• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.967-977
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• 2018

The problems of lack of skilled worker and poor productivity at the construction site continue to be raised, and the introduction of construction automation as one of the solutions to this has been considered. The development of various types of equipment and systems has been carried out, especially for earthwork operations with multiple construction equipment. However, the level of commercialization of developed equipment or systems is very limited. Although the single-product type of earthwork equipment has been applied to the site, the integrated type of earthwork system is still in the field testing stage. Considering these constraints, the limited budget and research period, a strategy is needed to identify which technology areas and core technologies should be developed first. In this study, the technology areas and detailed core technologies that are essential for the development of earthwork systems at the level of commercialization are set and the priority of development is determined. In addition, the earthwork system that has been developed so far is analyzed and the detailed development direction is presented based on it. The findings can be used for a decision making to set the priority for core technologies that should be developed first in the limited budget and period.

• Journal of Practical Engineering Education
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• v.9 no.1
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• pp.69-75
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• 2017

In this paper, we analyzed the factors influencing the size of Korea Polytechnic as a public vocational education and training institution through analysis of demand, region, industry, and demand with established existing campus and new campus in Korea Polytechnic. By analyzing data on admission, training, and employment for 3 years out of 37 campuses, we have sampled 5 campuses by type of Korea Polytechnic, fused with the results derived from the literature analysis and in-depth analysis results, so that the regional campus will play a leading role and the direction of development. The selection of five campuses by type is a precedent study to analyze 37 campuses in the future. As a result of the study, the demand analysis through objective indicators such as the number of high school graduates, the number of employed persons, the presence of nearby industrial complexes, and policy variables is very important and reflects the reality well. Therefore, it is necessary to analyze the demand through the objective indicators in decision making related to the new campus at the pre-analysis stage. In addition to the general data proposed in this paper, that is, common variables in all regions, it is important to consider the factors that can reflect local demand characteristics when considering specific locations.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.649-661
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• 2020

Cut-slope management system (CSMS) has been investigated all slopes on the road of the whole country to evaluate risk rating of each slope. Based on this evaluation, the decision-making for maintenance can be conducted, and this procedure will be helpful to establish a consistent and efficient policy of safe road. CSMS has updated the database of all slopes annually, and this database is constructed based on a basic and detailed investigation. In the database, there are two type of data: first one is an objective data such as slopes' location, height, width, length, and information about underground and bedrock, etc; second one is subjective data, which is decided by experts based on those objective data, e.g., degree of emergency and risk, maintenance solution, etc. The purpose of this study is identifying an data application plan to utilize those CSMS data. For this purpose, logistic regression, which is a basic machine-learning method to construct a prediction model, is performed to predict a judging-type variable (i.e., subjective data) based on objective data. The constructed logistic model shows the accurate prediction, and this model can be used to judge a priority of slopes for detailed investigation. Also, it is anticipated that the prediction model can filter unusual data by comparing with a prediction value.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.146-153
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• 2022

Purpose: In the case of domestic port facilities, port structures that have been in use for a long time have many problems in terms of safety performance and functionality due to the enlargement of ships, increased frequency of use, and the effects of natural disasters due to climate change. A big data analysis method was studied to develop an approximate model that can predict the aging pattern of a port facility based on the maintenance history data of the port facility. Method: In this study, member-level maintenance history data for caisson-type quay walls were collected, defined as big data, and based on the data, a predictive approximation model was derived to estimate the aging pattern and deterioration of the facility at the project level. A state-based aging pattern prediction model generated through Gaussian process (GP) and linear interpolation (SLPT) techniques was proposed, and models suitable for big data utilization were compared and proposed through validation. Result: As a result of examining the suitability of the proposed method, the SLPT method has RMSE of 0.9215 and 0.0648, and the predictive model applied with the SLPT method is considered suitable. Conclusion: Through this study, it is expected that the study of predicting performance degradation of big data-based facilities will become an important system in decision-making regarding maintenance.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.6
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• pp.51-64
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• 2022

Along with the urbanization, the risk of urban flooding due to climate change is increasing. Flood regulation, one of the ecosystem services, is implemented in the different level of function of flood risk mitigation by the type of ecosystem such as forests, arable land, wetlands etc. Land use changes due to development pressures have become an important factor in increasing the vulnerability by flash flood. This study has conducted evaluating the urban flood regulation service using InVEST UFRM(Urban Flood Risk Model). As a result of the simulation, the potential water retention by ecosystem type in the event of a flash flood according to RCP 4.5(10 year frequency) scenario was 1,569,611 tons in urbanized/dried areas, 907,706 tons in agricultural areas, 1,496,105 tons in forested areas, 831,705 tons in grasslands, 1,021,742 tons in wetlands, and 206,709 tons in bare areas, the water bodies was estimated to be 38,087 tons. In the case of more severe 100-year rainfall, 1,808,376 tons in urbanized/dried areas, 1,172,505 tons in agricultural areas, 2,076,019 tons in forests, 1,021,742 tons in grasslands, 47,603 tons in wetlands, 238,363 tons in bare lands, and 52,985 tons in water bodies. The potential economic damage from flood runoff(100 years frequency) is 122,512,524 thousand won in residential areas, 512,382,410 thousand won in commercial areas, 50,414,646 thousand won in industrial areas, 2,927,508 thousand won in Infrastructure(road), 8,907 thousand won in agriculture, Total of assuming a runoff of 50 mm(100 year frequency) was estimated at 688,245,997 thousand won. In a conclusion. these results provided an overview of ecosystem functions and services in terms of flood control, and indirectly demonstrated the possibility of using the model as a tool for policy decision-making. Nevertheless, in future research, related issues such as application of models according to various spatial scales, verification of difference in result values due to differences in spatial resolution, improvement of CN(Curved Number) suitable for the research site conditions based on actual data, and development of flood damage factors suitable for domestic condition for the calculation of economic loss.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.203-212
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• 2021

The high-tech industry, a highly knowledge-intensive industry based on advanced technologies such as electronics, new materials, and IT, is developing rapidly centering on the semiconductor, display, and battery fields. The market size of this industry is continuously increasing, and various challenges are coming forward due to various factors such as changes in the market, changes in demand, and the requirements of the clients. Many strategies are being implemented to advance the start-up time of factories, such as fast-track construction and basic line construction. Therefore, construction of high-tech factory is required to respond to various types of construction plans and early decision making, and an accurate and reliable method of calculating construction costs is needed. In this study the existing construction type was classified into the overall line configuration considering the total production of the factory, and a basic line configuration for quick production start-up. The correction ratio/value for each detailed construction required to calculate the construction cost of the basic line configuration type was derived. Finally, reliability and accuracy were verified by applying the correction ratio suggested in this study to a new high-tech factory construction project.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.3-12
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• 2022

In general construction project planning ratio of manpower and quantity of outputs produced, such as the construction estimate standard, is used as the criterion for labor productivity. This method is highly effective in construction projects with repetitive work, however, there is a limit to apply in large-scale projects with high complexity. This is because the influence of non-work time caused by various work interruption factors that act complexly on the productivity of the project is greater than the average labor productivity derived from the performance data of the project. Therefore, this study proposes a productivity measurement method that can evaluate the characteristics of construction works and the cause of non-working time. To this end, first, detailed work processes and their non-work factors for each work type are defined, and the Adv-FMR technique is developed for quantitatively measuring them. Next, based on the concept of obtainable productivity, methods for comparative productivity analysis by work type, evaluating non-work factors, and deriving productivity improvement methods are proposed. Finally, a case study is conducted to validate that the analysis results based on Adv-FMR data can support the decision-making of construction managers on productivity management.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.69-79
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• 2024

Companies should resolve consumer dissatisfaction and increase brand loyalty by actively identifying the factors of consumer dissatisfaction and proactively responding to expected complaint behavior to induce repurchase. This is a management goal that should be pursued in common regardless of the size of the company. The specific purpose of this study is to find out whether the degree of dissatisfaction differs depending on whether or not consumers' expected performance before purchase and the actual perceived performance after purchase is compared, whether the degree of dissatisfaction affects the type of complaint behavior, which is a subsequent behavior, and whether the attributable behavior has a moderating effect in this process and whether the persistence of the result and the controllability of the cause act as a factor that determines the attribution position. In particular, compared to general companies, venture companies are more likely to overload the information processing ability of managers and are likely to make various irrational errors in decision making, so this study has important academic and practical implications. As a result of the analysis, the negative inconsistency group had the highest degree of dissatisfaction, and the higher the degree of inconsistency, the higher the dissatisfaction. The attributable behavior of unsatisfied consumers had a moderating effect on the degree of dissatisfaction, and the dissatisfaction was significantly higher in the external attributable group than the internal attributable group, which was statistically significant. On the other hand, the persistence of the result had a statistically significant effect on the attribution position, but the controllability of the cause was not. The degree of attributable behavior and dissatisfaction did not affect the type of complaining behavior, showing limited influence. Along with the interpretation of these results, this study presents various implications, especially for small and medium-sized/venture companies that provide new durable products.

• The Journal of Bigdata
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• v.8 no.1
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• pp.111-129
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• 2023

With the diffusion of digital innovation, the adoption of innovative medical technologies based on artificial intelligence is increasing in the medical field. This is driving the launch and adoption of AI-based SaMD(Software as a Medical Device), but there is a lack of research on the factors that influence the adoption of SaMD by medical institutions. The purpose of this study is to identify key factors that influence medical institutions' decisions to adopt AI-based SaMDs, and to analyze the weights and priorities of these factors. For this purpose, we conducted Delphi surveys based on the results of literature studies on technology acceptance models in healthcare industry, medical AI and SaMD, and developed a research model by combining HOTE(Human, Organization, Technology and Environment) framework and HABIO(Holistic Approach {Business, Information, Organizational}) framework. Based on the research model with 5 main criteria and 22 sub-criteria, we conducted an AHP(Analytical Hierarchy Process) analysis among the experts from domestic medical institutions and SaMD providers to empirically analyze SaMD adoption factors. The results of this study showed that the priority of the main criteria for determining the adoption of AI-based SaMD was in the order of technical factors, economic factors, human factors, organizational factors, and environmental factors. The priority of sub-criteria was in the order of reliability, cost reduction, medical staff's acceptance, safety, top management's support, security, and licensing & regulatory levels. Specifically, technical factors such as reliability, safety, and security were found to be the most important factors for SaMD adoption. In addition, the comparisons and analyses of the weights and priorities of each group showed that the weights and priorities of SaMD adoption factors varied by type of institution, type of medical institution, and type of job in the medical institution.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.4
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• pp.317-322
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• 2009

Purpose: $^{18}$F-flurodeoxyglucose (FDG) uptake on positron emission tomography (PET) scan has been found to reflect tumor aggressiveness and prognosis in various types of cancer. However, pattern of FDG uptake in biliary malignancies and its clinical significance have not been studied well. The purpose of this study was to assess the additional value of $^{18}$F-FDG PET in differential diagnosis and prognosis of cholangiocarcinoma (CC) according to the tumor location and tumor morphology. Materials and Methods: From April 2005 to May 2008, eighty two patients (M:F = 55:27, age 66.2$\pm$9.6 yrs) with CC underwent $^{18}$F-FDG PET. For semiquantitative analysis, the maximum standardized uptake value (SUV$_{max}$) was obtained from the primary tumor. The difference of SUV$_{max}$ according to the tumor location and tumor growth pattern, such as scirrhous type, nodular type, polypoid type were compared. Results: Overall sensitivity of PET scan was 81.7% in CC. SUV$_{max}$ on PET scan in intrahepatic CC was significantly higher compared to extrahepatic CC. In extrahepatic CC, polypoid type showed significantly higher SUV$_{max}$ compared to scirrhous type. Conclusion: $^{18}$F-FDG PET may have a significant impact on clinical decision-making and on the management of intrahepatic cholangiocarcinoma. And it is related to the shape of the tumor and the sensitivity of detection is higher in the mass-forming type than in the scirrhous type.