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International Conference on Information Science and Engineering (ICISE)

作者： Liu Ming Junqi Zhang Yu Wang Jie Li Department of Computer Science and Technology The Key Laboratory of Embedded System and Service Computing Ministry of Education University of Tongji Shanghai China

ISBN: (纸本)9781424476169

Grid is a promising infrastructure which enables scientists and engineers to access geographically distributed resources. Grid computing is a new technology which focuses on aggregating various kinds of resource (e.g., processor cycles, disk storage, and contents) into one computing platform. The realization of grid computing requires a resource agent to manage and monitor available resources. Based on study of past models, this paper presents a new agent-based resource monitoring model whose main feature is multi-layered monitoring architecture, which enhances the ability to monitor related resource efficiently. In the meantime, the new model has been implemented in the development of a resource monitoring module integrated within a academic grid project.

关键词： Monitoring Computational modeling Databases Grid computing Automation Resource management XML

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Quantized H2 Filtering for Markovian Jump Linear systems over Networks with Non-accessible Mode Information

Quantized H2 Filtering for Markovian Jump Linear Systems ove...

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The 8th World Congress on Intelligent Control and Automation(第八届智能控制与自动化世界大会 WCICA 2010)

作者： Tao Liu Qijun Chen Hao Zhang Department of Electronics and Information Engineering Tongji University The Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China

This paper is concerned with the problems of quantized *** for discrete-time Markovian jump linear systems over networks with non-accessible mode information. The quantizer considered here is logarithmic quantizer. In this paper, a linear time-invariant mode-independent quantized *** is designed such *** error system is stochastically stable. *** conditions for the existence of *** is given in terms of linear matrix inequalities. A numerical example is provided to demonstrate the effectiveness of the proposed approach.

关键词： Quantization Bismuth Linear matrix inequalities Symmetric matrices Linear systems Upper bound Networked control systems

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Research on a Remote Network Monitoring Model for Large-scale Materials Manufacturing

Research on a Remote Network Monitoring Model for Large-scal...

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2011 International Conference on Advanced Materials and Computer Science(ICAMCS 2011)

作者： Xiaohui ZENG Manhua LI Wenlang LUO Department of Computer Science and Technology Jinggangshan University The Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University

A remote network monitoring model for large-scale materials manufacturing is proposed, including five modules: center control module, data collection and fault alarm module, graph drawing module and data storage module. The center control module not only interacts with users, but also controls the other four modules to work together in harmony. According to this monitoring model, a remote network monitoring platform is designed and realized. The user can interact with the control center module through an Internet browser, and the information about the monitored manufacturing machines and devices can be displayed by means of text, chart, graphic and sound, etc. Moreover, the details about the problems or faults from the monitored objects can be obtained in time. The experimental results indicate that the network monitoring platform can accurately get the information of the monitored objects, and users can conveniently get the online running state of those monitored objects.

关键词： remote network monitoring data storage fault alarm materials manufacturing

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A New One-Class Classification Method with Multiple Encoder-Decoder Pairs for Images

A New One-Class Classification Method with Multiple Encoder-...

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International Conference on Intelligent Human-Machine systems and Cybernetics, IHMSC

作者： Dongxiang Chen Chungang Yan Mimi Wang Department of Electronics and Information Engineering Tongji University The Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China

One of the main destinations of image classification methods is to screen out the images belonging to the target class (positive) and identify the images of other classes (negative). Although most classifiers are trained on both positive samples and negative samples, in reality, negative samples are often unavailable. One-class classifiers trained only on positive samples, are proposed to solve this problem. However, how to train effectively a classifier remains a daunting challenge. Considering the success of deep learning in the field of computer vision in recent years, we propose a one-class classification model for images based on convolutional neural network (CNN). The model consists of two parts of networks with different responsibilities. The network of the first part works as the discriminator, used to identify whether the images are positive. The networks of the second part, each of which consists of an encoder-decoder pair work as the guiders of the discriminator. They guide the discriminator to learn what images it should identify to be negative. Different encoder-decoder pairs can restore images to different degrees. Images restored to different degrees can be used to train the discriminator. The discriminator learns that images under a specific restored degree don't belong to the target class. The experiment results on CIFAR-10 show that our method can achieve good performance, with less difficulty in training than the GAN-based counterparts'.

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Lane Detection Method Based on Improved RANSAC Algorithm

Lane Detection Method Based on Improved RANSAC Algorithm

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International Symposium on Autonomous Decentralized systems (ISADAS)

作者： Jie Guo Zhihua Wei Duoqian Miao Ministry of Education Key Laboratory of Embedded System and Service Computing Shanghai China Department of Computer Science and Technology Tongji University

ISBN: (纸本)9781479982622

Lane detection based on computer vision is a key technology of Automatic Drive system for intelligent vehicles. In this paper, we propose a real-time and efficient lane detection algorithm that can detect lanes appearing in urban streets and highway roads under complex background. In order to enhance lane boundary information and to be suitable for various light conditions, we adopt canny algorithm for edge detection to get good feature points. We use the generalized curve lane parameter model, which can describe both straight and curved lanes. We propose an improved random sample consensus (RANSAC) algorithm combined with the least squares technique to estimate lane model parameters based on feature extraction. Experiments are conducted on both real road lane videos captured by Tongji University and Caltech Lane Datasets. The experimental results show that our algorithm is can meet the real time requirement and fit lane boundaries well in various challenging road conditions.

关键词： Feature extraction Roads Computational modeling Image edge detection Algorithm design and analysis Real-time systems Mathematical model

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keystroke dynamics in password authentication for multi-user account

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Journal of Computational Information systems 2015年第1期11卷 321-331页

作者： Zhang, Xiaomeng Zhao, Peihai Wang, Mimi Department of Computer Science and Technology Tongji University Shanghai China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

In the field of identity authentication, existing researches on user keystroke authentication only focus on the situation in which a single user uses a single account. When multiple users share one account, there emerges the problem of inaccurate modeling. The key to construct the keyboard behaviour pattern in a single-account-for-multiple-users case is to cluster and build the unique keyboard behaviour pattern for each user under the shared account. In this paper, the original K-means clustering algorithm is improved by adding variance determination conditions. And when the number of users is unknown, the algorithm will determine whether the account is a multi-user account or not and identify the number of users under the account to carry out keyboard behaviour clustering in a single-account-for-multiple-users situation. We build a model based on keyboard behaviour data after clustering. Compared with other methods, experiments arrive at the expected results. This method can be used for keyboard behaviour authentication in real-world scenarios in which multiple users share one account at home or in companies. ©, 2014, Journal of Computational Information systems. All right reserved.

关键词： Authentication

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SelectCast: Scalable data aggregation scheme in wireless sensor networks

SelectCast: Scalable data aggregation scheme in wireless sen...

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IEEE INFOCOM 2011

作者： Wang, Cheng Tang, Shaojie Li, Xiang-Yang Jiang, Changjun Department of Computer Science Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China Department of Computer Science Illinois Institute of Technology Chicago IL 60616 United States TNLIST School of Software Tsinghua University China

ISBN: (纸本)9781424499212

In this work, for a wireless sensor network (WSN) of n randomly placed sensors with node density λ ∈ [1, n], we study the tradeoffs between the aggregation throughput and gathering efficiency. The gathering efficiency refers to the ratio of the number of the sensors whose data have been gathered to the total number of sensors. Specifically, we design two efficient aggregation schemes, called single-hop-length (SLH) scheme and multiple-hop-length (MLH) scheme. By novelly integrating these two schemes, we theoretically prove that our protocol achieves the optimal tradeoffs, and derive the optimal aggregation throughput depending on a given threshold value (lower bound) on gathering efficiency. Particularly, we show that under the MLH scheme, for a practically important set of symmetric functions called perfectly compressible functions, including the mean, max, or various kinds of indicator functions, etc., the data from Θ(n) sensors can be aggregated to the sink at the throughput of a constant order Θ(1), implying that our MLH scheme is indeed scalable. © 2011 IEEE.

关键词： Efficiency

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Evaluating feedback systems for residential building energy monitoring

Evaluating feedback systems for residential building energy ...

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2013 IEEE International Conference on Automation Science and Engineering, CASE 2013

作者： Guo, Wenqi Wendy Ullah, Tania Zhou, Mengchu National Institute of Standards and Technology Gaithersburg MD 20899 United States ECE Dept. New Jersey Institute of Technology Newark NJ 07102 United States Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China

ISBN: (纸本)9781479915156

Rising global energy demand, increasing electricity prices, and the limitation of natural resources have led to increased interest in energy monitoring of residential buildings. Much research has been done to examine the effect of energy use feedback to building occupants. An important step towards energy awareness is to provide timely and finegrained consumption information of major household energy expenditures through feedback systems, known as residential energy monitoring systems (REMS). To accomplish this, researchers and product designers are intent on improving the residential whole-building energy consumption estimates gained through sensor networks at homes. Additionally, profiling the usage of appliances and devices within a home can be used to determine an occupant's daily activities and to optimize energy consumption. In this work, we take a step toward creating an evaluation procedure for REMS by determining factors that affect their ability to accurately convey energy usage to occupants. Two feedback sensor systems are assessed in a testbed in which electrical loads typical to a home are operated. Preliminary tests show that the accuracy of the REMS measurement is dependent on an electrical load's power factor. Together with other findings, the results will assist researchers in forming a comprehensive test procedure that will characterize feedback systems in the future. © 2013 IEEE.

关键词： Sensor networks

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Research on the Matthews correlation coefficients metrics of personalized recommendation algorithm evaluation

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International Journal of Hybrid Information Technology 2015年第1期8卷 163-172页

作者： Liu, Yingbo Cheng, Jiujun Yan, Chendan Wu, Xiao Chen, Fuzhen Key Laboratory of Embedded System and Service Computing of Ministry of Education Tongji University Shanghai China Department of Computer Science and Technology Tongji University Shanghai China

The personalized recommendation systems could better improve the personalized service for network user and alleviate the problem of information overload in the Internet. As we all know, the key point of being a successful recommendation system is the performance of recommendation algorithm. When scholars put forward some new recommendation algorithms, they claim that the new algorithms have been improved in some respects, better than previous algorithm. So we need some evaluation metrics to evaluate the algorithm performance. Due to the scholar didn’t fully understand the evaluation mechanism of recommendation algorithms. They mainly emphasized some specific evaluation metrics like Accuracy, Diversity. What’s more, the academia did not establish a complete and unified assessment of recommendation algorithms evaluation system which is credibility to do the work of recommendation evaluation. So how to do this work objective and reasonable is still a challengeable task. In this article, we discussed the present evaluation metrics with its respective advantages and disadvantages. Then, we put forward to use the Matthews Correlation Coefficient to evaluate the recommendation algorithm’s performance. All this based on an open source projects called mahout which provides a rich set of components to construct the classic recommendation algorithm. The results of the experiments show that the applicability of Matthews correlation coefficient in the relative evaluation work of recommendation algorithm. © 2015 SERSC.

关键词： Recommender systems

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A study on the optimum state for classroom learning from brain cognition perspective-research on relaxed alertness

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Journal of Convergence Information Technology 2012年第23期7卷 564-571页

作者： Gu, Rong Li, Jie Department of Electronic Science and Technology Tongji University Shanghai China The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

Booming development in brain science injects new vitality into the reform of teaching methods. Based on the perspective of brain cognition, this article addresses the optimum state for classroom learning- the relaxed alertness. This is a good state of mind combined low threats with high challenges. Specially, the vigilance is estimated by extracting useful electroencephalogram (EEG) information in time-domain, frequency-domain and spatial distribution. It is used as an indicator to judge whether a student is in the optimum state. Focusing on how to achieve that ideal state, this article discusses some new teaching methods, including the use of Baroque music to stimulate alpha brainwave, the design of effective pattern of guiding class to arouse positive emotions of students and the conversion of teaching forms as novel stimuli to heip them improve vigilance and tide over thinking trough. The effectiveness of these methods is verified by the relevant experimental results.

关键词： Electroencephalography

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