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The dynamic allocation model for the resources of cloud services delivery networks

Jisuanji Xuebao/Chinese Journal of computers 2011年第12期34卷 2305-2318页

作者： Shi, Pei-Chang Wang, Huai-Min Yin, Gang Liu, Xue-Ning Yuan, Xiao-Qun Shi, Dian-Xi National Laboratory for Parallel and Distributed Processing School of Computer and Science National University of Defense Technology Changsha 410073 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China Department of Electronics and Information Engineering Huazhong Univ. of Sci. and Technol. Wuhan 430074 China

Cloud Services Delivery Networks (CSDN) constructs a layer distributed server overlay over the Internet, which uses the way to the nearest and on-demand approach providing services to end users. Facing the scale and diversification of the resource demand characteristics of the Internet cloud services, CSDN forms different logical sub-server overlay for different kinds of cloud services. However, most servers and bandwidth resources of CSDN are used to deliver the streaming and downloading kind of cloud services, and the dynamic allocation of their delivery resource is the main research emphasis in this paper. This paper first models the problem to be a multi-dimensional facility location problem, according to the two characteristics: the memory resource and bandwidth resource of this kind of application are the bottleneck resource;the hot contents of this kind of application can be delivered using the Peer-to-Peer mechanisms. After the model analyzed and its NP-Complete proved, we then propose a heuristic algorithm. Finally, using the service delivery cost savings as the performance metrics, while the actual system's operation trace is as the input, the effectiveness of the algorithm are comprehensively assessed.

关键词： Heuristic algorithms

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Combining global and local features for food identification in dietary assessment

Combining global and local features for food identification ...

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IEEE International Conference on Image processing

作者： Marc Bosch Fengqing Zhu Nitin Khanna Carol J. Boushey Edward J. Delp School of Electrical and Computer Engineering Video and Image Processing Laboratory USA Department of Foods and Nutrition Purdue University West Lafayette IN USA

Many chronic diseases, such as heart diseases, diabetes, and obesity, can be related to diet. Hence, the need to accurately measure diet becomes imperative. We are developing methods to use image analysis tools for the identification and quantification of food consumed at a meal. In this paper we describe a new approach to food identification using several features based on local and global measures and a “voting” based late decision fusion classifier to identify the food items. Experimental results on a wide variety of food items are presented.

关键词： Image color analysis Visualization Feature extraction Image segmentation Color Conferences Vectors

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Efficient Approach for Repeated Patterns Mining Based on Indent Shape of HTML Documents

Efficient Approach for Repeated Patterns Mining Based on Ind...

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International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC

作者： Yanxu Zhu Gang Yin Huaimin Wang Dianxi Shi Xiang Rao Lin Yuan School of computer National Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha Hunan China College of Electronic Technology Information Engineering University Zhengzhou Henan China

Mining of repeated patterns from HTML documents is the key step towards Web-based data mining and knowledge extraction. Many web crawling applications need efficient repeated patterns mining techniques to generate their wrapper automatically. Existing approaches such as tree matching and string matching can detect repeated patterns with high precision, but their performance is still a challenge for practical web crawling applications. In this paper, we propose an efficient approach for mining repeated patterns based on indent shape of HTML document. Indent shape is a novel and simple model of HTML document, in which tandem repeated waves have strong association with the repeated patterns to be detected. By scanning an indent shape with a horizontal indent-line from bottom to top, the tandem repeated waves are identified by filtering the wave segments with low self-similarities. After that the boundary of HTML code corresponding to repeated patterns can be identified, which could be transformed to regular expressions formal-defined easily. Extensive experiments on two practical data sets retrieved from Internet show that our approach achieves high efficiency significantly, and its precision performance is also generally better than the existing approaches.

关键词： Shape HTML Data mining Web pages Vectors Visualization Algorithm design and analysis

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Assessing lung volumetric variation to detect and stage COPD

Assessing lung volumetric variation to detect and stage COPD

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2011 1st Middle East Conference on Biomedical engineering, MECBME 2011

作者： Hosseini, M. Parsa Soltanian-Zadeh, Hamid Akhlaghpoor, Shahram Department of Electrical Engineering Islamic Azad University Science and Research Branch of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI United States Department of Radiology Tehran University of Medical Sciences Sina Hospital Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781424470006

Chronic obstructive pulmonary disease (COPD) is a devastating disease. In this paper, we propose a novel method for scoring of air trapping in the lungs for detection and evaluation of COPD. The proposed method finds volumetric changes of the lungs from inspiration to expiration. To this end, trachea CT images at full inspiration and expiration are compared. For this comparison, the lungs parenchyma in the inspiration and expiration images are found and changes in the surface and volume of the lungs between inspiration and expiration are used to define quantitative measures (features). Using these features, the subjects are classified into two groups of normal class and COPD patients using a Bayesian classifier. In addition, t-tests are applied to evaluate discrimination powers of the features for this classification. The main advantage of the proposed method is its ability to estimate air trapping in the lungs from CT images without human intervention. The proposed method may assists radiologists in the detection of COPD as a computer aided diagnosis (CAD) system. It may also assist them with the scoring of the disease (severity of air trapping in the lungs). © 2011 IEEE.

关键词： computerized tomography

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A novel method for identification of COPD in inspiratory and expiratory states of CT images

A novel method for identification of COPD in inspiratory and...

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2011 1st Middle East Conference on Biomedical engineering, MECBME 2011

ISBN: (纸本)9781424470006

Chronic obstructive pulmonary disease (COPD) refers to a group of lung diseases that block airflow and cause a huge degree of human suffering. While there is no cure for COPD and the lung damage that results in this disease cannot be reversed, it is very important to diagnose it as early as possible. Additional to diagnosis, using a mathematical model to estimate severity of disease would be helpful for evaluation of treatment effects. This paper presents a new method for identifying COPD from three-dimensional (3-D) pulmonary X-ray CT images. The method has five main steps. First, corresponding positions of lungs in inspiration and expiration are found based on anatomical structures. Then, lung regions are segmented from the CT images by active contours. Next, the left and right lungs are separated using a sequence of morphological operations. Then, parenchyma variations in each lung are found as a relationship between inspiratory and expiratory states. Finally, a classifier is used to decide about the disease and its severity. A t-test is done to evaluate the results. Twelve patients with variable severity of COPD and twelve normal adults were included in this study. The proposed method may assist radiologists in the detection of COPD as a computer aided diagnosis (CAD) system. © 2011 IEEE.

关键词： Pulmonary diseases

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A new Scalable Multi-View Video Coding configuration for mobile applications

A new Scalable Multi-View Video Coding configuration for mob...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Hoda Roodaki Lavasani Mahmoud Reza Hashemi Shervin Shirmohammadi Multimedia Processing Laboratory School of Electrical and Computer Engineering College of Engineering University of Tehran Iran Distributed and Collaborative Virtual Environments Research Laboratory (DISCOVER Lab) School of Information Technology and Engineering (SITE) University of Ottawa Canada

Transmission of multi-view video content is not practical in most mobile environments due to the limited bandwidth and processing power of mobile devices. To support such environments, one can limit the number of views that are being transmitted, known as Scalable Multi-view Video Coding (SMVC). In this paper, we propose a new view selection method for view scalability in multi-view video coding in mobile environments, which uses inter and intra view dissimilarities to determine the most suitable views for the base layer corresponding to the prediction structure and user selected limited number of views. By selecting more correlated views for the base layer, the proposed method provides an improved performance, as confirmed by simulation results, even when all the enhancement layers are dropped due to network limitations.

关键词： Video coding Three dimensional displays Mobile communication Scalability Bit rate Receivers PSNR

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Extracting Image Semantic Object Based on Artificial Bee Colony Algorithm

Extracting Image Semantic Object Based on Artificial Bee Col...

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The second International Conference of electrical and Electronics engineering(ICEEE 2011)

作者： Xiao Yong-hao Chen Yong-chang Yu Wei-yu Tian Jing School of Electronic and Information Engineering South China University of Technology Provincial Key Laboratory for Computer Information Processing Technology Soochow University School of Electrical and Electronic Engineering Nanyang Technological University

In this paper, an efficient approach for extracting semantic object using artificial bee colony algorithm(ABCA) has been proposed. First, we reduce speckle noise in the image. Then fitness function of ABC algorithm is constructed, and image pixels are classified into different regions. Further semantic objects are extracted in terms of color information. The simulation results show that the color clustering via bee colony algorithm gives superior results in enhancing cluster compactness.

关键词： artificial bee colony algorithm,image semantic,image segmentation

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Towards energy saving and load balancing data aggregation for wireless sensor networks

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Information Technology Journal 2011年第2期10卷 409-415页

作者： Liang, Wei Xu, Jianbo Liu, Yuanyuan Key Laboratory of Knowledge Processing and Networked Manufacturing School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan 411201 China Department of Electrical Engineering Guangdong Songshan Polytechnic College Shaoguang 512126 China

In this study, we focus on the development of energy efficient and achievable load balancing mechanisms for wireless sensor networks. Due to resource constraint and tremendous amount of sensors, one possible way of achieving maximum lifetime of the network is applying data aggregation on sensor data. However, existing approaches introduce significant computation and control overheads that often not suitable for sensor networks applications. In view of this, we propose an in-network data aggregation scheme by exploiting the inherent spatial correlation of the sensed data. Each sensor multiplies its reading with a random coefficient and sends the product to the next hop to calculate a weighted sum of all the massage. Instead of receiving individual sensor readings, the sink will receive all weighted sum and restore the original data. By doing so, each node only performs one addition and one multiplication in order to compute one weighted sum and consume the same amount of energy. Simulation results demonstrate that the proposed scheme is efficient and outperforms existing schemes in terms of energy gain and network lifetime. © 2011 Asian Network for Scientific Information.

关键词： Energy efficiency

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Extracting salient lines by Visual Attention for omnidirectional image classification

Extracting salient lines by Visual Attention for omnidirecti...

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IEEE Symposium on Computational Intelligence for Multimedia, Signal and Vision processing (CIMSIVP)

作者： AmirHossein Habibian Majid Nili-Ahmadabadi Babak Nadjar Araabi Robotics and AI Laboratory Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Faculty of Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute for Research in Fundamental Sciences Tehran Iran

Representing an image as a set of its key and interesting lines facilitates the image understanding and classification. In this paper, we propose a method to extract the significant and interesting lines of the scene, which probably are useful in image classification. The proposed method is inspired from the Visual Attention, which is a perceptual mechanism in human and other primates that direct their perceptions to the limited regions of the scene. The attended regions are usually valuable in performing the task. Since the approach of using the lines to classify the images is particularly useful for omnidirectional images, we specialize our method to deal with these kinds of images. In the experiments, we demonstrate how our proposed methods improve the image classification performance with processing only small parts of the input images.

关键词： Feature extraction Visualization Image classification Gabor filters Image edge detection Histograms Computational modeling

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A Unique Vertex Deleting Algorithm for Graph Isomorphism

A Unique Vertex Deleting Algorithm for Graph Isomorphism

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International Symposium on Image and Data Fusion (ISIDF)

作者： Baida Zhang Yuhua Tang Junjie Wu Linqi Huang National laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha Hunan P. R. China School of Resources and Safety Engineering Central South University Changsha P. R. China

Graph isomorphism problem has applications in many fields, such as chemistry, computer science, electronics, and network theory. But the exponential complexity of the algorithm makes the testing is time consuming. In this paper, a new algorithm named Unique Vertex Delete (UVD for short) is presented to speed up the process of isomorphic testing. The main idea of UVD algorithm is deleting vertex continuously to reduce the scale of the problem, and new field is added for each vertex to indicate the information of deleted neighbor vertices. Theoretical analysis and experiments show that the UVD algorithm consistently and significantly outperforms existing state-of-the-art approaches.

关键词： Algorithm design and analysis Testing Educational institutions Polynomials Software algorithms Complexity theory Partitioning algorithms

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