VNU-UET Repository: No conditions. Results ordered -Date Deposited. 2024-03-29T09:46:34ZEPrintshttp://eprints.uet.vnu.edu.vn/images/sitelogo.pnghttps://eprints.uet.vnu.edu.vn/eprints/2016-12-29T08:27:04Z2016-12-29T08:27:04Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/2371This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/23712016-12-29T08:27:04ZACOGNA: An Efficient Method for Protein-Protein Interaction Network AlignmentProtein–protein interaction network alignment enables us to identify orthologous proteins, predict protein functions and build evolutionary relationships of species. This article introduces an algorithm for global alignment of protein- protein interaction network based on ant colony optimization (ACO) method. The experimental results offer outstanding advantages of the proposed algorithms.Ngoc Ha TranXuan-Huan Hoanghuanhx@vnu.edu.vn2016-12-29T08:26:40Z2016-12-29T08:26:40Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/2369This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/23692016-12-29T08:26:40ZAn Improved Artificial Immune Network For Solving Construction Site Layout OptimizationNature-inspired algorithms are often used to find optimal solutions for many combinatorial problems. An immune inspired algorithm, opt-aiNet algorithm, is well known for func- tion optimization. In this paper, we develop a combination of local search with opt-aiNet, called lopt-aiNet, to solve construction site layout (CSL) problem. The effectiveness of the proposed algorithm is investigated through experiments on some datasets taken from the state-of-art and a randomly created dataset. Ex- perimental results show that the lopt-aiNet can produce optimal transportation cost with lower run time compared to the site layouts generated by metaheuristics: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and aiNet.Duc Quang VuVan Truong NguyenXuan-Huan Hoanghuanhx@vnu.edu.vn2015-06-12T16:02:57Z2015-06-12T16:02:57Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/1187This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/11872015-06-12T16:02:57ZMột chỉ số đánh giá số cụm mới cho thuật toán C-means mờTrung Duc NguyenXuan-Huan Hoanghuanhx@vnu.edu.vn2015-06-12T16:00:40Z2015-06-12T16:00:40Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/1188This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/11882015-06-12T16:00:40ZA Novel Ant Based Algorithm for Multiple Graph AlignmentNgoc Ha TranDuc Dong DoXuan-Huan Hoanghuanhx@vnu.edu.vn2015-01-08T07:21:30Z2015-01-08T07:21:31Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/446This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/4462015-01-08T07:21:30ZAn Efficient Ant Colony Algorithm for DNA Motif FindingXuan-Huan Hoanghuanhx@vnu.edu.vnT.A. Tuyet DuongT.T. Ha DoanT. Hung Nguyen2013-08-23T02:25:29Z2013-08-23T02:25:29Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/186This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/1862013-08-23T02:25:29ZACOHAP: An Efficient Ant Colony Optimization for the Haplotype Inference by Pure Parsimony ProblemDong Do Ducdongdd@vnu.edu.vnSy Vinh Levinhls@vnu.edu.vnXuan-Huan Hoanghuanhx@vnu.edu.vn2013-08-08T06:30:59Z2015-01-22T07:05:02Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/184This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/1842013-08-08T06:30:59ZACOHAP: An Efficient Ant Colony Optimization for the Haplotype Inference by Pure Parsimony ProblemDong Do Ducdongdd@vnu.edu.vnSy Vinh Levinhls@vnu.edu.vnXuan-Huan Hoanghuanhx@vnu.edu.vn2013-03-27T05:50:25Z2013-06-29T04:37:01Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/135This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/1352013-03-27T05:50:25ZAn Efficient Method for Fingerprint Matching based on Local Point ModelThis paper proposes a fingerprint matching method based on local Thin-Plate-Spline (TPS) deformation model, a warping technique, to deal with non-linear distorted fingerprints. After determining the set of corresponding minutiae pairs between two fingerprints by using an affine transformation, a set of corresponding pseudo-minutiae pairs are created based on their local ridge-valley structure comparison. These points are associated with the known corresponding point pairs to select a suitable landmark point set for using Local Thin Plate Spline deformation model over 9 partial areas of fingerprint images in order to find new corresponding minutiae pairs. This procedure is repeated until no more new corresponding minutiae pairs are distinguished or the number of corresponding point pairs is large enough. The experimental results on the database FVC2004 show that the proposed method significantly improves matching performance compared to the global TPS warping method.Thi Huong Thuy NguyenXuan-Huan Hoanghuanhx@vnu.edu.vnNgoc Ky Nguyen2013-03-27T05:48:48Z2013-06-29T04:37:57Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/136This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/1362013-03-27T05:48:48ZAn Efficient Ant Colony Optimization Algorithm for Multiple Graph AlignmentThe Multiple Graph Alignment (MGA) is a new method to analyze the structure of biological molecules. This method allows detect functional similarities in the structure of biological systems. This article introduces an ant colony optimization algorithm combined with local search for optimal align multi-graph analysis of protein structures. Experiment results showed that the new algorithm outperformed the other heuristic approach and existing evolutionary computing.Ngoc Ha TranDuc Dong DoXuan-Huan Hoanghuanhx@vnu.edu.vn2013-01-08T07:39:38Z2013-06-29T04:40:45Zhttp://eprints.uet.vnu.edu.vn/eprints/id/eprint/113This item is in the repository with the URL: http://eprints.uet.vnu.edu.vn/eprints/id/eprint/1132013-01-08T07:39:38ZGASVM: A Genetic Algorithm for Improving Gene Regulatory Activity PredictionGene regulatory activity prediction problem is one of the important steps to understand the significant factors for gene regulation in biology. The advents of recent sequencing technologies allow us to deal with this task efficiently. Amongst these, Support Vector Machine (SVM) has been applied successfully up to more than 80 accuracy in the case of predicting gene regulatory activity in Drosophila embryonic development. In this paper, we introduce a metaheuristic based on genetic algorithm (GA) to select the best parameters for regulatory prediction from transcriptional factor binding profiles. Our approach helps to improve more than 10 accuracy compared to the traditional grid search. The improvements are also significantly supported by biological experimental data. Thus, the proposed method helps boosting not only the prediction performance but also the potentially biological insights.Dong Do DucTri-Thanh LeTrung-Nghia VuH.Q. DinhXuan-Huan Hoanghuanhx@vnu.edu.vn