الصفحة 7
الصفحة 7
Computer organization and design : The hardware / software interface ; 6th ed.
Designed to be used in modern computing environments such as cloud computing, mobile devices, and other embedded systems. With the post-PC era now upon us, Computer Organization and Design moves forward to explore this generational change with examples, exercises, and material highlighting the emergence of mobile computing and the Cloud. Updated content featuring tablet computers, Cloud infrastructure, and the x86 (cloud computing) and ARM (mobile computing devices) architectures is included
Computer Network Security ; Vol. 3685
This volume contains papers presented at the 3rd International Workshop on Mathematical Methods, Models and Architectures for Computer Network - curity (MMM-ACNS 2005) held in St. Petersburg, Russia, 2005. The 1st and the 2nd International Workshops on Mathematical Methods, Models and Architectures for Computer Network Security (MMM-ACNS 2001 and MMM-ACNS 2003), hosted by the St. Petersburg Institute for Informatics and Automation, demonstrated the keen interest of the international research community in the subject area. It was recognized that conducting a biannual series of such workshops in St. Petersburg stimulates fruitful exchanges between the di?erent schools of thought, facilitates the dissemination of new ideas and promotesthespirit of cooperationbetweenresearchersontheinternationalscale. MMM-ACNS 2005 provided an international forum for sharing original - search results and application experiences among specialists in fundamental and applied problems of computer network security. An important distinction of the workshop was its focus on mathematical aspects of information and computer network security addressing the ever-increasing demands for secure computing and highly dependable computer networks.
Computer Network Security ; 4th International Conference on Mathematical Methods, Models and Architectures for Computer Network Security, MMM-ACNS 2007, St. Petersburg, Russia, September 13-15, 2007, Proceedings
This volume focus on mathematical aspects of information and computer network security addressing the ever-increasing demands for secure computing and highly dependable computer networks.
Computer Algebra in Scientific Computing ; Vol. 4194 ; 9th International Workshop, CASC 2006, Chisinau, Moldova, September 11-15, 2006, Proceedings
This volume contains revised versions of the papers submitted to the workshop by the participants and accepted by the program committee after a thorough reviewing process. The collection of papers included in the proceedings covers not only various expanding applications of computer algebra to scienti?c computing but also the computer algebra systems themselves and the CA algorithms.
Computer algebra in scientific computing ; Vol. 3718 ; 8th International workshop, CASC 2005, Kalamata, Greece, September 12-16, 2005, Proceedings
This volume contains the proceedings of the CASC 2005 continued a tradition — started in 1998 — of international con-ferences on the latest advances in the application of computer algebra systems(CASs) and methods to the solution of various problems in scientific computing.The methods of scientific computing play an important role in research andengineering applications in the natural and the engineering sciences. The signif-icance and impact of computer algebra methods and computer algebra systemsfor scientific computing has increased considerably in recent times. Nowadays,such general-purpose computer algebra systems as Maple, Magma, Mathematica,MuPAD, Singular, CoCoA and others enable their users to solve the followingthree important tasks within a uniform framework:(a) symbolic manipulation;(b) numerical computation;(c) visualization. The result of this job is reflected in this volume, which contains revised versionsof the accepted papers. The collection of papers included in the proceedingscovers various topics of computer algebra methods, algorithms, and softwareapplied to scientific computing:
Computer Algebra in Scientific Computing ; 10th International Workshop, CASC 2007, Bonn, Germany, September 16-20, 2007, Proceedings
The book covers not only various expanding applications of computer algebra to scientific computing but also the computer algebra systems themselves and the CA algorithms. Topics addressed are studies in polynomial and matrix algebra, quantifier elimination, and Gröbner bases, as well as stability investigation of both differential equations and difference methods for them. Several papers are devoted to the application of computer algebra methods and algorithms to the derivation of new mathematical models in biology and in mathematical physics.
Computer Aided Systems Theory – EUROCAST 2005 ; 10th International Conference on Computer Aided Systems Theory, Las Palmas de Gran Canaria, Spain, February 7-11, 2005, Revised Selected Papers
The concept of CAST, computer aided systems Theory, was introduced by F. Pichler of Linz in the late 1980s to include those computer theoretical and practical developments used as tools to solve problems in system science. It was considered as the third component (the other two being CAD and CAM) that would provide for a complete picture of the path from computer and systems sciences to practical developments in science and engineering. Selected papers were published as Springer Lecture Notes in Computer Science vols. 410, 585, 763, 1030, 1333, 1728, 2178 and 2809 and in several special issues of Cybernetics and Systems: an lnternational
Computational Discovery of Scientific Knowledge : Introduction, Techniques, and Applications in Environmental and Life Sciences
Advances in technology have enabled the collection of data from scientific observations, simulations, and experiments at an ever-increasing pace. For the scientist and engineer to benefit from these enhanced data collecting capabilities, it is becoming clear that semi-automated data analysis techniques must be applied to find the useful information in the data. Computational scientific discovery methods can be used to this end: they focus on applying computational methods to automate scientific activities, such as finding laws from observational data. In contrast to mining scientific data, which focuses on building highly predictive models, computational scientific discovery puts a strong emphasis on discovering knowledge represented in formalisms used by scientists and engineers, such as numeric equations and reaction pathways. This state-of-the-art survey provides an introduction to computational approaches to the discovery of scientific knowledge and gives an overview of recent advances in this area, including techniques and applications in environmental and life sciences.
Collaborative networks and their breeding environments ; IFIP TC 5 WG 5.5 Sixth IFIP Working Conference on VIRTUAL ENTERPRISES, 26-28 September 2005, Valencia, Spain
This book contains selected articles from PRO-VE'05, the sixth working conference on virtual enterprises, which was sponsored by the International Federation for Information Processing (IFIP) and held in Valencia, Spain. Being recognized as the most focused scientific / technical conference on Collaborative Networks, PRO-VE continues offering the opportunity for the presentation and discussion of both the latest research developments and practical application case studies. Following the IFIP vision. The articles included in this book represent a comprehensive overview of recent advances in various domains and lines of development of collaborative networks. Of particular relevance are the topics of holistic approaches and breeding environments management, creation and management of virtual organizations and professional virtual communications, performance measurement and management, benefit analysis, trust management, process modeling and meta-modeling, ICT infrastructures and support services, legal issues, and case studies.
Managing Humans : Biting and Humorous Tales of a Software Engineering Manager
Managing Humans is a selection of the best essays from Michael Lopp's web site, Rands in Repose. Drawing on Lopp's management experiences at Apple, Netscape, Symantec, and Borland, this book is full of stories based on companies in the Silicon Valley where people have been known to yell at each other. It is a place full of dysfunctional bright people who are in an incredible hurry to find the next big thing so they can strike it rich and then do it all over again. Among these people are managers, a strange breed of people who through a mystical organizational ritual have been given power over your future and your bank account.
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.
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.
Linear and Generalized Linear Mixed Models and Their Applications
This book covers two major classes of mixed effects models—linear mixed models and generalized linear mixed models—and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. It offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it discusses the latest developments and methods in the field, incorporating relevant updates since publication of the first edition. These include advances in high-dimensional linear mixed models in genome-wide association studies (GWAS), advances in inference about generalized linear mixed models with crossed random effects, new methods in mixed model prediction, mixed model selection, and mixed model diagnostics.
