• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.12
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• pp.2287-2297
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• 2007

The proposed ANIDS(Advanced Network Intrusion Detection System) which is network-based IDS using Association Rule Mining, collects the packets on the network, analyze the associations of the packets, generates the pattern graph by using the highly associated packets using Association Rule Mining, and detects the intrusion by using the generated pattern graph. ANIDS consists of PMM(Packet Management Module) collecting and managing packets, PGGM(Pattern Graph Generate Module) generating pattern graphs, and IDM(Intrusion Detection Module) detecting intrusions. Specially, PGGM finds the candidate packets of Association Rule large than $Sup_{min}$ using Apriori algorithm, measures the Confidence of Association Rule, and generates pattern graph of association rules large than $Conf_{min}$. ANIDS reduces the false positive by using pattern graph even before finalizing the new pattern graph, the pattern graph which is being generated is compared with the existing one stored in DB. If they are the same, we can estimate it is an intrusion. Therefore, this paper can reduce the speed of intrusion detection and the false positive and increase the detection ratio of intrusion.

• Korean Journal of Computational Design and Engineering
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• v.16 no.4
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• pp.300-304
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• 2011

This paper proposes an approach to generate tool-path for laser pattern machining. Considering the mechanical structure of a laser pattern machine, it is quite similar to that of a 2D milling machine. Based on the observation, one may try to utilize the tool-path generation methodologies of 2D milling for the laser pattern machining. However, it is not possible to generate tool-path without considering the technological requirements of laser pattern machining which are different from those of 2D milling. In this paper, we identify the technological requirement of laser pattern machining, and propose a proper tool-path generation methodology to satisfy the technological requirements. For the efficient generation of tool-path, this paper proposes a tool-path element computation method, which is based on the concept of a monotone chain.

• Structural Engineering and Mechanics
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• v.16 no.4
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• pp.441-468
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• 2003

This paper investigates the structural behavior of modular falsework system under sequential pattern loads. Based on the studies of 25 construction sites, the pattern load sequence modeling is defined as models R (rectangle), L and U. The study focuses on the system critical loads, regions of largest reaction forces, discrepancy between the pattern load and the uniform load, and the warning-system plan. The analysis results show that the critical loads of modular falsework systems with sequential pattern loads are very close to those with the uniform load used in design. The regions of largest reaction forces are smaller than those calculated by the uniform load. However, the regions of largest reaction forces of three models under sequential pattern loads can be considered as the crucial positions of warning-system based on the measured index of loading. The positions of the sensors for the warning-system for these three different models are not identical.

• Journal of Nutrition and Health
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• v.54 no.3
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• pp.247-261
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• 2021

Purpose: This study was conducted to identify the association between insulin resistance and the major dietary patterns of Korean adults. Methods: This study used data from the 2015 Korea National Health and Nutrition Examination Survey. The subjects were 2,276 adults aged 19 to 64 years old. Based on the food frequency questionnaire data, 112 food items were reclassified into 30 food groups. The principal component analysis method was applied to identify major dietary patterns. We used homeostatic model assessment of insulin resistance (HOMA-IR) and quantitative insulin sensitivity check index (QUICKI) value as indicators of insulin resistance. The association between major dietary patterns and insulin resistance was investigated using logistic regression analysis. Results: Three major dietary patterns were identified and assigned descriptive names based on the food items with high loadings: 'healthy Korean meal pattern', 'western meal pattern', and 'white rice, alcohol, meat pattern'. As the 'white rice, alcohol, meat pattern' score increased, significant increasing trends for fasting glucose concentration and HOMA-IR and a significant decreasing trend for QUICKI were observed after adjusting for age and sex. The odds ratio of insulin resistance according to the 'healthy Korean meal pattern' and the 'western meal pattern' were not statistically significant. the 'white rice, alcohol, meat pattern' showed a significant positive association with the risk of insulin resistance after adjusting for covariates. Conclusion: These results suggest that the 'white rice, alcohol, meat pattern' is positively associated with the risk of insulin resistance. The white rice, alcohol, meat pattern was related to the high consumption of alcohol together with rice or meat. This pattern was also associated with the high intake of sodium and low intakes of vitamin C, calcium, potassium, and dietary fiber. To confirm the association, further longitudinal studies are required.

• Fashion & Textile Research Journal
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• v.23 no.6
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• pp.744-757
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• 2021

This study aims to develop a bodice and a jacket in 3D of the late 19th to early 20th based on the pattern drafting book of Gordon S. S., which contains body measurement method and pattern drafting system. The findings of this research are as follows. First, female tops of the late 19th to early 20th century are categorized as outer, jacket, vest, and bodice. Of these, this study highlights the jacket, which can be divided into 4 types: 4 kinds of basic jacket, 2 kinds of riding jacket, bolero jacket, and newmarket jacket. Second, by referring to Gordon's pattern drafting system and book, a bodice was developed in 3D format based on the adherence to the following steps: analysis of the pattern drafting system, pattern drafting, 3D virtual simulation, 3D virtual fitting analysis, and the pattern correction. A bodice pattern corrected by 3D virtual clothing simulation results was proposed. Last, a basic sleeve and collar pattern for a basic jacket was drafted, which was followed by the correction and transformation of the bodice pattern. The jacket developed shows great fit except for the issues at the armhole line and shoulder, which were caused by the unique shape of the sleeves(big sleeve head) of the time. The study attempted to develop the past costumes in 3D, providing the basis for interdisciplinary research in the field of fashion history field and suggesting a new approach for the virtual restoration of costumes. Future studies should target to 3D virtual simulation in accordance to the 3D avatar pose in the developed virtual costume.

• Journal of Communications and Networks
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• v.17 no.6
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• pp.568-581
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• 2015

Predicting locations of users with portable devices such as IP phones, smart-phones, iPads and iPods in public wireless local area networks (WLANs) plays a crucial role in location management and network resource allocation. Many techniques in machine learning and data mining, such as sequential pattern mining and clustering, have been widely used. However, these approaches have two deficiencies. First, because they are based on profiles of individual mobility behaviors, a sequential pattern technique may fail to predict new users or users with movement on novel paths. Second, using similar mobility behaviors in a cluster for predicting the movement of users may cause significant degradation in accuracy owing to indistinguishable regular movement and random movement. In this paper, we propose a novel fusion technique that utilizes mobility rules discovered from multiple similar users by combining clustering and sequential pattern mining. The proposed technique with two algorithms, named the clustering-based-sequential-pattern-mining (CSPM) and sequential-pattern-mining-based-clustering (SPMC), can deal with the lack of information in a personal profile and avoid some noise due to random movements by users. Experimental results show that our approach outperforms existing approaches in terms of efficiency and prediction accuracy.

• Journal of Environmental Science International
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• v.29 no.4
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• pp.361-369
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• 2020

With the increasing role of environmental design in promoting urban safety, new design attempts have been made to improve pedestrian safety in crosswalks. This study proposes an evidence-based design solution for improving crosswalk function by conducting simulations and field experiments. Drivers with more than one-year driving experience participated in this study. Four different crosswalk design patterns were prepared: (1) a zebra pattern, (2) zebra pattern with colored triangles, (3) 3D pattern, and (4) art pattern with unique colors and design. The results supported that the zebra pattern with colored triangles could be the most effective solution for crosswalk design by increasing visibility, attention, deceleration, and landscape aesthetics. This study provided objective data to support the performance of various crosswalk patterns and suggested the need to reevaluate the present crosswalk design guidelines.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.9
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• pp.540-546
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• 2003

A fast pattern classification algorithm with Cellular Nonlinear Network-based dynamic programming is proposed. The Cellular Nonlinear Networks is an analog parallel processing architecture and the dynamic programing is an efficient computation algorithm for optimization problem. Combining merits of these two technologies, fast pattern classification with optimization is formed. On such CNN-based dynamic programming, if exemplars and test patterns are presented as the goals and the start positions, respectively, the optimal paths from test patterns to their closest exemplars are found. Such paths are utilized as aggregating keys for the classification. The algorithm is similar to the conventional neural network-based method in the use of the exemplar patterns but quite different in the use of the most likely path finding of the dynamic programming. The pattern classification is performed well regardless of degree of the nonlinearity in class borders.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.25-30
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• 2018

Pattern classification system is often an important component of intelligent systems. In this paper, we present a pattern classification system consisted of the feature selection module, knowledge base construction module and decision module. We introduce a feature impact evaluation selection method based on fuzzy cluster analysis considering computational approach and generalization capability of given data characteristics. A fuzzy neural network, OFUN-NET based on unsupervised learning data mining technique produces knowledge base for representative clusters. 240 blemish pattern images are prepared and applied to the proposed system. Experimental results show the feasibility of the proposed classification system as an automating defect inspection tool.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.45-50
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• 2021

The adjustment of lens magnification can make the degree of precision in pattern measurement be improved, but several problems such as high cost, smaller field of view and stage error accumulation are followed. In this paper, a method for precisely measuring patterns is proposed based on gradient transition vector, in order to solve these problems. The performance of our method is evaluated using pattern images with several directions. Also, it is compared with previous methods based on edge and gray-level moment. It is judged that the proposed method outperforms consistent pattern width results, and so could be applied to automation processes for measurement and inspection of precise and complexed patterns in IT, BT industry products.