest atrial activation (recording in any channel) in the region of the sinus node and at the region of the atrioventricular node. Usually, the earliest atrial activation is represented by the P wave onset on the surface ECG. Normal value is 25–55 milliseconds (ms).
AH interval represents the conduction time from the low-right atrium at the interatrial septum through the atrioventricular (AV) node to the His bundle. It is measured between the atrial electrogram recorded by the His bundle catheter and the beginning of the His electrogram itself. The normal range is 55–150 ms [4]. The AH interval is sensitive to autonomic tone. A prolonged AH interval may indicate AV nodal disease or high vagal tone, whereas a shorter than normal AH can occur during sympathetic activation.
HV interval reflects conduction through the His-Purkinje system and is measured on the His bundle electrogram from the beginning of the His deflection to the earliest identified ventricular activity on the surface ECG. An HV interval of 35–55 ms is considered normal. In the presence of anterograde conducting accessory pathway, the HV interval may be shorter. Prolonged HV interval represents infrahisian conduction disturbances.
Time measurements are reported in milliseconds in the case of EP procedures. To characterize the heart rate, the cycle length (CL) is used instead of the frequency. CL represents the length of time between each atrial or ventricular beats. For example, a tachycardia with a heart rate of 150 beats per minute has a CL of 400 ms (Figure 5). The faster the heart rate the shorter the CL.
Atrial pacing at a cycle length of 400 ms, which means a rate of 150 beats per minute. Sharp pacing artifacts are present before P waves. P waves are negative in the inferior leads (pacing from coronary sinus ostium). Paper speed is 100 mm/s.
Besides IEGM recordings, electrode catheters previously inserted in the heart are also used for pacing. An external stimulator is connected to the catheters. When pacing starts, electrical current is passed by catheters resulting in cardiac cells’ depolarization near the catheter’s electrode. The depolarization of these cells generates an electrical wavefront, spreading over the heart as the impulse originating from the sinus node. As a result, stimulator pacing generates cardiac impulse artificially. Carefully positioned catheters can impulse the heart from almost any position. During the EPS, pacing is used to introduce electrical impulses in predetermined patterns and at precise time intervals. Such pacing is called programmed stimulation [1]. Programmed stimulation consists of the main type of pacing technique: burst and extrastimulus pacing.
Burst pacing consists of implementing a series of electrical impulses (so-called drive train) at a fixed cycle length. By definition, each impulse is called S1 and the difference between the impulses is the same (Figure 6).
Ventricular burst pacing from RVa position. Note the pacing artifact on RVa channel and before the QRS complexes. Pacing cycle length is fixed (500 ms). Paper speed is 50 mm/s.
Extrastimulus testing means introduction of a drive train (usually 8 beats, S1) followed by one or more extrastimuli with shorter coupling interval than the cycle length of the drive. S2 means the first programmed extrastimulus, S3 is used for the second, and so on (Figure 7).
Atrial extrastimulus testing from coronary sinus catheter (CS). The drive train consists of 8 beats at a cycle length of 400 ms is followed by an extrastimulus with a shorter coupling interval (300 ms). Ablation catheter (ABL) is in the His region showing His bundle electrogram. Paper speed is 50 mm/s.
During EPS, refractory periods of cardiac tissues can be characterized by measuring effective, functional, and relative refractory periods [5].
Most commonly used as it is part of a routine EPS. It represents the longest coupling interval that fails to capture the tissue or be conducted over the structure (Figure 8).
Programmed atrial stimulation from CS 9,10. Drive cycle length is 400 ms. Panel A shows ventricular contraction (i.e., QRS complex) after S2 extrastimulus at a coupling interval of 240 ms. However, Panel B represents atrioventricular block after S2 extrastimulus at a coupling interval of 230 ms. In this case, effective refractory period of the AV node (AVNERP) is 230 ms.
A routine EPS does not include the measurements of the functional and relative refractory period. Functional refractory period means the lower limit shortest “output” coupling interval that can be produced by any “input” interval. Relative refractory periods represent the point at which latency begins to occur. RRP means “input” interval to a tissue at which the “output” interval just begins to differ from the “input” interval.
This chapter summarized the basics of electrophysiological studies of the heart. The author sincerely hopes that the chapter may have contributed to a deeper understanding of the world of electrocardiograms.
The author declares no conflict of interest.
"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges".
\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.
",metaTitle:"About Open Access",metaDescription:"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges.\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.",metaKeywords:null,canonicalURL:"about-open-access",contentRaw:'[{"type":"htmlEditorComponent","content":"The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\\n\\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\\n\\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
\\n\\n“By “open access” to [peer-reviewed research literature], we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited” (reference: http://www.budapestopenaccessinitiative.org)
\\n\\nOAI-PMH
\\n\\nAs a firm believer in the wider dissemination of knowledge, IntechOpen supports the Open Access Initiative Protocol for Metadata Harvesting (OAI-PMH Version 2.0). Read more
\\n\\nLicense
\\n\\nBook chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen upholds a very flexible Copyright Policy. There is no copyright transfer to the publisher and Authors retain exclusive copyright to their work. All Monographs/Compacts are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Read more
\\n\\nPeer Review Policies
\\n\\nAll scientific works are Peer Reviewed prior to publishing. Read more
\\n\\nOA Publishing Fees
\\n\\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
\\n\\nDigital Archiving Policy
\\n\\nIntechOpen is committed to ensuring the long-term preservation and the availability of all scholarly research we publish. We employ a variety of means to enable us to deliver on our commitments to the scientific community. Apart from preservation by the Croatian National Library (for publications prior to April 18, 2018) and the British Library (for publications after April 18, 2018), our entire catalogue is preserved in the CLOCKSS archive.
\\n\\nOpen Science is transparent and accessible knowledge that is shared and developed through collaborative networks.
\\n\\nOpen Science is about increased rigour, accountability, and reproducibility for research. It is based on the principles of inclusion, fairness, equity, and sharing, and ultimately seeks to change the way research is done, who is involved and how it is valued. It aims to make research more open to participation, review/refutation, improvement and (re)use for the world to benefit.
\\n\\nOpen Science refers to doing traditional science with more transparency involved at various stages, for example by openly sharing code and data. It implies a growing set of practices - within different disciplines - aiming at:
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The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\n\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\n\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
\n\n“By “open access” to [peer-reviewed research literature], we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited” (reference: http://www.budapestopenaccessinitiative.org)
\n\nOAI-PMH
\n\nAs a firm believer in the wider dissemination of knowledge, IntechOpen supports the Open Access Initiative Protocol for Metadata Harvesting (OAI-PMH Version 2.0). Read more
\n\nLicense
\n\nBook chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen upholds a very flexible Copyright Policy. There is no copyright transfer to the publisher and Authors retain exclusive copyright to their work. All Monographs/Compacts are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Read more
\n\nPeer Review Policies
\n\nAll scientific works are Peer Reviewed prior to publishing. Read more
\n\nOA Publishing Fees
\n\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
\n\nDigital Archiving Policy
\n\nIntechOpen is committed to ensuring the long-term preservation and the availability of all scholarly research we publish. We employ a variety of means to enable us to deliver on our commitments to the scientific community. Apart from preservation by the Croatian National Library (for publications prior to April 18, 2018) and the British Library (for publications after April 18, 2018), our entire catalogue is preserved in the CLOCKSS archive.
\n\nOpen Science is transparent and accessible knowledge that is shared and developed through collaborative networks.
\n\nOpen Science is about increased rigour, accountability, and reproducibility for research. It is based on the principles of inclusion, fairness, equity, and sharing, and ultimately seeks to change the way research is done, who is involved and how it is valued. It aims to make research more open to participation, review/refutation, improvement and (re)use for the world to benefit.
\n\nOpen Science refers to doing traditional science with more transparency involved at various stages, for example by openly sharing code and data. It implies a growing set of practices - within different disciplines - aiming at:
\n\nWe aim at improving the quality and availability of scholarly communication by promoting and practicing:
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Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. 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After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. 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