• Journal of Korea Water Resources Association
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• v.32 no.3
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• pp.255-263
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• 1999

The laboratory datas are for local scour depth measurement at vertical-wall abutment. These include the data to demonstrate the effects of local scour depth of abutment nose shape, alignment angle, flow depth and flume slope. The pattern of local scour were measured and analyzed the abutments which are rectangular, sharp, chamfered rectangular and ablong nose shapes. The experiments were carried out with varing the flume slope and alignment algle increasing flow depth every step in 1cm for four abutment types on the live-bed scour conditions. The flume slope and alignment angle were varied in five cases : for latter 30 $^{\circ}$, 60 $^{\circ}$, 90 $^{\circ}$, 120 $^{\circ}$ and 150 $^{\circ}$, for former 0.01%, 0.03%, 0.05%, 0.1% and 0.2%. The maximum scour depths were analyzed for the shaped of abutment nose with rectangular, ablong, chamfered rectangular and sharp in order. The results of the experiments show that the scour depth varies not only with abutment nose shapes and alignment angle but also with the flow depth and flume slope.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1627-1648
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• 2012

We propose an adaptive method for detecting plagiarized pairs from a large set of source code. This method is adaptive in that it uses an adaptive algorithm and it provides an adaptive threshold for determining plagiarism. Conventional algorithms are based on greedy string tiling or on local alignments of two code strings. However, most of them are not adaptive; they do not consider the characteristics of the program set, thereby causing a problem for a program set in which all the programs are inherently similar. We propose adaptive local alignment-a variant of local alignment that uses an adaptive similarity matrix. Each entry of this matrix is the logarithm of the probabilities of the keywords based on their frequency in a given program set. We also propose an adaptive threshold based on the local outlier factor (LOF), which represents the likelihood of an entity being an outlier. Experimental results indicate that our method is more sensitive than JPlag, which uses greedy string tiling for detecting plagiarism-suspected code pairs. Further, the adaptive threshold based on the LOF is shown to be effective, and the detection performance shows high sensitivity with negligible loss of specificity, compared with that using a fixed threshold.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.23-30
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• 2004

Ontologies play an important role in the Semantic Web by providing well-defined meaning to ontology consumers. But as the ontologies are authored in a bottom-up distributed mimer, a large number of overlapping ontologies are created and used for the similar domains. Ontology sharing and reuse have become a distinguished topic, and ontology merging and alignment are the solutions for the problem. Ontology merging and alignment algorithms previously proposed detect conflicts between concepts by making use of only local syntactic information of concept names. And they depend only on a semi-automatic approach, which makes ontology engineers tedious. Consequently, the quality of merging and alignment tends to be unsatisfying. To remedy the defects of the previous algorithms, we propose a new algorithm for ontology merging and alignment which uses local and global semantic set of a concept. We evaluated our algorithm with several pairs of ontologies written in OWL, and achieved around 91% of precision in merging and alignment. We expect that, with the widespread use of web ontology, the need for ontology sharing and reuse ill become higher, and our proposed algorithm can significantly reduce the time required for ontology development. And also, our algorithm can easily be applied to various fields such as ontology mapping where semantic information exchange is a requirement.

• Journal of Korean Neurosurgical Society
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• v.66 no.1
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• pp.33-43
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• 2023

Objective : To compare the outcomes of anterior lumbar interbody fusion (ALIF), oblique lumbar interbody fusion (OLIF), and transforaminal lumbar interbody fusion (TLIF) in terms of global sagittal alignment. Methods : From January 2007 to December 2019, 141 adult patients who underwent multilevel interbody fusion for lumbar degenerative disorders were enrolled. Regarding the approach, patients were divided into the ALIF (n=23), OLIF (n=60), and TLIF (n=58) groups. Outcomes, including local radiographic parameters and global sagittal alignment, were then compared between the treatment groups. Results : Regarding local radiographic parameters, ALIF and OLIF were superior to TLIF in terms of the change in the anterior disc height (7.6±4.5 mm vs. 6.9±3.2 mm vs. 4.7±2.9 mm, p<0.001), disc angle (-10.0°±6.3° vs. -9.2°±5.2° vs. -5.1°±5.1°, p<0.001), and fused segment lordosis (-14.5°±11.3° vs. -13.8°±7.5° vs. -7.4°±9.1°, p<0.001). However, regarding global sagittal alignment, postoperative lumbar lordosis (-42.5°±9.6° vs. -44.4°±11.6° vs. -40.6°±12.3°, p=0.210), pelvic incidence-lumbar lordosis mismatch (7.9°±11.3° vs. 6.7°±11.6° vs. 11.5°±13.0°, p=0.089), and the sagittal vertical axis (24.3±28.5 mm vs. 24.5±34.0 mm vs. 25.2±36.6 mm, p=0.990) did not differ between the groups. Conclusion : Although the anterior approaches were superior in terms of local radiographic parameters, TLIF achieved adequate global sagittal alignment, comparable to the anterior approaches.

• Bioinformatics and Biosystems
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• v.1 no.2
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• pp.123-127
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• 2006

TIM barrel domain is widely studied since it is one of most common structure and mediates diverse function maintaining overall structure. TIM barrel domain's function is determined by local structural environment at the C-terminal end of barrel structure. We classified TIM barrel domains by local structural alignment tool, LSHEBA, to understand characteristics of TIM barrel domain's functionalvariation. TIM barrel domains classified as the same cluster share common structure, function and ligands. Over 80% of TIM barrels in clusters share exactly the same catalytic function. Comparing clustering result with that of SCOP, we found that it's important to know local structural environment of TIM barrel domains rather than overallstructure to understand specific structural detail of TIM barrel function. Non TIM barrel domains were associated to make different domain combination to form a different function. The relationship between domain combination, we suggested expected evolutional history. We finally analyzed the characteristics of amino acids around ligand interface.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.359-366
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• 2009

Analysis of 3-dimensional (3D) protein structure plays an important role of structural bioinformatics. The protein structure alignment is the main subjects of the structural bioinformatics and the most fundamental problem. Protein Structures are flexible and undergo structural changes as part of their function, and most existing protein structure comparison methods treat them as rigid bodies, which may lead to incorrect alignment. We present a new method that carries out the flexible structure alignment by means of finding SSPs(Similar Substructure Pairs) and flexible points of the protein. In order to find SSPs, we encode the coordinates of atoms in the backbone of protein into RDA(Relative Direction Angle) using local similarity of protein structure. We connect the SSPs with Floyd-Warshall algorithm and make compatible SSPs. We compare the two compatible SSPs and find optimal flexible point in the protein. On our well defined performance experiment, 68 benchmark data set is used and our method is better than three widely used methods (DALI, CE, FATCAT) in terms of alignment accuracy.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.109-112
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• 2005

Identifying orthologous paralogenes is a fundamental problem in comparative genomics and can facilitate the study of evolutionary history of the species. Existing approaches for locating paralogs make use of local alignment based algorithms such as BLAST. However, there are cases that genes with high alignment scores are not paralogenes. On the other hand, whole genome alignment tools are designed to locate orthologs. Most of these tools are based on some unique substrings (called anchors) in the corresponding orthologous pair to identify them. Intuitively, these tools may not be useful in identifying orthologous paralogenes as paralogenes are very similar and there may not be enough unique anchors. However, our study shows that this is not true. Paralogenes although are similar, they have undergone different mutations. So, there are enough unique anchors for identifying them. Our contributions include the followings. Based on this counter-intuitive finding, we propose to employ the whole genome alignment tools to help verifying paralogenes. Our experiments on five pairs of human-mouse chromosomes show that our approach is effective and can identify most of the mis-classified paralog groups (more than 80%). We verify our finding that whole genome alignment tools are able to locate orthologous paralogenes through a simulation study. The result from the study confirms our finding.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.1926-1945
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• 2014

In this paper, we propose a distributed signal subspace interference alignment algorithm for single beam K-user ($3K{\geq}$) MIMO interference channel based on sum rate maximization and game theory. A framework of game theory is provided to study relationship between interference signal subspace and altruistic-egoistic bayesian game cost function. We demonstrate that the asymptotic interference alignment under proposed scheme can be realized through a numerical algorithm using local channel state information at transmitters and receivers. Simulation results show that the proposed scheme can achieve the total degrees of freedom that is equivalent to the Cadambe-Jafar interference alignment algorithms with perfect channel state information. Furthermore, proposed scheme can effectively minimize leakage interference in desired signal subspace at each receiver and obtain a moderate average sum rate performance compared with several existing interference alignment schemes.

• Journal of Computational Design and Engineering
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• v.1 no.4
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• pp.223-232
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• 2014

This paper describes a variant of the extended Gaussian image based registration algorithm for point clouds with surface color information. The method correlates the distributions of surface normals for rotational alignment and grid occupancy for translational alignment with hue filters applied during the construction of surface normal histograms and occupancy grids. In this method, the size of the point cloud is reduced with a hue-based down sampling that is independent of the point sample density or local geometry. Experimental results show that use of the hue filters increases the registration speed and improves the registration accuracy. Coarse rigid transformations determined in this step enable fine alignment with dense, unfiltered point clouds or using Iterative Common Point (ICP) alignment techniques.

• Journal of Computing Science and Engineering
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• v.11 no.4
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• pp.121-129
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• 2017

Feature selection has been widely established as an efficient technique for microarray data analysis. Feature selection aims to search for the most important feature/gene subset of a given dataset according to its relevance to the current target. Unsupervised feature selection is considered to be challenging due to the lack of label information. In this paper, we propose a novel method for unsupervised feature selection, which incorporates embedded learning and $l_{2,1}-norm$ sparse regression into a framework to select genes in microarray data analysis. Local tangent space alignment is applied during embedded learning to preserve the local data structure. The $l_{2,1}-norm$ sparse regression acts as a constraint to aid in learning the gene weights correlatively, by which the proposed method optimizes for selecting the informative genes which better capture the interesting natural classes of samples. We provide an effective algorithm to solve the optimization problem in our method. Finally, to validate the efficacy of the proposed method, we evaluate the proposed method on real microarray gene expression datasets. The experimental results demonstrate that the proposed method obtains quite promising performance.