• Journal of the Korea Safety Management & Science
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• v.7 no.3
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• pp.47-61
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• 2005

Many researchers have proved that risk measurement of information systems is a very effective tool for improving confidence of information systems. However, information system risk in Korea still includes many subjective judgements. This study deals with applying a quantitative model to improve risk measurement of information system quality. First of all, we have come up with solutions to improve the evaluation efficiency on risk measurement. We have merged the risk guidelines of COBIT and CMM, and developed a quantified evaluation scheme that call by risk point. We have proved the validity of this model by interviews with experts and by case studies.

• Journal of Korean Clinical Nursing Research
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• v.19 no.3
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• pp.357-368
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• 2013

Purpose: The purpose of this study was to investigate risk factors related to delirium and to develop screening model on delirium occurrence in MICU (Medical Intensive Care Unit) patients. Methods: For developing a preliminary tool for delirium, the data of 166 patients were collected and analyzed. In order to estimate the accuracy and discriminating power for the developed screening model, 98 patients were enrolled. The data used in this study were collected by EMR (Electronic Medical Record) review from January to September in 2012. The collected data were analyzed using SPSS/PC Win 18.0 program. Results: Screening model on delirium in MICU patients was developed using the results of logistic regression. The total score of screening model was 24 point and measuring point was 10 point. When the measuring point is over 10 point, it means that the risk of delirium occurrence is high. The discriminating power and the validity of screening model showed AUC .908 (p <.001) and .935 (p <.001) respectively. This result showed that the screening model on delirium which developed in this study was an appropriate model for screening the delirium risk group in MICU. The sensitivity of the screening model was 83%, specificity 89% and accuracy 84%. Conclusion: The developed screening model on delirium occurrence in MICU should be combined with EMR for screening and preventing delirium in a high risk group.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.49 no.5
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• pp.533-540
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• 2016

This study assessed the risk of an oyster-shucking site to establish the hazard analysis critical control point (HACCP) system model by measuring viable cell counts, coliform group Staphylococcus aureus foreign material on oysters, oyster-producing equipment, and washing water. The viable cell count and coliform group levels of the harvested raw oysters were 4.00 log CFU/g and 1.1×10² MPN/100 g, while those of washed oysters were 2.99 log CFU/g and (3.2−4.6) × 10 MPN/100 g, respectively. After washing the oysters, no Escherichia coli or pathogenic bacteria (E. coli O157:H7, Listeria monocytogenes, S. aureus, Salmonella spp., Vibrio parahaemolyticus, and Clostridium perfringens) were detected. Regardless of the location of foreign matter, up to 100% more metallic and non-metallic foreign matter was detected at 1.5 mmΦ than at 3.5 mmΦ, using a metal detector with increased sensitivity. According to the results, the critical control points (CCP) are the washing and metal-detection processes. These results can be used as basic data to improve sanitation at oyster-shucking sites in factories with an HACCP system.

• Journal of Biomedical Engineering Research
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• v.44 no.2
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• pp.139-146
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• 2023

Osteoporosis is a disease in which the risk of bone fractures increases due to a decrease in bone density caused by aging. Osteoporosis is diagnosed by measuring bone density in the total hip, femoral neck, and lumbar spine. To accurately measure bone density in the lumbar spine, the vertebral region must be segmented from the lumbar X-ray image. Deep learning-based automatic spinal segmentation methods can provide fast and precise information about the vertebral region. In this study, we used 695 lumbar spine images as training and test datasets for a deep learning segmentation model. We proposed a lumbar automatic segmentation model, CM-Net, which combines the center point of the spine and the modified U-Net network. As a result, the average Dice Similarity Coefficient(DSC) was 0.974, precision was 0.916, recall was 0.906, accuracy was 0.998, and Area under the Precision-Recall Curve (AUPRC) was 0.912. This study demonstrates a high-performance automatic segmentation model for lumbar X-ray images, which overcomes noise such as spinal fractures and implants. Furthermore, we can perform accurate measurement of bone density on lumbar X-ray images using an automatic segmentation methodology for the spine, which can prevent the risk of compression fractures at an early stage and improve the accuracy and efficiency of osteoporosis diagnosis.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.868-871
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• 2007

The current economy is summarized by increasing business competitiveness and leaner organizations, and the risk and uncertainties inherent in such dynamic environments have increased the importance of managing organizational knowledge. Like the preceding, the construction industry is required to make an effort for survival and takeoff, and most construction companies recognize that knowledge management improves efficiency and effectiveness and the necessity on the innovation of business itself and it is the current of the times. But at this point in time, companies have doubts about performance following the introduction of KM, and set to show interest in developing a measurement method. So, This study analyzes the existing model for performance measurement and based on results derived, presents the method for performance measurement.

• Fire Science and Engineering
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• v.34 no.3
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• pp.67-75
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• 2020

In this study, the risk of heat generation due to normal and overload currents that vary with the abnormal loosening angle of wire-connecting bolts were identified. The risks were analyzed based on the thermal characteristics to minimize the carbonization accidents of terminal blocks inside distribution panels typically used in industrial sites. We applied a method for measuring the heating temperature and temperature variations in the terminal blocks in real-time by installing a resistance temperature detector sensor board in the terminal block. The experimental results showed that the terminal block model with a low-rated current exhibited a higher heating temperature, thus, confirming the need to select the terminal block capacity based on load currents. Additionally, the higher the rated current of the terminal block with a high-rated current and the higher the degree of loosening, the faster the carbonization point. Such heating temperature monitoring enabled real-time thermal temperature measurement and a step-by-step risk level setting through thermal analysis. The results of the measurement and analysis of carbonization risks can provide a theoretical basis for further research regarding the risk of fire due to carbonization. Furthermore, the deterioration measurement method using the temperature sensor board developed in this study is widely applicable to prevent fires caused by poor electrical contact as well as risk-level management.

• Journal of the Ergonomics Society of Korea
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• v.30 no.5
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• pp.637-644
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• 2011

Objective & Background: When applying various evaluation tools that analyze work posture risk through observation, accurate measurement of body flexion angle is very important. Method: This study investigated differences and appropriateness of 5 different existing reference points commonly used in the analysis of the work posture. Twenty five ergonomist and trained professionals were participated in this study. A Same flexion angle was utilized for the evaluation of risk assessment of musculoskeletal disorders using five different reference points to investigate the degree of difference between them. To investigate how different the observers' preferred flexion angle measuring methods were compared to the ISO 11226 Reference Posture, a virtual body model was constructed using the Poser 6.0 program. Six types of body flexion postures were constructed, and since neck flexion differs according to body angle, five types of neck flexion postures were constructed with the trunk bending $20^{\circ}$ forward, making up a total of 30 virtual flexion postures. Results: Results showed that the observers used personally preferred reference points instead of reference points recommend in the evaluation tools. Also the results revealed the their seems to be 6 types of flexion angle for the trunk and 11 types of measurement methods for the neck flexion angle in the form of personally preferred reference points. The results showed that a mean difference of $14^{\circ}$($4{\sim}23^{\circ}$) occurred in the trunk, and a mean difference of $20^{\circ}$($-8{\sim}51^{\circ}$) occurred in the neck. To increase accuracy when using the 5 evaluation tools in combination, the ISO 11226 standards, observers' preferred flexion posture standards, and common flexion posture standards of the evaluation tools were compared with the reference points of the 5 evaluation tools. Results showed considerable variance in angle difference for each evaluation tool. Conclusion: According to the results of this study, considering the angle difference between the flexion angle reference points of the evaluation tool and the reference points selected by the observers, it is concluded that instead of personally preferred reference points, the standardized reference points to enhance the accuracy and the objectivity. Application: The result of this study can be used as reference guide to develop the standardized reference point in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.1118-1125
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• 2014

The past IMF foreign exchange crisis and subprime financial crisis had a big influence on variability of macroeconomics, even if the origin of its occurrence might be different. This not only had a significant infrequence on the overall industries, but also produced many insolvent companies by being closely linked with a management environment of an individual construction company leading the construction industry. The purpose of this research is to investigate characteristics of management condition of construction company according to the size of construction company using KMV model developed on the basis of the Black & Scholes option pricing theory. This research has set 28 construction companies listed to KOSPI/KOSDAQ for applying the KMV model and measuring the level of the default risk of construction companies. The data was retrieved from TS2000 established by Korea Listed Companies Association (KLCA), Statistics Korea. The analysis period is between first quarter of 2004 and fourth quarter of 2010. This research examine characteristics of the level and fluctuation process of the management condition of construction company according to the size of construction company.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.