• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.79-80
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• 2021

인터넷은 우리 경제를 디지털 경제로 변화시키며 전자상거래도 증가하고 있다. 따라서 구매자가 전자상거래에서 남기는 긍정적인, 부정적인 상품평은 상품기획의 주요 정보가 될 수 있다. 본 논문에서는 버티컬 무소음 마우스 10,000개에 대한 정형화된 데이터셋을 Word2Vec을 이용하여 유사도 분석, 온라인 상품평 빈도분석 상위 50개 단어를 제시하여 실제 상품을 사용한 후 설문조사 시행을 하였다. 온라인 상품평 유사도 분석결과 클릭 키워드에 대한 장점으로 통증(.986), 디자인(.982)가 분석되었으며 단점은 적응(.866), 불편(.854)이었다. 오프라인 상품평에서는 장점으로 디자인(17명), 단점으로 불편(11명)이었다. 또한 온라인과 오프라인의 상품평을 비교함으로써 구매자의 긍정, 부정의 의미를 교차 확인하여 유의미한 정보를 제시 하였다고 볼수 있다. 따라서 본 연구에서 제시하는 상품기획 프로세스를 신상품 개발 및 기존 상품의 개선 전략으로 적용할 수 있겠다.

• Smart Structures and Systems
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• v.32 no.5
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• pp.309-318
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• 2023

The appropriate maintenance of highway roads is critical for the safe operation of road networks and conserves maintenance costs. Multiple methods have been developed to investigate the surface of roads for various types of cracks and potholes, among other damage. Like road surface damage, the condition of expansion joints in concrete pavement is important to avoid unexpected hazardous situations. Thus, in this study, a new system is proposed for autonomous expansion joint monitoring using a vision-based system. The system consists of the following three key parts: (1) a camera-mounted vehicle, (2) indication marks on the expansion joints, and (3) a deep learning-based automatic evaluation algorithm. With paired marks indicating the expansion joints in a concrete pavement, they can be automatically detected. An inspection vehicle is equipped with an action camera that acquires images of the expansion joints in the road. You Only Look Once (YOLO) automatically detects the expansion joints with indication marks, which has a performance accuracy of 95%. The width of the detected expansion joint is calculated using an image processing algorithm. Based on the calculated width, the expansion joint is classified into the following two types: normal and dangerous. The obtained results demonstrate that the proposed system is very efficient in terms of speed and accuracy.

• Journal of Wellbeing Management and Applied Psychology
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• v.7 no.1
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• pp.17-25
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• 2024

Purpose: This study aims to explore the citizens' perceptions of living labs in the context of enhancing the living environment. Specifically, it employs quantitative research to investigate the perspectives of Millennials and Generation Z. This study proposed research questions to examine how the impacts of citizen-driven management, social factors, locally-driven management, open innovation operation, economic value, and environmental value influence the overall attitude toward living labs. Additionally, this study investigated the effects of overall attitudes on intention to participate in living labs and expected satisfaction towards living labs. Research design, data and methodology: This study employed an online survey conducted by a well-known research organization. Factor and regression analysis were utilized for data analysis. Results: The results revealed significant effects of citizen-driven management, social factors, economic value, and environmental value on overall attitude, with social factors exhibiting the highest effect size on overall attitude. Additionally, significant effects of overall attitude on intention and expected satisfaction were observed. Conclusions: The findings suggest which aspects of living labs should be fostered for the development of residents, the local economy, and citizens' quality of life, particularly with consideration of the perspectives of Millennials and Generation Z, who play a crucial role in utilizing a diverse array of ICT tools.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.167-179
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• 2024

This study addresses the challenge of objectively evaluating the performance of early-stage startups amidst limited information and uncertainty. Focusing on companies selected by TIPS, a leading private sector-driven startup support policy in Korea, the research develops a new indicator to assess technological efficiency. By analyzing various input and output variables collected from Crunchbase and KIND (Korea Investor's Network for Disclosure System) databases, including technology use metrics, patents, and Crunchbase rankings, the study derives technological efficiency for TIPS-selected startups. A prediction model is then developed utilizing machine learning techniques such as Random Forest and boosting (XGBoost) to classify startups into efficiency percentiles (10th, 30th, and 50th). The results indicate that prediction accuracy improves with higher percentiles based on the technical efficiency index, providing valuable insights for evaluating and predicting startup performance in early markets characterized by information scarcity and uncertainty. Future research directions should focus on assessing growth potential and sustainability using the developed classification and prediction models, aiding investors in making data-driven investment decisions and contributing to the development of the early startup ecosystem.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.191-196
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• 2024

Recently, research on intelligent IoT technology has been actively conducted by various companies and research institutes to analyze various data collected from IoT devices and provide it through actual application services. However, security issues such as personal information leakage may arise in the process of transmitting and receiving data to use data collected from IoT devices for research and development. In addition, as data collected from multiple IoT devices increases, data management difficulties exist, and data movement is costly and time consuming. Therefore, in this paper, we intend to develop an Ethereum network-based federated learning system with guaranteed reliability to improve security issues and inefficiencies in a federated learning environment composed of various devices.

• Journal of Web Engineering
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• v.20 no.8
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• pp.2335-2360
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• 2021

A folksonomy is a classification system in which volunteers collaboratively create and manage tags to annotate and categorize content. The folksonomy has several problems in retrieving music using tags, including problems related to synonyms, different tagging levels, and neologisms. To solve the problem posed by synonyms, we introduced a mood vector with 12 possible moods, each represented by a numeric value, as an internal tag. This allows moods in music pieces and mood tags to be represented internally by numeric values, which can be used to retrieve music pieces. To determine the mood vector of a music piece, 12 regressors predicting the possibility of each mood based on acoustic features were built using Support Vector Regression. To map a tag to its mood vector, the relationship between moods in a piece of music and mood tags was investigated based on tagging data retrieved from Last.fm, a website that allows users to search for and stream music. To evaluate retrieval performance, music pieces on Last.fm annotated with at least one mood tag were used as a test set. When calculating precision and recall, music pieces annotated with synonyms of a given query tag were treated as relevant. These experiments on a real-world data set illustrate the utility of the internal tagging of music. Our approach offers a practical solution to the problem caused by synonyms.

• Journal of Wellbeing Management and Applied Psychology
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• v.7 no.4
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• pp.15-20
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• 2024

Purpose: Climate change is greatly affecting the frequency and intensity of fires around the world. The main effects of climate change on fires are rising temperatures, dry seasons and extreme droughts, changes in precipitation, increased strong winds, extended fire danger periods, and changes in natural ecosystems. Several factors due to climate change are increasing the risk of large-scale fires, such as wildfires. Research design, data and methodology: Rising temperatures caused by climate change will make forests and grasslands drier, make it easier for wildfires to occur in drier environments and spread quickly to wider areas, and the generated wildfires will release large amounts of greenhouse gases into the atmosphere, such as carbon dioxide (CO₂), and the released greenhouse gases will strengthen the global greenhouse effect, further raising the temperature. As temperatures rise, the risk of wildfires increases in drier environments, and this process is repeated, leading to a vicious cycle of intensifying climate change as more fires occur and more greenhouse gases are released. Results: In conclusion, climate change is increasing the risk of fire occurrence and this phenomenon is expected to become more frequent and severe in the future. Conclusions: In order to cope with the increasing fire risk caused by climate change, fire prevention and management. Fire detection and response systems need to be strengthened, supportive policies and international cooperation are needed to restore ecosystems, and these measures, along with fire prevention, management and countermeasures, should take into account long-term climate change and adaptation as well as short-term responses.

• Asia pacific journal of information systems
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• v.34 no.2
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• pp.421-446
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• 2024

Through Information and Communication Technology (ICT), the growth of music streaming platforms has revolutionized music consumption. "Digital Shadow Work" (DSW) refers to unpaid labor in digital spaces, with some prior research on its aspects. However, a comprehensive understanding is hindered by limitations in existing studies such as a lack of universality and dynamic exploration. To address these gaps and enable a comprehensive investigation into the role of DSW within highly versatile digital applications such as digital streaming platforms, this study employs a grounded theory methodology, a qualitative approach well-suited for exploring the intricacies of DSW among users of Chinese music streaming applications over a two-month period, involving longitudinal interviews with nine participants. The study findings elucidate the dynamic nature of DSW perceptions, which fluctuate across different stages of use and change in intensity over time. This study uncovers mixed attitudes towards DSW tasks, and observes a waning enthusiasm for social features over time, prompting some users to consider switching platforms. This study highlights the importance of thoughtful and user-centric feature development to enhance user satisfaction and the understanding of DSW, providing practical design and enhancement implications for music streaming applications.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.28 no.3
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• pp.96-107
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• 2024

We consider the bifocusing method (BFM) for a fast identification of small objects in microwave imaging. In many researches, it was very hard to measure the scattering parameter data if the location of the transmitter and the receiver is the same. Due to this reason, the imaging function of BFM has mainly been designed by converting unknown measurement data into the zero constant; this approach has yielded reliable imaging results, but the theoretical reason for this conversion has not been investigated yet. In this study, we converted unknown measurement data to a fixed constant and applied the BFM to retrieve small objects. To demonstrate the effect of the converted constant, we show that the imaging function of the BFM can be represented in terms of an infinite series of the Bessel functions of an integer order, antenna setting, material properties, and applied constant. Based on the theoretical result, we concluded that converting unknown measurement data to constant zero guarantees good imaging results, including the unique determination of the objects. Simulation results obtained with synthetic and real data support the theoretical result.

• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.813-823
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• 2020

Purpose: In order to maximize the stability and productivity of the work through simulation prior to high-risk facilities and high-cost work such as dismantling the facilities inside the reactor, we intend to use digital twin technology that can be closely controlled by simulating the specifications of the actual control equipment. Motion control errors, which can be caused by the time gap between precision control equipment and simulation in applying digital twin technology, can cause hazards such as collisions between hazardous facilities and control equipment. In order to eliminate and control these situations, prior research is needed. Method: Unity 3D is currently the most popular engine used to develop simulations. However, there are control errors that can be caused by time correction within Unity 3D engines. The error is expected in many environments and may vary depending on the development environment, such as system specifications. To demonstrate this, we develop crash simulations using Unity 3D engines, which conduct collision experiments under various conditions, organize and analyze the resulting results, and derive tolerances for precision control equipment based on them. Result: In experiments with collision experiment simulation, the time correction in 1/1000 seconds of an engine internal function call results in a unit-hour distance error in the movement control of the collision objects and the distance error is proportional to the velocity of the collision. Conclusion: Remote decomposition simulators using digital twin technology are considered to require limitations of the speed of movement according to the required precision of the precision control devices in the hardware and software environment and manual control. In addition, the size of modeling data such as system development environment, hardware specifications and simulations imitated control equipment and facilities must also be taken into account, available and acceptable errors of operational control equipment and the speed required of work.