• Journal of the Korea Construction Safety Engineering Association
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• s.36
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• pp.73-81
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• 2006

Construction fall accidents have been investigated by many researchers. Construction workers are prone to fall when elevations of the construction site is high. And falls are the most fatal accidents: it can be directly linked to the death. Construction fall accidents might be reduced by predetermining several areas which are highly probable to have fall accidents and by controlling such areas until the completion of the building construction. In this paper, a fall prevention system is suggested which can identify the areas where the focus on fall protection is perhaps most needed from the process characteristics. Main methodologies for this research are summarized as follows: 1. A data base on elements and types of falls is constructed from the data analysis of last 10 years fall accidents history. 2. Guideline is derived by identifying the highly probable areas of fall accidents with respect to the specific construction process. 3. Developed system is verified by applying the system to construction sites. 4. Finally a fall prevention system is suggested by utilizing the fall accidents data.

• Physical Therapy Rehabilitation Science
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• v.7 no.2
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• pp.54-60
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• 2018

Objective: Persons with chronic stroke fall more often than healthy elderly individuals. The Timed Up and Go test (TUG) is used as a fall prediction tool, but only provides a result for the total measurement time. This study aimed to determine the optimal cut-off values for each of the 6 components of the TUG. Design: Retrospective study. Methods: Thirty persons with chronic stroke participated in the study. TUG evaluation was performed using a wearable miniaturized inertial sensor. Sensitivity, specificity, and predictive values were calculated using the Receiver Operating Characteristic (ROC) curve analysis for the measured values in each section. Optimal values for fall risk classification were determined. Logistic regression analysis was used to investigate the risk of future falls based on TUG. Results: The cut-off values of the 6 sections of the TUG were determined, as follows: sit-to-stand >2.00 seconds (p<0.05), forward gait >4.68 seconds (p<0.05), mid-turn >3.82 seconds (p<0.05), return gait >4.81 seconds (p<0.05), end-turn >2.95 seconds (p<0.05), and stand-to-sit >2.13 seconds (p<0.05). The risk of falling increased by 2.278 times when the mid-turn value was >3.82 seconds (p<0.05). Conclusions: The risk of falls increased by 2.28 times when the value of the mid-turn interval exceeded 3.82 seconds. Therefore, when interpreting TUG results, the predictive accuracy for falls will be higher when the measurement time for each section is analyzed, together with the total time for TUG.

• ETRI Journal
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• v.44 no.4
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• pp.654-671
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• 2022

Accidental falls frequently occur during activities of daily living. Although many studies have proposed various accident detection methods, no high-performance accident detection system is available. In this study, we propose a method for integrating data and accident detection algorithms presented in existing studies, collect new data (from two stunt performers and 15 people over age 60) using a developed wearable device, demonstrate new features and related accident detection algorithms, and analyze the performance of the proposed method against existing methods. Comparative analysis results show that the newly defined features extracted reflect more important risk factors than those used in existing studies. Further, although the traditional algorithms applied to integrated data achieved an accuracy (AC) of 79.5% and a false positive rate (FPR) of 19.4%, the proposed accident detection algorithms achieved 97.8% AC and 2.9% FPR. The high AC and low FPR for accidental falls indicate that the proposed method exhibits a considerable advancement toward developing a commercial accident detection system.

• Explosives and Blasting
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• v.36 no.1
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• pp.20-33
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• 2018

A locally damaged structure is a structure that cannot be reused due to having parts that have lost their structural function as a result of abnormal load across the interior or exterior of the structure. The causes of the abnormal load occurrences can be classified into natural disaster and artificial disaster. Locally damaged structures caused by this abnormal load have risk factors that may lead to the possibility of additional secondary collapses, so such structures require immediate and complete dismantling. The case presented in this study involves the application of explosive demolition to a steel truss structured bridge in the Philippines that was damaged due to construction failures and the hurricane. Although shaped charges were needed in explosive demolitions, difficulties in locally obtaining such material. So, we made a charge container to charging of emulsion explosive during the explosive demolition. The explosive demolition resulted in the vertical free fall of the mid-section of the bridge and the free fall rotating of the both end section of the bridge. The neighboring posts and bridge piers did not show signs of damages, while post-demolition fragmentation of removed parts was found to be satisfactory.

• Journal of Conservation Science
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• v.37 no.5
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• pp.505-515
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• 2021

In this study, we evaluated the slope stability of the Pohang Daljeon-ri columnar joint (Natural Monuments # 415) and calculated the maximum energy, jumping height and moving distance of rockfalls using a simulation. Based on the results, we established the range of rockfall risk. The slopes of the Pohang Daljeon-ri columnar joint have dip directions of 93.79°, 131.99°, 165.54° and 259.84° from left (SW) to right (NE). Furthermore, they have a fan-like shape. The Pohang Daljeon-ri columnar joints are divided into four sections depending on the dip direction. The measurement results of the discontinuous face show that zone 1 is 125, zone 2 is 261, zone 3 is 262, zone 4 is 43. The results of slope stability analyses for each section using a stereographic projection method correspond to the range of planar and toppling failure. Although it is difficult to diagnose the type of failure, risk evaluation of currently falling rocks requires further focus. The maximum movement distance of a rockfall in the simulation was approximately 66 m and the rockfall risk range was the entire area under slope. In addition, it is difficult to forecast where a rock will fall as it rolls in various directions due to topographic factors. Thus, the installation of measures to prevent falling is suggested to secure the stability based on the results of the rockfall simulations and its probabilistic analysis.

• Journal of Korean Society of Transportation
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• v.18 no.5
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• pp.7-16
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• 2000

This paper is focused on verifying time-space repetition of the highway accident and finding the their causes and deterrents. We classify all months into several seasonal groups, develop the model for each seasonal group and analyze the results of these models for Joong-bu highway. The existence of seasonal effect is verified by the analysis or self-organizing map and the accident indices. Agglomerative hierarchical cluster analysis which is used to decide the seasonal groups in accordance with accident patterns, winter group, spring-fall group. and summer group. The accident features of winter group are that the accident rate is high but the severity rate is low. while those of summer group are that the accident rate is low but the severity rate is high. Also, the regression model which is developed to identify the accident Pattern or each seasonal group represents that the season-related factors, such as the amount of rainfall, the amount of snowfall, days of rainfall, days of snowfall etc. are strongly related to the accident pattern of evert seasonal group and among these factors the traffic volume, amount of rainfall. the amount of snowfall and days of freezing importantly affect the local accident Pattern. So, seasonal effect should be considered to the identification of high-risk road section. the development of descriptive and Predictive accident model, the resource allocation model of accident in order to make safety management plan efficient.