• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.601-602
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• 2011

In this paper, we propose head/rear lamp detection algorithm for stopped and wrong way vehicle recognition. It is shown that our algorithm detected vehicles based on the experimental analysis about the color information of vehicle's lamps. The simulation results show the detection rate about stopped and wrong way vehicles is achieved over 94% and 96% in the tunnel HD(High Definition) video image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.2A
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• pp.204-209
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• 2008

It is the most important in the traffic information system how fast to transmit the traffic conditions on each road, or event such as RTM (Road Traffic Message). In order to operate the event information more efficiently in the TPEG system, it is likely that the effective transmission system shall be needed, and this paper will propose the improved transmission system; Breaking away from the conventional method which is to transmit the traffic information by using simple FIFO method while encoding it into TPEG data, the improved transmission system is to transmit the important information more quickly or to advance the transmission cycle by scheduling according to degree of its importance after deciding which one is the important traffic information by comparing the importance ratings in between diverse information. The traffic information with low importance rating is to be transmitted slowly, and its transmission cycle shall become slow as well. In the computer simulations, it is shown that the proposed approach enables to transmit more quickly a sudden change of traffic conditions and the important traffic data.

• Journal of Korean Society of Transportation
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• v.29 no.5
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• pp.121-138
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• 2011

More affordable and available cutting-edge technologies (e.g., wireless vehicle communication) are regarded as a possible alternative to the fixed infrastructure-based traffic information system requiring the expensive infrastructure investments and mostly implemented in the uninterrupted freeway network with limited spatial system expansion. This paper develops an advanced decentralized traveler information System (ATIS) using vehicle-to-vehicle (V2V) communication system whose performance (drivers' travel time savings) are enhanced by three complementary functions (autonomous automatic incident detection algorithm, reliable sample size function, and driver behavior model) and evaluates it in the typical $6{\times}6$ urban grid network with non-recurrent traffic state (traffic incident) with the varying key parameters (traffic flow, communication radio range, and penetration ratio), employing the off-the-shelf microscopic simulation model (VISSIM) under the ideal vehicle communication environment. Simulation outputs indicate that as the three key parameters are increased more participating vehicles are involved for traffic data propagation in the less communication groups at the faster data dissemination speed. Also, participating vehicles saved their travel time by dynamically updating the up-to-date traffic states and searching for the new route. Focusing on the travel time difference of (instant) re-routing vehicles, lower traffic flow cases saved more time than higher traffic flow ones. This is because a relatively small number of vehicles in 300vph case re-route during the most system-efficient time period (the early time of the traffic incident) but more vehicles in 514vph case re-route during less system-efficient time period, even after the incident is resolved. Also, normally re-routings on the network-entering links saved more travel time than any other places inside the network except the case where the direct effect of traffic incident triggers vehicle re-routings during the effective incident time period and the location and direction of the incident link determines the spatial distribution of re-routing vehicles.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.419-432
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• 2019

Most of deep learning model training was proceeded by supervised learning, which is to train labeling data composed by inputs and corresponding outputs. Labeling data was directly generated manually, so labeling accuracy of data is relatively high. However, it requires heavy efforts in securing data because of cost and time. Additionally, the main goal of supervised learning is to improve detection performance for 'True Positive' data but not to reduce occurrence of 'False Positive' data. In this paper, the occurrence of unpredictable 'False Positive' appears by trained modes with labeling data and 'True Positive' data in monitoring of deep learning-based CCTV accident detection system, which is under operation at a tunnel monitoring center. Those types of 'False Positive' to 'fire' or 'person' objects were frequently taking place for lights of working vehicle, reflecting sunlight at tunnel entrance, long black feature which occurs to the part of lane or car, etc. To solve this problem, a deep learning model was developed by simultaneously training the 'False Positive' data generated in the field and the labeling data. As a result, in comparison with the model that was trained only by the existing labeling data, the re-inference performance with respect to the labeling data was improved. In addition, re-inference of the 'False Positive' data shows that the number of 'False Positive' for the persons were more reduced in case of training model including many 'False Positive' data. By training of the 'False Positive' data, the capability of field application of the deep learning model was improved automatically.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.1
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• pp.95-107
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• 2017

In this study, a preliminary study was undertaken for development of a tunnel incident automatic detection system based on a machine learning algorithm which is to detect a number of incidents taking place in tunnel in real time and also to be able to identify the type of incident. Two road sites where CCTVs are operating have been selected and a part of CCTV images are treated to produce sets of training data. The data sets are composed of position and time information of moving objects on CCTV screen which are extracted by initially detecting and tracking of incoming objects into CCTV screen by using a conventional image processing technique available in this study. And the data sets are matched with 6 categories of events such as lane change, stoping, etc which are also involved in the training data sets. The training data are learnt by a resilience neural network where two hidden layers are applied and 9 architectural models are set up for parametric studies, from which the architectural model, 300(first hidden layer)-150(second hidden layer) is found to be optimum in highest accuracy with respect to training data as well as testing data not used for training. From this study, it was shown that the highly variable and complex traffic and incident features could be well identified without any definition of feature regulation by using a concept of machine learning. In addition, detection capability and accuracy of the machine learning based system will be automatically enhanced as much as big data of CCTV images in tunnel becomes rich.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.1 no.1
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• pp.79-88
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• 2002

As a part of NERI:;, Truck Shipment Safety Information is divided into Optimal Route Guidance system and Emergency Response system. This study which is for developing of Truck Shipment Incident Emergency Response System intends to prevent or early response damage caused by incidents through realtime monitoring about the position and the state of Hazard material transport truck. For this, we divide it into three scenarios; realtime monitoring, management of incidents, information provision to related organizations and present functional requirements and architecture coming with each scenario. As a result of the first step among total three steps, it would able to not only realtime management of trucks but also guide for auto-enforcement or management about illegal act like dumping scrapped material. It is now under examination about position of detection and technology of communication to application. From now on, it is expect to test in the range of Metropolitan after selecting appropriate technology.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.91-98
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• 2004

This study focuses on the development of dynamic assignment for evaluation and application for dynamic route guidance strategy. Travelers are classified according to information contents which they received pre/on trip. The first group have no traffic information, so they travel with fixed route. The second group have real-time shortest path and travel according to it. The last group have car navigation system or individual method(cellular phone, PDA-two way communication available) for traffic information on trip. And then they are assigned in accordance with the proposed multiclass dynamic assignment model. At this time the last group is gotten under control with DFS(decentralized feedback strategy). In use of this Process we expect that various traffic information strategy can be tested and also be the key factor for success of ITS, location of VMS(variable message sign), cycle of information, area of traffic information, etc).

• Sijohaknonchong
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• v.20
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• pp.97-111
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• 2004

It is extremely crucial in academic researches to clarify exact spellings and original contents of the works under analysis. In the case of Sijo, the works in different collections of poems with the same title prove to have been transformed in its spellings and expressions through the long period. Therefore it has been a very important step which should be taken prior to a research of Sijo that spellings and expressions of those works be compared and checked. In this point of view, I believe the book titled A Full Collection of Sijo. Yokdae Sijojunseo, written by me can be of great help to identify the expressions and contents. Moreover this book enables us to check authors and melodies of the works. This is a study on the aspects and phases of transformation of an original work by examining 'Eobusasisa'. The findings are the following: first of all, the number of collections including 'Eobusasisa' is unexpectedly small; secondly, how the original work was transformed and modified in various collections. A representative collection including 'Eobusasisa' as a transformed style into Sijo is Haedonggayo, where 38 poems out of 40 of 'Eobusasisa' are collected. All the modifications and changes have been checked in this study. To sum up, it is very important to compare the variations of a Sijo work with each other. It enables us to check up and to identify the writers, spellings, expressions, and melodies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.287-296
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• 2015

Recent navigation systems provide quick guide services, based on processing real-time traffic information and past traffic information by applying predictable pattern for traffic information. However, the current pattern for traffic information predicts traffic information by processing past information that it presents an inaccuracy problem in particular circumstances(accidents and weather). So, this study presented a more precise predictive traffic information system than historical traffic data first by analyzing route search data which the drivers ask in real time for the quickest way then by grasping traffic congestion levels of the route in which future drivers are supposed to locate. First results of this study, the congested route from Yang Jae to Mapo, the analysis result shows that the accuracy of the weighted value of speed of existing commonly congested road registered an error rate of 3km/h to 18km/h, however, after applying the real predictive traffic information of this study the error rate registered only 1km/h to 5km/h. Second, in terms of quality of route as compared to the existing route which allowed for an earlier arrival to the destination up to a maximum of 9 minutes and an average of up to 3 minutes that the reliability of predictable results has been secured. Third, new method allows for the prediction of congested levels and deduces results of route searches that avoid possibly congested routes and to reflect accurate real-time data in comparison with existing route searches. Therefore, this study enabled not only the predictable gathering of information regarding traffic density through route searches, but it also made real-time quick route searches based on this mechanism that convinced that this new method will contribute to diffusing future traffic flow.

• Journal of Sasang Constitutional Medicine
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• v.12 no.1
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• pp.1-9
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• 2000

1. Objects of Research Dong-mu Lee Je-ma was tried to solve the diseases of human beings through Sasang Constitutional Medicine with new viewpoints on human beings and life compared with the existed medicine. So it was very important to understand his medical views in order to apply Sasang Constitutional Medicine in clinical treatment. In this paper, I tried to find his medical views on human beings, life, and diseases to get informations in clinical application. 2. Methods of Research It was researched as bibliologically with his writings such as "Dongyi Soose Bowon(東醫壽世保元)", "Dongyi Soose Bowon Sasang Chobongyun(東醫壽世保元四象草本卷)", "Dongmu Yugo(東武遺稿)", "Gyuk-chigo(格致藁)". 3. Results and Conclusions The conclusions were as follows. 1. "I Ching"'s recognition of Things is that based on Yin-yang theory, originated from Taoism, and aimed to 'the Fine point of Easiness and Simpleness(易簡之妙)'. On the other hand, Dong-mu's is that based on Sasang theory, originated from Confucianism and designed to developed 'the Fine point of Easiness and Simpleness' in view of Sasang(四象). 2. Dong-mu Lee Je-ma had devoted himself in his whole life to establishing new paradigm in the Confucianism, inventing new medicine and, furthermore, embodying the spirit of General health maintenance. 3. Dong-mu Lee Je-ma recognized 'the Fine point of Easiness and Simpleness' in view of Sasang and offered new viewpoint of human being through summarizing various existing viewpoints. 4. Dong-mu Lee Je-ma established new viewpoint of life span of human being through offering new ideas such as 'Inherent vitality(命脈實數)', 'Essential power of organ(臟의 本常之氣)' and 'Regimen in ordinary life(生息允補之道)'. 5. Dong-mu Lee Je-ma embodied 'the Fine point of Easiness and Simpleness' in medicine through offering, in a wide meaning, the spirit of the General health maintenance and the spirit of the Positive medical treatment.