2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies最新文献_第5页

A GPU Implementation of Fast Parallel Markov Clustering in Bioinformatics Using EllPACK-R Sparse Data Format 基于EllPACK-R稀疏数据格式的生物信息学快速并行马尔可夫聚类GPU实现

2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies Pub Date : 2010-12-02 DOI: 10.1109/ACT.2010.10

A. Bustamam, K. Burrage, N. Hamilton

{"title":"A GPU Implementation of Fast Parallel Markov Clustering in Bioinformatics Using EllPACK-R Sparse Data Format","authors":"A. Bustamam, K. Burrage, N. Hamilton","doi":"10.1109/ACT.2010.10","DOIUrl":"https://doi.org/10.1109/ACT.2010.10","url":null,"abstract":"The massively parallel computing using graphical processing unit (GPU), which based on tens of thousands of parallel threats within hundreds of GPU’s streaming processors, has gained broad popularity and attracted researchers in a wide range of application areas from finance, computer aided engineering, computational fluid dynamics, game physics, numerics, science, medical imaging, life science, and so on, including molecular biology and bioinformatics. Meanwhile, Markov clustering algorithm (MCl) has become one of the most effective and highly cited methods to detect and analyze the communities/clusters within an interaction network dataset on many real world problems such us social, technological, or biological networks including protein-protein interaction networks. However, as the dataset become bigger and bigger, the computation time of MCl algorithm become slower and slower. Hence, GPU computing is an interesting and challenging alternative to attempt to improve the MCl performance. In this poster paper we introduce our improvement of MCl performance based on EllPACK-R sparse dataset format using GPU computing with the Compute Unified Device Architecture tool (CUDA) from NVIDIA (called CUDA-MCl). As the results show the significant improvement in CUDA-MCl performance and with the low-cost and widely available GPU devices in the market today, this CUDA-MCl implementation is allowing large-scale parallel computation on off-the-shelf desktop machines. Moreover the GPU computing approaches potentially may contribute to significantly change the way bioinformaticians and biologists compute and interact with their data.","PeriodicalId":147311,"journal":{"name":"2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133628660","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: 6

Semantic Document Annotation Ranking Model 语义文档标注排序模型

2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies Pub Date : 2010-12-02 DOI: 10.1109/ACT.2010.56

Syarifah Bahiyah Rahayu, S. Noah, Andrianto Arfan Wardhana

引用次数: 2

Analysis of Machine learning Techniques Used in Behavior-Based Malware Detection 基于行为的恶意软件检测中使用的机器学习技术分析

2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies Pub Date : 2010-12-02 DOI: 10.1109/ACT.2010.33

Ivan Firdausi, Charles Lim, Alva Erwin, A. Nugroho

{"title":"Analysis of Machine learning Techniques Used in Behavior-Based Malware Detection","authors":"Ivan Firdausi, Charles Lim, Alva Erwin, A. Nugroho","doi":"10.1109/ACT.2010.33","DOIUrl":"https://doi.org/10.1109/ACT.2010.33","url":null,"abstract":"The increase of malware that are exploiting the Internet daily has become a serious threat. The manual heuristic inspection of malware analysis is no longer considered effective and efficient compared against the high spreading rate of malware. Hence, automated behavior-based malware detection using machine learning techniques is considered a profound solution. The behavior of each malware on an emulated (sandbox) environment will be automatically analyzed and will generate behavior reports. These reports will be preprocessed into sparse vector models for further machine learning (classification). The classifiers used in this research are k-Nearest Neighbors (kNN), Naïve Bayes, J48 Decision Tree, Support Vector Machine (SVM), and Multilayer Perceptron Neural Network (MlP). Based on the analysis of the tests and experimental results of all the 5 classifiers, the overall best performance was achieved by J48 decision tree with a recall of 95.9%, a false positive rate of 2.4%, a precision of 97.3%, and an accuracy of 96.8%. In summary, it can be concluded that a proof-of-concept based on automatic behavior-based malware analysis and the use of machine learning techniques could detect malware quite effectively and efficiently.","PeriodicalId":147311,"journal":{"name":"2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127267484","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: 265

Information Technology Risk Measurement Using NIST (Case Study at Pt. Pintraco) 使用NIST进行信息技术风险度量(以Pintraco公司为例)

2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies Pub Date : 2010-12-02 DOI: 10.1109/ACT.2010.57

A. Gui, R. Kristanto, Hasnah Haron, Ega Adrian

引用次数: 4

A Novel Static and Moving Obstacles Avoidance Method Using Bayesian Filtering for Service Robot 一种基于贝叶斯滤波的服务机器人动、静态避障方法

2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies Pub Date : 2010-12-02 DOI: 10.1109/ACT.2010.51

W. Budiharto, D. Purwanto, A. Jazidie

引用次数: 6

A Comparative Study of Skeletal and Keyframe Animations in a Multiplayer Online Game 多人在线游戏中骨架动画和关键帧动画的比较研究

2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies Pub Date : 2010-12-02 DOI: 10.1109/ACT.2010.54

Garry Pranatio, R. Kosala

引用次数: 7

Business Process Integration Using BPEl to Create Direct Rewarding Module in loyalty Management System 在忠诚度管理系统中使用BPEl创建直接奖励模块的业务流程集成

2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies Pub Date : 2010-12-02 DOI: 10.1109/ACT.2010.36

Ryan Andhika Perdana, James Purnama

引用次数: 2

Fourier Transform of Untransformable Signals Using Pattern Recognition Technique 基于模式识别技术的不可变换信号傅里叶变换

2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies Pub Date : 2010-12-02 DOI: 10.1109/ACT.2010.11

Varun Gupta, Gavendra Singh, Manish Mittal, S. K. Pahuja

{"title":"Fourier Transform of Untransformable Signals Using Pattern Recognition Technique","authors":"Varun Gupta, Gavendra Singh, Manish Mittal, S. K. Pahuja","doi":"10.1109/ACT.2010.11","DOIUrl":"https://doi.org/10.1109/ACT.2010.11","url":null,"abstract":"In this paper we are highlighting the signals that are not Fourier transformable and give its Fourier transform using PCA (Principle Component Analysis), lDA (linear Discriminant Analysis). Such signals are step signal, signum, etc. Basically Fourier transform transforms time domain signal into frequency domain and after transformation describes what frequencies original signal have. Principle Component Analysis is a way of identifying patterns (recognition) in the data and the differences of the data is highlighted. With the help of PCA & lDA we do the dimension reduction of the signal. lDA is used in statistics and machine learning to find a linear combination of features which characterize or separate two or more classes of objects or events. The resulting combination may be used as a linear classifier or, more commonly, for dimensionality reduction before later classification. lDA is closely related to anova (analysis of variance). PCA is used for analyzing. Main advantage of PCA is that once patterns are found and data is compressed that is by reducing the number of dimension without much loss of information. Dimension reduction is the process of reducing the number of random variables under consideration, and can be divided into feature selection and feature extraction. Feature selection approaches try to find a subset of the original variables and feature extraction transforms the data in the high-dimensional space to a space of fewer dimensions.","PeriodicalId":147311,"journal":{"name":"2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122650635","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: 10

Using Pattern Matching in the 1-D Domain of Chain Code Signals for the Compression of Binary Printed Farsi and Arabic Textual Images 利用链码信号一维域的模式匹配压缩二值印刷波斯语和阿拉伯语文本图像

2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies Pub Date : 2010-12-02 DOI: 10.1109/ACT.2010.23

Esmaeil Shojaei, H. Grailu

{"title":"Using Pattern Matching in the 1-D Domain of Chain Code Signals for the Compression of Binary Printed Farsi and Arabic Textual Images","authors":"Esmaeil Shojaei, H. Grailu","doi":"10.1109/ACT.2010.23","DOIUrl":"https://doi.org/10.1109/ACT.2010.23","url":null,"abstract":"Pattern Matching is the most conventional method of binary text image compression that has been only used in the 2-D domain of textual image signals. In this paper a pattern matching technique is proposed in the 1-D domain of chain code description signal of printed binary textual Farsi-Arabic images. In printed Farsi-Arabic scripts, contrary to latin scripts, letters usually attach to each other and produce many different patterns. Hence some patterns are fully or partially subsets of others. Detecting such situations and exploiting them to reduce the number of library prototypes has a great effect on the compression efficiency. The Proposed method, contrary to the existing compression methods, has used this property for increasing the compression ratio. For the template matching part of the proposed method, we may use either the cross correlation or a proposed similarity measure which has lower computation time and better results. Experimental results show that the compression performance of the proposed method is as high as 4.5 times that of the conventional one.","PeriodicalId":147311,"journal":{"name":"2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122555808","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: 0

Feedback Delay Effect on the CDMA Closed loop Power Control 反馈延迟效应在CDMA闭环功率控制中的应用

2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies Pub Date : 2010-12-02 DOI: 10.1109/ACT.2010.16

Filiyal Fahri, Dwi Astharini

{"title":"Feedback Delay Effect on the CDMA Closed loop Power Control","authors":"Filiyal Fahri, Dwi Astharini","doi":"10.1109/ACT.2010.16","DOIUrl":"https://doi.org/10.1109/ACT.2010.16","url":null,"abstract":"This paper is aimed to evaluate the effect of feedback delay on the performance of closed loop power control in CDMA System. Even though power control can mitigate the problem fluctuation due to fading, however due to the feedback delay, that advantage is invisible if this parameter is not decreased. Feedback delay is the total time that is taken by the power control from the mobile transmit signal is estimated at base station until power update command is received again at the mobile to do the transmission power update. Feedback delay worsens the performance of closed loop power control. To see this effect of feedback delay, in this study we evaluated the system of closed loop at three delay interval, i.e. 1Tp (Tp=power control interval), 2Tp and 3Tp. Performance of power control subject to feedback delay would be evaluated in term of bit error rate (BER) as a function of bit energy Eb to interference power spectral density I0 (Eb/I0). The simulation results have shown that the feedback delay cause the performance of system is degraded even at feedback delay of 3Tp, the performance is drop until the system performance without power control. By joining analysis between feedback delay and selecting step size, we have found the tradeoff between step size=1 dB and 2 dB in specific feedback delay.","PeriodicalId":147311,"journal":{"name":"2010 Second International Conference on Advances in Computing, Control, and Telecommunication Technologies","volume":"398 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132081685","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