• Journal of Navigation and Port Research
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• v.41 no.6
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• pp.445-450
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• 2017

It is necessary to set a route to reflect the traffic flow for the safety of the traffic vessels. This ongoing analysis is needed to ensure that the vessels comply with a route. The purpose of this study is to discover the problems of the recommended route vicinity for Wando Harbor and suggest an improvement plan. We used a support vector machine based on the ship's trajectory to establish an efficient route center line. Since the vessels should navigate to the starboard side, with reference to the center line of the recommended route, the trajectories of the vessels were divided into two clusters. The support vector machine is being used in many fields such as pattern recognition, and it is effective for this binary classification. As a result of this study, about 79.5 % of the merchant eastbound ships in a 2.4 NM distance to Jangjuk Sudo did not observe the recommended route, so the risk of collision always existed. The contraflow traffic rate of the route of the eastbound ships decreased from 79.5 % to 30.9 % when the recommended route was reset about 300 meters to the north, from its present position. The support vector machine applied in this study is expected to be applicable, to effectively set the route center line because the ship trajectories can be classified into two clusters.

• Journal of Korean Society of Transportation
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• v.30 no.6
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• pp.27-36
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• 2012

In Korea, 28,641 cases of traffic accidents were caused by drunk driving in 2010. These statistics accounted for 12.62% of total number of traffic accidents. Moreover, the percentages of deaths and injuries from them were nearly 15% of those from whole traffic accidents. While police has emphasized enforcement efforts in order to reduce drunk driving, culture generous to drunk driving in addition to the absence of an appropriate intervention system for habitual drunk drivers have contributed to the increasing number of the drunk driving accidents in Korea. This study examined specific behavioral changes in drunk driving by comparing drivers' behavior pattern in non-alcoholic condition to those in alcoholic condition, using a psychomotor test and a driving simulator. In the psychomotor test measuring participants' reactions to the target stimulus, it was revealed that participants' correct responses were decreased, false responses were increased, and no responses also were increased after drinking. Furthermore, in the driving simulator performance after drinking, not only driving speed was faster but also the deviation of an accelerator pedal pressure and of the vehicle's lateral position were much increased. These results indicated that alcohol consumption would impair visio-cognitive ability and deteriorate driving safety. Finally, the implications and limitations of our findings and suggestions for the future research were discussed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.132-145
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• 2022

This study was based on the black box images of traffic accidents on highways, cluster analysis and prediction model comparisons were carried out. As analysis data, vehicle driving behavior and road surface conditions that can grasp road and traffic conditions just before the accident were used as explanatory variables. Considering that traffic accident data is affected by many factors, cluster analysis reflecting data heterogeneity is used. Each cluster classified by cluster analysis was divided based on the ratio of the severity level of the accident, and then an accident prediction evaluation was performed. As a result of applying the Logit model, the accident prediction model showed excellent predictive ability when classifying groups by cluster analysis and predicting them rather than analyzing the entire data. It is judged that it is more effective to predict accidents by reflecting the characteristics of accidents by group and the severity of accidents. In addition, it was found that a collision accident during stopping such as a secondary accident and a side collision accident during lane change act as important driving behavior variables.

• Convergence Security Journal
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• v.22 no.4
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• pp.161-168
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• 2022

After the corona virus, as non-face-to-face services are activated, domain services that guarantee integrity by embedding sensing information of the Internet of Things (IoT) with block chain technology are expanding. For example, in areas such as safety and security using CCTV, a process is required to safely update firmware in real time and to confirm that there is no malicious intrusion. In the existing safe security processing procedures, in many cases, the person in charge performing official duties carried a USB device and directly updated the firmware. However, when private blockchain technology such as Hyperledger is used, the convenience and work efficiency of the Internet of Things environment can be expected to increase. This article describes scenarios in how to prevent vulnerabilities in the operating environment of various customers such as firmware updates and device changes in a non-face-to-face environment. In particular, we introduced the optimal blockchain technique for the Internet of Things (IoT), which is easily exposed to malicious security risks such as hacking and information leakage. In this article, we tried to present the necessity and implications of security management that guarantees integrity through operation applying block chain technology in the increasingly expanding Internet of Things environment. If this is used, it is expected to gain insight into how to apply the blockchain technique to guidelines for strengthening the security of the IoT environment in the future.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1099-1110
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• 2023

The recognition system of autonomous driving and robot navigation performs vision work such as object recognition, tracking, and lane detection after multi-sensor fusion to improve performance. Currently, research on a deep learning model based on the fusion of a camera and a lidar sensor is being actively conducted. However, deep learning models are vulnerable to adversarial attacks through modulation of input data. Attacks on the existing multi-sensor-based autonomous driving recognition system are focused on inducing obstacle detection by lowering the confidence score of the object recognition model.However, there is a limitation that an attack is possible only in the target model. In the case of attacks on the sensor fusion stage, errors in vision work after fusion can be cascaded, and this risk needs to be considered. In addition, an attack on LIDAR's point cloud data, which is difficult to judge visually, makes it difficult to determine whether it is an attack. In this study, image scaling-based camera-lidar We propose an attack method that reduces the accuracy of LCCNet, a fusion model (camera-LiDAR calibration model). The proposed method is to perform a scaling attack on the point of the input lidar. As a result of conducting an attack performance experiment by size with a scaling algorithm, an average of more than 77% of fusion errors were caused.

• Journal of Chest Surgery
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• v.42 no.4
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• pp.532-536
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• 2009

Bypass surgery is performed for insuring continuity of a blood supply that is restricted due to obstruction of the native blood supply. Two types of surgery are commonly carried out: one is anatomic bypass and the other is extraanatomic bypass. Especially, extraanatomic bypass surgery is performed in patients who are a high risk for performing anatomical bypass surgery. The risk factors for anatomical bypass surgery are old age, infection, previous surgery and trauma. A 96-year-old patient underwent extraanatomic bypass surgery from the right femoral artery to the left femoral artery due to total occlusion of the left iliac artery, and 7 years after that operation, a pseudoaneurysm abruptly and spontaneously appeared from the bypass suture site without any predisposing factor. The lesion was revealed to be an organizing thrombus.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5D
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• pp.445-451
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• 2012

Visual changes and speed changes in curved sections of highways are more dangerous than straight sections According to the enquetes conducted by Coalition for Transportation Culture in 1999, about 78% of drivers are dissatisfied with traffic guide and safety signs, with lack of visibility being the largest reason with about 27.9% of respondents indicating it as reason for dissatisfaction. In particular, the lack of visibility during nighttime or bad weather not only threatens driver safety due to poor delivery of information, but also affects the service level of highways. Because of this a new delineation must be installed and managed to enhance driver visibility. In this research, an optimal delineation system to enhance traffic safety is presented. In this research drivers effectively obtained information on highway alignment on the curved sections using a retro-reflection type delineation system and a newly-developed internal lighting delineation system to improve safety on the highways. A statistical comparison was conducted and analysis was done for the delineation systems that enhanced visibility through primary and secondary enquaetes. As a result, inside-lighting delineator will be selected in terms of safety at the curve sections. The inside-lighting delineator was more effective than the retro-reflection delineator on visibility, the necessity of reduction of speed and will reduce the hazard at curve sections. It is anticipated that when a delineation system based on this research is installed, a reduction in the number the number and severity of traffic accidents on curved sections will be reduced. In addition this system will more effectively provide drivers with information about highway alignment.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.107-116
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• 2002

Crash Cushion is a kind of safety facilities on roadside which acts the role of absorbing impact energy when vehicles are driven out of normal route such as Gore area of freeway off ramp. Criteria for severity index considering accident occurrence possibility are needed to have strong effect on installing the facilities. However, present criteria for establishing crash cushion design do not include such processes. Therefore, the paper presents two kinds of study to develop criteria for severity index. First of all, development of accident forecasting model on freeway off ramp is presented. The module is a relationship between accidents and road environment by negative binomial distribution (NB) which is called to reflect very well quality of accidents at Gore of crash cushion installed freeway Secondly, freeway exiting behavior model is developed because the human factor is the most important one. However, many literatures have shown between road environment and accidents which are more quantitative than human factor. The study supposed advanced process steps on actual freeway and analysed correlation between variables and accidents. The criteria for severity index is presented to determine whether to install or not by benefit cost analysis for each module. The standard for severity index will help to determine whether to install the crash cushion or not and to estimate severity for freeway and off ramp.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.20-33
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• 2021

This study is to suggest improvements of personal information protection in South Korea, according to requiring the safety of process and protection of personal information. Accordingly, based on data collection and analysis through literature research, this study derived the issues and suitable standards of personal information for major artificial intelligence services. In addition, this cases studies were reviewed, focusing on the legal compliance and porcessing compliance for personal information proection in major countries. And it suggested the improvement plan applied in South Korea. As the results, in legal compliance, it is required reorganization of related laws, responsibility and compliance to develop and provide AI, and operation of risk management for personal information protection laws in AI services. In terms of processing compliance, first, in pre-processing and refining, it is necessary to standardize data set reference models, control data set quality, and voluntarily label AI applications. Second, in development and utilization of algorithm, it is need to establish and apply a clear regulation of the algorithm. As such, South Korea should apply suitable improvement tasks for personal information protection of safe AI service.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.73-87
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• 2023

Furnishing traffic safety information can contribute to providing hazard warnings to drivers, thereby avoiding crashes. A smart road lighting platform that instantly recognizes road conditions using various sensors and provides appropriate traffic safety information has therefore been developed. This study analyzes the short-term traffic safety improvement effects of the smart road lighting's tunnel traffic safety information service using surrogate safety measures (SSM). Individual driving behavior was investigated by applying the vehicle trajectory data collected with RADAR in the Anin Avalanche 1 and 2 tunnel sections in Gangneung. Comparing accumulated speeding, speed variation, time-to-collision, and deceleration rate to avoid the crash before and after providing traffic safety information, all SSMs showed significant improvement, indicating that the tunnel traffic safety information service is beneficial in improving traffic safety. Analyzing potential crash risk in the subdivided tunnel and access road sections revealed that providing traffic safety information reduced the probability of traffic accidents in most segments. The results of this study will be valuable for analyzing the short-term quantitative effects of traffic safety information services.