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Designing an adaptive QOS-oriented and secure framework for wireless sensor networks in emergency situation

Journal of Theoretical and Applied Information Technology 2012年第1期42卷 59-69页

作者： Haji, Rachid Ghallali, Mohamed Hasbi, Abderrahim El Ouahidi, Bouabid Network Team and Intelligent Systems Laboratory Mohammed V University Mohammadia School of Engineering Rabat Morocco Data Mining and Network Laboratory Mohammed V University Faculty of Sciences Rabat Morocco

The most important factor characterizing an emergency situation is the lack of information or the difficult access to it. The use of wireless sensor networks (WSN) in this type of applications allows having an almost real-time status of the supervised area by collecting relevant information and thus assisting in the process of rapid response to the disaster. In such cases, the information availability, reliability, security and delay of its delivery are critical to the success of rescue operations. In this paper we design a new Framework Ad-M-QoS-DS (Adaptive Management of QoS in different situations) that permits an adaptive management according to the QoS requirements of each situation in the supervised area by grouping multiple modules and parameters. Next, we have proposed a Sensor Security Module (SSM) for our Framework to dispute sensor security challenges and describe the role of its components. At the end of the paper, we implement the proposed Module within the Base Station (BS). © 2005-2012 JATIT & LLS.

关键词： Quality of service

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Biologically inspired intrinsically motivated learning for service robots based on novelty detection and habituation

Biologically inspired intrinsically motivated learning for s...

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IEEE International Conference on Robotics and Biomimetics

作者： Yiannis Gatsoulis Chris Burbridge T. Martin McGinnity Intelligent Systems Research Centre Faculty of Computing and Engineering University of Ulster Derry UK Intelligent Robotics Laboratory School of Computer Science University of Birmingham Birmingham UK

The effective operation of service robots relies on developmental programs that allow the robot to expand its knowledge about its dynamic operating environment. Motivation theories from neuroscience and neuropsychology study the underlying mechanisms that drive the engagement of biological creatures to certain activities, such as learning. This research uses a physical Willow Garage PR2 robot, which is equipped with a cumulative learning mechanism driven by the intrinsic motivation of novelty detection based on computational models of biological habituation. It cumulatively learns the 360° appearance of novel real-world objects by picking them up. This paper discusses the theoretical motivations and background information on intrinsic motivations as novelty detection. The results and conclusions from the experimental study are presented.

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Mental Ontology model for medical diagnosis based on some intuitionistic fuzzy functions

Mental Ontology model for medical diagnosis based on some in...

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International Symposium on intelligent systems and Informatics (SISY)

作者： Hamido Fujita Imre J. Rudas Faculty of Software and Information Science Iwate Prefectural University Takizawa Iwate Japan Institute of Intelligent Engineering Systems Óbuda University Budapest Hungary

This paper extends reasoning issues on medical diagnosis related to Virtual Doctor System (VDS). Intuitionistic fuzzy aggregation functions have been used to represent concept reflective to the mental model of the VDS. The VDS project used two physical ontology model and mental ontology model aligned on medical ontology for reasoning. In this paper the mental ontology related to medical diagnosis is the main emphasis. The mental Ontology is represented as two models: Emotion state model, and ego state model. The attributes of mental state are represented as fuzzy intuitionistic criteria. The emotion state related attributes are represented using harmonic hybrid weighted Ordered Intuitionistic fuzzy aggregation function. The ego state related attributes are represented using Bonferroni ordered weight average aggregate function. The both aggregate functions as well as the physical ontology aggregate functions are aligned on medical knowledge based. The model is built for testing.

关键词： Ontologies Medical services Humans Avatars Medical diagnostic imaging Cognition Decision making

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NeNMF: An Optimal Gradient Method for Nonnegative Matrix Factorization

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IEEE Transactions on Signal Processing 2012年第6期60卷 2882-2898页

作者： Naiyang Guan Dacheng Tao Zhigang Luo Bo Yuan School of Computer Science National University of Defense Technology Changsha China Center for Quantum Computation and Intelligent Systems and the Faculty of Engineering and Information Technology University of Technology Sydney NSW Australia Department of Computer Science and Engineering Shanghai Jiaotong University Shanghai China

Nonnegative matrix factorization (NMF) is a powerful matrix decomposition technique that approximates a nonnegative matrix by the product of two low-rank nonnegative matrix factors. It has been widely applied to signal processing, computer vision, and data mining. Traditional NMF solvers include the multiplicative update rule (MUR), the projected gradient method (PG), the projected nonnegative least squares (PNLS), and the active set method (AS). However, they suffer from one or some of the following three problems: slow convergence rate, numerical instability and nonconvergence. In this paper, we present a new efficient NeNMF solver to simultaneously overcome the aforementioned problems. It applies Nesterov's optimal gradient method to alternatively optimize one factor with another fixed. In particular, at each iteration round, the matrix factor is updated by using the PG method performed on a smartly chosen search point, where the step size is determined by the Lipschitz constant. Since NeNMF does not use the time consuming line search and converges optimally at rate in optimizing each matrix factor, it is superior to MUR and PG in terms of efficiency as well as approximation accuracy. Compared to PNLS and AS that suffer from numerical instability problem in the worst case, NeNMF overcomes this deficiency. In addition, NeNMF can be used to solve -norm, -norm and manifold regularized NMF with the optimal convergence rate. Numerical experiments on both synthetic and real-world datasets show the efficiency of NeNMF for NMF and its variants comparing to representative NMF solvers. Extensive experiments on document clustering suggest the effectiveness of NeNMF.

关键词： Gradient methods Convergence Matrix decomposition Sparse matrices Least squares approximation Educational institutions

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Network-based subsumption architecture for multiple mobile robots system

Network-based subsumption architecture for multiple mobile r...

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International Symposium on Soft Computing and intelligent systems (SCIS)

作者： Fusaomi Nagata Akimasa Otsuka Keigo Watanabe Department of Mechanical Engineering Faculty of Engineering Tokyo University of Science Sanyo-Onoda Yamaguchi Japan Department of Intelligent Mechanical Systems Graduate School of Natural Science and Technology Okayama University Okayama Japan

In this paper, a unique multiple mobile robots system is proposed to enable students or mechanical engineers to efficiently learn a subsumption architecture for swarm intelligence. The subsumption architecture is known as one of the behaviour-based artificial intelligences. Each of multiple mobile robots has three wheels driven by DC motors and six PSD (Position Sensitive Detector) sensors. A network-based subsumption architecture is considered to realize a schooling behaviour by using only information from the PSD sensors. Further, a server supervisory control is introduced for poor hardware platforms with limitations of software development, i.e., the mobile robots that can only behave based on the most simply subdivided reaction behaviours, i.e., reflex actions, generated from agents. Experimental results show interesting behaviour among the multiple mobile robots, such as following, avoidance and schooling.

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Transductive cartoon retrieval by multiple hypergraph learning

Transductive cartoon retrieval by multiple hypergraph learni...

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19th International Conference on Neural Information Processing, ICONIP 2012

作者： Yu, Jun Cheng, Jun Wang, Jianmin Tao, Dacheng Computer Science Department Xiamen University Xiamen 361005 China Shenzhen Institues of Advanced Technology Chinese Academy of Sciences Shenzhen China Chinese University of Hong Kong Shatin Hong Kong Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney NSW Australia

ISBN: (纸本)9783642344862

Cartoon characters retrieval frequently suffers from the distance estimation problem. In this paper, a multiple hypergraph fusion based approach is presented to solve this problem. We build multiple hypergraphs on cartoon characters based on their features. In these hypergraphs, each vertex is a character, and an edge links to multiple vertices. In this way, the distance estimation between characters is avoided and the high-order relationship among characters can be explored. The experiments of retrieval are conducted on cartoon datasets, and the results demonstrate that the proposed approach can achieve better performance than state-of-the-arts methods. © 2012 Springer-Verlag.

关键词： Graph theory

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Object placement planner for robotic pick and place tasks

Object placement planner for robotic pick and place tasks

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2012 IEEE/RSJ International Conference on intelligent Robots and systems

作者： K. Harada T. Tsuji K. Nagata N. Yamanobe H. Onda T. Yoshimi Y. Kawai Intelligent Systems Research Institute National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Japan Faculty of Information Science and Electrical Engineering Kyushu University Fukuoka Japan

ISBN: (纸本)9781467317375

This paper proposes an object placement planner for a grasped object during pick-and-place tasks. The proposed planner automatically determines the pose of an object stably placed near a user assigned point on an environment surface. The proposed method first constructs a polygon model of the surrounding environment, and then clusters the polygon model of both the environment and the object where each cluster is approximated by a planar region. The placement of the object can be determined by selecting a pair of clusters between the object and the environment. We further impose several conditions to determine the pose of the object placed on the environment. We show that we can determine the position/orientation of the object placed on the environment for several cases such as hanging a mug cup on a bar. The effectiveness of the proposed research is confirmed through several numerical examples.

关键词： Robots Search problems Planning Vectors Clustering algorithms Clustering methods Stability analysis

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Enlarging output of high torque controllable clutch using ER gel

Enlarging output of high torque controllable clutch using ER...

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2012 9th IEEE International Conference on Mechatronics and Automation, ICMA 2012

作者： Takata, Yudai Koyanagi, Ken'ichi Anzai, Hidenobu Sakurai, Koji Kakinuma, Yasuhiro Motoyoshi, Tatsuo Oshima, Toru Department of Intelligent Systems Design Engineering Toyama Prefectural University Kurokawa 5180 Imizu Toyama Japan Fujikura Kasei Co. Ltd. 5-3-1 Sakurada Kuki Saitama Japan Faculty of Science and Technology Keio University 3-14-1 Hiyoshi Kohoku Yokohama Japan

ISBN: (纸本)9781467312776

This study is concerned with the development of an Electro-Rheological (ER) Gel Linear Actuator (ERGLA) as the principle component of a high torque controllable clutch that has applications in robots that coexist with humans. Applying the ER gel to clutches in force transmission assembly decreases the inertia and mechanical limit of the maximum speed, enabling keeping high controllability. This paper focuses on enlarging the output torque of the clutch with ER gels, which is a the main part of the ERGLA. © 2012 IEEE.

关键词： Functional materials

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Towards an adaptive QoS-oriented and secure framework for wireless sensor networks in emergency situations

Towards an adaptive QoS-oriented and secure framework for wi...

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IEEE International Conference on Multimedia Computing and systems (ICMCS)

作者： Rachid Haji Abderrahim Hasbi Mohamed Ghallali Bouabid El Ouahidi Network Team and Intelligent Systems Laboratory Mohammadia School of Engineering Mohammed V University Rabat Morocco Data Mining and Network Laboratory Faculty of Sciences Mohammed V University Rabat Morocco

ISBN: (纸本)9781467315180

In an emergency situation, the information availability, reliability, security and delay of its delivery are critical to the success of rescue operations. The use of wireless sensor networks (WSN) in this type of applications allows having an almost real situation about the supervised area by collecting relevant information. This paper proposes a new Framework Ad-M-QoS-DS (Adaptive Management of QoS in different situations) that permits an adaptive management according to the QoS requirements of each situation in the supervised area by grouping multiple parameters. The proposed Framework Ad-MQoS-DS includes security architecture based on the base station.

关键词： Wireless sensor networks Sensors Quality of service Security Base stations Reliability Ad hoc networks

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Pusher reheating furnace control via fuzzy-neural model predictive control synthesis

Pusher reheating furnace control via fuzzy-neural model pred...

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2012 6th IEEE International Conference intelligent systems, IS 2012

作者： Stojanovski, Goran Stankovski, Mile Rudas, Imre J. Jing, Juanwei Faculty of Electrical Eng. and Information Technologies Karpos 2 SS Cyril and Methodius University Skopje MK-1000 Macedonia Institute of Intelligent Engineering Systems Óbuda University Bécsi út 96/B H-1034 Budapest Hungary College of Information Science Engineering Institute of Control Theory Navigation Technology Northeastern University Shenyang Liaoning 100006 China

ISBN: (纸本)9781467327824

A design of fuzzy model-based predictive control for industrial furnaces has been derived and applied to the model of three-zone 25 MW RZS pusher furnace at Skopje Steelworks. The fuzzy-neural variant of Sugeno fuzzy model, as an adaptive neuro-fuzzy implementation, is employed as a predictor in a predictive controller. In order to build the predictive controller the adaptation of the fuzzy model using dynamic process information is carried out. Optimization procedure employing a simplified gradient technique is used to calculate predictions of the future control actions. © 2012 IEEE.

关键词： Optimization

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