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Malware Detection
Malware Detection, based on the Special ARO/DHS Workshop on Malware Detection at Rosslyn, VA, in 2005, captures the state of the art research in the area of malicious code detection, prevention and mitigation.
Malliavin Calculus for Lévy Processes with Applications to Finance
While the original works on Malliavin calculus aimed to study the smoothness of densities of solutions to stochastic differential equations, this book has another goal. It portrays the most important and innovative applications in stochastic control and finance, such as hedging in complete and incomplete markets, optimisation in the presence of asymmetric information and also pricing and sensitivity analysis. In a self-contained fashion, both the Malliavin calculus with respect to Brownian motion and general Lévy type of noise are treated. Besides, forward integration is included and indeed extended to general Lévy processes. The forward integration is a recent development within anticipative stochastic calculus that, together with the Malliavin calculus, provides new methods for the study of insider trading problems.
Making Healthcare Safe : The Story of the Patient Safety Movement
This unique and engaging open access title provides a compelling and ground-breaking account of the patient safety movement in the United States, told from the perspective of one of its most prominent leaders, and arguably the movement’s founder, Lucian L. Leape, MD. Covering the growth of the field from the late 1980s to 2015, Dr. Leape details the developments, actors, organizations, research, and policy-making activities that marked the evolution and major advances of patient safety in this time span. In addition, and perhaps most importantly, this book not only comprehensively details how and why human and systems errors too often occur in the process of providing health care, it also promotes an in-depth understanding of the principles and practices of patient safety, including how they were influenced by today’s modern safety sciences and systems theory and design. Indeed, the book emphasizes how the growing awareness of systems-design thinking and the self-education and commitment to improving patient safety, by not only Dr. Leape but a wide range of other clinicians and health executives from both the private and public sectors, all converged to drive forward the patient safety movement in the US.
Making Globally Distributed Software Development a Success Story : International Conference on Software Process, ICSP 2008 Leipzig, Germany, May 10-11, 2008 Proceedings
This volume contains papers presented at the International Conference on Software Process (ICSP 2008) held in Leipzig, Germany, during May 10-11, 2008. ICSP 2008 was the second conference of the ICSP series. The theme of ICSP 2008 was “Making Globally Distributed Software Development a Success Story. ” Software developers work in a dynamic context of frequently changing technologies and with limited resources. Globally distributed development teams are under ev- increasing pressure to deliver their products more quickly and with higher levels of qu- ity. At the same time, global competition is forcing software development organizations to cut costs by rationalizing processes, outsourcing part of or all development activities, reusing existing software in new or modified applications, and evolving existing systems to meet new needs, while still minimizing the risk of projects failing to deliver.
Making Beautiful Deep-Sky Images : Astrophotography with Affordable Equipment and Software
Professor Greg Parker's astronomical photographs are widely known for their excellence, and a selection of them has recently been shown as a public exhibition in the UK. In Making Beautiful Deep-Sky Images, he provides a detailed account of how spectacular deep-sky images can be taken by amateur astronomers using CCD cameras, and how they can subsequently be processed and enhanced in the "electronic darkroom" for maximum beauty and impact. Quite simply, this is a "how to do it" book for people who want to make stunning astronomical pictures.
Macrophytes in Aquatic Ecosystems : from Biology to Management ; Proceedings of the 11th International Symposium on Aquatic Weeds, European Weed Research Society
Macrophytes and macrophytes ecology have gained an added importance with the introduction of, and legal requirement to implement, the European Water Framework Directive. This reflects the valuable role that aquatic plant communities play in assessing the ecological status of water bodies. Significant changes in the status and general abundance of these communities has been recorded in the last three decades, consequent on such factors as global warming and, increasingly, on the spread of aggressive alien species. These changes have been most felt in those waters that are exploited for amenity and recreational pursuits. The increased biomass of aquatic vegetation in water bodies has adversely impacted on leisure use of these systems but has also impacted on their use for agricultural, flood relief, municipal and domestic purposes. The loss to national economies resulting from this excessive plant biomass has been appreciable and has put pressure on water managers to develop weed control procedures that are efficient, environmentally sensitive and cost-effective.
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.
MacLaurins Physical Dissertations
The Scottish mathematician Colin MacLaurin (1698-1746) is best known for developing and extending Newton’s work in calculus, geometry and gravitation; his 2-volume work "Treatise of Fluxions" (1742) was the first systematic exposition of Newton’s methods. It is well known that MacLaurin was awarded prizes by the Royal Academy of Sciences, Paris, for his earlier work on the collision of bodies (1724) and the tides (1740); however, the contents of these essays are less familiar – although some of the material is discussed in the Treatise of Fluxions - and the essays themselves often hard to obtain.
Machine Learning: ECML 2007 ; 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007, Proceedings
The two premier annual European conferences in the areas of machine learning and data mining have been collocated ever since the ?rst joint conference in Freiburg, 2001. The European Conference on Machine Learning (ECML) traces its origins to 1986, when the ?rst European Working Session on Learning was held in Orsay, France. The European Conference on Principles and Practice of KnowledgeDiscoveryinDatabases(PKDD) was?rstheldin1997inTrondheim, Norway.
Machine Learning for Multimodal Interaction ; 5th International Workshop, MLMI 2008, Utrecht, The Netherlands, September 8-10, 2008. Proceedings
The 12 revised full papers and 15 revised poster papers presented together with 5 papers of a special session on user requirements and evaluation of multimodal meeting browsers/assistants were carefully reviewed and selected from 47 submissions. The papers cover a wide range of topics related to human-human communication modeling and processing, as well as to human-computer interaction, using several communication modalities. Special focus is given to the analysis of non-verbal communication cues and social signal processing, the analysis of communicative content, audio-visual scene analysis, speech processing, interactive systems and applications.
Machine Learning for Multimodal Interaction ; 4th International Workshop, MLMI 2007, Brno, Czech Republic, June 28-30, 2007, Revised Selected Papers
This book contains a selection of revised papers from the 4th Workshop on Machine Learning for Multimodal Interaction (MLMI 2007), which took place in Brno, Czech Republic, during June 28 30, 2007. As in the previous editions of the MLMI series, the 26 chapters of this book cover a large area of topics, from multimodal processing and human computer interaction to video, audio, speech and language processing. The application of machine learning techniques to problems arising in these felds and the design and analysis of software
Machine learning for data streams : With practical examples in MOA
The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA.
Machine learning for cyber security ; 3rd International Conference, ML4CS 2020, Guangzhou, China, October 8–10, 2020, Proceedings, Part III
Constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi’an, China in October 2020. The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.
Machine Learning for Cyber Security ; 3rd International Conference, ML4CS 2020, Guangzhou, China, October 8–10, 2020, Proceedings, Part II
Constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi’an, China in October 2020. The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.
Machine Learning for Cyber Security ; 3rd International Conference, ML4CS 2020, Guangzhou, China, October 8–10, 2020, Proceedings, Part I
Constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi’an, China in October 2020. The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.
Machine Learning for Cyber Agents : Attack and Defence
The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter.
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 approach for cloud data analytics in IoT
Covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications. Elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.
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 Intelligence and Big Data Analytics for Cybersecurity Applications
Presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis. Cyber-attacks have posed real and wide-ranging threats for the information society. Detecting cyber-attacks becomes a challenge, not only because of the sophistication of attacks but also because of the large scale and complex nature of today’s IT infrastructures. It discusses novel trends and achievements in machine intelligence and their role in the development of secure systems and identifies open and future research issues related to the application of machine intelligence in the cybersecurity field.
