• Journal of Korean Neurosurgical Society
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• v.59 no.4
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• pp.346-351
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• 2016

Objective : Early progressive infarction (EPI) is frequently observed and related to poor functional outcome in patients with middle cerebral artery (MCA) infarction caused by MCA occlusion. We evaluated the perfusion parameters of magnetic resonance imaging (MRI) as a predictor of EPI. Methods : We retrospectively analyzed patients with acute MCA territory infarction caused by MCA occlusion. EPI was defined as a National Institutes of Health Stroke Scale increment ${\geq}2$ points during 24 hours despite receiving standard treatment. Regional parameter ratios, such as cerebral blood flow and volume (rCBV) ratio (ipsilateral value/contralateral value) on perfusion MRI were analyzed to investigate the association with EPI. Results : Sixty-four patients were enrolled in total. EPI was present in 18 (28%) subjects and all EPI occurred within 3 days after hospitalization. Diabetes mellitus, rCBV ratio and regional time to peak (rTTP) ratio showed statically significant differences in both groups. Multi-variate analysis indicated that history of diabetes mellitus [odds ratio (OR), 6.13; 95% confidence interval (CI), 1.55-24.24] and a low rCBV ratio (rCBV, <0.85; OR, 6.57; 95% CI, 1.4-30.27) was significantly correlated with EPI. Conclusion : The incidence of EPI is considerable in patients with acute MCA territory infarction caused by MCA occlusion. We suggest that rCBV ratio is a useful neuro-imaging parameter to predict EPI.

• Atmosphere
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• v.20 no.2
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• pp.73-89
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• 2010

An updateable model output statistics (UMOS) system for daily maximum and minimum temperature ($T_M$ and $T_m$) over South Korea based on the Canadian UMOS system were developed and validated. RDAPS (regional data assimilation and prediction system) and KWRF (Korea WRF) which have quite different physics and dynamics were used for the development of UMOS system. The 20 most frequently selected potential predictors for each season, station, and forecast projection time from the 68 potential predictors of the MOS system, were used as potential predictors of the UMOS system. The UMOS equations were developed through the weighted blending of the new and old model data, with weights chosen to emphasize the new model data while including enough old model data to ensure stable equations and a smooth transition of dependency from the old model to the new model. The UMOS equations are being updated by every 7 days. The validation results of $T_M$ and $T_m$ showed that seasonal mean bias, RMSE, and correlation coefficients for the total forecast projection times are -0.41-0.17 K, 1.80-2.46 K, and 0.80-0.97, respectively. The performance is slightly better in autumn and winter than in spring and summer. Also the performance of UMOS system are clearly dependent on location, better at the coastal region than inland area. As in the MOS system, the performance of UMOS system is degraded as the forecast day increases.

• Safety and Health at Work
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• v.8 no.1
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• pp.105-115
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• 2017

Background: The goal of this study is to develop a general population job-exposure matrix (GPJEM) on asbestos to estimate occupational asbestos exposure levels in the Republic of Korea. Methods: Three Korean domestic quantitative exposure datasets collected from 1984 to 2008 were used to build the GPJEM. Exposure groups in collected data were reclassified based on the current Korean Standard Industrial Classification ($9^{th}$ edition) and the Korean Standard Classification of Occupations code ($6^{th}$ edition) that is in accordance to international standards. All of the exposure levels were expressed by weighted arithmetic mean (WAM) and minimum and maximum concentrations. Results: Based on the established GPJEM, the 112 exposure groups could be reclassified into 86 industries and 74 occupations. In the 1980s, the highest exposure levels were estimated in "knitting and weaving machine operators" with a WAM concentration of 7.48 fibers/mL (f/mL); in the 1990s, "plastic products production machine operators" with 5.12 f/mL, and in the 2000s "detergents production machine operators" handling talc containing asbestos with 2.45 f/mL. Of the 112 exposure groups, 44 groups had higher WAM concentrations than the Korean occupational exposure limit of 0.1 f/mL. Conclusion: The newly constructed GPJEM which is generated from actual domestic quantitative exposure data could be useful in evaluating historical exposure levels to asbestos and could contribute to improved prediction of asbestos-related diseases among Koreans.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.1
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• pp.37-43
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• 2001

Crop status monitoring and yield prediction at higher spatial resolution is a valuable tool in various decision making processes including agricultural policy making by the national and local governments. A prototype crop forecasting system was developed to project the size of rice crop across geographic areas nationwide, based on daily weather pattern. The system consists of crop models and the input data for 1,455 cultivation zone units (the smallest administrative unit of local government in South Korea called "Myun") making up the coterminous South Korea. CERES-rice, a rice crop growth simulation model, was tuned to have genetic characteristics pertinent to domestic cultivars. Daily maximum/minimum temperature, solar radiation, and precipitation surface on 1km by 1km grid spacing were prepared by a spatial interpolation of 63 point observations from the Korea Meteorological Administration network. Spatial mean weather data were derived for each Myun and transformed to the model input format. Soil characteristics and management information at each Myun were available from the Rural Development Administration. The system was applied to the forecasting of national rice production for the recent 3 years (1997 to 1999). The model was run with the past weather data as of September 15 each year, which is about a month earlier than the actual harvest date. Simulated yields of 1,455 Myuns were grouped into 162 counties by acreage-weighted summation to enable the validation, since the official production statistics from the Ministry of Agriculture and Forestry is on the county basis. Forecast yields were less sensitive to the changes in annual climate than the reported yields and there was a relatively weak correlation between the forecast and the reported yields. However, the projected size of rice crop at each county, which was obtained by multiplication of the mean yield with the acreage, was close to the reported production with the $r^2$ values higher than 0.97 in all three years.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.6
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• pp.2805-2810
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• 2016

Background: Differentiated thyroid cancer is the most common endocrine malignancy with a generally good prognosis. Knowing long-term outcomes of each patient helps management planning. The study was conducted to develop and validate a clinical prognostic score for predicting disease remission in patients with differentiated thyroid cancer based on patient, tumor and treatment factors. Materials and Methods: A retrospective cohort study of 1,217 differentiated thyroid cancer patients from two tertiary-care hospitals in the Northeast of Thailand was performed. Associations between potential clinical prognostic factors and remission were tested by Cox proportional-hazards analysis in 852 patients (development cohort). The prediction score was created by summation of score points weighted from regression coefficients of independent prognostic factors. Risks of disease remission were estimated and the derived score was then validated in the remaining 365 patients (validation cohort). Results: During the median follow-up time of 58 months, 648 (76.1%) patients in the development cohort had disease remission. Five independent prognostic factors were identified with corresponding score points: duration from thyroid surgery to $^{131}I$ treatment (0.721), distant metastasis at initial diagnosis (0.801), postoperative serum thyroglobulin level (0.535), anti-thyroglobulin antibodies positivity (0.546), and adequacy of serum TSH suppression (0.293). The total risk score for each patient was calculated and three categories of remission probability were proposed: ${\leq}1.628$ points (low risk, 83% remission), 1.629-1.816 points (intermediate risk, 87% remission), and ${\geq}1.817$ points (high risk, 93% remission). The concordance (C-index) was 0.761 (95% CI 0.754-0.767). Conclusions: The clinical prognostic scoring model developed to quantify the probability of disease remission can serve as a useful tool in personalized decision making regarding treatment in differentiated thyroid cancer patients.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10a
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• pp.53-58
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• 2006

MicroRNA (miRNA)는 약 22 nt의 작은 RNA 조각으로 이루어져 있으며 stem-loop 구조의 precursor 형태에서 최종적으로 만들어 진다. miRNA는 mRNA의 3‘UTR에 상보적으로 결합하여 유전자의 발현을 억제하거나 mRNA의 분해를 촉진한다. miRNA를 동정하기 위한 실험적인 방법은 조직 특이적인 발현, 적은 발현양 때문에 방법상 한계를 가지고 있다. 이러한 한계는 컴퓨터를 이용한 방법으로 어느 정도 해결될 수 있다. 하지만 miRNA의 서열상의 낮은 보존성은 homology를 기반으로 한 예측을 어렵게 한다. 또한 기계학습 방법인 support vector machine (SVM) 이나 naive bayes가 적용되었지만, 생물학적인 의미를 해석할 수 있는 generative model을 제시해 주지 못했다. 본 연구에서는 우수한 miRNA 예측을 보일 뿐만 아니라 학습된 모델로부터 생물학적인 지식을 얻을 수 있는 Bayesian network을 적용한다. 이를 위해서는 생물학적으로 의미 있는 특질들의 선택이 중요하다. 여기서는 position weighted matrix (PWM)과 Markov chain probability (MCP), Loop 크기, Bulge 수, spectrum, free energy profile 등을 특질로서 선택한 후 Information gain의 특질 선택법을 통해 예측에 기여도가 높은 특질 25개 와 27개를 최종적으로 선택하였다. 이로부터 Bayesian network을 학습한 후 miRNA의 예측 성능을 10 fold cross-validation으로 확인하였다. 그 결과 pre-/mature miRNA 각 각에 대한 예측 accuracy가 99.99% 100.00%를 보여, SVM이나 naive bayes 방법보다 높은 결과를 보였으며, 학습된 Bayesian network으로부터 이전 연구 결과와 일치하는 pre-miRNA 상의 의존관계를 분석할 수 있었다.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.827-835
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• 2019

In the pooling stage of a full reference image quality assessment (FR-IQA) technique, the global perceived quality for any distorted image is usually measured from the quality of its local image patches. But all the image patches do not have equal contribution when estimating the overall visual quality since the degree of degradation on those patches depends on various considerations i.e., types of the patches, types of the distortions, distortion sensitivities of the patches, saliency score of the patches, etc. As a result, weighted pooling strategy comes into account and different weighting mechanisms are used by the existing FR-IQA methods. This paper performs a thorough analysis and proposes a novel weighting function by considering the luminance adaptation as well as the visual saliency effect to offer more appropriate local weights, which can be adopted in the existing FR-IQA frameworks to improve their prediction accuracy. The extended experimental results show the effectiveness of the proposed weighting function.

• Journal of Korean Neurosurgical Society
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• v.64 no.1
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• pp.110-119
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• 2021

Objective : Preoperative prediction of the arachnoid membrane descent in pituitary surgery is useful for achieving gross total removal and avoiding cerebrospinal fluid leakage resulting from tearing of the arachnoid membrane in the chiasmatic cistern. In this study, we analyzed the patterns of arachnoid membrane descent during or after pituitary tumor surgery and identified the factors related to this descent. Methods : Analysis was restricted to pituitary macroadenomas not extending into the third ventricle or over the internal carotid artery. To minimize confounding factors, patients who underwent revision surgery, those who had a torn arachnoid during operation or small medial diaphragma sellae (DS) opening, and subtotal resections were excluded. We enrolled 41 consecutive patients in this retrospective analysis. The degree of arachnoid descent was categorized using intraoperative videos. Preoperative magnetic resonance findings, including tumor height, suprasellar extension, and variables including DS area and medial opening size, tumor composition, and displacement of the pituitary stalk and gland were evaluated to determine their correlations with arachnoid membrane descent. Results : Arachnoid membrane descent was significantly correlated with DS area and medial opening size. Based on T2-weighted images (T2WI) magnetic resonance (MR) images, tumor composition was significantly associated with arachnoid membrane descent. Other factors were not significantly correlated with arachnoid membrane descent. Conclusion : T2WI of tumor composition and preoperative MR imaging of DS area and medial opening provided valuable information regarding arachnoid membrane descent. These parameters may serve as fundamental measures to facilitate complete resection of pituitary macroadenomas.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.93-100
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• 2022

In the era of information overload on the Internet, the recommendation system, which is an indispensable function, is a service that recommends products that a user may prefer, and has been successfully provided in various commercial sites. Recently, studies to reflect the rating time of items to improve the performance of collaborative filtering, a representative recommendation technique, are active. The core idea of these studies is to generate the recommendation list by giving an exponentially lower weight to the items rated in the past. However, this has a disadvantage in that a time function is uniformly applied to all items without considering changes in users' preferences according to the characteristics of the items. In this study, we propose a time-aware collaborative filtering technique from a completely different point of view by developing a new similarity measure that integrates the change in similarity values between items over time into a weighted sum. As a result of the experiment, the prediction performance and recommendation performance of the proposed method were significantly superior to the existing representative time aware methods and traditional methods.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.87-93
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• 2023

Determining the timing of buying and selling in stock investment is one of the most important factors to increase the return on stock investment. Buying low and selling high makes a profit, but buying high and selling low makes a loss. The price is determined by the quantity of buying and selling, which determines the price of a stock, and buying and selling is also related to corporate performance and economic indicators. The fear and greed index provided by CNN uses seven factors, and by assigning weights to each element, the weighted average defined as greed and fear is calculated on a scale between 0 and 100 and published every day. When the index is close to 0, the stock market sentiment is fearful, and when the index is close to 100, it is greedy. Therefore, we analyze the trading criteria that generate the maximum return when buying and selling the US S&P 500 index according to CNN fear and greed index, suggesting the optimal buying and selling timing to suggest a way to increase the return on stock investment.