2008 2nd IEEE International Conference on Digital Ecosystems and Technologies最新文献_第4页

Detection of traffic volume anomalies by evolution of negative classifiers in Artificial Immune Systems 基于人工免疫系统负分类器进化的交通流量异常检测

2008 2nd IEEE International Conference on Digital Ecosystems and Technologies Pub Date : 2008-09-30 DOI: 10.1109/DEST.2008.4635190

A. Azzini, E. Damiani, G. Gianini, S. Marrara

引用次数: 0

Adding factory floor automation to digital ecosystems; tools, technology and transformation. 在数字生态系统中增加工厂车间自动化;工具、技术和转型。

2008 2nd IEEE International Conference on Digital Ecosystems and Technologies Pub Date : 2008-09-30 DOI: 10.1109/DEST.2008.4635176

P. Phaithoonbuathong, T. Kirkham, C. S. McLeod, M. Capers, R. Harrison, R. Monfared

引用次数: 12

Accommodating substructure similarity-based search in a recipe database system 适应配方数据库系统中基于子结构相似性的搜索

2008 2nd IEEE International Conference on Digital Ecosystems and Technologies Pub Date : 2008-09-30 DOI: 10.1109/DEST.2008.4635199

Liping Wang, Qing Li, Na Li

引用次数: 1

Potential risks and benefits of Service-oriented Collaboration - basic considerations and results from an empirical study 面向服务的协作的潜在风险和收益——一个实证研究的基本考虑和结果

2008 2nd IEEE International Conference on Digital Ecosystems and Technologies Pub Date : 2008-09-30 DOI: 10.1109/DEST.2008.4635153

Stefan Schulte, N. Repp, J. Eckert, R. Berbner, K. Blanckenburg, Ralf Schaarschmidt, Ralf Steinmetz

引用次数: 7

Agent-based modelling of supply chain management in a Virtual Enterprise 基于agent的虚拟企业供应链管理建模

2008 2nd IEEE International Conference on Digital Ecosystems and Technologies Pub Date : 2008-09-30 DOI: 10.1109/DEST.2008.4635215

R. M. Alade, S. Sadik, A. Ali, A. Farooq, H. Suguri

{"title":"Agent-based modelling of supply chain management in a Virtual Enterprise","authors":"R. M. Alade, S. Sadik, A. Ali, A. Farooq, H. Suguri","doi":"10.1109/DEST.2008.4635215","DOIUrl":"https://doi.org/10.1109/DEST.2008.4635215","url":null,"abstract":"The supply chain plays a vital role in the procurement, delivery and manufacturing of raw materials as well as supply of finished products in a network of business processes. The major challenges facing the system are efficient coordination and prompt production planning in meeting and sometimes exceeding customerspsila expectations. Agent-based approach to modelling such business processes has much recompense especially in a virtual enterprise where business entities are distributed over dispersed geographical locations. This model takes advantage of core agentpsilas features and adds autonomous and flexible properties to supply chain system, thus making it proactive and responsive to better compete and efficiently collaborate in creating customer-centred products. In this paper, we propose a multi-agent system framework for a Virtual Enterprise (VE) involved in the manufacturing of products and capture the logic of the production planning with a simple decision tree. This approach relatively simplifies the transformation of the complex logic property of the system to a declarative programming language and facilitates implementation. Also, the agents collaboratively get product order from customers, plan and execute the production processes as well as coordinate the prompt delivery of the finished products. This makes the system akin to a digital ecosystem and invariably gives such business enterprise an edge over its counterparts in the highly competitive market place.","PeriodicalId":380627,"journal":{"name":"2008 2nd IEEE International Conference on Digital Ecosystems and Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129729760","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

Raising information security awareness in digital ecosystem with games - a pilot study in Thailand 通过游戏提高数字生态系统的信息安全意识——泰国试点研究

2008 2nd IEEE International Conference on Digital Ecosystems and Technologies Pub Date : 2008-09-30 DOI: 10.1109/DEST.2008.4635145

C. Fung, V. Khera, A. Depickere, P. Tantatsanawong, P. Boonbrahm

引用次数: 27

Comparison of attribute selection techniques and algorithms in classifying bad behaviors of vocational education students 高职学生不良行为分类的属性选择技术与算法比较

2008 2nd IEEE International Conference on Digital Ecosystems and Technologies Pub Date : 2008-09-30 DOI: 10.1109/DEST.2008.4635213

Sukontip Wongpun, A. Srivihok

{"title":"Comparison of attribute selection techniques and algorithms in classifying bad behaviors of vocational education students","authors":"Sukontip Wongpun, A. Srivihok","doi":"10.1109/DEST.2008.4635213","DOIUrl":"https://doi.org/10.1109/DEST.2008.4635213","url":null,"abstract":"This study presents the comparison of attribute selection techniques which used for classifying the bad behaviors of vocational education students. There are two classification methods: hybrid classification and single classification. Hybrid classification includes two steps, step one is attribute selection by search method using genetic search and results are compared by three evaluators: 1) Correlation-based Feature Selection (CFS) 2) Consistency-based Subset Evaluation and 3) Wrapper Subset Evaluation. Step two is the classification of data set by using selected attributed from step one and four classification algorithms. Next, Simple classification used classification algorithms only without attribute selection. The four classification algorithms that used in this experiment for comparing in two methods are : 1) Naive Bayes classifier 2) Baysian Belief Network 3) C4.5 algorithm and 4) RIPPER algorithm. The measurements of classification efficiency had been obtained by using the k-fold cross validation technique. From the experiment, it was found that hybrid classification technique using genetic search and CFS evaluator with C4.5 algorithm, gives the highest accuracy rate at 82.52%. However, results from F-measure evaluation showed that C4.5 algorithm did not fit for all data types. The hybrid classification technique using genetic search and wrapper subset with Baysian belief network can give a better precision value which can be seen in the F-measure, and it gives the accuracy rate at 82.42%.","PeriodicalId":380627,"journal":{"name":"2008 2nd IEEE International Conference on Digital Ecosystems and Technologies","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132864270","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: 21

A resource based formal methodology to detect non-conformance in processes 一种基于资源的正式方法，用于检测过程中的不符合项

2008 2nd IEEE International Conference on Digital Ecosystems and Technologies Pub Date : 2008-09-30 DOI: 10.1109/DEST.2008.4635184

Sean Thompson, T. Torabi

引用次数: 0

Personalized information retrieval in digital ecosystems 数字生态系统中的个性化信息检索

2008 2nd IEEE International Conference on Digital Ecosystems and Technologies Pub Date : 2008-09-30 DOI: 10.1109/DEST.2008.4635207

Dengya Zhu, H. Dreher

引用次数: 2

Web-based evaluation system for online courses and Learning Management Systems 基于网络的在线课程评估系统和学习管理系统

2008 2nd IEEE International Conference on Digital Ecosystems and Technologies Pub Date : 2008-09-30 DOI: 10.1109/DEST.2008.4635208

C. Snae, M. Bruckner

引用次数: 4