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This book brings together for the first time the complete theory of data based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data based modelling new concepts including extended additive and multiplicative submodels are developed. All of these algorithms are illustrated with benchmark examples to demonstrate their efficiency. The book aims at researchers and advanced professionals in time series modelling, empirical data modelling, knowledge discovery, data mining and data fusion.
In recent years, there has been growing interest in industrial systems, especially in robotic manipulators and mobile robot systems. As the cost of robots goes down and become more compact, the number of industrial applications of robotic systems increases. Moreover, there is need to design industrial systems with intelligence, autonomous decision making capabilities, and self-diagnosing properties. Intelligent Industrial Systems: Modeling, Automation and Adaptive Behavior analyzes current trends in industrial systems design, such as intelligent, industrial, and mobile robotics, complex electromechanical systems, fault diagnosis and avoidance of critical conditions, optimization, and adaptive behavior. This book discusses examples from major areas of research for engineers and researchers, providing an extensive background on robotics and industrial systems with intelligence, autonomy, and adaptive behavior giving emphasis to industrial systems design.
2.1 Text Summarization “Text summarization is the process of distilling the most important information from a source (or sources) to produce an abridged version for a particular user (or users) and task (or tasks)” [3]. Basic and classical articles in text summarization appear in “Advances in automatic text summarization” [3]. A literature survey on information extraction and text summarization is given by Zechner [7]. In general, the process of automatic text summarization is divided into three stages: (1) analysis of the given text, (2) summarization of the text, (3) presentation of the summary in a suitable output form. Titles, abstracts and keywords are the most common summaries in Academic papers. Usually, the title, the abstract and the keywords are the first, second, and third parts of an Academic paper, respectively. The title usually describes the main issue discussed in the study and the abstract presents the reader a short description of the background, the study and its results. A keyword is either a single word (unigram), e.g.: ‘learning', or a collocation, which means a group of two or more words, representing an important concept, e.g.: ‘machine learning', ‘natural language processing'. Retrieving collocations from text was examined by Smadja [5] and automatic extraction of collocations was examined by Kita et al. [1].
Intelligent Control techniques are becoming important tools in both academia and industry. Methodologies developed in the field of soft-computing, such as neural networks, fuzzy systems and evolutionary computation, can lead to accommodation of more complex processes, improved performance and considerable time savings and cost reductions. Intelligent Control Systems using Computational Intellingence Techniques details the application of these tools to the field of control systems. Each chapter gives and overview of current approaches in the topic covered, with a set of the most important references in the field, and then details the author's approach, examining both the theory and practical applications.
Mechatronics represents a unifying interdisciplinary and intelligent engineering science paradigm that features an interdisciplinary knowledge area and interactions in terms of the ways of work and thinking, practical experiences, and theoretical knowledge. Mechatronics successfully fuses (but is not limited to) mechanics, electrical, electronics, informatics and intelligent systems, intelligent control systems and advanced modeling, intelligent and autonomous robotic systems, optics, smart materials, actuators and biomedical and biomechanics, energy and sustainable development, systems engineering, artificial intelligence, intelligent computer control, computational intelligence, precision engineering and virtual modeling into a unified framework that enhances the design of products and manufacturing processes. Interdisciplinary Mechatronics concerns mastering a multitude of disciplines, technologies, and their interaction, whereas the science of mechatronics concerns the invention and development of new theories, models, concepts and tools in response to new needs evolving from interacting scientific disciplines. The book includes two sections, the first section includes chapters introducing research advances in mechatronics engineering, and the second section includes chapters that reflects the teaching approaches (theoretical, projects, and laboratories) and curriculum development for under- and postgraduate studies. Mechatronics engineering education focuses on producing engineers who can work in a high-technology environment, emphasize real-world hands-on experience, and engage in challenging problems and complex tasks with initiative, innovation and enthusiasm. Contents: 1. Interdisciplinary Mechatronics Engineering Science and the Evolution of Human Friendly and Adaptive Mechatronics, Maki K. Habib. 2. Micro-Nanomechatronics for Biological Cell Analysis and Assembly, Toshio Fukuda, Masahiro Nakajima, Masaru Takeuchi, Tao Yue and Hirotaka Tajima. 3. Biologically Inspired CPG-Based Locomotion Control System of a Biped Robot Using Nonlinear Oscillators with Phase Resetting, Shinya Aoi. 4. Modeling a Human’s Learning Processes toward Continuous Learning Support System, Tomohiro Yamaguchi, Kouki Takemori and Keiki Takadama. 5. PWM Waveform Generation Using Pulse-Type Hardware Neural Networks, Ken Saito, Minami Takato, Yoshifumi Sekine and Fumio Uchikoba. 6. Parallel Wrists: Limb Types, Singularities and New Perspectives, Raffaele Di Gregorio. 7. A Robot-Assisted Rehabilitation System – RehabRoby, Duygun Erol Barkana and Fatih Özkul. 8. MIMO Actuator Force Control of a Parallel Robot for Ankle Rehabilitation, Andrew Mcdaid, Yun Ho Tsoi and Shengquan Xie. 9. Performance Evaluation of a Probe Climber for Maintaining Wire Rope, Akihisa Tabata, Emiko Hara and Yoshio Aoki. 10. Fundamentals on the Use of Shape Memory Alloys in Soft Robotics, Matteo Cianchetti. 11. Tuned Modified Transpose Jacobian Control of Robotic Systems, S. A. A. Moosavian and M. Karimi. 12. Derivative-Free Nonlinear Kalman Filtering for PMSG Sensorless Control, Gerasimos Rigatos, Pierluigi Siano and Nikolaos Zervos. 13. Construction and Control of Parallel Robots, Moharam Habibnejad Korayem, Soleiman Manteghi and Hami Tourajizadeh. 14. A Localization System for Mobile Robot Using Scanning Laser and Ultrasonic Measurement, Kai Liu, Hongbo Li and Zengqi Sun. 15. Building of Open-Structure Wheel-Based Mobile Robotic Platform, Aleksandar Rodic and Ivan Stojkovic. 16. Design and Physical Implementation of Holonomous Mobile Robot–Holbos, Jasmin Velagic, Admir Kaknjo, Faruk Dautovic, Muhidin Hujdur and Nedim Osmic. 17. Advanced Artificial Vision and Mobile Devices for New Applications in Learning, Entertainment and Cultural Heritage Domains, Gian Luca Foresti, Niki Martinel, Christian Micheloni and Marco Vernier. 18. Application of Stereo Vision and ARM Processor for Motion Control, Moharam Habibnejad Korayem, Michal Irani and Saeed Rafee Nekoo. 19. Mechatronics as Science and Engineering – or Both, Balan Pillai and Vesa Salminen. 20. A Mechatronic Platform for Robotic Educational Activities, Ioannis Kostavelis, Evangelos Boukas, Lazaros Nalpantidis and Antonios Gasteratos. 21. The Importance of Practical Activities in the Formation of Mechatronic Engineers, Joao Carlos M. Carvalho and Vera Lúcia D.S. Franco About the Authors Maki K. Habib is Professor of Robotics and Mechatronics in the School of Science and Engineering, at the American University in Cairo, Egypt. He has been regional editor (Africa/Middle East,) for the International Journal of Mechatronics and Manufacturing Systems (IJMMS) since 2010. He is the recipient of academic awards and has published many articles and books. J. Paulo Davim is Aggregate Professor in the Department of Mechanical Engineering at the University of Aveiro, Portugal and is Head of MACTRIB (Machining and Tribology Research Group). His main research interests include manufacturing, materials and mechanical engineering.
This monograph addresses problems of: • nonlinear control, estimation and filtering for robotic manipulators (multi-degree-of freedom rigid-link robots, flexible-link robots, underactuated, redundant and cooperating manipulators and closed-chain robotic mechanisms); and• nonlinear control, estimation and filtering for autonomous robotic vehicles operating on the ground, in the air, and on and under water, independently and in cooperating groups. The book is a thorough treatment of the entire range of applications of robotic manipulators and autonomous vehicles. The nonlinear control and estimation methods it develops can be used generically, being suitable for a wide range of robotic systems. Such methods can improve robustness, precision and fault-tolerance in robotic manipulators and vehicles at the same time as enabling the reliable functioning of these systems under variable conditions, model uncertainty and external perturbations.
The implementation of wireless sensor networks has wide-ranging applications for monitoring various physical and environmental settings. However, certain limitations with these technologies must be addressed in order to effectively utilize them. The Handbook of Research on Advanced Wireless Sensor Network Applications, Protocols, and Architectures is a pivotal reference source for the latest research on recent innovations and developments in the field of wireless sensors. Examining the advantages and challenges presented by the application of these networks in various areas, this book is ideally designed for academics, researchers, students, and IT developers.
Using MATLAB examples wherever possible, Multi-Sensor Data Fusion with MATLAB explores the three levels of multi-sensor data fusion (MSDF): kinematic-level fusion, including the theory of DF; fuzzy logic and decision fusion; and pixel- and feature-level image fusion. The authors elucidate DF strategies, algorithms, and performance evaluation mainly