• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.11
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• pp.927-933
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• 2020

This paper presents a fuel quantity measurement system (FQMS) for an aircraft supplementary fuel tank considering the change of aircraft attitude. The developed FQMS consists of fuel sensors, a signal process unit, an indicator and a software to estimate the fuel quantity from the sensor data. To replicate the change of the roll and pitch attitude on the ground, the test simulator is developed in this work. Using the test simulator, the sensor data at various fuel quantities, roll and pitch angles are automatically measured to build a training data set. The data-driven software to estimate the fuel quantity is then developed using a trilinear interpolation method with the training data set. The developed FQMS is verified by investigating the fuel estimation error of the test data set that we know the true values. Through the test, it is confirmed that the error of the developed FQMS system satisfies the criteria of TSO-C55 document.

• Journal of Radiation Protection and Research
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• v.46 no.4
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• pp.204-212
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• 2021

Background: Identification of radioisotopes for plastic scintillation detectors is challenging because their spectra have poor energy resolutions and lack photo peaks. To overcome this weakness, many researchers have conducted radioisotope identification studies using machine learning algorithms; however, the effect of data normalization on radioisotope identification has not been addressed yet. Furthermore, studies on machine learning-based radioisotope identifiers for plastic scintillation detectors are limited. Materials and Methods: In this study, machine learning-based radioisotope identifiers were implemented, and their performances according to data normalization methods were compared. Eight classes of radioisotopes consisting of combinations of ²²Na, ⁶⁰Co, and ¹³⁷Cs, and the background, were defined. The training set was generated by the random sampling technique based on probabilistic density functions acquired by experiments and simulations, and test set was acquired by experiments. Support vector machine (SVM), artificial neural network (ANN), and convolutional neural network (CNN) were implemented as radioisotope identifiers with six data normalization methods, and trained using the generated training set. Results and Discussion: The implemented identifiers were evaluated by test sets acquired by experiments with and without gain shifts to confirm the robustness of the identifiers against the gain shift effect. Among the three machine learning-based radioisotope identifiers, prediction accuracy followed the order SVM > ANN > CNN, while the training time followed the order SVM > ANN > CNN. Conclusion: The prediction accuracy for the combined test sets was highest with the SVM. The CNN exhibited a minimum variation in prediction accuracy for each class, even though it had the lowest prediction accuracy for the combined test sets among three identifiers. The SVM exhibited the highest prediction accuracy for the combined test sets, and its training time was the shortest among three identifiers.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.10 no.2
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• pp.7-12
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• 2014

Government has recently restricted heating and cooling set temperatures for the commercial and public buildings due to increasing national energy consumption. The goal of this paper is to visualize a future two way indoor set temperature control impact on building energy consumption by using TRNSYS simulation modeling. The building was modelled based on the twin test cell with the same dimension. Air source ground coupled heat pump performance data has been used for modeling by TRNSYS 17. Daejeon weather data has been used from Korea Solar Energy Society. The heating set temperature in the reference room is $24^{\circ}C$ as well as the target room set temperature are $23^{\circ}C$, $22^{\circ}C$, $21^{\circ}C$ and $20^{\circ}C$. The cooling set temperature of the reference room is also $24^{\circ}C$ as well as the target room set temperature of $25^{\circ}C$, $26^{\circ}C$, $27^{\circ}C$ and $28^{\circ}C$. For the air source heat pump system, heating season energy consumption is $35.52kWh/m^2y$ in the reference room. But the heating energy consumption in the target room is reduced to 7.5% whenever the set temperature decreased every $1^{\circ}C$. The cooling energy consumption in the reference room is $4.57kWh/m^2y$. On the other hand, the energy consumption in the target room is reduced to 22% whenever the set temperature increased every $1^{\circ}C$ by two way controller. For the geothermal heat pump system, heating energy consumption in the reference room is reduced to 20.7%. The target room heating energy consumption is reduced to 32.6% when the set temperature is $22^{\circ}C$. The energy consumption in the target room is reduced to 59.5% when the set temperature is $26^{\circ}C$.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.239-249
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• 2020

Rice flour varieties have been developed to replace wheat, and consumption of rice flour has been encouraged. damage related to pre-harvest sprouting was occurring due to a weather disaster during the ripening period. Thus, it is necessary to develop pre-harvest sprouting rate prediction system to minimize damage for pre-harvest sprouting. Rice cultivation experiments from 20 17 to 20 19 were conducted with three rice flour varieties at six regions in Gangwon-do, Chungcheongbuk-do, and Gyeongsangbuk-do. Survey components were the heading date and pre-harvest sprouting at the harvest date. The weather data were collected daily mean temperature, relative humidity, and rainfall using Automated Synoptic Observing System (ASOS) with the same region name. Gradient Boosting Machine (GBM) which is a machine learning model, was used to predict the pre-harvest sprouting rate, and the training input variables were mean temperature, relative humidity, and total rainfall. Also, the experiment for the period from days after the heading date (DAH) to the subsequent period (DA2H) was conducted to establish the period related to pre-harvest sprouting. The data were divided into training-set and vali-set for calibration of period related to pre-harvest sprouting, and test-set for validation. The result for training-set and vali-set showed the highest score for a period of 22 DAH and 24 DA2H. The result for test-set tended to overpredict pre-harvest sprouting rate on a section smaller than 3.0 %. However, the result showed a high prediction performance (R2=0.76). Therefore, it is expected that the pre-harvest sprouting rate could be able to easily predict with weather components for a specific period using machine learning.

• Journal of Korean language education
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• v.28 no.3
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• pp.1-24
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• 2017

This article explores the developmental history of TOPIK over the last 20 years and its recent trends. Over the last two decades, TOPIK underwent two major systematic reforms, achieving both quantitative and qualitative growth over the course of its 52 testing sessions. TOPIK has utilized a six-level evaluation system from its inception to the present. The evaluation system was amended from the earlier six-test set - whereby each level corresponded with a separate test (1997~2005: the $1^{st}{\sim}9^{th}$) - to the three-test set (2006~2014: the $10^{th}{\sim}34^{th}$), and finally to the two-test set (2014~present: the $35^{th}{\sim}42^{nd}$). In the earlier exams, abilities in Vocabulary Grammar, Writing, Listening, and Reading were assessed. However, beginning with the $35^{th}$ TOPIK, abilities in Listening, Reading, and Writing (only in TOPIK II) were assessed and the evaluation of the writing section was changed to a task-based process, improving TOPIK into a more qualified analysis of proficiency. Over the last 20 years, the number of countries TOPIK is administered in has greatly increased from 4 to 73 countries, and the annual number of test-takers has also significantly increased from 2,692 to 250,141. The distribution of proficiency levels of the test-takers has shifted over time - initially "Beginner>Intermediate>Advanced" in the earlier exams, to "Intermediate>Advanced>Beginner" after the mid 2000s - as the number of those studying the Korean language for specific purposes and continuing education increased. Test-takers have indicated a shift in their purpose for taking the exam, initially citing "to assess proficiency" and more recently selecting "to study abroad," and this could also correlate with changes in the proportion of test-takers' proficiency level. In general, 85~95% of beginner, 50~65% of intermediate, and 45~60% of advanced test applicants passed the respective proficiency level. To date, no practices have yet been implemented to standardize the difficulty level longitudinally across test sets.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.411-416
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• 1998

A simple nonparametric test of complete or total independence is suggested for continuous multivariate distributions. This procedure first discretizes the original variables based on their order statistics, and then tests the hypothesis of complete independence for the resulting contingency table. Under the hypothesis of independence, the chi-squared test statistic has an asymptotic chi-squared distribution. We present a simulation study to illustrate the accuracy in finite samples of the limiting distribution of the test statistic. We compare our method to another nonparametric test of complete independence via a simulation study. Finally, we apply our method to the residuals from a real data set.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.129-139
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• 2004

We consider the problem of testing for outliers in generalized linear model. We proceed by first specifying a mean shift outlier model, assuming the suspect set of ourliers is known. Given this model, we discuss standard approaches to obtaining score test for outliers as an alternative to the likelihood ratio test.

• Journal of Computing Science and Engineering
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• v.3 no.3
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• pp.165-180
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• 2009

The HKIB, or Hankookilbo, test collections are two archives of Korean newswire stories manually categorized with semi-hierarchical or hierarchical category taxonomies. The base newswire stories were made available by the Hankook Ilbo (The Korea Daily) for research purposes. At first, Chungnam National University and KISTI collaborated to manually tag 40,075 news stories with categories by semi-hierarchical and balanced three-level classification scheme, where each news story has only one level-3 category (single-labeling). We refer to this original data set as HKIB-40075 test collection. And then Yonsei University and KISTI collaborated to select 20,000 newswire stories from the HKIB-40075 test collection, to rearrange the classification scheme to be fully hierarchical but unbalanced, and to assign one or more categories to each news story (multi-labeling). We refer to this modified data set as HKIB-20000 test collection. We benchmark a k-NN categorization algorithm both on HKIB-20000 and on HKIB-40075, illustrating properties of the collections, providing baseline results for future studies, and suggesting new directions for further research on Korean text categorization problem.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1089-1102
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• 2017

In software systems, it has been observed that a fault is often caused by an interaction between a small number of input parameters. Even for moderately sized software systems, exhaustive testing is practically impossible to achieve. This is either due to time or cost constraints. Combinatorial (t-way) testing provides a technique to select a subset of exhaustive test cases covering all of the t-way interactions, without much of a loss to the fault detection capability. In this paper, an approach is proposed to generate 2-way (pairwise) test sets using genetic algorithms. The performance of the algorithm is improved by creating an initial solution using the overlap coefficient (a similarity matrix). Two mutation strategies have also been modified to improve their efficiency. Furthermore, the mutation operator is improved by using a combination of three mutation strategies. A comparative survey of the techniques to generate t-way test sets using genetic algorithms was also conducted. It has been shown experimentally that the proposed approach generates faster results by achieving higher percentage coverage in a fewer number of generations. Additionally, the size of the mixed covering arrays was reduced in one of the six benchmark problems examined.

• Journal of Korean language education
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• v.28 no.1
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• pp.221-250
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• 2017

This study aims to discuss the basic foundations to set levels and language skills for developing a Korean Proficiency Test for young and adolescent learners. Recently, there has been an increase in demand regarding young and adolescent learners from multicultural and overseas backgrounds. However, the current Korean Proficiency Test lacks the appropriate means to determine the Korean proficiency of young and adolescent learners with general purposes of language learning. Therefore, there is an urgent need for developing a specialized and new form of language assessment for young and adolescent learners who are exposed to a foreign language or a second language learning environment. The study examines and analyzes cases of foreign language examinations for young & adolescent learners; furthermore, the objectives and target were set based on the results of a needs analysis and in-depth interviews conducted among teachers and education officials in overseas Korean Hangeul Schools, international schools, elementary and secondary schools. Finally, the levels and language skills appropriate for the objectives of a proficiency test and target learners have been suggested.