• Journal of Korean Society for Quality Management
• /
• v.50 no.3
• /
• pp.571-591
• /
• 2022

Purpose: The purpose of this study is to examine the factors affecting the intention to use online collaboration tools for non-face-to-face educational environment in the perspective of the learners. Methods: For empirical analysis, the survey of this study was administered with data that were limited to experienced learners using online collaboration tools such as Google Docs, Allo, Padlet, and Slido in online education environments such as Zoom, Webex, MS Teams, etc. and valid 400 data were analyzed by SPSS(ver 22.0) and R(ver 4.1.0) program package. Results: The results of empirical analysis showed that performance expectancy were found to have an effect on reliability of system quality, empathy of service quality, playfulness and informativity of content quality among the characteristics of online collaboration tools. On the other hand, it was found that the security of system quality, responsiveness of service quality, and extroversion of user personality characteristics did not affect. It was analyzed that playfulness had the greatest positive effect, followed by informativity, empathy, and reliability. Among the characteristics of online collaboration tools, it was found that the reliability and security of system quality and informativity of content quality had an effect on the effort expectancy. It was analyzed that informativity has the greatest influence, followed by security and reliability. Conclusion: This study is meaningful in that it examines the perspectives of users and learners, who can be said to be the end customers of online collaboration tools. Based on the results of this study, it is expected that not only platform operators that provide online collaborative tools, but also providers that use online collaboration tools will have a significant impact on the development of edutech and infrastructure in the educational environment.

• Knowledge Management Research
• /
• v.23 no.3
• /
• pp.285-311
• /
• 2022

In this study, based on the S-O-R framework, how individual's stimuli (i.e., video characteristics, YouTuber characteristics, real-time broadcasting characteristics of YouTube channel) form organisms (i.e., perceived usefulness, perceived pleasure, social presence), leading to viewers' responses (i.e., continuous watching intention, paid sponsorship intention) on real-time YouTube channels. For this purpose, a research model and hypotheses were constructed, and 369 questionnaire data collected from users of real-time broadcasting channel services on the YouTube platform were analyzed. Result findings confirmed that some video/YouTuber/real-time broadcasting characteristics significantly affect viewers' perceived usefulness/perceived pleasure/social presence, and further influence continuous watching/paid sponsorship intentions. Theoretical and practical implications of the findings are discussed in conclusion.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.11
• /
• pp.1670-1675
• /
• 2021

The adoption of smart construction technology in the construction industry is progressing rapidly. By utilizing smart construction technologies such as BIM (Building Information Modeling), drones, artificial intelligence, big data, and Internet of Things technology, it has the effect of lowering the accident rate at the construction site and shortening the construction period. In order to introduce a digital twin platform for construction site management, real-time construction site management is possible in real time by constructing the same virtual space. The digital twin virtual space construction method collects and processes data from the entire construction cycle and visualizes it using a 3D model file. In this paper, we introduce a modeling automation technique that constructs an efficient digital twin space by automatically generating 3D modeling that composes a digital twin space based on 3D spatial data.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.2
• /
• pp.61-66
• /
• 2023

As the use of smartphones expands to various areas and the level of multitasking increases, the support of swap is becoming increasingly important. However, swap support in smartphones is known to cause excessive storage traffic, resulting in memory thrashing. In this paper, we analyze how the thrashing of swaps that occurred in early smartphones has changed with the advancement of smartphone hardware. As a result of this analysis, we show that the swap thrashing problem can be resolved to some extent when the memory size increases. However, we also show that thrashing still occurs when the number of running apps continues to increase. Based on further analysis, we observe that this thrashing is caused by some hot data and suggest a way to solve this through an NVM-based architecture. Specifically, we show that a small size NVM with judicious management can resolve the performance degradation caused by smartphone swap.

• International Journal of Computer Science & Network Security
• /
• v.22 no.12
• /
• pp.37-50
• /
• 2022

Modern supply chains include multiple activities from collecting raw materials to transferring final products. These activities involve many parties who share a huge amount of valuable data, which makes managing supply chain systems a challenging task. Current supply chain management (SCM) systems adopt digital technologies such as the Internet of Things (IoT) and blockchain for optimization purposes. Although these technologies can significantly enhance SCM systems, they have their own limitations that directly affect SCM systems. Security, performance, and scalability are essential components of SCM systems. Yet, confidentiality and scalability are one of blockchain's main limitations. Moreover, IoT devices are lightweight and have limited power and storage. These limitations should be considered when developing blockchain-based IoT-SCM systems. In this paper, the requirements of efficient supply chain systems are analyzed and the role of both IoT and blockchain technologies in providing each requirement are discussed. The limitations of blockchain and the challenges of IoT integration are investigated. The limitations of current literature in the same field are identified, and a secure and scalable blockchain-based IoT-SCM system is proposed. The proposed solution employs a Hyperledger fabric blockchain platform and tackles confidentiality by implementing private data collection to achieve confidentiality without decreasing performance. Moreover, the proposed framework integrates IoT data to stream live data without consuming its limited resources and implements a dualstorge model to support supply chain scalability. The proposed framework is evaluated in terms of security, throughput, and latency. The results demonstrate that the proposed framework maintains confidentiality, integrity, and availability of on-chain and off-chain supply chain data. It achieved better performance through 31.2% and 18% increases in read operation throughput and write operation throughput, respectively. Furthermore, it decreased the write operation latency by 83.3%.

• Journal of Biomedical Engineering Research
• /
• v.44 no.2
• /
• pp.125-138
• /
• 2023

The development of AI systems for radiation therapy is important to improve the accuracy, effectiveness, and safety of cancer treatment. The current system has the disadvantage of monitoring patients using CCTV, which can cause errors and mistakes in the treatment process, which can lead to misalignment of radiation. Developed the PMRP system, an AI automation system that uses depth cameras to measure patient's fine movements, segment patient's body into parts, align Z values of depth cameras with Z values, and transmit measured feedback to positioning devices in real time, monitoring errors and treatments. The need for such a system began because the CCTV visual monitoring system could not detect fine movements, Z-direction movements, and body part movements, hindering improvement of radiation therapy performance and increasing the risk of side effects in normal tissues. This study could provide the development of a field of radiotherapy that lags in many parts of the world, along with the economic and social importance of developing an independent platform for radiotherapy devices. This study verified its effectiveness and efficiency with data through phantom experiments, and future studies aim to help improve treatment performance by improving the posture correction mechanism and correcting left and right up and down movements in real time.

• Journal of Korean Society of Disaster and Security
• /
• v.16 no.1
• /
• pp.37-48
• /
• 2023

The possibility of a super-large disaster is increasing due to changes in national territory, urban space and social environment, extreme weather conditions due to climate change, and paralysis of national infrastructure due to natural disasters. In this study, in order to support the systematic establishment of national territorial disaster prevention strategies for future disasters, alternatives to intelligent national territorial disaster prevention policies for future disasters were considered. Changes in the national environment related to future disasters, domestic and foreign prior studies and policy trends related to national disaster prevention, and studies related to the national disaster management system were investigated, and institutional and technical policy alternatives were derived. As a policy alternative, it was suggested that the creation of a self-adapting national territory for future disasters should be systematized and continuously supported through a technically intelligent decision-making support system.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.34 no.3
• /
• pp.109-134
• /
• 2023

The purpose of this study is to identify the current status of institutional research data repositories in the field of science and technology and to suggest ways to activate them. The study conducted literature research, case analysis, and interviews with repository managers both domestically and internationally. The study suggested strategies with a focus on establishing repository regulations and policies, improving awareness of research data sharing, and enhancing research data quality management. First, in terms of repository regulations and policy establishment, it was considered necessary to promote the status of the National R&D Information Processing Standards, a regulation related to research data, and clarify repository basis regulations. Second, to enhance awareness of research data sharing, the need for comprehensive research data education and the identification of exemplary cases were suggested. Third, in terms of strengthening research data quality management, the need for preparation for interaction between researchers-persons in charge-committees, standardization work, and long-term preservation was suggested.

• International conference on construction engineering and project management
• /
• 2009.05a
• /
• pp.250-256
• /
• 2009

This paper presents a robotic tower-crane system using encoder and gyroscope sensors as path tracking devices. Tower crane work is often associated with falling accidents and industrial disasters. Such problems often incur a loss of time and money for the contractor. For this reason, many studies have been done on an automatic tower crane. As a part of 5-year 23-million-dollar research project in Korea, we are developing a robotic tower crane which aims to improve the safety level and productivity. We selected a luffing tower crane, which is commonly used in urban construction projects today, as a platform for the robotic tower crane system. This system comprises two modules: the automated path planning module and the path tracking module. The automated path planning system uses the 3D Cartesian coordinates. When the robotic tower crane lifts construction material, the algorithm creates a line, which represents a lifting path, in virtual space. This algorithm seeks and generates the best route to lift construction material while avoiding known obstacles from real construction site. The path tracking system detects the location of a lifted material in terms of the 3D coordinate values using various types of sensors including adopts encoder and gyroscope sensors. We are testing various sensors as a candidate for the path tracking device. This specific study focuses on how to employ encoder and gyroscope sensors in the robotic crane These sensors measure a movement and rotary motion of the robotic tower crane. Finally, the movement of the robotic tower crane is displayed in a virtual space that synthesizes the data from two modules: the automatically planned path and the tracked paths. We are currently field-testing the feasibility of the proposed system using an actual tower crane. In the next step, the robotic tower crane will be applied to actual construction sites with a following analysis of the crane's productivity in order to ascertain its economic efficiency.

• Journal of Korean Society for Quality Management
• /
• v.51 no.1
• /
• pp.55-65
• /
• 2023

Purpose: The purpose of this study is to propose an optimization process to improve product yield in the process using process data. Recently, research for low-cost and high-efficiency production in the manufacturing process using machine learning or deep learning has continued. Therefore, this study derives major variables that affect product defects in the manufacturing process using eXplainable Artificial Intelligence(XAI) method. After that, the optimal range of the variables is presented to propose a methodology for improving product yield. Methods: This study is conducted using the injection molding machine AI dataset released on the Korea AI Manufacturing Platform(KAMP) organized by KAIST. Using the XAI-based SHAP method, major variables affecting product defects are extracted from each process data. XGBoost and LightGBM were used as learning algorithms, 5-6 variables are extracted as the main process variables for the injection process. Subsequently, the optimal control range of each process variable is presented using the ICE method. Finally, the product yield improvement methodology of this study is proposed through a validation process using Test Data. Results: The results of this study are as follows. In the injection process data, it was confirmed that XGBoost had an improvement defect rate of 0.21% and LightGBM had an improvement defect rate of 0.29%, which were improved by 0.79%p and 0.71%p, respectively, compared to the existing defect rate of 1.00%. Conclusion: This study is a case study. A research methodology was proposed in the injection process, and it was confirmed that the product yield was improved through verification.