LEADER 05598nam 2200697Ia 450 001 9910780290703321 005 20221221223042.0 010 $a1-138-13577-1 010 $a9786611028442 010 $a0-08-051086-8 010 $a1-136-38555-X 010 $a1-281-02844-4 035 $a(CKB)111082128295674 035 $a(EBL)300571 035 $a(OCoLC)728653730 035 $a(SSID)ssj0000196802 035 $a(PQKBManifestationID)11179050 035 $a(PQKBTitleCode)TC0000196802 035 $a(PQKBWorkID)10154192 035 $a(PQKB)10686482 035 $a(MiAaPQ)EBC300571 035 $a(Au-PeEL)EBL300571 035 $a(CaPaEBR)ebr10178628 035 $a(CaONFJC)MIL102844 035 $a(EXLCZ)99111082128295674 100 $a20020408d2002 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aManaging conservation in museums /$fSuzanne Keene 205 $aSecond edition. 210 $aOxford $cButterworth-Heinemann$d2002 215 $a1 online resource (vii, 258 pages) $cillustrations 300 $aPrevious ed.: 1996. 311 0 $a0-7506-5603-4 311 0 $a0-585-45956-8 320 $aIncludes bibliographical references and index. 327 $a""Cover""; ""Managing Conservation in Museums ""; ""Copyright""; ""Contents""; ""Preface""; ""Acknowledgements""; ""1 Introduction""; ""Collections, conservation, and management""; ""Museums""; ""Management and information""; ""Case study""; ""References""; ""2 Museums, collections, and people""; ""Museums""; ""Paradigms for collections""; ""Museum users and their needs""; ""Conservation and museums""; ""Professional roles""; ""References""; ""3 Management and information""; ""Views from general management studies""; ""Information in management""; ""The management of museums"" 327 $a""Issues in museum management""""Conclusions""; ""References""; ""4 Management tools: quantitative planning""; ""Management science and conservation""; ""Conservation costs and benefits""; ""Deciding priorities""; ""Quantifying collections preservation""; ""Quantification: do we need it?""; ""Conclusions""; ""References""; ""5 Management tools: options and priorities""; ""Risk analysis""; ""Contextual analysis: PEST and SWOT""; ""Strategy development""; ""Case study""; ""Conclusions""; ""References""; ""6 A systems view of museums""; ""The systems approach""; ""The soft systems methodology"" 327 $a""Museums as systems""""Real world and system contrast""; ""The changing scene""; ""References""; ""7 The preservation system""; ""The real world: the Rich Picture and Analyses 1, 2 and 3""; ""Relevant systems""; ""Root definitions""; ""The conceptual model""; ""Real world and system contrast""; ""From analysis into management""; ""Conclusions""; ""References""; ""8 Preservation""; ""Preservation standards and policies""; ""Reviews and reports""; ""Case study""; ""Environmental monitoring""; ""Presenting and using environmental data""; ""Case study""; ""Tales of the environment"" 327 $a""Conclusions""""References""; ""9 Collections condition""; ""Surveying collections""; ""Existing work""; ""Defining the data""; ""The audit method""; ""Gathering the data: the survey itself""; ""Analysing and presenting data""; ""Reporting audit results""; ""Monitoring condition over time""; ""Case study""; ""Conclusions""; ""References""; ""10 Direction and strategy""; ""Terminology""; ""Statements of purpose""; ""Policies""; ""Strategy and planning""; ""Approaches to strategic planning""; ""Case study""; ""Performance""; ""Conclusions""; ""References""; ""11 Planning and monitoring work"" 327 $a""Planning work and communicating plans""""Management-by-objectives""; ""Project planning""; ""Allocating resources""; ""Monitoring and reporting""; ""Presenting and using management information""; ""Case study""; ""Planning for skills and quality""; ""Conclusions""; ""References""; ""12 Conservation and digitization""; ""Conservation records on computer""; ""Information for preservation""; ""The conservation information requirement""; ""Case study""; ""Digital preservation""; ""Case study""; ""References""; ""13 Future, present, past""; ""Information for all""; ""The value of information"" 327 $a""Evaluation"" 330 $aExplaining and critically reviewing management procedures such as performance indicators and strategic planning, this book shows how techniques from mainstream management can be used to facilitate a holistic and professional approach to the business of conservation and collection preservation. It offers practical guidance on strategy, quantitative planning and condition surveying, and presents many solutions to the challenges faced by museum staff and conservation specialists.This new edition takes into account changes such as the arrival of the Heritage Lottery Fund, policies for access and t 606 $aMaterial culture$xConservation and restoration$vHandbooks, manuals, etc 606 $aMuseum conservation methods$vHandbooks, manuals, etc 606 $aMuseum techniques$vHandbooks, manuals, etc 615 0$aMaterial culture$xConservation and restoration 615 0$aMuseum conservation methods 615 0$aMuseum techniques 676 $a069.53 700 $aKeene$b Suzanne$0627699 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910780290703321 996 $aManaging Conservation in Museums$91213586 997 $aUNINA LEADER 07465nam 22008655 450 001 9910484600003321 005 20251226202304.0 010 $a1-280-38597-9 010 $a9786613563897 010 $a3-642-12127-6 024 7 $a10.1007/978-3-642-12127-2 035 $a(CKB)2670000000010128 035 $a(SSID)ssj0000399491 035 $a(PQKBManifestationID)11290898 035 $a(PQKBTitleCode)TC0000399491 035 $a(PQKBWorkID)10385502 035 $a(PQKB)10646507 035 $a(DE-He213)978-3-642-12127-2 035 $a(MiAaPQ)EBC3065164 035 $a(PPN)149059876 035 $a(BIP)29190111 035 $a(EXLCZ)992670000000010128 100 $a20100325d2010 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aMultiple Classifier Systems $e9th International Workshop, MCS 2010, Cairo, Egypt, April 7-9, 2010, Proceedings /$fedited by Neamat El Gayar, Josef Kittler, Fabio Roli 205 $a1st ed. 2010. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2010. 215 $a1 online resource (X, 328 p. 77 illus.) 225 1 $aTheoretical Computer Science and General Issues,$x2512-2029 ;$v5997 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a3-642-12126-8 320 $aIncludes bibliographical references and index. 327 $aClassifier Ensembles(I) -- Weighted Bagging for Graph Based One-Class Classifiers -- Improving Multilabel Classification Performance by Using Ensemble of Multi-label Classifiers -- New Feature Splitting Criteria for Co-training Using Genetic Algorithm Optimization -- Incremental Learning of New Classes in Unbalanced Datasets: Learn?+?+?.UDNC -- Tomographic Considerations in Ensemble Bias/Variance Decomposition -- Choosing Parameters for Random Subspace Ensembles for fMRI Classification -- Classifier Ensembles(II) -- An Experimental Study on Ensembles of Functional Trees -- Multiple Classifier Systems under Attack -- SOCIAL: Self-Organizing ClassIfier ensemble for Adversarial Learning -- Unsupervised Change-Detection in Retinal Images by a Multiple-Classifier Approach -- A Double Pruning Algorithm for Classification Ensembles -- Estimation of the Number of Clusters Using Multiple Clustering Validity Indices -- Classifier Diversity -- ?Good? and ?Bad? Diversity in Majority Vote Ensembles -- Multi-information Ensemble Diversity -- Classifier Selection -- Dynamic Selection of Ensembles of Classifiers Using Contextual Information -- Selecting Structural Base Classifiers for Graph-Based Multiple Classifier Systems -- Combining Multiple Kernels -- A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities -- Combining Multiple Kernels by Augmenting the Kernel Matrix -- Boosting and Bootstrapping -- Class-Separability Weighting and Bootstrapping in Error Correcting Output Code Ensembles -- Boosted Geometry-Based Ensembles -- Online Non-stationary Boosting -- Handwriting Recognition -- Combining Neural Networks to Improve Performance of Handwritten Keyword Spotting -- Combining Committee-Based Semi-supervised and Active Learning and Its Application toHandwritten Digits Recognition -- Using Diversity in Classifier Set Selection for Arabic Handwritten Recognition -- Applications -- Forecast Combination Strategies for Handling Structural Breaks for Time Series Forecasting -- A Multiple Classifier System for Classification of LIDAR Remote Sensing Data Using Multi-class SVM -- A Multi-Classifier System for Off-Line Signature Verification Based on Dissimilarity Representation -- A Multi-objective Sequential Ensemble for Cluster Structure Analysis and Visualization and Application to Gene Expression -- Combining 2D and 3D Features to Classify Protein Mutants in HeLa Cells -- An Experimental Comparison of Hierarchical Bayes and True Path Rule Ensembles for Protein Function Prediction -- Recognizing Combinations of Facial Action Units with Different Intensity Using a Mixture of Hidden Markov Models and Neural Network -- Invited Papers -- Some Thoughts at the Interface of Ensemble Methods and Feature Selection -- Multiple Classifier Systems for the Recogonition of Human Emotions -- Erratum -- Erratum. 330 $aThese proceedings are a record of the Multiple Classi'er Systems Workshop, MCS 2010, held at the Nile University, Egypt in April 2010. Being the ninth in a well-established series of meetings providing an international forum for d- cussion of issues in multiple classi'er system design, the workshop achieved its objective of bringing together researchers from diverse communities (neural n- works, pattern recognition, machine learning and statistics) concerned with this researchtopic.Frommorethan50submissions,theProgramCommitteeselected 31 papers to create an interesting scienti'c program.Paperswere organizedinto sessionsdealingwithclassi'ercombinationandclassi'erselection,diversity,b- ging and boosting, combination of multiple kernels, and applications. The wo- shopprogramandthisvolumewereenrichedbytwoinvitedtalksgivenbyGavin Brown(University of Manchester,UK), and Friedhelm Schwenker(University of Ulm, Germany). As usual, the workshop would not have been possible without the help of many individuals and organizations. First of all, our thanks go to the members of the MCS 2010 Program Committee, whose expertise and dedication helped us create an interesting event that marks the progressmade in this ?eld overthe last year and aspire to chart its future research. The help of James Field from the University of Surrey, who administered the submitted paper reviews, and of Giorgio Fumera who managed the MCS website deserve a particular mention. Special thanks are due to the members of the Nile University Organizing C- mittee,AhmedSalah,AmiraElBaroudy,EsraaAly,HebaEzzat,NesrineSameh, Rana Salah and Mohamed Zahhar for their indispensable contributions to the registration management, local organization, and proceedings preparation. 410 0$aTheoretical Computer Science and General Issues,$x2512-2029 ;$v5997 606 $aArtificial intelligence 606 $aApplication software 606 $aPattern recognition systems 606 $aAlgorithms 606 $aComputer science 606 $aDatabase management 606 $aArtificial Intelligence 606 $aComputer and Information Systems Applications 606 $aAutomated Pattern Recognition 606 $aAlgorithms 606 $aTheory of Computation 606 $aDatabase Management 615 0$aArtificial intelligence. 615 0$aApplication software. 615 0$aPattern recognition systems. 615 0$aAlgorithms. 615 0$aComputer science. 615 0$aDatabase management. 615 14$aArtificial Intelligence. 615 24$aComputer and Information Systems Applications. 615 24$aAutomated Pattern Recognition. 615 24$aAlgorithms. 615 24$aTheory of Computation. 615 24$aDatabase Management. 676 $a006.3 701 $aEl Gayar$b Neamat$01754896 701 $aKittler$b Josef$f1946-$013183 701 $aRoli$b Fabio$f1962-$0275187 712 12$aMCS 2010 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484600003321 996 $aMultiple classifier systems$94191409 997 $aUNINA