• Journal of Distribution Science
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• v.17 no.11
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• pp.73-79
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• 2019

Purpose: The purpose of this study was evaluated to compare the predictive power of distress prediction models by using discriminant analysis method and logit analysis method for food service franchise industry in Korea. Research design, data and methodology: Forty-six food service franchise industry with high sales volume in the 2017 were selected as the sample food service franchise industry for analysis. The fourteen financial ratios for analysis were calculated from the data in the 2017 statement of financial position and income statement of forty-six food service franchise industry in Korea. The fourteen financial ratios were used as sample data and analyzed by t-test. As a result seven statistically significant independent variables were chosen. The analysis method of the distress prediction model was performed by logit analysis and multiple discriminant analysis. Results: The difference between the average value of fourteen financial ratios of forty-six food service franchise industry was tested through t-test in order to extract variables that are classified as top-leveled and failure food service franchise industry among the financial ratios. As a result of the univariate test appears that the variables which differentiate the top-leveled food service franchise industry to failure food service industry are income to stockholders' equity, operating income to sales, current ratio, net income to assets, cash flows from operating activities, growth rate of operating income, and total assets turnover. The statistical significances of the seven financial ratio independent variables were also confirmed by logit analysis and discriminant analysis. Conclusions: The analysis results of the prediction accuracy of each distress prediction model in this study showed that the forecast accuracy of the prediction model by the discriminant analysis method was 84.8% and 89.1% by the logit analysis method, indicating that the logit analysis method has higher distress predictability than the discriminant analysis method. Comparing the previous distress prediction capability, which ranges from 75% to 85% by discriminant analysis and logit analysis, this study's prediction capacity, which is 84.8% in the discriminant analysis, and 89.1% in logit analysis, is found to belong to the range of previous study's prediction capacity range and is considered high number.

• Proceedings of the KSRS Conference
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• v.2
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• pp.664-667
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• 2006

Seasonal threshold values for fog detection over the ten airport areas in the Korean Peninsula have been derived, using the satellite-observed data of polar-orbit (Aqua/Terra MODIS) and geostationary (GOES-9) during two years. The values are obtained from reflectance at 0.65 ${\mu}m$ $(R_{0.65})$ and the difference in brightness temperature between 3.7 ${\mu}m$ and 11 ${\mu}m$ $(T_{3.7-11})$. In order to examine the discrepancy between the threshold values of two kinds of satellites, the following parameters have been analyzed under the condition of daytime/nighttime and fog/clear-sky, utilizing their simultaneous observations over the Seoul Metropolitan Area. The parameters are the brightness temperature at 3.7 ${\mu}m$ $(T_{3.7})$, the temperature at 11 ${\mu}m$ $(T_{11})$, and $T_{3.7-11}$ for day and night. The $R_{0.65}$ data are additionally included in the daytime. The GOES-9 thresholds over the nine airport areas except the Cheongju airport have revealed the accuracy of 60% in the daytime and 70% in the nighttime, based on statistical verification as follows; FAR, POD and CSI. However, the accuracy decreases in the foggy cases with twilight, precipitation, short persistence, or the higher cloud above fog.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.10
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• pp.884-892
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• 2014

In this paper, a meta model using neural network substituting for the simulator aerodynamic database is proposed to improve simulation fidelity near the critical flight area and real-time performance. It is shown that the accuracy of the meta model is relatively higher than the existing table lookup methods for arbitrary nonlinear database and the calculation speed is also improved for a specific F-16 maneuver simulation. The increase in the number of hidden nodes in the meta model for better accuracy of database representations causes a delay in function generation due to increased time required for computing exponential functions. In order to make up this drawback, we additionally study the fast exponential function method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.115-120
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• 2005

In this paper, we propose a new robust content-based musical genre classification algorithm using multi-feature clustering(MFC) method. In contrast to previous works, this paper focuses on two practical issues of the system dependency problem on different input query patterns(or portions) and input query lengths which causes serious uncertainty of the system performance. In order to solve these problems, a new approach called multi-feature clustering(MFC) based on k-means clustering is proposed. To verify the performance of the proposed method, several excerpts with variable duration were extracted from every other position in a queried music file. Effectiveness of the system with MFC and without MFC is compared in terms of the classification accuracy. It is demonstrated that the use of MFC significantly improves the system stability of musical genre classification performance with higher accuracy rate.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.12
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• pp.1322-1328
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• 2009

This paper presents vibration analysis of maskless exposure module in printed circuit board(PCB) manufacturing system. In order to complete exposure process in PCB, masking type module has been widely used in electronics industries. However, masking process confronts some limitations of application due to higher production cost for masking as well as lower printing resolution. Therefore, maskless exposure module is started to be in the spotlight for flexible production system to meet the needs of fabrication in variable patterns at low cost. Since maskless exposure process adopts direct patterning to PCB, vibration problems become more critical compared to conventional masking type process. Moreover, movements of exposure engine as well as stage generate vibration sources in the system. Thus, it is imperative to analyze the vibration characteristics for the maskless exposure module to improve the quality and accuracy of PCB. In this study, vibration analysis using the finite element analysis is conducted to identify the critical structural parts deteriorating vibration performance. Also, Experimental investigations are conducted by single/dual encoder measurement process under the operating module speed. Measurement points of vibration are selected by three places, which are base of stage, exposure engine and top of stage, to check the effect of vibration from the exposure engine. Comparisons between analysis results and experimental measurement are conducted to confirm the accuracy of analysis results including the developed FE model. Finally, this studies show feasibility of optimal design using the developed FE analysis model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.2
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• pp.260-267
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• 2016

The Internet has brought lots of changes to us sharing information mutually. However, as all social symptom have double-sided character, it has serious social problem. Vicious users have been taking advantage of anonymity on the Internet, stating comments aggressively for defamation, personal attacks, privacy violation and more. Malicious comments on the Internet are creating the biggest problem regarding unlawful acts and insults which occur on the Internet. In order to solve the issues, several studies have been done to efficiently manage the comments. However, there are limitations to recognize modified malicious vocabulary in previous research. So, in this paper, we propose a malicious comments detection technique by improving limitation of previous studies. The experimental result has shown accuracy of 87.8% providing higher accuracy as compared to previous studies done.

• Steel and Composite Structures
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• v.37 no.2
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• pp.117-136
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• 2020

Curved steel-concrete composite box girder has been widely adopted in urban overpasses and ramp bridges. In order to investigate its mechanical behavior under complicated and combined bending, shear and torsion load, two large-curvature composite box girders with interior angles of 25° and 45° were tested under static hogging moment. Based on the strain and deflection measurement on critical cross-sections during the static loading test, the failure mode, cracking behavior, load-displacement relationship, and strain distribution in the steel plate and rebar were investigated in detail. The test result showed the large-curvature composite box girders exhibited notable shear lag in the concrete slab and steel girder. Also, the constraint torsion and distortion effect caused the stress measured at the inner side of the composite beam to be notably higher than that of the outer side. The strain distribution in the steel web was approximately linear; therefore, the assumption that the plane section remains plane was approximately validated based on strain measurement at steel web. Furthermore, the full-process non-linear elaborate finite element (FE) models of the two specimens were developed based on commercial FE software MSC.MARC. The modeling scheme and constitutive model were illustrated in detail. Based on the comparison between the FE model and test results, the FE model effectively simulated the failure mode, the load-displacement curve, and the strain development of longitudinal rebar and steel girder with sufficient accuracy. The comparison between the FE model and the test result validated the accuracy of the developed FE model.

• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.263-269
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• 2020

In this study, a rotating machine that can reproduce normal condition and 8 fault conditions were produced, and vibration data was acquired. Feature is calculated from the acquired data, and accuracy is analyzed through fault diagnosis using artificial neural networks and genetic algorithms. In order to achieve optimal timing and higher accuracy, features by three domains were applied to the fault diagnosis. The learning number was selected as a setting variable. As a result of the rotating machine fault diagnosis, high precision was found in the frequency domain than in others, and precise fault diagnoses were accomplished through all of 10 operations, at the learning number of 5000 and 8000. Given the efficiency of time, it was estimated to be the most efficient when the number of learning was 5000.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1152-1162
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• 2019

With the rapid development of the VR industry, many VR contents are produced and circulated, and the need for copyright protection is increasing. In this paper, we propose a method of embedding and extracting watermarks in consideration of VR production process. In embedding, SIFT is performed by selecting the region where distortion is minimized in VR production, and transformed into frequency domain using DWT and embedded into the QIM method. In extracting process, in order to correct the distortion in the projection process, the top and bottom regions are changed to different projection methods and some middle regions are rotated using 3DoF to extract the watermark. After this processing, extracted watermark has higher accuracy than the conventional watermark method, and the validity of the proposed watermark is shown by showing that the accuracy is maintained even in various attacks.

• Journal of Physiology & Pathology in Korean Medicine
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• v.25 no.2
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• pp.318-321
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• 2011

In this study, when a physician make a diagnosis of the Pattern Identifications(PIs) of stroke patients, the development methods of the PIs classification function is considered by diagnostic questionnaire of the PIs for stroke patients. Clinical data collected from 1,502 stroke patients who was identically diagnosed for the PIs subtypes diagnosed by two clinical experts with more than 3 years experiences in 13 oriental medical hospitals. In order to develop the classification function into PIs using the 44 items-Fire&heat(19), Qi-deficiency(11), Yin-deficiency(7), Dampness phlegm(7)- of them was significant statistically by univariate analysis in 61 questionnaires totally, we make some comparisons of the results of discriminant analysis model and generalized logit model. The overall diagnostic accuracy rate of the PIs subtypes for discriminant model(74.37%) was higher than 3% of generalized logit model(70.09%).