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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Luca Pasolli Claudia Notarnicola Lorenzo Bruzzone Giacomo Bertoldi Georg Niedrist Ulrike Tappeiner Marc Zebish Fabio Del Frate Gaia Vaglio Laurin Department of Information Engineering and Computer Science University of Trento Trento Italy Institute for Applied Remote Sensing EURAC Research Bolzano Italy Institute for Alpine Environment EURAC Research Bolzano Italy Department of Computer System and Production Engineering Tor Vergata University Rome Italy

In this work, fully polarimetric RADARSAT2 SAR images and advanced feature extraction strategies are investigated for improving the retrieval of soil moisture content in Alpine meadows and pastures. More in detail, standard Intensity & Phase polarimetric features, polarimetric decompositions and general purpose feature extraction strategies are exploited in combination with a sequential forward selection to increase the accuracy of the system. The capability of the system to provide spatially and temporally distributed estimates of soil moisture is also addressed by using different satellite acquisitions. The achieved results indicate that the polarimetric information in the SAR data, if properly exploited, allows one to improve the estimation of soil moisture content in the investigated mountain area. Concerning the mapping of the target variable, the analysis of the results suggest that the proposed estimation system is promising and effectively maps the soil moisture status both in time and space.

关键词： Feature extraction Estimation Soil moisture Synthetic aperture radar Data mining Remote sensing

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Network management in collective intelligent robotic environment

Network management in collective intelligent robotic environ...

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International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Dong-Bum Kim Chang-Eun Lee Hyun-Ja Im Seung-Ik Lee Young-Jo Cho Sung-Hoon Kim Department of Computer Software and Engineering University of Science and Technology Dae-jeon Korea Department of Robot/Cognitive System Research Electronics and Telecommunications Research Institute Dae-jeon Korea Department of Robot/Cognitive System Research Electronics and Telicommunications Research Institute Daejeon South Korea

ISBN: (纸本)9781457707223

In collective intelligent robotic environment, robots typically behaves in communication with each other to achieve the global intelligent goal. In general, a collective intelligent robotic system works based on a backbone-less ad-hoc network. For controlling robots in that environment, several issues are raised in the system: action control, environment recognition, robot networking, and system supervisor control. The collective intelligent robot system is quite different from general multi-robot systems in the viewpoint of networking, since it should show intelligence collectively with different types of networked robots. That is, the existing network systems do not work well in the collective intelligent robotic environment. We propose an ad-hoc network system with two essential components, routing manager and topology manager, suitable for the collective intelligent robotic environment.

关键词： Collective Intelligent Robot Multi-Robot Networking Network Management Router Manager Topology Manager Network management Robot manager Robot system Environments Ad hoc networks Networking Network robot Comment

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Near-infrared based nighttime pedestrian detection by combining multiple features

Near-infrared based nighttime pedestrian detection by combin...

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International Conference on Intelligent Transportation

作者： Yu-Chun Lin Yi-Ming Chan Luo-Chieh Chuang Li-Chen Fu Shih-Shinh Huang Pei-Yung Hsiao Min-Fang Luo Intelligent Robot and Automation Laboratory Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan National Taiwan University Taipei TW Department of Computer and Communication Engineering National Kaohsiung First University of Science and Technology Kaohsiung Taiwan Department of Electrical Engineering National University of Kaohsiung Kaohsiung Taiwan System development center Chung-Shan Institute of Science and Technology Longtan Shaiang Taoyuan Taiwan

Pedestrian detection is important in the computer vision field. In the nighttime, pedestrian detection is even more valuable. In this paper, we address the issue of detecting pedestrians in video streams from a moving camera at nighttime. Most nighttime human detection approaches only use single feature extracted from images. The effective image features in daytime environment may suffer from textureless, high contrast and low light problems at night. To deal with these issues, we first segment the foreground by using the proposed Smart Region Detection approach to generate candidates. Then we design a nighttime pedestrian detection system based on the AdaBoost and the support vector machine (SVM) classifiers with contour and histogram of oriented gradients (HOG) features to effectively recognize pedestrians from those candidates. Combining different type of complementary features improve the detection performance. Results show that our pedestrian detection system is promising in the nighttime environment.

关键词： Feature extraction Image segmentation Cameras Humans Databases Lighting Support vector machines

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Solving Constrained Optimization Problems by an Improved Particle Swarm Optimization

Solving Constrained Optimization Problems by an Improved Par...

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International Conference on Innovations in Bio-inspired Computing and Applications (IBICA)

作者： Chaoli Sun Jianchao Zeng Shuchuan Chu John F. Roddick Jengshyang Pan Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Taiyuan Shanxi China School of Computer Science Engineering and Mathematics Flinders University Australia Department of Electronic Engineering National Kaohsiung University of Applied Sciences Kaohsiung Taiwan

Constrained optimization problems compose a large part of real-world applications. More and more attentions have gradually been paid to solve this kind of problems. An improved particle swarm optimization (IPSO) algorithm based on feasibility rules is presented in this paper to solve constrained optimization problems. The average velocity of the swarm and the best history position in the particle's neighborhood are introduced as two turbulence factors, which are considered to influence the fly directions of particles, into the algorithm so as not to converge prematurely. The performance of IPSO algorithm is tested on 13 well-known benchmark functions. The experimental results show that the proposed IPSO algorithm is simple, effective and highly competitive.

关键词： Optimization Particle swarm optimization Algorithm design and analysis Convergence History Educational institutions

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A Method for Detecting Unknown Malicious Executables

A Method for Detecting Unknown Malicious Executables

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Boris Rozenberg Ehud Gudes Yuval Elovici Yuval Fledel Deutche Telekom Laboratories at BGU and Department of Computer Science Ben Gurion University Beersheva Israel Deutche Telekom Laboratories at BGU and Department of Information System Engineering Ben Gurion University Beersheva Israel

We present a method for detecting new malicious executables, which comprise the following steps: (a) in an offline training phase, finding a set of (not necessary consecutive) system call sequences that are characteristic only to malicious files, when such malicious files are executed, and storing said sequences in a database; (b) in a real time detection phase, for each running executable, continuously monitoring its issued system calls and comparing with the stored sequences of system calls within the database to determine whether there exists a match between a portion of the sequence of the run-time system calls and one or more of the database sequences, and when such a match is found, declaring said executable as malicious. We have evaluated our method and the preliminary results are promising and justify the use of system calls sequences for the purpose of detection of new malicious executables.

关键词： Malware Databases Genetic algorithms Training Monitoring Real time systems Accuracy

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Model Predictive Control of Type 1 Diabetes added to Conventional Therapy

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IFAC Proceedings Volumes 2011年第1期44卷 7108-7113页

作者： L. Magni C. Toffanin C. Dalla Man B. Kovatchev C. Cobelli G. De Nicolao Department of Computer Engineering and Systems Science University of Pavia via Ferrata 1 I-27100 Pavia Italy Department of Information Engineering University of Padova Via Gradenigo 6/B I-35131 Padova Italy University of Virginia Health System Box 800137 Charlottesville VA 22908 USA

Abstract Recent technological advancements in subcutaneous glucose monitoring and subcutaneous insulin delivery systems have stimulated the development of closed-loop systems for maintaining normoglycaemia in Type I diabetes. The main obstacle to satisfactory closed-loop control is the presence of disturbances (e.g. meals and physical activity), delays, pump limitation, sensor noise and inter-variability. A Model Predictive Control ( MPC ) strategy has been applied in a clinical study at the University of Virginia, Padova and Montpellier covering night and breakfast on 20 patients. Night regulation was very satisfactory, while breakfast compensation was slightly worse than with a conventional therapy. This was due to the trade-off in the tuning of the cost function between prompt meal reaction and attenuation of measurement noise. In order to overcome this limitation, in this paper an MPC algorithm added to a conventional therapy is described. In this way all the knowledge incorporated in the (personalized) open-loop therapy is used as a feedforward term while the MPC controller is a feedback correction that guarantees robustness with respect to model uncertainty and incomplete meal knowledge. Finally a procedure for tuning the regulator aggressiveness as a function of few clinical parameters (carbo-ratio and basal insulin delivery) is described.

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Tracking end-users in web databases

Tracking end-users in web databases

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International Conference on Network and system Security, NSS

作者： Boris Rozenberg Yaron Gonen Ehud Gudes Nurit Gal-Oz Erez Shmueli Deutche Telekom Laboratories at BGU and Department of Computer Science Ben Gurion University Beersheva Israel Deutche Telekom Laboratories at BGU and Department of Information System Engineering Ben Gurion University Beersheva Israel

When a database is accessed via a web application, users usually receive a pooled connection to the database. From a database point of view, such a connection is always established by the same user (i.e. the web application) and specific data on the end user is not available. As a consequence, users' specific transactions cannot be audited and fine-grained access control cannot be enforced at the database level. In this paper we propose a method and a system which provide the ability to track the end users in web databases. The new method can be applied to legacy web applications without requiring any changes in their existing infrastructure. Furthermore, the new users tracking ability provides a basis for native database protection mechanisms, and intrusion detection systems.

关键词： Databases Training Access control Fingerprint recognition Web servers

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A neuro fuzzy PI controller used for speed control of a direct torque to twelve sectors controlled induction machine drive

A neuro fuzzy PI controller used for speed control of a dire...

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IEEE International Conference on Multimedia Computing and systems (ICMCS)

作者： M. R. Douiri M. Cherkaoui T. Nasser A. Essadki Department of electrical engineering Mohammadia School of Engineers (EMI) Rabat Morocco Department Communication Networks National School of Computer Science and System Analysis ENSIAS Rabat Morocco Department electrical engineering Superior School of Technical Education ENSET Rabat Morocco

This paper presents a new speed controller based on the theory of adaptive fuzzy inference system based on neural (ANFIS) for a direct torque to twelve sectors controlled of the induction motor. The proposed controller integrates fuzzy logic algorithm with a structure of artificial neural network (ANN) five-layer in order to reap the benefits of both methods, the learning abilities of the first and readability and flexibility of the second. The controller replaces the conventional PI is the rule fuzzy inference system with the hybrid learning algorithm. This makes learning the fuzzy system. The performance of the proposed neuro-fuzzy control for induction motor speed was studied at different operating conditions. The simulation study shows the robustness and relevance of control for applications in high performance driving.

关键词： Torque Stators Neurons Torque control Inference algorithms Induction motors Switches

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Boxing Punch Analysis Using 3D Gyro Sensor

Boxing Punch Analysis Using 3D Gyro Sensor

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SICE Annual Conference

作者： Manabu Morita Kajiro Watanabe Kazuyuki Kobayashi Yousuke Kurihara Department of System Engineering Faculty of Engineering Hosei University Department of System Engineering Hosei University Department of Computer and Information Science Seikei University

ISBN: (纸本)9784907764388

The objective of this study was to discriminate different types of punches based on signals measured by gyro sensors. If a boxer consistently uses the same pattern of attack, his opponent could easily determine what type of punch is coming next. Thus, by feeding back information on the frequency of each type of punch, the attack pattern can be identified and the counterattack can be improved.

关键词： 3D gyro sensor Angular velocity Cross-correlation Boxing

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Creating granular learning object towards reusability of Learning Object in e-learning context

Creating granular learning object towards reusability of Lea...

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International Conference on Electrical engineering and Informatics, ICEEI

作者： Siti Fadzilah Mat Noor Norazah Yusof Siti Zaiton Mohd Hashim Universiti Kebangsaan Malaysia Bangi Selangor MY Software Engineering Department Faculty of Computer Science & Information System University Technology of Malaysia Universiti Teknologi Malaysia Skudai Johor MY

Learning Object (LO) is one of the main research topics in the e-learning community in the recent years, and most researchers pay attention to the issue of Learning Object Reusability. The most obvious motivation is the economic interest of reusing learning material instead of repeatedly authoring it. In this paper we present the process of creating granular learning object for enabling the reusing of LO in e-Learning context. Reusability requires the LO to be in a fine-grain form because raw media elements are often much easier to reuse then aggregate assemblies. In other words, as the LO size decreases (lower granularity), its potential for reuse increases. A prototype of learning objects repository that contain granular LO has been developed to show the process of granularizing LO. Each of existing LO will be extracted into granular element with the metadata and the system generated unique id for each LO based on its identifier (URL of LO) and save automatically the metadata contain in the LO. These metadata will be used for searching and retrieval process of the granule LO.

关键词： Materials Electronic learning XML Economics Context Educational institutions

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