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2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)最新文献

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Design of an energy efficiency model and architecture for cloud management using prediction models 使用预测模型设计用于云管理的能源效率模型和架构
2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR) Pub Date : 2013-12-18 DOI: 10.1109/SOCPAR.2013.7054153
A. Nguyen, Alexandru-Adrian Tantar, P. Bouvry, E. Talbi
{"title":"Design of an energy efficiency model and architecture for cloud management using prediction models","authors":"A. Nguyen, Alexandru-Adrian Tantar, P. Bouvry, E. Talbi","doi":"10.1109/SOCPAR.2013.7054153","DOIUrl":"https://doi.org/10.1109/SOCPAR.2013.7054153","url":null,"abstract":"In this paper, we present a new energy efficiency model and architecture for cloud management based on a prediction model with Gaussian Mixture Models. The methodology relies on a distributed agent model and the validation will be performed on OpenStack. This paper intends to be a position paper, the implementation and experimental run will be conducted in future work. The design concept leverages the prediction model by providing a full architecture binding the resource demands, the predictions and the actual cloud environment (Openstack). The prediction analysis feeds the power-aware agents that run on the compute nodes in order to turn the nodes into sleep mode when the load state is low to reduce the energy consumption of the data center.","PeriodicalId":315126,"journal":{"name":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122924577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Text classification based on semi-supervised learning 基于半监督学习的文本分类
2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR) Pub Date : 2013-12-01 DOI: 10.1109/SOCPAR.2013.7054133
Vo Duy Thanh, P. M. Tuan, V. T. Hung, Doan Van Ban
{"title":"Text classification based on semi-supervised learning","authors":"Vo Duy Thanh, P. M. Tuan, V. T. Hung, Doan Van Ban","doi":"10.1109/SOCPAR.2013.7054133","DOIUrl":"https://doi.org/10.1109/SOCPAR.2013.7054133","url":null,"abstract":"In this paper, we present our solution and experimental results of the application of semi-supervised machine learning techniques and the improvement of SVM algorithm to build text classification applications. Firstly, we create a features model which is based on labeled data, and then we will be improved it by the unlabeled data. The technique that is to be added a label into new data is based on binary classification. Our experiment is implemented on three data layers which are extracted from papers in three topics sports, entertainment and education on VNEXPRESS.NET. We experimented and compared the accuracy of the classification results between before and after improve features model through semi-supervised machine learning method and classification algorithm based on SVM model. Experiments show that classification quality is enhanced after improvement features model.","PeriodicalId":315126,"journal":{"name":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116782318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
A genetic-based approach for discovering pathways in protein-protein interaction networks 发现蛋白质-蛋白质相互作用网络通路的一种基于遗传学的方法
2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR) Pub Date : 2013-12-01 DOI: 10.1109/SOCPAR.2013.7054106
Nguyen Hoai Anh, C. Vu, Tu Minh Phuong, L. Bui
{"title":"A genetic-based approach for discovering pathways in protein-protein interaction networks","authors":"Nguyen Hoai Anh, C. Vu, Tu Minh Phuong, L. Bui","doi":"10.1109/SOCPAR.2013.7054106","DOIUrl":"https://doi.org/10.1109/SOCPAR.2013.7054106","url":null,"abstract":"This paper introduces an approach of using the genetic algorithm for orienting protein-protein interaction networks (PPIs) and discovering pathways. Biological pathways such as metabolic or signaling ones play an important role in understanding cell activities and evolution. A cost-effective method to discover such pathways is analyzing accumulated information about protein-protein interactions, which are usually given in forms of undirected networks or graphs. Previous findings show that orienting protein interactions can improve pathway discovery. However, assigning orientation for protein interactions is a combinatorial optimization problem which has been proved to be NP-hard, making it critical to develop efficient algorithms. For our proposal, we first study the mathematical model of the problem. Then, based on this model, a genetic algorithm is designed to find the solution for the problem. We conducted multiple runs on the data of yeast PPI networks to test the best option for the problem. The preliminary results were compared with the results of the random search algorithm, which was shown to the best in dealing with this problem, in terms of the run time, fitness function values, especially the ratio of gold standard pathways. The findings show that our genetic-based approach addressed this problem better than the random search algorithm did.","PeriodicalId":315126,"journal":{"name":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","volume":"43 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126072074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Accelerating multi-target tracking by a swarm of mobile robots with network preservation 基于网络保存的移动机器人群多目标跟踪加速算法
2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR) Pub Date : 2013-12-01 DOI: 10.1109/SOCPAR.2013.7054152
Pham Duy Hung, Minh-Trien Pham, T. Q. Vinh, T. Ngo
{"title":"Accelerating multi-target tracking by a swarm of mobile robots with network preservation","authors":"Pham Duy Hung, Minh-Trien Pham, T. Q. Vinh, T. Ngo","doi":"10.1109/SOCPAR.2013.7054152","DOIUrl":"https://doi.org/10.1109/SOCPAR.2013.7054152","url":null,"abstract":"This paper addresses a decentralized control of robot swarm for multi-target tracking with network preservation - namely swarm dispersion algorithm (SDA). The robot swarm moves towards targets while preserving connectivities for networking communication. The developed controller relied on local information of neighboring robots is synthesized by the rules of behavioral control and connectivity maintenance. The swarm dispersion algorithm accelerates the multi-target tracking by minimizing connectivities but preserving an ad-hoc communication network through all the robots. The decentralized control consists of three major functionalities: (1) maintaining connectivities between the robots for swarm movement towards the targets; (2) breaking down triangle and k-connected topologies to accelerate the target reaching; (3) adjusting the robots' velocity to preserve connectivities for an ad-hoc communication network through all the robots. The developed algorithm is demonstrated and verified in simulation.","PeriodicalId":315126,"journal":{"name":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115911540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Image contrast enhancement for outdoor machine vision applications 用于户外机器视觉应用的图像对比度增强
2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR) Pub Date : 2013-12-01 DOI: 10.1109/SOCPAR.2013.7054162
M. Wahab, Nasriah Zakaria, R. Latip, R. A. Salam
{"title":"Image contrast enhancement for outdoor machine vision applications","authors":"M. Wahab, Nasriah Zakaria, R. Latip, R. A. Salam","doi":"10.1109/SOCPAR.2013.7054162","DOIUrl":"https://doi.org/10.1109/SOCPAR.2013.7054162","url":null,"abstract":"Outdoor machine vision is getting a concern nowadays. Ranging from surveillance and monitoring system to automotive system such as driver assistance system require vision application or artificial eye to keep monitoring the situations. However, most of these applications works very well during clear weather and degrade during bad weather due to the atmospheric particles mitigate the quality of vision system. This paper discuss the state of the art of image enhancement techniques used to adjust the contrast of an outdoor image degrade by fog, haze, and rain. A brief overview of bad weather will be discussed and several recent techniques on removing fog, haze and rain are discussed.","PeriodicalId":315126,"journal":{"name":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134011769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Using contour information for image segmentation 利用轮廓信息进行图像分割
2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR) Pub Date : 2013-12-01 DOI: 10.1109/SOCPAR.2013.7054139
Duong-Trung-Dung Nguyen, Huynh Thi Thanh Binh
{"title":"Using contour information for image segmentation","authors":"Duong-Trung-Dung Nguyen, Huynh Thi Thanh Binh","doi":"10.1109/SOCPAR.2013.7054139","DOIUrl":"https://doi.org/10.1109/SOCPAR.2013.7054139","url":null,"abstract":"This paper proposes an algorithm for image segmentation that improves the graph-based segmentation algorithm by exploiting contour information. The graph-based image segmentation [9] is a fast and efficient method of generating a set of segments from an image. However, its drawback is neglecting the contour information of pixels. Contour can provide significant cues to facilitate the efficient segmentation. We propose an improved weight function that incorporates contour feature into the dissimilarity measure of pixels. We performed experiments on the Berkeley image dataset. Our proposed approach attains significant performance. The experimental results show that our proposed approach is comparable to or even outperforms some state-of-the-art algorithms. In term of global consistency error, our method gives better result while other measures including Probabilistic Rand Index, Variation of Information, and Boundary Displacement Error are close to the best result given by state-of-the-art algorithms.","PeriodicalId":315126,"journal":{"name":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134271805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
An experimental study of minimum routing cost spanning tree algorithms 最小路由开销生成树算法的实验研究
2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR) Pub Date : 2013-12-01 DOI: 10.1109/SOCPAR.2013.7054119
Quoc Phan Tan, N. D. Nghia
{"title":"An experimental study of minimum routing cost spanning tree algorithms","authors":"Quoc Phan Tan, N. D. Nghia","doi":"10.1109/SOCPAR.2013.7054119","DOIUrl":"https://doi.org/10.1109/SOCPAR.2013.7054119","url":null,"abstract":"The task of finding the Minimum Routing Cost Spanning Tree (MRCST) can be found in many network design problems. In general cases, MRCST problem is a NP-hard problem. Till now, several algorithms for solving the problem are proposed and their performance were evaluated on different data sets. This paper presents a short survey of well known MRCST algorithms and gives a report on an extensive experimentation based on benchmark instances collected from the literature. In addition, the paper is also the first pioneering research that experiment on graphs with up to 1000 vertices.","PeriodicalId":315126,"journal":{"name":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129393334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
A fast temporal median filter and its applications for background estimation in video surveillance 一种快速时域中值滤波器及其在视频监控背景估计中的应用
2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR) Pub Date : 2013-12-01 DOI: 10.1109/SOCPAR.2013.7054097
Thanh-Sach Le, T. Luu
{"title":"A fast temporal median filter and its applications for background estimation in video surveillance","authors":"Thanh-Sach Le, T. Luu","doi":"10.1109/SOCPAR.2013.7054097","DOIUrl":"https://doi.org/10.1109/SOCPAR.2013.7054097","url":null,"abstract":"Median filter is well-known for researchers in many fields. In image and video processing, it can be used for filtering noises, for estimating background images, and so on. Its effectiveness is undoubtful. However, median filter is time-consuming. This paper presents a new method for computing median filter's response. The proposed method is O(1) and better than existing methods analytically and experimentally. The experimental results with background estimation problem consolidate the finding in this paper.","PeriodicalId":315126,"journal":{"name":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117248582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A new approach based on enhanced PSO with neighborhood search for data clustering 基于邻域搜索增强粒子群算法的数据聚类新方法
2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR) Pub Date : 2013-12-01 DOI: 10.1109/SOCPAR.2013.7054109
Dang Cong Tran, Zhijian Wu, Van Xuat Nguyen
{"title":"A new approach based on enhanced PSO with neighborhood search for data clustering","authors":"Dang Cong Tran, Zhijian Wu, Van Xuat Nguyen","doi":"10.1109/SOCPAR.2013.7054109","DOIUrl":"https://doi.org/10.1109/SOCPAR.2013.7054109","url":null,"abstract":"The well-known K-means algorithm has been successfully applied to many practical clustering problems, but it has some drawbacks such as local optimal convergence and sensitivity to initial points. Particle swarm optimization algorithm (PSO) is one of the swarm intelligent algorithms, it is applied in solving global optimization problems. An integration of enhanced PSO and K-means algorithm is becoming one of the popular strategies for solving clustering problems. In this study, an approach based on PSO and K-means is presented (denoted EPSO), in which PSO is enhanced by neighborhood search strategies. By hybrid with enhanced PSO, it does not only help the algorithm escape from local optima but also overcomes the shortcoming of the slow convergence speed of the PSO algorithm. Experimental results on eight benchmark data sets show that the proposed approach outperforms some other data clustering algorithms, and has an acceptable efficiency and robustness.","PeriodicalId":315126,"journal":{"name":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129139752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Assessing general well-being using de-identified features of facial expressions 使用面部表情去识别特征来评估总体幸福感
2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR) Pub Date : 2013-12-01 DOI: 10.1109/SOCPAR.2013.7054134
Insu Song, J. Vong
{"title":"Assessing general well-being using de-identified features of facial expressions","authors":"Insu Song, J. Vong","doi":"10.1109/SOCPAR.2013.7054134","DOIUrl":"https://doi.org/10.1109/SOCPAR.2013.7054134","url":null,"abstract":"The UN has predicted that cell-phone ownership will reach 5 billion in 2010. This proliferation of cell phones and connectivity offers an unprecedented opportunity to access vast populations, including previously hard-to-reach populations in rural areas and mountainous zones and underserved populations. Cell phones now can provide capabilities for the developing world that includes text, image processing and image displays. The available standardized interfaces can be leveraged to create powerful systems. In particular, digital cameras of cell phones provide easy to use interfaces for capturing useful information on the general well-being and emotive features of individuals. However, photographic images contain private and sensitive personal information in its raw form and thus considered unsuitable for online services. Therefore, there is a need for a computational algorithm for extracting anonymous digital features (for example, Hamming distance) from captured facial expression images for estimating different states of well-being. We have developed computer algorithms predicting well-being states from anonymous facial expression features. The research outcome can be used in a variety of online services including suggesting useful health information to improve general well-being.","PeriodicalId":315126,"journal":{"name":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129297603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
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