LEADER 04261 am 2200781 n 450 001 9910552973603321 005 20210421 010 $a2-36781-415-5 024 7 $a10.4000/books.pulm.15598 035 $a(CKB)4100000012773907 035 $a(FrMaCLE)OB-pulm-15598 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/86310 035 $a(PPN)261977997 035 $a(EXLCZ)994100000012773907 100 $a20220325j|||||||| ||| 0 101 0 $aeng 135 $auu||||||m|||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aTerror and its Representations $eStudies in Social History and Cultural Expression in the United States and Beyond /$fLarry Portis, Joseph Zitomersky 210 $aMontpellier $cPresses universitaires de la Méditerranée$d2021 215 $a1 online resource (320 p.) 225 1 $aHorizons anglophones 311 $a2-84269-841-X 330 $aWhat are the origins and nature of terror and terrorism in the United States and beyond? This book of essays about the history and contemporary reality of terror reveals little-known aspects of a compelling subject. Since the American and French Revolutions, governments and their opponents have used terror and terrorism for different political reasons. We learn how terror and terrorism have marked the evolution of social values and have entered into cultural expression of all types - literature, music, television, cinema - and have influenced the formation of ideologies and political institutions. The authors of the introduction and eighteen chapters comprising Terror and Its Representations show how a sensitive subject can be treated with conviction while maintaining the critical distance necessary for serious debate. Quelles sont les origines et la nature de la terreur et du terrorisme aux États-Unis et ailleurs ? Cet ouvrage composé d?essais sur l?histoire de la terreur et sur sa réalité contemporaine met en lumière des aspects peu connus d?un sujet captivant. Depuis les révolutions française et étatsunienne, les gouvernements et leurs opposants ont utilisé la terreur et le terrorisme pour différentes raisons politiques. On apprendra ici comment la terreur et le terrorisme ont marqué l?évolution des valeurs sociales, comment ils sont entrés dans les expressions culturelles de tout type - littéraires, musicales, télévisuelles, cinématographiques - et comment ils ont influencé la formation des idéologies et des institutions politiques. Il est possible de traiter un sujet sensible en gardant la distance critique nécessaire à un débat de fond : c?est ce que les auteurs de cet ouvrage ont voulu montrer. 606 $aHistory 606 $asocial history 606 $aUnited States 606 $aterror 606 $arepresentation 610 $asocial history 610 $aUnited States 610 $aterror 610 $arepresentation 615 4$aHistory 615 4$asocial history 615 4$aUnited States 615 4$aterror 615 4$arepresentation 700 $aBellesîles$b Michael$01329263 701 $aBianchi$b Serge$0211594 701 $aCeschi$b Matteo$01329264 701 $aCreagh$b Ronald$0615115 701 $aFannin$b Mark$01329265 701 $aFeeley$b Francis McCollum$01329266 701 $aFields$b Gary$01329267 701 $aFiume$b Fabrizio$0251818 701 $aGuerlain$b Pierre$01282040 701 $aHarvey$b Robert$018344 701 $aHorwitz$b Barry David$01329268 701 $aMackenthun$b Gesa$0240962 701 $aMannucci$b Erica$01329269 701 $aMannucci$b Loretta Valtz$01329270 701 $aPellerin$b Simone$01316408 701 $aPortis$b Larry$01329271 701 $aRiches$b William T. Martin$01329272 701 $aSmith$b Thérèse$01329273 701 $aUrbanowski$b Anne$01296591 701 $aVovelle$b Michel$0139780 701 $aZitomersky$b Joseph$01329274 701 $aPortis$b Larry$01329271 701 $aZitomersky$b Joseph$01329274 801 0$bFR-FrMaCLE 906 $aBOOK 912 $a9910552973603321 996 $aTerror and its Representations$93039361 997 $aUNINA LEADER 09357nam 22008775 450 001 9910768481303321 005 20241120174950.0 010 $a3-031-09034-9 024 7 $a10.1007/978-3-031-09034-9 035 $a(MiAaPQ)EBC31016755 035 $a(Au-PeEL)EBL31016755 035 $a(DE-He213)978-3-031-09034-9 035 $a(OCoLC)1415895688 035 $a(CKB)29374735700041 035 $a(oapen)doab132010 035 $a(EXLCZ)9929374735700041 100 $a20231207d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aClassification and Data Science in the Digital Age /$fedited by Paula Brito, José G. Dias, Berthold Lausen, Angela Montanari, Rebecca Nugent 205 $a1st ed. 2023. 210 $aCham$cSpringer Nature$d2023 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (393 pages) 225 1 $aStudies in Classification, Data Analysis, and Knowledge Organization,$x2198-3321 311 08$aPrint version: Brito, Paula Classification and Data Science in the Digital Age Cham : Springer International Publishing AG,c2024 9783031090332 327 $aPreface -- R. Abdesselam: A Topological Clustering of Individuals -- C. Anton and I. Smith: Model Based Clustering of Functional Data with Mild Outliers -- F. Antonazzo and S. Ingrassia: A Trivariate Geometric Classification of Decision Boundaries for Mixtures of Regressions -- E. Arnone, E. Cunial, and L. M. Sangalli: Generalized Spatio-temporal Regression with PDE Penalization -- R. Ascari and S. Migliorati: A New Regression Model for the Analysis of Microbiome Data -- R. Aschenbruck, G. Szepannek, and A. F. X. Wilhelm: Stability of Mixed-type Cluster Partitions for Determination of the Number of Clusters -- A. Ashofteh and P. Campos: A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment -- V. Batagelj: Clustering and Blockmodeling Temporal Networks ? Two Indirect Approaches -- R. Boutalbi, L. Labiod, and M. Nadif: Latent Block Regression Model -- N. Chabane, M. Achraf Bouaoune, R. Amir Sofiane Tighilt, B. Mazoure, N. Tahiri, and V. Makarenkov: Using Clustering and Machine Learning Methods to Provide Intelligent Grocery Shopping Recommendations -- T. Chadjipadelis and S. Magopoulou: COVID-19 Pandemic: a Methodological Model for the Analysis of Government?s Preventing Measures and Health Data Records -- J. Champagne Gareau, É. Beaudry, and V. Makarenkov: pcTVI: Parallel MDP Solver Using a Decomposition into Independent Chains -- C. Di Nuzzo and S. Ingrassia: Three-way Spectral Clustering -- J. Dob?a and H. A. L. Kiers: Improving Classification of Documents by Semi-supervised Clustering in a Semantic Space -- J. Gama: Trends in Data Stream Mining -- L. A. García-Escudero, A. Mayo-Iscar, G. Morelli, and M. Riani: Old and New Constraints in Model Based Clustering -- V. G Genova, G. Giordano, G . Ragozini, and M. Prosperina Vitale: Clustering Student Mobility Data in 3-way Networks -- R. Giubilei: Clustering Brain Connectomes Through a Density-peak Approach -- T. Górecki, M. ?uczak, and P. Piasecki: Similarity Forest for Time Series Classification -- K. Hayashi, E. Hoshino, M. Suzuki, E. Nakanishi, K. Sakai, and M. Obatake: Detection of the Biliary Atresia Using Deep Convolutional Neural Networks Based on Statistical Learning Weights via Optimal Similarity and Resampling Methods -- Ch. Hennig: Some Issues in Robust Clustering -- J. Kalina and P. Janá£ek: Robustness Aspects of Optimized Centroids -- L. Labiod and M. Nadif: Data Clustering and Representation Learning Based on Networked Data -- Lazhar Labiod and Mohamed Nadif: Towards a Bi-stochastic Matrix Approximation of k-means and Some Variants -- A. LaLonde, T. Love, D. R. Young, and T. Wu: Clustering Adolescent Female Physical Activity Levels with an Infinite Mixture Model on Random Effects -- Á. López-Oriona, J. A. Vilar, and P. D?Urso: Unsupervised Classification of Categorical Time Series Through Innovative Distances -- D. Masís, E. Segura, J. Trejos, and A. Xavier: Fuzzy Clustering by Hyperbolic Smoothing -- R. Meng, H. K. H. Lee, and K. Bouchard: Stochastic Collapsed Variational Inference for Structured Gaussian Process Regression Networks -- H. Duy Nguyen, F. Forbes, G. Fort, and O. Cappé: An Online Minorization-Maximization Algorithm -- L. Palazzo and R. Ievoli: Detecting Differences in Italian Regional Health Services During Two Covid-19 Waves -- G. Panagiotidou and T. Chadjipadelis: Political and Religion Attitudes in Greece: Behavioral Discourses -- K. Pawlasová, I. Karafiátová, and J. Dvo?ák: Supervised Classification via Neural Networks for Replicated Point Patterns -- G. Perrone and G. Soffritti: Parsimonious Mixtures of Seemingly Unrelated Contaminated Normal Regression Models -- N. Pronello, R. Ignaccolo, L. Ippoliti, and S. Fontanella: Penalized Model-based Functional Clustering: a Regularization Approach via Shrinkage Methods -- D. Rodrigues, L. P. Reis, and B. M. Faria: Emotion Classification Based on Single Electrode Brain Data: Applications for Assistive Technology -- R. Scimone, A. Menafoglio, L. M. Sangalli, and P. Secchi: The Death Process in Italy Before and During the Covid-19 Pandemic: a Functional Compositional Approach -- O. Silva, Á. Sousa, and H. Bacelar-Nicolau: Clustering Validation in the Context of Hierarchical Cluster Analysis: an Empirical Study -- C. Silvestre, M. G. M. S. Cardoso, and M. Figueiredo: An MML Embedded Approach for Estimating the Number of Clusters -- Á. Sousa, O. Silva, M. Graça Batista, S. Cabral, and H. Bacelar-Nicolau: Typology of Motivation Factors for Employees in the Banking Sector: An Empirical Study Using Multivariate Data Analysis Methods -- J. Michael Spoor, J. Weber, and J. Ovtcharova: A Proposal for Formalization and Definition of Anomalies in Dynamical Systems -- N. Tahiri and A. Koshkarov: New Metrics for Classifying Phylogenetic Trees Using -means and the Symmetric Difference Metric -- S. D. Tomarchio: On Parsimonious Modelling via Matrix-variate t Mixtures -- G. Zammarchi, M. Romano, and C. Conversano: Evolution of Media Coverage on Climate Change and Environmental Awareness: an Analysis of Tweets from UK and US Newspapers. 330 $aThe contributions gathered in this open access book focus on modern methods for data science and classification and present a series of real-world applications. Numerous research topics are covered, ranging from statistical inference and modeling to clustering and dimension reduction, from functional data analysis to time series analysis, and network analysis. The applications reflect new analyses in a variety of fields, including medicine, marketing, genetics, engineering, and education. The book comprises selected and peer-reviewed papers presented at the 17th Conference of the International Federation of Classification Societies (IFCS 2022), held in Porto, Portugal, July 19?23, 2022. The IFCS federates the classification societies and the IFCS biennial conference brings together researchers and stakeholders in the areas of Data Science, Classification, and Machine Learning. It provides a forum for presenting high-quality theoretical and applied works, and promoting and fostering interdisciplinary research and international cooperation. The intended audience is researchers and practitioners who seek the latest developments and applications in the field of data science and classification. 410 0$aStudies in Classification, Data Analysis, and Knowledge Organization,$x2198-3321 606 $aArtificial intelligence$xData processing 606 $aMachine learning 606 $aData mining 606 $aMultivariate analysis 606 $aStatistics$xComputer programs 606 $aData Science 606 $aStatistical Learning 606 $aMachine Learning 606 $aData Mining and Knowledge Discovery 606 $aMultivariate Analysis 606 $aStatistical Software 606 $aIntel·ligència artificial$2thub 606 $aAprenentatge automàtic$2thub 606 $aMineria de dades$2thub 606 $aAnàlisi multivariable$2thub 608 $aLlibres electrònics$2thub 615 0$aArtificial intelligence$xData processing. 615 0$aMachine learning. 615 0$aData mining. 615 0$aMultivariate analysis. 615 0$aStatistics$xComputer programs. 615 14$aData Science. 615 24$aStatistical Learning. 615 24$aMachine Learning. 615 24$aData Mining and Knowledge Discovery. 615 24$aMultivariate Analysis. 615 24$aStatistical Software. 615 7$aIntel·ligència artificial. 615 7$aAprenentatge automàtic. 615 7$aMineria de dades. 615 7$aAnàlisi multivariable 676 $a005.7 700 $aBrito$b Paula$01459040 701 $aDias$b José G$01459041 701 $aLausen$b Berthold$01459042 701 $aMontanari$b Angela$0100774 701 $aNugent$b Rebecca$01459043 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK9 912 $a9910768481303321 996 $aClassification and Data Science in the Digital Age$93658465 997 $aUNINA LEADER 02274nam 2200517z- 450 001 9910557594403321 005 20211118 035 $a(CKB)5400000000043733 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/72931 035 $a(oapen)doab72931 035 $a(EXLCZ)995400000000043733 100 $a20202111d2019 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aIntegrative Toxicogenomics: Analytical Strategies to Amalgamate Exposure Effects With Genomic Sciences 210 $cFrontiers Media SA$d2019 215 $a1 online resource (112 p.) 225 1 $aFrontiers Research Topics 311 08$a2-88945-766-4 330 $aThis eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact 517 $aIntegrative Toxicogenomics 606 $aMedical genetics$2bicssc 606 $aScience: general issues$2bicssc 610 $abioinformatics 610 $achemicals 610 $aexposures 610 $aGene Expression 610 $agene regulatory network 610 $aintegration 610 $amode of action 610 $aNext-generation sequencing 610 $atoxicogenomics 610 $aToxicology 615 7$aMedical genetics 615 7$aScience: general issues 700 $aBushel$b Pierre R$4edt$01286914 702 $aTong$b Weida$4edt 702 $aBushel$b Pierre R$4oth 702 $aTong$b Weida$4oth 906 $aBOOK 912 $a9910557594403321 996 $aIntegrative Toxicogenomics: Analytical Strategies to Amalgamate Exposure Effects With Genomic Sciences$93019990 997 $aUNINA