• Journal of Korea Game Society
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• v.18 no.3
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• pp.61-70
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• 2018

Thanks to the 4th Industrial Revolution, interest in virtual reality increased and many improvements of VR devices were made. Among the VR devices, the simulator plays an important role in improving the real feeling of virtual presence. In this paper, we analyze the case of existing simulator and control method for efficient interlocking of motion simulator and VR contents, and classify motion control elements in VR contents into four types. Based on this preliminary study, this paper proposes a modular motion control method to help the contents and simulator work more effectively in the production of VR contents.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1241-1251
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• 2014

Based on the 4 principal research-performance criteria in 28 national universities in Korea, both cluster analysis and multidimensional scaling are performed in this paper. We can classify and/or specialize the initially unknown groups into a group of relatively homogeneous universities and then create new groupings without any preconceived notion of what clusters may arise. Furthermore, the level of similarity of individual universities can be visualized on the multidimensional space so that each university is then assigned coordinates in each of the 2 dimensions. Both types and characteristics of each university can be relatively evaluated and be practically exploited for the policy of the university authority through these results.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.426-426
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• 2023

대설은 일반적으로 해양과 대륙의 온도차가 큰 지역, 바다·호수와 같이 상대적으로 따뜻한 곳이 인접해 있어 기단 변질이 잘 일어나는 지역, 산악에 의해 습윤한 공기가 강제 상승되는 지역에서 자주 발생한다. 우리나라는 찬 대륙고기압 공기가 해수 온도 차로 눈 구름대가 만들어지거나, 고기압 가장자리에서 한기를 동반한 상층 기압골이 우리나라 상공을 통과하면서 대설이 발생한다. 최근 우리나라에서 빈번하게 발생하는 대설피해는 직접피해와 간접피해로 나뉘며, 이에 따라 사회·경제적으로 막대한 피해를 야기한다. 우리나라 대설피해양상은 지역적 특성, 방재 대책, 대처능력 등에 따라 달라지는 것이 특징이며, 지역적으로 다르게 발생하는 대설피해를 효과적으로 대비할 수 있는 연구가 필요하다. 따라서 본 연구에서는 지역적 특성을 고려한 차등화된 대설 피해를 예측하는 연구를 진행하고자 하였다. 본 연구에서는 기상요소 및 사회·경제적 요소 등을 입력자료로 활용하고, DPSIR 분석을 통해 Red Zone, Orange Zone, Yellow Zone, Green Zone으로 위험 등급을 분류 및 등급 별 대설피해 예측기법을 개발하였다. 최종적으로 1994년부터 2020년까지의 과거 대설 피해액 자료와 다중회귀분석을 이용하여 기법을 개발하였고, 기법의 예측력 평가를 위해 RMSE와 RMSE를 표준화한 NRMSE의 두 가지 통계 지표를 사용하여 평가하였다. 모형별 예측력 평가 결과 Yellow 등급 모형이 가장 우수한 예측력을 보였다. 추후 본 연구결과를 통해 대설피해 범위를 예측하는 연구가 진행된다면 사전에 대설피해에 대한 대응방안 수립과 지역별제설 우선순위를 결정할 수 있는 지표가 개발될 것으로 기대된다.

• Journal of Hospice and Palliative Care
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• v.12 no.2
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• pp.80-87
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• 2009

Purpose: The purposes of this study were to identify the types of widow's bereavement experience and understand the nature of it's bereavement by using Q-methodological approach. Methods: Contents Q sample included 46 statements obtained from literatures and interviews with 5 widows. P sample consisted of 13 widows who bereaved within 2 years. The data were collected from October 2004 to December 2006 and analyzed using Quanal program. Results: Two types of widow's experience were found. Type 1 was characterized by loss suffering, and type 2 was characterized by acceptance and adaptation Conclusion: Widows were found to experience different types of bereavement. Therefore, bereavement care team should assess the types of suffering pain and provide appropriate care to the widows. Also, need to be developed programs to relieve or prevent suffering of bereavement.

• Korean Journal of Microbiology
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• v.44 no.4
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• pp.352-357
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• 2008

We evaluated cultivation methods to obtain pure cultures of previously uncultivated bacteria from soil. Soil bacteria (suspensions) were inoculated onto various oligotrophic media with one of the following additives: 1) soil extract; 2) anthraquinone disulfonate (humic acid analogue); 3) acyl homoserine lactones (quorum-signaling compounds); 4) catalase (for the protection of bacteria from exogenous peroxides). After the relatively long period (60 days) of incubation with elevated concentrations of $CO_2$ (5%, v/v), the media containing catalase showed the highest colony count. We purified 147 randomly selected colonies from the media and the isolates were subjected to the phylogenetic analyses of their 16S rRNA gene sequences. Phylogenetic analysis revealed that approximately 30% of the isolates might belong to novel species or novel family, suggesting that the media and incubation conditions used could be useful for the cultivation of as-yet-uncultured bacteria. Especially, bacteria belonging to the phylum Acidobacteria, ubiquitous bacterial taxon known as an uncultured bacterial group (at least difficult to culture from environmental samples), were successfully cultured in this study.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.91-117
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• 2022

The number of depressed patients in Korea and around the world is rapidly increasing every year. However, most of the mentally ill patients are not aware that they are suffering from the disease, so adequate treatment is not being performed. If depressive symptoms are neglected, it can lead to suicide, anxiety, and other psychological problems. Therefore, early detection and treatment of depression are very important in improving mental health. To improve this problem, this study presented a deep learning-based depression tendency model using Korean social media text. After collecting data from Naver KonwledgeiN, Naver Blog, Hidoc, and Twitter, DSM-5 major depressive disorder diagnosis criteria were used to classify and annotate classes according to the number of depressive symptoms. Afterwards, TF-IDF analysis and simultaneous word analysis were performed to examine the characteristics of each class of the corpus constructed. In addition, word embedding, dictionary-based sentiment analysis, and LDA topic modeling were performed to generate a depression tendency classification model using various text features. Through this, the embedded text, sentiment score, and topic number for each document were calculated and used as text features. As a result, it was confirmed that the highest accuracy rate of 83.28% was achieved when the depression tendency was classified based on the KorBERT algorithm by combining both the emotional score and the topic of the document with the embedded text. This study establishes a classification model for Korean depression trends with improved performance using various text features, and detects potential depressive patients early among Korean online community users, enabling rapid treatment and prevention, thereby enabling the mental health of Korean society. It is significant in that it can help in promotion.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.91-101
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• 2001

It has been shown that the multiple trees predictors are more accurate in reducing test set error than a single tree predictor. There are two ways of generating multiple trees. One is to generate modified training sets by resampling the original training set, and then construct trees. It is known that arcing algorithm is efficient. The other is to perturb randomly the working split at each node from a list of best splits, which is expected to generate reasonably good trees for the original training set. We propose a new combined multiple regression trees predictor which uses the latter multiple regression tree predictor as a predictor based on a modified training set at each stage of arcing. The efficiency of those prediction methods are compared by applying to high throughput screening of chemical compounds for biological effects.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.3
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• pp.303-309
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• 2011

Situation awareness services which increasingly expand their influence in everyday life can be classified into location-based service and social network service. Their quality of service (QoS) can be differed based on the location accuracy of smart phones and accuracy of directional recognition technology. This study was conducted to analyze GPS, digital compass, radio communication, and geospatial web information which can provide a clue in using the situation aware services based on lab experiments and surveys. According to the result of lab experiment on accuracy of determining location / direction with smart phones, owing to inherent lack of indoor accuracy in determining position and direction, as well as errors in spatial data used as platform, it was found that devices were not provided with sufficiently accurate data when using the situation aware services indoors compared to outdoors. To enhance accuracy of determining indoor positions, there are several methods including location metering based on Wi-Fi, which had several problems compared with GPS used in outdoor environment. Thus, it was determined that more study would be necessary to solve these issues.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.945-956
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• 2013

The character industry is a high value-added industry, and is one of the strategic industries to be fostered. However, the character industry is struggling due to the lack of national consensus on the importance and value of the character industry. Therefore, in order to resolve this issue, the study used the character Input-Output Table of year 2009 of korea to analyze how much the character industry(Toys and games, Models and decorations) contributes to the national economy by measuring economic spreading effects of character industry on national economy. The results shows that character industry shows that production inducement coefficient is column 1.602, row 1.007, index of the sensitivity of dispersion is 0.543, Index of the power of dispersion is 0.864, value-added coefficient is 0.620, income inducement coefficient is 0.334, tax inducement coefficient is 0.066, employment inducement coefficient is 0.008.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.963-967
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• 2009

The Log-structured File System (LFS) collects all modified data into a memory buffer and writes them sequentially to a segment on disk. Therefore, it has the potential to utilize the maximum bandwidth of storage devices where sequential writes are much faster than random writes. However, as disk space is finite, LFS has to conduct cleaning to produce free segments. This cleaning operation is the main reason LFS performance deteriorates when file system utilization is high. To overcome painful cleaning and reduced performance of LFS, we propose the segment space recycling (SSR) scheme that directly writes modified data to invalid areas of the segments and describe the classification method of data and segment to consider locality of reference for optimizing SSR scheme. We implement U-LFS, which employs our segment space recycling scheme in LFS, and experimental results show that SSR scheme increases performance of WOLF by up to 1.9 times in HDD and 1.6 times in SSD when file system utilization is high.