الصفحة 5
الصفحة 5
Microphone Array Signal Processing
Microphone arrays have attracted a lot of interest in the last two decades. The reason behind this is that they have the potential to solve many important problems in both human-machine and human-human interfaces for different kinds of communications. But before microphone arrays can be deployed broadly, there is a strong need for a deep understanding of the problems encountered in the real world and their clear formulation in order that useful algorithms can be developed to process the sensor signals.
Micromachined Thin-Film Sensors for SOI-CMOS Co-Integration
Co-integration of sensors with their associated electronics on a single silicon chip may provide many significant benefits regarding performance, reliability, miniaturization and process simplicity without significantly increasing the total cost. Micromachined Thin-Film Sensors for SOI-CMOS Co-integration covers the challenges and interests and demonstrates the successful co-integration of gas-flow sensors on dielectric membrane, with their associated electronics, in CMOS-SOI technology.
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.
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.
Metal Forming Practise : Processes - Machines - Tools
Economical and flexible, advanced metal-forming processes form the core of modern industrial production. This professional sourcebook presents the most important metal-working and shearing processes and the related machines and tooling - in a concise form that is supplemented by ample illustrations, tables and flow charts. Practical examples show how to calculate the forces and strain energy of the processes and the specific parameters of the machines, while exercises enable readers to check their comprehension.
Medical image synthesis : Methods and clinical applications
Image synthesis across and within medical imaging modalities is an active area of research with broad applications in radiology and radiation oncology. This book covers the principles and methods of medical image synthesis, along with state-of-the-art research. First, various traditional non-learning-based, traditional machine-learning-based, and recent deep-learning-based medical image synthesis methods are reviewed. Second, specific applications of different inter- and intra-modality image synthesis tasks and of synthetic image-aided segmentation and registration are introduced and summarized, listing and highlighting the proposed methods, study designs, and reported performances with the related clinical applications of representative studies. Third, the clinical usages of medical image synthesis, such as treatment planning and image-guided adaptive radiotherapy, are discussed. Last, the limitations and current challenges of various medical synthesis applications are explored, along with future trends and potential solutions to solve these difficulties.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005 ; 8th International Conference, Palm Springs, CA, USA, October 26-29, 2005, Proceedings, Part I
This paper presents a method for classification of medical images, using machine learning and deformation-based morphometry. A morphological representation of the anatomy of interest is first obtained using highdimensional template warping, from which regions that display strong correlations between morphological measurements and the classification (clinical) variable are extracted using a watershed segmentation, taking into account the regional smoothness of the correlation map which is estimated by a crossvalidation strategy in order to achieve robustness to outliers. A Support Vector Machine-Recursive Feature Elimination (SVM-RFE) technique is then used to rank computed features from the extracted regions, according to their effect on the leave-one-out error bound. Finally, SVM classification is applied using the best set of features, and it is tested using leave-one-out. The results from a group of 61 brain images of female normal controls and schizophrenia patients demonstrate not only high classification accuracy (91.8%) and steep ROC curves, but also exceptional stability with respect to the number of selected features and the SVM kernel size
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.
Mechatronics and Machine Vision in Practice
From grading and preparing harvested vegetables to the tactile probing of a patient’s innermost recesses, mechatronics has become part of our way of life. The addition of senses and computing intelligence to blend with mechanical actuation gives rise to a breed of new machines with all the best attributes of a robot.
Mechanical System Dynamics
This textbook gives a clear and thorough presentation of the fundamental principles of mechanical systems and their dynamics. It provides both the theory and applications of mechanical systems in an intermediate theoretical level, ranging from the basic concepts of mechanics, constraint and multibody systems over dynamics of hydraulic systems and power transmission systems to machine dynamics and robotics.
Mechanical Engineering : Grundlagen des Maschinenbaus in englischer Sprache
Dieses Lehrbuch in englischer Sprache bietet für deutschsprachige Studierende einen Einstieg in die englischen Fachbegriffe der Ingenieurwissenschaften. Es enthält Grundkenntnisse einzelner Bereiche des Maschinenbaues wie Mechanik, Maschinenelemente, Thermodynamik oder auch Fertigungstechnik.
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).
Investment valuation and asset pricing : Models and methods
Offers an overview of original works on foundational asset pricing studies that follows their historical publication chronologically throughout the text. Each chapter stays close to the original works of these major authors, including quotations, examples, graphical exhibits, and empirical results. Additionally, it includes statistical concepts and methods as applied to finance. These statistical materials are crucial to learning asset pricing, which often applies statistical tests to evaluate different asset pricing models.
Intuitive Human Interfaces for Organizing and Accessing Intellectual Assets ; International Workshop, Dagstuhl Castle, Germany, March 1-5, 2004, Revised Selected Papers
This book constitutes the thoroughly refereed post-proceedings of the 2004 International Workshop on Intuitive Human Interfaces for Organizing and Accessing Intellectual Assets, held in Dagstuhl Castle, Germany in March 2004. The 17 revised full papers presented together with an introductory overview have gone through two rounds of reviewing and revision. The papers are organized in topical sections on man-machine interface for intuitive knowledge access, intelligent pad and meme media, visualization and design of information access spaces, and semantics and narrative organization and access of knowledge.
Introduction to the theory of computation
Gain a solid understanding of the fundamental mathematical properties of computer hardware, software, and applications with a blend of practical and philosophical coverage and mathematical treatments, including advanced theorems and proofs.
