LEADER 00822nam0-22002891i-450- 001 990001004920403321 035 $a000100492 035 $aFED01000100492 035 $a(Aleph)000100492FED01 035 $a000100492 100 $a20000920d1968----km-y0itay50------ba 101 0 $aeng 200 1 $aMathematical Structures of Language$fZellig Harris 210 $aNew York$cInterscience$d1968 225 1 $aInterscience Tracts in Pure and Applied Mathematics$v21 610 0 $aLinguistica 676 $a410 700 1$aHarris,$bZellig Sabbettai$047566 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990001004920403321 952 $a3-010$b6382$fFI1 952 $a3-010.001$b13889$fFI1 959 $aFI1 996 $aMathematical Structures of Language$9354601 997 $aUNINA DB $aING01 LEADER 05370nam 2200649 450 001 9910463428403321 005 20200520144314.0 010 $a1-5231-1750-8 010 $a1-60807-512-5 035 $a(CKB)2670000000327380 035 $a(EBL)1115667 035 $a(OCoLC)827208673 035 $a(SSID)ssj0000873799 035 $a(PQKBManifestationID)12439482 035 $a(PQKBTitleCode)TC0000873799 035 $a(PQKBWorkID)10878056 035 $a(PQKB)10805751 035 $a(MiAaPQ)EBC1115667 035 $a(Au-PeEL)EBL1115667 035 $a(CaPaEBR)ebr10857820 035 $a(CaBNVSL)mat09100724 035 $a(IEEE)9100724 035 $a(EXLCZ)992670000000327380 100 $a20200730d2012 uy 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aPower system state estimation /$fMukhtar Ahmad 210 1$aBoston :$cArtech House,$d[2013] 210 2$a[Piscataqay, New Jersey] :$cIEEE Xplore,$d[2012] 215 $a1 online resource (207 p.) 225 1 $aArtech House power engineering series 300 $aDescription based upon print version of record. 311 $a1-60807-511-7 320 $aIncludes bibliographical references and index. 327 $aPreface; 1Energy Management Systems; 1.1 Real-Time Control of a Power System; 1.2 Energy Control Center; 1.3 Security Analysis and Monitoring; 1.4 State Estimation; References; 2Power Flow Equations; 2.1 Power System Representation; 2.1.1 Transmission Lines; 2.1.2 Power Transformer; 2.2 Admittance Diagram; 2.3 Power Flow Analysis; 2.3.1 Gauss-Seidel Method; 2.3.2 Newton-Raphson Method; 2.4 Decoupled Power Flow; 2.5 Visual Tools for Power Flow Studies; 2.6 DC Power Flow; 2.7 Regulating Transformers; References; 3Weighted Least Square Estimation; 3.1 Introduction. 327 $a3.2 Properties of Weighted Least Square3.3 Maximum Likelihood Weighted Least Square State Estimation; 3.3.1 Likelihood Function; 3.4 Matrix Formulation and Measurement Measurement Model; 3.4.1 Measurement Model; 3.5 WLS State Estimation Algorithm; 3.5.1 State Estimation by Orthogonal Decomposition; 3.5.2 Equality Constrained State Estimation; 3.6 Decoupled State Estimation Method; 3.6.1 Algorithm Decoupling; 3.6.2 Model Decoupling; 3.7 DC State Estimator; References; 4Network Observability and Pseudomeasurem; 4.1 Network Graphs and Matrices; 4.2 Bus Admittance and Bus Impedance Matrices. 327 $a4.2.1 Loop to Branch Incidence Matrix4.3 Loop Equations; 4.4 Observability Analysis; 4.5 Branch Variable Formulation; 4.5.1 New Branch Variables; 4.5.2 Measurement Model Using Branch Variables; 4.5.3 Observability Analysis for Branch Variable Formulation; 4.6 Network Topology Processing; 4.7 Network Configuration; 4.7.1 Topological Observability; 4.7.2 Topological Observability Algorith; 4.8 Topology Error Processing; 4.9 Detection and Identification of Topology Errors; 4.9.1 Residual Analysis; References; 5Bad Data Detection; 5.1 Bad Data Detection in WLS Method; 5.1.1 Leverage Points. 327 $a5.2 Methods of Bad Data Detection5.2.1 Chi-Squares Test; 5.3 Identification of Bad Data; 5.3.1 Method of Normalized Residual; 5.3.2 Normalized Residuals; 5.3.3 Largest Normalized Residual Test; 5.4 Hypothesis Testing Identification; 5.5 Case Study: Improved Bad Data Processing with Strategic Placement of PMUs; References; Appendix 5A: Chi-Square Test; 6Robust State Estimation; 6.1 Basic Formulation; 6.2 Breakdown Points; 6.2.1 Leverage Points; 6.3 M-Estimators; 6.4 State Estimation Methods with Bad Data Rejection Properties; 6.4.1 Methods Using Nonquadratic Objective Functions. 327 $a6.5 Least Absolute Value State Estimator6.6 Simplex Method; 6.7 Interior Point Algorithm; 6.8 LMS Estimator; References; Appendix 6A: Linear Programming; 6A.1 Simplex Algorithm; 7 State Estimation Using Line Current Measurements; 7.1 Introduction; 7.2 Modeling State Equations; 7.3 State Estimation with Current Measurements; 7.3.1 Multiple Solutions; 7.4 Methods to Obtain a Unique Solution; 7.5 Determining the Uniqueness of a Solution Based on Numerical Methods; 7.6 Bad Data Detection in the Presence of Current Measurements; 7.6.1 WLS State Estimation; 7.6.2 WLAV Estimation. 330 $aState estimation is one of the most important functions in power system operation and control. This area is concerned with the overall monitoring, control, and contingency evaluation of power systems. It is mainly aimed at providing a reliable estimate of system voltages. State estimator information flows to control centers, where critical decisions are made concerning power system design and operations. This valuable resource provides thorough coverage of this area, helping professionals overcome challenges involving system quality, reliability, security, stability, and economy. Engineers are. 410 0$aArtech House power engineering series. 606 $aElectric power systems$xState estimation 608 $aElectronic books. 615 0$aElectric power systems$xState estimation. 676 $a621.31 676 $a621.319/1 700 $aAhmad$b Mukhtar$f1948-$0969655 801 0$bCaBNVSL 801 1$bCaBNVSL 801 2$bCaBNVSL 906 $aBOOK 912 $a9910463428403321 996 $aPower system state estimation$92258305 997 $aUNINA LEADER 06993nam 22007575 450 001 996203621803316 005 20200702165402.0 010 $a3-319-06269-7 024 7 $a10.1007/978-3-319-06269-3 035 $a(CKB)3710000000106756 035 $a(DE-He213)978-3-319-06269-3 035 $a(SSID)ssj0001204920 035 $a(PQKBManifestationID)11687283 035 $a(PQKBTitleCode)TC0001204920 035 $a(PQKBWorkID)11181018 035 $a(PQKB)10127212 035 $a(MiAaPQ)EBC3093508 035 $a(PPN)178320439 035 $a(EXLCZ)993710000000106756 100 $a20140402d2014 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aHealth Information Science$b[electronic resource] $eThird International Conference, HIS 2014, Shenzhen, China, April 22-23, 2014, Proceedings /$fedited by Yanchun Zhang, Guiqing Yao, Jing He, Lei Wang, Neil R. Smalheiser, Xiaoxia Yin 205 $a1st ed. 2014. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014. 215 $a1 online resource (XIV, 282 p. 123 illus.) 225 1 $aInformation Systems and Applications, incl. Internet/Web, and HCI ;$v8423 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-319-06268-9 327 $a?Machine Beauty? ? Should It Inspire eHealth Designers? -- Mean Shift Based Feature Points Selection Algorithm of DSA Images -- Numerical Evaluation of the Effectiveness of the Air Chamber of Shoes Pad for Diabetes with FE-SPH Method -- Effect of Suture Density on the Dynamic Behavior of the Bioprosthetic Heart Valve: A Numerical Simulation Study -- An Analysis on Risk Factors of Chronics Diseases Based on GRI -- A Study on the Nonlinearity Relationship between Quadriceps Thickness and Torque Output during Isometric Knee Extension -- A Comparative Study of Improvements Filter Methods Bring on Feature Selection Using Microarray Data -- Real-Time Estimation of Tibialis Anterior Muscle Thickness from Dysfunctional Lower Limbs Using Sonography -- A Prosthesis Control System Based on the Combination of Speech and sEMG Signals and Its Performance Assessment -- Detecting Adolescent Psychological Pressures from Micro-Blog -- Detecting Abnormal Patterns of Daily Activities for the Elderly Living Alone -- Detecting Noun Phrases in Biomedical Terminologies: The First Step in Managing the Evolution of Knowledge -- Color-Coded Imaging with Adaptive Multiscale Spatial Filtering -- An Architecture and a Platform for Recording and Replaying the Healthcare Information -- Design and Development of a 3-Lead ECG System Based on the ISO/IEEE 11073-10406 Standards -- Data Integration in a Clinical Environment Using the Global-as-Local-View-Extension Technique -- Fall Detection with the Optimal Feature Vectors Based on Support Vector Machine -- Pre-impact and Impact Detection of Falls Using Built-In Tri-Accelerometer of Smartphone -- Portable Assessment of Emotional Status and Support System -- Mining Order-Preserving Submatrices Based on Frequent Sequential Pattern Mining -- Unsupervised Segmentation of Blood Vessels from Colour Retinal Fundus Images -- Mobile Graphic-Based Communication: Investigating Reminder Notifications to Support Tuberculosis Treatment in Africa -- Multiscale Geometric Active Contour Model and Boundary Extraction in Kidney MR Images -- Discovering New Analytical Methods for Large Volume Medical and Online Data Processing -- Water Molecules Diffusion in Diffusion Weighted Imaging -- Feasibility Study of Signal Similarity Measurements for Improving Morphological Evaluation of Human Brain with Images from Multi-Echo T2-Star Weighted MR Sequences -- Multi-agent Based Clinical Knowledge Representation with Its Dynamic Parse and Execution -- Research on Applications of Multi-Agent System Based on Execution Engine in Clinical Decision-Making -- A Comfortable THz Source for Biological Effect. 330 $aThis book constitutes the refereed proceedings of the Third International Conference on Health Information Science, HIS 2014, held in Shenzhen, China, in April 2014. The 29 full papers presented were carefully reviewed and selected from 61 submissions. They cover a wide range of topics in health information sciences and systems that support the health information management and health service delivery. They deal with medical/health/biomedicine information resources, such as patient medical records, devices and equipments, software and tools to capture, store, retrieve, process, analyse, and optimize the use of information in the health domain; data management, data mining, and knowledge discovery, all of which play a key role in the decision making, management of public health, examination of standards, privacy and security issues; computer visualization and artificial intelligence for computer-aided diagnosis; and development of new architectures and applications for health information systems. 410 0$aInformation Systems and Applications, incl. Internet/Web, and HCI ;$v8423 606 $aHealth informatics 606 $aApplication software 606 $aData mining 606 $aArtificial intelligence 606 $aInformation storage and retrieval 606 $aHealth Informatics$3https://scigraph.springernature.com/ontologies/product-market-codes/I23060 606 $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 615 0$aHealth informatics. 615 0$aApplication software. 615 0$aData mining. 615 0$aArtificial intelligence. 615 0$aInformation storage and retrieval. 615 14$aHealth Informatics. 615 24$aInformation Systems Applications (incl. Internet). 615 24$aData Mining and Knowledge Discovery. 615 24$aArtificial Intelligence. 615 24$aInformation Storage and Retrieval. 676 $a502.85 702 $aZhang$b Yanchun$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aYao$b Guiqing$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aHe$b Jing$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWang$b Lei$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSmalheiser$b Neil R$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aYin$b Xiaoxia$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a996203621803316 996 $aHealth Information Science$91934688 997 $aUNISA