• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1325-1334
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• 2016

The video incident detection System is a probe for rapid detecting the walker, falling, stopped, backwards, smoke situation in tunnel. Recently, the importance is increases from the downtown double deck tunnel in great depth underground space[1], but the legal basis is weak and the vulnerable situation experimental data. So, In this paper, we introduce a long-term log data analysis information in the tunnenl video incident detection system installed and experimental results in order to verify the feasibility of apply to video incident detection system for the double deck tunnel. It is proposed a few things about derives the problem of existing video incident detection system, improvements and reflect attributes for double deck tunnel. The contents described in this paper will contribute to refine the prototype of video incident detection system will apply to future double deck multi-layer tunnels.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.46-56
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• 2021

Predicting the incident clearance time is important for eliminating the high transportation costs and congestion from non-repetitive congestion caused by incidents. In this study, the factors influencing the clearance time suitable for domestic road conditions were analyzed, using a training dataset for predicting the incident clearance time using artificial neural networks. In a previous study, the under-prediction problem for high incident clearance time was used. In the present study, over-sampling training data applied using the SMOGN technique was obtained and applied to the model as a solution. As a result, the DNN model applying the SMOGN technique could compensate for the limitations of the previously developed prediction model by predicting the clearance time with the highest accuracy among the models developed in the research process with MAE = 18.3 minutes.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.5
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• pp.149-154
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• 1996

We propose the concept of incident angle of complex number and analyze planar optical waveguides by applying the concept. The incident angle of complex number is concerned with the modeling of prism-gap-waveguide structures. It is shown that, when optical waveguides are analyzed by use of the transfer matrix method, the proposed concept enable us to find solutions faster and more accurately than ghatak's method which introduces the leaky structure.

• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.17-30
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• 2002

Incident duration prediction is one of the most important steps of the overall incident management process. An accurate and reliable estimate of the incident duration can be the main difference between an effective incident management operation and an unacceptable one since, without the knowledge of such time durations, traffic impact can not be estimated or calculated. This research presents several multiple linear regression models for incident duration prediction using data consisting of 384 incident cases. The main source of various incident cases was the Traffic Incident Reports filled out by the Motorist Assistant Units of the Korea Highway Corporation. The models were proposed separately according to the time of day(daytime vs. nighttime) and the fatality/injury incurred (fatality/injury vs. property damage only). Two models using an integrated dataset, one with an intercept and the other without it, were also calibrated and proposed for the generality of model application. Some findings are as follows ; ?Variables such as vehicle turnover, load spills, the number of heavy vehicles involved and the number of blocked lanes were found to significantly affect incident duration times. ?Models, however, tend to overestimate the duration times when a dummy variable, load spill, is used. It was simply because several of load spill incidents had excessively long clearance times. The precision was improved when load spills were further categorized into "small spills" and "large spills" based on the size of vehicles involved. ?Variables such as the number of vehicles involved and the number of blocked lanes found not significant when a regression model was calibrated with an intercept. whereas excluding the intercept from the model structure signifies those variables in a statistical sense.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5D
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• pp.623-631
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• 2011

In this study, a new method which can detect incidents in interrupted traffic flow was suggested. The applied method of detecting the incident is the Latin Square Analysis Method by using traffic traits. In the Latin Square Analysis, unlike other previously tried methods, the traffic situation was analyzed, this time considering the changes in traffic traits for each lane and for each time period. The data used in this study were the data observed in the actual field with fine weather. The traffic volumes, the vehicle speed and the occupancy rate were collected on the interrupted flow road. The data were collected in normal and incident situations. The incidents occurred on the second lane, the time of persistent incidents was set to 10 minutes. The Latin Square Analyses were performed using the collected data with the traffic volume, with the vehicle speed or with the occupancy rate. As a result in this study, in case of detecting the traffic situations with Latin Square Analysis, it will be more successful to apply traffic volume to detect the traffic situations than to apply other factors.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.32-33
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• 2019

The purpose of this study are analyzing marine incident occurred in Busan VTS area, establishing standard of marine incident based on the data, and presenting the way to activate marine incident system. As implement this system, it is figured out that marine incident system could contribute to preventing similar accident, standing out role of VTS and improvement of VTS officer's ability. It includes efficiency of VTS marine incident and matters which necessary to implement this system.

• Journal of Ocean Engineering and Technology
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• v.23 no.6
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• pp.1-6
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• 2009

An Overtopping Wave Energy Convertor (OWEC) is an offshore wave energy convertor used for collecting overtopping waves and converting the water pressure head into electric power through hydro turbines installed in a vertical duct affixed to the sea bed. A numerical wave tank based on the commercial computational fluid dynamics code Fluent is established for the corresponding analysis. The Reynolds Averaged Navier-Stokes equation and two-phase VOF model are utilized to generate the 2D numerical linear propagating waves, which are validated by the overtopping experiment results. Calculations are made for several incident wave conditions and shape parameters for the overtopping device. Both the incident wave periods and heights have evident effects on the overtopping performance of the OWEC device. The computational analysis demonstrates that the present overtopping device is more compatible with longer incident wave periods.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.37 no.4
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• pp.313-320
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• 2001

In the presence of incident waves with different frequencies, there are second order sum and difference frequency wane exciting forces due to the nonlinearty of the incident waves. Although the magnitudes of these nonlinear forces are small, they act at sum and difference frequencies away from those of the incident waves. So, the second order sum and difference frequency wane loads occurring close to the natural frequencies of TLPs often give greater contributions to high and low frequency resonant responses. The components of the second order forces which depend on first order quantities have been evaluated using the three dimensional source distribution method. The numerical results of time domain motion analysis for the nonlinear wave exciting forces in regular waves are compared with the numerical ones of frequency domain analysis. The results of comparison confirmed the validity of the proposed approach.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.38-50
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• 2023

Recent advances in artificial intelligence (AI) technology have enabled the integration of AI technology into image sensors, such as Closed-Circuit Television (CCTV), to detect specific traffic incidents. However, most incident detection methods have been carried out using fixed equipment. Therefore, there have been limitations to incident detection for all roadways. Nevertheless, the development of mobile image collection and analysis technology, such as image sensors and edge-computing, is spreading. The purpose of this study is to estimate the reducing effect of the incident detection time according to the introduction level of mobile image collection and analysis equipment (or connected vehicles). To carry out this purpose, we utilized data on the number of incidents collected by the Suwon branch of the Gyeongbu expressway in 2021. The analysis results showed that if the market penetration rate (MPR) of connected vehicles is 4% or higher for two-lane expressway and 3% or higher for three-lane expressways, the incident detection time was less than one minute. Furthermore, if the MPR is 0.4% or higher for two-lane expressways and 0.2% or higher for three-lane expressways, the incident detection time decreased compared to the average incident detection time announced by the Korea Expressway Corporation for both two-lane and three-lane expressways.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.21 no.2
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• pp.154-163
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• 2009

Incident wave angles are conventionally estimated by the directional spectrum analysis of wave data collected from in-situ sensors. The in-situ measurements are limited in monitoring incident wave angles in the wide surf zone, since the techniques are typically expensive, labor-intensive, and point-measuring. In this study, estimation of incident wave angles using wave crest features captured in digital video imagery is proposed to observe incident wave directions over the surf zone. Line signatures of wave crests having high image pixel intensities are extracted by moving an interrogation window to identify high intensity pixels in sequential video images. Wave angles are computed by taking the first derivative of the extracted crest signatures, i.e. local slope of the crest signatures in the two-dimensional physical plane. Compared to the wave angle estimates obtained by the directional spectrum analysis, video-based wave angle estimates show good agreements in general.