الصفحة 5
الصفحة 5
Micro-Assembly Technologies and Applications ; IFIP TC5 WG5.5 Fourth International Precision Assembly Seminar (IPAS’2008) Chamonix, France February 10–13, 2008
The IFIP series publishes state-of-the-art results in the sciences and technologies of information and communication. The scope of the series includes: foundations of computer science; software theory and practice; education; computer applications in technology; communication systems; systems modeling and optimization; information systems; computers and society; computer systems technology; security and protection in information processing systems; artificial intelligence; and human-computer interaction. Proceedings and post-proceedings of referred international conferences in computer science and interdisciplinary fields are featured. These results often precede journal publication and represent the most current research.
MICAI 2008 : Advances in Artificial Intelligence ;7th Mexican International Conference on Artificial Intelligence, Atizapán de Zaragoza, Mexico, October 27-31, 2008 Proceedings
The 96 revised full papers presented together with 2 invited lectures were carefully reviewed and selected from 363 submissions. The papers are organized in topical sections on logic and reasoning, knowledge-based systems, knowledge representation and acquisition, ontologies, natural language processing, machine learning, pattern recognition, data mining, neural networks, genetic algorithms, hybrid intelligent systems, computer vision and image processing, robotics, planning and scheduling, uncertainty and probabilistic reasoning, fuzzy logic, intelligent tutoring systems, multi-agent systems and distributed ai, intelligent organizations, bioinformatics and medical applications, as well as applications.
MICAI 2007 : Advances in artificial intelligence ; 6th Mexican International Conference on Artificial Intelligence, Aguascalientes, Mexico, November 4-10, 2007, Proceedings
The Mexican International Conference on Artificial Intelligence (MICAI), a yearly international conference series organized by the Mexican Society for Artificial Intelligence (SMIA), is a major international AI forum and the main event in the academic life of the country’s growing AI community.
MICAI 2006 : Advances in Artificial Intelligence ; 5th Mexican International Conference on Artificial Intelligence, Apizaco, Mexico, November 13-17, 2006, Proceedings
This volume contains the papers presented during the oral session of the 5 Mexican International Conference on Artificial Intelligence, held on November 13–17, 2006, at the Technologic Institute of Apizaco, Mexico. The conference received for evaluation 448 submissions by 1207 authors from 42 different countries
MICAI 2005 : Advances in Artificial Intelligence ; 4th Mexican International Conference on Artificial Intelligence, Monterrey, Mexico, November 14-18, 2005, Proceedings
Constitutes the refereed proceedings of the 4th Mexican International Conference on Artificial Intelligence, MICAI 2005, held Mexico, in November 2005. This book is organized in topical sections on knowledge representation and management, logic and constraint programming, uncertainty reasoning, multiagent systems and distributed AI, and others.
Methods and Procedures for the Verification and Validation of Artificial Neural Networks
Methods and Procedures for the Verification and Validation of Artificial Neural Networks is the culmination of the first steps in that research. This volume introduces some of the more promising methods and techniques used for the verification and validation (V&V) of neural networks and adaptive systems. A comprehensive guide to performing V&V on neural network systems, aligned with the IEEE Standard for Software Verification and Validation, will follow this book. The NASA IV&V and the Institute for Scientific Research, Inc. are working to be at the forefront of software safety and assurance for neural network and adaptive systems.
Methodological Investigations in Agent-Based Modelling : With Applications for the Social Sciences
Examines the methodological complications of using complexity science concepts within the social science domain. The opening chapters take the reader on a tour through the development of simulation methodologies in the fields of artificial life and population biology, then demonstrates the growing popularity and relevance of these methods in the social sciences. Following an in-depth analysis of the potential impact of these methods on social science and social theory, the text provides substantive examples of the application of agent-based models in the field of demography. This work offers a unique combination of applied simulation work and substantive, in-depth philosophical analysis, and as such has potential appeal for specialist social scientists, complex systems scientists, and philosophers of science interested in the methodology of simulation and the practice of interdisciplinary computing research.
Metalearning : Applications to Automated Machine Learning and Data Mining
This book as one of the fastest-growing areas of research in machine learning, metalearning studies principled methods to obtain efficient models and solutions by adapting machine learning and data mining processes. This adaptation usually exploits information from past experience on other tasks and the adaptive processes can involve machine learning approaches. As a related area to metalearning and a hot topic currently, automated machine learning (AutoML) is concerned with automating the machine learning processes. Metalearning and AutoML can help AI learn to control the application of different learning methods and acquire new solutions faster without unnecessary interventions from the user.
Medical Imaging and Informatics ; 2nd International Conference, MIMI 2007, Beijing, China, August 14-16, 2007 Revised Selected Papers
This book constitutes the thoroughly refeered post-conference proceedings of the Second Interational Conference on Medical Imaging and Informatics, MIMI 2007, held in Beijing, China, in August 2007.The 40 revised full papers presented together with 4 keynote talks were carefully reviewed and selected from 110 submissions. The papers are organized in topical sections on medical image segmentation and registration, medical informatics, PET, fMRI, ultrasound and thermal imaging, 3D reconstruction and visualization. The volume is rounded off by 4 papers from 2 workshops on legal, ethical and social issues in medical imaging and informatics, as well as on computer-aided diagnosis (CAD).
Medical Imaging and Augmented Reality ; 4th International Workshop Tokyo, Japan, August 1-2, 2008 Proceedings
Constitutes the refereed proceedings of the 4th International Workshop on Medical Imaging and Augmented Reality, MIAR 2008, held in Tokyo, Japan, in August 2008.The 44 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections on surgical planning and simulation, medical image computing, image analysis, shape modeling and morphometry, image-guided robotics, image-guided intervention, interventional imaging, image registration, augmented reality, and image segmentation.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008 ; 11th International Conference, New York, NY, USA, September 6-10, 2008, Proceedings, Part II
The program committee carefully selected 258 revised papers from numerous submissions for presentation in two volumes, based on rigorous peer reviews. The first volume includes 127 papers related to medical image computing, segmentation, shape and statistics analysis, modeling, motion tracking and compensation, as well as registration. The second volume contains 131 contributions related to robotics and interventions, statistical analysis, segmentation, intervention, modeling, and registration.
Medical data processing and analysis
Medical data can be defined as obtaining information from patients (such as signals, images, sounds, chemical components and their concentration, body temperature, respiratory rate, blood pressure, and different treatment measurements) to quantify the patient’s status and disease stage. Computer-aided diagnostic (CAD) systems use classical image processing, computer vision, machine learning, and deep learning methods for image analysis. Using image classification or segmentation algorithms, they find a region of interest (ROI) pointing to a specific location within the given image or an outcome of interest in the form of a label pointing to a diagnosis or prognosis. Computer science, with the evolution of artificial intelligence and machine learning techniques, facilitates the modeling and interpretation of results—from carrying out measurements to experiments and observations.
Medical Biometrics ; 1st International Conference, ICMB 2008, Hong Kong, China, January 4-5, 2008, Proceedings
Medical biometrics primarily refers to the usage of beh- ioral and physiological characteristics of humans for medical diagnosis and body care. Thus the goal of medical biometrics is to explore solutions to the open problems in medicine using biometric measurements, technologies and systems.
Mechanizing Mathematical Reasoning : Essays in Honor of Jörg H. Siekmann on the Occasion of His 60th Birthday
By presenting state-of-the-art results in logical reasoning and formal methods in the context of artificial intelligence and AI applications, this book commemorates the 60th birthday of Jörg H. Siekmann. The 30 revised reviewed papers are written by former and current students and colleagues of Jörg Siekmann; also included is an appraisal of the scientific career of Jörg Siekmann entitled "A Portrait of a Scientist: Logics, AI, and Politics." The papers are organized in four parts on logic and deduction, applications of logic, formal methods and security, and agents and planning.
Mechanisms, Symbols, and Models Underlying Cognition ; 1st International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2005, Las Palmas, Canary Islands, Spain, June 15-18, 2005, Proceedings, Part I
Constitute the refereed proceedings of the First International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2005. This two-volume set contains papers that are related with the conceptual developments in the fields of Neurophysiology and cognitive science, and also to bioinspired programming strategies.
MDATA : A New Knowledge Representation Model: Theory, Methods and Applications
This book introduces a new knowledge representation model called MDATA (Multi-dimensional Data Association and inTelligent Analysis). By modifying the representation of entities and relations in knowledge graphs, dynamic knowledge can be efficiently described with temporal and spatial characteristics. The MDATA model can be regarded as a high-level temporal and spatial knowledge graph model, which has strong capabilities for knowledge representation. This book introduces some key technologies in the MDATA model, such as entity recognition, relation extraction, entity alignment, and knowledge reasoning with spatiotemporal factors. The MDATA model can be applied in many critical applications and this book introduces some typical examples, such as network attack detection, social network analysis, and epidemic assessment.
IOT control and surveillance system
An automated system is a combination of both software and hardware which is designed and programmed to work automatically without the need of any human operator to provide inputs and instructions for each operation. The Internet of Things (IoT) is a network of connected things. These ‘things’ (devices) communicate with each other using machine to machine communication (M2M). Information is traversed between devices so that processes can be automated, without the need for human intervention. By reducing the number of people involved in a business process, several advantages arise, including improved accuracy and up-time. We will build an IoT automated system to control access of humans and vehicles to a warehouse based on biometrics and image recognition techniques.
IoT and AI Technologies for Sustainable Living : A Practical Handbook
Brings together all the latest methodologies, tools and techniques related to the Internet of Things and Artificial Intelligence in a single volume to build insight into their use in sustainable living. The areas of application include agriculture, smart farming, healthcare, bioinformatics, self-diagnosis systems, body sensor networks, multimedia mining, and multimedia in forensics and security. Provides a comprehensive discussion of modeling and implementation in water resource optimization, recognizing pest patterns, traffic scheduling, web mining, cyber security and cyber forensics. It will help develop an understanding of the need for AI and IoT to have a sustainable era of human living. The tools covered include genetic algorithms, cloud computing, water resource management, web mining, machine learning, block chaining, learning algorithms, sentimental analysis and Natural Language Processing (NLP).
Introduction to Machine Learning with Applications in Information Security
Provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn't prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec.
Introduction to Intelligent Construction Technology of Transportation Infrastructure
Expounds on the related technologies of intelligent transportation infrastructure construction. Based on the essential characteristics of intelligent construction, "perception, analysis, decision-making, and execution," the basic structure of intelligent construction technology (ICT) is established. With the integration of engineering construction technologies, the analyses of the essence of intelligent algorithms and the feasibility of Artificial Intelligence (AI) are provided. The book introduces the essential characteristics of Big Data and the Internet of Things and their relationship with engineering construction. On this basis, the feasibility and implementation plan of intelligent technology applications in design, construction, and maintenance are analyzed and demonstrated with engineering examples.
