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Combinatorial pattern matching ; Vol. 3537 ; 16th Annual Symposium, CPM 2005, Jeju Island, Korea, June 19-22, 2005, Proceedings
This volume presents the proceedings of The 16th Annual Symposium on Combinatorial Pattern Matching was heldon Jeju Island, Korea on June 19–22, 2005. the Program Committee accepted 37 of the submissionsto be presented at the conference. This collection of papers offers original research contributionsin combinatorial pattern matching and its applications.In addition to the selected papers
Combinatorial pattern matching ; 18th Annual Symposium, CPM 2007, London, Canada, July 9-11, 2007, Proceedings
This book presented original research contri- tions on computational pattern matching and analysis, data compression and compressed text processing, sufix arrays and trees, and computational biology. Combinatorial Pattern Matching addresses issues of searching and matching strings and more complicated patterns such as trees, regular expressions, graphs, point sets, and arrays.The goal is to derive non-trivial combinatorial properties of such structures and to exploit these properties in order to either achieve superior performance for the corresponding computational problems or pinpoint conditions under which searches cannot be performed eficiently.
Combinatorial optimization and applications ; 2nd International Conference, COCOA 2008, St. John’s, NL, Canada, August 21-24, 2008. Proceedings
This book constitutes the refereed proceedings of the Second International Conference on Combinatorial Optimization and Applications, COCOA 2008, held in St. John's, Canada, in August 2008.
Combinatorial optimization and applications ; 1st International Conference, COCOA 2007, Xi'an, China, August 14-16, 2007, Proceedings
This book presented feature original research in the areas of combinatorial optimization - both theoretical issues and and applications motivated by real-world problems thus showing convincingly the usefulness and efficiency of the algorithms discussed in a practical setting.
Mathematical Modelling of Biosystems
This volume is an interdisciplinary book, which introduces, in a very readable way, state of the art research in the fundamental topics of mathematical modelling of Biosystems. These topics include: the study of Biological Growth and its mechanisms, the coupling of pattern to form via theorems of Differential Geometry, the human immunodeficiency virus dynamics, the inverse folding problem and the possibility of analysing true protein backbone flexibility, the Biclustering techniques for the organization of microarray data, the analytical approach to the modelling of biomolecular structure via Steiner trees, the action of biocides on resistance mechanisms of mutated and phenotypic bacteria strains, a description of the fundamental processes for the distribution and abundances of species towards a unified theory of Ecology, and a special introduction to Protein Physics aiming to explain the all-or-none first order phase transitions from native to denatured states.
Mathematical Foundations of Computer Science 2008 ; 33rd International Symposium, MFCS 2008, Toru´n, Poland, August 25-29, 2008. Proceedings
Constitutes the refereed proceedings of the 33rd International Symposium on Mathematical Foundations of Computer Science, MFCS 2008, held in Torun, Poland, in August 2008.The 45 revised full papers presented together with 5 invited lectures were carefully reviewed and selected from 119 submissions. All current aspects in theoretical computer science and its mathematical foundations are addressed, ranging from algorithmic game theory, algorithms and data structures, artificial intelligence, automata and formal languages, bioinformatics, complexity, concurrency and petrinets, cryptography and security, logic and formal specifications, models of computations, parallel and distributed computing, semantics and verification.
Mathematical Foundations of Computer Science 2007 ; 32nd International Symposium, MFCS 2007 Ceský Krumlov, Czech Republic, August 26-31, 2007, Proceedings
This book constitutes the refereed proceedings of the 32nd International Symposium on Mathematical Foundations of Computer Science, MFCS 2007, held in Cesk?? Krumlov, Czech Republic, August 26-31, 2007. All current aspects in theoretical computer science and its mathematical foundations are addressed.
Mathematical foundations of computer science 2006 ; 31st International Symposium, MFCS 2006, Stará Lesná, Slovakia, August 28-September 1, 2006, Proceedings
This book constitutes the refereed proceedings of the 31st International Symposium on Mathematical Foundations of Computer Science, MFCS 2006, held in Stará Lesná, Slovakia in August/September 2006. The 62 revised full papers presented together with the full papers or abstracts of 7 invited talks were carefully reviewed and selected from 174 submissions. All current aspects in theoretical computer science and its mathematical foundations are addressed, ranging from algorithms and data structures, to complexity, automata, semantics, logic, formal specifications, models of computation, concurrency theory, computational geometry, parallel and distributed computing, networks, bioinformatics, quantum computing, cryptography, knowledge-based systems, and artificial intelligence.
Machine learning in healthcare : Fundamentals and recent applications
Discusses how to build various ML algorithms and how they can be applied to improve healthcare systems. Healthcare applications of AI are innumerable: medical data analysis, early detection and diagnosis of disease, providing objective-based evidence to reduce human errors, curtailing inter- and intra-observer errors, risk identification and interventions for healthcare management, real-time health monitoring, assisting clinicians and patients for selecting appropriate medications, and evaluating drug responses. Extensive demonstrations and discussion on the various principles of machine learning and its application in healthcare is provided, along with solved examples and exercises.
Machine learning for biomedical application
Biomedicine is a multidisciplinary branch of medical science that consists of many scientific disciplines, e.g., biology, biotechnology, bioinformatics, and genetics; moreover, it covers various medical specialties. In recent years, this field of science has developed rapidly. This means that a large amount of data has been generated, due to (among other reasons) the processing, analysis, and recognition of a wide range of biomedical signals and images obtained through increasingly advanced medical imaging devices. The analysis of these data requires the use of advanced IT methods, which include those related to the use of artificial intelligence, and in particular machine learning. It is a summary of the Special Issue “Machine Learning for Biomedical Application”, briefly outlining selected applications of machine learning in the processing, analysis, and recognition of biomedical data, mostly regarding biosignals and medical images.
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.
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.
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
Life System Modeling and Simulation; International Conference on Life System Modeling, and Simulation, LSMS 2007, Shanghai, China, September 14-17, 2007. Proceedings
The International Conference on Life System Modeling and Simulation (LSMS) was formed to bring together international researchers and practitioners in the field of life system modeling and simulation as well as life system-inspired theory and methodology. The arrival of the 21st century has been marked by a resurgence of research interest both in arriving at a systems-level und- standing of biology and in applying such knowledge in complex real-world appli- tions. Consequently, computational methods and intelligence in systems, biology, as well as bio-inspired computational intelligence, have emerged as key drivers for new computational methods. For this reason papers dealing with theory, techniques and real-world applications relating to these two themes were especially solicited.
Knowledge-Based Intelligent Information and Engineering Systems ; Vol.3683 : 9th International Conference, KES 2005, Melbourne, Australia, September 14-16, 2005, Proceedings, Part III
The KES conference series has been established for almost a decade, and it cont- ues each year to attract participants from all geographical areas of the world, including Europe, the Americas, Australasia and the Paci?c Rim. The KES conferences cover a wide range of intelligent systems topics. The broad focus of the conference series is the theory and applications of intelligent systems. From a pure research ?eld, intel- gent systems have advanced to the point where their abilities have been incorporated into many business and engineering application areas. KES 2005 provided a valuable mechanism for delegates to obtain an extensive view of the latest research into a range of intelligent-systems algorithms, tools and techniques. The conference also gave de- gates the chance to come into contact with those applying intelligent systems in diverse commercial areas. The combination of theory and practice represented a unique opp- tunity to gain an appreciation of the full spectrum of leading-edge intelligent-systems activity. The papers for KES 2005 were either submitted to invited sessions, chaired and organized by respected experts in their ?elds, or to a general session, managed by an extensive International Program Committee, or to the Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP) Workshop, managed by an International Workshop Technical Committee.
Knowledge Discovery in Life Science Literature ; International Workshop, KDLL 2006, Singapore, April 9, 2006, Proceedings
Constitutes the refereed proceedings of the International Workshop on Knowledge Discovery in Life Science Literature, KDLL 2006, held in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006). The 12 revised full papers presented together with two invited talks were carefully reviewed and selected for inclusion in the book. The papers cover all topics of knowledge discovery in life science data.
Knowledge Discovery and Emergent Complexity in Bioinformatics ; 1st International Workshop, KDECB 2006, Ghent, Belgium, May 10, 2006, Revised Selected Papers
Contains selected and revised papers of the International Symposium on Knowledge Discovery and Emergent Complexity in Bioinformatics (KDECB 2006), held at the University of Ghent, Belgium, May 10, 2006.
Kernel Based Algorithms for Mining Huge Data Sets : Supervised, Semi-supervised, and Unsupervised Learning
"Kernel Based Algorithms for Mining Huge Data Sets" is the first book treating the fields of supervised, semi-supervised and unsupervised machine learning collectively. The book presents both the theory and the algorithms for mining huge data sets by using support vector machines (SVMs) in an iterative way. It demonstrates how kernel based SVMs can be used for dimensionality reduction (feature elimination) and shows the similarities and differences between the two most popular unsupervised techniques, the principal component analysis (PCA) and the independent component analysis (ICA).
Java for Bioinformatics and Biomedical Applications
Illustrates how individual bioinformatics applications (such as BLAST and Genscan) can be stitched together into a pipeline so that users can direct the output of one tool (for example, gene predictions using Genscan) to perform further analysis (say, homology searching using BLAST).
