• Journal of the military operations research society of Korea
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• v.5 no.1
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• pp.37-72
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• 1979

This paper presents the FORTRAN program for expected damage by surface-to-surface weapons. One of the methods can be used to determine the effectiveness of general purpose (GP) bombs and cluster weapons against single unitary targets, linear targets, area targets, and areas of unitary target elements, The effectiveness index is in terms of fractional damage ($F_D$) or the number of volleys ($N_V$).

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.902-908
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• 2006

We propose a scheme for more efficient navigation in a hierarchical file system. In the proposed scheme, a program running in the background computes the degree of relationship between a current file and others, and builds a list of the most related files. The current relationship metric being used by the program is a linear combination of five parameters: the name, the directory path, the type, the created time, and the last accessed time of a file. A simulated annealing algorithm is used in order to determine the weighting factors of the parameters. A set of experiments were conducted in order to access the effectiveness of the proposed scheme.

• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.381-383
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• 2002

This paper proposes a MATLAB program for solving security-constrained optimal power flow using linear programming. Security-constrained optimal power flow can find an optimal generation satisfying bus voltage limits, line flow limits, reactive generation limits, even if contingency occurs. Sensitivity matrixes are obtained based on power flow solutions with and without single line contingency. This program is tested for an IEEE 14bus system with 5 generators Results shows good ability of finding optimal solution in case of a single line contingency.

• Proceedings of the KSR Conference
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• 1998.05a
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• pp.510-516
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• 1998

Dynamic stability of a high speed train is very important. This paper presents a dynamic stability analysis of K-TGV using Vampire Program. The analysis of stability on this paper is performed in condition of track irregularity, curved track and strong gust. The critical speed of K-TGV is 140m1s, and it is stable when runs on 7000R(cant 150mm) curved track and on linear track with the body exerted 101kN lateral impulse force.

• Journal of Communications and Networks
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• v.12 no.3
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• pp.246-252
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• 2010

A binary linear integer program is formulated for the problem of expanding the capacity of a fiber optic network and routing the traffic to deliver new interactive multimedia services. A two-phase Lagrangian dual search procedure and a Lagrangian heuristic are developed. Computational results show superior performance of the two-phase subgradient optimization compared with the conventional one-phase approach.

• Proceedings of the KSR Conference
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• 1998.11a
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• pp.313-320
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• 1998

The critical speed of a train running on the straight railway track is investigated by in-house program. The program is developed to find out nonlinear critical speed and it bases on the bifurcation theory. As a result, it is found that nonlinear critical speed exists on the lower speed band than linear critical speed and this fact imply a possibility of induction of a big accident.

• The Journal of Fisheries Business Administration
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• v.50 no.1
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• pp.17-37
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• 2019

The purpose of this study is to estimate the resource recovery effect and the economic effect of the fishermen by the fisheries vessel buy-back program. First, this study standardizes the fishing efforts of coastal gill net, coastal trap, and coastal composite fisheries using Gavaris general linear model. Second, the resource evaluation is performed by using vessel buy-back program data, and also the CYP model based on exponential growth function is applied. In order to derive the effect of the vessel buy-back program, the MSY with the vessel buy-back program is compared with the MSY without the vessel buy-back program. Finally, we compare and analyze producer surplus under the equilibrium of the MEY and the OA using bioeconomic model. In conclusion, the vessel buy-back program has shown an increase in resource growth and economic improvement for the remaining fishermen. The result shows that the remaining fishermen are able to obtain an increase in producer surplus of about 53% due to the vessel buy-back program under equilibrium levels of the open access and the maximum economic yield.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.11
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• pp.1551-1557
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• 2015

The missing heritability has been a major problem in the analysis of best linear unbiased prediction (BLUP). We introduced the traditional genome-wide association study (GWAS) into the BLUP to improve the heritability estimation. We analyzed eight pork quality traits of the Berkshire breeds using GWAS and BLUP. GWAS detects the putative quantitative trait loci regions given traits. The single nucleotide polymorphisms (SNPs) were obtained using GWAS results with p value <0.01. BLUP analyzed with significant SNPs was much more accurate than that with total genotyped SNPs in terms of narrow-sense heritability. It implies that genomic estimated breeding values (GEBVs) of pork quality traits can be calculated by BLUP via GWAS. The GWAS model was the linear regression using PLINK and BLUP model was the G-BLUP and SNP-GBLUP. The SNP-GBLUP uses SNP-SNP relationship matrix. The BLUP analysis using preprocessing of GWAS can be one of the possible alternatives of solving the missing heritability problem and it can provide alternative BLUP method which can find more accurate GEBVs.

• Radiation Oncology Journal
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• v.33 no.1
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• pp.42-49
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• 2015

Purpose: In order to keep the acceptable level of the radiation oncology linear accelerators, it is necessary to apply a reliable quality assurance (QA) program. Materials and Methods: The QA protocols, published by authoritative organizations, such as the American Association of Physicists in Medicine (AAPM), determine the quality control (QC) tests which should be performed on the medical linear accelerators and the threshold levels for each test. The purpose of this study is to increase the accuracy and precision of the selected QC tests in order to increase the quality of treatment and also increase the speed of the tests to convince the crowded centers to start a reliable QA program. A new method has been developed for two of the QC tests; optical distance indicator (ODI) QC test as a daily test and gantry angle QC test as a monthly test. This method uses an image processing approach utilizing the snapshots taken by the CCD camera to measure the source to surface distance (SSD) and gantry angle. Results: The new method of ODI QC test has an accuracy of 99.95% with a standard deviation of 0.061 cm and the new method for gantry angle QC has a precision of $0.43^{\circ}$. The automated proposed method which is used for both ODI and gantry angle QC tests, contains highly accurate and precise results which are objective and the human-caused errors have no effect on the results. Conclusion: The results show that they are in the acceptable range for both of the QC tests, according to AAPM task group 142.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.3
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• pp.136-141
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• 2012

One of the main reasons for serious road accidents is driving while drowsy. For this reason, drowsiness detection and warning system for drivers has recently become a very important issue. Monitoring physiological signals provides the possibility of detecting features of drowsiness and fatigue of drivers. One of the effective signals is to measure electroencephalogram (EEG) signals and electrooculogram (EOG) signals. The aim of this study is to extract drowsiness-related features from a set of EEG signals and to classify the features into three states: alertness, drowsiness, sleepiness. This paper proposes a neural-network-based drowsiness detection system using Linear Predictive Coding (LPC) coefficients as feature vectors and Multi-Layer Perceptron (MLP) as a classifier. Samples of EEG data from each predefined state were used to train the MLP program by using the proposed feature extraction algorithms. The trained MLP program was tested on unclassified EEG data and subsequently reviewed according to manual classification. The classification rate of the proposed system is over 96.5% for only very small number of samples (250ms, 64 samples). Therefore, it can be applied to real driving incident situation that can occur for a split second.