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In this paper, we document the face detection competition that we have organized in conjunction with the ISDA 2010 conference. The objective was to compare different face detection engines performance on new unpublished datasets. We believe researchers can benefit from this competition by identifying strong and weak areas in their algorithms relative to others. We have also identified, based on the...
Distribution fitting is a widely recurring problem in different fields such as telecommunication, finance and economics, sociology, physics, etc. Standard methods often require solving difficult equations systems or investments in specialized software. The paper presents a new approach to distribution fitting that exploits Genetic Algorithms in order to simultaneously identify the distribution type...
A genetic algorithm is combined with two variants of the modularity (Q) network analysis metric to examine a substantial amount fisheries catch data. The data set produces one of the largest networks evaluated to date by genetic algorithms applied to network community analysis. Rather than using GA to decide community structure that simply maximizes modularity of a network, as is typical, we use two...
This paper reports the investigations and experimental procedures conducted for designing an automatic sleep classification tool basedconly in the features extracted with wavelets from EEG, EMG and EOG (electro encephalo-mio- and oculo-gram) signals, without any visual aid or context-based evaluation. Real data collected from infants was processed and classified by several traditional and bio-inspired...
This work presents the design and development of a web-based system that supports cross-language similarity analysis and plagiarism detection. A suspicious document dq in a language Lq is to be submitted to the system via a PHP web-based interface. The system will accept the text through either uploading or pasting it directly to a text-area. In order to lighten large texts and provide an ideal set...
Cervix cancer is the most common gynecological malignancy and second most common cancer among female in Malaysia after breast cancer. The objective of this study is to extract the size of nucleus and cytoplasm, as well as gray level values of cervical cells from ThinPrep images so that accurate value of those parameters can easily be obtained. An alternative approach of extracting features for Pap...
Defining a boundary between inliers and outliers is a major challenge in unsupervised outlier detection. In the absence of labeled data, the true outliers set cannot be evaluated. This lays the burden on both the choice of an efficient outlier detection criterion, and parameter selection. While numerous unsupervised outlier detection criteria, with different parameters, have been proposed, an unsupervised...
Modern business goals are often fulfilled with workflows that may cross many organisations and utilise services on a variety of devices and/or supported by different platforms. Current workflows are inherently context-aware. Each context is governed and constrained by its own policies and rules to prevent unauthorised participants from executing sensitive tasks and also to prevent tasks from accessing...
In this paper character recognition in Saudi Automobile License Plates is described. Due to special properties of Saudi license plates, simpler procedures as compared to the ones used for Lebanese plates have been developed. A limited character set for recognition enables the development of smaller recognition trees. The process relies on processing pixels along vertical and horizontal lines taken...
We present a new framework and method for solving Multiple Instance Learning (MIL) problems. As a variation on supervised learning, MIL addresses the problem of classifying a bag of instances. If at least one of the instances in a bag is positive the bag is labeled positive, otherwise it is negative. We use a divide and conquer strategy to identify true positive group of instances in the positive...
There are numerous problems of increasing significance where a pattern can have several classes simultaneously associated. This kind of problems, usually called multi-label problems, should be tackled with specific techniques in order to generate models more accurate than those obtained with classical classification algorithms. This work presents the adaptation of the J48 algorithm to multi-label...
The selection of a particular neural network model belonging to the Pareto front is a problem that exists in all multi-objective algorithms. This paper proposes a novel solution to this problem based on a linear combination of the outputs of the two extremes in the Pareto front, which form an ensemble. The decision support TOPSIS method is used to determine which linear combination creates the best...
Association rule mining makes interesting associations and/or correlations among large sets of data. Those associations can be refined as decision rules to be used and stored in a knowledge base system. In this paper, an approach based on association rule and knowledge base is proposed and implemented in the fault diagnosis of a transformer system. According to the features of association rule, the...
Translation memories play a vital role in Computer-Aided Translation (CAT). Approaches to align sentences from parallel corpora are generally used to construct translation memories. In this paper, we present, on the one hand, a hybrid approach to align sentences combining different information sources (bilingual lexicon, sentence length and sentence position, semantic similarity), and on the other...
The main purpose of this paper is to present a new approach for High-Stake Decision Support Systems. We introduce the challenge of the exploitation of heterogeneous community-based knowledge for decision-aid in critical situations. Knowledge shared in e-communities can be very rich, but is also inherently chaotic and questionable. Such uncontrolled knowledge is not usually considered in High-Stake...
In this work we suggest a model according to which semantics has been already generated during the perception through the interaction of three dynamic levels of perceptual organization. We consider perceptual grouping as the first order processing. Shape formation is considered as the second order processing. Both grouping and shape formation can be considered as two complementary and interrelated...
In this paper, we propose an associative watermarking scheme which is conducted by the concept of Association Mining Rules (AMRs) and the ideas of Vector Quantization (VQ) and Soble operator. Performing associative watermarking rules to the images will reduct the amount of the embedded data, and using VQ indexing scheme can easily recall the embedded watermark for the purpose of image authentication,...
In this paper, we propose a rule-based system for semantically understanding and analyzing the motion of the trajectories of the human activity. The proposed system can be used as a preprocessing phase for enhancing the object detection process. Detected trajectories are classified into three categories; normal, semi-normal and abnormal trajectories according to the distances between their adjacent...
This paper presents the interactive web interface for inquiring about the long-term care insurance system in Japan. In Japan, health care services provided by the long-term care insurance system takes costs depending on the health care level. Although the system has been revised several times, such revision made the system more complex, so that a web-based system by which every people can accurately...
Internet contains a tremendous amount of valuable web applications that can be used in many systems. To use this kind of applications with other systems, the interaction needs to be in a standard structured format such as XML web service. In this paper, we present a method to convert the current web applications into standard XML web services. The system design and implementation are presented. We...
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