• Korean Architects
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• s.650
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• pp.96-99
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• 2023

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.145-154
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• 2008

The purpose of this study is to evaluate the quality of on-line departure time-based link travel time estimates. For this, accuracy (i.e. estimation error) and timeliness (i.e. degree of time lag) are proposed as MOE of the quality of on-line link travel time estimates. Then the relationship between quality of link travel time estimates and link length and level of congestion is analyzed. It was found that there is trade-off between the accuracy and timeliness of link travel time estimates. The estimation error was modeled to consist of two components: one is systematic error and the other is mean square error which reflects level of congestion. further, time lag was again segmented into three parts for the analysis purpose. There are minimum one, congestion-related one, and update interval-related one. From the real-world data using AVI system, it was revealed that regardless of the link length and level of congestion, 10 minutes of time lag occurs in general.

• Journal of the Korean Society for Railway
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• v.20 no.1
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• pp.142-155
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• 2017

It is anticipated that, in cases in which different train operators share railway network, conflicts may occur among train operators with regard to train operation rate, train priorities, and arrival and departure time; besides this, during times when there is high demand for trains, operators will request train operations intensively, steadily increasing train conflict phenomena. In the present study, train operation sequence, minimum headway, arrival and departure time, train priorities, etc., were analyzed, and while using train departure times as decision variables in variably given train schedules, by adjusting train time requested by train operators, and finally rejecting the train times in cases in which conflict resolution is impossible, so that various constraints can be satisfied, a train slot allocation model was suggested to find the objective function, that is, the maximum number of train slots that can be practically applicable to railway operation.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.54 no.3
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• pp.246-254
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• 2018

In this study, we developed a thermoelectric generation system for coastal fishing boats that allows for a high-density arrangement of thermoelectric modules, verified the improvement in performance by conducting comparative analysis between field test results and results from previous studies. The developed thermoelectric generation system was installed in a 3-ton gill-netter to analyze the engine revolutions per minute and energy production per day for each fishing process over a period of 20 days. From the experimental results, the maximum electric energy generated was 207.1 Wh, the minimum was 53.93 Wh and the average electric energy was 129.98 Wh. In accordance with the increasing of the engine r.p.m., the maximum electric production was 183 W at 1,500 r.p.m. It was approximately 80.5% of designed capacity, 227.2 W. Considering the result in the earlier research was 50.7% of designed capacity, 115.8 W. It was improved by 30% compared to the earlier one. The fishing operation was classified as departure, fishing and arrival. From the result on production analysis of electric energy, the composition of energy was 63% in fishing, 19.5% in departure and 17.5% in arrival. The electric energy production per unit hour was 42.8% in arrival, 32.9% in departure and 24.3% in fishing.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.65-77
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• 2013

Recent advanced sensors and communication technologies have been widely applied to advanced safety vehicle (ASV) for reducing traffic accident and injury severity. To apply the advanced safety vehicle technologies, it is important to quantify the safety benefits, which is a fundamental for justifying application. This study proposed a methodology for quantifying the effectiveness of the advanced driver assistant system (ADAS), and applied the methodology to lane departure warning system (LDWS) and automatic emergency braking system (AEBS) which are typical advanced driver assistant systems. When the proposed methodology is applied to 2008-2010 gyeonggi-province crash data, LDWS would reduce about 10~14% of relevant crashes such as head-on, run-off-the road, rollover and fixed-object collisions on the road. In addition, AEBS could potentially prevent about 50% of total rear-end crashes. The outcomes of this study support decision making for developing not only vehicular technology but also relevant safety policies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.38-49
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• 2017

In general, railroad operation companies sell tickets to maximize their profits by applying the ticketing release time (when selling any tickets regardless of trip distances). This study is to analyze the effect of the release time on KTX ticket reservation behavior. The reservation behavior in this study means the reservation time calculated by difference between ticketing time and departure time. The data come from KTX ticket sales data of Gyeongbu-line for a week including Saturday and Sunday. The results show that the factors to affect the reservation time are day of the week, trip distance and operation direction, in addition to the release time. Furthermore, most of tickets were reserved three hours before their departure time, and most of the up line weekend users reserved their tickets a day before the departure time. Before the release time, reservation time was affected by up line and long distance travel. On the other hand, after the release time, it was affected by long distance travel and Sunday.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.241-246
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• 2016

Nowadays many people have an interest in facial expression and the behavior of people. These are human-robot interaction (HRI) researchers utilize digital image processing, pattern recognition and machine learning for their studies. Facial feature point detector algorithms are very important for face recognition, gaze tracking, expression, and emotion recognition. In this paper, a cascade facial feature point detector is used for finding facial feature points such as the eyes, nose and mouth. However, the detector has difficulty extracting the feature points from several images, because images have different conditions such as size, color, brightness, etc. Therefore, in this paper, we propose an algorithm using a modified cascade facial feature point detector using a convolutional neural network. The structure of the convolution neural network is based on LeNet-5 of Yann LeCun. For input data of the convolutional neural network, outputs from a cascade facial feature point detector that have color and gray images were used. The images were resized to $32{\times}32$. In addition, the gray images were made into the YUV format. The gray and color images are the basis for the convolution neural network. Then, we classified about 1,200 testing images that show subjects. This research found that the proposed method is more accurate than a cascade facial feature point detector, because the algorithm provides modified results from the cascade facial feature point detector.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.4
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• pp.275-281
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• 2016

Subcooled boiling under low pressure was numerically investigated using computational fluid dynamics(CFD). The wall boiling model was used for simulating the subcooled boiling; this model requires sub-models consisting of bubble departure diameter, nucleation site density and bubble departure frequency. The CFD code CFX provides the default models based on experimental data. Because these models are mostly developed under high pressure conditions, it would not be predicted well in low pressure conditions. Thus in this study, CFD validation for subcooled boiling under low pressure was analyzed. The numerical results were compared with experimental data from published paper. Simulations were performed with mass flux ranging from 250 to $750kg/m^2s$, heat flux ranging from 0.37 to $0.77MW/m^2$ and constant outlet pressure of 0.11 MPa. Employing the empirical correlation developed under low pressures could increase the accuracy of numerical analysis.

• Journal of Korean Society of Transportation
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• v.25 no.2 s.95
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• pp.145-155
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• 2007

The objectives of this study aye to develop an on-line departure time-based travel time estimation method and to determine an optimal link length for the estimation. This study developed a link-based rolling horizon logic as the travel time estimation method. In order to determine an optimal link length, the information error of the travel time provision from the user's perspective was defined and employed as a selection criterion. It was found that, when the travel time aggregation size was set as five minutes, a link length of four kilometers gave the most accurate result.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.6
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• pp.9-16
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• 2017

An Algorithm for Lane Detection and Lane Departure Warning for a Vehicle Driving on Roads is proposed in This Paper. Using Images Obtained from On-board Cameras for Lane Detection has Some Difficulties, e.g. the Increase of Fault Detection Ratio Due to Symbols on Roads, Missing Yellow Lanes in the Tunnel due to a Similar Color Lighting, Missing Some Lanes in Rainy Days Due to Low Intensity of Illumination, and so on. The Proposed Algorithm has been developed Focusing on Solving These Problems. It also has an Additional Function to Determine How much the Vehicle is leaning to any Side between The Lanes and, If Necessary, to Give a Warning to a Driver. Experiments Using an Image Database Built by Collecting with Vehicle On-board Blackbox in Six Different Situations have been conducted for Validation of the Proposed Algorithm. The Experimental Results show a High Performance of the Proposed Algorithm with Overall 97% Detection Success Ratio.