• Journal of Digital Convergence
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• v.19 no.4
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• pp.467-475
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• 2021

Purpose: When a patient with acute deterioration occurs in a ward, the decision to transfer to intensive care unit (ICU) is critical to improve the patient's outcomes. However, when available ICU resources limited, it is difficult to determine which of the deteriorating ward patients to transfer to the ICU. Therefore the purpose of this study was to identify risk factors in predicting deteriorating ward patients transferred to intensive care unit (ICU). Methods: We reviewed retrospectively clinical data of 2,945 deteriorating ward patients who referred medical emergency team. Data were analyzed with multivariate logistic regression. Results: The solid cancer that diagnosed at hospitalization (odds ratio[OR] 0.39; 95% confidence interval [CI] 0.32-0.47), when the cause of deterioration was respiratory problem (1.51; 95% CI 1.17-1.95), high MEWS (1.22; 1.17-1.28) and SpO2/FiO2 score (2.41; 2.23-2.60) were predictive of ICU transfer. Conclusion: These findings suggest that early prediction and treatment of patients with high risk of ICU transfer may improve the prognosis of patients.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.157-177
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• 2003

This paper presents a comprehensive and successful application of data mining methodologies to improve and predict wafer yield in a semiconductor wafer fabrication system. As the wafer fabrication process is getting more complex and the volume of technological data gathered continues to be vast, it is difficult to analyze the cause of yield deterioration effectively by means of statistical or heuristic approaches. To begin with this paper applies a clustering method to automatically identify AUF (Area Uniform Failure) phenomenon from data instead of naked eye that bad chips occurs in a specific area of wafer. Next, sequential pattern analysis and classification methods are applied to and out machines and parameters that are cause of low yield, respectively. Furthermore, radial bases function method is used to predict yield of wafers that are in process. Finally, this paper demonstrates an information system, Y2R-PLUS (Yield Rapid Ramp-up, Prediction, analysis & Up Support), that is developed in order to analyze and predict wafer yield in a korea semiconductor manufacturer.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.219-227
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• 2009

In H.264/AVC, if each block is quantized with a adaptive quantization parameter(QP) regardless of the characteristics of a block, it could be the deterioration of the picture quality. In this paper, an adaptive block-based QP selection method is proposed in order to improve picture quality by utilizing the bit amounts of the zigzag-scanned integer transform coefficients of the neighboring blocks and changing the QP value in the current block. The proposed method works in the same way as the encoder and decoder without transmitting the change of QP value to the decoder side. The experimental results show that the proposed method achieves a gain of about $0.1\sim0.3dB$ compared with H.264/AVC.

• Journal of Korean Neurosurgical Society
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• v.63 no.2
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• pp.248-260
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• 2020

Objective : To investigate the efficiency of diffusion tensor imaging (DTI) fiber-tracking based neuronavigation and assess its usefulness in the preoperative surgical planning, prognostic prediction, intraoperative course and outcome improvement. Methods : Seventeen patients with cerebral masses adjacent to corticospinal tract (CST) were given standard magnetic resonance imaging and DTI examination. By incorporation of DTI data, the relation between tumor and adjacent white matter tracts was reconstructed and assessed in the neuronavigation system. Distance from tumor border to CST was measured. Results : The sub-portion of CST in closest proximity to tumor was found displaced in all patients. The chief disruptive changes were classified as follows : complete interruption, partial interruption, or simple displacement. Partial interruption was evident in seven patients (41.2%) whose lesions were close to cortex. In the other 10 patients (58.8%), delineated CSTs were intact but distorted. No complete CST interruption was identified. Overall, the mean distance from resection border to CST was 6.12 mm (range, 0-21), as opposed to 8.18 mm (range, 2-21) with simple displacement and 2.33 mm (range, 0-5) with partial interruption. The clinical outcomes were analyzed in groups stratified by intervening distances (close, <5 mm; moderated, 5-10 mm; far, >10 mm). For the primary brain tumor patients, the proportion of completely resected tumors increased progressively from close to far grouping (42.9%, 50%, and 100%, respectively). Five patients out of seven (71.4%) experienced new neurologic deficits postoperatively in the close group. At meantime, motor deterioration was found in six cases in the close group. All patients in the far and moderate groups received excellent (modified Rankin Scale [mRS] score, 0-1) or good (mRS score, 2-3) rankings, but only 57.1% of patients in the close group earned good outcome scores. Conclusion : DTI fiber tracking based neuronavigation has merit in assessing the relation between lesions and adjacent white matter tracts, allowing prediction of patient outcomes based on lesion-CST distance. It has also proven beneficial in formulating surgical strategies.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.12
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• pp.357-362
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• 2023

Bridges are important transportation infrastructure, but they are subject to damage and cracking due to various environmental factors and constant traffic loads, which accelerate their aging. With many bridges now older than their original construction, there is a need for systems to ensure safety and diagnose deterioration. Bridges are already utilizing structural health monitoring (SHM) technology to monitor the condition of bridges in real time or periodically. Along with this technology, the development of intelligent bridge monitoring technology utilizing artificial intelligence and Internet of Things technology is underway. In this paper, we study an edge system technique for predicting bridge safety using fast Fourier transform and dimensionality reduction algorithm for maintenance of aging bridges. In particular, unlike previous studies, we investigate whether it is possible to form a dataset using sensor data collected from actual bridges and check the safety of bridges.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.220-227
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• 2021

PCT (Power Cable Tunnel) and UT (Utility Tunnel), which are non-transport underground infrastructures, are mostly RC (Reinforced Concrete) structures, and their durability decreases due to the deterioration caused by carbonation over time. In particular, since the rate of carbonation varies by use and region, a predictive model based on actual carbonation data is required for individual maintenance. In this study, a carbonation prediction model was developed for non-transport underground infrastructures, such as PCT and UT. A carbonation prediction model was developed using multiple regression analysis and deep neural network techniques based on the actual data obtained from a safety inspection. The structures, region, measurement location, construction method, measurement member, and concrete strength were selected as independent variables to determine the dependent variable carbonation rate coefficient in multiple regression analysis. The adjusted coefficient of determination (Ra2) of the multiple regression model was found to be 0.67. The coefficient of determination (R2) of the model for predicting the carbonation of non-transport underground infrastructures using a deep neural network was 0.82, which was superior to the comparative prediction model. These results are expected to help determine the optimal timing for repair on carbonation and preventive maintenance methodology for PCT and UT.

• Korean Journal of Radiology
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• v.22 no.7
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• pp.1213-1224
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• 2021

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion: CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

• Korean Journal of Food Science and Technology
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• v.23 no.4
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• pp.447-451
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• 1991

Red pepper peels stored with seeds or stems in the powder state at $30^{\circ}C$ resulted in decrease of quality components such as capsanthin, capsaicin and total sugars. The effect of seeds on the quality deterioration was larger than stems. A near-infrared reflectance spectroscopic(NIRS) method was evaluated for the determination of seed and stem contents in red pepper peels. The standard error of prediction was 1.76% in seeds and 0.43% in stems. It is concluded that the NIRS method is suitable for the determination of seen and stem contents in red pepper powder.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1391-1394
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• 2006

노후 상수도관의 개량사업이 지속적으로 시행되고 있지만 노후관 개량사업은 경험적 판단에 의존하는 노후관 평가 및 대안의 선정, 사고예방을 위한 대응적 차원의 개량 사업을 실시함으로 인해 경제적 손실은 물론 시스템의 유기적 기능향상이 이루어지지 않고 있는 실정이다. 이에 본 연구에서는 상수관로 중에서 아연도 강관, 도복장 강관, 닥타일 주철관을 선정하여 현장조사를 실시하였으며, 직접 채취된 관체 시편을 대상으로 육안분석, 관체분석, 그리고 토양부식성 등을 평가하여 채취한 관의 노후도를 종합적으로 평가하였다. 기본적으로 노후도 평가를 점수 평가법을 사용하였으며, 평가된 결과를 바탕으로 향후 노후 수도관 개량사업 추진 내용에서 개대체 우선순위를 결정하기 위한 모델을 제안하였다. 상수관로 노후도 영향 인자 및 가중치 추정은 현재 매설된 상수관로의 노후진척도를 평가하기 위한 노후도 예측모형의 기본 요소이며, 모형의 정확도를 향상시키기 위해 필수적인 사항이다. 관로 노후진척도 분석의 정확도는 장기간의 자료 수집을 통하여 이루어져 이에 대한 분석이 필요하며, 대상관로를 이용하여 개발된 제안식은 향후 지속적으로 현장조사를 실시하여 보완이 필요하겠지만, 노후수도관의 개량 우선순위를 분석하기 위한 매우 유용한 자료가 될 것으로 판단한다.

• Journal of the Korean Society of Safety
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• v.20 no.2 s.70
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• pp.113-118
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• 2005

Recently, the corrosion of reinforced concrete structures has received great attention related with the deterioration of sea-side structures, such as new airport, bridges, and nuclear power plants. In this regards, many studies have been done on the chloride attack in concrete structures. The purpose of the present study is to explore the influences of chloride attack parameters to service life of reinforced concrete structures and to propose the rational program for the guarantee of service life. for this purpose, several codes for durability design have been examined and the diffusion analysis based on Fick's second law has been performed with various parameter value. The present study indicates that durability design code of Japan Society of Civil Engineers is more rational than other codes but the application of durability design code of JSCE to domestic durability design needs more studies to the various parameter values related with chloride penetration.