2012 Conference on Technologies and Applications of Artificial Intelligence最新文献

A Visualization System for Animating Vertebrate Animal Models 脊椎动物模型动画可视化系统

2012 Conference on Technologies and Applications of Artificial Intelligence Pub Date : 2012-11-16 DOI: 10.1109/TAAI.2012.10

Lieu-Hen Chen, Yu-Sheng Chen, E. Sato-Shimokawara, Y. Takama, Toru Yamaguchi

{"title":"A Visualization System for Animating Vertebrate Animal Models","authors":"Lieu-Hen Chen, Yu-Sheng Chen, E. Sato-Shimokawara, Y. Takama, Toru Yamaguchi","doi":"10.1109/TAAI.2012.10","DOIUrl":"https://doi.org/10.1109/TAAI.2012.10","url":null,"abstract":"As computer graphics continue to progress, there is an increasingly large number of 3D models available on the internet. However, most of these models are static, with a rigid shape and fixed pose. Only a few models can be animated with restricted motion, which is generally produced by professional animators, or by using expensive motion capture equipment. Novice users generally have great difficulty trying to animate an arbitrarily static model without any motion data. In this paper, we propose an integrated animation system which aims to animate bipedal or quadrupedal 3D models. To achieve this, we began by developing a video-based motion database with several animal groups of biological classification. Each group consists of close genera and families which have similar features. In addition, for each group, there is an articulated standard skeleton with pre-designed cyclic motion patterns. Through a hierarchical graphical interface, users can select different motion pattern candidates from a biologically classified tree structure. The selected motion pattern is then applied to this model to automatically synthesize realistic bipedal or quadrupedal motion.","PeriodicalId":385063,"journal":{"name":"2012 Conference on Technologies and Applications of Artificial Intelligence","volume":"436 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115560225","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

Extended Binary Particle Swarm Optimization Approach for Disjoint Set Covers Problem in Wireless Sensor Networks 无线传感器网络不相交集覆盖问题的扩展二元粒子群优化方法

2012 Conference on Technologies and Applications of Artificial Intelligence Pub Date : 2012-11-16 DOI: 10.1109/TAAI.2012.63

Zhi-hui Zhan, Jun Zhang, Ke-Jing Du, Jing Xiao

{"title":"Extended Binary Particle Swarm Optimization Approach for Disjoint Set Covers Problem in Wireless Sensor Networks","authors":"Zhi-hui Zhan, Jun Zhang, Ke-Jing Du, Jing Xiao","doi":"10.1109/TAAI.2012.63","DOIUrl":"https://doi.org/10.1109/TAAI.2012.63","url":null,"abstract":"This paper proposes to use the binary particle swarm optimization (BPSO) approach to solve the disjoint set covers (DSC) problem in the wireless sensor networks (WSN). The DSC problem is to divide the sensor nodes into different disjoint sets and schedule them to work one by one in order to save energy while at the same time meets the surveillance requirement, e.g., the full coverage. The objective of DSC is to maximal the number of disjoint sets. As different disjoint sets form and work successively, only the sensors from the current set are responsible for monitoring the area, while nodes from other sets are sleeping to save energy. Therefore the DSC is a fundamental problem in the WSN and is significant for the network lifetime. In the literature, BPSO has been successfully applied to solve the optimal coverage problem (OCP) which is to find a subset of sensors with the minimal number of sensors to fully monitor the area. In this paper, we extend the BPSO approach to solve the DSC problem by solving the OCP again and again to find the disjoint subsets as many as possible. Once finding the minimal number of sensors for the OCP to fully monitor the area, we mark these sensors as unavailable and repeatedly find another subset of sensors in the remained WSN for the OCP. This way, BPSO can find disjoint subsets of the WSN as many as possible, which is the solution to the DSC problem. Simulations have been conducted to evaluate the performance of the proposed BPSO approach. The experimental results show that BPSO has very good performance in maximizing the disjoint sets number when compared with the traditional heuristic and the genetic algorithm approaches.","PeriodicalId":385063,"journal":{"name":"2012 Conference on Technologies and Applications of Artificial Intelligence","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122526401","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: 12

A High Coherent Association Rule Mining Algorithm 一种高相干关联规则挖掘算法

2012 Conference on Technologies and Applications of Artificial Intelligence Pub Date : 2012-11-16 DOI: 10.1109/TAAI.2012.51

Chun-Hao Chen, Guo-Cheng Lan, T. Hong, Yui-Kai Lin

引用次数: 3

An Efficient Subset-Lattice Algorithm for Mining Closed Frequent Itemsets in Data Streams 数据流中封闭频繁项集挖掘的高效子集-格算法

2012 Conference on Technologies and Applications of Artificial Intelligence Pub Date : 2012-11-16 DOI: 10.1109/TAAI.2012.12

Ye-In Chang, Chia-En Li, Wei-Hau Peng

{"title":"An Efficient Subset-Lattice Algorithm for Mining Closed Frequent Itemsets in Data Streams","authors":"Ye-In Chang, Chia-En Li, Wei-Hau Peng","doi":"10.1109/TAAI.2012.12","DOIUrl":"https://doi.org/10.1109/TAAI.2012.12","url":null,"abstract":"There are many applications of using association rules in data streams, such as market analysis, network security, sensor networks and web tracking. Mining closed frequent item sets is a further work of mining association rules, which aims to find the subsets of frequent item sets that could extract all frequent item sets. Formally, a closed frequent item set is a frequent item set which has no superset with the same support as it. One of well-known algorithms for mining closed frequent item sets based on the sliding window model is the New Moment algorithm. However, the New Moment algorithm could not efficiently mine closed frequent item sets in data streams, since they will generate closed frequent item sets and many unclosed frequent item sets. Moreover, when data in the sliding window is incrementally updated, the New Moment algorithm needs to reconstruct the whole tree structure. Therefore, we propose the Subset-Lattice algorithm which embeds the property of subsets into the lattice structure to efficiently mine closed frequent item sets over a data stream sliding window. Moreover, when data in the sliding window is incrementally updated, our Subset-Lattice algorithm will not reconstruct the whole lattice structure.","PeriodicalId":385063,"journal":{"name":"2012 Conference on Technologies and Applications of Artificial Intelligence","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128492187","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

Relationship between Emotional Words and Emoticons in Tweets 推文中情绪词与表情符号的关系

2012 Conference on Technologies and Applications of Artificial Intelligence Pub Date : 2012-11-16 DOI: 10.1109/TAAI.2012.30

Kaito Soranaka, Mitsunori Matsushita

引用次数: 14

Pattern Formation Based on Potential Field in Real-Time Strategy Games 基于势场的实时策略游戏模式形成

2012 Conference on Technologies and Applications of Artificial Intelligence Pub Date : 2012-11-16 DOI: 10.1109/TAAI.2012.40

Cheng-Yu Chen, Xin-Lan Liao, Chien-Chih Liao, Chuan-Kang Ting

引用次数: 1

Air Hockey iOS Game That Uses Fuzzy-Logic for Game-Balancing 《空中曲棍球》iOS游戏运用模糊逻辑实现游戏平衡

2012 Conference on Technologies and Applications of Artificial Intelligence Pub Date : 2012-11-16 DOI: 10.1109/TAAI.2012.17

C. Delgado-Mata, J. Ibáñez

引用次数: 3

Knowledge Source Selection by Estimating Distance between Datasets 估计数据集之间距离的知识来源选择

2012 Conference on Technologies and Applications of Artificial Intelligence Pub Date : 2012-11-16 DOI: 10.1109/TAAI.2012.37

Yi-Ting Chiang, Wen-Chieh Fang, Jane Yung-jen Hsu

引用次数: 3

Multi-objective Display Panel Design Optimization Using Circuit Simulation-Based Evolutionary Algorithm 基于电路仿真的进化算法的多目标显示面板设计优化

2012 Conference on Technologies and Applications of Artificial Intelligence Pub Date : 2012-11-16 DOI: 10.1109/TAAI.2012.48

Yu-Yu Chen, Yiming Li, Chieh-Yang Chen, Chien-Hsueh Chiang

引用次数: 0

A New Effective Learning Rule of Fuzzy ART 一种新的模糊艺术有效学习规则

2012 Conference on Technologies and Applications of Artificial Intelligence Pub Date : 2012-11-16 DOI: 10.1109/TAAI.2012.60

Nong Thi Hoa, T. D. Bui

引用次数: 3