الصفحة 45
الصفحة 45
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 in Pattern Recognition ; 4th International Conference, MLDM 2005, Leipzig, Germany, July 9-11, 2005, Proceedings
Today, artificial intelligence deals with large amounts of data and knowledge and finds new information using machine learning and data mining. Machine learning and data mining are irreplaceable subjects and tools for the theory of pattern recognition and in applications of pattern recognition such as bioinformatics and data retrieval. This was the fourth edition of MLDM in Pattern Recognition which is the main event of Technical Committee 17 of the International Association for Pattern Recognition; it started out as a workshop and continued as a conference in 2003. Today, there are many international meetings which are titled “machine learning” and “data mining”, whose topics are text mining, knowledge discovery, and applications. This meeting from the first focused on aspects of machine learning and data mining in pattern recognition problems. We planned to reorganize classical and well-established pattern recognition paradigms from the viewpoints of machine learning and data mining. Though it was a challenging program in the late 1990s, the idea has inspired new starting points in pattern recognition and effects in other areas such as cognitive computer vision.
Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks
Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.
Machine Learning : Modeling Data Locally and Globally
Machine Learning - Modeling Data Locally and Globally presents a novel and unified theory that tries to seamlessly integrate different algorithms. Specifically, the book distinguishes the inner nature of machine learning algorithms as either "local learning"or "global learning."This theory not only connects previous machine learning methods, or serves as roadmap in various models, but – more importantly – it also motivates a theory that can learn from data both locally and globally. This would help the researchers gain a deeper insight and comprehensive understanding of the techniques in this field. The book reviews current topics,new theories and applications.
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.
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.
Logical Data Modeling : What it is and How to do it
LOGICAL DATA MODELING: What It Is and How To Do IT is directed toward three groups of people: (1) Business subject matter experts, (2) information technology professionals, (3) advanced students in Computer Science, Management Information Systems, and e-Business. Its purpose is to outline the basics of logical data modeling—specifically, data modeling for relational database management systems—in simple, practical terms and in a business context. The focus on relational data modeling is consciously made because it is superior in modeling real business activities.
Logical aspects of computational linguistics ; 4th International Conference, LACL 2001, Le Croisic, France, June 27-29, 2001, Proceedings
Structural Equations in Language Learning.- On the Distinction between Model-Theoretic and Generative-Enumerative Syntactic Frameworks.- Contributed Papers.- A Formal Definition of Bottom-Up Embedded Push-Down Automata and Their Tabulation Technique.- An Algebraic Approach to French Sentence Structure.- Deductive Parsing of Visual Languages.- Lambek Grammars Based on Pregroups.- An Algebraic Analysis of Clitic Pronouns in Italian.- Consistent Identification in the Limit of Any of the Classes k-Valued Is NP-hard.- Polarized Non-projective Dependency Grammars.- On Mixing Deduction and Substitution in Lambek Categorial Grammars.- A Framework for the Hyperintensional Semantics of Natural Language with Two Implementations.- A Characterization of Minimalist Languages.- of Speech Tagging from a Logical Point of View.- Transforming Linear Context-Free Rewriting Systems into Minimalist Grammars.- Recognizing Head Movement.- Combinators for Paraconsistent Attitudes.- Combining Syntax and Pragmatic Knowledge for the Understanding of Spontaneous Spoken Sentences.- Atomicity of Some Categorially Polyvalent Modifiers.
Logical approaches to computational barriers ; 2nd Conference on Computability in Europe, CiE 2006, Swansea, UK, June 30-July 5, 2006, Proceedings
The sources of new ideas and methods include practical developments in areas such as neural networks, quantum computation, natural computation, molecular computation, and computational learning. Applications are everywhere, especially, in algebra, analysis and geometry, or data types and programming. This volume, Logical Approaches to Computational Barriers, is the proce- ings of the second in a series of conferences of CiE that was held at the Depa- ment of Computer Science, Swansea University, 30 June - 5 July, 2006.
Logical and Relational Learning
This textbook covers logical and relational learning in depth, and hence provides an introduction to inductive logic programming (ILP), multirelational data mining (MRDM) and (statistical) relational learning (SRL). These subfields of data mining and machine learning are concerned with the analysis of complex and structured data sets that arise in numerous applications, such as bio- and chemoinformatics, network analysis, Web mining, natural language processing, within the rich representations offered by relational databases and computational logic.
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, Language, and Computation ; 6th International Tbilisi Symposium on Logic, Language, and Computation. Batumi, Georgia, September 12-16, 2005, Revised Selected Papers
Edited in collaboration with FoLLI, the Association of Logic, Language and Information, this book constitutes the second volume of the FoLLI LNAI subline. It represents the thoroughly refereed post-proceedings of the 6th International Tbilisi Symposium on Logic, Language, and Computation, TbiLLC 2005, held in Batumi, Georgia, in September 2005.
Logic Programming ; Vol. 3668 : 21st International Conference, ICLP 2005, Sitges, Spain, October 2-5, 2005, Proceedings
This volume contains the proceedings of the 21st International Conference on Logic Programming which was held in Sitges (Barcelona), Spain, from October 2nd to 5th, 2005. The conference was colocated with the International Conf- ence on ConstraintProgramming(CP 2005)and the following 6 post-conference workshops: – CICLOPS 2005: Colloquium on Implementation of Constraint and Logic Programming Systems – CSLP 2005: Constraint Solving and Language Processing – WCB 2005: Constraint Based Methods for Bioinformatics – WLPE 2005: Logic-Based Methods in Programming Environments – MoVeLog 2005: Mobile Code Safety and Program Veri?cation Using C- putational Logic Tools – CHR 2005: Constraint Handling Rules The conferencecoincided with a solareclipse
Logging in Java with the JDK 1.4 Logging API and Apache log4j
In development scenarios where things can't be run in a debugger, or when you run the risk of masking the problem, logs are the greatest source of information about running a program. Pro Apache Log4j, Second Edition provides best practices guidelines and comprehensive coverage of the most recent release. Step by step, the book explains core concepts, from basic to advanced. Code samples are in Java and include guidelines for different application-specific needs. You'll also learn how to extend the API to write custom components and best practices for using the feature-rich log4j API. This book concludes with enterprise Java applications using log4j with JSP and J2EE.
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.
Location- and Context-Awareness ; Vol. 3987 ; 2nd International Workshop, LoCA 2006, Dublin, Ireland, May 10-11, 2006, Proceedings
Contain the papers presented at the 2 International Workshop on Location- and Context-Awareness in May of 2006. As computing moves increasingly into the everyday world, the importance of location and context knowledge grows. The range of contexts encountered while sitting at a desk working on a computer is very limited compared to the large variety of situations experienced away from the desktop. For computing to be relevant and useful in these situations, the computers must have knowledge of the user’s activity, resources, state of mind, and goals, i.e., the user’s context, of which location is an important indicator. This workshop was intended to present research aimed at sensing, inferring, and using location and context data in ways that help the user.
Location- and Context-Awareness ; Vol. 3479 ; First International Workshop, LoCA 2005, Oberpfaffenhofen, Germany, May 12-13, 2005, Proceedings
The workshop was organized by the Institute of Communications and Navigation of the German Aerospace Center (DLR) in Oberpfa?enhofen, and the Mobile and Distributed Systems Group of the University of Munich. During the workshop, novel positioning algorithms and location sensing techniques were discussed, comprising not only enhancements of singular systems, like positioning in GSM or WLAN, but also hybrid technologies, such as the integration of global satellite systems with inertial positioning. Furthermore, improvements in sensor technology, as well as the integration and fusion of sensors, were addressed both on a theoretical and on an implementation level. Personal and confidential data, such as location data of users, have p- found implications for personal information privacy. Thus privacy protection, privacy-oriented location-aware systems, and how privacy aspects the feasibility and usefulness of systems were also addressed in the workshop.
Location- and context-awareness ; 3rd International Symposium, LoCA 2007, Oberpfaffenhofen, Germany, September 20-21, 2007, Proceedings
These proceedings contain the papers presented at the 3rd International S- posium on Location- and Context-Awareness in September of 2007. Computing has become mobile, wireless, and portable. The rangeof contexts encountered while sitting at a desk working on a computer is very limited c- pared to the large variety of situations experienced away from the desktop.
Local Pattern Detection ; International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers
Introduction The dramatic increase in available computer storage capacity over the last 10 years has led to the creation of very large databases of scienti?c and commercial information. The need to analyze these masses of data has led to the evolution of the new field knowledge discovery in databases (KDD) at the intersection of machine learning, statistics and database technology. Being interdisciplinary by nature, the field offers the opportunity to combine the expertise of different fields into a common objective. Moreover, within each field diverse methods have been developed and justified with respect to different quality criteria. We have to investigate how these methods can contributet o solving the problem of KDD. Traditionally, KDD was seeking to end global models for the data that - plain most of the instances of the database and describe the general structure of the data. Examples are statistical time series models, cluster models, logic programs with high coverageor classi?cation models like decision trees or linear decision functions. In practice, though, the use of these models often is very l- ited, because global models tend to end only the obvious patterns in the data, 1 which domain experts already are aware of . What is really of interest to the users are the local patterns that deviate from the already-known background knowledge. David Hand, who organized a workshop in 2002, proposed the new field of local patterns.
