• Journal of Korean Society of Transportation
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• v.20 no.2
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• pp.105-115
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• 2002

For many rears, traffic accident statistics are the most direct measure of safety for a signalized intersection. However it takes more than 2 or 3 yearn to collect certain accident data for adequate sample sizes. And the accident data itself is unreliable because of the difference between accident data recorded and accident that is actually occurred. Therefore, it is rather difficult to evaluate safety for a intersection by using accident data. For these reasons, traffic conflict technique(TCT) was developed as a buick and accurate counter-measure of safety for a intersection. However, the collected conflict data is not always reliable because there is absence of clear criteria for conflict. This study developed objective and accurate conflict criteria, which is shown below based on traffic engineering theory. Frist, the rear-end conflict is regarded, when the following vehicle takes evasive maneuver against the first vehicle within a certain distance, according to car-following theory. Second, lane-change conflict is regarded when the following vehicle takes evasive maneuver against first vehicle which is changing its lane within the minimum stopping distance of the following vehicle. Third, cross and opposing-left turn conflicts are regarded when the vehicle which receives green sign takes evasive maneuver against the vehicle which lost its right-of-way crossing a intersection. As a result of correlation analysis between conflict and accident, it is verified that the suggested conflict criteria in this study ave applicable. And it is proven that estimating safety evaluation for a intersection with conflict data is possible, according to the regression analysis preformed between accident and conflict, EPDO accident and conflict. Adopting the conflict criteria suggested in this study would be both quick and accurate method for diagnosing safety and operational deficiencies and for evaluation improvements at intersections. Further research is required to refine the suggested conflict criteria to extend its application. In addition, it is necessary to develope other types of conflict criteria, not included in this study, in later study.

• Journal of Bio-Environment Control
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• v.22 no.3
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• pp.284-290
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• 2013

This study analyzed the geometric, compressive, cutting and friction properties of oriental melons in order to design a gripper capable of soft handling and a cutter for cutting oriental melon vine among the end effector of oriental melon as a preliminary step for developing the end effector of the robot capable of harvesting oriental melons in protected cultivation. As a result, the average length, diameter at the midpoint, weight, volume and roundness of the oriental melons were 108 mm, 70 mm, 188 g, 333 mL and 3.8 mm. Nonlinear regression analysis was performed on the equation $W=L^a{\times}D_2^b$ with variation of the length (L) and diameter (D2) of the weight (W) of the oriental melons. As a result, it was shown that there was a correlation between a of 2.0279 and b of -0.9998 as a constant value. The average diameter of the oriental melon vine was 3.8 mm, and most vines were distributed within a radius of 5 mm from the center. The average yield value, compressive strength and hardness of the oriental melons were $36.5N/cm^2$, $185.7N/cm^2$ and $636.7N/cm^2$, respectively. The average cutting force and shear strength of the oriental melon vines were $2.87{\times}10^{-2}\;N$ and $5.60N/cm^2$, respectively. The maximum friction coefficient of the oriental melons was rubber of 0.609, followed by aluminium of 0.393, stainless steel of 0.177 and teflon of 0.079. It was considered possible to apply it to the size of the gripper and cutter, turning radius, dynamics of drive motor and selection of materials and their quality in light of the position error and safety factor according to the movement when designing end effector based on the analyzed data.

• Journal of Korea Water Resources Association
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• v.42 no.1
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• pp.33-50
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• 2009

The impact on hydrologic components considering future potential climate, land use change and vegetation cover information was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated (1999 - 2000) and validated (2001 - 2002) for the upstream watershed ($260.4\;km^2$) of Gyeongancheon water level gauging station with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.77 to 0.60 and 0.79 to 0.60, respectively. Two GCMs (MIROC3.2hires, ECHAM5-OM) future weather data of high (A2), middle (A1B) and low (B1) emission scenarios of the IPCC (Intergovernmental Panel on Climate Change) were adopted and the data was corrected by 20C3M (20th Century Climate Coupled Model) and downscaled by Change Factor (CF) method using 30 years (1977 - 2006, baseline period) weather data. Three periods data of 2010 - 2039 (2020s), 2040 - 2069 (2050s), 2070 - 2099 (2080s) were prepared. To reduce the uncertainty of land surface conditions, future land use and vegetation canopy prediction were tried by CA-Markov technique and NOAA NDVI-Temperature relationship respectively. MIROC3.2 hires and ECHAM5-OM showed increase tendency in annual streamflow up to 21.4 % for 2080 A1B and 8.9 % for 2050 A1B scenario respectively. The portion of future predicted ET about precipitation increased up to 3 % in MIROC3.2 hires and 16 % in ECHAM5-OM respectively. The future soil moisture content slightly increased compared to 2002 soil moisture.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.59 no.3
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• pp.299-306
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• 2014

Fresh edible sweet corns demand relatively short period to harvest fresh ears, which can allow farmers to make a choice sweet corns for various cropping systems. For this reason, we were to find the optimum planting date of late-planted sweet corns to sell fresh ears in the autumn linked to cropping system with winter crops, investigating yield and properties of marketable fresh ears and growth traits of sweet corns (cv. 'Godangok' and cv. 'Guseulok') depending on planting dates such as 10 July, 20 July, and 30 July in Suwon 2012 and 2013, respectively. The 20 July-planted sweet corns showed the most fresh ear yield. However, the 10 July-planted and the 30 July-planted had 32% less yield caused by consecutive rainfall from 10 July through 20 July, and 15% less yield due to low air temperature during ripening than the 20 July-planted, respectively. The 10 and 20 July-planted sweet corns had average 140g of a fresh ear weight and 15% heavier ear than the 30 July-planted. For the July-planted sweet corns, silking days after planting ($r=-0.80^{**}$), and harvesting days after silking ($r=-0.97^{**}$) and planting ($r=-0.91^{**}$) were highly negatively correlated with daily mean air temperature during the period, resulting in it takes 1,100 growing degree days (GDD) to harvest fresh ears from the July-planted sweet corns. The fresh ears of the 20 July-planted sweet corns are able to be harvested by early October. Therefore it will be a good choice for the cropping system based on winter vegetable cash crops such as temperate garlic and onion with medium or late maturity. Among three planting dates 20 July-planted sweet corns had the best field performance in every year considering fresh ear yield, ear size, and stability to grow.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.