• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.833-836
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• 2013

In this paper, we proposed an intelligent surveillance system which can be determined by the overspeed of vehicle which continuously collects by video imaging device. Imaging device to capture images continuously, and filtering errors that occur as a natural, long-distance moving objects by comparing the images collected before and after the images. To measure the size of things, it proves that able to measure speed of the vehicle, depending on the amount of growing pixels using the pixel processing.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.164-181
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• 2023

In a low speed limit environment, the speed limit tolerance of automated traffic enforcement devices is very high, which is one of the main factors for the low compliance rate. Therefore, in this study, we aimed to the improve the speed limit tolerance and to present a new standard. The effects of the operator and user errors that can cause speeding by drivers were analyzed. Based on the results of the analysis, an improvement of the tolerance was proposed by applying an error in the enforcement device and GPS speed. In addition, long-term expected safety effects such as the accident rate and severity were estimated from the operator's perspective when improving the tolerance. As a result of the estimation, the speed limit compliance rate, accident rate, and change rate of a number of severe accidents due to speed change, and pedestrian traffic accident mortality rate were all improved in all speed limit environments. The introduction of the proposed improvement is expected to improve road safety significantly.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.19
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• pp.191-223
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• 2003

Electronic commerce and the Internet offer unprecedented opportunities. The explosive expansion of the use of the Internet makes it possible for businesses to expand their markets and render services. Global transaction costs are easy to cut off using Internet and transaction speed is faster than before. Where cyberspace is not free from claims, Offline transaction can lead to problems and disputes the same is for cyberspace transactions. However ADR is not meet for the online transaction for speed, cost and open network system, ODR methods to resolve electronic commerce conflicts is crucial for building confidence and permitting access to justice in an online business environment. The use of the Internet and the network in dispute resolution has an impact on the types of communication implied in the relevant processes such as automated negotiation, online mediation and online arbitration and involves new technological issues such as the integrity and confidentiality of data and communication used to transmit and store data. Among the ODR systems Online Arbitration is currently binding both parties disputed and can achieve the aim of dispute award the same as the traditional arbitration. Arbitration is based on the New York Convention 1958, Arbitration Model law 1985 and national Arbitration Act that are founded on territorial area and rested on arbitration agreement, constitution of the arbitral tribunal, due process, final and binding award and enforcement of the arbitration award. To compare with this issues Online arbitration has unnecessarily legal unstability and risk. ODR is the burgeoning field and has created a new issues. All such issues which have been debated in the ADR are composed with ODR. But these are not limited Some of issues are further complicated by the nature of the online environment such as confidentiality and principle of parties. It is true that online arbitration should comply with legal provisions, but which is impossible to adhere of the law. Flexible translation and functional equivalence of legal provisions are needed for acceptance of electronic commerce disputes. Finally electronic commerce now takes place on the Internet, it is inevitable that the commercial world wants access to dispute resolution process that best suits the new commercial environment. ODR methods are processing for development and legal issues are considered by both national and international authorities. Introduction of new Conventions or amend Convention and Model law of ODR comes near.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.64-80
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• 2018

In Korea, citizens can only know general information about crime. Thus it is difficult to know how much they are exposed to crime. If the police can predict the crime risky area, it will be possible to cope with the crime efficiently even though insufficient police and enforcement resources. However, there is no prediction system in Korea and the related researches are very much poor. From these backgrounds, the final goal of this study is to develop an automated crime prediction system. However, for the first step, we build a big data set which consists of local real crime information and urban physical or non-physical data. Then, we developed a crime prediction model through machine learning method. Finally, we assumed several possible scenarios and calculated the probability of crime and visualized the results in a map so as to increase the people's understanding. Among the factors affecting the crime occurrence revealed in previous and case studies, data was processed in the form of a big data for machine learning: real crime information, weather information (temperature, rainfall, wind speed, humidity, sunshine, insolation, snowfall, cloud cover) and local information (average building coverage, average floor area ratio, average building height, number of buildings, average appraised land value, average area of residential building, average number of ground floor). Among the supervised machine learning algorithms, the decision tree model, the random forest model, and the SVM model, which are known to be powerful and accurate in various fields were utilized to construct crime prevention model. As a result, decision tree model with the lowest RMSE was selected as an optimal prediction model. Based on this model, several scenarios were set for theft and violence cases which are the most frequent in the case city J, and the probability of crime was estimated by $250{\times}250m$ grid. As a result, we could find that the high crime risky area is occurring in three patterns in case city J. The probability of crime was divided into three classes and visualized in map by $250{\times}250m$ grid. Finally, we could develop a crime prediction model using machine learning algorithm and visualized the crime risky areas in a map which can recalculate the model and visualize the result simultaneously as time and urban conditions change.