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2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE)最新文献

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The history of hacking SIGMA: An autonomous and collaborative vocabulary learning system SIGMA:一个自主和协作的词汇学习系统
2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2011-05-11 DOI: 10.1109/JCSSE.2011.5930159
K. Kaneko, H. Miyakoda
{"title":"The history of hacking SIGMA: An autonomous and collaborative vocabulary learning system","authors":"K. Kaneko, H. Miyakoda","doi":"10.1109/JCSSE.2011.5930159","DOIUrl":"https://doi.org/10.1109/JCSSE.2011.5930159","url":null,"abstract":"In this paper, we recapitulate the history of hacking the SIGMA system, an autonomous and collaborative vocabulary learning system, over five years. The results obtained from various evaluation experiments have shown that (1) the vocabulary learning materials created by the SIGMA system are effective in enhancing vocabulary attainment; (2) the materials created not only by instructors but by the learners themselves are effective as learning tools; (3) the evaluation results that learners share in the system are actually helpful in allowing the users to select materials that enhance vocabulary learning.","PeriodicalId":287775,"journal":{"name":"2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128779534","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 objective visual fatigue measurement system by using a remote infrared camera 一种基于红外远红外相机的视觉疲劳测量系统
2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2011-05-11 DOI: 10.1109/JCSSE.2011.5930117
Jinman Kim, E. Lee, Jao Sang Lim
{"title":"A new objective visual fatigue measurement system by using a remote infrared camera","authors":"Jinman Kim, E. Lee, Jao Sang Lim","doi":"10.1109/JCSSE.2011.5930117","DOIUrl":"https://doi.org/10.1109/JCSSE.2011.5930117","url":null,"abstract":"This paper presents a new objective visual fatigue measurement system by using one remote camera. In captured image, eye and pupil regions are sequentially detected using some image processing methods. Based on the pupil region, pupil size, pupil accommodation speed, blink frequency, and eye closed duration can be determined. Because more frequent blinks and slower pupil accommodation indicate an increased level of visual fatigue, our system can objectively measure visual fatigue. Also, since there is no need to wear any device, inconvenience may be minimized. Experimental results showed the blink detection accuracy was 98.9% and pupil localization error was 1.9%.","PeriodicalId":287775,"journal":{"name":"2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123005568","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
Model-based system tool for Thai Tax Revenue Forecasting (MBS-TTRF) 基于模型的泰国税收预测系统工具(MBS-TTRF)
2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2011-05-11 DOI: 10.1109/JCSSE.2011.5930108
J. Mitrpanont, Pattama Tounprasert
{"title":"Model-based system tool for Thai Tax Revenue Forecasting (MBS-TTRF)","authors":"J. Mitrpanont, Pattama Tounprasert","doi":"10.1109/JCSSE.2011.5930108","DOIUrl":"https://doi.org/10.1109/JCSSE.2011.5930108","url":null,"abstract":"Model-Based System Tool for Thai Tax Revenue Forecasting (MBS-TTRF) is a model-based management system used to provide the flexibility and increase efficiency of Thai Tax Revenue Forecasting in the Revenue Department (RD). MBSTTRF contains five essential model-categories for Tax Revenue Forecasting, i.e., ETTRF Models, NITTRF Models, STTRF Models, TTRF A Models, and TTRFAC Models. The system supports the data analytical functions: Sensitivity, What-if and Goal-seeking analysis, useful for analyzing results before making a decision. Furthermore, this system also improves the accuracy of Thai Tax Revenue Forecasting by adding regression approach to NITTRF. The experimental results showed that NITTRF generated better results than the existing model-ETTRF. The results also showed that MBS-TTRF is suitable to assist a user/decision maker as an alternative model to forecast tax revenue and reduces time for Thai Tax Revenue Forecasting operation that depends mainly on human expertise.","PeriodicalId":287775,"journal":{"name":"2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127859136","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
A comparative study on indoor localization based on RSSI measurement in wireless sensor network 无线传感器网络中基于RSSI测量的室内定位比较研究
2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2011-05-11 DOI: 10.1109/JCSSE.2011.5930074
Ratana Priwgharm, Panarat Chemtanomwong
{"title":"A comparative study on indoor localization based on RSSI measurement in wireless sensor network","authors":"Ratana Priwgharm, Panarat Chemtanomwong","doi":"10.1109/JCSSE.2011.5930074","DOIUrl":"https://doi.org/10.1109/JCSSE.2011.5930074","url":null,"abstract":"This paper studies on the localization techniques using in wireless sensor network (WSN) for an indoor environment. We compare two main categories of localization techniques: range-based and fingerprinting-based techniques on a single experimental environment. The received signal strength indicator (RSSI received at sensor nodes are used for all localization techniques. For the range-base techniques, the location estimation approach based on the lateration estimation and the min-max approach are employed. For the fingerprinting based techniques, two pattern matching approaches are used: one is the simple nearest neighbor algorithm and another one is the k-nearest-nearest neighbor algorithm. The experiments are conducted in a meeting room where is a small number of obstacles inside to evaluate the performance of each technique. The results demonstrate that the location estimation algorithm using lateration estimation gives the best accuracy and also less computational time compared to other techniques.","PeriodicalId":287775,"journal":{"name":"2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"176 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122876328","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: 34
Classification of Japanese onomatopoeias using hierarchical clustering depending on contexts 基于上下文的日语拟声词分层聚类分类
2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2011-05-11 DOI: 10.1109/JCSSE.2011.5930103
Kanako Komiya, Y. Kotani
{"title":"Classification of Japanese onomatopoeias using hierarchical clustering depending on contexts","authors":"Kanako Komiya, Y. Kotani","doi":"10.1109/JCSSE.2011.5930103","DOIUrl":"https://doi.org/10.1109/JCSSE.2011.5930103","url":null,"abstract":"Japanese has thousands of onomatopoeias and they have recently started to attract a lot of attention of researchers on natural language processing. Some onomatopoeias are semantically or phonologically similar each other and the choice of these onomatopoeias sometimes give a big difference among Japanese sentences. In this paper, the authors classify Japanese onomatopoeias using single link hierarchical clustering depending on contexts such as surrounding words, their part-of-speeches and their meanings, and show explicitly the relationships of them from the perspective of word senses.","PeriodicalId":287775,"journal":{"name":"2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124412885","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
Bad-smell prediction from software design model using machine learning techniques 利用机器学习技术从软件设计模型中预测臭味
2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2011-05-11 DOI: 10.1109/JCSSE.2011.5930143
Nakarin Maneerat, Pomsiri Muenchaisri
{"title":"Bad-smell prediction from software design model using machine learning techniques","authors":"Nakarin Maneerat, Pomsiri Muenchaisri","doi":"10.1109/JCSSE.2011.5930143","DOIUrl":"https://doi.org/10.1109/JCSSE.2011.5930143","url":null,"abstract":"Bad-smell prediction significantly impacts on software quality. It is beneficial if bad-smell prediction can be performed as early as possible in the development life cycle. We present methodology for predicting bad-smells from software design model. We collect 7 data sets from the previous literatures which offer 27 design model metrics and 7 bad-smells. They are learnt and tested to predict bad-smells using seven machine learning algorithms. We use cross-validation for assessing the performance and for preventing over-fitting. Statistical significance tests are used to evaluate and compare the prediction performance. We conclude that our methodology have proximity to actual values.","PeriodicalId":287775,"journal":{"name":"2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117023093","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: 62
Solving software module clustering problem by evolutionary algorithms 用进化算法求解软件模块聚类问题
2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2011-05-11 DOI: 10.1109/JCSSE.2011.5930112
Kata Praditwong
{"title":"Solving software module clustering problem by evolutionary algorithms","authors":"Kata Praditwong","doi":"10.1109/JCSSE.2011.5930112","DOIUrl":"https://doi.org/10.1109/JCSSE.2011.5930112","url":null,"abstract":"Well organized software is easy to maintain but software modularization is complicated because of the number of modules. Automated software module clustering is transformed to a search-based problem. This paper describes the experiments on real-world problems of software module clustering by metaheuristic search methods such as genetic algorithms. This paper introduces the Grouping Genetic Algorithm (GGA) to the benchmarks. The fitness function measures a module granularity which is cohesion and coupling. Empirical result reports that the GGA outperforms a genetic algorithm with string representation.","PeriodicalId":287775,"journal":{"name":"2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115804269","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: 42
Clustering by attraction and distraction 通过吸引和分散来聚集
2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2011-05-11 DOI: 10.1109/JCSSE.2011.5930149
J. Chongstitvatana, Wanwara Thubtimdang
{"title":"Clustering by attraction and distraction","authors":"J. Chongstitvatana, Wanwara Thubtimdang","doi":"10.1109/JCSSE.2011.5930149","DOIUrl":"https://doi.org/10.1109/JCSSE.2011.5930149","url":null,"abstract":"Clustering is data analysis which aims to group similar objects together while separating them from dissimilar objects. Centroid-based clustering methods create clusters of objects in the shape of hyper-sphere, and thus cannot create clusters correctly when similar objects do not form a hyper-sphere. This work proposes an agglomerative clustering method using the concept of attraction and distraction. Attraction is measured by the number of similar object pairs in two clusters and the size of the two clusters. Distraction is the possibility that there are other possible cluster pairs to be merged. The proposed algorithm is evaluated against K-means algorithm, and it is found that it gives higher accuracy then K-means algorithm on iris and Haberman survival datasets, lower accuracy on breast cancer and SPECT heart test datasets, and comparable accuracy on wine dataset.","PeriodicalId":287775,"journal":{"name":"2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114741555","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: 4
Thai handwritten character recognition using heuristic rules hybrid with neural network 基于启发式规则和神经网络的泰文手写体字符识别
2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2011-05-11 DOI: 10.1109/JCSSE.2011.5930113
J. Mitrpanont, Yingyot Imprasert
{"title":"Thai handwritten character recognition using heuristic rules hybrid with neural network","authors":"J. Mitrpanont, Yingyot Imprasert","doi":"10.1109/JCSSE.2011.5930113","DOIUrl":"https://doi.org/10.1109/JCSSE.2011.5930113","url":null,"abstract":"This research enhanced two major processes of the previous work of the off-line Thai handwritten character recognition using hybrid techniques of heuristic rules and neural network system. The proposed functions are mainly in 1) Feature extraction enhancement to improve the feature conflict resolution rule and the specialized neural network-based zigzag feature extraction. These functions are used to refine the conflict features and zigzag patterns; 2) Neural network-based recognition. Specifically, a neural network technique improves the capabilities of the recognition process to handle various styles of writing. The result showed that the additional feature conflict resolution rule could achieve the feature extraction rate of 87.85% (increased 2.13%), the feature extraction rate of the specialized neural network-based zigzag extraction could achieve 90.48% (increased 47.9%) and the recognition rate of the neural network-based recognition which combine both of the two proposed feature extraction functions could achieve 92.78% (increased 9.77%).","PeriodicalId":287775,"journal":{"name":"2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125352470","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
Data dependency reduction in Dynamic Programming matrix 动态规划矩阵中数据依赖性的减少
2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2011-05-11 DOI: 10.1109/JCSSE.2011.5930126
Guillermo Delgado, C. Aporntewan
{"title":"Data dependency reduction in Dynamic Programming matrix","authors":"Guillermo Delgado, C. Aporntewan","doi":"10.1109/JCSSE.2011.5930126","DOIUrl":"https://doi.org/10.1109/JCSSE.2011.5930126","url":null,"abstract":"Dynamic Programming (DP) plays an important role in solving a large number of computational problems. As the number of cores per processor is increasing rapidly, new software must be capable of exploiting the advantages of multicore architectures. A typical DP begins with constructing a matrix, and then calculating each element one by one. The standard parallelization spawns multiple threads, one for each row, while maintains the data dependency via thread synchronization. However, as the number of cores increase, the performance degrades due to data dependency. Herein, we propose a novel method for calculating a DP matrix in parallel. In contrast to the standard method that always calculates from up to down and left to right, our method performs the calculation in multiple directions. Therefore, the wait time for data dependency is remarkably reduced. To demonstrate our method, a local sequence alignment algorithm called Smith-Waterman (SW) was chosen as an instance of DP. However, our method is not only limited to SW algorithm, but it is applicable to other DP problems that have the similar patterns of data dependency. A comparison with the standard method was conducted on HP Z800 Workstation equipped with two quad-core processors. The results show that our method performs significantly faster than the classical approach.","PeriodicalId":287775,"journal":{"name":"2011 Eighth International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125203240","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: 11
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