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17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)最新文献

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Automatic extraction of ground-glass opacity shadows on CT images of the thorax by correlation between successive slices 基于连续切片间相关性的胸部CT图像毛玻璃阴影自动提取方法
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.43
Hyoungseop Kim, Masaki Maekado, J. Tan, S. Ishikawa, Masaaki Tsukuda
{"title":"Automatic extraction of ground-glass opacity shadows on CT images of the thorax by correlation between successive slices","authors":"Hyoungseop Kim, Masaki Maekado, J. Tan, S. Ishikawa, Masaaki Tsukuda","doi":"10.1109/ICTAI.2005.43","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.43","url":null,"abstract":"In general, segmentation is difficult because surrounding soft tissues and organs have similar CT values and sometimes contact with each other. We propose a new technique for automatic segmentation of lung regions and its classification for ground-glass opacity from the segmented lung regions by computer based on a set of the thorax CT images. In this paper, we segment the lung region for extraction of the region of interest employing binarization and labeling process from the inputted each slices images. The region having the largest area is regarded as the tentative lung regions. Furthermore, the ground-glass opacity is classified by correlation distribution on the slice to slice from the extracted lung region with respect to the thorax CT images. Experiment is performed employing twenty six thorax CT image sets and 96% of recognition rates were achieved. Obtained results are shown along with a discussion","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127847509","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
A two-level gradient based approach for intelligent coordination of large-scale systems. Part I 基于两级梯度的大系统智能协调方法。第一部分
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.20
N. Sadati
{"title":"A two-level gradient based approach for intelligent coordination of large-scale systems. Part I","authors":"N. Sadati","doi":"10.1109/ICTAI.2005.20","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.20","url":null,"abstract":"In this paper, the concept of coordination is introduced within the framework of two-level large-scale systems and a new approach based on interaction prediction principle is presented. The proposed approach is formulated in an intelligent manner in such a way that it provides a new strategy that can be used to synthesize an on-line supervisory controller for the overall two-level large-scale systems, extendable to multi-level control systems. By using the new methodology, which is based on using neural network for modeling each sub-system, typical gradient method for optimization of first-level sub-problems, and the gradient of the interaction prediction errors related to the predicted interactions, at the second level, the coordination of the overall large-scale system is done. Simulation results demonstrate the effectiveness of the proposed strategy in compare to the classical methods","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134012534","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: 4
An adaptive de-blocking algorithm based on MRF 一种基于MRF的自适应去块算法
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.31
S. Xie, Zhiliang Xu
{"title":"An adaptive de-blocking algorithm based on MRF","authors":"S. Xie, Zhiliang Xu","doi":"10.1109/ICTAI.2005.31","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.31","url":null,"abstract":"One of the major drawbacks in block-based discrete cosine transform (BDCT) is the blocking artifacts at low bit rates. In this paper, an adaptive deblocking algorithm based on Markov random field (MRF) is proposed. A visibility function of blocking artifacts is introduced which based on human visual system (HVS), together with edge information to construct a new adaptive potential function of MRF. The experiment results show that the proposed algorithm reduces the blocking artifacts effectively and preserves the original edges faithful","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124702844","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
Robust airport gate assignment 稳健的机场登机口分配
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.110
A. Lim, Fan Wang
{"title":"Robust airport gate assignment","authors":"A. Lim, Fan Wang","doi":"10.1109/ICTAI.2005.110","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.110","url":null,"abstract":"In this paper, we propose a new strategy for the robust constraint resource assignment problem and apply it to solve the robust airport gate assignment (RAGA). RAGA attempts to accurately build an evaluation criteria for the ability of an aircraft-to-gate assignment to handle uncertainty on aircraft schedule; and to accurately and effectively search the most robust airport gate assignment. We model the RAGA by a stochastic programming model and transform it into a binary programming model by introducing the unsupervised estimation functions without knowing any information on the real-time arrival and departure time of aircrafts in advance. Moreover, a partition-based search space encoding, two neighborhood operators for single or multiple aircrafts reassignment, and a hybrid meta-heuristic combining a tabu search and a local search are proposed to solve RAGA efficiently. Experimental results on the real-life test data from Hong Kong International Airport demonstrate that the proposed RAGA model provides a valuable tool for the airport to improve its robustness in uncertain operations","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124565173","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: 60
Guided complete search for nurse rostering problems 指导护士名册问题的完整搜索
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.70
Spencer K. L. Fung, Ho-fung Leung, Jimmy Ho-man Lee
{"title":"Guided complete search for nurse rostering problems","authors":"Spencer K. L. Fung, Ho-fung Leung, Jimmy Ho-man Lee","doi":"10.1109/ICTAI.2005.70","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.70","url":null,"abstract":"Nurse rostering problem is one of the most difficult scheduling problems in artificial intelligence and operation research. In general, it consists of cardinality constraints and special pattern constraints that correspond to the given workforce demands, which form a complex problem structure. Many heuristics algorithms have been proposed to solve this particular problem. In this paper, we demonstrate the efficiency of our newly defined GCS/simplex solver, which incorporates simplex method into the GCS framework, on some difficult nurse rostering problem instances. Experimental results show that the GCS/Simplex solver is efficient in solving this kind of scheduling problems in terms of both computation time and number of fails","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130846590","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: 8
Application of neural networks to decentralized control of robot manipulators with high degree of freedom 神经网络在高自由度机器人分散控制中的应用
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.39
N. Sadati, E. Elhamifar
{"title":"Application of neural networks to decentralized control of robot manipulators with high degree of freedom","authors":"N. Sadati, E. Elhamifar","doi":"10.1109/ICTAI.2005.39","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.39","url":null,"abstract":"In this paper, a neural network decentralized control for trajectory tracking of robot manipulators is developed. The proposed decentralized control allows the overall closed-loop system to be stabilized while making the tracking error to be uniformly ultimately bounded (UUB), without having any prior knowledge of the robot manipulator dynamics. The interconnections in the dynamic equations of each subsystem are considered with unknown nonlinear bounds. The RBF neural networks (RBFNNs) are proposed to model the unknown nonlinear dynamics of the robots and the interconnection terms. Using Lyapunov method, the stability of the overall system is investigated","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130887597","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
Dot plots for time series analysis 点图时间序列分析
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.60
Dragomir Yankov, Eamonn J. Keogh, S. Lonardi, A. Fu
{"title":"Dot plots for time series analysis","authors":"Dragomir Yankov, Eamonn J. Keogh, S. Lonardi, A. Fu","doi":"10.1109/ICTAI.2005.60","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.60","url":null,"abstract":"Since their introduction in the seventies by Gibbs and McIntyre, dot plots have proved to be a powerful and intuitive technique for visual sequence analysis and mining. Their main domain of application is the field of bioinformatics where they are frequently used by researchers in order to elucidate genomic sequence similarities and alignment. However, this useful technique has remained comparatively constrained to domains where the data has an inherent discrete structure (i.e., text). In this paper we demonstrate how dot plots can be used for the analysis and mining of real-valued time series. We design a tool that creates highly descriptive dot plots which allow one to easily detect similarities, anomalies, reverse similarities, and periodicities well as changes in the frequencies of repetitions. As the underlying algorithm scales we with the input size, we also show the feasibility of the plots for on-line data monitoring","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129040210","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: 29
Satisfiability-based algorithms for pseudo-Boolean optimization using Gomory cuts and search restarts 基于可满足性的伪布尔优化算法，使用Gomory切割和搜索重启
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.113
Vasco M. Manquinho, Joao Marques-Silva
{"title":"Satisfiability-based algorithms for pseudo-Boolean optimization using Gomory cuts and search restarts","authors":"Vasco M. Manquinho, Joao Marques-Silva","doi":"10.1109/ICTAI.2005.113","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.113","url":null,"abstract":"Cutting planes are a well-known, widely used, and very effective technique for integer linear programming (ILP). In contrast, the utilization of cutting planes in pseudo-Boolean Optimization (PBO) is recent and results still preliminary. This paper addresses the utilization of cutting planes, namely Gomory mixed-integer cuts, in satisfiability-based algorithms for PBO, and shows how these cuts can be used for computing lower bounds and for learning new constraints. A side result of learning new constraints is that the utilization of cutting planes enables non-chronological backtracking. Besides cutting planes, the paper also proposes the utilization of search restarts in PBO. We show that search restarts can be effective in practice, allowing the computation of more aggressive lower bounds each time the search restarts. Experimental results show that the integration of cutting planes and search restarts in a SAT-based algorithm for PBO yields a very efficient and robust new solution for PBO","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129030613","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: 4
Convergence of estimation of distribution algorithms in optimization of additively noisy fitness functions 分布估计算法在加性噪声适应度函数优化中的收敛性
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.52
Yi-kai Hong, Qingsheng Ren, Jin Zeng, Yuchou Chang
{"title":"Convergence of estimation of distribution algorithms in optimization of additively noisy fitness functions","authors":"Yi-kai Hong, Qingsheng Ren, Jin Zeng, Yuchou Chang","doi":"10.1109/ICTAI.2005.52","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.52","url":null,"abstract":"Noise is a common phenomenon in many real-world optimizations. It has long been argued that evolutionary algorithm (EA) should be relatively robust against it. As a novel computing model in evolutionary computations, estimation of distribution algorithm (EDA) is also encountered with it. This paper initially presents three dynamic models of EDA under the additively noisy environment with three different selection methods (proportional selection method, truncation selection method and tournament selection method). We verify that when the population size is infinite, EDA can converge to the global optimal point. This concept establishes the theoretic foundation for optimization of noisy fitness functions with EDA","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127991782","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: 4
Latent process model for manifold learning 流形学习的潜在过程模型
17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Pub Date : 2005-11-14 DOI: 10.1109/ICTAI.2005.79
G. Wang, Weifeng Su, Xiangye Xiao, F. Lochovsky
{"title":"Latent process model for manifold learning","authors":"G. Wang, Weifeng Su, Xiangye Xiao, F. Lochovsky","doi":"10.1109/ICTAI.2005.79","DOIUrl":"https://doi.org/10.1109/ICTAI.2005.79","url":null,"abstract":"In this paper, we propose a novel stochastic framework for unsupervised manifold learning. The latent variables are introduced, and the latent processes are assumed to characterize the pairwise relations of points over a high dimensional and a low dimensional space. The elements in the embedding space are obtained by minimizing the divergence between the latent processes over the two spaces. Different priors of the latent variables, such as Gaussian and multinominal, are examined. The Kullback-Leibler divergence and the Bhattachartyya distance are investigated. The latent process model incorporates some existing embedding methods and gives a clear view on the properties of each method. The embedding ability of this latent process model is illustrated on a collection of bitmaps of handwritten digits and on a set of synthetic data","PeriodicalId":294694,"journal":{"name":"17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127566385","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
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