• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1183_1184
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• 2009

The synchronized visual message system device of level crossing provides warning system with the use of developed corresponding technology when the train is approaching forward to limited distance in level crossing. To ensure of safety driving for coming transit from road, it detect the location and velocity of train and transport the information to wayside warning device to prevent the collision with train. This paper is about the detailed design of synchronize VMS for passing transit at the level crossing and develop the physical contents of level crossing VMS with expression words, operational device, massage transportation algorism which are based on the proto type study of communication method and information contents for level crossing VMS.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.2_2
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• pp.163-171
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• 2020

The condition of tire tread is a key parameter closely related to the driving safety of a vehicle, which affects the contact force of the tire for braking, accelerating and cornering. The major factor influencing the contact force is tread wear, and the more tire tread wears out, the higher risk of losing control of a vehicle exits. The tire tread condition is generally checked by visual inspection that can be easily forgotten. In this paper, we propose the intelligent tire (iTire) system that consists of an acceleration sensor, a wireless signal transmission unit and a tread classifier. In addition, we also presents classification algorithm that transforms the acceleration signal into the frequency domain and extracts the features of several frequency bands as inputs to an artificial neural network. The artificial neural network for classifying tire wear was designed with an Multiple Layer Perceptron (MLP) model. Experiments showed that tread wear classification accuracy was over 80%.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.50-58
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• 2015

The research on autonomous vehicle that expected to greatly reduce accidents by driver's mistakes is increasing in the development of technology. The purpose of this research is to identify the factor that affect trust in autonomous vehicles and analyze the requirements of the driver in autonomous vehicles environment. Therefore, in this study, we defined the information and functions provided by the autonomous vehicles through the investigation of the prior studies, conducted a questionnaire survey and focused group interview (FGI). The results show that competency, error management were important factors influencing trust in autonomous vehicles and identified that driver took safety related information as high priority in autonomous vehicle. Also, it was identified that driver prefer to perform the multimedia function in autonomous vehicle environment. The study is looking forward to be the reference data for design of advanced autonomous vehicle. It will contribute to the improvement of the convenience and satisfaction of the drivers.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.3
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• pp.481-489
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• 2020

Safety and security during the handling of hazardous materials is a great concern for anyone in the field. One driving point in the security field is the ability to detect the source of the danger and take action against it as quickly as possible. Via the usage of a fully convolutional network, it is possible to create the label map of an input image, indicating what object is occupying the specific area of the image. This research employs the usage of U-net, which was constructed in biomedical field segmentation to segment cells, instead of the original FCN. One of the challenges that this research faces is the availability of ground truth with precise labeling for the dataset. Testing the network after training resulted in some images where the network pronounces even better detail than the expected label map. With better detailed label map, the network might be able to produce better segmentation is something to be studied in further research.

• Journal of Korean Tunnelling and Underground Space Association
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• v.13 no.5
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• pp.385-393
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• 2011

As the economic growth achieved and the straight road was increased. so, the tunnel built more than before. In these days, lighting of tunnel entrance is important for safety and comfortable driving. Most of the tunnel lighting depend on artificial lighting and they use a lot of energy. In this paper, as a research for illumination improvement and saving energy at tunnel, reflecting mirror system is suggested. The performance of the system was evaluated with respect to various aspects. By applying a reflective mirror system, tunnel lighting and environment can be improved. This study is a preliminary study for developing a system to save energy of tunnel artificial lighting.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.2
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• pp.92-97
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• 2011

Vehicle lightings are very important for safe driving during night time. Since the eye recovery time after an exposure to oncoming headlights would take after several seconds, the aiming point of vehicle head lamps have to pass safety requirements. Despite the fact that vehicle inclination is variable with vehicle load conditions, the head lamps aiming point is usually fixed at a constant position which is set by car manufacturer. Consequently, vehicle head lamps under varying load conditions often make people in the opposing vehicle uncomfortable, and even worse, can cause an accident. This paper presents an active vehicle lighting mechanism to automatically adjust its aiming point, or cut-off line, in order to compensate the change in vehicle inclination resulting from load variations. The effectiveness of the proposed method is demonstrated through a set of simulations and experiments with a real vehicle.

• Knowledge Management Research
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• v.15 no.3
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• pp.189-208
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• 2014

In spite of its popularity among practitioner and academic audiences, few existing studies go into any detail in examining the mechanisms of creating shared value (CSV), especially as applicable to the context of everyday operations. Nor do they provide recommendations to practitioners with regard to facilitating CSV concept. In response to this problem, I introduce benefit-sharing practice which I argue provides a solid route to the concept of CSV. Based on observations from the case study, 10 networks' benefit-sharing practices are analyzed and its featured characteristics are extracted accordingly. Findings demonstrate that such benefit-sharing models as 'Green-Development', 'Protection of the Environment', and 'Accreditation for Food Safety Management' can solve critical societal challenges while simultaneously driving greater profitability for both buyers and suppliers. The findings also suggest that benefit-sharing is a good vehicle of the realization of the CSV concept. I conclude by assessing how the findings add to the existing debate around collaborative supply-relationship and shared value. I suggest that benefit-sharing can contribute positively to the feasibility of CSV concept and, thereby, counter the assertion that CSV is the only immature-concept that lacks clear criteria of demarcation and cases for businesses to follow.

• Journal of Multimedia Information System
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• v.4 no.1
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• pp.9-18
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• 2017

Ubiquitous computing is a novel paradigm that is rapidly gaining in the scenario of wireless communications and telecommunications for realizing smart world. As rapid development of sensor technology, smart sensor system becomes more popular in automobile or vehicle. In this study, a new vehicle detection mechanism in real-time for blind spot area is proposed based on imaging sensors. To determine the position of other vehicles on the road is important for operation of driver assistance systems (DASs) to increase driving safety. As the result, blind spot detection of vehicles is addressed using an automobile detection algorithm for blind spots. The proposed vehicle verification utilizes the height and angle of a rear-looking vehicle mounted camera. Candidate vehicle information is extracted using adaptive shadow detection based on brightness values of an image of a vehicle area. The vehicle is verified using a training set with Haar-like features of candidate vehicles. Using these processes, moving vehicles can be detected in blind spots. The detection ratio of true vehicles was 91.1% in blind spots based on various experimental results.

• Journal of the Korean Society for Railway
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• v.9 no.2 s.33
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• pp.230-236
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• 2006

For a short-term measurement to reduce an accident on a railroad crossing, it is necessary to find out the weakness and problems of existing equipment in the railroad transportation system. The analysis of railroad crossing accidents shows that main causes of accidents (24.9%) are the careless driving including an engine problem, damage on the safety equipment, slide on the snow, and an engine stop on the railroad crossing. Therefore, it is required to install a sensor, or to make a crossing gate at the exist for detecting obstacles on a railroad to prevent collisions among trains. This paper suggests 'a panel sensor using the strain gauge' to make up the weaknesses of the sensing Dead Zone, which are caused by using a laser method, and to detect any small objects passing railroads in order to reduce the errors, which are occurred in the earth magnetic field for controlling Exit Slide Crossing Arm Detector. The device, suggested in this paper, is verified with detecting any small objects passing the railroad, with judging entry decision clearly, and with controlling passing gate and obstruction warnings/cautions obstacles at the same time, through an experimental test.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.123-132
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• 2017

Traffic lights contain very important information for safety driving. So, the delivery of the information to drivers in real-time is a very critical issue for advanced driver assistance systems. However, traffic light detection is quite difficult because of the small sized traffic lights and the occlusion in real world. In this paper, a traffic light detection method using modified color based saliency map and morphological information is proposed. It shows 98.14% of precisions and 83.52% of recalls on computer simulations.