الصفحة 32
الصفحة 32
Management divided : Contradictions of labor management
One of the central dynamics shaping organizations is a contradiction managers face between ensuring workforce discipline and harnessing worker creativity. In this rich study of American manufacturing, Matt Vidal offers a theory of 'organizational political economy', integrating concepts from organization theory into a classical Marxist framework
Making European Merger Policy More Predictable
Making European Merger Policy More Predictable analyses European Merger Control with regard to its capacity to generate predictability among the concerned parties. Starting from the premise that predictability is of overwhelming importance for the functioning of market economies, Voigt and Schmidt ask to what degree European Merger Control has been predictable over the last couple of years. The authors show both theoretically and empirically that there have been serious shortcomings with regard to the predictability of competition policy. They identify the insufficient recognition of the consequences of globalization on the competitive processes as well as an often inconsistent application of economic theory as the root causes for the lack of predictability. The inconsistent application of economic theory is particularly relevant with regard to potential competition and the evaluation of collective dominance. The authors generate a substantial number of proposals that could help to improve predictability. On this basis, Voigt and Schmidt critically assess the recent reforms of European Merger Control.
Making Beautiful Deep-Sky Images : Astrophotography with Affordable Equipment and Software
Professor Greg Parker's astronomical photographs are widely known for their excellence, and a selection of them has recently been shown as a public exhibition in the UK. In Making Beautiful Deep-Sky Images, he provides a detailed account of how spectacular deep-sky images can be taken by amateur astronomers using CCD cameras, and how they can subsequently be processed and enhanced in the "electronic darkroom" for maximum beauty and impact. Quite simply, this is a "how to do it" book for people who want to make stunning astronomical pictures.
Machine learning for cyber-physical systems: selected papers from the international conference ML4CPS 2023
Contains selected papers from the international conference ML4CPS – Machine Learning for Cyber-Physical Systems, which was held in Hamburg (Germany), from 29 to 31 March 2023. Cyber-physical systems are adaptive and learning: they analyze their environment and, based on observations, learn patterns, associations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnostics. Machine learning is the key technology for these developments.
Machine Learning for Cyber Physical Systems : Selected papers from the International Conference ML4CPS 2018
Presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.
Machine learning challenges : Evaluating predictive uncertainty, Visual Object Classification, and Recognizing Textual Entailment, 1st Pascal Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, Revised Selected Papers
Constitutes the refereed post-proceedings of the First PASCAL Machine Learning Challenges Workshop, MLCW 2005. 25 papers address three challenges: finding an assessment base on the uncertainty of predictions using classical statistics, Bayesian inference, and statistical learning theory; second, recognizing objects from a number of visual object classes in realistic scenes; third, recognizing textual entailment addresses semantic analysis of language to form a generic framework for applied semantic inference in text understanding.
Machine Learning Approaches in Cyber Security Analytics
Introduces various machine learning methods for cyber security analytics. With an overwhelming amount of data being generated and transferred over various networks, monitoring everything that is exchanged and identifying potential cyber threats and attacks poses a serious challenge for cyber experts. Further, as cyber attacks become more frequent and sophisticated, there is a requirement for machines to predict, detect, and identify them more rapidly. Machine learning offers various tools and techniques to automate and quickly predict, detect, and identify cyber attacks.
Machine learning and deep learning in medical data analytics and healthcare applications
Introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments.
Machine learning and data mining for sports analytics ; 7th international workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings
Constitutes the refereed post-conference proceedings of the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020, in Ghent, Belgium, in September 2020. The 11 papers presented were carefully reviewed and selected from 22 submissions. The papers present a variety of topics within the area of sports analytics, including tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation.
Machine learning and big data : Concepts, algorithms, tools and applications
Showcase novel use-cases and applications, present empirical research results from user-centered qualitative and quantitative experiments of these new applications, and facilitate a discussion forum to explore the latest trends in big data and machine learning by providing algorithms which can be trained to perform interdisciplinary techniques such as statistics, linear algebra, and optimization and also create automated systems that can sift through large volumes of data at high speed to make predictions or decisions without human intervention
Machine Learning : The Basics
Approaches ML as the computational implementation of the scientific principle. This principle consists of continuously adapting a model of a given data-generating phenomenon by minimizing some form of loss incurred by its predictions. Trains readers to break down various ML applications and methods in terms of data, model, and loss, thus helping them to choose from the vast range of ready-made ML methods.
Lung Pathology
Learning the diagnostic elements of lung pathology requires not only great familiarity with a wide diversity of cases, but also a sharp eye for analyzing pictorial images. In Lung Pathology: A Consultative Atlas, leading experts offer a novel and substantive approach to the teaching of pulmonary pathology. Drawing on 263 challenging, yet exemplary, referral cases taken from files collected over 20 years by internationally renowned lung pathologist, Dr. Eugene Mark, the authors introduce his state-of-the-art approach to the interpretation of pulmonary pathology. This text includes the primary and/or differential diagnosis and the pertinent histological features of each case, as well as clinical history, when available. Key words or phrases in the text are highlighted and digitally hyperlinked to associated images or regions of interest within those images to assist the readers in their correlation. Novel and user friendly, Lung Pathology: A Consultative Atlas describes a cutting-edge diagnostic approach to pulmonary pathology, describing its principles and demonstrating its application in text and full-color illustrations drawn from 263 difficult cases of human lung pathologies.
Location, Transport and Land-Use : Modelling Spatial-Temporal Information
Shows the use of statistical tools for forecasting and analyzing implications of land-use decisions. The idea is that la- use on a map is necessarily a consequence of individual, and often conflicting, siting decisions over time.
Local anesthesia in dentistry : A locoregional approach
Provides comprehensive coverage of all aspects of local anesthetics, including anatomic considerations, pharmacology, armamentarium, injection techniques, indications, contraindications, complications, novel anesthetics formulations, and more.
Living with Disfigurement in Early Medieval Europe
Examines social and medical responses to the disfigured face in early medieval Europe, arguing that the study of head and facial injuries can offer a new contribution to the history of early medieval medicine and culture, as well as exploring the language of violence and social interactions. Despite the prevalence of warfare and conflict in early medieval society, and a veritable industry of medieval historians studying it, there has in fact been very little attention paid to the subject of head wounds and facial damage in the course of war and/or punitive justice. The impact of acquired disfigurement —for the individual, and for her or his family and community—is barely registered, and only recently has there been any attempt to explore the question of how damaged tissue and bone might be treated medically or surgically..
Lived Nation as the History of Experiences and Emotions in Finland, 1800-2000
It revolves around the following questions: What kinds of experiences have engendered national mobilization and feelings of national belonging? How have political and societal conflicts turned into new communities of experience and emotion? What kinds of experiences have been integrated into, or excluded from, the national context in different instances? How have people internalized or contested the nation as a context for their personal, family and minority-group experiences? In what ways has the nation entered and affected people’s intimate spheres of life? How have “national” experiences been transmitted to children in the renewal of the nation? This edited collection points to the histories of experience and emotions as a novel way of studying nations and nationalism. Building on current debates in nationalism studies, it offers a theoretical framework for analyzing the historical construction of “lived nations,” and introduces a number of new methodological approaches to understand the experiences of the nation, extending from the investigation of personal reminiscences and music records to the study of dreams and children’s drawings.
Liquidity, markets and trading in action : An interdisciplinary perspective
This book addresses four standard business school subjects: microeconomics, macroeconomics, finance and information systems as they relate to trading, liquidity, and market structure. It provides a detailed examination of the impact of trading costs and other impediments of trading that the authors call “frictions”. It also presents an interactive simulation model of equity market trading, TraderEx, that enables students to implement trading decisions in different market scenarios and structures. Addressing these topics shines a bright light on how a real-world financial market operates, and the simulation provides students with an experiential learning opportunity that is informative and fun.
Linked Democracy : Foundations, Tools, and Applications
This book shows the factors linking information flow, social intelligence, rights management and modelling with epistemic democracy, offering licensed linked data along with information about the rights involved. This model of democracy for the web of data brings new challenges for the social organisation of knowledge, collective innovation, and the coordination of actions. Licensed linked data, licensed linguistic linked data, right expression languages, semantic web regulatory models, electronic institutions, artificial socio-cognitive systems are examples of regulatory and institutional design (regulations by design). The web has been massively populated with both data and services, and semantically structured data, the linked data cloud, facilitates and fosters human-machine interaction. Linked data aims to create ecosystems to make it possible to browse, discover, exploit and reuse data sets for applications. Rights Expression Languages semi-automatically regulate the use and reuse of content.
Linearity, Symmetry, and Prediction in the Hydrogen Atom
The predictive power of mathematics in quantum phenomena is one of the great intellectual successes of the 20th century. This textbook, aimed at undergraduate or graduate level students (depending on the college or university), concentrates on how to make predictions about the numbers of each kind of basic state of a quantum system from only two ingredients: the symmetry and the linear model of quantum mechanics. This method, involving the mathematical area of representation theory or group theory, combines three core mathematical subjects, namely, linear algebra, analysis and abstract algebra. Wide applications of this method occur in crystallography, atomic structure, classification of manifolds with symmetry, and other areas.
Linear Selection Indices in Modern Plant Breeding
This open access book focuses on the linear selection index (LSI) theory and its statistical properties. It addresses the single-stage LSI theory by assuming that economic weights are fixed and known - or fixed, but unknown - to predict the net genetic merit in the phenotypic, marker and genomic context. Further, it shows how to combine the LSI theory with the independent culling method to develop the multistage selection index theory. The final two chapters present simulation results and SAS and R codes, respectively, to estimate the parameters and make selections using some of the LSIs described. It is essential reading for plant quantitative geneticists, but is also a valuable resource for animal breeders.
