• KIPS Transactions on Software and Data Engineering
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• v.8 no.8
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• pp.317-322
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• 2019

Programming judge systems for programming training support are typically built on the Web, where the examiners uploads a programming problem, which the student reads and submits an answer to the problem. The judge system executes the submitted answer of source code to provide feedback such as pass, failure, and error messages. Students who receive the feedback except for the pass continues debugging the source code until they are judged to pass. We developed an online judge system to support programming training and analyzed answers submitted by the students and found that many of the students who were not judged to pass that test did not know exactly where they were wrong but continued to solve the problem. The current judge system generally feeds runtime error messages back to students. However, with only runtime error message, it is difficult for student who train to find the wrong part of the answer. Therefore, in this paper, we propose a system that provides the feedback of programming failure by analyzing the control flow of the test cases used in the source code submitted by the student. The proposed system helps students find the wrong parts more quickly by feeding back the paths where faults in the control flow may exist. In addition, we show that this system is applicable to the answer source code that the actual student submitted.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.140-147
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• 2019

The purpose of this study is to find biomechanical parameters for optimal shoes production through an ergonomic usability assessment of five existing types of shoes preferred by B-BOY. Ten experts and ten non-experts participated in the experiment, and 12 infrared cameras (Qualis, Oqus), force plate (Kistler, 9286AA) and foot pressure plate (Zebris Gmbh, Zebris PDM-System) were used to obtain the data. The results of the study are as follows. First, P shoes with a friction coefficient of 0.38 and a free moment of 0.32 N/m/kg are desirable in terms of traction capability and safety. Second, on the cushion, it was found that the N shoes 2.51 N, sec/kg and non-expert, and 2.86 N and sec/kg were suitable. Third, it is deemed appropriate for C shoes with a forefoot average pressure of 10.11 KPa (right), 10.05 KPa (left), and V shoes with a rearfoot average pressure of 8.4 KPa (right) and 8.36 KPa (left). In conclusion, the combination of the structure and material of V shoes should be developed for traction and stability, N shoes for cushion, and walking balance for C and V shoes.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.17-27
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• 2019

In this study, we conducted a study to predict the photovoltaic power by constructing the sensor based meteorological data observation system and the accurate terrain data obtained by using LiDAR surveying. The average sunshine hours in 2018 is 4.53 hours and the photovoltaic power is 2,305 MWh. In order to analyze the effect of photovoltaic power on the installation angle of solar modules, we installed module installation angle at $10^{\circ}$ intervals. As a result, the generation time was 4.24 hours at the module arrangement angle of $30^{\circ}$, and the daily power generation and the monthly power generation were the highest, 3.37 MWh and 102.47 MWh, respectively. Therefore, when the module arrangement angle is set to $30^{\circ}$, the generation efficiency is increased by about 4.8% compared with the module angle of $50^{\circ}$. As a result of analyzing the influence of the seasonal photovoltaic power by the installation angle of the solar module, it was found that the photovoltaic power was high in the range of $40^{\circ}{\sim}50^{\circ}$, where the module angle was large from November to February when the weather was cold. From March to October, it was found that the photovoltaic power amount is $10^{\circ}{\sim}30^{\circ}$ with small module angle.

• The Korean Journal of Applied Statistics
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• v.32 no.2
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• pp.229-263
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• 2019

The Korean fertility rate has been declining rapidly since 2000 with the fertility rate among provinces following a uniform tendency. In particular, the province-specific fertility rate is an essential tool for local governments to prepare local policies for low fertility aging policy, education and welfare policies. However, there is limitation on how to reflect different trends on the province-specific fertility rate because the KOSTAT's (2017) province-specific fertility rate projection estimates information use the national average birth rate date of vital statistics for the last 10 years (5 years). In this study, we propose an improvement plan that simultaneously considers important stable pattern maintenance and provincial fertility rate differentiation for an annual birth rate estimation. The method proposed in this study (proposal 1 and 2) can reflect birth rate changes from past to present and national and provincial differences by age that use time series data of the annual fertility rate. Proposal 3 also reflects the unique fertility rate trend from the past to the present by age according to province regardless of the relationship with the national trend. Therefore, it is preferable to use a relationship to the national rate when predicting the birth rate, as in proposals 1 and 2 because the national and the provincial fertility rate pattern are similar. These proposals show improved stability in terms of age-specific fertility rates.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.3
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• pp.279-298
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• 2019

This study comprehensively addresses recent progress at KAERI in waste treatment technology to cope with waste produced by pyroprocessing, which is used to effectively manage spent fuel. The goal of pyroprocessing waste treatment is to reduce final waste volume, fabricate durable waste forms suitable for disposal, and ensure safe packaging and storage. KAERI employs grouping of fission products recovered from process streams and immobilizes them in separate waste forms, resulting in product recycling and waste volume minimization. Novel aspects of KAERI approach include high temperature treatment of spent oxide fuel for the fabrication of feed materials for the oxide reduction process, and fission product concentration or separation from LiCl or LiCl-KCl salt streams for salt recycling and higher fission-product loading in the final waste form. Based on laboratory-scale tests, an engineering-scale process test is in progress to obtain information on the performance of scale-up processes at KAERI.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.77-83
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• 2019

With the increase in population, the number of such senior citizens is increasing day by day. These senior citizens have a variety of care needs, but there are not enough health workers to look after them. Ambient Assisted Living (AAL) aims at ensuring the safety and health quality of the older adults and extending the number of years the senior citizens can live independently in an environment of their own preference. AAL provides a system comprising of smart devices, medical sensors, wireless networks, computer and software applications for healthcare monitoring. AAL can be used for various purposes like preventing, curing, and improving wellness and health conditions of older adults. While information security and privacy are critical to providing assurance that users of AAL systems are protected, few studies take into account this feature. In this paper, we propose a secure and lightweight authentication scheme for the AAL systems. The proposed authentication scheme not only supports several important security requirements needed by the AAL systems, but can also withstand various types of attacks. Also, the security analysis results are presented to show the proposed authentication scheme is more secure and efficient rather than existing authentication schemes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.653-659
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• 2018

The accurate prediction of construction cost is a key factor in a project's success. However, it is hard to predict the construction costs in the planning stages rapidly and precisely when drawings, specifications, construction cost calculation statements are incomplete, among other factors. Accurate construction-cost prediction in the planning stage of a project is also important for project feasibility studies and successful completion. Therefore, various techniques have been applied to accurately predict construction costs at an early stage when project information is limited. There are many factors that affect the construction cost prediction. This paper presents a construction-cost prediction method as multiple regression model with seven construction factors as independent variables. The method was used to predict the construction cost of a local housing union project, and the error rate was 4.87%. It is not possible to compare the cost of the project at the planning stage of the local housing union project, but it has high prediction accuracy compared to the unit price of an existing unit area. It is likely to be applied in construction-cost calculation work and to contribute to the establishment of the budget for the local housing union project.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.2
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• pp.61-66
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• 2019

Augmented reality is a technology that makes a virtual object appear as if it exists in reality by composing a virtual object in real time with the image captured by the camera. In order to augment the virtual object on the object existing in reality, the homography of images utilized to estimate the position and orientation of the object. The homography can be estimated by applying the RANSAC algorithm to the feature points of the images. But the homography estimation method using the RANSAC algorithm has a problem that accurate homography can not be estimated when there are many feature points in the background. In this paper, we propose a method to filter feature points of a background when the object is near and the background is relatively far away. First, we classified the depth image into relatively near region and a distant region using the Otsu's method and improve homography estimation performance by filtering feature points on the relatively distant area. As a result of experiment, processing time is shortened 71.7% compared to a conventional homography estimation method, and the number of iterations of the RANSAC algorithm was reduced 69.4%, and Inlier rate was increased 16.9%.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.2
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• pp.79-88
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• 2019

Machine translation (MT) system, especially Korean-Mongolian MT system, has recently attracted much attention due to its necessary for the globalization generation. Korean and Mongolian have the same sentence structure SOV and the arbitrarily changing of their words order does not change the meaning of sentences due to postpositional particles. The particles that are attached behind words to indicate their grammatical relationship to the clause or make them more specific in meaning. Hence, the particles play an important role in the translation between Korean and Mongolian. However, one Korean particle can be translated into several Mongolian particles. This is a major issue of the Korean-Mongolian MT systems. In this paper, to address this issue, we propose a method to use the combination of UTagger and a Korean-Mongolian particles table. UTagger is a system that can analyze morphologies, tag POS, and disambiguate homographs for Korean texts. The Korean-Mongolian particles table was manually constructed for matching Korean particles with those of Mongolian. The experiment on the test set extracted from the National Institute of Korean Language's Korean-Mongolian Learner's Dictionary shows that our method achieved the accuracy of 88.38% and it improved the result of using only UTagger by 41.48%.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.3
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• pp.115-122
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• 2019

For Korean phoneme recognition, Hidden Markov-Gaussian Mixture model(HMM-GMM) or hybrid models which combine artificial neural network with HMM have been mainly used. However, current approach has limitations in that such models require force-aligned corpus training data that is manually annotated by experts. Recently, researchers used neural network based phoneme recognition model which combines recurrent neural network(RNN)-based structure with connectionist temporal classification(CTC) algorithm to overcome the problem of obtaining manually annotated training data. Yet, in terms of implementation, these RNN-based models have another difficulty in that the amount of data gets larger as the structure gets more sophisticated. This problem of large data size is particularly problematic in the Korean language, which lacks refined corpora. In this study, we introduce CTC algorithm that does not require force-alignment to create a Korean phoneme recognition model. Specifically, the phoneme recognition model is based on convolutional neural network(CNN) which requires relatively small amount of data and can be trained faster when compared to RNN based models. We present the results from two different experiments and a resulting best performing phoneme recognition model which distinguishes 49 Korean phonemes. The best performing phoneme recognition model combines CNN with 3hop Bidirectional LSTM with the final Phoneme Error Rate(PER) at 3.26. The PER is a considerable improvement compared to existing Korean phoneme recognition models that report PER ranging from 10 to 12.