2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing最新文献

Design of energy-consumption-aware evolutional agent system for portable devices 便携式设备能耗感知进化智能体系统设计

2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2013-07-16 DOI: 10.1109/ICCI-CC.2013.6622252

Wenpeng Wei, Akiko Takahashi, Tetsuo Kinoshita

引用次数: 0

Fusion of two visual perception systems utilizing cognitive diversity 利用认知多样性的两种视觉感知系统融合

2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2013-07-16 DOI: 10.1109/ICCI-CC.2013.6622248

Elena Paolercio, Cameron McMunn-Coffran, Brian Mott, D. Hsu, Christina Schweikert

{"title":"Fusion of two visual perception systems utilizing cognitive diversity","authors":"Elena Paolercio, Cameron McMunn-Coffran, Brian Mott, D. Hsu, Christina Schweikert","doi":"10.1109/ICCI-CC.2013.6622248","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622248","url":null,"abstract":"Decision-making tasks that are based on perception have been performed routinely by human beings in daily life and decision-makers in daily work. It has been observed that the combination of two perception-based decisions could be better than one, provided that the decision-makers communicate with each other and jointly adopt the most confident judgment; simply select the most confident judgment without any dyadic interaction, or communicate with each other on shareable arguments based on reasoning. In this paper, we report a recently conducted visual perception experiment with decisions from nineteen pairs of subjects and their reported confidence factors when making such a decision. Utilizing the concept of a “cognitive diversity” between two systems and the combinatorial fusion algorithm, our results demonstrated that the fusion of two visual perception decision systems can be better than each of the individual systems only if the two systems perform relatively good and they are cognitively diverse. Our study not only provides a robust algorithm to fuse two visual perception decision-making systems, but also suggests a resilient approach to use the cognitive diversity in fusion when the performance of each individual system is not known or cannot be obtained, which is often the case for complex problems.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121054033","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

Circuit delay computation based on ITTPN 基于ITTPN的电路延迟计算

2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2013-07-16 DOI: 10.1109/ICCI-CC.2013.6622282

Shuangjia Shao, G. Luo, Jian Luo, Xibin Zhao

引用次数: 0

A real-time soft measurement method based on the furnace system parameters of the forecast model 提出了一种基于炉系参数预测模型的实时软测量方法

2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2013-07-16 DOI: 10.1109/ICCI-CC.2013.6622283

Jun-ling Yang, Yingying Su, Xianrong Liu, W. Ye

引用次数: 0

Research on a novel image encryption algorithm based on the hybrid of chaotic maps and DNA encoding 基于混沌映射与DNA编码混合的图像加密算法研究

2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2013-07-16 DOI: 10.1109/ICCI-CC.2013.6622274

Jun Peng, Shangzhu Jin, Liang Lei, Qi Han

引用次数: 10

Brain dump: How publicly available fMRI can help inform neuronal network architecture 脑转储:如何公开可用的fMRI可以帮助告知神经网络架构

2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2013-07-16 DOI: 10.1109/ICCI-CC.2013.6622215

Gabriele Fariello

{"title":"Brain dump: How publicly available fMRI can help inform neuronal network architecture","authors":"Gabriele Fariello","doi":"10.1109/ICCI-CC.2013.6622215","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622215","url":null,"abstract":"Summary form only given. Connectomics is an emergent discipline of Neuroinformatics that studies how the brain is connected, both anatomically and functionally. A number of projects throughout the neuroscience community have tackled the problem of determining interconnectivity from the nano scale - such as those enabled by laser-scanning light microscopy and semi-automated electron microscopy - to the micro scale of neurons and neuron clusters, to the macro scale of fMRI. The amount of data required to map out the macro scale is in the manageable multi-terabyte range, and largely exists today, while gathering one milometer cubed of synaptic-level data already approaches the multi-petabyte scale and is a few years away. Between these two extremes most likely lies the fastest and most representative path to a useful map of human neuronal connectivity. Although extremely informative on may topics concerning neuronal connectivity, the of the main limitations of the smaller scale approaches are 1) the considerable amount of time and energy needed to have one sample which will likely not be widely representative of a typical human brain and 2) their highly invasive or destructive nature renders them poorly adaptable to living humans.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117028454","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

Prediction for the development data of oil field with multi-variable phase space reconstruction method and support vector machines 基于多变量相空间重构法和支持向量机的油田开发数据预测

2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2013-07-16 DOI: 10.1109/ICCI-CC.2013.6622290

Hong Liu, Jiangxin Feng, Shuoliang Wang, X. Zou, Jing Zhou, Jun Yang

{"title":"Prediction for the development data of oil field with multi-variable phase space reconstruction method and support vector machines","authors":"Hong Liu, Jiangxin Feng, Shuoliang Wang, X. Zou, Jing Zhou, Jun Yang","doi":"10.1109/ICCI-CC.2013.6622290","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622290","url":null,"abstract":"Time series analysis is a branch of the strong application of statistical probability. It has a wide range of applications in the field of industrial automation, hydrology, geology, meteorology and other natural domain. However, the application in the oil field development is not extensive. Currently the one-dimensional single variable time series analysis method is used to predict oil and water production. This method, however, is completely isolated without considering the relationship between oil production, water production and pressure. Moreover, it does not take advantage of the evolution and essential characteristics of the entire reservoir system. In this paper, we use multi-variable phase space reconstruction method, not only considering the variation of historical oil production, but also taking the effect of the pressure change and water production change into consideration. This method can provide the information for each prediction and other sequences. The amount of available information had increased significantly, and the accuracy of the prediction had improved greatly.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126366857","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

Soft biometric verification by integrating static and dynamic features based on fuzzy inference 基于模糊推理的静态特征与动态特征相结合的软生物特征验证

2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2013-07-16 DOI: 10.1109/ICCI-CC.2013.6622250

Y. Manabe, K. Sugawara

引用次数: 3

Image retrieval based on YCbCr color histogram 基于YCbCr颜色直方图的图像检索

2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2013-07-16 DOI: 10.1109/ICCI-CC.2013.6622287

Liang Lei, Jun Peng, Bo Yang

引用次数: 6

IDEAL: Interactive design environment for agent system with learning mechanism 理想:具有学习机制的智能体系统的交互设计环境

2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing Pub Date : 2013-07-16 DOI: 10.1109/ICCI-CC.2013.6622238

Takahiro Uchiya, Syo Itazuro, I. Takumi, Tetsuo Kinoshita

引用次数: 4