2009 IEEE-RIVF International Conference on Computing and Communication Technologies最新文献_第4页

Adaptive Iterative Receiver for CDMA Systems in Rayleigh Fading Channels 瑞利衰落信道下CDMA系统的自适应迭代接收机

2009 IEEE-RIVF International Conference on Computing and Communication Technologies Pub Date : 2009-07-13 DOI: 10.1109/RIVF.2009.5174616

T. Keovkolyan, C. Teekapakvisit

引用次数: 0

A Fast Algorithm for Constructing Constrained Delaunay Triangulation 构造约束Delaunay三角剖分的快速算法

2009 IEEE-RIVF International Conference on Computing and Communication Technologies Pub Date : 2009-07-13 DOI: 10.1109/RIVF.2009.5174607

N. M. Nam, H. Kiem, Nguyen Vinh Nam

引用次数: 9

Design and Optimization of Reconfigurable Inset-Fed Microstrip Patch Antennas with High Gain for Wireless Sensor Networks 无线传感器网络中可重构插入式高增益微带贴片天线的设计与优化

2009 IEEE-RIVF International Conference on Computing and Communication Technologies Pub Date : 2009-07-13 DOI: 10.1109/RIVF.2009.5174635

D. Phan, G. Chung

引用次数: 3

Temporal 3D Graphical Data Management from a Database Perspective 从数据库的角度看时间三维图形数据管理

2009 IEEE-RIVF International Conference on Computing and Communication Technologies Pub Date : 2009-07-13 DOI: 10.1109/RIVF.2009.5174660

Vo Thi Ngoc Chau, S. Chittayasothorn

引用次数: 0

Eye Gaze Tracking 眼球注视追踪

2009 IEEE-RIVF International Conference on Computing and Communication Technologies Pub Date : 2009-07-13 DOI: 10.1109/RIVF.2009.5174639

B. L. Nguyen

引用次数: 34

Visualization of Self-Organizing Networks Operated by the ANR Algorithm 基于ANR算法的自组织网络可视化

2009 IEEE-RIVF International Conference on Computing and Communication Technologies Pub Date : 2009-07-13 DOI: 10.1109/RIVF.2009.5174664

H. Quan, Tobias Åström, M. Jern, Johan Moe, F. Gunnarsson, Harald Kallin

{"title":"Visualization of Self-Organizing Networks Operated by the ANR Algorithm","authors":"H. Quan, Tobias Åström, M. Jern, Johan Moe, F. Gunnarsson, Harald Kallin","doi":"10.1109/RIVF.2009.5174664","DOIUrl":"https://doi.org/10.1109/RIVF.2009.5174664","url":null,"abstract":"Cellular radio networks are continually growing in both node count and complexity. It therefore becomes more and more difficult to manage the networks and necessary to use time and cost effective automatic computer algorithms to organize the network's neighbor cell relations. Ericsson has developed such an algorithm, called automatic neighbor relations (ANR), which solves a part of this problem by automatically creating and updating neighbor cell relation (NCR) lists, based on measured network data. Network operators need to have an understanding of the algorithm and of its reliability and performance, which is not easily perceived. This paper presents a visualization tool that visualizes the performance of ANR and gives the user a possibility to control it via policies. The tool allows the operators to follow the evolution of the network and to find problems occurring over time. In addition, it also supports finding potential problems that can occur in the future. The tool was evaluated by a group of relevant domain users and the results from the evaluation were highly positive.","PeriodicalId":243397,"journal":{"name":"2009 IEEE-RIVF International Conference on Computing and Communication Technologies","volume":"307 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129352374","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

Interfering Job Set Scheduling on Two-Operation Three-Machine Flowshop 二工序三机流程车间的干扰作业集调度

2009 IEEE-RIVF International Conference on Computing and Communication Technologies Pub Date : 2009-07-13 DOI: 10.1109/RIVF.2009.5174646

N. H. Tuong, A. Soukhal

引用次数: 8

B-spline Surface Reconstruction by Inverse Subdivisions 基于逆细分的b样条曲面重构

2009 IEEE-RIVF International Conference on Computing and Communication Technologies Pub Date : 2009-07-13 DOI: 10.1109/RIVF.2009.5174628

Khoi Nguyen-Tan, Romain Raffin, M. Daniel, C. Le

引用次数: 2

A Robust Stereo Matching Method for Low Texture Stereo Images 低纹理立体图像的鲁棒匹配方法

2009 IEEE-RIVF International Conference on Computing and Communication Technologies Pub Date : 2009-07-13 DOI: 10.1109/RIVF.2009.5174612

Le Thanh Sach, K. Atsuta, K. Hamamoto, S. Kondo

{"title":"A Robust Stereo Matching Method for Low Texture Stereo Images","authors":"Le Thanh Sach, K. Atsuta, K. Hamamoto, S. Kondo","doi":"10.1109/RIVF.2009.5174612","DOIUrl":"https://doi.org/10.1109/RIVF.2009.5174612","url":null,"abstract":"Computing disparity images for stereo pairs of low texture images is a challenging task because matching costs inside low texture areas of the stereo pairs are almost similar. This problem can not be solved straightforwardly by increasing the size of aggregation windows or by using global optimization methods, e.g. dynamic programming, because those approaches will smooth depth discontinued boundaries as well. Based on the assumption that disparities of pixels in homogeneous regions are similar, this paper proposes a new method that is able to robustly perform stereo matching for low texture stereo images. The proposed method utilizes the edge maps computed from the stereo pairs to guide the cost aggregation process in stereo matching. By using edge maps, the proposed method can achieve the effect of using different shapes and sizes of aggregation windows. Moreover, the computational complexity of the proposed method is independent from the window size, similar to the moving average aggregation method. Experimental results from both of an artificial and a real stereo image sequence demonstrate that the proposed method can produce a larger number of and a better accuracy of reliable disparities for low texture stereo images than the moving average method.","PeriodicalId":243397,"journal":{"name":"2009 IEEE-RIVF International Conference on Computing and Communication Technologies","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124265373","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: 15

Using Artificial Neural Network for Robust Voice Activity Detection Under Adverse Conditions 基于人工神经网络的恶劣条件下鲁棒语音活动检测

2009 IEEE-RIVF International Conference on Computing and Communication Technologies Pub Date : 2009-07-13 DOI: 10.1109/RIVF.2009.5174662

T. V. Pham, Chien T. Tang, M. Stadtschnitzer

{"title":"Using Artificial Neural Network for Robust Voice Activity Detection Under Adverse Conditions","authors":"T. V. Pham, Chien T. Tang, M. Stadtschnitzer","doi":"10.1109/RIVF.2009.5174662","DOIUrl":"https://doi.org/10.1109/RIVF.2009.5174662","url":null,"abstract":"We present an approach to model-based voice activity detection (VAD) for harsh environments. By using mel-frequency cepstral coefficients feature extracted from clean and noisy speech samples, an artificial neural network is trained optimally in order to provide a reliable model. There are three main aspects to this study: First, in addition to the developed model, recent state-of-the-art VAD methods are analyzed extensively. Second, we present an optimization procedure of neural network training, including evaluation of trained network performance with proper measures. Third, a large assortment of empirical results on the noisy TIMIT and SNOW corpuses including different types of noise at different signal-to-noise ratios is provided. We evaluate the built VAD model on the noisy corpuses and compare against the state-of-the-art VAD methods such as the ITU-T Rec. G. 729 Annex B, the ETSI AFE ES 202 050, and recently promising VAD algorithms. Results show that: (i) the proposed neural network classifier employing MFCC feature provides robustly high scores under different noisy conditions; (ii) the invented model is superior to other VAD methods in terms of various classification measures; (iii) the robustness of the developed VAD algorithm is still hold in the case of testing it with the completely mismatched environment.","PeriodicalId":243397,"journal":{"name":"2009 IEEE-RIVF International Conference on Computing and Communication Technologies","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130694494","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: 23