الصفحة 19
الصفحة 19
Mathematical foundations of computer science 2006 ; 31st International Symposium, MFCS 2006, Stará Lesná, Slovakia, August 28-September 1, 2006, Proceedings
This book constitutes the refereed proceedings of the 31st International Symposium on Mathematical Foundations of Computer Science, MFCS 2006, held in Stará Lesná, Slovakia in August/September 2006. The 62 revised full papers presented together with the full papers or abstracts of 7 invited talks were carefully reviewed and selected from 174 submissions. All current aspects in theoretical computer science and its mathematical foundations are addressed, ranging from algorithms and data structures, to complexity, automata, semantics, logic, formal specifications, models of computation, concurrency theory, computational geometry, parallel and distributed computing, networks, bioinformatics, quantum computing, cryptography, knowledge-based systems, and artificial intelligence.
Mathematical Foundations of Computer Science 2005 ; 30th International Symposium, MFCS 2005, Gdansk, Poland, August29-September 2. 2005, Proceedings
Constitutes the proceedings of the 30th International Symposium on Mathematical Foundations of Computer Science, MFCS 2005, held in Gdansk, Poland in August/September 2005. The 62 papers address various aspects in theoretical computer science, ranging from quantum computing, approximation, automata, circuits, scheduling, games, and more.
Matematica generale con il calcolatore
By introducing mathematical objects, it teaches students how to use a computer to perform numerical and symbolic calculations, define a function and calculate its values, plot and explore graphs, and execute simple algorithms. The course is rich in examples, applications, and models, drawn from economics, physics, biology, statistics, and mathematics itself. The analysis of these models constitutes, in a certain sense, the true purpose of the mathematical theory covered. Automatic calculation tools (mathematics software, spreadsheets) are used extensively to explore and illustrate concepts and properties. Mathcad® software, in particular, was used, both as a calculation tool and as a simple yet powerful programming language. Considerable space is devoted to approximation, emphasizing the distinction between numerical and symbolic calculation; to algorithms as a synthesis of the syntactic and semantic aspects of mathematical objects; and to computer simulation, interpreted as a "physical" experiment and a source of conjecture. The ability to use a calculator marks a sort of "democratization" of mathematics: even complex results, which have always required a broad background of knowledge and laborious calculations, are now quickly accessible to anyone who understands the meaning of mathematical objects and knows how to use the syntax.
Marswalk One : First Steps on a New Planet
MARSWALK ONE: First Steps on a New Planet addresses the question of why we should embark on a journey to Mars, documenting what the first human crew will do when they place their feet in the red dust of the planet. The book also addresses why we need to carry out these tasks and, more importantly, what a human crew could achieve that an automated mission could not. Understanding the clear benefits of sending a human crew to the surface of Mars, and how these benefits can be seen back on Earth, is the key to sustained long-term public and political support for the programme in terms of cash and commitment. The book accepts that the journey will be made, but does not specify precisely when. Flight time, and how to get to and from the planet are discussed briefly, to understand why the suggested duration spent at Mars is reasonable. The main objective of the work is to look at what science will be done on the surface – supported by orbital operations – and what hardware and technology will be employed to achieve the mission objectives. This analysis is drawn from previous experiences in manned and unmanned space programmes, including Apollo, Skylab, Salyut/Mir, Shuttle and ISS, Viking, Luna/Lunokhod, and recent Mars missions such as Pathfinder and Global Surveyor.
Marketing analytics : A machine learning approach
Gives a comprehensive overview of marketing analytics, incorporating machine learning methods of data analysis that automates analytical model building. The volume covers the important aspects of marketing analytics, including segmentation and targeting analysis, statistics for marketing, marketing metrics, consumer buying behavior, neuromarketing techniques for consumer analytics, new product development, forecasting sales and price, web and social media analytics, and much more.
Manufacturing Systems Control Design : A Matrix-based Approach
The matrix-based approach presented here is a solution to the real-time application of control in discrete event systems and flexible manufacturing systems (FMS), and offers a sound practical basis for the design of controllers for manufacturing systems.
Manufacturing Systems and Technologies for the New Frontier ; The 41st CIRP Conference on Manufacturing Systems May 26–28, 2008, Tokyo, Japan
Manufacturing systems and technology stand on a new frontier, facing up to the challenges posed by the ever-evolving requirements of global sustainability. Value-creation is taking its place alongside more traditional production-process priorities. Collected here are over a hundred papers concerned with all manner of new directions in manufacturing systems and given at the 41st CIRP Conference on Manufacturing Systems. The high-quality material presented in this volume includes reports of work from both scientific and engineering standpoints and several invited and keynote papers addressing the current cutting edge and likely future trends in manufacturing systems.
Managing Agile Business Technology : The Business and Technology Relationship Model in Practice
Describes in detail how the BTRM, combined with a focus on value creation and value delivery, will enable continuous change, in the context of current, emerging and future technologies. It illustrates the potential for real-time insight and control not previously considered and provides a wide range of information to plan an implementation, understand where AI can be applied, and its importance in the world of self-managing systems.
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
