• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.577-585
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• 2010

Traffic accidents are caused by several factors such as drivers, vehicles, and road environment. It is necessary to investigate and analyze them in advance to prevent similar and repetitive traffic accidents. Especially, the human factor is most significant element and traffic accidents by drinking-driving caused from human factor have become social problem to be paid attention to. The study analyzes traffic accidents resulting from drinking-driving and the effects of driver's attributes and environmental factors on them. The study is composed as two parts. First, the log-linear model is applied to analyze that accidents by drinking or non-drinking driving associate with road geometry, weather condition and personal characteristics. Probability is tested for drinking-driving accidents relative to non-drinking drive accidents. The study analyzes probability differences between genders, between ages, and between kinds of vehicles through odds multipliers. Second, traffic accidents related to drinking are classified into property damage, minor injury, heavy injury, and death according to their severity. Heavy injury is more serious than minor one and death is more serious than heavy injury. The ordinal regression models are established to find effecting factors on traffic accident severity.

• The Journal of Korean Philosophical History
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• no.29
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• pp.375-396
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• 2010

The aim of this paper is to suggest some ways of moral education for the building of children's social awareness and relationship skills as social and emotional competencies. Based on the social and emotional learning(SEL), this paper is tried to provide the effective ways to develop children's social awareness and relationship skill. According to SEL, social and emotional competence is the ability to understand, manage, and express the social and emotional aspects of one's life in ways that enable the successful management of life tasks such as learning, forming relationships, solving everyday problems, and adapting to the complex demands of growth and development. And it is also the process of acquiring and effectively applying the knowledge, attitudes, and skills necessary to recognize and manage emotions. Five key competencies such as self-awareness, social awareness, responsible decision making, self-management, relationship skills are taught, practiced, and reinforced through SEL programming. Moral education and social and emotional learning have emerged as two prominent formal approaches used schools to provide guidance for students' behavior. social awareness and relationship skills are necessary for succeeding in school, in the family, in the community, in life in general. Equipped with such skills, attitudes and beliefs, young children are more likely to make healty, caring, ethical, and responsible decisions and to avoid engaging in behaviors with negative consequences such as interpersonal violence and bullying.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.236-238
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• 2022

According to the current Road Traffic Act, the 2020 amendment bill is currently in effect as a system that designates vehicle types for each lane for the purpose of securing road use efficiency and traffic safety. When comparing the number of traffic accident fatalities per 10,000 vehicles in Germany and Korea, the number of traffic accident deaths in Germany is significantly lower than in Korea. The representative case of the German autobahn, which did not impose a speed limit, suggests that Korea's speeding laws are not the only answer to reducing the accident rate. The designated lane system, which is observed in accordance with the keep right principle of the Autobahn Expressway, plays a major role in reducing traffic accidents. Based on this fact, we propose a traffic enforcement system to crack down on vehicles violating the designated lane system and improve the compliance rate. We develop a designated lane enforcement system that recognizes vehicle types using Yolo5, a deep learning object recognition model, recognizes license plates and lanes using OpenCV, and stores the extracted data in the server to determine whether or not laws are violated.Accordingly, it is expected that there will be an effect of reducing the traffic accident rate through the improvement of driver's awareness and compliance rate.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.1-8
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• 2023

If there is a defect in the wheel bearing, which is a major part of the car, it can cause problems such as traffic accidents. In order to solve this problem, big data is collected and monitoring is conducted to provide early information on the presence or absence of wheel bearing failure and type of failure through predictive diagnosis and management technology. System development is needed. In this paper, to implement such an intelligent wheel hub bearing maintenance system, we develop an embedded system equipped with sensors for monitoring reliability and soundness and algorithms for predictive diagnosis. The algorithm used acquires vibration signals from acceleration sensors installed in wheel bearings and can predict and diagnose failures through big data technology through signal processing techniques, fault frequency analysis, and health characteristic parameter definition. The implemented algorithm applies a stable signal extraction algorithm that can minimize vibration frequency components and maximize vibration components occurring in wheel bearings. In noise removal using a filter, an artificial intelligence-based soundness extraction algorithm is applied, and FFT is applied. The fault frequency was analyzed and the fault was diagnosed by extracting fault characteristic factors. The performance target of this system was over 12,800 ODR, and the target was met through test results.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.79-85
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• 2023

Skid resistance pavement is an accessory to the road and is a facility for the safe driving of cars by increasing the skid resistance of road pavement. In particular, in bad weather conditions such as snow, rain, and black ice, the skid resistance performance of skid resistance pavement greatly affects the safety of road traffic and drivers. However, BPT(British Pendulum Tester) has a test area of only 0.009 m², making it difficult to represent the overall packaging surface. A reliable method of evaluating slip resistance performance is needed for maintaining non-slip packaging. In this study, the conventional BPT test and the skid resistance performance evaluation method of the PFT(Pavement Friction Tester) and µGT(Micro Grip Tester) tests were compared through guidelines and standard investigations and applied to the field skid resistance performance evaluation. In addition, skid resistance pavement with different skid resistance performance was installed at the test-bed and actual road demonstration sites to compare BPN(British Pendulum Number), SN(Skid Number), GN(Grip Number), and to derive correlations for each performance evaluation method. As a result of the experiment, SN and GN showed similar skid resistance performance, and the GN value was derived similar to BPN × 0.01.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.81-89
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• 2023

In modern society, blind people face difficulties in navigating common environments such as sidewalks, elevators, and crosswalks. Research has been conducted to alleviate these inconveniences for the visually impaired through the use of visual and audio aids. However, such research often encounters limitations when it comes to practical implementation due to the high cost of wearable devices, high-performance CCTV systems, and voice sensors. In this paper, we propose an artificial intelligence fusion algorithm that utilizes low-cost video sensors integrated into smartphones to help blind people safely navigate their surroundings during walking. The proposed algorithm combines motion capture and object detection algorithms to detect moving people and various obstacles encountered during walking. We employed the MediaPipe library for motion capture to model and detect surrounding pedestrians during motion. Additionally, we used object detection algorithms to model and detect various obstacles that can occur during walking on sidewalks. Through experimentation, we validated the performance of the artificial intelligence fusion algorithm, achieving accuracy of 0.92, precision of 0.91, recall of 0.99, and an F1 score of 0.95. This research can assist blind people in navigating through obstacles such as bollards, shared scooters, and vehicles encountered during walking, thereby enhancing their mobility and safety.

• Information Systems Review
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• v.25 no.4
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• pp.113-130
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• 2023

Due to economic development and increasing gross national income, the number of automobiles continues to rise, leading to a serious issue of illegal parking due to limited road conditions and insufficient parking facilities. Illegal parking causes significant inconvenience and displeasure to people and can even result in accidents and loss of lives. The severity of accidents and their consequences, related to the growing number of vehicles and illegal parking, is escalating, particularly in the metropolitan areas. Consequently, efforts are being made to address this problem as a cause of social issues and come up with measures to reduce illegal parking. In particular, half of the public complaints in the metropolitan area are related to illegal parking, and the highest physical and human damage occurs in Gyeonggi. Thus, this study aims to use machine learning techniques based on data related to illegal parking in Suwon city, Gyeonggi, to categorize regional characteristics and propose effective measures to crack down on illegal parking. Additionally, practical, social, policy, and legal measures to decrease illegal parking in the metropolitan area are suggested. This study has academic significance in that it solved the problem of illegal parking, which is mentioned as one of the social problems that cause traffic congestion, by classifying regional characteristics using K-prototype, a machine learning algorithm. Furthermore, the results of this study contribute to practical and social aspects by providing measures to decrease illegal parking in the metropolitan area.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.33 no.6
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• pp.216-225
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• 2023

This paper describes the finite element analysis and die design change of cold heading punching process to increase the cold forging tool life and reduce the tool wear and stress concentration. Through this study, the optimization of punch tool design has been studied by an analysis of tool stress and wear distribution to improve the tool life. Plastic deformation analysis was carried out in order to understand the cold heading process between tool and workpiece stress distribution. Cold heading punch die design was set up to each process with different four types analysis progressing, the cold heading punch dies shapes with combination of point angle and punch edge corner radius shapes of cold forging dies, punch die material properties and frictional coefficient. The design parameters of point angle and corner radius of punch die geometry, die material properties and frictional coefficient were selected to apply optimization with the DoE (design of experiment) and Taguchi method. DoE and Taguchi method was performed to optimize the cold heading punch die design parameters optimization for bolt head cold forging process, it was possible to expect an reduce the cold heading punch die wear to the 37 % compared with current using cold heading punch in the shop floor.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.413-419
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• 2023

Light Emitting Diodes(LEDs) are widely utilized not only in lighting but also in various applications such as mobile phones, automobiles, displays, etc. The integration of LED lighting with communication, specifically Visible Light Communication(VLC), has gained significant attention. This paper presents the direct implementation and experimentation of a Vehicle-to-Vehicle(V2V) Visible Light Communication system using commonly used red and yellow LEDs in typical vehicles. Data collected from the leading vehicle, including positional and speed information, were modulated using Non-Return-to-Zero On-Off Keying(NRZ-OOK) and transmitted through the rear lights equipped with red and yellow LEDs. A photodetector(PD) received the visible light signals, demodulated the data, and restored it. To mitigate the interference from fluorescent lights and natural light, a PD for interference removal was installed, and an interference removal device using a polarizing filter and a differential amplifier was employed. The performance of the proposed visible light communication system was analyzed in an ideal case, indoors and outdoors environments. In an outdoor setting, maintaining a distance of approximately 30[cm], and a transmission rate of 4800[bps] for inter-vehicle data transmission, the red LED exhibited a performance improvement of approximately 13.63[dB], while the yellow LED showed an improvement of about 11.9[dB].

• Knowledge Management Research
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• v.24 no.4
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• pp.131-152
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• 2023

One of the key domains within a smart tourism city, smart mobility, encompasses advanced transportation means and services rooted in Information and Communication Technology (ICT). This includes shared bicycles, scooters, car-sharing services, smart transportation infrastructure, and more, aiming to surpass limitations of conventional transport and improve the movement of people and goods. It also serves tourists as an affordable and convenient mode of transport between attractions while also enhancing the overall travel experience. This study has defined 'smart tourism mobility' as a form of mobility grounded in ICT, exhibiting exceptional connectivity, serving public interest, and serving as a mode of transport for both residents and tourists in a smart tourism city. The research aimed to outline the scope of smart tourism mobility-related industries through expert Delphi surveys and estimate their economic effects within a smart tourism city. Specifically, this study updated 2015 input-output table and made 2020 regional input-output table of Seoul adopting RAS method and location quotient method. The results showed that the about 2.8 billion KRW investment of Seoul in smart tourism mobility may create more than 4.1 billion KRW in production inducement effect which is expected to create more than 1.6 billion KRW of income-inducing effect, 3.6 billion KRW of value-added-inducing effect, and 54 employment across all industries in Seoul in 2022.