Автор: Tigabu Degu Getahun Название: Industrial Clustering, Firm Performance and Employee Welfare: Evidence from the Shoe and Flower Cluster in Ethiopia ISBN: 3631667442 ISBN-13(EAN): 9783631667446 Издательство: Peter Lang Рейтинг: Цена: 71900.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The author examines the productivity, profitability and welfare effects of industrial clustering and a public policy promoting industrial clusters in Ethiopia. He uses reliable counterfactuals as well as original enterprise and worker level data. By investigating the effect of firm, time, entrepreneur and site specific factors as well as endogenous location choice issues, the author finds strong evidence for the existence of significant agglomeration economies in the Ethiopia leather footwear cluster. Using primary survey data collected from firms which benefited from the cluster policy and those that did not, both before and after the implementation of the policy, the author shows the unintended negative impact of a cluster prompting policy in Ethiopia. The book is essential reading for those who are interested in the gender and welfare impact of female full time labor force participation in industrial jobs.
Автор: Hermann Moisl Название: Cluster Analysis for Corpus Linguistics ISBN: 3110350254 ISBN-13(EAN): 9783110350258 Издательство: Walter de Gruyter Цена: 128870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The standard scientific methodology in linguistics is empirical testing of falsifiable hypotheses. As such the process of hypothesis generation is central, and involves formulation of a research question about a domain of interest and statement of a hypothesis relative to it. In corpus linguistics the domain is text, and generation involves abstraction of data from text, data analysis, and formulation of a hypothesis based on inference from the results. Traditionally this process has been paper-based, but the advent of electronic text has increasingly rendered it obsolete both because the size of digital corpora is now at or beyond the limit of what can efficiently be used in the traditional way, and because the complexity of data abstracted from them can be impenetrable to understanding. Linguists are increasingly turning to mathematical and statistical computational methods for help, and cluster analysis is such a method. It is used across the sciences for hypothesis generation by identification of structure in data which are too large or complex, or both, to be interpretable by direct inspection. This book aims to show how cluster analysis can be used for hypothesis generation in corpus linguistics, thereby contributing to a quantitative empirical methodology for the discipline.
Автор: Braunerhjelm, Pontus; Feldman, Maryann P. Название: Cluster Genesis ISBN: 0199232202 ISBN-13(EAN): 9780199232208 Издательство: Oxford Academ Рейтинг: Цена: 51210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Clusters - regional concentrations of related firms and organizations - are seen as an important element of economic growth and innovation. But there is little understanding of how clusters come into existence, and little guidance provided on the role of policies in promoting this. Cluster Genesis focuses on these early origins of clusters.
Автор: Daniel N. Allen; Gerald Goldstein Название: Cluster Analysis in Neuropsychological Research ISBN: 1461467438 ISBN-13(EAN): 9781461467434 Издательство: Springer Рейтинг: Цена: 81050.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book reviews the basics of cluster analysis, examines challenges to its use and applies its methods to neuropsychological research. It examines how behaviorally based subgroups within clinical entities can be related to various other neuroscience methods.
Автор: Abonyi JГЎnos, Feil BalГЎzs Название: Cluster Analysis for Data Mining and System Identification ISBN: 3764379871 ISBN-13(EAN): 9783764379872 Издательство: Springer Рейтинг: Цена: 93130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents new approaches to data mining and system identification. Algorithmsthat can be used for the clustering of data have been overviewed. New techniques andtools are presented for the clustering, classification, regression and visualization ofcomplex datasets. Special attention is given to the analysis of historical process data,tailored algorithms are presented for the data driven modeling of dynamical systems,determining the model order of nonlinear input-output black box models, and thesegmentation of multivariate time-series. The main methods and techniques areillustrated through several simulated and real-world applications from data mining andprocess engineering practice.The books is aimed primarily at practitioners, researches, and professionals in statistics,data mining, business intelligence, and systems engineering, but it is also accessible tograduate and undergraduate students in applied mathematics, computer science, electricaland process engineering. Familiarity with the basics of system identification and fuzzysystems is helpful but not required.
Автор: Slawomir Wierzcho?; Mieczyslaw A. K?opotek Название: Modern Algorithms of Cluster Analysis ISBN: 3319693077 ISBN-13(EAN): 9783319693071 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides the reader with a basic understanding of the formal concepts of the cluster, clustering, partition, cluster analysis etc. The book explains feature-based, graph-based and spectral clustering methods and discusses their formal similarities and differences. Understanding the related formal concepts is particularly vital in the epoch of Big Data; due to the volume and characteristics of the data, it is no longer feasible to predominantly rely on merely viewing the data when facing a clustering problem. Usually clustering involves choosing similar objects and grouping them together. To facilitate the choice of similarity measures for complex and big data, various measures of object similarity, based on quantitative (like numerical measurement results) and qualitative features (like text), as well as combinations of the two, are described, as well as graph-based similarity measures for (hyper) linked objects and measures for multilayered graphs. Numerous variants demonstrating how such similarity measures can be exploited when defining clustering cost functions are also presented. In addition, the book provides an overview of approaches to handling large collections of objects in a reasonable time. In particular, it addresses grid-based methods, sampling methods, parallelization via Map-Reduce, usage of tree-structures, random projections and various heuristic approaches, especially those used for community detection.
Автор: S. Miyamoto Название: Fuzzy Sets in Information Retrieval and Cluster Analysis ISBN: 9048140676 ISBN-13(EAN): 9789048140671 Издательство: Springer Рейтинг: Цена: 214290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The present monograph intends to establish a solid link among three fields: fuzzy set theory, information retrieval, and cluster analysis.
Автор: Daniel N. Allen; Gerald Goldstein Название: Cluster Analysis in Neuropsychological Research ISBN: 1489998632 ISBN-13(EAN): 9781489998637 Издательство: Springer Рейтинг: Цена: 81050.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book reviews the basics of cluster analysis, examines challenges to its use and applies its methods to neuropsychological research. It examines how behaviorally based subgroups within clinical entities can be related to various other neuroscience methods.
Автор: Allan Donner, Neil Klar Название: Design and Analysis of Cluster Randomization Trials in Health Research ISBN: 0470711000 ISBN-13(EAN): 9780470711002 Издательство: Wiley Рейтинг: Цена: 67530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A cluster randomization trial is one in which intact social units, or clusters of individuals, are randomized to different intervention groups.
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