• International conference on construction engineering and project management
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• 2022.06a
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• pp.1247-1248
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• 2022

Due to rapid urbanization and population growth, it has become crucial to analyze the various volumes and characteristics of pedestrian pathways to understand the capacity and level of service (LOS) for pathways to promote a better walking environment. Different indicators have been developed to measure pedestrian volume. The pedestrian level of service (PLOS), tailored to analyze pedestrian pathways based on the concept of the LOS in transportation in the Highway Capacity Manual, has been widely used. PLOS is a measurement concept used to assess the quality of pedestrian facilities, from grade A (best condition) to grade F (worst condition), based on the flow rate, average speed, occupied space, and other parameters. Since the original PLOS approach has been criticized for producing idealistic results, several modified versions of PLOS have also been developed. One of these modified versions is perceived PLOS, which measures the LOS for pathways by considering pedestrians' awareness levels. However, this method relies on survey-based measurements, making it difficult to continuously deploy the technique to all the pathways. To measure PLOS more quantitatively and continuously, researchers have adopted computer vision technologies to automatically assess pedestrian flows and PLOS from CCTV videos. However, there are drawbacks even with this method because CCTVs cannot be installed everywhere, e.g., in alleyways. Recently, a technique to monitor bio-signals, such as electrodermal activity (EDA), through wearable sensors that can measure physiological responses to external stimuli (e.g., when another pedestrian passes), has gained popularity. It has the potential to continuously measure perceived PLOS. In their previous experiment, the authors of this study found that there were many significant EDA responses in crowded places when other pedestrians acting as external stimuli passed by. Therefore, we hypothesized that the EDA responses would be significantly higher in places where relatively more dynamic objects pass, i.e., in crowded areas with low PLOS levels (e.g., level F). To this end, the authors conducted an experiment to confirm the validity of EDA in inferring the perceived PLOS. The EDA of the subjects was measured and analyzed while watching both the real-world and virtually created videos with different pedestrian volumes in a laboratory environment. The results showed the possibility of inferring the amount of pedestrian volume on the pathways by measuring the physiological reactions of pedestrians. Through further validation, the research outcome is expected to be used for EDA-based continuous measurement of perceived PLOS at the alley level, which will facilitate modifying the existing walking environments, e.g., constructing pathways with appropriate effective width based on pedestrian volume. Future research will examine the validity of the integrated use of EDA and acceleration signals to increase the accuracy of inferring the perceived PLOS by capturing both physiological and behavioral reactions when walking in a crowded area.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.15-22
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• 2022

In order to improve the accuracy of the deep learning object detection technique, the effect of magnification rate conditions and seasonal factors on detection accuracy in aerial photographs and drone images was analyzed through experiments. Among the deep learning object detection techniques, Mask R-CNN, which shows fast learning speed and high accuracy, was used to detect the vehicle to be detected in pixel units. Through Seoul's aerial photo service, learning images were captured at different screen magnifications, and the accuracy was analyzed by learning each. According to the experimental results, the higher the magnification level, the higher the mAP average to 60%, 67%, and 75%. When the magnification rates of train and test data of the data set were alternately arranged, low magnification data was arranged as train data, and high magnification data was arranged as test data, showing a difference of more than 20% compared to the opposite case. And in the case of drone images with a seasonal difference with a time difference of 4 months, the results of learning the image data at the same period showed high accuracy with an average of 93%, confirming that seasonal differences also affect learning.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.679-686
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• 2006

Recently, the city railway in the Seoul Metropolitan Area (SMA) has offered a low quality of service as a passage time, because it was operated slowly. So, the people who live in modern society are not satisfied about passage time, therefore, this study tried to make that the subway in the SMA becomes a more functional and effective wide-area-transportation-network through an express train introduction's method which examined cases from abroad and current system. and then presented how express train could be applied to current system. In a case study, We used the An-San Line and Su-In Line as a examples and developed a schedule which can minimize the delaying time of subway by using Branch & Bound Algorithm. The train operational plan was loaded to consider a railroad siding, Obtained site, and the dispatch interval(three to ten minutes) for the express and local lines and finally, We presented an alternative operational plan which made by those factors.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.565-571
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• 2006

This study aimed to analyze access mode choice behavior for KTX Passengers. To fulfill the aims of this study, Dong-Daegu Station was selected as a station for a case study. This study takes place in two stages. These are (i) descriptive statistical analysis of transportation status before and after introduction of the KTX, (ii) empirical model estimation for analyzing access mode choice behavior. This study makes use of the data from travel survey from Daegu metropolitan area. The main part of the survey was carried out in the KTX Dong-Daegu station. The data was collected from a sample of 1,800 individuals. The survey data includes the information on travel from Dong-Daegu station to Seoul. From descriptive statistical analysis of transportation status before and after introduction of the KTX, it is found that revealed demand of the KTX is lower than that expected. Moreover, it is found that the low demand of the KTX stems from high cost for the KTX itself and inconvenience( including travel time and cost) of access mode. In order to analyze mode choice behavior for accessing Dong-Daegu station, multinomial logit model structure is used. For the model specification, a variety of behavioral assumptions about the factors which affect the access mode choice, were considered. From the empirical model estimation, it si found that access travel time and access travel cost are significant in choosing access mode. Given the empirical evidence, we see that improvement of access transportation system for Dong-Daegu station is very important for enhancing the use of KTX.

• Korean Journal of Culture and Social Issue
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• v.15 no.2
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• pp.251-271
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• 2009

This research measured a concept of mobility which is included objective travel behavior as well as psychological and physical mechanism that influenced travel behavior. And then, this research examined the relation between mobility and the quality of life in elderly drivers. In research 1, to evaluate the reliability and validity of "Mobility Questionnaire(MQ)", we tested "MQ" to 207 drivers aged 20 years and older. In research 2, we examined the mobility level of elderly drivers. Also we investigated the influence that mobility of elderly drivers impacts on their quaility of life. we used "MQ", "Psychological Well-Being Questionnaire(PWBQ)" to 91 drivers aged 65 years and older. To factor analysis, MQ consisted of 'Safe Driving Ability(ADA)', 'Travel Increase(TI)', 'Travel Decrease(TD)', 'Social Activity(SA)', and 'Driving Situational Adaptability(DSA)'. The amount and speed of driving of elderly drivers reduced driving behavior than other drivers. Also, elderly drivers negatively assessed their physical abilities for safe driving and felt a low confidence in specific driving situation. On the other hand, elderly drivers take parts in social activity constructively. A review of the relation of mobility and quality of life showed that mobility of elderly drivers had positive correlation with PWB. Specially, 'ADA', 'SA', and 'DSA' had significant correlations with PWB of elderly drivers. The mobility of elderly drivers had an effect on 'Autonomy', 'Environmental mastery', 'Self-acceptance', and 'Positive relations with others'.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.1
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• pp.88-93
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• 2024

To evaluate the possibility as a multi-level memory medium for the Ge₂Sb₂Te₅/TiN/W-doped Ge₂Sb₂Te₅ cell structure, the crystallization rate and stabilization characteristics according to voltage (V)- and current (I)- pulse sweeping were investigated. In the cell structures prepared by a magnetron sputtering system on a p-type Si (100) substrate, the Ge₂Sb₂Te₅ and W-doped Ge₂Sb₂Te₅ thin films were separated by a barrier metal, TiN, and the individual thicknesses were varied, but the total thickness was fixed at 200 nm. All cell structures exhibited relatively stable multi-level states of high-middle-low resistance (HR-MR-LR), which guarantee the reliability of the multilevel phase-change random access memory (PRAM). The amorphousto-multilevel crystallization rate was evaluated from a graph of resistance (R) vs. pulse duration (T) obtained by the nanoscaled pulse sweeping at a fixed applied voltage (12 V). For all structures, the phase-change rates of HR→MR and MR→LR were estimated to be approximately t<20 ns and t<40 ns, respectively, and the states were relatively stable. We believe that the doublestack structure of an appropriate Ge-Sb-Te film separated by barrier metal (TiN) can be optimized for high-speed and stable multilevel PRAM.

• Journal of Practical Engineering Education
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• v.16 no.3_spc
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• pp.391-399
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• 2024

All highway toll gates in Korea use low-speed WIM(Weight-In-Motion) to block overloaded cargo vehicles from entering the main highway, but some cargo vehicle owners are illegally modifying vehicles to operate variable axles and evading crackdowns by manipulating the axles. In previous studies detect all tires of a running vehicle were detected to determine whether there is axle manipulation. However, because the vehicle entry area at the highway toll gate checkpoint is very narrow, there is a problem that it is realistically difficult to film all tires of the entering vehicle in one video frame. In this paper, we proposed a system that can determine whether the axle is being operated through changes in the height of the vehicle's cargo box rather than by detecting tires. To detect changes in the height of a cargo box, we propose a method to extract the representative line of the cargo box using Hough transform and then measure the change in height of the representative line to detect the change in height of the cargo box. In addition, we propose a method to detect changes in the vertical height of a cargo box by accumulating motion vectors of pixels within a certain area of the image using optical flow. And the two methods were compared and their advantages and disadvantages were analyzed and presented.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.1
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• pp.29-34
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• 2024

The heating element utilizing the Joule heating generated when current flows through a conductor is widely researched and developed for various industrial applications such as moisture removal in automotive windshield, high-speed train windows, and solar panels. Recently, research utilizing heating elements with various nanostructures has been actively conducted to develop flexible heating elements capable of maintaining stable heating even under mechanical deformation conditions. In this study, flexible polyurethane possessing excellent flexibility was selected as the substrate, and silver (Ag) thin films with low electrical resistivity (1.6 μΩ-cm) were fabricated as the heating layer using magnetron sputtering. The 2D heating structure of the Ag thin films demonstrated excellent heating reproducibility, reaching 95% of the target temperature within 20 seconds. Furthermore, excellent heating characteristics were maintained even under mechanically deforming environments, exhibiting outstanding flexibility with less than a 3% increase in electrical resistance observed in repetitive bending tests (10,000 cycles, based on a curvature radius of 5 mm). This demonstrates that polyurethane/Ag planar heating structure bears promising potential as a flexible/wearable heating element for curved-shaped appliances and objects subjected to diverse stresses such as human body parts.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.34 no.1
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• pp.1-7
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• 2024

β-Ga₂O₃ is a material with a wide band gap of ~4.8 eV and a high breakdown-voltage of 8 MV/cm, and is attracting much attention in the field of power device applications. In addition, compared to representative WBG semiconductor materials such as SiC, GaN and Diamond, it has the advantage of enabling single crystal growth with high growth rate and low manufacturing cost [1-4]. In this study, we succeeded in growing a 10 mm thick β-Ga₂O₃ single crystal doped with 0.3 mol% SnO₂ through the EFG (Edge-defined Film-fed Growth) method using multi-slit structure. The growth direction and growth plane were set to [010]/(010), respectively, and the growth speed was about 12 mm/h. The grown β-Ga₂O₃ single crystal was cut into various crystal planes (010, 001, 100, ${\bar{2}}01$) and surface processed. The processed samples were compared for characteristics according to crystal plane through analysis such as XRD, UV/VIS/NIR/Spec., Mercury Probe, AFM and Etching. This research is expected to contribute to the development of power semiconductor technology in high-voltage and high-temperature applications, and selecting a substrate with better characteristics will play an important role in improving device performance and reliability.