• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.111-117
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• 2019

The purpose of this study was a convergence study to find a way to shorten pre-hospital emergency medical response time in vehicle accident. This study analyzed the factors of hospital emergency response time by utilizing weather, road type, accident type, and rescue response to 353 vehicle passengers who visited the three emergency medical centers from January 1, 2011 to July 30, 2016 in Korea In-Depth Accident Study. The results of the study showed that the highway used the most time to prehospital emergency medical response time and was a factor affecting the overall time (${\beta}=.543$, p<.001). In order to shorten the emergency medical response time in highway, the operation of emergency services on the highway, the active use of emergency turn road and the automatic emergency rescue service with individual devices were proposed.

• International Journal of Highway Engineering
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• v.11 no.1
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• pp.153-164
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• 2009

This Paper presents the severity analysis result of the year 2006 national pedestrian crashes using the data base of 37,589 records prepared for the National Police Bureau. A set of attributing factors considered to affect pedestrian crash patterns were selected, and their contributing effects were investigated by applying the Ordered Logit Model. This model was selected because this model has been able to afford satisfactory results when the dependent variable involved ordered severity levels; fatal, injury, and property- damage-only in this investigation. The investigation has unveiled the followings; First, the pedestrian crash patterns were dependent upon human -drivel and pedestrian- characteristics including gender, age, and drinking conditions. Second, other contributing factors included vehicle, roadway geometric, weather, and hour of day characteristics. Third, seasonal effect was not contributive to crash patterns. Finally, the application of the Ordered Logit Model facilitated the ordered severity level analysis of the pedestrian crash data. This paper concludes that conventional wisdom on the pedestrian crash characteristics is largely truthful. However, this conclusion is limited only to the data used in this analysis, and further research is required for its generalization.

• Journal of the Korean Society for Marine Environment & Energy
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• v.7 no.4
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• pp.159-163
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• 2004

This study was performed to estimate the water quality of pH, salinity, dissolved oxygen, ammonium and sulfur hydroxides of sediment in shrimp aquaculture farms of Southwestern coastal of Korea from June to September, 2003. We surveyed the status of water quality and achieved the improve water and sediment quality to restraint the production of ammonium and sulfur hydroxides from sediment of shrimp aquaculture farms. The concentrations of dissolved oxygen increased from noon to the evening for 6 hour and decreased to 2.98 ppm at six o'clock in the next morning and increased repeatedly, even though DO level has a different level in sunny day and cloudy day. This results suggest that the most importance time of the control of DO in shrimp aquaculture farm is next early morning and if the DO concentration increased continuously which may be growing up the concentrations of NH₄/sup +/ and H₂S. The measured of pH and salinity were suitable to growth of shrimp. However, the level of ammonium and sulfur hydroxides produced from the sediments of shrimp aquaculture farms were 2.30 ppm and 0.075 ppm, respectively, which are exceeded to the concentration of guide line for the growth of shrimp. In the results of this study, we found it difficult to improve the water quality using of the present frame of shrimp aquaculture farms. Then, we can improved water quality of DO, NH₄/sup +/ and sediment quality of ORP, H₂S and also achieved down to the rate of shrimp fatal by changed the frame of shrimp aquaculture farms in the scale of laboratory.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.157-165
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• 2011

With respect to the trend of highway traffic accident, highway accident is in decline, whileas, the fatality is on an increasing trend. Thus, many efforts to decrease highway traffic accidents and improve the safety, are required. In particular, in case of highway, the management standard by grade for accident black spot is designated. Thus, investing the effect factors by grade for highway traffic accident is required in detail. Thus, in this study, the factors affecting the traffic accidents among the environmental factors based on the graded data for the accident black spot in the applicable section targeting the Seoul-Pusan Express Highway, were reviewed; accident forecasting model which would analyze the characteristics of the accidents for determining the accident grade, was developed. As a result of establishing a model by using Quantification Theory of Type II, considering the characteristics of the dependent and independent variables based on the geometric structure, 'the fixed variable' among the variables relating to the accident, for the variables influencing over the accident grade, 'the type of vans, a chassis and people', 'the trailers, special vehicles and chassis people' and 'the negligence of watching and cloudy weather' were analyzed as common factors, in case of 'horizontal alignment', 'longitudinal slope' and, 'barricade' respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.480-488
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• 2018

The development of information and communication technology has been carried out actively in the field of agriculture to generate valuable information from large amounts of data and apply big data technology to utilize it. Crops and their varieties are determined by the influence of the natural environment such as temperature, precipitation, and sunshine hours. This paper derives the climatic factors affecting the production of crops using the garlic growth process and daily meteorological variables. A prediction model was also developed for the production of garlic per unit area. A big data analysis technique considering the growth stage of garlic was used. In the exploratory data analysis process, various agricultural production data, such as the production volume, wholesale market load, and growth data were provided from the National Statistical Office, the Rural Development Administration, and Korea Rural Economic Institute. Various meteorological data, such as AWS, ASOS, and special status data, were collected and utilized from the Korea Meteorological Agency. The correlation analysis process was designed by comparing the prediction power of the models and fitness of models derived from the variable selection, candidate model derivation, model diagnosis, and scenario prediction. Numerous weather factor variables were selected as descriptive variables by factor analysis to reduce the dimensions. Using this method, it was possible to effectively control the multicollinearity and low degree of freedom that can occur in regression analysis and improve the fitness and predictive power of regression analysis.

• Journal of the Korea Institute of Building Construction
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• v.19 no.4
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• pp.361-371
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• 2019

In 2017, the ratio of the number of victims and deaths in the construction industry was the highest with 25.2% and 29.6%, respectively. Especially, as safety accidents at construction sites continue to increase, the economic loss is greatly increased too. Therefore, in order to prevent safety accidents in the construction work, the safety risk assessment index by type of construction was developed, and the main results of this study are as follows. First, 17 factors related to safety accidents at construction sites were derived through survey and interview survey, and this study suggested 9 items(process, type of construction, progress rate, contract amount, number of floors, safety education, working days and weather) throughout the expert advisory meeting. Second, the risk assessment index for safety accidents was developed based on the ratio and intensity of safety accidents. Third, to verify the risk assessment model, the construction safety risk assessment index by type of construction was derived by surveying and analyzing the statistics of the construction accident. In addition, the risk strength was calculated by dividing human damage caused by construction safety accidents into those killed and injured. The risk assessment index based on the frequency and intensity of safety accidents by type of construction is expected to be utilized as basic data when assessing the risk of similar projects in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.305-316
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• 2021

Construction accidents occur due to a number of reasons-worker carelessness, non-adoption of safety equipment, and failure to comply with safety rules are some examples. Because much construction work is done outdoors, weather conditions can also be a factor in accidents. Past construction accident data are useful for accident prevention, but since construction accident data are often in a text format consisting of natural language, extracting construction hazards from construction accident data can take a lot of time and that entails extra cost. Therefore, in this study, we extracted construction hazards from 2,026 domestic construction accident reports using text mining and performed a seasonal analysis of construction hazards through frequency analysis and centrality analysis. Of the 254 construction hazards defined by Korea's Ministry of Land, Infrastructure, and Transport, we extracted 51 risk factors from the construction accident data. The results showed that a significant hazard was "Formwork" in spring and autumn, "Scaffold" in summer, and "Crane" in winter. The proposed method would enable construction safety managers to prepare better safety measures against outdoor construction accidents according to weather, season, and climate.

• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.103-119
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• 2008

Traditional market which is characterized by the folksy retailing market has lost its competitiveness rapidly due to the emergence of the Internet and the change of customer's purchasing behavior. The recession of the traditional market contracts the regional economy. We suggest a u-Market, a traditional market with ubiquitous computing capability, to revitalize traditional market. The suggested u-Market system applies ubiquitous computing technologies characterized by communications between customers and objects without limitations of time and location. The proposed u-Market system offers location information and specific contents of traditional market to customers. Furthermore, u-Market system recommends the store and product list that customers are likely to visit and purchase based on their contexts, so they can save their time and effort to search the products or contents.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.561-571
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• 2014

This study analyzes traffic accident severity of old age drivers in fourteen cities and counties of Jeonbuk Province. It is assumed that traffic accident effecting factors have two staged structure by personal and driving environment and urban characteristics. Multilevel Analysis Model is used under the assumption of hierarchical characteristics to analyze factors effecting severity. As the driver's age increases after sixty-five years old, accident damages become severe. The drunk driving is likely to make traffic accident damage more severer. The number of fatal accident by old age drivers is about three time more than by no old age drivers. Old age drivers have higher number of night traffic accidents but severer ones in daytime. Old age drivers show the higher number of traffic accidents but severer ones in fine weather. Wet road surface also influences damage severity and especially old age drivers show higher serious damage and fatal than no old drivers.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.360-365
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• 2014

There are many types of advanced devices for weather prediction process such as weather radar, satellite, radiosonde, and other weather observation devices. Among them, the weather radar is an essential device for weather forecasting because the radar has many advantages like wide observation area, high spatial and time resolution, and so on. In order to analyze the weather radar observation result, we should know the inside structure and data. Some non-precipitation echoes exist inside of the observed radar data. And these echoes affect decreased accuracy of weather forecasting. Therefore, this paper suggests a method that could remove line-shaped non-precipitation echo from raw radar data. The line-shaped echoes are distinguished from the raw radar data and extracted their own features. These extracted data pairs are used as learning data for naive bayesian classifier. After the learning process, the constructed naive bayesian classifier is applied to real case that includes not only line-shaped echo but also other precipitation echoes. From the experiments, we confirm that the conclusion that suggested naive bayesian classifier could distinguish line-shaped echo effectively.