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2015 International Conference on Computational Science and Computational Intelligence (CSCI)最新文献

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Measures for the Improvement of Construction Work Accident Information Service Contents in CPMS: Focused on Analysis of Construction Work Accidents Big Data 完善CPMS建筑施工事故信息服务内容的措施——以建筑施工事故大数据分析为重点
2015 International Conference on Computational Science and Computational Intelligence (CSCI) Pub Date : 2015-12-07 DOI: 10.1109/CSCI.2015.51
Sung-Hoon Yang, Jin-uk Kim, Young-Jin Kim, Hyun Ok
{"title":"Measures for the Improvement of Construction Work Accident Information Service Contents in CPMS: Focused on Analysis of Construction Work Accidents Big Data","authors":"Sung-Hoon Yang, Jin-uk Kim, Young-Jin Kim, Hyun Ok","doi":"10.1109/CSCI.2015.51","DOIUrl":"https://doi.org/10.1109/CSCI.2015.51","url":null,"abstract":"This paper analyzes 14,578 cases of construction industry accidents based on big data for the improvement of the construction work accident information service contents of the Construction Project Management System (\"CPMS\"). The data were gathered from South Korea's major portal site that provides the accident causes, workers' behavior, injury areas, and injury factors. The data were surveyed in the following order. Factors (words) were extracted and classified into various categories, factors with predicates and adverbs were re-extracted, the target data were verified, factors were standardized and classified, and the rate and correlational rate by factor were analyzed. The analysis revealed that crash accidents involving high-place work accounted for 47% of all the accidents, arm and leg injuries, 29% and 26%, respectively, and bone fractures, 47%. For the injury causes by injury factor, crashes from ladders and roofs occurred most frequently, and for the injury areas by injury factor, leg injuries associated with materials, reinforcing bars, and excavators occurred most frequently.","PeriodicalId":417235,"journal":{"name":"2015 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116126753","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
Accumulated Citation Count as Fertileness of Scientific Article 累计引用计数作为科学文章的肥沃度
2015 International Conference on Computational Science and Computational Intelligence (CSCI) Pub Date : 2015-12-07 DOI: 10.1109/CSCI.2015.74
S. Hirokawa, Tetsuya Nakatoh, Hayato Nakanishi
{"title":"Accumulated Citation Count as Fertileness of Scientific Article","authors":"S. Hirokawa, Tetsuya Nakatoh, Hayato Nakanishi","doi":"10.1109/CSCI.2015.74","DOIUrl":"https://doi.org/10.1109/CSCI.2015.74","url":null,"abstract":"The literature survey by scientific bibliographic data base is indispensable in the research activities. We can find related articles with appropriate keywords. However, the threads of related research are not easy to grasp from the search result. It is necessary to repeat a search, judge a citation relation and figure out the thread. The present paper proposes the index \"accumulated citation count\" of a scientific article to measure the thread of citations that starts from the article.","PeriodicalId":417235,"journal":{"name":"2015 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126251463","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
Collaborative working: Understanding mobile applications requirements 协同工作:理解移动应用程序需求
2015 International Conference on Computational Science and Computational Intelligence (CSCI) Pub Date : 2015-12-07 DOI: 10.1109/CSCI.2015.86
Lizbeth Gallardo-López, B. González-Beltrán, Roberto Garcia-Madrid, Marco Ferruzca, Irma A. Zafra-Ballinas, J. Reyes-Ortíz
{"title":"Collaborative working: Understanding mobile applications requirements","authors":"Lizbeth Gallardo-López, B. González-Beltrán, Roberto Garcia-Madrid, Marco Ferruzca, Irma A. Zafra-Ballinas, J. Reyes-Ortíz","doi":"10.1109/CSCI.2015.86","DOIUrl":"https://doi.org/10.1109/CSCI.2015.86","url":null,"abstract":"The Rational Unified Process (RUP) as well as the related work embrace the importance of collaborative working teams during software development, but, user-interface designers and system analysts work in parallel or in sequential mode. However, this kind of relationship may not be effective, resulting on functional software but not meeting usability issues. Our proposal is that in order to understand mobile applications requirements work should be made collaboratively between analysts and user-interface designers through sharing artifacts like use-case scenarios, sketching and mock-up. In this paper, we propose a collaborative work framework to meet mobile applications requirements. Also, we show preliminary results of a case study to assess this approach. Results suggest that the collaborative team got a common understanding about system limits and functional and usability requirements.","PeriodicalId":417235,"journal":{"name":"2015 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126191913","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 Healthcare Decision-Making Model Using a Classifier-Based Disease Reasoning 基于分类器的疾病推理的医疗决策模型
2015 International Conference on Computational Science and Computational Intelligence (CSCI) Pub Date : 2015-12-07 DOI: 10.1109/CSCI.2015.96
Byungkwan Lee, E. Jeong, Jeong Ah Kim
{"title":"A Healthcare Decision-Making Model Using a Classifier-Based Disease Reasoning","authors":"Byungkwan Lee, E. Jeong, Jeong Ah Kim","doi":"10.1109/CSCI.2015.96","DOIUrl":"https://doi.org/10.1109/CSCI.2015.96","url":null,"abstract":"This paper proposes a Healthcare Decision-making Model using a Classifier-based Disease Reasoning. The proposed model consists of a Classifier-based Filtering Module (CFM) and a Disease Reasoning Module (DRM). The CFM extracts only the data necessary for a Decision-making by filtering Disease and Therapy data with a Classifier based Feature Elimination (CFE) algorithm. The DRM generates disease reasoning rules with the data extracted from the CFM by using Markov Process and makes a decision with the generated reasoning rules. The experimental result, the precision of CFE algorithm is improved better than that of the SVM by average 4.7%. In addition, the reasoning result generated by the DRM excels the C 4.5 algorithm by 2% in precision.","PeriodicalId":417235,"journal":{"name":"2015 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128213523","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
Applied Machine Learning to Identify Alzheimer's Disease through the Analysis of Magnetic Resonance Imaging 应用机器学习识别阿尔茨海默病通过分析磁共振成像
2015 International Conference on Computational Science and Computational Intelligence (CSCI) Pub Date : 2015-12-07 DOI: 10.1109/CSCI.2015.143
E. Novoa-Del-Toro, J. Fernández-Ruíz, H. Acosta-Mesa, N. Cruz-Ramírez
{"title":"Applied Machine Learning to Identify Alzheimer's Disease through the Analysis of Magnetic Resonance Imaging","authors":"E. Novoa-Del-Toro, J. Fernández-Ruíz, H. Acosta-Mesa, N. Cruz-Ramírez","doi":"10.1109/CSCI.2015.143","DOIUrl":"https://doi.org/10.1109/CSCI.2015.143","url":null,"abstract":"Alzheimer's disease is among the most common neurodegenerative diseases [1], doubling the number of patients every 5-year interval beyond age 65 [2]. Different investigations have proven that patients with Alzheimer's disease, show volume reduction at specific areas of the brain [1, 3-11]. Some of these areas, like the precuneus, start showing atrophy since early stages of the disease [1, 3, 6, 12-14], as measured through the use of Magnetic Resonance Imaging [9]. Considering this, we studied the possible use of the precuneus as a biomarker to identify such disease. Our results suggest that the precuneus is a potential biomarker to detect Alzheimer's disease, since 7 out of 10 patients (73.33% of accuracy) can be correctly classified.","PeriodicalId":417235,"journal":{"name":"2015 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127241822","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
A New Scheme for Implementing S-box Based on Neural Network 基于神经网络的S-box实现新方案
2015 International Conference on Computational Science and Computational Intelligence (CSCI) Pub Date : 2015-12-07 DOI: 10.1109/CSCI.2015.9
Xia Zhang, F. Chen, Bo Chen, Zhongwei Cao
{"title":"A New Scheme for Implementing S-box Based on Neural Network","authors":"Xia Zhang, F. Chen, Bo Chen, Zhongwei Cao","doi":"10.1109/CSCI.2015.9","DOIUrl":"https://doi.org/10.1109/CSCI.2015.9","url":null,"abstract":"S-box (Substitution box) is one of the most important components in the block cipher. As the high non-linearity of neural network (or artificial neural network, ANN) is in high accordance with the properties of cipher, the application of neural network in cryptography becomes a significant orientation. In this paper, we present a new scheme for implementing S-box used in ciphers basing on neural network. Differing from the previous network models, the proposed network, which can be used to implement any Boolean function in S-box, consists of multiple neural network perceptrons, and each perceptron only has a low number of input variables (4-bits input). By DNA-like learning algorithm, it is very convenient to train the weight and threshold values of the network.","PeriodicalId":417235,"journal":{"name":"2015 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"32 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130735551","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
Biologically-Inspired Neural Network for Coordinated Urban Traffic Control: Parameter Determination and Stability Analysis 基于生物启发的城市交通协调控制神经网络:参数确定与稳定性分析
2015 International Conference on Computational Science and Computational Intelligence (CSCI) Pub Date : 2015-12-07 DOI: 10.1109/CSCI.2015.43
Guilherme B. Castro, D. S. Miguel, B. P. Machado, A. Hirakawa
{"title":"Biologically-Inspired Neural Network for Coordinated Urban Traffic Control: Parameter Determination and Stability Analysis","authors":"Guilherme B. Castro, D. S. Miguel, B. P. Machado, A. Hirakawa","doi":"10.1109/CSCI.2015.43","DOIUrl":"https://doi.org/10.1109/CSCI.2015.43","url":null,"abstract":"Traffic congestions are a major concern for big cities around the world due to its multifaceted negative impacts. A cost-effective solution to reduce vehicle travel times and prevent traffic congestions is traffic signal control. In this work, we investigate a biologically-inspired neural network, which, in contrast to other approaches, is able to continuously monitor the system state and make decisions. An extension of a previous model is proposed, establishing a multiagent system and allowing the coordinated control of multiple intersections. Methods for parameter determination and stability analysis are also proposed. Finally, the model performance for different sets of parameters and vehicle demands is evaluated with a simulator of urban mobility and compared to a conventional cycle-based control method.","PeriodicalId":417235,"journal":{"name":"2015 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131838564","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
Sharing Information Promoting Unhealthy Behavior through Social Media: Examination of the Users and the Content Using the Case of Pro-Anorexia in Tumblr 通过社交媒体分享促进不健康行为的信息:以Tumblr的亲厌食症为例对用户和内容的考察
2015 International Conference on Computational Science and Computational Intelligence (CSCI) Pub Date : 2015-12-07 DOI: 10.1109/CSCI.2015.122
M. McLaughlin, Mina Park, Yao Sun
{"title":"Sharing Information Promoting Unhealthy Behavior through Social Media: Examination of the Users and the Content Using the Case of Pro-Anorexia in Tumblr","authors":"M. McLaughlin, Mina Park, Yao Sun","doi":"10.1109/CSCI.2015.122","DOIUrl":"https://doi.org/10.1109/CSCI.2015.122","url":null,"abstract":"Social media provides a place where individuals obtain health information and share social support. Previous literature, however, has suggested that social media may promote harm when users share information advocating unhealthy behaviors. By focusing on online discourse around pro-anorexia content on Tumblr (the promotion of behaviors related to the eating disorder based on a lifestyle view that being extremely thin is beautiful), this study aims to look at how information about the pro-anorexia perspective is circulated among social media users and the way in which such users can be characterized. Specifically, we plan to analyze the content and examine the shared characteristics of the users who are exposed to similar social media content and have a desire to share it.","PeriodicalId":417235,"journal":{"name":"2015 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131919328","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
On Predicting the Optimal Number of Hidden Nodes 关于最优隐节点数的预测
2015 International Conference on Computational Science and Computational Intelligence (CSCI) Pub Date : 2015-12-07 DOI: 10.1109/CSCI.2015.33
Alan J. Thomas, M. Petridis, S. Walters, Saeed Malekshahi Gheytassi, R. Morgan
{"title":"On Predicting the Optimal Number of Hidden Nodes","authors":"Alan J. Thomas, M. Petridis, S. Walters, Saeed Malekshahi Gheytassi, R. Morgan","doi":"10.1109/CSCI.2015.33","DOIUrl":"https://doi.org/10.1109/CSCI.2015.33","url":null,"abstract":"Determining the optimal number of hidden nodes is the most challenging aspect of Artificial Neural Network (ANN) design. To date, there are still no reliable methods of determining this a priori, as it depends on so many domain-specific factors. Current methods which take these into account, such as exhaustive search, growing and pruning and evolutionary algorithms are not only inexact, but also extremely time consuming -- in some cases prohibitively so. A novel approach embodied in a system called Heurix is introduced. This rapidly predicts the optimal number of hidden nodes from a small number of sample topologies. It can be configured to favour speed (low complexity), accuracy, or a balance between the two. Single hidden layer feedforward networks (SLFNs) can be built twenty times faster, and with a generalisation error of as little as 0.4% greater than those found by exhaustive search.","PeriodicalId":417235,"journal":{"name":"2015 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125642728","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: 31
Visualization of Subtopics of the Thematic Document Collection Using the Context-Semantic Graph 基于上下文语义图的专题文档集子主题可视化
2015 International Conference on Computational Science and Computational Intelligence (CSCI) Pub Date : 2015-12-07 DOI: 10.1109/CSCI.2015.124
A. Sboev, I. Moloshnikov, D. Gudovskikh, R. Rybka
{"title":"Visualization of Subtopics of the Thematic Document Collection Using the Context-Semantic Graph","authors":"A. Sboev, I. Moloshnikov, D. Gudovskikh, R. Rybka","doi":"10.1109/CSCI.2015.124","DOIUrl":"https://doi.org/10.1109/CSCI.2015.124","url":null,"abstract":"An approach for visualization of nested topics within large collections of documents is proposed. The approach is based on set of parameters: information entropy, Kullback-Leibler divergence, Ginzburg algorithm, similarity the distributions of keywords and key phrases in the documents with Bernoulli's theoretical distributions. The results of comparisons of our approach with implementations based on TF-IDF approaches are presented.","PeriodicalId":417235,"journal":{"name":"2015 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132249315","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
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