• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.105-118
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• 2022

The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.76-95
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• 2023

As information and communications technology-based "smart hospitals" and "digital healthcare" have become a hot topic in the healthcare field, hospital mobile apps are gaining attention; but, the utilization rate is low due to lack of publicity, unstable systems, and late updates. In this situation, systematic research is needed to increase the utilization rate of hospital mobile apps, but related research has been rare. Therefore, this study integrates the information systems success model (ISSM) from the technical perspective and the expectation-confirmation model (ECM) from the cognitive perspective to demonstrate the influence mechanism on the continuous use intention of hospital mobile apps. For this purpose, an online survey was conducted among 181 Korean adults who have used hospital mobile apps. The results of the structual equation modeling showed that most of the quality factors have significant effects on expectation confirmation, perceived usefulness, and satisfaction. Additionally, expectation confirmation significantly affects perceived usefulness and satisfaction, and both perceived usefulness and satisfaction significantly affect the continuous use intention of hospital mobile apps. This study is of importance in that it integrates the ISSM and ECM and applies them to the context of using hospital mobile apps, which are underutilized in the healthcare field, and provides practical implications for increasing the utilization rate of hospital mobile apps and operating effective and efficient services through the findings.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6B
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• pp.551-560
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• 2009

This paper describes a newly developed pollutant transport model named ARPTM which was designed to simulate the transport and characteristics of pollutant materials after an accidental spill in upstream of river system up to a given position in the downstream. In particular, the ARPTM incorporated ADCP data to compute longitudinal dispersion coefficient and advection velocity which are necessary to apply one-dimensional advection-dispersion equation. ARPTM was built on top of the geographic information system platforms to take advantage of the technology's capabilities to track geo-referenced processes and visualize the simulated results in conjunction with associated geographic layers such as digital maps. The ARPTM computes travel distance, time, and concentration of the pollutant cloud in the given flow path from the river network, after quickly finding path between the spill of the pollutant material and any concerned points in the downstream. ARPTM is closely connected with a recently developed GIS-based Arc River database that stores inputs and outputs of ARPTM. ARPTM thereby assembles measurements, modeling, and cyberinfrastructure components to create a useful cyber-tool for determining and visualizing the dynamics of the clouds of pollutants while dispersing in space and time. ARPTM is expected to be potentially used for building warning system for the transport of pollutant materials in a large basin.

• Therapeutic Science for Rehabilitation
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• v.12 no.4
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• pp.97-109
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• 2023

Objective : This study aimed to investigate the mediating effect of play on the relationship between toddlers' sleep habits and problem-solving. Methods : In total, 1,734 participants were selected from the 3rd wave of the Panel Study on Korean Children. A structural equation modeling approach was utilized to examine the relationship among toddlers' play, sleep habits, and problem-solving, as well as to investigate the mediating effect of play. Results : The monthly age of the study participants ranged from 23 to 32 months, with 885 (51.0%) boys and 849 (49.0%) girls. The indirect effects of play on problem-solving skills (β = 0.137, p = .006) were statistically significant, but the direct effects of sleep habits on problem-solving skills (β = -.015, p = .871) and the total effect (β = 0.122, p = .057) were not significant. Conclusion : This study indicated that sleep habits did not have a direct effect on problem-solving ability, but that the indirect effects were significant and fully mediated by play. Incorrect sleep habits can negatively affect lifelong development. Therefore, parents would need to be aware of whether their child is developing good sleep habits during the toddler age.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.967-971
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• 2023

Recently, a variety of AI-based platform services are available, and one of them is ChatGPT that processes a large quantity of data in the natural language and generates an answer after self-learning. ChatGPT can perform various tasks including software programming in the IT sector. Particularly, it may help generate a simple program and correct errors using C Language, which is a major programming language. Accordingly, it is expected that ChatGPT is capable of effectively using Verilog HDL, which is a hardware language created in C Language. Verilog HDL synthesis, however, is to generate imperative sentences in a logical circuit form and thus it needs to be verified whether the products are executed properly. In this paper, we aim to select small-scale logical circuits for ease of experimentation and to verify the results of circuits generated by ChatGPT and human-designed circuits. As to experimental environments, Xilinx ISE 14.7 was used for module modeling, and the xc3s1000 FPGA chip was used for module embodiment. Comparative analysis was performed on the use area and processing time of FPGA to compare the performance of ChatGPT products and Verilog HDL products.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.309-323
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• 2023

As the role of online reviews has become increasingly crucial, numerous studies have been conducted to utilize helpful reviews. Helpful reviews, perceived by customers, have been verified in various research studies to be influenced by factors such as ratings, review length, review content, and so on. The determination of a review's helpfulness is generally based on the number of 'helpful' votes from consumers, with more 'helpful' votes considered to have a more significant impact on consumers' purchasing decisions. However, recently written reviews that have not been exposed to many customers may have relatively few 'helpful' votes and may lack 'helpful' votes altogether due to a lack of participation. Therefore, rather than relying on the number of 'helpful' votes to assess the helpfulness of reviews, we aim to classify them based on review content. In addition, the text of the review emerges as the most influential factor in review helpfulness. This study employs text mining techniques, including topic modeling and sentiment analysis, to analyze the diverse impacts of content and emotions embedded in the review text. In this study, we propose a review helpfulness prediction model based on review content, utilizing movie reviews from IMDb, a global movie information site. We construct a review helpfulness prediction model by using an explainable Graph Neural Network (GNN), while addressing the interpretability limitations of the machine learning model. The explainable graph neural network is expected to provide more reliable information about helpful or non-helpful reviews as it can identify connections between reviews.

• Journal of the Korean Institute of Gas
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• v.27 no.4
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• pp.19-26
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• 2023

Earthquakes are one of the most important disasters affecting underground structures. Urban gas underground pipes may cause safety problems of structures in the event of an earthquake. Since Korea began digital observation, the number of earthquakes has been steadily increasing. The seismic design standard for urban gas pipes was established in 2008, but it is difficult to estimate the impact of pipes in the event of an earthquake based on the installation of pipes. In this study, structural analysis was performed on PE (polyethylene pipe) pipes and PLP (polyethylene coated steel pipe) pipes, which are mainly used as buried pipes in Korea, according to environmental and pipe variables in the event of an earthquake. This study sought to find the variables of the most vulnerable buried pipe by modeling pipes through Computer Aided Engineering (CAE) and generating displacement on the ground. Through this study, it was confirmed that the larger the elastic modulus of the soil, the deeper the buried depth, the smaller the tube diameter, and the higher the pressure, the more PLP pipes are affected by earthquakes than PE. Based on these results, the vulnerable points of buried urban gas pipes are inferred and used for special inspections of buried pipes in the event of an earthquake.

• Steel and Composite Structures
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• v.50 no.6
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• pp.705-720
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• 2024

Analyzing the collapse behavior of thin-walled steel structures holds significant importance in ensuring their safety and longevity. Geometric imperfections present on the surface of metal materials can diminish both the durability and mechanical integrity of steel shells. These imperfections, encompassing local geometric irregularities and deformations such as holes, cavities, notches, and cracks localized in specific regions of the shell surface, play a pivotal role in the assessment. They can induce stress concentration within the structure, thereby influencing its susceptibility to buckling. The intricate relationship between the buckling behavior of these structures and such imperfections is multifaceted, contingent upon a variety of factors. The buckling analysis of thin-walled steel shell structures, similar to other steel structures, commonly involves the determination of crucial material properties, including elastic modulus, shear modulus, tensile strength, and fracture toughness. An established method involves the emulation of distributed geometric imperfections, utilizing real test specimen data as a basis. This approach allows for the accurate representation and assessment of the diversity and distribution of imperfections encountered in real-world scenarios. Utilizing defect data obtained from actual test samples enhances the model's realism and applicability. The sizes and configurations of these defects are employed as inputs in the modeling process, aiding in the prediction of structural behavior. It's worth noting that there is a dearth of experimental studies addressing the influence of geometric defects on the buckling behavior of cylindrical steel shells. In this particular study, samples featuring geometric imperfections were subjected to experimental buckling tests. These same samples were also modeled using Finite Element Analysis (FEM), with results corroborating the experimental findings. Furthermore, the initial geometrical imperfections were measured using digital image correlation (DIC) techniques. In this way, the response of the test specimens can be estimated accurately by applying the initial imperfections to FE models. After validation of the test results with FEA, a numerical parametric study was conducted to develop more generalized design recommendations for the stainless-steel shell structures with the initial geometric imperfection. While the load-carrying capacity of samples with perfect surfaces was up to 140 kN, the load-carrying capacity of samples with 4 mm defects was around 130 kN. Likewise, while the load carrying capacity of samples with 10 mm defects was around 125 kN, the load carrying capacity of samples with 14 mm defects was measured around 120 kN.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.99-106
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• 2002

Researches on integration of design and construction information from earlier era focused on the conceptual data models. Development and prevalent use of commercial database management system led many researchers to design database schemas for enlightening of relationship between non-graphic data items. Although these researches became the foundation fur the proceeding researches. they did not utilize the graphic data providable from CAD system which is already widely used. 4D CAD concept suggests a way of integrating graphic data with schedule data. Although this integration provided a new possibility for integration, there exists a limitation in data dependency on a specific application. This research suggests a new approach on integration for design and construction information, 'Product Model Centered Integration Methodology'. This methodology achieves integration by preliminary research on existing methodology using 4D CAD concept. and by development and application of new integration methodology, 'Product Model Centered Integration Methodology'. 'Design Component' can be converted into digital format by object based CAD system. 'Unified Object-based Graphic Modeling' shows how to model graphic product model using CAD system. Possibility of reusing design information in latter stage depends on the ways of creating CAD model, so modeling guidelines and specifications are suggested. Then prototype system for integration management, and exchange are presented, using 'Product Frameworker', and 'Product Database' which also supports multiple-viewpoints. 'Product Data Model' is designed, and main data workflows are represented using 'Activity Diagram', one of UML diagrams. These can be used for writing programming codes and developing prototype in order to automatically create activity items in actual schedule management system. Through validation processes, 'Product Model Centered Integration Methodology' is suggested as the new approach for integration of design and construction information.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.287-316
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• 2023

As global energy crisis and the COVID-19 pandemic have emerged as social issues, there is a growing demand for companies to move away from profit-centric business models and embrace sustainable management that balances environmental, social, and governance (ESG) factors. ESG activities of companies vary across industries, and industry-specific weights are applied in ESG evaluations. Therefore, it is important to develop strategic management approaches that reflect the characteristics of each industry and the importance of each ESG factor. Additionally, with the stance of strengthened focus on ESG disclosures, specific guidelines are needed to identify and report on sustainable management activities of domestic companies. To understand corporate sustainability strategies, analyzing ESG reports and news articles by industry can help identify strategic characteristics in specific industries. However, each company has its own unique strategies and report structures, making it difficult to grasp detailed trends or action items. In our study, we analyzed ESG reports (2019-2021) and news articles (2019-2022) of six companies in the 'Finance,' 'Manufacturing,' and 'IT' sectors to examine the sustainability strategies of leading domestic ESG companies. Text mining techniques such as keyword frequency analysis and topic modeling were applied to identify industry-specific, ESG element-specific management strategies and issues. The analysis revealed that in the 'Finance' sector, customer-centric management strategies and efforts to promote an inclusive culture within and outside the company were prominent. Strategies addressing climate change, such as carbon neutrality and expanding green finance, were also emphasized. In the 'Manufacturing' sector, the focus was on creating sustainable communities through occupational health and safety issues, sustainable supply chain management, low-carbon technology development, and eco-friendly investments to achieve carbon neutrality. In the 'IT' sector, there was a tendency to focus on technological innovation and digital responsibility to enhance social value through technology. Furthermore, the key issues identified in the ESG factors were as follows: under the 'Environmental' element, issues such as greenhouse gas and carbon emission management, industry-specific eco-friendly activities, and green partnerships were identified. Under the 'Social' element, key issues included social contribution activities through stakeholder engagement, supporting the growth and coexistence of members and partner companies, and enhancing customer value through stable service provision. Under the 'Governance' element, key issues were identified as strengthening board independence through the appointment of outside directors, risk management and communication for sustainable growth, and establishing transparent governance structures. The exploration of the relationship between ESG disclosures in reports and ESG issues in news articles revealed that the sustainability strategies disclosed in reports were aligned with the issues related to ESG disclosed in news articles. However, there was a tendency to strengthen ESG activities for prevention and improvement after negative media coverage that could have a negative impact on corporate image. Additionally, environmental issues were mentioned more frequently in news articles compared to ESG reports, with environmental-related keywords being emphasized in the 'Finance' sector in the reports. Thus, ESG reports and news articles shared some similarities in content due to the sharing of information sources. However, the impact of media coverage influenced the emphasis on specific sustainability strategies, and the extent of mentioning environmental issues varied across documents. Based on our study, the following contributions were derived. From a practical perspective, companies need to consider their characteristics and establish sustainability strategies that align with their capabilities and situations. From an academic perspective, unlike previous studies on ESG strategies, we present a subdivided methodology through analysis considering the industry-specific characteristics of companies.