• International journal of advanced smart convergence
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• v.12 no.4
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• pp.182-189
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• 2023

A recently research, object detection and segmentation have emerged as crucial technologies widely utilized in various fields such as autonomous driving systems, surveillance and image editing. This paper proposes a program that utilizes the QT framework to perform real-time object detection and precise instance segmentation by integrating YOLO(You Only Look Once) and Mask R CNN. This system provides users with a diverse image editing environment, offering features such as selecting specific modes, drawing masks, inspecting detailed image information and employing various image processing techniques, including those based on deep learning. The program advantage the efficiency of YOLO to enable fast and accurate object detection, providing information about bounding boxes. Additionally, it performs precise segmentation using the functionalities of Mask R CNN, allowing users to accurately distinguish and edit objects within images. The QT interface ensures an intuitive and user-friendly environment for program control and enhancing accessibility. Through experiments and evaluations, our proposed system has been demonstrated to be effective in various scenarios. This program provides convenience and powerful image processing and editing capabilities to both beginners and experts, smoothly integrating computer vision technology. This paper contributes to the growth of the computer vision application field and showing the potential to integrate various image processing algorithms on a user-friendly platform

• The Journal of Information Systems
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• v.33 no.1
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• pp.91-114
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• 2024

Purpose The purpose of this study is to empirically investigate the factors that influence users' continuous intention to use ChatGPT based on the Expectation Confirmation Model(ECM). Drawing from the literature, this study identifies anthropomorphism and trust as key characteristics of generative AI and ChatGPT. Design/methodology/approach The research model was developed based on ECM and literature research to investigate the impacts of anthropomorphism and trust on continuous intention of using ChatGPT. In order to test the hypothese, a total of 193 questionnaires were collected and analyzed for the structural equation modeling with SmartPLS 4.0. Findings The study's findings show that all proposed hypotheses were supported, suggesting that the ECM is a valid framework for examining continuous intention of using ChatGPT. Moreover, the study stressed the crucial role of anthropomorphism in the model, showing the positive impact on expectation confirmation, perceived usefulness, and trust in ChatGPT. Also, trust positively affects perceived usefulness. These findings provide valuable insights for enhancing user satisfaction and continuous usage intention, serving as a foundation for development strategies for ChatGPT and similar AI-based systems.

• The Korean Journal of Franchise Management
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• v.15 no.2
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• pp.17-37
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• 2024

Purpose: This study used the SOR model to analyze the impact of live commerce's modified livecommercescape factors (interactivity, presence, playfulness, convenience, and broadcaster characteristics) on repurchase intention through usefulness and flow. Research design, data, and methodology: 1,149 respondents with live commerce purchase experience were collected through an online survey, and the collected data was analyzed with SPSS 25.0 and SmartPLS 4.0 statistical package programs. Results: Presence and playfulness were found to have the highest influence on flow and usefulness. In particular, Presence and broadcaster characteristics were found to be the factors that had the greatest influence on flow. Playfulness was found to have the greatest impact on usefulness, and two-way communication was found to have the lowest influence among the five servicescape factors. Broadcaster characteristics also affect flow but not usefulness, and convenience only affects usefulness and does not affect flow. Flow shows results that affect usefulness and repurchase intention. Conclusion: Our findings provide a richer understanding of causal relationships within the SOR framework, demonstrating that broadcaster characteristics, two-way communication, presence, and playfulness can influence flow, perceived usefulness, and, consequently, consumer purchasing behavior.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.63-67
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• 2024

Recently, artificial intelligence (AI) workloads encompassing various industries such as smart logistics, FinTech, and entertainment are being executed on the cloud. In this paper, we address the scheduling issues of various AI workloads on a multi-tenant cloud system composed of heterogeneous GPU clusters. Traditional scheduling decreases GPU utilization in such environments, degrading system performance significantly. To resolve these issues, we present a new scheduling approach utilizing genetic algorithm-based optimization techniques, implemented within a process-based event simulation framework. Trace driven simulations with diverse AI workload traces collected from Alibaba's MLaaS cluster demonstrate that the proposed scheduling improves GPU utilization compared to conventional scheduling significantly.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.249-257
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• 2024

As the main driver of economic growth and employment, the agricultural sector plays an important role in Vietnam's economy. However, in recent years, the sector has faced new challenges and also presented new investment opportunities to stimulate agricultural growth. Many Vietnamese agricultural producers currently lack the modern technology and decision support tools needed to maintain and improve productivity in a rapidly changing environment. Other stakeholders in the agricultural value chain, such as input suppliers, distributors, and consumers, also face significant challenges, including disrupted value chains, transportation costs. The cost of transporting goods across the supply chain continues to increase and information exchange remains fragmented. A potential solution to address these challenges is the application of digital transformation in agricultural supply chains. Farmers and other value chain participants can improve the production of their goods and procedures by utilizing new and cutting-edge technologies that are integrated into a unified system as part of the digital transformation of agricultural supply chains. In this study, we evaluate the current status of digital transformation in the supply chain of the agriculture industry by finding and examining pertinent publications from key agencies as well as prior research. From there, in the framework of the digital economy, this study suggests a digital transformation roadmap for the agricultural supply chain.

• Smart Structures and Systems
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• v.33 no.3
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• pp.177-188
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• 2024

The fatigue-induced sequential failure of a structure having structural redundancy requires system-level analysis to account for stress redistribution. System reliability-based design optimization (SRBDO) for preventing fatigue-initiated structural failure is numerically costly owing to the inclusion of probabilistic constraints. This study incorporates the Branch-and-Bound method employing system reliability Bounds (termed the B³ method), a failure-path structural system reliability analysis approach, with a metaheuristic optimization algorithm, namely grey wolf optimization (GWO), to obtain the optimal design of structures under fatigue-induced system failure. To further improve the efficiency of this new optimization framework, an additional bounding rule is proposed in the context of SRBDO against fatigue using the B³ method. To demonstrate the proposed method, it is applied to complex problems, a multilayer Daniels system and a three-dimensional tripod jacket structure. The system failure probability of the optimal design is confirmed to be below the target threshold and verified using Monte Carlo simulation. At earlier stages of the optimization, a smaller number of limit-state function evaluation is required, which increases the efficiency. In addition, the proposed method can allocate limited materials throughout the structure optimally so that the optimally-designed structure has a relatively large number of failure paths with similar failure probability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2377-2398
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• 2021

In the recent modernized world, utilization of natural resources (renewable & non-renewable) is increasing drastically due to the sophisticated life style of the people. The over-consumption of non-renewable resources causes pollution which leads to global warming. Consequently, government agencies have been taking several initiatives to control the over-consumption of non-renewable natural resources and encourage the production of renewable energy resources. In this regard, we introduce an IoT powered integrated framework called as green home architecture (GHA) for green score calculation based on the usage of natural resources for household purpose. Green score is a credit point (i.e.,10 pts) of a family which can be calculated once in a month based on the utilization of energy, production of renewable energy and pollution caused. The green score can be improved by reducing the consumption of energy, generation of renewable energy and preventing the pollution. The main objective of GHA is to monitor the day-to-day usage of resources and calculate the green score using the proposed green score algorithm. This algorithm gives positive credits for economic consumption of resources and production of renewable energy and also it gives negative credits for pollution caused. Here, we recommend a green score based tax calculation system which gives tax exemption based on the green score value. This direct beneficiary model will appreciate and encourage the citizens to consume fewer natural resources and prevent pollution. Rather than simply giving subsidy, this proposed system allows monitoring the subsidy scheme periodically and encourages the proper working system with tax exemption rewards. Also, our GHA will be used to monitor all the household appliances, vehicles, wind mills, electricity meter, water re-treatment plant, pollution level to read the consumption/production in appropriate units by using the suitable sensors. These values will be stored in mass storage platform like cloud for the calculation of green score and also employed for billing purpose by the government agencies. This integrated platform can replace the manual billing and directly benefits the government.

• Journal of Bio-Environment Control
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• v.32 no.3
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• pp.181-189
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• 2023

Hydrogen has gained attention as an environmentally friendly energy source among various renewable options, however, its application in agriculture remains limited. This study aims to apply the hydrogen fuel cell triple heat-combining system, originally not designed for greenhouses, to greenhouses in order to save energy and reduce greenhouse gas emissions. This system can produce heating, cooling, and electricity from hydrogen while recovering waste heat. To implement a hydrogen fuel cell triple heat-combining system in a greenhouse, it is crucial to evaluate the greenhouse's heating and cooling load. Accurate analysis of these loads requires considering factors such as greenhouse configuration, existing heating and cooling systems, and specific crop types being cultivated. Consequently, this study aimed to estimate the cooling and heating load using building energy simulation (BES). This study collected and analyzed meteorological data from 2012 to 2021 for semi-enclosed greenhouses cultivating tomatoes in Jeonju City. The covering material and framework were modeled based on the greenhouse design, and crop energy and soil energy were taken into account. To verify the effectiveness of the building energy simulation, we conducted analyses with and without crops, as well as static and dynamic energy analyses. Furthermore, we calculated the average maximum heating capacity of 449,578 kJ·h^-1 and the average cooling capacity of 431,187 kJ·h^-1 from the monthly maximum cooling and heating load analyses.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.5
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• pp.1-18
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• 2023

The Ecosystem Conservation Levy (formerly known as the Ecosystem Conservation Cooperation Fund) system has been in place for 20 years, and it can be said that it has now entered the settlement stage. Based on an analysis of publicly available project implementation data from 2014 to 2020, we found that: 1) As the number of return projects increases, the targets of restoration technologies are also strengthening, and it is necessary to frame a series of processes from application, creation, and monitoring for some detailed projects to improve the effectiveness and efficiency of utilizing the levy. 2) Most of the implemented projects are applied as micro-ecosystem creation, but there are many cases where the contents of the project can be seen as other project categories. This shows that the purpose of the return project needs to be approached more clearly and suggests that institutional complementation is needed from the project application stage. 3) The detailed technologies applied tend to be gradually expanding, but most of them are technologies that are not differentiated from general development projects. It is urgent to secure a more technical identity, such as a range and list of utilized technologies suitable for the characteristics and purposes of return projects. 4) It is necessary to establish a relevant evaluation system or framework to utilize the monitoring results of restoration projects. 5) There have been few cases of application of single restoration technologies since the beginning, but the content and scope of the complexity tend to expand in recent years. Even if the objectives are not comprehensive and diverse, it can be seen that many parts of the projects are oriented toward convergence, so it is necessary to conduct separate research on this. 6) As for the direction of improvement of the return project, it is possible to consider expanding the restoration and conservation focus to partially accommodate the complexity of the natural environment and human ecology. It seems that the expansion of restoration technologies that consider the role and function of humans in the natural environment should be explored.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.109-115
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• 2015

The new medical device technologies for bio-signal information and medical information which developed in various forms have been increasing. Information gathering techniques and the increasing of the bio-signal information device are being used as the main information of the medical service in everyday life. Hence, there is increasing in utilization of the various bio-signals, but it has a problem that does not account for security reasons. Furthermore, the medical image information and bio-signal of the patient in medical field is generated by the individual device, that make the situation cannot be managed and integrated. In order to solve that problem, in this paper we integrated the QR code signal associated with the medial image information including the finding of the doctor and the bio-signal information. bio-signal. System implementation environment for medical imaging devices and bio-signal acquisition was configured through bio-signal measurement, smart device and PC. For the ROI extraction of bio-signal and the receiving of image information that transfer from the medical equipment or bio-signal measurement, .NET Framework was used to operate the QR server module on Window Server 2008 operating system. The main function of the QR server module is to parse the DICOM file generated from the medical imaging device and extract the identified ROI information to store and manage in the database. Additionally, EMR, patient health information such as OCS, extracted ROI information needed for basic information and emergency situation is managed by QR code. QR code and ROI management and the bio-signal information file also store and manage depending on the size of receiving the bio-singnal information case with a PID (patient identification) to be used by the bio-signal device. If the receiving of information is not less than the maximum size to be converted into a QR code, the QR code and the URL information can access the bio-signal information through the server. Likewise, .Net Framework is installed to provide the information in the form of the QR code, so the client can check and find the relevant information through PC and android-based smart device. Finally, the existing medical imaging information, bio-signal information and the health information of the patient are integrated over the result of executing the application service in order to provide a medical information service which is suitable in medical field.