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The Universal Decimal Classification (UDC) is a documentary language used for information representation and retrieval in most libraries in the Western world, particularly in Portugal. This classification language has two purposes: (i) to represent and categorize the subjects of the documents that integrate the collections and, in some cases, (ii) to physically arrange those documents. This work aims to be a guide for the application and use of the UDC and to help understanding its theoretical foundations. The theoretical and practical dimension of this work and its didactic discourse make it an important text for both Information Science students and professionals. This work is structured in three parts: Part I: About the UDC principles; Part II: Structure of UDC; And Part III: UDC Main Classes. Part I, purely theoretical, defines the CDU as a documentary language, addresses its origin, contextualizes it, and refers to its main functions. In a theoretical dimension, this first part refers to the general foundations and characteristics that distinguish this documentary language from other controlled vocabularies. In Part II, the structure of the CDU is analyzed in a more theoretical-practical perspective: (i) the index and its function; (Ii) the notation and its characteristics; (Iii) Auxiliary Tables, their typology, function and characteristics, as well as the signs that identify them; And (iv) the Main Tables, their characteristics and functions. In Part III, each of the classes of the Main Tables is analyzed individually. To this purpose, a common structure was used to study each class. The practical dimension of this manual gains expression with the exercises that are proposed at the end of each class, offering students and professionals the opportunity to solidify their learning and to check their results through the solutions found at the end of the book.

Bibliographic classifications --- Universal Decimal Classification --- manual

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Critique et constructif à la fois, l'ouvrage critique le traitement classique des classifications dualistes (droite/gauche, masculin/féminin, noir/blanc, pur/impur...) et présente une perspective nouvelle à partir d'un exemple ethnographique africain très développé emprunté aux Nyamwezi et d'une reconsidération de cas classiques (africains, chinois, nord-américains). Dans l'essai de Robert Hertz au début de ce siècle, et de façon plus rigide encore de nos jours chez Rodney Needham et ses associés, le système classificatoire d'une société, si éloignée soit-elle du type moderne, est vu dans des catégories logiques qui relèvent de la pensée classique et moderne : non-contradiction, égalité des termes, rationalité du discours linéaire. On n'aboutit ainsi à des listes dichotomiques qu'arbitrairement et moyennant de nombreuses contradictions. A cette logique atomique Serge Tcherkézoff oppose une logique du tout, une logique hiérarchique qui, d'une part, privilégie le système idéologique et rituel global, de l'autre, se caractérise par la distinction de niveaux de représentation et d'expérience dont la gradation tolère et même prescrit la contrariété. A une plate dichotomie est ainsi substituée une figure multidimensionnelle, épaisse, vivante, dont l'unité est en même temps vigoureusement affirmée.

classification primitive --- Nyamwezi --- peuple africain --- anthropologie

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Big data is revolutionizing our ability to measure and study the human brain. New technology increases the resolution of images that are being study as well as enables researchers to study the brain as it functions. These technological advances are combined with efforts to collect neuroimaging data on large numbers of subjects, in some cases longitudinally. This combination of advances in measurement and scope of studies requires novel development in the statistical analysis. Fast, scalable, robust and accurate models and approaches need to be developed to make headway on these problems. This volume represents a unique collection of researchers providing deep insights on the statistical analysis of big neuroimaging data.

big data --- Neuroscience --- fMRI --- EEG --- MEG --- functional connectivity --- Classification --- prediction

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In this work, different methods for material classification by hyperspectral images in the near infrared range are investigated. Specifically, the design of problem-adapted camera systems and the choice of optimal optical filters are discussed. In addition, a method for the fusion of multiple camera signals by spectral unmixing is presented.

Sichtprüfung, hyperspektral, Inspektionssystem, Klassifikation, Materialvisual inspection, hyperspectral, material, classification

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In 2007, Jeremy Jass proposed a molecular classification of colorectal cancer including KRAS, BRAF, Mismatch Repair, CIMP and MGMT Status. Since then, many prognostic and predictive studies have been published on this topic, mainly focusing on one single molecular marker. The aim of the e-book is to summarize the knowledge in 2014 from a multidisciplinary point of view that can potentially be used as a manual by CRC researchers in every field.

colorectal cancer --- Molecular classification --- Cdx2 --- Wnt Signaling Pathway --- MGMT --- telomere length --- ras signaling pathway --- microRNA