الصفحة 47
الصفحة 47
Making Ammonia : Fritz Haber, Walther Nernst, and the Nature of Scientific Discovery
This book discusses the progress of science and the transfer of scientific knowledge to technological application. It also identifies the factors necessary to achieve this progress. Based on a case study of the physical chemist Fritz Haber's discovery of ammonia synthesis between 1903 and 1909, the book places Haber's work in historical and scientific (physicochemical) context. The scientific developments of the preceding century are framed in a way that emphasizes the confluence of knowledge needed for Haber's success. Against this background, Haber's work is presented in detail along with the indispensable contributions of his colleague, the physical chemist, Walter Nernst, and their assistants. The detailed accounts of scientific advancement remind us of the physical basis on which our scientific theories and ideas are built. Without this reminder we often forget how complex, and how beautiful achievements in science can be.
Magneto-Fluid Dynamics : Fundamentals and Case Studies of Natural Phenomena
Concerns the generation of electric currents and of electric space charges inside conducting media that move in magnetic fields. The authors postulate nothing but the Maxwell equations. They discuss at length the disk dynamo, which serves as a model for the natural self-excited dynamos that generate magnetic fields such as that of sunspots. There are 36 Examples and 13 Case Studies. The Case Studies concern solar phenomena -- magnetic elements, sunspots, spicules, coronal loops -- and the Earth's magnetic field.
Magnesium Technology : Metallurgy, Design Data, Applications
Magnesium, with a density of 1.74 g/cm², is the lightest structural metal and magnesium are increasingly chosen for weight-critical applications such as in land-based transport systems. "Magnesium Technology" substantially updates and complements existing reference sources on this key material. It assembles international contributions from seven countries covering a wide range of research programs into new alloys with the requisite property profiles, i.e., the current state of both research and technological applications of magnesium. In particular, the international team of authors covers key topics, such as: casting and wrought alloys; fabrication methods; corrosion and protection; engineering requirements and strategies, with examples from the automobile, aerospace, and consumer-goods industries, and recycling.
Magnesium Injection Molding
Injection molding of metallic alloys is a modern and environment-friendly technology with universal features, capable of implementing many conventional and novel processing methods based on semisolid and liquid routes. After its application to magnesium and recent commercialization, it is used to manufacture millions of light-weight, fully-recyclable components for various markets, including consumer electronics housings, automotive parts, sporting goods, household devices and office equipment.
Made by James : The Honest Guide to Creativity and Logo Design
Includes: Annotated case studies that follow designs from concept to completion The advantages of a hands-on, human approach to design The value of personal and career growth, and how to enjoy the journey of improvement Effective work habits that can make you more efficient, productive, and satisfied
Macroeconomics of Monetary Union
This book, unlike other books, provides readers with a practical yet sophisticated grasp of the macroeconomic principles necessary to understand a monetary union. By definition, a monetary union is a group of countries that share a common currency. The most important case in point is the Euro area. Policy makers are the central bank, national governments, and national labour unions. Policy targets are price stability and full employment. Policy makers follow cold-turkey or gradualist strategies. Policy decisions are taken sequentially or simultaneously. The countries can differ in size or behaviour. Policy expectations are adaptive or rational. To illustrate all of this there are numerical simulations of monetary policy, fiscal policy, and wage policy.
Macroeconomic modelling of R&D and innovation policies
This book encompasses a collection of in-depth analyses showcasing the challenges and ways forward for macroeconomic modelling of R&D and innovation policies. Based upon the proceedings of the EC-DG JRC-IEA workshop held in Brussels in 2017, it presents cutting-edge contributions from a number of leading economists in the field. It provides a comprehensive overview of the current academic and policy challenges surrounding R&D as well as of the state-of-the-art modelling techniques.
Machine-learning-assisted intelligent processing and optimization of complex systems
Focuses on the most recent developments in intelligent optimization methods and their applications in various test cases. The reprint covers various topics, including distributed multiagent modeling, metaheuristic algorithms, multisource data fusion, mobile computing and mobile sensing, machine learning-based intelligent processing for modeling complex manufacturing systems, and data-driven intelligent modeling
Machine Learning: ECML 2006 ; 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings
This book constitutes the refereed proceedings of the 17th European Conference on Machine Learning, ECML 2006, held in Berlin, Germany in September 2006, jointly with PKDD 2006. The 46 revised full papers and 36 revised short papers presented together with abstracts of 5 invited talks were carefully reviewed and selected from 564 papers submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning.
Machine Learning Techniques for Multimedia : Case Studies on Organization and Retrieval
This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains .
Machine Learning Techniques and Analytics for Cloud Security
covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions
Machine Learning for Computer Scientists and Data Analysts: From an Applied Perspective
Describes traditional as well as advanced machine learning algorithms / Enables students to learn which algorithm is most appropriate for the data being handled / Includes numerous, practical case-studies; implementation codes in Python available for readers
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 Applications in Civil Engineering
Discusses machine learning and deep learning models for different civil engineering applications. These models work for stochastic methods wherein internal processing is done using randomized prototypes. The book explains various machine learning model designs that will assist researchers to design multi domain systems with maximum efficiency. It introduces Machine Learning and its applications to different Civil Engineering tasks, including Basic Machine Learning Models for data pre-processing, models for data representation, classification models for Civil Engineering Applications, Bioinspired Computing models for Civil Engineering, and their case studies.
Machine Learning and Probabilistic Graphical Models for Decision Support Systems
Presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.
Machine Learning and Knowledge Discovery in Databases ; European Conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part II
Constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008.The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer.
Machine Learning and Knowledge Discovery in Databases ; European Conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I
Constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008.The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer.
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 : ECML 2005 ; 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings
The European Conference on Machine Learning (ECML) and the European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) were jointly organized this year for the ?fth time in a row, after some years of mutual independence before. After Freiburg (2001), Helsinki (2002), Cavtat (2003) and Pisa (2004), Porto received the 16th edition of ECML and the 9th PKDD in October 3–7. Having the two conferences together seems to be working well: 585 di?erent paper submissions were received for both events, which maintains the high s- mission standard of last year. Of these, 335 were submitted to ECML only, 220 to PKDD only and 30 to both. Such a high volume of scienti?c work required a tremendous e?ort from Area Chairs, Program Committee members and some additional reviewers. On average, PC members had 10 papers to evaluate, and Area Chairs had 25 papers to decide upon. We managed to have 3 highly qualified independent reviews per paper (with very few exceptions) and one additional overall input from one of the Area Chairs. After the authors’ responses and the online discussions for many of the papers, we arrived at the ?nal selection of 40 regular papers for ECML and 35 for PKDD. Besides these, 32 others were accepted as short papers for ECML and 35 for PKDD. This represents a joint acceptance rate of around 13% for regular papers and 25% overall.
