• Journal of Information Technology Applications and Management
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• v.22 no.1
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• pp.17-36
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• 2015

Many companies are now trying to utilize SNS (social network service) by building it as marketing communication platform that delivers marketing messages and builds customer relationship. This study investigates the factors affecting consumers' intention to use of brand's SNS identity page (e.g., fan page in Facebook). It specifically focuses on four social support functions -self-esteem, informational, emotional and social networking support-in virtual space. Research model attempts to explore the impact of social supports on brands' SNS identity page adoption with modified technology acceptance model which includes perceived usefulness, ease of use and enjoyment. Empirical study adopts SEM (structural equation modelling) to test research model. The result indicates that perceived ease of use is influenced by informational support, and perceived usefulness is influenced by informational, emotional, and self-esteem support. And perceived enjoyment is influenced by emotional support. In addition, it reveals that there were no significant effects of social networking support on both perceived usefulness and enjoyment. These findings provide managerial implications for attracting potential and actual customers to brand's SNS identity page. And it also suggests the importance of managing sociability in brand's SNS identity page to make it as marketing communication platform.

• Journal of the Korean Geophysical Society
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• v.9 no.4
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• pp.371-376
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• 2006

Digital high resolution cameras are widely available, and are increasingly use in digital close-range photogrammetry. And photogrammetry instruments are developing rapidly and the precision is improving continuously. The building of 3D terrains of high precision are possible and the calculation of the areas or the earthwork volumes have high precision due to the development of the technique of the spatial information system using computer. Using the digital camera which has capacity of keeping numerical value by itself and easy carrying, we analyze the positioning error according to various change of photographing condition. Also we try to find a effective method of acquiring basis data for 3D modeling of high-accuracy in pixel degree through digital close-range photogrammetry with bundle adjustment for digital elevation model generation.

• Journal of Distribution Science
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• v.19 no.2
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• pp.5-14
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• 2021

Purpose: We examined informational justice, cognitive trust, and satisfaction in healthcare distribution market and their associations within the physician-patient (provider-purchaser) relationship. Methodology: 253 valid survey samples collected from patients and used structural equation modelling for analysis. Findings: We postulated that (1) physicians' informational justice has a positive impact on patients' cognitive trust, (2) patients' cognitive trust has a positive impact on satisfaction, and (3) patients' perceived informational justice has a positive impact on satisfaction. Participants were 253 people who had visited a hospital in South Korea in the past year. Results confirmed that the presence of informational justice has a positive impact on patients' cognitive trust and satisfaction in the physician-patient relationship. Additionally, once cognitive trust was built, it positively influenced patients' satisfaction. We discussed the concept and the impacts of informational justice in light of our analyses regarding patients' perceived cognitive trust and their satisfaction in the physician-patient relationship. Implications: These results emphasize the importance of ethics in healthcare, particularly physicians' frankness and honesty when providing information to patients. Further, these findings present implications for physician education, as part of their training must involve building their patients' cognitive trust as a prerequisite for developing patient satisfaction.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1154-1161
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• 2022

Building Information Modelling (BIM) has evolved into a comprehensive, collaborative method in construction project delivery. Most industrialized and developed countries have made BIM mandatory in the government and public projects, whereas developing countries are embracing and catching up BIM technologies to improve their professional's abilities and reduce claims in the construction projects. However, BIM awareness and professional's competence have become critical in implementing BIM in infrastructure projects in Nepal, particularly hydropower projects. The objectives of this study are to find the BIM awareness among hydropower professionals in Nepal and assess their response. The study used a questionnaire survey to assess the awareness. The results showed that only few professionals (12 percentage in this study) are aware of BIM and its application in Hydropower infrastructures. Majority of the respondents (more than 50%) were interested in BIM trainings and believed BIM implementation in future projects. The study indicated that lack of BIM training and lack of BIM awareness were the top factors affecting BIM implementation in hydropower projects in Nepal. The findings showed that about 66 percent of the respondents who used BIM in their projects mainly used during construction phase. More than 80 percent believed that BIM should be mandated for the hydropower projects in Nepal. The findings presented in this study could promote awareness among different professionals, organization, and construction team and encourage BIM implementation in Hydropower projects. The findings could raise awareness of BIM in Nepal's infrastructure sectors and its invaluable benefits in construction.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.183-183
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• 2020

Accurate quantitative precipitation estimation plays an important role in hydrological modelling and prediction. Instantaneous quantitative precipitation estimation (QPE) by utilizing the weather radar data is a great applicability for operational hydrology in a catchment. Previously, regression technique performed between reflectivity (Z) and rain intensity (R) is used commonly to obtain radar QPEs. A novel, recent approaching method which might be applied in hydrological area for QPE is Long Short-Term Memory (LSTM) Networks. LSTM networks is a development and evolution of Recurrent Neuron Networks (RNNs) method that overcomes the limited memory capacity of RNNs and allows learning of long-term input-output dependencies. The advantages of LSTM compare to RNN technique is proven by previous works. In this study, LSTM networks is used to estimate the quantitative precipitation from weather radar for an urban catchment in South Korea. Radar information and rain-gauge data are used to evaluate and verify the estimation. The estimation results figure out that LSTM approaching method shows the accuracy and outperformance compared to Z-R relationship method. This study gives us the high potential of LSTM and its applications in urban hydrology.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.686-693
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• 2022

Construction is a collaborative endeavor. The complexity in delivering construction projects successfully is impacted by the effective collaboration needs of a multitude of stakeholders throughout the project life-cycle. Technologies such as Building Information Modelling and relational project delivery approaches such as Alliancing and Integrated Project Delivery have developed to address this conundrum. However, with the onset of the pandemic, the digital economy has surged world-wide and advances in technology such as in the areas of machine learning (ML) and Artificial Intelligence (AI) have grown deep roots across specializations and domains to the point of matching its capabilities to the human mind. Several recent studies have both explored the role of AI in the construction process and highlighted its benefits. In contrast, literature in the organization studies field has highlighted the fear that tasks currently done by humans will be done by AI in future. Motivated by these insights and with the understanding that construction is a labour intensive sector where knowledge is both fragmented and predominantly tacit in nature, this paper explores the integration of AI in construction processes across project phases from planning, scheduling, execution and maintenance operations using literary evidence and experiential insights. The findings show that AI can complement human skills rather than provide a substitute for them. This preliminary study is expected to be a stepping stone for further research and implementation in practice.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.103-113
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• 2020

The construction industry is undergoing a digital transformation in which Building Information Modelling (BIM) is a key technology. The potential of BIM in several areas such as design optimization, time management, cost management, and asset management/facility management (AM/FM) is widely acknowledged by the AECO (Architecture, Engineering, Construction, and Operation) industry around the world. However, BIM implementation in construction projects is faced with problems such as project delay and cost overruns. The lack of identification of risks in BIM projects and standard guidelines on mitigation techniques furthers poor performance, dissatisfaction, and disputes between employers and project participants, which results in low BIM adoption rates. Therefore, the objective of this paper is to identify the potential risks in BIM implementation under the primary categories - (1) technical, (2) contractual, (3) management-related, and (4) personnel-related risks in BIM projects and present solutions to reduce, manage, and mitigate risks. To meet the objective of this paper, a survey was designed and conducted in the Hong Kong construction industry in which over 140 respondents from different disciplines, with experience in BIM projects, have participated. Based on the analysis of the survey data, the most severe and frequently occurring BIM risks and their potential mitigation strategies were identified and discussed in this paper.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.243-243
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• 2015

Low-flow simulation and forecasting is one of the emerging issues in hydrology due to the increasing demand of water in dry periods. Even though low-flow simulation and forecasting remains a difficult issue for hydrologists better simulation and earlier prediction of low flows are crucial for efficient water management. The UN has never stated that South Korea is in a water shortage. However, a recent study by MOLIT indicates that Korea will probably lack water by 4.3 billion m3 in 2020 due to several factors, including land cover and climate change impacts. The two main situations that generate low-flow events are an extended dry period (summer low-flow) and an extended period of low temperature (winter low-flow). This situation demands the hydrologists to concentrate more on low-flow hydrology. Korea's annual average precipitation is about 127.6 billion m3 where runoff into rivers and losses accounts 57% and 43% respectively and from 57% runoff discharge to the ocean is accounts 31% and total water use is about 26%. So, saving 6% of the runoff will solve the water shortage problem mentioned above. The main objective of this study is to present the hydrological modelling approach for low-flow simulation and forecasting using a model that have a capacity to represent the real hydrological behavior of the catchment and to address the water management of summer as well as winter low-flow. Two lumped hydrological models (GR4J and CAT) will be applied to calibrate and simulate the streamflow. The models will be applied to Seolmacheon catchment using daily streamflow data at Jeonjeokbigyo station, and the Nash-Sutcliffe efficiencies will be calculated to check the model performance. The expected result will be summarized in a different ways so as to provide decision makers with the probabilistic forecasts and the associated risks of low flows. Finally, the results will be presented and the capacity of the models to provide useful information for efficient water management practice will be discussed.

• KSCI Review
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• v.14 no.2
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• pp.147-152
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• 2006

Data size of moving current GIS great exponentially from 2D to 3D and the processing speed becomes slow thereby and user's real time rendering request is growing. Have problem that time and expense to process data of bulky quantity produce constraint condition of the processing speed. third dimension processing skill, virtual reality processing skill etc. and third dimension GIS about space data of bulk much overmuch to materialize. In this paper DEM data that acquire from satellite or aviation solve these problem embody virtual city in web save topography information that visualization to 3D visualization by VRML, and use modelling tool and acquire 3D campus information for building and road. 3D information acquired this to express texture and natural gifts that have truth stuff more to thing through near texture mapping work 3D imagination illustration of web based embody can.

• Spatial Information Research
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• v.14 no.1 s.36
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• pp.151-161
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• 2006

This paper has a goal to construct monitoring web GIS system which displays maps that are results of the fire detecting algorithms using MODIS image. To design and build more efficient system, foreign fire monitoring systems using satellite image are researched and analyzed. As a result of that, the information about interfaces and services provided by them are obtained. In concretely, new logical DFD is used to do a process modelling. ArcIMS 4.0 of ESRI, IIS 5.1 of Microsoft are utilized to build the web GIS System. In the aspects of data input and transfer, a specific module, which converts a binary image to a kind of vector file, is developed to adjust raster data to the web GIS system.