• Tunnel and Underground Space
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• v.31 no.6
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• pp.440-459
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• 2021

Roadheaders have begun to be adopted in Korean tunneling sites. The performance prediction models proposed by the manufacturer are used by Korean construction companies. The models use UCS (uniaxial compressive strength) value to predict the net cutting rate, but the rock specimens conducted for the uniaxial compression test have 1.0 of the diameter to length ratio. It has been reported that the specimen shape generally influences the rock strength. The previous references studying the shape effect were cited, and the UCS data of Korean rocks are also updated to analyze the shape effect on UCS. The cause of effect was discussed by previous theory. The change amount of UCS values of Korean rocks was estimated by the data, and the modified prediction model for NCR was finally suggested.

• Journal of Intelligence and Information Systems
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• v.10 no.1
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• pp.77-91
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• 2004

This research compares the use of accounting data versus market data in the prediction of bankruptcy. Comparison is made through neural networks so that prediction accuracy is model-independent. Results of this study indicate that both market and accounting data provide useful information on corporate bankruptcies. Interestingly, using market and accounting information together can achieve substantial gain in prediction accuracy.

• Annual Conference of KIPS
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• 2022.05a
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• pp.401-404
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• 2022

한국 문학이 세계로 뻗어나감에 따라 해외 시장에서 자리를 잡는 것이 중요해진 시점이다. 본 연구에서는 2016 년도부터 2020 년도까지 최근 5 년간 해외 출간된 도서들 중에서 굿셀러로 분류되는 누적 5 천부 이상 판매 여부를 예측하고자 했다. 굿셀러로 분류되는 도서는 전체 번역 도서 중 적은 비율을 차지하여 데이터 불균형이 발생하였으며, 본 연구에서는 SMOTE 기법과 앙상블 알고리즘을 적용하여 데이터 불균형 문제를 해결하였다. 그 결과, 데이터 클래스 비율이 1:1 에 가까울수록 성능 개선 효과가 나타났으며 LightGBM 모델이 99.83%의 AUC 값을 얻어 다른 앙상블 알고리즘에 비해 가장 좋은 예측 성능을 보임을 검증하였다. 또한 누적 5 천부 이상 판매 여부 예측에 있어 큰 영향을 미치는 변수로는 작가가 가장 중요한 요인으로 나타났으며 출간 국가, 그리고 평점 평균, 평점 참여자 수 같은 온라인 요인도 판매 예측에 유의미한 변수로 나타난 것을 확인할 수 있었다.

• Journal of the Korea Concrete Institute
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• v.19 no.1
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• pp.121-130
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• 2007

To investigate the enhancement in strength and deformation capacities of concrete confined by FRP composites, tests under axial loads were carried out on three groups of thirty six short columns in circular section with diverse GFRP confining reinforcement. The major test variables considered include fiber content or orientation, wrap or tube type by varying the end loading condition, and continuous or discontinuous confinement depending on the presence of vortical spices between its two halves. The circumferential FRP strains at failure for different types of confinements were also investigated with emphasis. Various analytical models capable of predicting the ultimate strength and strain of the confined concrete were examined by comparing to observed results. Tests results showed that FRP wraps or tubes provide the substantial increase in strength and deformation, while partial wraps comprising the vertical discontinuities fail in an explosive manner with less increase in strength, particularly in deformation. A bilinear stress-strain response was observed throughout all tests with some variations of strain hardening. The failure hoop strains measured on the FRP surface were less than those obtained from the tensile coupons in all tests with a high degree of variation. In overall, existing predictive equations overestimated ultimate strengths and strains observed in present tests, with a much larger scatter related to the latter. For more accuracy, two simple design- oriented equations correlated with present tests are proposed. The strength equation was derived using the Mohr-Coulomb failure criterion, whereas the strain equation was based on entirely fitting of test data including the unconfined concrete strength as one of governing factors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.384-390
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• 2020

Purpose: Organophosphate insecticide poisoning can have clinically fatal results. This study aimed to evaluate the relationship between the neutrophil/lymphocyte ratio (NLR) and the occurrence of death in patients with organophosphate insecticide poisoning. Methods: For this retrospective study, data on patients with organophosphate insecticide poisoning who visited the emergency room between January 2008 and November 2018 were collected. The NLR was measured at the time of arrival in the emergency room. The patients were divided into survival and death groups. Results: Overall, 150 patients were enrolled: 15 (10%) in the death group and 135 (90%) in the survival group. In the univariate analysis, the following variables were significantly different between the two groups: age, white blood cell count, amylase level, creatinine level, Acute Physiology And Chronic Health Evaluation (APACHE) II score, and NLR. In the logistic regression analysis of variables with significant differences in the univariate analysis, there were significant differences between the two groups with respect to age, APACHE II score, and NLR. The NLR was significantly higher in the death group than in the survival group (20.83 ± 22.24 vs. 7.38 ± 6.06, p=0.036). Conclusion: High NLR in patients with organophosphate insecticide poisoning may be useful in predicting mortality.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.3
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• pp.133-140
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• 2023

The performance of lithium ion batteries depends on the usage environment and the combination ratio of cathode materials. In order to develop a high-performance lithium-ion battery, it is necessary to manufacture the battery and measure its performance while varying the cathode material ratio. However, it takes a lot of time and money to directly develop batteries and measure their performance for all combinations of variables. Therefore, research to predict the performance of a battery using an artificial intelligence model has been actively conducted. However, since measurement experiments were conducted with the same battery in the existing published battery data, the cathode material combination ratio was fixed and was not included as a data attribute. In this paper, we define a training data model required to develop an artificial intelligence model that can predict battery performance according to the combination ratio of cathode materials. We analyzed the factors that can affect the performance of lithium-ion batteries and defined the mass of each cathode material and battery usage environment (cycle, current, temperature, time) as input data and the battery power and capacity as target data. In the battery data in different experimental environments, each battery data maintained a unique pattern, and the battery classification model showed that each battery was classified with an error of about 2%.

• The Journal of Bigdata
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• v.3 no.2
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• pp.101-112
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• 2018

The purpose of the study is to predict the number of police calls using neural network which is one of the machine learning and negative binomial regression, by using the data of 112 police calls received from Chungnam Provincial Police Agency from June 2016 to May 2017. The variables which may affect the police calls have been selected for developing the prediction model : time, holiday, the day before holiday, season, temperature, precipitation, wind speed, jurisdictional area, population, the number of foreigners, single house rate and other house rate. Some variables show positive correlation, and others negative one. The comparison of the methods can be summarized as follows. Neural network has correlation coefficient of 0.7702 between predicted and actual values with RMSE 2.557. Negative binomial regression on the other hand shows correlation coefficient of 0.7158 with RMSE 2.831. Neural network has low interpretability, but an excellent predictability compared with the negative binomial regression. Based on the prediction model, the police agency can do the optimal manpower allocation for given values in the selected variables.

• 한국HCI학회:학술대회논문집
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• 2007.02b
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• pp.1-6
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• 2007

최근 다양한 기기와 환경에서 문자 입력에 대한 요구가 높아지고 있다. 이에 따라 효율적인 문자 입력 인터페이스 설계를 위해 문자 입력 인터페이스의 평가가 필요한 실정이다. 기존 연구를 살펴보면 문자 입력 시간을 시각 탐색 시간과 손가락 이동 시간으로 나누고 정보처리 이론인 Hick-Hyman Law와 Fitts’ Law를 통해 예측, 평가 하였다. 하지만 위 두 과정은 연속적(serial)인 과정으로 눈과 손의 coordination(협응)에 대해 관과 하는 한계가 있다. 또한, 기존 문자 입력 시간 예측 모델은 전문가라는 특정 숙련도를 가정하고 만들어졌기 때문에 실제 문자 입력 시간에 비해 과대 측정되어 왔다. 이에 본 연구는 문자 입력 시간 예측 모델에 눈-손 coordination 매개변수를 삽입하고자 눈-손 coordination의 시간을 측정하고 행태를 분석하였다. 또한, 비숙련자와 숙련자의 구분을 통해 시각 탐색 시간과 손 움직임 시간 그리고 눈-손 coordination의 시간 과 행태가 어떻게 변화하는 지 분석하였다. 그 결과 눈-손 coordination 시간은 문자 입력 시간과 밀접한 관계가 있었다, 그리고, 눈-손 coordination 시간은 숙련도에 상관없이 문자 입력 시간의 22%를 차지하였다. 또한, 숙련자와 비숙련자의 문자 입력 시간과 비교해 손과 coordination 시간 비율은 차이가 없었다. 하지만, 눈의 움직임 시간 비율은 큰 차이를 나타내었다. 이 결과는 눈-손 coordination과 숙련도 차이를 기존 문자 입력 예측 모델에 매개변수로써 적용하기 위한 기초 자료가 될 것이다.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.1-6
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• 2018

In this paper, we propose the method to eliminate repetitive processes for key-point detection on multi-scale image space. The proposed method detects key-points from the original image, and select a good key-points using the cluster filters, and create the key-point clusters. And it select reference objects by using direction angles of the key-point clusters, predict the scale of the original image by using the distributed distance ratio. It transform the scale of the reference image, and apply the detection of key-points to the transformed reference image. In the results of the experiment, the proposed method can be found to improve the key-points detection time by 75 % and 71 % compared to SIFT method and scaled ORB method using the multi-scale images.

• Korea Journal of Geothermal Energy
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• v.6 no.4
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• pp.13-18
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• 2010