2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing最新文献_第6页

The multi-deformable assembly contact analysis of rotate test tree 旋转试验树多变形装配接触分析

2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2012-09-24 DOI: 10.1109/ICCI-CC.2012.6311185

Jinghua Liu, G. Hu

引用次数: 0

Application of BP neural network to prediction of library circulation BP神经网络在图书馆流通量预测中的应用

2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2012-09-24 DOI: 10.1109/ICCI-CC.2012.6311183

Runhua Wang, Yi Tang, Lei Li

引用次数: 7

Security testing of a modular cryptosystem based on continuous cellular automata 基于连续元胞自动机的模块化密码系统的安全性测试

2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2012-09-24 DOI: 10.1109/ICCI-CC.2012.6311130

J. D. T. Gonzalez, W. Kinsner

引用次数: 1

Competences memory map: A model for the representation of competences applied in education 能力记忆图:一种在教育中应用的能力表征模型

2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2012-09-24 DOI: 10.1109/ICCI-CC.2012.6311175

C. Ramírez, Erik Sanchez

引用次数: 2

A collaborative management model in learning and teaching process (CollMMod-LTP): An application for problem solving and algorithms 学习与教学过程的协同管理模型(CollMMod-LTP):问题解决与算法的应用

2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2012-09-24 DOI: 10.1109/ICCI-CC.2012.6311190

L. Reynoso, Laura Sánchez, Jorge Rodríguez, Mabel Álvarez

{"title":"A collaborative management model in learning and teaching process (CollMMod-LTP): An application for problem solving and algorithms","authors":"L. Reynoso, Laura Sánchez, Jorge Rodríguez, Mabel Álvarez","doi":"10.1109/ICCI-CC.2012.6311190","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2012.6311190","url":null,"abstract":"This research aims at improving the management of learning and teaching process (LTP), more specifically observing the students' learning achievement and persistence, and teacher's interventions. To fulfill this purpose a Collaborative Management Model (CollMMod) has been defined during the last four years. In this paper we describe its main components (LTP-goals, LTP-stakeholders, LTP-variables, LTP-instruments, LTP-assessments) and its application in a course about Problem Solving and Algorithms at Universidad Nacional del Comahue using LTP-cognitive-variables. Results from the experience show that: collaborative members engaged in conducting and managing a TLP process may positively influence students' achievement; persistent practice activities where students can detect and correct their errors contribute to improve their achievement. Collected data were statistically analyzed; preliminary results show that there exists a moderate correlation between TLP cognitive variable-derived indicators and students' rate of success in final exams.","PeriodicalId":427778,"journal":{"name":"2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134026224","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

Researches on the topology optimization and simulation against attacks for MCN based on redundant links 基于冗余链路的MCN拓扑优化及抗攻击仿真研究

2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2012-09-24 DOI: 10.1109/ICCI-CC.2012.6311182

Xi Wan, Shigang Lin, Hongqin Zhou, H. Gu

引用次数: 1

Construction and analysis of dynamic S-boxes based on spatiotemporal chaos 基于时空混沌的动态s盒构造与分析

2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2012-09-24 DOI: 10.1109/ICCI-CC.2012.6311160

Jun Peng, Shangzhu Jin, Liang Lei, X. Liao

引用次数: 10

Proposal and evaluation of the toilet timing suggestion method for the elderly 老年人如厕时机建议方法的提出与评价

2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2012-09-24 DOI: 10.1109/ICCI-CC.2012.6311144

Airi Tsuji, Tomoko Yonezawa, H. Yamazoe, Shinji Abe, N. Kuwahara, K. Morimoto

引用次数: 4

Identification of Oil/Gas and water zones in geological logging with Support-vector Machine 支持向量机在地质测井油气水层识别中的应用

2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2012-09-24 DOI: 10.1109/ICCI-CC.2012.6311161

Hong Liu, Chunbi Xu, Xiaolu Wang, Tianyou Wang

{"title":"Identification of Oil/Gas and water zones in geological logging with Support-vector Machine","authors":"Hong Liu, Chunbi Xu, Xiaolu Wang, Tianyou Wang","doi":"10.1109/ICCI-CC.2012.6311161","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2012.6311161","url":null,"abstract":"Support Vector Machines (SVM) is systematic and properly motivated by Statistical Learning Theory (SLT). Training involves separating the classes with a surface that maximizes the margin between them. An interesting property of this approach is that it is an approximate implementation of Structural Risk Minimization (SRM) induction principle, therefore, SVM is more generalized performance and accurate as compared to artificial neural network which embodies the Embodies Risk Minimization (ERM) principle. The theory and method of Support Vector Machines based the Statistical Learning Theory and proposed a pattern recognition method based Support Vector Machine to determine oil, gas and water zones in geological logging are studied. The outline of the method is as follows: First, the basic parameters of the gasometry logging and geochemistry logging, and induced some significant parameters, such as hydrocarbon moistness index, pyrolysis hydrocarbon equilibrium index, gasometry hydrocarbon equilibrium index ,etc. are researched, which can help to distinguish the feature of reservoir; then the Support Vector Machine to study the relationship of those parameters is used, and the recognition mode and develop its program to determine of oil, gas and water zones are set up. Application and analysis of the experimental results in Xinjiang oilfield proved that SVM can achieve greater accuracy than the BP neural network does. It proved that identification of oil/gas and water zones in geological logging with SVM is reliable, adaptable, precise and easy to operate.","PeriodicalId":427778,"journal":{"name":"2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125598543","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 learning automaton for interaction with triple level environments 与三层环境交互的一种新的学习自动机

2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2012-09-24 DOI: 10.1109/ICCI-CC.2012.6311198

A. Jamalian, R. Rezvani, Hossein Shams, Shamim Mehrabi

{"title":"A new learning automaton for interaction with triple level environments","authors":"A. Jamalian, R. Rezvani, Hossein Shams, Shamim Mehrabi","doi":"10.1109/ICCI-CC.2012.6311198","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2012.6311198","url":null,"abstract":"Heretofore, the most presented Learning Automata (LA) is invented to interact with double level environments (one level for reward and the other for penalty). Those LA are often expedient, optimal or both of them and can minimize their mean value of receiving penalties (or at least converge to the minimum point) during time an d work much better than a pure-chance automaton. However, in many operational applications, the environment has three level responses; one for reward, one for small scale penalty and the last one for large scale penalty. In these applications, the old LA not only can not minimize the mean value of receiving penalties, but also in some cases their mean value of receiving penalties are even more than a pure-chance automaton. In this paper, first the triple level environments with illustrative example are described precisely. Then, the new fixed structure stochastic LA (called TILA) is introduced and its properties are considered mathematically. The simulation results show the old LA can not converge to the minimum value of the mean value of receiving penalties, but TILA receives fewer penalties in comparison with the older ones.","PeriodicalId":427778,"journal":{"name":"2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124155375","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: 7