• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.217-228
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• 2021

After the integrated fare system has been applied, public transportation and transfer traffic increased. As a result, transfer passengers must be considered in the operation of the bus. Although previous studies have limitations due to utilizing deterministic mathematical models, which fails to reflect the stochastic movements of passengers and buses, in this study, a more realistic bus stop micro-simulation model is proposed. Based on the proposed simulation model, we represent the relationship between bus arrival interval and passenger wait time as a regression model and empirically show the differences between the cases with and without transfer passengers. Also, we propose a method converting passenger waiting time to cost and find optimal bus arrival interval based on the converted cost. It is expected the proposed method enables bottom-up decision making reflecting practical situation.

• Design Convergence Study
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• v.18 no.5
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• pp.1-17
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• 2019

Buses, subways, taxis, etc., called public transportation, are attached with a variety of advertisements Each public transportation is promoted and advertised to suit the environment and characteristics. Against this backdrop, the No. 1 tram project has been launched of public transportation in Korea. Unlike traditional public transportation, tram are not fast enough to use railways and are connected to ordinary roads, so advertisements and promotional materials can be applied in various methods. However, in order to minimize problems such as indiscriminate ad placement, this study examines how inside and outside of tram are attached methods of Central Europe where public transportation has developed. The surveyed attachment method proposes design guidelines for adhering Korean tram by modifying them in consideration of the features, environment and so on of the use of Korean tram. The guidelines produced are evaluated through interviews of three Busan citizens.

• Journal of Environmental Health Sciences
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• v.46 no.6
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• pp.757-763
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• 2020

Objectives: The objective of this study was to evaluate the concentrations of airborne fungi in public transportation from autumnl 2016 to summer 2017. Methods: This study measured the concentrations of airborne fungi on six subway lines and intercity buses in Seoul. Results: The concentration of fungi in the air in public transportation was found to be lower than the standard (500 CFU/㎥) for vulnerable group facilities among public use facities. In summer, the concentration of airborne fungi was relatively higher than in autumn. The concentrations of airborne fungi in subway (252.0 CFU/㎥) and train (45.1 CFU/㎥) were high tendency during non-rush hours in summer, while intercity bus was hightendency during rush hours in summer (111.9 CFU/㎥). The major types of airborne fungi in public transportation were Cladosporium, Penicillium, and Aspergillus. Conclusions: The harmful airborne fungus were detected though they did not exceed the standard in all public transportation. As a result, further studies on the analysis of the distribution of airborne fungi by ventilation and the characterization of indoor environments are needed to propose effective management of airborne fungi in public transportation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.849-856
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• 2020

Recently, as the number of high-height vehicles such as double-decker buses has increased, collision accidents have occurred in bridges and tunnels due to the deviation from the designated routes and driver's carelessness. In the case of the existing front collision warning system, it is limited to vehicles and pedestrians, so it is difficult to use it as a pass height warning system for the high height vehicles. In this paper, we propose a system that generates a warning by determining the correlation and time series characteristics of data for each segment using multiple lidar sensors and then determining the possibility of collision in the upper part of the vehicle. Also, the proposed system confirmed the proper operation through a real-time driving test and a system performance evaluation by the Korea Automobile Testing & Research Institute.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.89-96
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• 2021

The number of confirmed cases of coronavirus-19 is soaring around the world and has caused numerous deaths. Wearing a mask is very important to prevent infection. Incidents and accidents have occurred due to the recommendation to wear a mask in public places such as buses and subways, and it has emerged as a serious social problem. To solve this problem, this paper proposes an open source-based face mask wearing monitoring system. We used open source software, web-based artificial intelligence tool teachable machine and open source hardware Arduino. It judges whether the mask is worn, and performs commands such as guidance messages and alarms. The learning parameters of the teachable machine were learned with the optimal values of 50 learning times, 32 batch sizes, and 0.001 learning rate, resulting in an accuracy of 1 and a learning error of 0.003. We designed and implemented a mask wearing monitoring system that can perform commands such as guidance messages and alarms by determining whether to wear a mask using a web-based artificial intelligence tool teachable machine and Arduino to prove its validity.

• Korean Journal of Clinical Pharmacy
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• v.32 no.3
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• pp.166-177
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• 2022

Background: Recently clinical trials have expanded extensively in Korea; thus, ensuring the rights of subjects participating in clinical trials is imperative. Accordingly, national regulations on subject recruitment advertisement were enforced from October 25, 2018. In this study, the effect of this regulation was evaluated by analyzing the difference in the provision of information before and after enforcement of the regulation. Methods: Recruitment advertisements for clinical trial subjects 3 years before and after enforcement of the regulation were collated by the significance sampling approach. Print-based (newspapers, buses, and subways) and web-based (clinical trial center websites and online platforms) materials for recruitment in clinical trials of phase 1 to 4 for investigational drugs, medical devices, and oriental medicine were considered. Chi-square tests were conducted for inter-group comparisons. SPSS version 26 was employed for statistical analyses. Results: A total of 137 advertisements were collected comprising 60 pre- and 77 post-regulation enforcement. The overall rate of delivery of critical information in advertisements increased significantly from 47.5% before regulation to 93.2% after regulation enforcement. Particularly, details on expected adverse events augmented significantly (p<0.001). Benefits from participation in clinical trial reduced significantly from 88.3% to 70.1% (p<0.05). As the information provision amplified, the inclusion of professional terms increased. Conclusions: Enforcement of regulations has led to a surge in the amount of information and challenging terms contained in advertisements for recruiting subjects. Therefore, additional efforts are required by subjects to completely understand the information provided in the advertisements.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.57-65
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• 2022

Gyeongsangnam-do has been operating Bravo-taxi, a Gyeongnam-type DRT using taxi vehicles, since 2017 to guarantee the right of mobility for residents who live in areas lacking public transportation. This research investigated and analyzed changes in users' awareness over two years from beginning of Bravo-taxi operation in Gyeongsangnam-do, which started operating Bravo-taxis in 2017, targeting sites lacking public transportation. Through this study, the positive effects of taxi-type DRT were confirmed, such as improving the mobility of residents in areas underprivileged by public transportation, reducing required time for trips, and increasing preference for Bravo-taxis compared to existing buses. On the other hand, problems with the current Bravo-taxi system were also identified. In some areas, it was found that there were not enough coupons for Bravo-taxis, or in the case of Bravo-taxis operating at fixed times, the user's desired time and operating time did not match, resulting in lower satisfaction. The results of this research are expected to be utilized as basic data for service continuity of taxi-type DRT in operation by other local governments.

• Smart Media Journal
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• v.11 no.3
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• pp.90-101
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• 2022

Buses are a popular means of transportation. As such, thorough preparation is needed for passenger safety management. However, the safety system is insufficient because there are accidents such as a death accident occurred when the bus departed without recognizing the elderly approaching to get on in 2018. There is a safety system that prevents pinching accidents through sensors on the back door stairs, but such a system does not prevent accidents that occur in the process of getting on and off like the above accident. If it is possible to predict the intention of bus passengers to get on and off, it will help to develop a safety system to prevent such accidents. However, studies predicting the intention of passengers to get on and off are insufficient. Therefore, in this paper, we propose a 1×1 CNN3D-based getting on and off intention prediction model using skeleton keypoints of passengers extracted from the camera image attached to the bus through UDP-Pose. The proposed model shows approximately 1~2% higher accuracy than the RNN and LSTM models in predicting passenger's getting on and off intentions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1330-1339
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• 2022

3D object detection generally aims to detect relatively large data such as automobiles, buses, persons, furniture, etc, so it is vulnerable to small object detection. In addition, in an environment with limited resources such as embedded devices, it is difficult to apply the model because of the huge amount of computation. In this paper, the accuracy of small object detection was improved by focusing on local features using only one layer, and the inference speed was improved through the proposed knowledge distillation method from large pre-trained network to small network and adaptive quantization method according to the parameter size. The proposed model was evaluated using SUN RGB-D Val and self-made apple tree data set. Finally, it achieved the accuracy performance of 62.04% at mAP@0.25 and 47.1% at mAP@0.5, and the inference speed was 120.5 scenes per sec, showing a fast real-time processing speed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.133-146
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• 2023

Traffic states in urban areas are essential to implement effective traffic operation and traffic control. However, installing traffic sensors on numerous road sections is extremely expensive. Accordingly, estimating the traffic state using a vehicle-mounted camera, which shows a high penetration rate, is a more effective solution. However, the previously proposed methodology using object tracking or optical flow has a high computational cost and requires consecutive frames to obtain traffic states. Accordingly, we propose a method to detect vehicles and lanes by object detection networks and set the region between lanes as a region of interest to estimate the traffic density of the corresponding area. The proposed method only uses less computationally expensive object detection models and can estimate traffic states from sampled frames rather than consecutive frames. In addition, the traffic density estimation accuracy was over 90% on the black box videos collected from two buses having different characteristics.