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Management by Business Process : A Managerial Perspective of People, Process, and Technology
To support businesses managed through an organizational structure oriented by business processes, it is essential that the manager has a set of knowledge, technical skills, and professional demeanor. This text focuses on these aspects, presenting: a) the theoretical foundation, describing the central concepts of the M-B-BP approach; b) the set of necessary techniques from different areas, describing and exemplifying those skills; and c) the required behaviors of managers and employees for structuring, operation, management, and continuous improvement of the organization's business processes.
Machines, Computations, and Universality ; 5th International Conference, MCU 2007, Orleans, France, September 10-13, 2007, Proceedings
The 18 revised full papers presented together with nine invited papers cover Turing machines, register machines, word processing, cellular automata, tiling of the plane, neural networks, molecular computations, BSS machines, infinite cellular automata, real machines, and quantum computing.
Machines, Computations, and Universality ; 4th International Conference, MCU 2004, Saint Petersburg, Russia, September 21-24, 2004, Revised Selected Papers
Constitutes the post-proceedings of the 4th International Conference on Machines, Computations, and Universality, MCU 2004, held in St Petersburg, Russia in September 2004. This book covers a variety of foundational aspects in theoretical computer science such as cellular automata, molecular computing, quantum computing, and formal languages
Machine Learning Refined : Foundations, Algorithms, and Applications
Provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology.
Machine learning refined : Foundations, algorithms, and applications
Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization
Machine learning methods for reverse engineering of defective structured surfaces
Pascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces: parametrization of curves and surfaces, geometric primitive classification and inpainting of high-resolution textures. The proposed methods aim to improve the reconstruction quality while further automating the process. The contributions demonstrate that machine learning can be a viable part of the CAD reverse engineering pipeline.
Machine Learning in Document Analysis and Recognition
The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphicalcomponents of a document and to extract information. With ?rst papers dating back to the 1960’s, DAR is a mature but still gr- ing research?eld with consolidated and known techniques. Optical Character Recognition (OCR) engines are some of the most widely recognized pr- ucts of the research in this ?eld, while broader DAR techniques are nowadays studied and applied to other industrial and o?ce automation systems. In the machine learning community, one of the most widely known - search problems addressed in DAR is recognition of unconstrained handwr- ten characters which has been frequently used in the past as a benchmark for evaluating machine learning algorithms, especially supervised classi?ers.
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 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 Algorithms Using Python Programming
Presents the key concepts of Machine Learning which includes Python concepts and Interpreter, Foundation of Machine Learning, Data Pre-processing, Supervised Machine Learning, Unsupervised Machine Learning, Reinforcement Learning, Kernel Machine, Design and analysis of Machine Learning experiment and Data visualization. The theoretical concepts along with coding implementation are covered. This book aims to pursue a middle ground between a theoretical textbook and one that focuses on applications. The book concentrates on the important ideas in machine learning.
Logistics Systems Analysis
It has two new sections, a new appendix, and more than half a dozen new figures. A few references have also been added, Much of the new material is based on work , The financial support of the National Science Foundation and the Volvo Foundations Center of Excellence for the Future of Urban Transportation at U. C. Berkeley is also acknowledged. The new appendix presents the logic behind the traveling salesman and vehicle routing results used in Sec. 4. 2 to describe the transportation ope- tion; Chapter 4 is more self-contained as a result. New section 5. 6 int- duces and evaluates a general method that automatically translates the c- tinuum approximation recipes of Chapters 4 and 5 into discrete system designs. This closes a gap in previous editions. Other additions include an explanation of how to develop system designs that can efficiently acc- modate real-time control strategies to manage uncertainty (new section 4. 6. 3), and extensions of the many-to-many design ideas of Chap. 6
Logics in artificial intelligence ; 10th European Conference, JELIA 2006, Liverpool, UK, September 13-15, 2006, Proceedings
Constitutes the refereed proceedings of the 10th European Conference on Logics in Artificial Intelligence, JELIA 2006. The 34 revised full papers and 12 revised tool description papers presented together with 3 invited talks were carefully reviewed and selected from 96 submissions. The papers cover a range of topics within the remit of the Conference, such as logic programming, description logics, non-monotonic reasoning, agent theories, automated reasoning, and machine learning.
Logical foundations of computer science ; International Symposium, LFCS 2007, New York, NY, USA, June 4-7, 2007, Proceedings
Constitutes the refereed proceedings of the International Symposium on Logical Foundations of Computer Science, LFCS 2007, held in New York, NY, USA in June 2007. The volume presents 36 revised refereed papers that address all current aspects of logic in computer science.
Logical aspects of computational linguistics ; 4th International Conference, LACL 2001, Le Croisic, France, June 27-29, 2001, Proceedings
Structural Equations in Language Learning.- On the Distinction between Model-Theoretic and Generative-Enumerative Syntactic Frameworks.- Contributed Papers.- A Formal Definition of Bottom-Up Embedded Push-Down Automata and Their Tabulation Technique.- An Algebraic Approach to French Sentence Structure.- Deductive Parsing of Visual Languages.- Lambek Grammars Based on Pregroups.- An Algebraic Analysis of Clitic Pronouns in Italian.- Consistent Identification in the Limit of Any of the Classes k-Valued Is NP-hard.- Polarized Non-projective Dependency Grammars.- On Mixing Deduction and Substitution in Lambek Categorial Grammars.- A Framework for the Hyperintensional Semantics of Natural Language with Two Implementations.- A Characterization of Minimalist Languages.- of Speech Tagging from a Logical Point of View.- Transforming Linear Context-Free Rewriting Systems into Minimalist Grammars.- Recognizing Head Movement.- Combinators for Paraconsistent Attitudes.- Combining Syntax and Pragmatic Knowledge for the Understanding of Spontaneous Spoken Sentences.- Atomicity of Some Categorially Polyvalent Modifiers.
Logic for Programming, Artificial Intelligence, and Reasoning ; Vol. 3835 : 12th International Conference, LPAR 2005, Montego Bay, Jamaica, December 2-6, 2005, Proceedings
Constitutes the refereed proceedings of the 12th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR 2005. This book presents 46 revised papers with 3 abstracts, addressing issues in logic programming, logic-based program manipulation, formal method, automated reasoning, and various kinds of AI logics.
Logic for Programming, Artificial Intelligence, and Reasoning ; Vol. 3452 : 11th International Workshop, LPAR 2004, Montevideo, Uruguay, March 14-18, 2005, Proceedings
Contains the papers presented at the 11th International Conference on Logic for Programming, Arti'cial Intelligence, and Reasoning (LPAR), held from March 14 to 18, 2005, in Montevideo, Uruguay, together with the 5th - ternational Workshop on the Implementation of Logics (organized by Stephan Schulz and Boris Konev) and the Workshop on Analytic Proof Systems (or- nized by Matthias Baaz). The call for papers attracted 77 paper submissions, each of which was - viewed by at least three expert reviewers. The ?nal decisions on the papers were taken during an electronic Program Committee meeting held on the Internet. The Internet-based submission, reviewing, and discussion software EasyChair, provided by the second PC co-chair, supported each stage of the reviewing p- cess.
Logic for Programming, Artificial Intelligence, and Reasoning ; 15th International Conference, LPAR 2008, Doha, Qatar, November 22-27, 2008. Proceedings
This book constitutes the refereed proceedings of the 15th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR 2008, which took place in Doha, Qatar, during November 22-27, 2008.The 45 revised full papers presented together with 3 invited talks were carefully revised and selected from 153 submissions. The papers address all current issues in automated reasoning, computational logic, programming languages and their applications and are organized in topical sections on automata, linear arithmetic, verification knowledge representation, proof theory, quantified constraints, as well as modal and temporal logics.
Logic for programming, artificial intelligence, and reasoning ; 14th International Conference, LPAR 2007, Yerevan, Armenia, October 15-19, 2007, Proceedings
This book constitutes the refereed proceedings of the 14th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR 2007, held in Yerevan, Armenia.
Logic for Programming, Aritficial Intelligence, and Reasoning ; 13th International Conference, LPAR 2006, Phnom Penh, Cambodia, November 13-17, 2006, Proceedings
This book constitutes the refereed proceedings of the 13th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR 2006, held in Phnom Penh, Cambodia in November 2006. The 38 revised full papers presented together with one invited talk were carefully reviewed and selected from 96 submissions.
