2009 International Conference of Soft Computing and Pattern Recognition最新文献_第7页

Situation-Awareness and Sensor Stream Mining for Sustainable Human Life 可持续人类生活的态势感知和传感器流挖掘

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.121

Z. Rehman, M. Shahbaz, Muhammad Shaheen, A. Guergachi

{"title":"Situation-Awareness and Sensor Stream Mining for Sustainable Human Life","authors":"Z. Rehman, M. Shahbaz, Muhammad Shaheen, A. Guergachi","doi":"10.1109/SoCPaR.2009.121","DOIUrl":"https://doi.org/10.1109/SoCPaR.2009.121","url":null,"abstract":"Criminal activities cause a huge amount of loss both financially and in terms of human lives. Because of these acts, business and social sectors are struggling. This paper illustrates the development of an online sensor stream mining system that is able to analyze the situational behavior of all of the persons in specific areas and in turn propose real-time alert systems to take countermeasures. This system gathers different information from heterogeneous sensors, fuse that information, and generate real-time alerts to minimize the likelihood of disaster. These alerts and alarms assist security personnel in making appropriate decisions in real-time scenarios. The novelty of this approach comprises context-awareness with online diagnoses to take countermeasures in real-time to reduce the loss of lives, and damage to societies and economies. This technique makes the sensor stream mining process more dependable and increases the reliability of the overall system. To fulfill the objectives of this research, we incorporate lightweight online mining algorithms to extract useful but hidden information from the data gathered. Contextual information such as a person’s pattern of movement, current location, personal profile, and area of residence are exploited to detect anomalous behaviors. The major goal of this research is to detect those persons performing malicious activities and in turn minimize society’s exposure to risks and vulnerabilities.","PeriodicalId":284743,"journal":{"name":"2009 International Conference of Soft Computing and Pattern Recognition","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134365324","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

Automatic Multilevel Thresholding Using Binary Particle Swarm Optimization for Image Segmentation 基于二值粒子群优化的自动多级阈值分割

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.25

L. Djerou, N. Khelil, H. Dehimi, M. Batouche

引用次数: 13

Effects of the Use of Multiple Fuzzy Partitions on the Search Ability of Multiobjective Fuzzy Genetics-Based Machine Learning 使用多个模糊分区对多目标模糊遗传机器学习搜索能力的影响

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.74

Y. Nojima, Yusuke Nakashima, H. Ishibuchi

{"title":"Effects of the Use of Multiple Fuzzy Partitions on the Search Ability of Multiobjective Fuzzy Genetics-Based Machine Learning","authors":"Y. Nojima, Yusuke Nakashima, H. Ishibuchi","doi":"10.1109/SoCPaR.2009.74","DOIUrl":"https://doi.org/10.1109/SoCPaR.2009.74","url":null,"abstract":"An important issue in the design of fuzzy rule-based systems is to find a good accuracy-complexity tradeoff. While simple fuzzy systems with high interpretability are usually not accurate, complicated fuzzy systems with high accuracy are usually not interpretable. Recently evolutionary multiobjective optimization (EMO) algorithms have been used to search for simple and accurate fuzzy systems. The main advantage of EMO-based approaches over single-objective techniques is that a number of alternative fuzzy systems with different accuracy-complexity tradeoffs can be obtained by their single run. We have already proposed a multiobjective fuzzy genetics-based machine learning (GBML) algorithm for pattern classification problems. In our GBML algorithm, multiple fuzzy partitions with different granularities are simultaneously used. This is because we usually do not know an appropriate fuzzy partition for each input variable. However, the use of multiple fuzzy partitions significantly increases the size of the search space. In this paper, we examine the effect of the use of multiple fuzzy partitions on the search ability of our multiobjective fuzzy GBML algorithms through computational experiments.","PeriodicalId":284743,"journal":{"name":"2009 International Conference of Soft Computing and Pattern Recognition","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133558514","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

Experimental Study of Different FSAs in Classifying Protein Function 不同FSAs对蛋白质功能分类的实验研究

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.104

S. A. Rahman, Z. Mohamed-Hussein, A. Bakar

引用次数: 5

An Artificial Neural Network Model for Multi Dimension Reduction and Data Structure Exploration 面向多维约简和数据结构探索的人工神经网络模型

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.59

C. S. Teh, Ming Leong Yii, Chwen Jen Chen

引用次数: 2

Efficient Handling of Over/Under-exposure in Stereo Vision 立体视觉中曝光过度/曝光不足的有效处理

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.113

O. Ng, V. Ganapathy

引用次数: 3

Improved Intrusion Detection System Using Fuzzy Logic for Detecting Anamoly and Misuse Type of Attacks 基于模糊逻辑的改进入侵检测系统检测异常和误用类型的攻击

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.51

Bharanidharan Shanmugam, N. Idris

{"title":"Improved Intrusion Detection System Using Fuzzy Logic for Detecting Anamoly and Misuse Type of Attacks","authors":"Bharanidharan Shanmugam, N. Idris","doi":"10.1109/SoCPaR.2009.51","DOIUrl":"https://doi.org/10.1109/SoCPaR.2009.51","url":null,"abstract":"Currently available intrusion detection systems focus mainly on determining uncharacteristic system events in distributed networks using signature based approach. Due to its limitation of finding novel attacks, we propose a hybrid model based on improved fuzzy and data mining techniques, which can detect both misuse and anomaly attacks. The aim of our research is to reduce the amount of data retained for processing i.e., attribute selection process and also to improve the detection rate of the existing IDS using data mining technique. We then use improved Kuok fuzzy data mining algorithm, which in turn a modified version of APRIORI algorithm, for implementing fuzzy rules, which allows us to construct if-then rules that reflect common ways of describing security attacks. We applied fuzzy inference engine using mamdani inference mechanism with three variable inputs for faster decision making. The proposed model has been tested and benchmarked against DARPA 1999 data set for its efficiency and also tested against the “live” networking environment inside the campus and the results has been discussed.","PeriodicalId":284743,"journal":{"name":"2009 International Conference of Soft Computing and Pattern Recognition","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128906978","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: 50

Detection and Recognition of Human in Videos Using Adaptive Method and Neural Net 基于自适应方法和神经网络的视频人物检测与识别

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.119

S. Ali, M. F. Zafar, Moeen Tayyab

引用次数: 4

League Championship Algorithm: A New Algorithm for Numerical Function Optimization 联赛冠军算法:一种新的数值函数优化算法

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.21

A. H. Kashan

引用次数: 229

Modeling Permutations for Genetic Algorithms 遗传算法的排列建模

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SOCPAR.2009.31

P. Krömer, J. Platoš, V. Snás̃el

引用次数: 7