• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.8
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• pp.661-673
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• 2014

In this paper, a precise orbit determination process was carried out based on KARISMA(KARI Collision Risk Management System) developed by KARI(Korea Aerospace Research Institute), in which optical tracking data of a geostationary satellite was used. The real optical tracking data provided by ESA(European Space Agency) for the ARTEMIS geostationary satellite was used. And orbit determination error was approximately 420 m compared to that of the ESA's orbit determination result from the same optical tracking data. In addition, orbit prediction was conducted based on the orbit determination result with optical tracking data for 4 days, and the position error for the orbit prediction during 3 days was approximately 500~600 m compared to that of ESA's result. These results imply that the performance of the KARISMA's orbit determination function is suitable to apply to the collision risk assessment for the space debris.

• Journal of the Korea Safety Management & Science
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• v.22 no.1
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• pp.23-32
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• 2020

There has been a significant decline in the number of rail accidents in Korea since system safety management activities were introduced. Nonetheless, analyzing and preventing human error-related accidents is still an important issue in railway industry. As a railway system is increasingly automated and intelligent, the mechanism and process of an accident occurrence are more and more complicated. It is now essential to consider a variety of factors and their intricate interactions in the analysis of rail accidents. However, it has proved that traditional accident models and methods based on a linear cause-effect relationship are inadequate to analyze and to assess accidents in complex systems such as railway systems. In order to supplement the limitations of traditional safety methods, recently some systemic safety models and methods have been developed. Of those, FRAM(Functional Resonance Analysis Method) has been recognized as one of the most useful methods for analyzing accidents in complex systems. It reflects the concepts of performance adjustment and performance variability in a system, which are fundamental to understanding the processes of an accident in complex systems. This study aims to apply FRAM to the analysis of a rail accident involving human errors, which occurred recently in South Korea. Through the application of FRAM, we found that it can be a useful alternative to traditional methods in the analysis and assessment of accidents in complex systems. In addition, it was also found that FRAM can help analysts understand the interactions between functional elements of a system in a systematic manner.

• Journal of Navigation and Port Research
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• v.33 no.3
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• pp.181-191
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• 2009

In general, seafarer's human error is considered to be the preponderant muse for the majority of maritime transportation accidents in a merchant ship. The implementation techniques for Human Error Model (HEM) to assess possible accident risk by deck officers including captain, chief officer, second mate and third mate are described in this study. The scope of this work is focused to 642 deck officers in the ship management company with 130 vessels. At first, HEM can be constructed through the statistical analysis and expert's brainstorming process with human data to 642 deck officers. Then the variables $\upsilon$ for the human factors, the evaluation level EP($\upsilon$) for $\upsilon$, the weight $\alpha$ of $\upsilon$, and the title weight $\beta$ of each deck officers can be decided. In addition, through the analysis of ship's accident history, the accident causation ratios by human error ${\gamma}_H$ and by external error ${\gamma}_B$ can be found as 0.517(51.7%) and 0.483(48.3%), respectively. The correlation coefficients to $\upsilon$ are also shown significant for a 95% confidence interval (p < 0.05) for each coefficient. And the validity of HEM is also surveyed by the analysis of normal probability distribution of risk level RL to each deck officer.

• Korean Journal of Clinical Pharmacy
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• v.26 no.3
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• pp.230-237
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• 2016

Background: Since the use of opioid analgesics is frequent in operation rooms (OR), the risk of medication error is high; however the use of medication in the OR has been operating independently with the hospital pharmacy. Therefore, the assessment on management of medication use in operation and the pharmacist's role is needed. Methods: We conducted the literature review and survey from anesthesiologists, operating nurses at Chung-Ang Hospital on management of medication for operation use, awareness on need for medication management efficiency, need for satellite pharmacy in the operating room and its effect. Results: 56% of medical staffs responded that management of medication in the operating room is efficient; however, 82.6% responded that they felt the inconvenience in medication delivery to the OR when additional prescription was ordered. 51.5% also responded that extra time was required for management of narcotics and inventory/record keeping. 80% agreed that there could be lost costs due to prescription missed. Medical staffs responded improving the drug management system could increase the OR efficiency (87%), and eventually bring the increase in hospital revenue (80.4%). Those who responded that implementation of OR satellite pharmacy was needed include physicians (84.6%), nurses (63.6%), and also responded that it'd bring more profit to the hospital by increasing the efficiency in OR (60.9%). Conclusion: For efficient management of medications, implementation of OR satellite pharmacy would lead to improved drug management and increased efficiency in OR and reduced cost and improved patient care.

• Journal of The Korean Society of Agricultural Engineers
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• v.48 no.5
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• pp.29-38
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• 2006

Geographic Information System has extended to higher assessment of water resources. GIS linking with hydrological model becomes a trend in water resource assessment modeling. One of the most popular models is SWAT2000 which have effectiveness in multi-purpose processes for predicting the impact of land management practices on water, sediments and chemicals yields in large complex watershed with varying soils, land uses, and management conditions over long period of time. In this study, SWAT2000 model was applied to Gap stream watershed in Daejeon city where TMDL (Total Maximum Daily Load) Regulation would be implanted. The Gap Stream watershed was partitioned into 8 subbasins, however, only 3 out of 8 subbaisns were observed for having practical gauged data on the basis of streamflow from the year of 2002 to 2005. Gauged streamflow data of Indong, Boksu and Hoeduck stations were used for calibration and validation of the SWAT Streamflow simulation. Estimation Efficiency Analysis (COE), Regression Analysis ($R^{2}$), Relative Error (R.E.) were used for comparing observed streamflow data of the 3 subbasins on the daily and monthly basis with estimated streamflow data in order to fix optimized parameters for the best fitted results. COE value for the daily and monthly streamflow was ranged from 0.45 to 0.96. $R^{2}$ values for daily and monthly streamflow ranged from 0.51 to 0.97. R.E. values for total streamflow volume ranged from 3 % to 22.5 %. The accuracy of the model results shows that the SWAT2000 model can be applicable to Korean watersheds like the Gap Stream watershed that needs to be partitioned into a number of subbasins for TMDL regulation.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.2
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• pp.41-50
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• 2023

Gait analysis is an important tool in the clinical management of cerebral palsy, allowing for the assessment of condition severity, identification of potential gait abnormalities, planning and evaluation of interventions, and providing a baseline for future comparisons. However, traditional methods of gait analysis are costly and time-consuming, leading to a need for a more convenient and continuous method. This paper proposes a method for analyzing the posture of cerebral palsy patients using only smartphone videos and deep learning models, including a ResNet-based image tilt correction, AlphaPose for human pose estimation, and SmoothNet for temporal smoothing. The indicators employed in medical practice, such as the imbalance angles of shoulder and pelvis and the joint angles of spine-thighs, knees and ankles, were precisely examined. The proposed system surpassed pose estimation alone, reducing the mean absolute error for imbalance angles in frontal videos from 4.196° to 2.971° and for joint angles in sagittal videos from 5.889° to 5.442°.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.54 no.1
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• pp.38-53
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• 2018

The purpose of this study is to estimate potential yield (PY) for Korean west coast fisheries using the holistic production method (HPM). HPM involves the use of surplus production models to apply input data of catch and standardized fishing efforts. HPM compared the estimated parameters of the surplus production from four different models: the Fox model, CYP model, ASPIC model, and maximum entropy model. The PY estimates ranged from 174,232 metric tons (mt) using the CYP model to 238,088 mt using the maximum entropy model. The highest coefficient of determination ($R^2$), the lowest root mean square error (RMSE), and the lowest Theil's U statistic (U) for Korean west coast fisheries were obtained from the maximum entropy model. The maximum entropy model showed relatively better fits of data, indicating that the maximum entropy model is statistically more stable and accurate than other models. The estimate from the maximum entropy model is regarded as a more reasonable estimate of PY. The quality of input data should be improved for the future study of PY to obtain more reliable estimates.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.4
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• pp.9-19
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• 2014

The objective of this study was to evaluate of the Tank model in simulating runoff discharge from rural watershed in comparison to the SWAT (Soil and Water Assessment Tool) model. The model parameters of SWAT was calibrated by the shuffled complex evolution-university Arizona (SCE-UA) method while Tank model was calibrated by genetic algorithm (GA) and validated. Four dam watersheds were selected as the study areas. Hydrological data of the Water Management Information System (WAMIS) and geological data were used as an input data for the model simulation. Runoff data were used for the model calibration and validation. The determination coefficient ($R^2$), root mean square error (RMSE), Nash-Sutcliffe efficiency index (NSE) were used to evaluate the model performances. The result indicated that both SWAT model and Tank model simulated runoff reasonably during calibration and validation period. For annual runoff, the Tank model tended to overestimate, especially for small runoff (< 0.2 mm) whereas SWAT model underestimate runoff as compared to observed data. The statistics indicated that the Tank model simulated runoff more accurately than the SWAT model. Therefore the Tank model could be a good tool for runoff simulation considering its ease of use.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2021-2028
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• 2010

Rail human factors research has grown rapidly in both quantity and quality of output over the past few years. Human factors, also, still plays a significant part in many railway accidents. In this paper we review categorized performance shaping factors of human errors associated with railway accidents within and out of the country. This paper deals with the selection of the important performance shaping factors under accident management situations in railway for use in the assessment of human errors. The purpose of this study is to classify which human error would be selected for accident analysis. Therefore, the classification of human errors suggested in this study may be useful to enhance the Korean railway system safety.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.417-423
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• 2017

This paper intend to implement monitoring systems for individual customized diagnostics to maintain ongoing disease management to promote human health. Analyze the threshold of a measured biological signal using a number of measuring sensors. Performance assessment revealed that the SVM algorithm for bio-signal analysis showed an average error rate of 2 %. The accuracy of the classification is 97.2%, and reduced the maximum of 19.2% of the storage space when you split the window into 5,000 pieces. Out of the total 5,000 bio-signals, 84 results showed that results from the system were differently the results of the expert's diagnosis and showed about 98 % accuracy. However, the results of the monitoring system did not occur when the results of the monitoring system were lower than that of experts. And About 98% accuracy was shown.