Detection and recognition of the moving objects in dynamic environment is difficult task. This paper presents a modified framework for the detection and recognition of moving people in videos. Detection part of the pr...
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Detection and recognition of the moving objects in dynamic environment is difficult task. This paper presents a modified framework for the detection and recognition of moving people in videos. Detection part of the proposed method consists of average background model with supportive secondary model and an adaptive threshold selection model based on Gaussian distribution. The background model used for background modelling and adaptive threshold method is used to simultaneously update the system according to environment. Then feature extraction is performed by an established human model. This human model consists of five parts with robust features to facilitate recognition process. For recognition purpose, back propagation neural network has been used as a classifier. Experimental results show the effectiveness of proposed system.
This paper is a review on knowledge discovery in the field of web mining for the benefit of research on the personalization of web-based information services. The essence of personalization is the adaptability of info...
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This paper is a review on knowledge discovery in the field of web mining for the benefit of research on the personalization of web-based information services. The essence of personalization is the adaptability of information systems to the needs of their users. This issue is becoming increasingly important on the Web, as non-expert users are overcame by the quantity of information available online. This article investigates the application of artificial immune systems (AIS) to knowledge discovery as a web personalization tool. AIS are thought to confer the adaptability and learning required for this task.
This paper presents a method for performing a robust association between the apneas and hypopneas recorded on a polysomnogram and the desaturations they cause. It is based on a structural algorithm that takes advantag...
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ISBN:
(纸本)9783642024801
This paper presents a method for performing a robust association between the apneas and hypopneas recorded on a polysomnogram and the desaturations they cause. It is based on a structural algorithm that takes advantage of the fuzzy set theory to represent the medical knowledge on which it relies. The method aims to generate information that could serve as a starting point for gaining a deeper insight into the Sleep Apnea-Hypopnea Syndrome by means of data mining techniques. This has led to a sacrifice of sensitivity for specificity. We have validated our proposal over 37 hours of polysomnographic recordings. 88% of the hypoventilations present in the recordings were associated with the desaturations they caused, presenting a rate of false associations of 0.86%.
Combinatorial optimization problems form a class of appealing theoretical and practical problems attractive for their complexity and known hardness. They are often NP-hard and as such not solvable by exact methods. Co...
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Combinatorial optimization problems form a class of appealing theoretical and practical problems attractive for their complexity and known hardness. They are often NP-hard and as such not solvable by exact methods. Combinatorial optimization problems are subject to numerous heuristic and metaheuristic algorithms, including genetic algorithms. In this paper, we present two new permutation encodings for genetic algorithms and experimentally evaluate the influence of the encodings on the performance and result of genetic algorithm on two synthetic and real-world optimization problems.
Set Covering Problem and Set Partitioning Problem are models for many important industrial applications. In this paper, we solve some Operational Research benchmarks with Ant Colony Optimization using a new transition...
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Set Covering Problem and Set Partitioning Problem are models for many important industrial applications. In this paper, we solve some Operational Research benchmarks with Ant Colony Optimization using a new transition rule. A Lookahead mechanism was incorporated to check constraint consistency in each iteration. Computational results are presented showing the advantages to use this additional mechanism to Ant Colony Optimization.
Given an image, there is no unique measure to quantitatively judge the quality of an image enhancement operator. It is also not clear which measure is to be used for the given image. The present work expresses the pro...
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ISBN:
(纸本)9783642111631
Given an image, there is no unique measure to quantitatively judge the quality of an image enhancement operator. It is also not clear which measure is to be used for the given image. The present work expresses the problem as a multi-objective optimization problem and a methodology has been proposed based on multi-objective genetic algorithm (MOGA). The methodology exploits the effectiveness of MOGA for searching global optimal solutions in selecting an appropriate image enhancement operator.
In the past, the up-to-date patterns is proposed to mine the frequent itemsets within its corresponding lifetime. This hybrid method is based on the Apriori-like approach, which requests high computational cost and me...
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In the past, the up-to-date patterns is proposed to mine the frequent itemsets within its corresponding lifetime. This hybrid method is based on the Apriori-like approach, which requests high computational cost and memory requirement. In this paper, the up-to-date pattern tree (UDP tree) is proposed to keep the up-to-date patterns in a tree structure. The experimental results show that the proposed approach has a better performance than the level-wise up-to-date algorithm.
This paper proposes a novel algorithm for complete exact pattern-matching focusing the specificities of protein sequences (alphabet of 20 symbols) but, also highly efficient considering larger alphabets. The searching...
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ISBN:
(纸本)9783642024801
This paper proposes a novel algorithm for complete exact pattern-matching focusing the specificities of protein sequences (alphabet of 20 symbols) but, also highly efficient considering larger alphabets. The searching strategy uses large search windows allowing multiple alignments per iteration. A new filtering heuristic, named compatibility rule, contributed decisively to the efficiency improvement. The new algorithm's performance is, on average, superior in comparison with its best-rated competitors.
The paper applies image segmentation and recognition theory, one novel method is proposed for the bill searches in bank system. In general, bank bill of Chinese is color image for encrpytion techniques, and right-up a...
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This paper presents a new approach for recognizing nonstationary signals in power quality (PQ) disturbances. Meanwhile the new approach includes the most types of PQ disturbance, such as voltage sags, swells, interrup...
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ISBN:
(纸本)9781424447541
This paper presents a new approach for recognizing nonstationary signals in power quality (PQ) disturbances. Meanwhile the new approach includes the most types of PQ disturbance, such as voltage sags, swells, interruptions, transients and harmonics. The new model mainly includes two steps. Firstly, S-transform is used to analyze power system disturbance signals, and two most distinguishing features are extracted. In this process based on these two features, 2D feature vectors are clustered using hierarchical Fuzzy C-means algorithm (FCM). Secondly, a binary decision tree is constructed from FCM cluster centers to automatic recognize disturbance patterns. Finally the simulation results show the validity and efficiency of the proposed model.
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