• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.391-393
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• 2022

In recent years, technologies forecasting demand based on deep learning and big data have accelerated the smartification of the field of e-commerce, logistics and distribution areas. In particular, ports, which are the center of global transportation networks and modern intelligent logistics, are rapidly responding to changes in the global economy and port environment caused by the 4th industrial revolution. Port traffic forecasting will have an important impact in various fields such as new port construction, port expansion, and terminal operation. Therefore, the purpose of this study is to compare the time series analysis and deep learning analysis, which are often used for port traffic prediction, and to derive a prediction model suitable for the future container prediction of Busan Port. In addition, external variables related to trade volume changes were selected as correlations and applied to the multivariate deep learning prediction model. As a result, it was found that the LSTM error was low in the single-variable prediction model using only Busan Port container freight volume, and the LSTM error was also low in the multivariate prediction model using external variables.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.59-68
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• 2024

China's huge population and industrial diversification have driven increased demand for IoT, and in a social environment where IoT technology is changing all aspects of personal and family life, including smart shopping, this study was conducted in Changchun, China. The study aimed to find ways to meet the Fashion needs of female college students living in the country and promote the development of the fashion product industry by improving the service quality of Chinese fashion product live commerce. The analysis results are as follows. First, the service quality characteristics of Chinese fashion product live commerce had a positive effect on customer satisfaction. Second, the service quality characteristics of Chinese fashion product live commerce had a positive effect on reuse intention. Third, customer satisfaction had a positive effect on reuse intention. Based on these results, it can be concluded that improving the service quality of live commerce can directly promote product sales and create direct economic benefits. In addition, based on the results of the study, which show that the service quality of fashion product live commerce affects customer satisfaction and reuse intention, it is judged that it will provide useful information in establishing marketing strategies for live commerce platforms by region and target.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.83-92
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• 2023

The purpose of this study is to provide a rational management strategy to improve the management performance of companies through intellectual property activities. Through this study, we aim to explore countermeasures to strengthen competitiveness in a changing global environment. A survey of 200 companies was conducted from September 1 to October 30, 2023. Statistical analysis was conducted using frequency analysis, exploratory factor analysis, reliability analysis, correlation analysis, multiple regression analysis, and difference analysis. The conclusions are as follows. First, the impact of intellectual property activities on management performance was found to be creation and utilization. Second, the impact of management strategies on management performance was found to be differentiation strategy, cost advantage strategy, and concentration strategy. Third, cost advantage strategy has a partial mediation effect on the relationship between creation activities and managerial performance of intellectual property activities. Fourth, the differentiation strategy has a partial mediating effect on the relationship between the creation of intellectual property activities and managerial performance. In addition, differentiation strategy has a full mediating effect on the relationship between the utilization of intellectual property activities and performance. Fifth, concentration strategy has a partial mediating effect on the relationship between intellectual property activity utilization and management performance. Sixth, there is a difference between creation activities, protection activities, utilization activities, cost advantage strategy, differentiation strategy, financial performance, and non-financial performance based on venture certification status. As the importance of intellectual property is increasing in the era of technological hegemony, IoT companies will need to improve their management performance through venture certification and strategies utilizing intellectual property in order to secure future competitiveness. Based on this study, we hope that IoT companies will maximize their performance by implementing efficient strategies that consider IP activities.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.9
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• pp.283-290
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• 2023

With the recent steady development of IoT technology, it is widely used in medical systems and smart TV watches. 66% of software development is developed through language C, which is vulnerable to memory attacks, and acts as a threat to IoT devices using language C. A stack-smashing overflow attack inserts a value larger than the user-defined buffer size, overwriting the area where the return address is stored, preventing the program from operating normally. IoT devices with low memory capacity are vulnerable to stack smashing overflow attacks. In addition, if the existing vaccine program is applied as it is, the IoT device will not operate normally. In order to defend against stack smashing overflow attacks on IoT devices, we used canaries among several detection methods to set conditions with random values, checksum, and DSLR (random storage locations), respectively. Two canaries were placed within the buffer, one in front of the return address, which is the end of the buffer, and the other was stored in a random location in-buffer. This makes it difficult for an attacker to guess the location of a canary stored in a fixed location by storing the canary in a random location because it is easy for an attacker to predict its location. After executing the detection program, after a stack smashing overflow attack occurs, if each condition is satisfied, the program is terminated. The set conditions were combined to create a number of eight cases and tested. Through this, it was found that it is more efficient to use a detection method using DSLR than a detection method using multiple conditions for IoT devices.

• Information Systems Review
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• v.23 no.4
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• pp.103-125
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• 2021

Mobility services are rapidly developing along with information and communication technology (ICT) innovation. Recently, the on-demand mobility platform market is growing, and an environment is provided in which users can call services more conveniently and check the connection status in real time using smartphones. This study investigates the current status of users' perceptions and experiences of car-hailing mobility services such as KAKAO Taxi and UT Taxi, and it analyzes the factors affecting the intention to continuously use the car-hailing service, focusing on environmental and instrumental benefits and trust in driver and platform. In particular, this study examines whether the significance of the relationship between influencing factors and continuous use intention could vary depending on the degree of innovativeness and ICT utilization. The results of this study showed that perceived benefits (environmental benefits and convenience and economic instrumental benefits) and trust in driver had significant effects on increasing trust in platform. It was analyzed that the higher the trust in platform, the higher the intention to continuously use the car-hailing service. Furthermore, the influence of perceived environmental benefits and economic benefits on the trust in platform was different depending on the degree of individual innovativeness, and the influence of convenience and economic benefits on the trust in platform varied depending on the degree of ICT utilization. Referring to the results of this study, mobility service providers can better understand the current status of users' perceptions and trust for car-hailing services, and implement service promotion strategies suitable for individual characteristics.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.2
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• pp.61-68
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• 2024

The majority of high-speed railway bridges along the domestic Gyeongbu and Honam lines feature a PSC-box type structure with a span length ranging from 35 to 40m, which typically exhibits a first bending natural frequency of approximately 4 to 5Hz. When KTX high-speed trains transverse these bridges at speeds ranging from 290 to 310km/h, the vibration induced by the trains approaches the first bending natural frequency of the bridge. Furthermore, with the upcoming operation of a EMU-320 high-speed train and the anticipated increase in the speeds of these high-speed trains, there is a need to analyze the dynamic response of high-speed railway bridges. For this, based on measured responses from actual railway bridges, a numerical model was constructed using a numerical model updating technique. The dynamic response of the updated numerical model exhibited a strong agreement with the measured response from the actual railway bridges. Subsequently, this updated model was utilized to analyze the dynamic response characteristics of the bridges when KTX and EMU-320 trains operate at increased speeds. The maximum vertical displacement and acceleration at the mid-span of the bridges were also compared to those specified in the railway design standard with the increasing speed of KTX and EMU-320.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.1-9
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• 2024

This study proposes a multi-scale template matching technique with image pyramids (TMI) to measure structural dynamic displacement using a vision sensor under atmospheric turbulence conditions and evaluates its displacement measurement performance. To evaluate displacement measurement performance according to distance, the three-story shear structure was designed, and an FHD camera was prepared to measure structural response. The initial measurement distance was set at 10m, and increased with an increment of 10m up to 40m. The atmospheric disturbance was generated using a heating plate under indoor illuminance condition, and the image was distorted by the optical turbulence. Through preliminary experiments, the feasibility of displacement measurement of the feature point-based displacement measurement method and the proposed method during atmospheric disturbances were compared and verified, and the verification results showed a low measurement error rate of the proposed method. As a result of evaluating displacement measurement performance in an atmospheric disturbance environment, there was no significant difference in displacement measurement performance for TMI using an artificial target depending on the presence or absence of atmospheric disturbance. However, when natural targets were used, RMSE increased significantly at shooting distances of 20 m or more, showing the operating limitations of the proposed technique. This indicates that the resolution of the natural target decreases as the shooting distance increases, and image distortion due to atmospheric disturbance causes errors in template image estimation, resulting in a high displacement measurement error.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.74-82
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• 2024

In this study, feature point detection and displacement measurement performance depending on feature extraction algorithms were compared and analyzed according to environmental changes and target types in the feature point-based displacement measurement algorithm. A three-story frame structure was designed for performance evaluation, and the displacement response of the structure was digitized into FHD (1920×1080) resolution. For performance analysis, the initial measurement distance was set to 10m, and increased up to 40m with an increment of 10m. During the experiments, illuminance was fixed to 450lux or 120lux. The artificial and natural targets mounted on the structure were set as regions of interest and used for feature point detection. Various feature detection algorithms were implemented for performance comparisons. As a result of the feature point detection performance analysis, the Shi-Tomasi corner and KAZE algorithm were found that they were robust to the target type, illuminance change, and increase in measurement distance. The displacement measurement accuracy using those two algorithms was also the highest. However, when using natural targets, the displacement measurement accuracy is lower than that of artificial targets. This indicated the limitation in extracting feature points as the resolution of the natural target decreased as the measurement distance increased.

• Korean Journal of Construction Engineering and Management
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• v.25 no.1
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• pp.42-49
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• 2024

In recent years, the construction industry has diligently focused on improving the quality and safety of buildings through smart technologies. However, there is a growing trend of leakage defects, especially in educational facilities, due to aging. The objective of this study is to analyze the causes of these defects in educational environments using the Fault Tree Analysis (FTA) technique and propose preventive measures based on the findings. The FTA technique is explained through a review of domestic literature, and data from the Educational Support Center from 2019 to 2021 are examined to identify major defects. The construction of the Fault Tree (FT) for leakage defects resulted in the identification of 12 basic events. Subsequently, a comprehensive understanding of the causes of leakage is achieved through FTA analysis, leading to the identification of the primary causes of defects. Leakage defects accounted for 46.8% of all reported issues in educational facilities, with roof (ceiling) leaks being the most common problem. FTA analysis revealed that poor substrate treatment was the main cause of roof (ceiling) leaks, which could be attributed to cracks in the waterproof layer, joint cracks, and microvoids in the waterproof layer. The primary achievement of this research is to provide essential data for preventing leakage defects in educational facilities and developing preventive measures through the FTA technique. These results are expected to significantly enhance the management of educational facilities and the prevention of leakage issues.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.45-58
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• 2024

Drought risk is expected to increase as the frequency, intensity, and duration of droughts increase due to climate change. Drought risk is related to not only hydro-meteorological factors, but also water supply and demand. Recently, along with climate change, socioeconomic factors have also been recognized to increase drought risk. Therefore, it is necessary to outlook the drought risk considering various conditions for coping with future extreme droughts in a timely manner. In addition, considering various drought scenarios help reduce the uncertainty in future drought outlook. In this study, drought scenarios considering climate change scenarios, population, and water demand were created to outlook drought risk for 160 administrative districts in Korea, then new levels of drought risk were assigned based on the results of drought risk outlook to suggest drought management measures. The results showed that the drought risk will increase in the future in 2020, 2025, and 2030, compared to past. Especially the drought risk is likely twice as high in 2030 under the baseline and high scenarios. Applying the drought outlook results from this study to the new methodology for setting the risk levels shows that most regions are in Response (V) in 2020 and 2030 for baseline and high scenarios.