• Journal of Platform Technology
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• v.12 no.1
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• pp.77-84
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• 2024

With the recent increase in the use of artificial intelligence, AI TRiSM data management within organizations has become important, and thus securing data reliability has emerged as an essential requirement for data-based decision-making. Digital content is transmitted through the unreliable Internet to the cloud where the digital content storage is located, then used in various applications. When detecting anomaly of data, it is difficult to provide a function to check content modification due to its damage in digital content systems. In this paper, we design a technique to guarantee the reliability of video data by expanding the function of data annotation. The designed annotation technique constitutes a prototype based on gRPC to handle a request and a response in a webUI that generates classification label and Merkle tree of given video data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.580-586
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• 2021

The CAT methodology is a numerical analysis technique using CAE. Recently, a methodology of applying artificial intelligence techniques to a simulation has been studied. A previous study compared the deformation results according to the injection molding process using a machine learning technique. Although MLP has excellent prediction performance, it lacks an explanation of the decision process and is like a black box. In this study, data was generated using Autodesk Moldflow 2018, an injection molding analysis software. Several Machine Learning Algorithms models were developed using RapidMiner version 9.5, a machine learning platform software, and the root mean square error was compared. The decision-tree showed better prediction performance than other machine learning techniques with the RMSE values. The classification criterion can be increased according to the Maximal Depth that determines the size of the Decision-tree, but the complexity also increases. The simulation showed that by selecting an intermediate value that satisfies the constraint based on the changed position, there was 7.7% improvement compared to the previous simulation.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.1
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• pp.1-14
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• 2023

To secure national future competitiveness, the Korean government announced the 『National Ultra-High Performance Computing (HPC) Innovation Strategy (2021.5.28.)』 and set three innovation strategy goals throughout establishing an innovation ecosystem. This study presented a heterogenous data-based strategic support framework that allowed to understand both the current status of domestic & foreign R&D areas and domestic industrial economy areas in terms of strategic fields related to ultra-high performance computing, and the empirical research was conducted in the life science and public health area. The HPC innovation ecosystem platform based on the connection of heterogeneous data (domestic R&D project-technology-industry-overseas R&D project) presented in this study provided useful and essential information that allowed establishing a specific action plan for the national HPC innovation strategy and contributing to vitalizing the innovation ecosystem. Since the evidence-based policy assumes that a more reasonable consensus is reached through a non-biased decision- making process among stakeholders, the proposed platform may contribute to enhancing policy momentum by increasing legitimacy and trust of planning of the national HPC strategy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.186-188
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• 2021

The architecture named IDPS is a design concept of web-based integrated platform for heterogeneous naval combat system, which accomplishes efficiency(decreasing complexity) of diagnosis process and reduces time to diagnose system. Each type of surface vessel has its own diagnostic processes and applications, and that means it also requires its own diagnostic engineer(inefficiency in human resource management). In addition, man-based diagnostic causes quality issues such as difference approach of log analysis in accordance with engineer skills. Thus In this paper, we designed integrated diagnostic platform named IDPS with simplified common process regardless of type of surface vessel and we reinforced IDPS with status decision algorithm(SDA) that judges current software status of vessel based on gathered lots of logs. It will enable engineers to diagnose system more efficiently and to use more resources in utilizing SDA-analyzed diagnostic results.

• Information Systems Review
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• v.25 no.2
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• pp.103-123
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• 2023

One of the valid perspectives in the e-commerce platform literature is the seller signaling strategy in the information asymmetry situation. In this study, a research model was constructed based on signaling theory and shopping goal theory to systematically explore the effects of a seller's signaling strategy on consumer decision-making. Specifically, the study examined whether the signaling effects (i.e., reputation, electronic word-of-mouth, price) provided by the seller differed based on consumers' shopping goals. For the empirical analysis, the Gaussian Copula method was employed, utilizing 26,246 data collected from Amazon, a leading e-commerce platform. The analysis revealed that the signals provided by the seller positively impacted sales, and this effect was moderated by consumers' shopping goals. Drawing on shopping goal theory, this study contributes to signaling theory and e-commerce literature by discovering differences in the effectiveness of a seller's signaling strategy based on the keywords input by consumers.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.382-388
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• 2022

Satellite communication for high altitude platform stations (HAPS) and low earth orbit (LEO) systems suffer from dust and sand (DU&SA) storms in the desert regions such as Saudi Arabia. These attenuations have a distorting effect on signal fidelity at high frequency of operations. This results signal to noise ratio (SNR) to dramatically decreasing and leads to wireless transmission error. The main focus in this paper is to propose common relations between HAPS and LEO for the atmospheric impairments affecting the satellite communication networks operating above Ku-band crossing the propagation path. A double phase three dimensional relationship for HAPS and LEO systems is then presented. The comparison model present the analysis of atmospheric attenuation with specific focus on sand and dust based on particular size, visibility, adding gaseous effects for different frequency, and propagation angle to provide system operations with a predicted vision of satellite parameters' values. Skillful decision and control system (SD&CS) is proposed to control applied parameters that lead to improve satellite network performance and to get the ultimate receiving wireless signal under bad weather condition.

• Journal of Platform Technology
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• v.6 no.4
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• pp.49-58
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• 2018

Complex disasters make greater damage and higher losses unexpected than the past. To prevent these disasters, it needs to prepare a plan for handling unexpected results. Especially an accident at a facility like an atomic power plant makes a big problem cause of climate change. A simulation needs to do preliminary researches based on diverse situations. In this research we define the basic component techniques to design and implement the disaster management system. Basically a hierarchical system design method is to build on the resources provided from high performance computing(HPC) and large-scale storage systems. To develop the system, it is considered middleware as well as application studies, data studies and decision making services in convergence areas.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.8
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• pp.47-56
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• 2019

The purpose of this study is to explore the possibility of using crowdsourcing as a means to expand the participation of citizens in the process of smart urban regeneration New Deal policy. Using mobile devices, they built a crowdsourcing prototype system that enables residents to provide location-based ideas and opinions about the urban regeneration New Deal policy and share and manage the collected data. The system was applied to the actual urban regeneration New Deal project site to draw implications. The main research results are as follows. First, crowdsourcing is a means of strengthening expertise by utilizing collective intelligence dispersed among local residents. Through the online platform developed in this study, various ideas and opinions of the community can be collected. Second, the procedural legitimacy and transparency of the rehabilitation project can be secured by expanding the participation opportunities of the residents. Third, the efficiency of project promotion can be improved through participation of residents using online platform.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.561-573
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• 2021

Knowing how to build and maintain consumer trust is crucial for e-commerce. Despite the number of empirical studies that have explored the factors that influence consumer trust, none of them considers the relative importance of different antecedents and how they interact to influence consumer trust. Therefore, based on the integrated Decision Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) approaches, we establish a hierarchical structural model, which not only demonstrates the intensity of the relationships but also identifies the interdependence among the drivers of consumer trust in E-commerce. The findings confirm that propensity to trust is the most important determinant of consumer trust. The brand-related factors and platform-related factors are prominent in the process of building trust as they influence consumer trust indirectly through propensity to trust. Geographic location, demographic variables, and high security are identified as the root causes that affect consumer trust through other trust antecedents. Furthermore, the findings of this study offer valuable insights into an important element of e-commerce and provide a useful platform for future research. More represented samples and factors are encouraged for further research to ensure research fairness and minimize consumer distrust and uncertainty.

• Journal of Platform Technology
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• v.11 no.3
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• pp.45-55
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• 2023

This paper presents a model that supports decision-makers in the Korean film industry to maximize the success of online movies. To achieve this, we collected historical box office movies and clustered them into types to propose a model predicting each type's online box office performance. We considered various features to identify factors contributing to movie success and reduced feature dimensionality for computational efficiency. We systematically classified the movies into types and predicted each type's online box office performance while analyzing the contributing factors. We used automated machine learning (AutoML) techniques to automatically propose and select machine learning algorithms optimized for the problem, allowing for easy experimentation and selection of multiple algorithms. This approach is expected to provide a foundation for informed decision-making and contribute to better performance in the film industry.