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1. |
Record Nr. |
UNINA9910953376203321 |
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Autore |
Balding D. J |
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Titolo |
Weight-of-evidence for DNA profiles / / David J. Balding |
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Pubbl/distr/stampa |
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Hoboken, N.J., : John Wiley & Sons, c2005 |
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ISBN |
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9786610272112 |
9781280272110 |
1280272112 |
9780470300503 |
0470300507 |
9780470867693 |
0470867698 |
9780470867662 |
0470867663 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (199 p.) |
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Collana |
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Disciplina |
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Soggetti |
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Forensic genetics - Statistical methods |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references (175-181) and index. |
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Nota di contenuto |
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Weight-of-evidence for Forensic DNA Profiles; Statistics in Practice; Contents; Preface; 1 Introduction; 1.1 Weight-of-evidence theory; 1.2 About the book; 1.3 DNA profiling technology; 1.4 What you need to know already; 1.5 Other resources; 2 Crime on an island; 2.1 Warm-up examples; 2.1.1 Disease testing: Positive Predictive Value (PPV); 2.1.2 Coloured taxis; 2.2 Rare trait identification evidence; 2.2.1 The "island" problem; 2.2.2 A first lesson from the island problem; 2.3 Making the island problem more realistic; 2.3.1 Uncertainty about p; 2.3.2 Uncertainty about N |
2.3.3 Possible typing errors2.3.4 Searches; 2.3.5 Other evidence; 2.3.6 Relatives and population subdivision; 2.4 Weight-of-evidence exercises; 3 Assessing evidence via likelihood ratios; 3.1 Likelihood ratios; 3.2 The weight-of-evidence formula; 3.2.1 Application to the island problem; 3.2.2 The population P; 3.3 General application of the formula; 3.3.1 Several items of evidence; 3.3.2 Assessing all the |
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evidence; 3.3.3 The role of the expert witness; 3.4 Consequences for DNA evidence; 3.4.1 Many possible culprits; 3.4.2 Incorporating the non-DNA evidence; 3.4.3 Relatives |
7.1.4 Multiple loci: the effect of linkage |
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Sommario/riassunto |
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Assessing Weight-of-Evidence for DNA Profiles is an excellent introductory text to the use of statistical analysis for assessing DNA evidence. It offers practical guidance to forensic scientists with little dependence on mathematical ability as the book includes background information on statistics - including likelihood ratios - population genetics, and courtroom issues. The author, who is highly experienced in this field, has illustrated the book throughout with his own experiences as well as providing a theoretical underpinning to the subject. It is an ideal choice for forensic scientis |
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2. |
Record Nr. |
UNINA9910483609603321 |
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Titolo |
Scalable Uncertainty Management : 7th International Conference, SUM 2013, Washington, DC, USA, September 16-18, 2013, Proceedings / / edited by Weiru Liu, V S Subrahmanian, Jef Wijsen |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 |
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ISBN |
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Edizione |
[1st ed. 2013.] |
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Descrizione fisica |
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1 online resource (XIV, 387 p. 43 illus.) |
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Collana |
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Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 8078 |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Application software |
Information storage and retrieval systems |
Computer networks |
Database management |
Data mining |
Artificial Intelligence |
Computer and Information Systems Applications |
Information Storage and Retrieval |
Computer Communication Networks |
Database Management |
Data Mining and Knowledge Discovery |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di contenuto |
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Argumentation -- Analysis of dialogical argumentation via finite state machines -- What Can Argumentation Do for Inconsistent Ontology Query Answering? -- Enforcement in Argumentation is a kind of Update -- A Conditional Logic-Based Argumentation Framework -- Modelling Uncertainty in Persuasion -- On the implementation of a multiple output algorithm for defeasible argumentation -- A formal characterization of the outcomes of rule-based argumentation systems -- Bimodal Graphs for Meta-Argumentation with Argument Schemes -- Efficiently Estimating the Probability of Extensions in Abstract Argumentation -- AFs with Necessities : Further Semantics and Labelling Characterization -- Ranking-based semantics for argumentation frameworks -- A Logical Theory about Dynamics in Abstract Argumentation -- Belief Functions, Possibility Theory and their Applications -- Sound Source Localization from Uncertain Information using the Evidential EM Algorithm -- An Improvement of Subject Reacquisition by Reasoning and Revision -- Belief Functions: a Revision of Plausibility Conflict and Pignistic Conflict -- Bipolar possibility theory as a basis for a logic of desires and beliefs -- Databases -- A New Class of Lineage Expressions over Probabilistic Databases computable in P-time -- The Semantics of Aggregate Queries in Data Exchange Revisited -- PossDB: An Uncertainty Database Management System -- Aggregate Count Queries in Probabilistic Spatio-Temporal Databases -- Intelligent Data Analytics -- Approximate Reasoning about Generalized Conditional Independence with Complete Random Variables -- Combinatorial Prediction Markets: An Experimental Study -- A scalable learning algorithm for kernel probabilistic classifier -- Logics, Description Logic, and Semantic Web -- Privacy-Preserving Social Network Publication Based on Positional Indiscernibility -- On the implementation of a fuzzy DL solver over infinite-valued product logic with SMT solvers -- On the Merit of Selecting Different Belief Merging Operators -- Possibilistic DL-Lite -- Group Preferences for Query Answering in Datalog+/- Ontologies -- Reasoning with Semantic-Enabled Qualitative Preferences. |
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Sommario/riassunto |
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This book constitutes the refereed proceedings of the 7th International Conference on Scalable Uncertainty Management, SUM 2013, held in Washington, DC, USA, in September 2013. The 26 revised full papers and 3 revised short papers were carefully reviewed and selected from 57 submissions. The papers cover topics in all areas of managing and reasoning with substantial and complex kinds of uncertain, incomplete or inconsistent information including applications in decision support systems, machine learning, negotiation technologies, semantic web applications, search engines, ontology systems, information retrieval, natural language processing, information extraction, image recognition, vision systems, data and text mining, and the consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge. |
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