• Journal of Korean Society for Atmospheric Environment
• /
• v.25 no.6
• /
• pp.539-549
• /
• 2009

The purpose of this study is to estimate hourly Asian dust emission flux in springtime by using the optimized Weather Research Forecasting model (WRF) in order to accurately predict the horizontal flux of Asian dusts. Asian dust emission flux using 5 empirical formulas such as US EPA, Park and Inn, Wang, The Goddard Chemistry Aerosol Radiation and Transport (GOCART) and Dust Entrainment and Deposition (DEAD) were calculated and compared by using classified land-use types and size distribution at various locations in China and Mongolia together with the hourly meteorological elements of the WRF model. As a result, the empirical formula in US EPA among them, which was considered the various conditions such as vegetation, soil type and terrain, was better than the other 4 empirical formulas. However, these formulas were adjusted hourly and vertically in time and space because there was different order and time resolution of dust emissions from original empirical formulas.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.9
• /
• pp.1337-1346
• /
• 2015

In this paper, pattern classifier is designed to classify precipitation and non-precipitation events from weather radar data. The proposed classifier is based on Fuzzy Neural Network(FNN) and consists of three FNNs which operate in parallel. In the proposed network, the connection weights of the consequent part of fuzzy rules are expressed as two polynomial types such as constant or linear polynomial function, and their coefficients are learned by using Least Square Estimation(LSE). In addition, parametric as well as structural factors of the proposed classifier are optimized through Differential Evolution(DE) algorithm. After event classification between precipitation and non-precipitation echo, non-precipitation event is to get rid of all echo, while precipitation event including non-precipitation echo is to get rid of non-precipitation echo by classifier that is also based on Fuzzy Neural Network. Weather radar data obtained from meteorological office is to analysis and discuss performance of the proposed event and echo patter classifier, result of echo pattern classifier compare to QC(Quality Control) data obtained from meteorological office.

• International Journal of Highway Engineering
• /
• v.15 no.2
• /
• pp.139-147
• /
• 2013

PURPOSES : This study aims to draw differences between primary and secondary crashes by comparing crash characteristics and to identify the unique characteristics of secondary crashes for making better effective countermeasures to reduce secondary crashes. METHODS : The characteristics of secondary crashes were compared to those of primary crashes through a two sample proportional test (z-test). RESULTS : The results showed that vehicle-to-vehicle crashes and vehicle-to-person crashes are dominant crash types in secondary crashes. Compared to primary crashes, secondary crashes were likely to occur during nighttime. With respect to season and weather, the proportion of secondary crashes occurred during winter and in snowy weather is relatively higher than that of primary crashes. The main causes of primary crashes were found to be drowsiness, speeding, and exaggerated steering control, whereas main factors affecting the occurrence of secondary crashes were negligence of keeping eyes forward and no keeping a safe distance as expected. CONCLUSIONS : The characteristics affecting the occurrence of secondary crashes are different from those of primary crashes, indicating that proper countermeasures should be established to prevent the occurrence of secondary crashes on highways.

• KIEAE Journal
• /
• v.6 no.3
• /
• pp.49-56
• /
• 2006

The roof among the outer surfaces of buildings is an optimum place to install PV since it is the best favorable part in the building to be exposed to day light. Especially, in case of module of BIPV for Roof, it should have essentially the functions of both electricity generation and roof-finish as a construction material. The followings are the results of the study which has analyzed the architectural conditions and applications thereof at the job site. -The aesthetic function of BIPV module is very important because the roof, mostly located at the top of the buildings, is easily recognized and affects outer interior design of the building a lot. -The heat proof of BIPV for Roof could affect the energy consumption through the roof having a wide area. -For architectural condition to the weather, the roof has to ensure the stability of the weather, humidity proof, and airtightness to the wind respectively. -For architectural condition of the structure, endurance by physical power such as stability of both combining and fixing and transfer of load should be ensured. -For residents protection, it has also architectural functions to secure for the space and shield ozone, UV and noxious substances. -Through its practical applications, It is already confirmed that there are various types of BIPV modules overseas and its application has been proved successfully.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.8 no.1
• /
• pp.22-27
• /
• 2006

Many aspects of climate have been observed to be increasingly volatile during the past several decades. Episodic climate change is not considered to be uncommon. However, there are substantial environmental, social, and economic impacts associated with climate variability that can be managed if the climate and its impacts are properly understood. Plants and natural communities exhibit several types of adaptive strategy to climate change. There is ample reason to relate increasingly erratic weather with a warming climate. Historic climate extremes, the adaptive mechanisms plants exhibit, and how people have (or have not) responded with strategically sound concepts and policy to facilitate a sustainable environmental ethic are reviewed with a vision of international needs and economic stability.

• Journal of Environmental Science International
• /
• v.28 no.11
• /
• pp.1047-1059
• /
• 2019

To address the increase of weather hazards and the emergence of new types of such hazards, an optimization technique for three-dimensional (3D) representation of meteorological facts and atmospheric information was examined in this study as a novel method for weather analysis. The proposed system is termed as "meteorological and air quality information visualization engine" (MAIVE), and it can support several file formats and can implement high-resolution 3D terrain by employing a 30 m resolution digital elevation model. In this study, latest 3D representation techniques such as wind vector fields, contour maps, stream vector, stream line flow along the wind field and 3D volume rendering were applied. Implementation of the examples demonstrates that the results of numerical modeling are well reflected, and new representation techniques can facilitate the observation of meteorological factors and atmospheric information from different perspectives.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.6 no.5
• /
• pp.311-317
• /
• 2011

The blind spot is an area where drivers visibility does not reach. When drivers change a lane to adjacent lane, they need to give an attention because of the blind spot. If drivers try to change lane without notice of vehicle approaching in the blind spot, it causes a reason to have a car accident. This paper proposes a night-time blind spot vehicle detection using cameras. At nighttime, head-lights are used as characteristics to detect vehicles. Candidates of headlight are selected by high luminance feature and then shape filter and kalman filter are employed to remove other noisy blobs having similar luminance to head-lights. In addition, vehicle position is estimated from detected head-light, using virtual center line represented by approximated the first order linear equation. Experiments show that proposed method has relatively high detection porformance in clear weather independent to the road types, but has not sufficient performance in rainy weather because of various ground reflectors.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.45 no.2
• /
• pp.20-29
• /
• 2022

This study intends to present a traffic node-based and link-based accident prediction models using XGBoost which is very excellent in performance among machine learning models, and to develop those models with sustainability and scalability. Also, we intend to present those models which predict the number of annual traffic accidents based on road types, weather conditions, and traffic information using XGBoost. To this end, data sets were constructed by collecting and preprocessing traffic accident information, road information, weather information, and traffic information. The SHAP method was used to identify the variables affecting the number of traffic accidents. The five main variables of the traffic node-based accident prediction model were snow cover, precipitation, the number of entering lanes and connected links, and slow speed. Otherwise, those of the traffic link-based accident prediction model were snow cover, precipitation, the number of lanes, road length, and slow speed. As the evaluation results of those models, the RMSE values of those models were each 0.2035 and 0.2107. In this study, only data from Sejong City were used to our models, but ours can be applied to all regions where traffic nodes and links are constructed. Therefore, our prediction models can be extended to a wider range.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.26 no.1
• /
• pp.23-48
• /
• 2022

In this paper, we provide predictive models for the market price of fruits, and analyze the performance of each fruit price predictive model. The data used to create the predictive models are fruit price data, weather data, and Korea composite stock price index (KOSPI) data. We collect these data through Open-API for 10 years period from year 2011 to year 2020. Six types of fruit price predictive models are constructed using the LSTM algorithm, a special form of deep learning RNN algorithm, and the performance is measured using the root mean square error. For each model, the data from year 2011 to year 2018 are trained to predict the fruit price in year 2019, and the data from year 2011 to year 2019 are trained to predict the fruit price in year 2020. By comparing the fruit price predictive models of year 2019 and those models of year 2020, the model with excellent efficiency is identified and the best model to provide the service is selected. The model we made will be available in other countries and regions as well.

• Journal of Environmental Science International
• /
• v.21 no.8
• /
• pp.939-951
• /
• 2012

This study is conducted to estimate the air temperature decreasing effects by restoring urban streams using WRF/CALMET coupled system. The types of land use on covered streams are constructed with the land cover map from Korea ministry of environment. Restoring covered streams changes the types of land use on covered areas to water. Two different types of land use(CASE 1 and CASE 2) are inputted to the WRF/CALMET coupled system in order to calculate the temperature difference. The results of the WRF/CALMET coupled system are similar to the observed values at automatic weather stations(AWS) in Busan area. Restoring covered streams causes temperature to be decreased by about $0.34{\sim}2^{\circ}C$ according to the locations of streams and the regions that temperature is reduced are widely distributed over the restored area. Reduction of temperature is increased rapidly from morning and maximus at 13LST. Natural restoration of streams will reduce the built-up area within urban. With this, temperature reductions which are the cause to weaken the urban heat island appear. Relief of urban heat island will help to improve the air quality such as accumulation of air pollutants in within urban area.