LEADER 07451nam 22006615 450 001 996465592503316 005 20220519141221.0 010 $a3-642-53914-9 024 7 $a10.1007/978-3-642-53914-5 035 $a(CKB)3710000000078897 035 $a(DE-He213)978-3-642-53914-5 035 $a(SSID)ssj0001090075 035 $a(PQKBManifestationID)11617867 035 $a(PQKBTitleCode)TC0001090075 035 $a(PQKBWorkID)11126222 035 $a(PQKB)11367577 035 $a(MiAaPQ)EBC3093564 035 $a(PPN)176118373 035 $a(EXLCZ)993710000000078897 100 $a20131214d2013 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvanced Data Mining and Applications$b[electronic resource] $e9th International Conference, ADMA 2013, Hangzhou, China, December 14-16, 2013, Proceedings, Part I /$fedited by Hiroshi Motoda, Zhaohui Wu, Longbing Cao, Osmar Zaiane, Min Yao, Wei Wang 205 $a1st ed. 2013. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2013. 215 $a1 online resource (XXII, 588 p. 217 illus.) 225 1 $aLecture Notes in Artificial Intelligence ;$v8346 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-642-53913-0 327 $aOpinion Mining -- Mining E-Commerce Feedback Comments for Dimension Rating Profiles -- Generating Domain-Specific Sentiment Lexicons for Opinion Mining -- Effective Comment Sentence Recognition for Feature-based Opinion Mining -- Exploiting Co-occurrence Opinion Words for Semi-supervised Sentiment Classification -- Behavior Mining -- HN-Sim: A Structural Similarity Measure over Object-Behavior Networks -- Community Based User Behavior Analysis on Daily Mobile Internet Usage -- Stream Mining -- Tracking Drift Types in Changing Data Streams -- Continuously Extracting High-quality Representative Set from Massive Data Streams -- Change Itemset Mining in Data Streams -- Sequential Data Mining -- TKS: Efficient Mining of Top-K Sequential Patterns -- When Optimization is Just an Illusion -- Accurate and fast dynamic time warping -- Online Detecting Spreading Events with the Spatio-temporal Relationship in Water Distribution Networks -- MLSP: Mining Hierarchically-Closed Multi-Level Sequential Patterns -- Mining Maximal Sequential Patterns without Candidate Maintenance -- Web Mining -- Improved Slope One Collaborative Filtering Predictor Using Fuzzy Clustering -- Towards Building Virtual Vocabularies in the Semantic Web -- Web Mining Accelerated with In-Memory and Column Store Technology -- Image Mining -- Constructing a novel pos-neg manifold for global-based image classification -- 3-D MRI Brain Scan Feature Classification Using an Oct-tree Representation -- Biometric Template Protection Based on Biometric Certificate and Fuzzy Fingerprint Vault -- A Comparative Study of Three Image Representations for Population Estimation Mining Using Remote Sensing Imagery -- Mixed-Norm Regression for Visual Classification -- Research on Map Matching Based on Hidden Markov Model -- Text Mining -- A Rule-Based Named-Entity Recognition for Malay Articles -- Small is Powerful! Towards a Refinedly Enriched Ontology by Careful Pruning and Trimming -- Refine the Corpora Based on Document Manifold -- Social Network Mining -- Online Friends Recommendation based on Geographic Trajectories and Social Relations -- The Spontaneous Behavior in Extreme Events: A Clustering-based Quantitative Analysis -- Restoring: A Greedy Heuristic Approach Based on Neighborhood for Correlation Clustering -- A Local Greedy Search Method for Detecting Community Structure in Weighted Social Networks -- Tree-based Mining for Discovering Patterns of Reposting Behavior in Microblog -- An Improved Parallel Hybrid Seed Expansion (PHSE) Method for Detecting Highly Overlapping Communities in Social Networks -- A Simple Integration of Social Relationship and Text Data for Identifying Potential Customers in Microblogging -- An Energy Model for Network Community Structure Detection -- A Label Propagation-based Algorithm for Community Discovery in Online Social Networks -- Mining Twitter Data for Potential Drug Effects -- Social-Correlation Based Mutual Reinforcement for Short Text Classification and User Interest Tagging -- Classification -- Graph based Feature Augmentation for Short and Sparse Text Classification -- Exploring Deep Belief Nets to Detect and Categorize Chinese Entities -- Extracting Novel Features for E-commerce Page Quality Classification -- Hierarchical Classification for Solving Multi-class Problems: A New Approach Using Naive Bayesian Classification -- Predicting Features in Complex 3D Surfaces Using a Point Series Representation: A Case Study in Sheet Metal Forming -- Automatic Labeling of Forums using Bloom's Taxonomy -- Classifying Papers from Different Computer Science Conferences -- Vertex Unique Labelled Subgraph Mining for Vertex Label Classification -- A Similarity-Based Grouping Method for Molecular Docking in Distributed System -- A Bag-of-Tones Model with MFCC Features for Musical Genre Classification -- The GEPSO-Classification Algorithm. 330 $aThe two-volume set LNAI 8346 and 8347 constitutes the thoroughly refereed proceedings of the 9th International Conference on Advanced Data Mining and Applications, ADMA 2013, held in Hangzhou, China, in December 2013. The 32 regular papers and 64 short papers presented in these two volumes were carefully reviewed and selected from 222 submissions. The papers included in these two volumes cover the following topics: opinion mining, behavior mining, data stream mining, sequential data mining, web mining, image mining, text mining, social network mining, classification, clustering, association rule mining, pattern mining, regression, predication, feature extraction, identification, privacy preservation, applications, and machine learning. 410 0$aLecture Notes in Artificial Intelligence ;$v8346 606 $aArtificial intelligence 606 $aData mining 606 $aInformation storage and retrieval 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 615 0$aArtificial intelligence. 615 0$aData mining. 615 0$aInformation storage and retrieval. 615 14$aArtificial Intelligence. 615 24$aData Mining and Knowledge Discovery. 615 24$aInformation Storage and Retrieval. 676 $a006.3 702 $aMotoda$b Hiroshi$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWu$b Zhaohui$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aCao$b Longbing$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aZaiane$b Osmar$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aYao$b Min$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWang$b Wei$f1973-$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a996465592503316 996 $aAdvanced Data Mining and Applications$9771989 997 $aUNISA LEADER 05167nam 2200697Ia 450 001 9910815284203321 005 20240417003312.0 010 $a0-309-18008-2 010 $a1-280-54248-9 010 $a9786610542482 010 $a0-309-65790-3 035 $a(CKB)1000000000464992 035 $a(EBL)3378099 035 $a(SSID)ssj0000203275 035 $a(PQKBManifestationID)11168520 035 $a(PQKBTitleCode)TC0000203275 035 $a(PQKBWorkID)10258545 035 $a(PQKB)10921850 035 $a(MiAaPQ)EBC3378099 035 $a(Au-PeEL)EBL3378099 035 $a(CaPaEBR)ebr10132065 035 $a(OCoLC)923275608 035 $a(EXLCZ)991000000000464992 100 $a20060518d2006 uh 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 00$aMineral requirements for military personnel $elevels needed for cognitive and physical performance during garrison training /$fCommittee on Mineral Requirements for Cognitive and Physical Performance of Military Personnel, Committee on Military Nutrition Research, Food and Nutrition Board 205 $a1st ed. 210 $aWashington, DC $cNational Academies Press$dc2006 215 $a1 online resource (xv, 496 pages) $cillustrations, charts (some color) 300 $aDescription based upon print version of record. 311 1 $a0-309-10126-3 320 $aIncludes bibliographical references. 327 $a""Front Matter""; ""Reviewers""; ""Preface""; ""Contents""; ""Summary""; ""1 Introduction""; ""2 Military Dietary Reference Intakes: Process to Establish, Uses, and Delivery Methods""; ""3 Mineral Recommendations for Military Performance""; ""4 Research Needs""; ""5 Answers to the Military's Questions""; ""APPENDIXES""; ""A Workshop Agenda""; ""B Workshop Papers""; ""Concerns About the Effects of Military Environments on Mineral Metabolism and Consequences of Marginal Deficiencies to Performance Karl E. Friedl"" 327 $a""Derivation of the Military Dietary Reference Intakes and the Mineral Content of Military Rations Carol J. Baker-Fulco"" ""Bioavailability of Iron, Zinc, and Copper as Influenced by Host and Dietary Factors Janet R. Hunt""; ""Functional Metabolism of Copper, Zinc, and Iron Cathy W. Levenson""; ""Absorption Mechanisms, Bioavailability, and Metabolism of Calcium and Magnesium Connie M. Weaver""; ""Drinking Water as a Source of Mineral Nutrition Gerald F. Combs, Jr."" 327 $a""Assessment of Zinc, Copper, and Magnesium Status: Current Approaches and Promising New Directions Carl L. Keen and Janet Y. Uriu-Adams"" ""Environmental Stressors During Military Operations Robert Carter III, Samuel N. Cheuvront, Andrew J. Young, and Michael N. Sawka""; ""Mineral Sweat Losses During Exercise Emily M. Haymes""; ""Stress Factors Affecting Homeostasis: Weight Loss and Mineral Status Steven B. Heymsfield""; ""Protein Turnover and Mineral Metabolism Henry C. Lukaski"" 327 $a""Physical Activity and Tyrosine Supplementation: Two Effective Interventions Against Stress-Induced Immunosuppression Monika Fleshner"" ""Mineral Intake Needs and Infectious Diseases Davidson H. Hamer""; ""Copper, Zinc, and Immunity Susan S. Percival""; ""Impact of Nutritional Deficiencies and Psychological Stress on the Innate Immune Response and Viral Pathogenesis John F. Sheridan, Patricia A. Sheridan, and Melinda A. Beck""; ""The Influence of Minerals on Muscle Injury and Recovery Joseph G. Cannon"" 327 $a""Physical Activity and Nutrition: Effects on Bone Turnover, Bone Mass, and Stress Fracture Jeri W. Nieves"" ""Evaluating Nutritional Effects on Cognitive Function in Warfighters: Lessons Learned Harris R. Lieberman""; ""Iron and Cognitive Performance John L. Beard and Laura E. Murray-Kolb""; ""Zinc and Other Mineral Nutrients Required for Cognitive Function and Behavior in Military Personnel James G. Penland""; ""Zinc, Magnesium, and Copper Requirements and Exercise Henry C. Lukaski""; ""The Effects of Iron Deficiency on Physical Performance Jere D. Haas""; ""C Tables"" 327 $a""D Biographical Sketches of Workshop Speakers"" 606 $aOperational rations (Military supplies)$zUnited States 606 $aSoldiers$xNutrition$xRequirements$zUnited States 606 $aMinerals in human nutrition$zUnited States 606 $aStress (Physiology)$xNutritional aspects 615 0$aOperational rations (Military supplies) 615 0$aSoldiers$xNutrition$xRequirements 615 0$aMinerals in human nutrition 615 0$aStress (Physiology)$xNutritional aspects. 676 $a613.2/850243555 712 02$aNational Academy of Sciences (U.S.).$bCommittee on Mineral Requirements for Cognitive and Physical Performance of Military Personnel. 712 02$aInstitute of Medicine (U.S.).$bCommittee on Military Nutrition Research. 712 02$aNational Academy of Sciences (U.S.).$bFood and Nutrition Board. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910815284203321 996 $aMineral requirements for military personnel$93937215 997 $aUNINA