• Journal of Aerospace System Engineering
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• v.18 no.4
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• pp.96-101
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• 2024

The Synthetic Aperture Radar (SAR) is equipped with a Transmitter/Receiver (TR) module, which serves as the signal transmission and reception unit for acquiring image data. The TR module generates significant heat during signal generation and amplification, potentially degrading performance or causing mission failure. Furthermore, launch and operational environments may result in structural damage to the components. Thus, assessing the thermal and structural safety of the TR module through thermal and vibration tests is essential to guarantee its safety. Safety assessments can be verified through environmental tests prescribed in MIL-STD-883. This paper explores the thermal and structural safety characteristics of the TR module by simulating test environments using finite element analysis prior to conducting environmental tests.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.331-336
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• 2004

In order to strengthen the competitiveness of port against calling for the huge vessel and reducing the shipping service time, the productivity of container terminal must be improved. This productivity variously results according to the kinds of productivity evaluation model, input elements like yard, equipment, employee, facility, etc,. But, it is discussed that the productivity is measured by partial productivity evaluation model or general input elements. Therefore, we measured for the productivity of the container terminal using the Developed the data Envelopment Analysis (DEA), which is developed in order to evaluate the relative efficiency of decision making units - it's difficult to clear cause and effect between input and output. We measured the whole productivity of container terminal in Busan according to decision of the correct input elements. And we investigated the change of the productivity measurement result according to input elements, presents more accurate productivity evaluation model in container terminal.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.53-68
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• 2011

A selection of viewpoint is a first priority for landscape evaluation. However, it has been artificially carried out by a subjective method without of criterion. Therefore, this study proposed the objective and quantitative viewpoint selection methods using space syntax and GIS. For this, the study area on samduk3 residential improvement district located at Daegu city was divided into 24 sectors of visibility zone by distance and direction. After that, the preliminary viewpoints equally distributed in space were selected by axial map analysis of space syntax and viewshed-frequency analysis of GIS. According to the result of selection of the final viewpoints using the VEI(Viewpoint Evaluation Index), all the final viewpoints were placed in the National Debt Repayment Movement; VEI value of VP-2 was 112.63 in the foreground, VP-10 was 18.31 in the middleground and VP-18 was 5.55 in the background. Selected viewpoints were verified as a big changing of landscape variation and high chance of view such as the public area, the park and the high-density residential area. Thus, VEI will be used as a quantitative method of selecting viewpoints and it is expected to be able to use as the objective indicator.

• Journal of Educational Research in Mathematics
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• v.26 no.2
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• pp.189-204
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• 2016

As compared with the gender differences in the achievement of mathematics of the PISA 2009, the results of this study on the PISA 2012 show that the achievement of male students sharply increased, while that of female students maintained the status quo. Based on the premise that this result is derived from the ratio differences between male and female students of high level, this study analyzed the educational context variable effects on the achievements of gender differences observed between male and female students of high level. In particular, this study inquired into the factors which influence the gender difference, by analyzing the identical variables regarding Singapore and Finland of which the achievement of female students registers high among other top high-ranking countries of the PISA 2012. Hence, the binominal logistic multi-level analysis was conducted in order to consider the characteristics of hierarchical structure of PISA, and to compare the features of the educational context variable effects between the high level (above level 5) by country and the highest level (above level 6) by group. The analysis results are as follows: in terms of after-school learning time realized either in private lessons and private institutes, no significant effects were shown in any of the students of these three countries. In terms of after-school homework time, the students of Korea and Singapore gave significant influences on the probability which would be included in the group of high level or the highest level. In particular, regarding the variables which influence the probability of inclusion of Korean female students in the group of high level or the highest level, they correspond to "Homework set by teacher", "Attitude toward school: learning activities", "ESCS of School" and "Teacher-student relations". And "Cultural possessions at home" gave main influences on the probability of inclusion of the female students of Korea, Singapore and Finland in the group of the highest level.

• Journal of Korea Water Resources Association
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• v.52 no.7
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• pp.463-473
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• 2019

This study compared the characteristics of the optimization technique and the water supply and demand forecast using K-WEAP (Korea-Water Evaluation and Planning System) model and MODSIM (Modified SIMYLD) model considering wtaer supply priority. Currently, The national water resources plan applied same priority for municipal, industrial and agricultural demand. the K-WEAP model performs the ratio allocation to satisfy the maximum satisfaction rate, whereas the MODSIM model should be applied to the water supply priority of demands. As a result of applying the priority, water shortage decreased by an average of $1,035,000m^3$ than same prioritized results. It is due to the increase of the return flow rate as the distribution of Municipal and industrial water increases. Comparing the analysis results of K-WEAP and MODSIM applying the priorities, the relative error was within 5.3% and the coefficient of determination ($R^2$) was 0.9999. In addition, if both models provide reasonable water balance analysis results, K-WEAP is superior to GUI convenience for model construction and data processing. However, MODSIM is more effective in simulation time efficiency. It is expected that it will be able to carry out analysis according to various scenarios using the model.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.127-135
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• 2021

Raising large numbers of animals in very narrow environments such as laying hens house can be very damaged from small environmental change. Previously researched about laying hens sound analysis system has a problem for applying to the laying hens house because considering only the limited situation of laying hens house. In this paper, to solve the problem, we propose a new laying hens sound analysis model using MFCC feature vector. This model can detect 7 situations that occur in actual laying hens house through 9 kinds of laying hens sound analysis. As a result of the performance evaluation of the proposed laying hens sound analysis model, the average AUC was 0.93, which is about 43% higher than that of the frequency feature analysis method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.669-678
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• 2018

This study developed information technology infrastructures for building a driving environment analysis platform using various big data, such as vehicle sensing data, public data, etc. First, a small platform server with a parallel structure for big data distribution processing was developed with H/W technology. Next, programs for big data collection/storage, processing/analysis, and information visualization were developed with S/W technology. The collection S/W was developed as a collection interface using Kafka, Flume, and Sqoop. The storage S/W was developed to be divided into a Hadoop distributed file system and Cassandra DB according to the utilization of data. Processing S/W was developed for spatial unit matching and time interval interpolation/aggregation of the collected data by applying the grid index method. An analysis S/W was developed as an analytical tool based on the Zeppelin notebook for the application and evaluation of a development algorithm. Finally, Information Visualization S/W was developed as a Web GIS engine program for providing various driving environment information and visualization. As a result of the performance evaluation, the number of executors, the optimal memory capacity, and number of cores for the development server were derived, and the computation performance was superior to that of the other cloud computing.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.543-555
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• 2013

This study is to analyze effectiveness of golf skills (driving distance, rating of fairway, green in regulation, sand save ratio, recovery ratio, putting average) to average score using records of PGA, LPGA, KPGA, KLPGA. Independent variables were driving distance, rating of fairway, green in regulation, sand save ratio or recovery ratio, putting average. Dependent variable was the scoring average in this study. To analyze these variables, multi-group (PGA vs LPGA, KPGA vs KLPGA, PGA vs KPGA, LPGA vs KLPGA) path analysis was used through AMOS 18.0 program and significance level was set at 0.05. As the result, the variables that show significant differences of path coefficient between PGA model and LPGA model were driving distance and green in regulation to average score. The variables that show significant differences of path coefficient between KPGA model and KLPGA model were driving distance, recovery ratio, and putting average to average score. The variables that show significant differences of path coefficient between PGA model and KPGA model were driving distance, recovery ratio, and putting average to average score. There was not significant difference of path coefficient between LPGA model and KLPGA model.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.6
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• pp.959-972
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• 2017

In evaluation of blast-induced vibration, peak particle velocity (PPV) is generally calculated by using attenuation relation curve. Calculated velocity is compared with the value in legal requirements or the standards to determine the stability. Attenuation relation curve varies depending on frequency of test blasting, geological structure of the site and blasting condition, so it is difficult to predict accurately using such an equation. Since PPV is response value from the ground, direct evaluation of the structure is impractical. Because of such a limit, engineers tend to use the commercial numerical analysis program in evaluating the stability of the structure more accurately. However, when simulate the explosion process using existing numerical analysis program, it's never easy to accurately simulate the complex conditions (fracture, crushing, cracks and plastic deformation) around blasting hole. For simulating such a process, the range for modelling will be limited due to the maximum node count and it requires extended calculation time as well. Thus, this study is intended to simulate the elastic energy after fractured zone only, instead of simulating the complex conditions of the rock that results from the blast, and the analysis of response characteristics of the velocity depending on shape and size of the fractured zone was conducted. As a result, difference in velocity and attenuation character were calculated depending on fractured zone around the blast source appeared. Propagation of vibration tended to spread spherically as it is distanced farther from the blast source.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.99-104
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• 2021

In this paper, we propose health risk management using feature extraction and cluster analysis considering time flow. The proposed method proceeds in three steps. The first is the pre-processing and feature extraction step. It collects user's lifelog using a wearable device, removes incomplete data, errors, noise, and contradictory data, and processes missing values. Then, for feature extraction, important variables are selected through principal component analysis, and data similar to the relationship between the data are classified through correlation coefficient and covariance. In order to analyze the features extracted from the lifelog, dynamic clustering is performed through the K-means algorithm in consideration of the passage of time. The new data is clustered through the similarity distance measurement method based on the increment of the sum of squared errors. Next is to extract information about the cluster by considering the passage of time. Therefore, using the health decision-making system through feature clusters, risks able to managed through factors such as physical characteristics, lifestyle habits, disease status, health care event occurrence risk, and predictability. The performance evaluation compares the proposed method using Precision, Recall, and F-measure with the fuzzy and kernel-based clustering. As a result of the evaluation, the proposed method is excellently evaluated. Therefore, through the proposed method, it is possible to accurately predict and appropriately manage the user's potential health risk by using the similarity with the patient.