Background: The mining industry is known worldwide for its highly risky and hazardous working environment. Technological advancement in ore extraction techniques for proliferation of production levels has caused further concern for safety in this industry. Research so far in the area of safety has revealed that the majority of incidents in hazardous industry take place because of human error, the control of which would enhance safety levels in working sites to a considerable extent. Methods: The present work focuses upon the analysis of human factors such as unsafe acts, preconditions for unsafe acts, unsafe leadership, and organizational influences. A modified human factor analysis and classification system (HFACS) was adopted and an accident predictive fuzzy reasoning approach (FRA)-based system was developed to predict the likelihood of accidents for manganese mines in India, using analysis of factors such as age, experience of worker, shift of work, etc. Results: The outcome of the analysis indicated that skill-based errors are most critical and require immediate attention for mitigation. The FRA-based accident prediction system developed gives an outcome as an indicative risk score associated with the identified accident-prone situation, based upon which a suitable plan for mitigation can be developed. Conclusion: Unsafe acts of the worker are the most critical human factors identified to be controlled on priority basis. A significant association of factors (namely age, experience of the worker, and shift of work) with unsafe acts performed by the operator is identified based upon which the FRA-based accident prediction model is proposed.
Journal of The Korean Society of Agricultural Engineers
/
v.52
no.6
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pp.135-144
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2010
This study was performed to suggest a soil loss reduction skill through estimating soil erosion from a small watershed including each type of sloping agriland by using GEOWEPP model. Experimental watershed at Gangwon province was selected for very typical sloping fields of highland agriculture in Alpine area. Runoff discharge and sediment load, hourly rainfall amount occurred during storm event were gauged, and weather data were obtained from Daegwallyeong meteorological station. The results of GEOWEPP model estimation showed that relative error values for total runoff discharge and sediment load were 3 %, -14.5 % respectively. Based on the result, soil erosion and waterway path map for each hillslope were made to select target hillslope. Several hillslopes of severe soil erosion were analyezed and then the optimal vegetative filter strip construction width and waterway path to plant grass were decided by using GEOWEPP Model.
Aircraft observations constitute one of the major sources of temperature observations which provide three-dimensional information. But it is well known that the aircraft temperature data have warm bias against sonde observation data, and therefore, the correction of aircraft temperature bias is important to improve the model performance. In this study, the algorithm of the bias correction modified from operational KMA (Korea Meteorological Administration) global model is adopted in the preprocessing of aircraft observations, and the effect of the bias correction of aircraft temperature is investigated by conducting the two experiments. The assimilation with the bias correction showed better consistency in the analysis-forecast cycle in terms of the differences between observations (radiosonde and GPSRO (Global Positioning System Radio Occultation)) and 6h forecast. This resulted in an improved forecasting skill level of the mid-level temperature and geopotential height in terms of the root-mean-square error. It was noted that the benefits of the correction of aircraft temperature bias was the upper-level temperature in the midlatitudes, and this affected various parameters (winds, geopotential height) via the model dynamics.
The process-based XBeach model has numerous empirical parameters because of insufficient understanding of hydrodynamics and sediment transport on the nearshore; hence, it is necessary to calibrate parameters to apply to various study areas and wave conditions. Therefore, the calibration process of parameters is essential for the improvement of model performance. Generally, the trial-and-error method is widely used; however, this method is passive and limited to various and comprehensive parameter ranges. In this study, the Generalized Likelihood Uncertainty Estimation (GLUE) method was used to estimate the optimal range of three parameters (gamma, facua, and gamma2) using morphological field data collected in Maengbang beach during the four typhoons that struck from September to October 2019. The model performance and optimal range of empirical parameters were evaluated using Brier Skill Score (BSS) along with the baseline profiles, sensitivity, and likelihood density analysis of BSS in the GLUE tools. Accordingly, the optimal parameter combinations were derived when facua was less than 0.15 and simulated well the shifting shape, from crescentic sand bar to alongshore uniform sand bars in the surf zone of Maengbang beach after storm impact. However, the erosion and accretion patterns nearby in the surf zone and shoreline remain challenges in the XBeach model.
Journal of Elementary Mathematics Education in Korea
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v.20
no.2
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pp.353-370
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2016
This study examined elementary mathematics teacher's guidebook to determine the inclusion level of 11 critical features of evidence based instruction. And the inclusion level of the features in teacher's guidebook were interpreted as 'Low', 'Middle' and 'High'. The results are as followings. First, The overall inclusion level of the features in teacher's guidebook is 'Middle' The inclusion level of the features in teacher's guidebook for 1st, 2nd, 3rd and 4th were 'Middle' but for 5th and 6th were 'Low'. Second, the inclusion level of the features 'Clarity of Objective', 'Single Concepts and Skill Taught', 'Use of Manipulatives and Representation', 'Explicit Instruction', 'Provision of Examples for new concepts and skill', 'Adequate Independent Practice Opportunities' and 'Progress Monitoring' were 'Middle' The inclusion level of the features 'Review of Prerequisite Mathematical Skills', 'Error correction and Corrective Feedback' and 'Instruction of Strategies' were 'Low'. And discussed the results.
The purpose of this research was to evaluate retention of cognitive knowledge, psychomotor skills and self-confidence on CPR 3 months after CPR training program. The sample consisted of 39 nursing students. We provided one rescuer CPR training program for nursing college students on the basis of AHA. The questionnaires for knowledge of CPR were developed 50 items based on AHA guidelines. Self-confidence were checked by 11 items questionnaires. The accuracy of CPR skills were checked by Skillreporter CPR training manikin and by researcher's evaluation based on CPR skill checklist. The results were as follows ; 1. The majority of participants didn't have any previously experiences of CPR training (76.9%). Only 15.1% previously took the CPR training with CPR practice. 2. In terms of self-confidence of CPR. The score were increased for 2 days (p>.001) but retention of self confidence was significantly statistical decreased in 3 months after training (p<.001). 3. There was a statistically significant decrement in mean of knowledge of CPR between 2 days and 3 months after CPR training (p<.001). 4. There was a statistically significant decrement in cognitive knowledge of CPR based on CPR skills checklist(p<.001). 5. Retention scores of psychomotor skills of CPR 3 months after training were 42.10% in numbers of adequate ventilation, 52.81% in numbers of adequate chest compression (p<.001) respectively. 6. Retention of passing rate on chest compressions of CPR 3 months after training was 27% (p<.001), on ventilation was 2.63% (p>.001). The error items with statistically significant differences 3 months after CPR training were too little ventilation (74.36%) and too little chest compressions (92.31%). The results of the study suggest that we need further evaluation of course components which could improve retention of CPR for all trainees.
Lee, Jung Eun;Koh, Bong Yeun;Lee, In Mo;Choi, Keun Myung;Park, Shin Il;Ahn, Hong Gi
The Korean Journal of Emergency Medical Services
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v.7
no.1
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pp.43-54
/
2003
The purpose of this study was to evaluate the accuracy of CPR skills and the satisfaction of CPR Training targeted for college students. Also, this study made comparative study of nursing students and non-nursing students. The sample consisted of 248 students(132 nursing students, 116 non-nursing students). CPR Training was designed by two components which were a lecture and demonstration by one professor and individual practice by instructors. As tool of measurement estimation satisfaction of CPR Training questionnaires were developed based on educated contents. The accuracy of CPR skills were checked by SkillReporter CPR training manikin. Collected data were computerized and analyzed by SPSS-WIN program. The results were as follows : 1. The skills of CPR were cardiac compression 92.79 times/min, correct cardiac compression rate 90.85%, ventilation 9.93 times/min, correct ventilation rate 79.34%. 2. The mean of the accuracy of CPR skills were 2.94(SD .87). 3. When errors were analyzed, the highest item was stomach distension(51.2%) of ventilation skills and too little(70.6%) of cardiac compression skills. 4. The mean of the satisfaction of CPR training were 2.87(SD .17), the highest item of the satisfaction of CPR Training was practice. 5. We found significant statistical differences based on the accuracy and the error, non-nursing students were high in correct cardiac compression per minute(t=3.615, p=.000) and ventilation too much(t=4.292, p=.000), nursing students were high in correct ventilation rate(t=-3.885, p=.000) and cardiac compression too shallow) t=-2.842, p=.005).
Journal of the Korea Institute of Information and Communication Engineering
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v.8
no.7
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pp.1399-1404
/
2004
The development of computer technology and the advancement of the technology of information and communications spread the technology of multimedia and increased the use of multimedia data with large capacity. Users can grasp the overall video data and they are able to play wanted video back. To grasp the overall video data it is necessary to offer the list of summarized video data information. In order to search video efficiently an index process of video data is essential and it is also indispensable skill. Therefore, this thesis suggested the effective method about the cut detection of frames which will become a basis of an index based on contents of video image data. This suggested method was detected as the unchanging pixel rotor intelligence value, classified into diagonal direction. Pixel value of color detected in each frame of video data is stored as A(i, i) matrix - i is the number of frames, i is an image height of frame. By using the stored pixel value as the method of UE(Mean Square Error) I calculated a specified value difference between frames and detected cut quickly and exactly in case it is bigger than threshold value set in advance. To carry out an experiment on the cut detection of lames comprehensively, 1 experimented on many kinds of video, analyzing and comparing efficiency of the cut detection system.
Objectives : The goal of surgical management of cerebral arteriovenous malformation(AVM) is elimination of the lesion without development of new neurological deficits. To improve the management results of cerebral AVMs in the future, this article discusses about surgical complications of the AVM and their management. Material and Methods : During the past 18 years, 116 patients with cerebral AVMs were managed by surgery. Among these cases, 7 cases died, 7 cases developed new neurological deficits, 11 cases residual AVM and 5 cases intracerebral hematoma(ICH) after surgery. The author analyzes the causes of those complications and investigates the methods to minimized those complications based on the review of the literatures. Results : One stage removal of AVM and ICH in the poor neurological state were performed in 5 of 7 death cases. Subtotal removal of ICH followed by delayed AVM surgery after recovery is regard as one method to improve the outcome of patient with large ICH. Postoperative new neurological deficits developed owing to normal perfusion pressure breakthrough(NPPB) in 3, judgement error in 2, preoperative embolization in 1 and cortical injury in 1 case(s). Proper management of NPPB, accurate anatomical knowledge and physiological monitoring during operation, and well trained skill for embolization are regard as methods to minimize those complications. Residual AVMs after surgery were noticed in 11 cases, in which unintended 6 cases due to inaccurate dissection of peripheral margin of AVM, and intended 3 cases due to massive brain swelling during operation, 1 cases due to diffuse type and 1 case due to multiple type of AVM. Accurate dissection of peripheral margin of AVM and mild hypotension during operation may help to avoid this complication. Postoperative hemorrhage occurred in 3 cases due to rupture of the residual AVM and in 2 cases due to oozing from the AVM bed. Complete resection of AVM, complete control of bleeding points at AVM bed and mild hypotension during early postoperative period are the methods to avoid this complication. Conclusion : A precise but flexible therapeutic strategy and refined skill for endovascular, radiosurgical and microsurgical techniques are required to successful treatment of cerebral AVM. Adequate timing of AVM resection, accurate anatomical knowledge, proper management of NPPB and accurate dissection of peripheral margin of AVM are the key points for avoiding complications of the AVM surgery.
A thermal index which considers metabolic heat generation of human body is proposed for operational forecasting. The new thermal index, Perceived Temperature (PT), is forecasted using Weather Research and Forecasting (WRF) mesoscale model and validated. Forecasted PT shows the characteristics of diurnal variation and topographic and latitudinal effect. Statistical skill scores such as correlation, bias, and RMSE are employed for objective verification of PT and input meteorological variables which are used for calculating PT. Verification result indicates that the accuracy of air temperature and wind forecast is higher in the initial forecast time, while relative humidity is improved as the forecast time increases. The forecasted PT during 2007 summer is lower than PT calculated by observation data. The predicted PT has a minimum Root-Mean-Square-Error (RMSE) of $7-8^{\circ}C$ at 9-18 hour forecast. Spatial distribution of PT shows that it is overestimated in western region, while PT in middle-eastern region is underestimated due to strong wind and low temperature forecast. Underestimation of wind speed and overestimation of relative humidity have caused higher PT than observation in southern region. The predicted PT from the mesoscale model gives appropriate information as a thermal index forecast. This study suggests that forecasted PT is applicable to the prediction of health warning based on the relationship between PT and mortality.
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