• Proceedings of the KSR Conference
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• 2006.11b
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• pp.1529-1535
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• 2006

Human error is one of the major contributors to the railway accidents or incidents. In order to develop an effective countermeasure to remove or reduce human errors, a systematic analysis should be preferentially performed to identify their causes, characteristics, and types of human error induced in accidents or incidents. This paper introduces a case study for human error analysis of the railway accidents and incidents. For the case study, more than 1,000 domestic railway accidents or incidents that happened during the year of 2004 have been investigated and a detailed error analysis was performed on the selected 90 cases, which were obviously caused by human error. This paper presents a classification structure for human error analysis, and summarizes the analysis results such as causes of the events, error modes and types, related worker, and task type.

• Communications for Statistical Applications and Methods
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• v.27 no.2
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• pp.163-175
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• 2020

We consider a wide class of general weakly-dependent processes, called ψ-weak dependence, which unify almost all weak dependence structures of interest found in statistics under natural conditions on process parameters, such as mixing, association, Bernoulli shifts, and Markovian sequences. For detecting the tail behavior of the weakly dependent processes, change point tests are developed by means of cumulative sum (CUSUM) statistics with the empirical distribution functions of sample extremes. The null limiting distribution is established as a Brownian bridge. Its proof is based on the ψ-weak dependence structure and the existence of the phantom distribution function of stationary weakly-dependent processes. A Monte-Carlo study is conducted to see the performance of sizes and powers of the CUSUM tests in GARCH(1, 1) models; in addition, real data applications are given with log-returns of financial data such as the Korean stock price index.

• The Journal of Engineering Research
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• v.6 no.2
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• pp.33-38
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• 2004

To investigate the reliability of the MTJs on the roughness of insulating tunnel barrier, we prepared two MTJs with the different uniformity of barrier thickness. Namely, the one has uniform insulating barrier thickness; the other has non-uniform insulating barrier thickness as compared to different thing. As to depositing amorphous layer CoZrNb under the pinning layer IrMn, we achieved MTJ with uniform barrier thickness. Toinvestigate the reliability of the MTJs dependent on the bottom electrode, time-dependent dielectric breakdown (TDDB) measurements were carried out under constant voltage stress. The Weibull fit of out data shows clearly that $t_{BD}$ scales with the thickness uniformity of MTJs tunnel barrier. Assuming a linear dependence of log($t_{BD}$) on stress voltages, we obtained the lifetime of $10^4$years at a operating voltage of 0.4 V at MTJs comprising CoNbZr layers. This study shows that the reliabilityof new MTJs structure was improved due to the ultra smooth barrier, because the surface roughness of the bottom electrode influenced the uniformity of tunnel barrier.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.473-481
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• 2008

This paper presents an approach to Back-propagation and Radial Basis Function neural network method with various training set for automatic vehicle detection from aerial images. The initial extraction of candidate object is based on Mean-shift algorithm with symmetric property of a vehicle structure. By fusing the density and the symmetry, the method can remove the ambiguous objects and reduce the cost of processing in the next stage. To extract features from the detected object, we describe the object as a log-polar shape histogram using edge strengths of object and represent the orientation and distance from its center. The spatial histogram is used for calculating the momentum of object and compensating the direction of object. BPNN and RBFNN are applied to verify the object as a vehicle using a variety of non-car training sets. The proposed algorithm shows the results which are according to the training data. By comparing the training sets, advantages and disadvantages of them have been discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.277-279
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• 2014

In case of APT attacks, the update server is being used as a means of dissemination, the update program is running malicious code or data in applications such as anti-virus signature is vulnerable to manipulation, SW Update threat identification and prevention measures are urgently required. This paper presents a natiional and international SW update structure, update process exploits and response measures to examine, Through the extraction/analysis of a domestic famous SW update log, we are willing to select the necessary component of the normal program update to identify a white list.

• Korean Chemical Engineering Research
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• v.54 no.5
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• pp.621-629
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• 2016

Recently, the researches on quantitative structure activity relationship (QSAR) for describing toxicities or activities of chemicals based on chemical structural characteristics have been widely carried out in order to estimate the toxicity of chemicals in multiuse facilities. Because the toxicity of chemicals are explained by various kinds of molecular descriptors, an important step for QSAR model development is how to select significant molecular descriptors. This research proposes a statistical selection of significant molecular descriptors and a new QSAR model based on partial least square (PLS). The proposed QSAR model is applied to estimate the logarithm of partition coefficients (log P) of 130 polychlorinated biphenyls (PCBs) and lethal concentration ($LC_{50}$) of 14 PCBs, where the prediction accuracies of the proposed QSAR model are compared to a conventional QSAR model provided by OECD QSAR toolbox. For the selection of significant molecular descriptors that have high correlation with molecular descriptors and activity information of the chemicals of interest, correlation coefficient (r) and variable importance of projection (VIP) are applied and then PLS model of the selected molecular descriptors and activity information is used to predict toxicities and activity information of chemicals. In the prediction results of coefficient of regression ($R^2$) and prediction residual error sum of square (PRESS), the proposed QSAR model showed improved prediction performances of log P and $LC_{50}$ by 26% and 91% than the conventional QSAR model, respectively. The proposed QSAR method based on computational toxicology can improve the prediction performance of the toxicities and the activity information of chemicals, which can contribute to the health and environmental risk assessment of toxic chemicals.

• The Korean Journal of Pesticide Science
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• v.4 no.2
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• pp.21-28
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• 2000

A new fourty six 2-(4-(6-chloro-2-benzoxazolyloxy)phenoxy)-N-phenylpro- pionamide derivatives were synthesized and the herbicidal activities against rice plant and barnyard grass with pre-emergence in down land were measured. The structure activity relationships (SAR) between the activities and physicochemical parameters of the substituted(X) N-phenyl group in substrates were analyzed and discussed by Free- Wilson and Hansch method from the basis on the former study (Sung. et. al., 1999). The conditions of selective herbicide activity both the barnyard grass and rice plant are shown that the optimal hydrophobicity, $({\pi})_{opt.}=1.34$ and electron donating with field effect (F<0) of meta and ortho, para-substituted mono or disubstituent on the N-phenyl ring were found to contribute significantly. The herbicidal activities against barnyard grass are roughly the same as the results in up land whereas damage to rice plant in down land more increase than that of up land. Degradation products in water are 2-(4-(6-chloro-2-benzoxazolyloxy)phenoxy)propionic acid ((A)) (obs. pKa=4.35 & obs. logP=4.77) and 6-chloro-2-benzoxazolone (B) (obs. pKa=8.40 & obs. logP=2.90). These results were supposing that the hydrolysis product of substrates, (A) is comparatively absorbed in rice plant but not in barnyard grass. And it is assumed from the SAR equations that the 2,6-dimethyl-4-methoxymethyl group substituent ($pI_{50}=5.41$, 3g/ha) is selected as the most highest herbicidal activity against barnyard grass in green house.

• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.6
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• pp.323-332
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• 2018

Recent two moderate earthquakes (2016 $M_w=5.4$ Gyeongju and 2017 $M_w=5.5$ Pohang) in Korea provided the unique chance of developing a set of relations to estimate instrumental seismic intensity in Korea by augmenting the time-history data from MMI seismic intensity regions above V to the insufficient data previously accumulated from the MMI regions limited up to IV. The MMI intensity regions of V and VI was identified by delineating the epicentral distance from the reference intensity statistics in distance derived by using the integrated MMI data obtained by combining the intensity survey results of KMA (Korea Meteorological Administration) and 'DYFI (Did You Feel It)' MMIs of USGS. The time-histories of the seismic stations from the MMI intensity regions above V were then preprocessed by applying the previously developed site-correction filters to be converted to a site-equivalent condition in a manner consistent with the previous study. The average values of the ground-motion parameters for the three ground motion parameters of PGA, PGV and BSPGA (Bracketed Summation of PGA per second for 30 seconds) were calculated for the MMI=V and VI and used to generate the dataset of the average values of the ground-motion parameters for the individual MMIs from I to VI. Based on this dataset, the linear regression analysis resulted in the following relations with proposed valid ranges of MMI. $MMI=2.36{\times}log_{10}(PGA(gal))+1.44$ ($I{\leq}MMI$$MMI=2.44{\times}log_{10}(PGV(kine))+4.86$ ($I{\leq}MMI$$MMI=2.59{\times}log_{10}(BSPGA(gal{\cdot}sec))-1.02$ ($I{\leq}MMI$

• Journal of KIISE:Software and Applications
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• v.33 no.9
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• pp.787-801
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• 2006

Ontology merging describes the process of integrating two ontologies into a new ontology. How this is done best is a subject of ongoing research in the Semantic Web, Data Integration, Knowledge Management System, and other ontology-related application systems. Earlier research on ontology merging, however, has studied for developing effective ontology matching approaches but missed analyzing and solving methods of problems of merging two ontologies given correspondences between them. In this paper, we propose a specific ontology merging process and a generic operator, T-MERGE, for integrating two source ontologies into a new ontology. Also, we define a taxonomy of merging conflicts which is derived from differing representations between input ontologies and a method for detecting and resolving them. Our T-MERGE operator encapsulates the process of detection and resolution of conflicts and merging two entities based on given correspondences between them. We define a data structure, MergeLog, for logging the execution of T-MERGE operator. MergeLog is used to inform detailed results of execution of merging to users or recover errors. For our experiments, we used oriental philosophy ontologies, western philosophy ontologies, Yahoo western philosophy dictionary, and Naver philosophy dictionary as input ontologies. Our experiments show that the automatic merging module compared with manual merging by a expert has advantages in terms of time and effort.

• Applied Biological Chemistry
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• v.39 no.4
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• pp.297-303
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• 1996

A series of the herbicidal N-(4,6-disubstituted pyrimidin-2-yl)aminocarbonyl-2-(1,1-ethylenedioxy-2-fluoro)ethyIbenzenesulfonamides, 1 and N-(4,6-disubstituted triazin-2-yl)aminocarbonyl-2-(1,1-ethylenodioxy-2-flu ore)ethylbenzenosuIfonamides, 2 were synthesized and their herbicidal activities in-vivo against rice(Oryza sativa L.), barnyard grass (Echinochloa crus-galli), bulrush(Scripus juncoides) and pickerel weed(Monochoria vaginalis presl.) were measured by the pot test under the paddy conditions. The structure activity relationships(SAR) between the herbicidal activity$(pI_{50})$ and a various physicochemical parameters of the hetero group and 4,6-disubstituents on the heterocyclic group were analyzed by the multiple regression technique. The SAR suggest that the 4,6-dimethoxypyrimidine substituent, 1a showed selective$({\Delta}obs.pI_{50}=1.12)$ and the most highest activity against barnyard grass, which depend on the hydrophobicity(log P<0) of heterocyclo group and molecular refractivity$((M_R)_{opt.}=14.58cm^3/mol)$ constant of 4,6-disubstituents on the heterocyclic group.