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IEEE Swarm Intelligence Symposium, SIS

作者： Yiheng Wang Alei Liang Haibing Guan School of Software Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiaotong University Shanghai China Department of Computer Science and Engineering Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiaotong University Shanghai China

Exploring an unknown environment using team of autonomous mobile robots is an important task in many real-world applications. Many existing map exploration algorithms are based on frontier, which is the boundary between unexplored space and known open space. In the context of multiple robots, the main problem of frontier-based algorithm is to choose appropriate target points for the individual robots so that they can efficiently explore the different part of the common area. This paper proposed a novel distributed frontier-based map exploration algorithm using Particle Swarm Optimization model for robot coordination. In this algorithm, the robot keeps moving to the nearby frontier to reduce the size of the unknown region, and is navigated towards frontier far away based on the PSO model after exploring the local area. The exploration is completed when there are no frontier cells on the map. Our algorithm has been implemented and tested both in simulation runs and real world experiment. The result shows that our method has a good scalability and efficiency.

关键词： Legged locomotion Robot kinematics Collision avoidance Algorithm design and analysis Robot sensing systems Redundancy

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A framework for efficient data analytics through automatic configuration and customization of scientific workflows

A framework for efficient data analytics through automatic c...

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7th IEEE International Conference on eScience, eScience 2011

作者： Hauder, Matheus Gil, Yolanda Liu, Yan Institute for Software and Systems Engineering University of Augsburg Universitätsstraße 6a Augsburg D 86135 Germany Information Sciences Institute University of Southern California 4676 Admiralty Way Marina del Rey CA 90292 United States Computer Science Department University of Southern California 941 Bloom Walk Los Angeles CA 90089-0781 United States

ISBN: (纸本)9780769545974

Data analytics involves choosing between many different algorithms and experimenting with possible combinations of those algorithms. Existing approaches however do not support scientists with the laborious tasks of exploring the design space of computational experiments. We have developed a framework to assist scientists with data analysis tasks in particular machine learning and data mining. It takes advantage of the unique capabilities of the Wings workflow system to reason about semantic constraints. We show how the framework can rule out invalid workflows and help scientists to explore the design space. We demonstrate our system in the domain of text analytics, and outline the benefits of our approach. © 2011 IEEE.

关键词： Data mining

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Energy-aware data processing techniques for wireless sensor networks: A review

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2011年 6790 LNCS卷 117-137页

作者： Chong, Suan Khai Gaber, Mohamed Medhat Krishnaswamy, Shonali Loke, Seng Wai Centre for Distributed Systems and Software Engineering Monash University 900 Dandenong Rd Caulfield East VIC 3145 Australia School of Computing University of Portsmouth Portsmouth Hampshire PO1 3HE United Kingdom Department of Computer Science and Computer Engineering La Trobe University Victoria 3086 Australia

ISBN: (纸本)9783642230738

Extensive data generated by peers of nodes in wireless sensor networks (WSNs) needs to be analysed and processed in order to extract information that is meaningful to the user. Data processing techniques that achieve this goal on sensor nodes are required to operate while meeting resource constraints such as memory and power to prolong a sensor network's lifetime. This survey serves to provide a comprehensive examination of such techniques, enabling developers of WSN applications to select and implement data processing techniques that perform efficiently for their intended WSN application. It presents a general analysis of the issue of energy conservation in sensor networks and an up-to-date classification and evaluation of data processing techniques that have factored in energy constraints of sensors. © 2011 Springer-Verlag Berlin Heidelberg.

关键词： Sensor nodes

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Towards runtime testing in automotive embedded systems

Towards runtime testing in automotive embedded systems

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International Symposium on Industrial Embedded systems

作者： C. Bradatsch T. Ungerer R. Zalman A. Lajtkep Systems and Networking Department of Computer Science University of Augsburg Augsburg Germany Automotive Electronics Microcontroller Development-System & Software Engineering Infineon Technologies Neubiberg Germany Electrics/Electronics and Driver Environment Platform Technologies Software and AUTOSAR BMW Group Munich Germany

Runtime testing is a common way to detect faults during normal system operation. To achieve a specific diagnostic coverage runtime testing is also used in safety critical, automotive embedded systems. In this paper we propose a test architecture to consolidate the hardware resource consumption and timing needs of runtime tests and of application and system tasks in a hard real-time embedded system as applied to the automotive domain. Special emphasis is put to timing requirements of embedded systems with respect to hard real-time and concurrent hardware resource accesses of runtime tests and tasks running on the target system.

关键词： Circuit faults Testing Runtime Hardware Safety Automotive engineering Embedded systems

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Reports of the AAAI 2010 fall symposia

Reports of the AAAI 2010 fall symposia

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作者： Azevedo, Roger Biswas, Gautam Bohus, Dan Carmichael, Ted Finlayson, Mark A. Hadzikadic, Mirsad Havasi, Catherine Horvitz, Eric Kanda, Takayuki Koyejo, Oluwasanmi Lawless, William F. Lenat, Doug Meneguzzi, Felipe Mutlu, Bilge Oh, Jean Pirrone, Roberto Raux, Antoine Sofge, Donald A. Sukthankar, Gita Van Durme, Benjamin Yorke-Smith, Neil Department of Educational and Counseling Psychology McGill University Canada Center for Intelligent Systems Vanderbilt University United States Microsoft Research Redmond United States Department of Software and Information Systems University of North Carolina Charlotte United States Complex Systems Institute United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology United States Media Lab. Massachusetts Institute of Technology United States ATR Intelligent Robotics and Communication Laboratories Kyoto Japan Department of Electrical and Computer Engineering University of Texas Austin United States Department of Mathematics Paine College Augusta GA United States Cycorp Austin TX United States Robotics Institute Carnegie Mellon University United States Department of Computer Sciences University of Wisconsin Madison United States University of Palermo Italy Honda Research Institute United States Navy Center for Applied Research in Artificial Intelligence Naval Research Laboratory Washington DC United States Department of Electrical Engineering and Computer Science University of Central Florida United States Department of Computer Science Johns Hopkins University United States American University of Beirut Lebanon SRI International's Artificial Intelligence Center United States

The Association for the Advancement of Artificial Intelligence (AAAI) presented the 2010 Fall Symposium Series on November 11-13, 2010. The eight symposia included Cognitive and Metacognitive Educational systems, Commonsense Knowledge, Complex Adaptive systems: Resilience, Robustness, and Evolvability, Computational Models of Narrative, Dialog with Robots, Manifold Learning and Its Applications, Proactive Assistant Agents and Quantum Informatics for Cognitive, Social, and Semantic Processes. Cognitive and Metacognitive Educational systems aimed to provide a comprehensive definition of metacognitive educational systems that is inclusive of the theoretical, architectural, and educational aspects of this field. The AAAI Commonsense Knowledge Fall Symposium had the goal of bringing together the diverse elements of this community whose work benefits from or contributes to the representation of general knowledge about the world. One of the specific goals of Proactive symposium was to gather the researchers from various projects in assistant agents to share their wisdom in retrospect.

关键词： Semantics

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MIND: A black-box energy consumption model for disk arrays

MIND: A black-box energy consumption model for disk arrays

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International Green Computing Conference

作者： Zhuo Liu Jian Zhou Weikuan Yu Fei Wu Xiao Qin Changsheng Xie Key Laboratory of Data Storage Systems Ministry of Education Wuhan National Laboratory for Optoelectronics School of Computer Science and Technology Huazhong University of Science and Technology Wuhan Hubei China Department of Computer Science & Software Engineering Aubum University AL USA

Energy consumption is becoming a growing concern in data centers. Many energy-conservation techniques have been proposed to address this problem. However, an integrated method is still needed to evaluate energy efficiency of storage systems and various power conservation techniques. Extensive measurements of different workloads on storage systems are often very time-consuming and require expensive equipments. We have analyzed changing characteristics such as power and performance of stand-alone disks and RAID arrays, and then defined MIND as a black box power model for RAID arrays. MIND is devised to quantitatively measure the power consumption of redundant disk arrays running different workloads in a variety of execution modes. In MIND, we define five modes (idle, standby, and several types of access) and four actions, to precisely characterize power states and changes of RAID arrays. In addition, we develop corresponding metrics for each mode and action, and then integrate the model and a measurement algorithm into a popular trace tool - blktrace. With these features, we are able to run different IO traces on large-scale storage systems with power conservation techniques. Accurate energy consumption and performance statistics are then collected to evaluate energy efficiency of storage system designs and power conservation techniques. Our experiments running both synthetic and real-world workloads on enterprise RAID arrays show that MIND can estimate power consumptions of disk arrays with an error rate less than 2%.

关键词： Power measurement Benchmark testing Throughput

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Value-transformation for monotone prediction by approximating fuzzy membership functions

Value-transformation for monotone prediction by approximatin...

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International Symposium on Computational Intelligence and Informatics

作者： Tomáš Horváth Alan Eckhardt Krisztián Buza Peter Vojtáš Lars Schmidt-Thieme Institute of Computer Science Pavol Jozef Safarik University in Kosice Slovakia Information Systems and Machine Learning Lab University of Hildesheim Germany Department of Software Engineering Charles University in Prague Czech Republic Department of Computer Science and Information Theory Budapest University of Technology and Economics Hungary

Monotone prediction problems, in which the target variable is non-decreasing given an increase of the explanatory variables, have became more popular nowadays in many problem settings which fulfill the so-called monotonicity constraint, namely, if an object is better in all attributes as another one then it should not be classified lower. Recent approaches to monotone prediction consider linear ordering on attribute domains, thus the meaning of being better in an attribute is limited to having a larger or a lower value in that attribute. However, this limitation restricts the use of recent approaches in cases where middle or marginal values of an attribute are better, what is natural in many real-world scenarios. We present a simple attribute value-transformation approach in this paper. The idea is to map attribute domains to real values where the mapped values express how the given value of an attribute contributes to higher classification of objects. Thus, we are searching for an data-specific approximation of a fuzzy membership function on the domain of each (numerical) attribute. Then, instead of the original attribute values we use their mapped values to mitigate the violation of monotonicity constraints in the data. Our approach is quite simple and is not limited to numerical attributes only. The described approach was tested and evaluated on benchmark datasets from the UCI machine learning repository.

关键词： Prediction algorithms Labeling Noise Machine learning Correlation Approximation methods Electronic mail

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Author Index Volume 7 (2011)

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Multiagent and Grid systems 2011年第6期7卷 311-313页

作者： [ Systems Research Institute Polish Academy of Sciences Warsaw and University of Gdansk Warsaw Poland Systems Research Institute Polish Academy of Sciences Warsaw and Management Academy Warsaw Poland Software Engineering Department Faculty of Automatics Computers and Electronics University of Craiova Bvd.Decebal Craiova Romania University of Duisburg-Essen Institute for Computer Science and Business Information Systems (ICB) Practical Computer Science Data Management Systems and Knowledge Representation Essen Germany

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A CSMA-based approach for detecting composite data aggregate events with collaborative sensors in WSN

A CSMA-based approach for detecting composite data aggregate...

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International Conference on computer Supported Cooperative Work in Design

作者： Chi Yang Kaijun Ren Zhimin Yang Peng Gong Chang Liu School of Computer Science and Software Engineering University of Western Australia Crawley WA Australia College of Computer National University of Defense Technology Changsha Hunan China Department of Computer Shandong University Weihai China Anhui Wenda Information and Technology College Hefei Anhui China CS3-Centre of Complex Software Systems and Services Swinburne University of Technology Melbourne Australia

Nowadays, wireless sensor networks are widely used to monitor real time events and answer the ad hoc queries from a certain member node. However, computing and maintaining the information of aggregate queries in event monitoring wireless sensor networks incurs high spatial and temporal overhead for storage and transmission where potentially high volumes of unnecessary data may run through with changing time. Failure of processing that data can lead to unsuccessful event detection which can be very dangerous and costly in real world application. In order to reduce the overhead caused by unnecessary data for aggregate, suppression techniques such as data fusion, data sharing, data prediction, lossless data compression and base station side query rewriting are widely discussed in the WSN research community. In this paper, a technique which makes use of the spatial data relationship of local sensor nodes collaboratively is proposed to rein the detection of composite events with data aggregate. An empirical study is carried out to show the efficiency of the new technique. In addition, the new algorithm is compared to the previous event detection algorithms without spatial data suppression technique to demonstrate the significant performance gains.

关键词： Aggregates Event detection Peer to peer computing Sensor phenomena and characterization Monitoring

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2D Simulator for Eddy Current Field Filters

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Procedia engineering 2011年 25卷 427-430页

作者： F. Liakou P. Dimitropoulos G. Stamoulis Center For Research and Technology Thessaly Technology Park Volos 38500 Greece SENSAP Microsystems Electronic Systems and Software Applications SA Ydras 2 Athens 18346 Greece University of Thessaly Computer & Communications Engineering DepartmentGlavani 37 Volos 38221 Greece

Hall devices are magnetic field current sensors based on the Hall effect. A bias current is applied via contacts through the Hall plates which are placed along magnetic field. High frequency components affect the Hall plates in a non- linear manner, disturbing the uniform biasing current flow. This problem can be alleviated by the development of a flux shaping device. A CAD tool is presented here, which can simulate the behavior of shields with different shape in order to choose the one that may be optimally used.

关键词： Eddy Current Hall Plate Magnetic Field Simulator

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