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2010 10th International Conference on Hybrid Intelligent Systems最新文献

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GPUMLib: A new Library to combine Machine Learning algorithms with Graphics Processing Units GPUMLib:一个将机器学习算法与图形处理单元相结合的新库
2010 10th International Conference on Hybrid Intelligent Systems Pub Date : 2010-10-18 DOI: 10.1109/HIS.2010.5600028
Noel Lopes, B. Ribeiro, Ricardo Quintas
{"title":"GPUMLib: A new Library to combine Machine Learning algorithms with Graphics Processing Units","authors":"Noel Lopes, B. Ribeiro, Ricardo Quintas","doi":"10.1109/HIS.2010.5600028","DOIUrl":"https://doi.org/10.1109/HIS.2010.5600028","url":null,"abstract":"The Graphics Processing Unit (GPU) is a highly parallel, many-core device with enormous computational power, especially well-suited to address Machine Learning (ML) problems that can be expressed as data-parallel computations. As problems become increasingly demanding, parallel implementations of ML algorithms become critical for developing hybrid intelligent real-world applications. The relative low cost of GPUs combined with the unprecedent computational power they offer, make them particularly well-positioned to automatically analyze and capture relevant information from large amounts of data. In this paper, we propose the creation of an open source GPU Machine Learning Library (GPUMLib) that aims to provide the building blocks for the scientific community to develop GPU ML algorithms. Experimental results on benchmark datasets demonstrate that the GPUMLib components already implemented achieve significant savings over the counterpart CPU implementations.","PeriodicalId":174618,"journal":{"name":"2010 10th International Conference on Hybrid Intelligent Systems","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129463586","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: 26
Improving black box testing by using neuro-fuzzy classifiers and multi-agent systems 利用神经模糊分类器和多智能体系统改进黑盒测试
2010 10th International Conference on Hybrid Intelligent Systems Pub Date : 2010-10-18 DOI: 10.1109/HIS.2010.5600020
Marcos Álvares Barbosa Junior, Fernando Buarque de Lima-Neto, Júlio C. S. Fort
{"title":"Improving black box testing by using neuro-fuzzy classifiers and multi-agent systems","authors":"Marcos Álvares Barbosa Junior, Fernando Buarque de Lima-Neto, Júlio C. S. Fort","doi":"10.1109/HIS.2010.5600020","DOIUrl":"https://doi.org/10.1109/HIS.2010.5600020","url":null,"abstract":"Automated software testing has become a fundamental requirement for several software engineering methodologies. Software development companies very often outsource the test of their products. In such cases, the hired companies sometimes have to test softwares without any access to the source code. This type of service is called black box testing, which includes presentation of some ad-hoc input to the software followed by an assessment of the outcome. The common place for black box testing is sequential approach and slow pace of work. This ineffectiveness is due to the combinatorial explosion of software parameters and payloads. This work presents a neuro-fuzzy and multi-agent system architecture for improving black box testing tools for client-side vulnerability discovery, specifically, memory corruption flaws. Experiments show the efficiency of the proposed hybrid intelligent approach over traditional black box testing techniques.","PeriodicalId":174618,"journal":{"name":"2010 10th International Conference on Hybrid Intelligent Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128553414","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: 5
Local and global Gaussian mixture models for hematoxylin and eosin stained histology image segmentation 苏木精和伊红染色组织图像分割的局部和全局高斯混合模型
2010 10th International Conference on Hybrid Intelligent Systems Pub Date : 2010-10-18 DOI: 10.1109/HIS.2010.5600019
Lei He, L. Long, Sameer Kiran Antani, G. Thoma
{"title":"Local and global Gaussian mixture models for hematoxylin and eosin stained histology image segmentation","authors":"Lei He, L. Long, Sameer Kiran Antani, G. Thoma","doi":"10.1109/HIS.2010.5600019","DOIUrl":"https://doi.org/10.1109/HIS.2010.5600019","url":null,"abstract":"This paper presents a new algorithm for hematoxylin and eosin (H&E) stained histology image segmentation. With both local and global clustering, Gaussian mixture models (GMMs) are applied sequentially to extract tissue constituents such as nuclei, stroma, and connecting contents from background. Specifically, local GMM is firstly applied to detect nuclei by scanning the input image, which is followed by global GMM to separate other tissue constituents from background. Regular RGB (red, green and blue) color space is employed individually for the local and global GMMs to make use of the H&E staining features. Experiments on a set of cervix histology images show the improved performance of the proposed algorithm when compared with traditional K-means clustering and state-of-art multiphase level set methods.","PeriodicalId":174618,"journal":{"name":"2010 10th International Conference on Hybrid Intelligent Systems","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125078819","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: 16
Mixing theory of retroviruses and Genetic Algorithm to build a new nature-inspired meta-heuristic for real-parameter function optimization problems 将逆转录病毒理论与遗传算法相结合，构建一种新的自然启发型元启发式算法求解实参数函数优化问题
2010 10th International Conference on Hybrid Intelligent Systems Pub Date : 2010-10-18 DOI: 10.17562/pb-42-7
R. S. Moreira, O. N. Teixeira, R. C. L. Oliveira
{"title":"Mixing theory of retroviruses and Genetic Algorithm to build a new nature-inspired meta-heuristic for real-parameter function optimization problems","authors":"R. S. Moreira, O. N. Teixeira, R. C. L. Oliveira","doi":"10.17562/pb-42-7","DOIUrl":"https://doi.org/10.17562/pb-42-7","url":null,"abstract":"This paper describes the development of a new hybrid meta-heuristic of optimization based on a viral lifecycle, specifically the retroviruses (the nature's swiftest evolvers'), called Retroviral Iterative Genetic Algorithm (RIGA). This algorithm uses Genetics Algorithms (GA) structures with features of retroviral replication, providing a great genetic diversity, confirmed by better results achieved by RIGA comparing with GA applied to some Real-Valued Benchmarking Functions.","PeriodicalId":174618,"journal":{"name":"2010 10th International Conference on Hybrid Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131069306","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
FCCTF: Fairness Congestion Control for a disTrustful wireless sensor network using Fuzzy logic 基于模糊逻辑的不信任无线传感器网络公平性拥塞控制
2010 10th International Conference on Hybrid Intelligent Systems Pub Date : 2010-10-18 DOI: 10.1109/HIS.2010.5601071
Mani Zarei, A. Rahmani, Razieh Farazkish, S. Zahirnia
{"title":"FCCTF: Fairness Congestion Control for a disTrustful wireless sensor network using Fuzzy logic","authors":"Mani Zarei, A. Rahmani, Razieh Farazkish, S. Zahirnia","doi":"10.1109/HIS.2010.5601071","DOIUrl":"https://doi.org/10.1109/HIS.2010.5601071","url":null,"abstract":"One of the most important challenges in a densely wireless sensor network (WSN) with potential congestions and packet loss is dissemination of distrusted packets. In this paper we present FCCTF: Fairness Congestion Control for a disTrustful WSN using Fuzzy logic. FCCTF increases each node capability for detecting and isolating malicious nodes in order to improve packet delivery while some important packets endanger dropping due to overflowing. Indeed, FCCTF attempts to improve our previous scheme Fuzzy based trust estimation for Congestion Control in WSNs (FCC) [1]. Simulation results show that FCCTF improves packet delivery up to 18.5% more and it reduces the related packet drop of legitimate nodes 20% less than FCC.","PeriodicalId":174618,"journal":{"name":"2010 10th International Conference on Hybrid Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130286589","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: 26
A hybrid approach for IEEE 802.11 intrusion detection based on AIS, MAS and naïve Bayes 基于AIS、MAS和naïve贝叶斯的IEEE 802.11入侵检测混合方法
2010 10th International Conference on Hybrid Intelligent Systems Pub Date : 2010-10-18 DOI: 10.1109/HIS.2010.5600083
Moisés Danziger, Fernando Buarque de Lima-Neto
{"title":"A hybrid approach for IEEE 802.11 intrusion detection based on AIS, MAS and naïve Bayes","authors":"Moisés Danziger, Fernando Buarque de Lima-Neto","doi":"10.1109/HIS.2010.5600083","DOIUrl":"https://doi.org/10.1109/HIS.2010.5600083","url":null,"abstract":"Many problems with wireless networks are directly related to the very means used to transport data, in this case, radio waves. In addition to mis-configured equipment lack of adaptable algorithms and wireless networks are major targets for attacks. New tools to refrain that are greatly in need. Due to the fact that it is easy to attack and not so to defend wireless networks, good candidate tools would be the ones that could profit from intelligent techniques. In this paper, we use the Danger Theory (DT) and a Bayesian classifier (using naïve Bayes) embedded in a military style multi-agent system (MAS) to create a lightweight, adaptable and dynamic detection system for wireless networks (WIDS). Experimental results show that the artificial immune aspect of the proposed system is capable of detecting unknown intrusion and to identify them automatically with considerable few false alarms and low cost for the network traffic.","PeriodicalId":174618,"journal":{"name":"2010 10th International Conference on Hybrid Intelligent Systems","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115855609","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: 9
A new third order particle swarm optimization and applications to test various functions 一种新的三阶粒子群优化方法及其在各种函数测试中的应用
2010 10th International Conference on Hybrid Intelligent Systems Pub Date : 2010-10-18 DOI: 10.1109/HIS.2010.5600024
H. Kang, Min Woo Kwon, H. Bae
{"title":"A new third order particle swarm optimization and applications to test various functions","authors":"H. Kang, Min Woo Kwon, H. Bae","doi":"10.1109/HIS.2010.5600024","DOIUrl":"https://doi.org/10.1109/HIS.2010.5600024","url":null,"abstract":"The particle swarm optimization is one of well known algorithms in the world with its performance and easy implementation. This algorithm is used for finding optimal values or regions of multi-dimensional spaces throughout the interaction of each particle positions and its values. Originally, the PSO has two factors such as position and velocity vectors which are sources for next positions of particles, respectively. However, in order to reach optimal regions quickly, accurately and even closely, we present a new third order particle swarm optimization which has three vectors: i.e. a position vector, a velocity vector and an acceleration vector. From the proposed PSO, we obtain a third order difference equation and we will derive the convergence region for four parameters from the equation. By setting four appropriate parameters near the convergence region with the proposed PSO algorithm, we test 2 benchmark functions with it and make comparison between the new third order PSO and the variant of the original PSO. Results from simulations clearly show that the proposed algorithm has better performance and faster convergence speed rather than the original PSO.","PeriodicalId":174618,"journal":{"name":"2010 10th International Conference on Hybrid Intelligent Systems","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116013857","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
Modular robot with adaptive connection topology 具有自适应连接拓扑的模块化机器人
2010 10th International Conference on Hybrid Intelligent Systems Pub Date : 2010-10-18 DOI: 10.1109/HIS.2010.5600785
P. Hartono, A. Nakane
{"title":"Modular robot with adaptive connection topology","authors":"P. Hartono, A. Nakane","doi":"10.1109/HIS.2010.5600785","DOIUrl":"https://doi.org/10.1109/HIS.2010.5600785","url":null,"abstract":"In this study, we physically built hardware modules which enable us to freely construct robots with various morphologies. As opposed to the existing studies of modular robotics where the connection topology among the modules has to be hand-designed, our modules are able to adaptively modify their connection topology which enables them to generate an overall behavior as one robot. We ran several physical experiments where robots with various morphologies are assembled from the proposed modules to acquire several target behaviors.","PeriodicalId":174618,"journal":{"name":"2010 10th International Conference on Hybrid Intelligent Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133831830","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
Feature selection algorithm for classification of multispectral MR images using constrained energy minimization 基于约束能量最小化的多光谱磁共振图像分类特征选择算法
2010 10th International Conference on Hybrid Intelligent Systems Pub Date : 2010-10-18 DOI: 10.1109/HIS.2010.5604768
G. Lin, Wen-June Wang, Chuin-Mu Wang
{"title":"Feature selection algorithm for classification of multispectral MR images using constrained energy minimization","authors":"G. Lin, Wen-June Wang, Chuin-Mu Wang","doi":"10.1109/HIS.2010.5604768","DOIUrl":"https://doi.org/10.1109/HIS.2010.5604768","url":null,"abstract":"This study proposes a new unsupervised approach for targets detection and classification in multispectral Magnetic Resonance (MR) images. The proposed method comprises two processes, namely Target Generation Process (TGP) and Constrained Energy Minimization (CEM). TGP is a fuzzy-set process that generates a set of potential targets from unknown information, and applies these targets to be desired targets in CEM Finally, the real MR images are used in the experiments to evaluate the effectiveness of proposed method. Experiment results reveal that the proposed method segments a multispectral MR image much more effectively than either FMRIB's Automated Segmentation Tool (FAST) or Fuzzy C-means (FC).","PeriodicalId":174618,"journal":{"name":"2010 10th International Conference on Hybrid Intelligent Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133511916","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
Embedding a Neural Network into WSN furniture 将神经网络嵌入WSN家具
2010 10th International Conference on Hybrid Intelligent Systems Pub Date : 2010-10-18 DOI: 10.1109/HIS.2010.5600016
S. Soares, A. Rocha, T. M. D. A. Barbosa, R. Araújo
{"title":"Embedding a Neural Network into WSN furniture","authors":"S. Soares, A. Rocha, T. M. D. A. Barbosa, R. Araújo","doi":"10.1109/HIS.2010.5600016","DOIUrl":"https://doi.org/10.1109/HIS.2010.5600016","url":null,"abstract":"Wireless Sensor Networks (WSN) is an emerging technology that is developed with a large number of useful applications. On the other hand, Artificial Neural Networks (ANN) have found many successful applications in nonlinear system and control, digital communication, pattern recognition, pattern classification, etc. There are many similarities between WSN and ANN. For example, the sensor node itself can be seen as a neuron since the WSN application show characteristics such as distributed processing, massive parallelism, adaptively, inherent contextual information processing, fault tolerance and low computation. This paper examines the possibility of embedding ANN and WSN into a Smart Table. Prototypal results have shown that ANN models are good candidates for using it deployed into low cost System-on-a-Chip (SoC).","PeriodicalId":174618,"journal":{"name":"2010 10th International Conference on Hybrid Intelligent Systems","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132854881","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: 5
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