الصفحة 1
الصفحة 1
Managing Traffic Performance in Converged Networks ; 20th International Teletraffic Congress, ITC20 2007, Ottawa, Canada, June 17-21, 2007, Proceedings
Managing traffic performance is a critical enabler for success. Reaching the desired performance levels requires adapting processes such as network planning, resource engineering, and network monitoring to the converged network milieu.
Managing Large-Scale Service Deployment ; 19th IFIP/IEEE International Workshop on Distributed Systems : Operations and Management, DSOM 2008, Samos Island, Greece, September 22-26, 2008. Proceedings
Contains all papers accepted for presentation at the 19th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management (DSOM 2008),which was held September 25-26, 2008 on the island of Samos, Greece. DSOM 2008 was the 19th event in a series of annual workshops. It followed in the footsteps of previous s- cessful meetings, the most recent of which were held in San Jos´ e, California, USA (DSOM 2007), Dublin, Ireland (DSOM 2006), Barcelona, Spain (DSOM 2005), Davis, California, USA (DSOM 2004), Heidelberg, Germany (DSOM 2003), and Montreal, Canada (DSOM 2002).
Managed Software Evolution
This book presents the outcomes of the “Design for Future – Managed Software Evolution” .The different lifecycles of software and hardware platforms lead to interoperability problems in such systems. Instead of separating the development, adaptation and evolution of software and its platforms, as well as aspects like operation, monitoring and maintenance, they should all be integrated into one overarching process. Accordingly, the book is split into three major parts, the first of which includes an introduction to the nature of software evolution, followed by an overview of the specific challenges and a general introduction to the case studies used in the project. The second part of the book consists of the main chapters on knowledge carrying software, and cover tacit knowledge in software evolution, continuous design decision support, model-based round-trip engineering for software product lines, performance analysis strategies, maintaining security in software evolution, learning from evolution for evolution, and formal verification of evolutionary changes. In turn, the last part of the book presents key findings and spin-offs. The individual chapters there describe various case studies, along with their benefits, deliverables and the respective lessons learned. An overview of future research topics rounds out the coverage.
Machine Learning, Image Processing, Network Security and Data Sciences ; 2nd International conference, MIND 2020, Silchar, India, July 30 - 31, 2020, Proceedings, Part II
This two-volume set (CCIS 1240-1241) constitutes the refereed proceedings of the Second International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2020, held in Silchar, India. Due to the COVID-19 pandemic the conference has been postponed to July 2020. The 79 full papers and 4 short papers were thoroughly reviewed and selected from 219 submissions. The papers are organized according to the following topical sections: data science and big data; image processing and computer vision; machine learning and computational intelligence; network and cyber security.
Machine learning, image processing, network security and data sciences ; 2nd International conference, MIND 2020, Silchar, India, July 30 - 31, 2020, Proceedings, Part I
This two-volume set (CCIS 1240-1241) constitutes the refereed proceedings of the Second International Conference on Machine Learning, Image Processing, Network Security and Data Sciences, MIND 2020, held in Silchar, India. Due to the COVID-19 pandemic the conference has been postponed to July 2020. The 79 full papers and 4 short papers were thoroughly reviewed and selected from 219 submissions. The papers are organized according to the following topical sections: data science and big data; image processing and computer vision; machine learning and computational intelligence; network and cyber security.
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 : 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.
Long-Term Preservation of Digital Documents : Principles and Practices
Key to our culture is that we can disseminate information, and then maintain and access it over time. While we are rapidly advancing from vulnerable physical solutions to superior, digital media, preserving and using data over the long term involves complicated research challenges and organization efforts. Uwe Borghoff and his coauthors address the problem of storing, reading, and using digital data for periods longer than 50 years. They briefly describe several markup and document description languages like TIFF, PDF, HTML, and XML, explain the most important techniques such as migration and emulation, and present the OAIS (Open Archival Information System) Reference Model. To complement this background information on the technology issues the authors present the most relevant international preservation projects, such as the Dublin Core Metadata Initiative, and experiences from sample projects run by the Cornell University Library and the National Library of the Netherlands. A rated survey list of available systems and tools completes the book.
Logic, language, information and computation ; 15th International Workshop, WoLLIC 2008 Edinburgh, UK, July 1-4, 2008 Proceedings
The papers cover all pertinent subjects in computer science with particular interest in cross-disciplinary topics. Typical areas of interest are: foundations of computing and programming; novel computation models and paradigms; broad notions of proof and belief; formal methods in software and hardware development; logical approach to natural language and reasoning; logics of programs, actions and resources; foundational aspects of information organization, search, flow, sharing, and protection.
Logic, language, information and computation ; 14th International Workshop, WoLLIC 2007, Rio de Janeiro, Brazil, July 2-5, 2007, Proceedings
The Workshop on Logic, Language, Information and Computation (WoLLIC) is an annual international forum on inter-disciplinary research involving formal logic, computing and programming theory, and natural language and reasoning. The WoLLIC meetings alternate between Brazil (and Latin America) and other countries, with the aim of fostering interest in applied logic among Latin Am- ican scientists and students, and facilitating their interaction with the international - plied logic community.
Logic for Computer Scientists
This book introduces the notions and methods of formal logic from a computer science standpoint, covering propositional logic, predicate logic, and foundations of logic programming. It presents applications and themes of computer science research such as resolution, automated deduction, and logic programming in a rigorous but readable way.The style and scope of the work, rounded out by the inclusion of exercises, make this an excellent textbook for an advanced undergraduate course in logic for computer scientists.
Leveraging applications of formal methods, verification and validation : Engineering Principles ; 9th International Symposium on Leveraging Applications of Formal Methods, ISoLA 2020, Rhodes, Greece, October 20–30, 2020, Proceedings, Part II
Constitutes the refereed proceedings of the 9th International Symposium on Leveraging Applications of Formal Methods, ISoLA 2020, which was planned to take place during October 20–30, 2020, on Rhodes, Greece. The event itself was postponed to 2021 due to the COVID-19 pandemic. The papers presented were carefully reviewed and selected for inclusion in the proceedings. Each volume focusses on an individual topic with topical section headings within the volume: Part II, Engineering Principles : Automating Software Re-Engineering ; Rigorous Engineering of Collective Adaptive Systems.
Learning Design : A Handbook on Modelling and Delivering Networked Education and Training
Put together contributions from members of the "Valkenburg Group", consisting of 33 experts deeply involved in e-learning and more specifically learning design. The result is a rich and lasting source of information for both e-learning course and tool developers, providing information about the specification itself, how to implement it in practice, what tools to use, and what pitfalls to avoid. The book not only reports first experiences, but also goes beyond the current state of the art by looking at future prospects and emerging applications.
Learning Classifier Systems ; International Workshops, IWLCS 2003-2005, Revised Selected Papers
The work embodied in this volume was presented across three consecutive e- tions of the International Workshop on Learning Classi?er Systems that took place in Chicago (2003), Seattle (2004), and Washington (2005). The Genetic and Evolutionary Computation Conference, the main ACM SIGEvo conference, hosted these three editions.
Learning and Adaption in Multi-Agent Systems ; 1st International Workshop, LAMAS 2005, Utrecht, The Netherlands, July 25, 2005, Revised Selected Papers
Contains selected and revised papers of the International Workshop on Lea- ing and Adaptation in Multi-Agent Systems (LAMAS 2005), held at the AAMAS 2005 Conference in Utrecht, The Netherlands, July 26. An important aspect in multi-agent systems (MASs) is that the environment evolves over time, not only due to external environmental changes but also due to agent int- actions. For this reason it is important that an agent can learn, based on experience, and adapt its knowledge to make rational decisions and act in this changing environment autonomously. Machine learning techniques for single-agent frameworks are well established. Agents operate in uncertain environments and must be able to learn and act - tonomously. This task is, however, more complex when the agent interacts with other agents that have potentially different capabilities and goals. The single-agent case is structurally different from the multi-agent case due to the added dimension of dynamic interactions between the adaptive agents. Multi-agent learning, i.e., the ability of the agents to learn how to cooperate and compete, becomes crucial in many domains. Autonomous agents and multi-agent systems (AAMAS) is an emerging multi-disciplinary area encompassing computer science, software engineering, biology, as well as cognitive and social sciences. A t- oretical framework, in which rationality of learning and interacting agents can be - derstood, is still under development in MASs, although there have been promising ?
Layce (Image data poisoning) = لايس (تسميم بيانات الصور )
The ongoing growth of image generative artificial intelligence models was paved with existing drawings and art pieces by great artists both past and present, and while generative models are very useful and helpful, there is the issue of the origin of the datasets trained on, and the morality of usage regarding copyrights and artistic identity. A novel line of defense that helps artists and visual content creators actively protect their pieces emerged, dubbed Data Poisoning and it works by misleading Artificial Intelligence models that attempt to use a Poisoned Image for training, or as a reference, as the Poisoned Image will appear to the human eye identical to the original art piece, while the Artificial Intelligence model will be seeing a remarkably different image, causing generative models to generate false positive results when given a prompt poisoned by the author or when trained on data poisoned by the original owner. This study aims to study image data poisoning methods and technologies, and build an application containing multiple image models, and poisoning models as well, accompanied by a Community for artists to share art and interact with each other.
Large scale management of distributed systems ; 17th IFIP/IEEE International Workshop on distributed systems: operations and management, DSOM 2006, Dublin, Ireland, October 23-25, 2006, Proceedings
Presents the proceedings of the 17 IFIP/IEEE International Workshop on Distributed Systems : Operations and Management (DSOM 2006), which was held rd th in Dublin, Ireland during October 23 to 25 , 2006. In line with its reputation as one of the pre-eminent fora for the discussion and debate of advances of distributed systems management, the 2006 iteration of DSOM brought together an international audience of researchers and practitioners from both industry and academia. th DSOM 2006 was the 17 in a series of annual workshops, and it followed the footsteps of highly successful previous meetings, the most recent of which were held in Barcelona, Spain (DSOM 2005), Davis, USA (DSOM 2004), Heidelberg, Germany (DSOM 2003), Montreal, Canada (DSOM 2002) and Nancy, France (DSOM 2001). The goal of the DSOM workshops is to bring together researchers in the areas of networks, systems and services management, from both industry and academia, to discuss recent advances and foster future growth in these ?elds. In contrast to the larger management symposia, such as Integrated Management (IM) and Network Operations and Management (NOMS), the DSOM workshops are organised as sing- track programmes in order to stimulate interaction among participants.
Languages and Compilers for Parallel Computing ; 21th International Workshop, LCPC 2008, Edmonton, Canada, July 31 - August 2, 2008, Revised Selected Papers
This book constitutes the thoroughly refereed post-conference proceedings of the 21th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2008, held in Edmonton, Canada, in July/August 2008.The 18 revised full papers and 6 revised short papers presented were carefully reviewed and selected from 35 submissions. The papers address all aspects of languages, compiler techniques, run-time environments, and compiler-related performance evaluation for parallel and high-performance computing and comprise
Knowledge Engineering : Practice and Patterns ; 16th International Conference, EKAW 2008, Acitrezza, Italy, September 29 - October 2, 2008. Proceedings
Constitutes the refereed proceedings of the 16th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2008, held in Acitrezza, Sicily, Italy, in September/October 2008.The 17 revised full papers and 15 revised short papers presented together with 3 invited talks were carefully reviewed and selected from 102 submissions. The papers are organized in topical sections on knowledge patterns and knowledge representation, matching ontologies and data integration, natural language, knowledge acquisition and annotations, search, query and interaction, as well as ontologies.
