• Korean Management Science Review
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• v.27 no.3
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• pp.137-147
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• 2010

Real-time supply chain environments based on RFID will be an important topic in future society; Nevertheless, adopting RFID in real industry SCM is still in its infancy. The aim of this paper is to develop the physical framework of a fully adopting RFID system from manufacturing to recycle phase and measure the effect. So, we built a simulation station with fully appling RFID and analyzed benefits with mathematic model. Then, specifying the advantages and improvement scheme for real industry limitations were suggested. This work concluded that fully appling RFID in SCM gives improvement of quality and service to both production and consumer.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.278-288
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• 2020

Modular Integrated Construction (MiC) has gained quite momentum as it provides solutions for several problems in the construction sector, particularly in Hong Kong. MiC is converting the building into modules and erecting them easily on site providing various benefits, such as cost and time savings, better quality, lower risk, higher sustainability, less injuries and accidents, etc. The MiC is considered the best alternative to traditional construction approaches in solving the huge housing demand problem in many cities all over the world due to the time-saving privilege. The utilization of MiC is facing a lot of challenges, which are considered obstacles to the wide acceptance of this technique in the construction industry in Hong Kong. This, in turn, has led the interests of the research community to investigate its benefits and challenges aiming at addressing several solutions to harness the benefits of this technique and to tackle these challenges. The present research aims to review the main concept of MiC and to determine the benefits and the challenges of implementing MiC in construction industry. The findings of this research highlight the advantages and limitations of incorporating MiC technique in Hong Kong, which will help the stakeholders to effectively utilize this technique in the construction industry.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.5
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• pp.649-659
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• 2013

Real time control (RTC) can be broadly defined as a system that dynamically adjusts the operation of facilities in response to online measurements in the field to maintain and meet the operational objectives, both during dry and wet weather conditions. RTC adds a dynamic component that is actively adjusted in real time based on system conditions. In terms of reducing or eliminating sewer flooding, CSOs and/or managing flows, implementation of RTC has various benefits to sewer system operation. It has been emerging as an attractive approach, but related elements (such as framework for the application, its components and equipments, aspects to be considered) towards its application on sewer systems have not been throughly introduced so far. The main goal of this study is to review several applications of RTC and firm guidelines published abroad, and finally to provide a framework for the proper application of RTC on sewer systems.

• Journal of the Korean Solar Energy Society
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• v.40 no.3
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• pp.1-20
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• 2020

In accordance with the Government's policy, renewable power generation is expanding very largely. This leads to increasing uncertainty in the power market and power system owing to the intermittent and fluctuating output characteristics of renewable power generators. Data on the acquisition of renewable power generators can be largely classified according to the operation of the power market and power system. Data on the settlement for the payment for the power amount are acquired in the power market, and real-time data for monitoring the status and output of the generators are acquired in the power system. However, renewable power generators operating in the power market have different acquisition cycles depending on the method of communication of the power meter. They acquire data only for settlement purposes and have no real-time data, which requires improvement. In this paper, the acquisition status is reviewed by classifying the data of renewable power generators into settlement and real-time data. In addition, measures and acquisition criteria for real-time data of renewable power generators for improving the acquisition method are proposed.

• Fourth Industrial Review
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• v.3 no.1
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• pp.13-20
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• 2023

Purpose - By designing a PEF(Personalized Education Feedback) system for real-time prediction of learning achievement and motivation through real-time EEG analysis of learners, this system provides some modules of a personalized adaptive learning system. By applying these modules to e-learning and offline learning, they motivate learners and improve the quality of learning progress and effective learning outcomes can be achieved for immersive self-directed learning Research design, data, and methodology - EEG data were collected simultaneously as the English test was given to the experimenters, and the correlation between the correct answer result and the EEG data was learned with a machine learning algorithm and the predictive model was evaluated.. Result - In model performance evaluation, both artificial neural networks(ANNs) and support vector machines(SVMs) showed high accuracy of more than 91%. Conclusion - This research provides some modules of personalized adaptive learning systems that can more efficiently complete by designing a PEF system for real-time learning achievement prediction and learning motivation through an adaptive learning system based on real-time EEG analysis of learners. The implication of this initial research is to verify hypothetical situations for the development of an adaptive learning system through EEG analysis-based learning achievement prediction.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.23 no.2
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• pp.121-131
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• 2020

Purpose: To determine the long-term efficacy of the anti-tumor necrosis factor (TNF) agents, infliximab (IFX) and adalimumab (ADA), in pediatric luminal Crohn's disease (CD) by performing a systematic literature review. Methods: An electronic search was performed in Medline, Embase, and the Cochrane Library from inception to September 26, 2019. Eligible studies were cohort studies with observation periods that exceeded 1 year. Studies that reported time-to-event analyses were included. Events were defined as discontinuation of anti-TNF therapy for secondary loss of response. We extracted the probabilities of continuing anti-TNF therapy 1, 2, and 3 years after initiation. Results: In total, 2,464 papers were screened, 94 were selected for full text review, and 13 studies (11 on IFX, 2 on ADA) met our eligibility criteria for inclusion. After 1 year, 83-97% of patients were still receiving IFX therapy. After 2 and 3 years the probability of continuing IFX therapy decreased to 67-91% and 61-85%, respectively. In total, 5 of the 11 studies subgrouped by concomitant medication consistently showed that the probabilities of continuing IFX therapy in patients with prolonged immunomodulator use were higher than those in patients on IFX monotherapy. Conclusion: This review of real-world evidence studies confirms the long-term therapeutic benefit of IFX therapy in diverse cohorts of children with luminal CD. Moreover, it supports the view that combination therapy with an immunomodulator prolongs the durability of IFX therapy in patients who previously failed to recover following first-line therapy. The limited number of time-to-event studies in patients on ADA prevented us from drawing definite conclusions about its long-term efficacy.

• Korea Real Estate Review
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• v.27 no.3
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• pp.71-86
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• 2017

The purpose of this study was to apply the deep running method to real estate price index predicting and to compare it with the time series analysis method to test the possibility of its application to real estate market forecasting. Various real estate price indices were predicted using the DNN (deep neural networks) and LSTM (long short term memory networks) models, both of which draw on the deep learning method, and the ARIMA (autoregressive integrated moving average) model, which is based on the time seies analysis method. The results of the study showed the following. First, the predictive power of the deep learning method is superior to that of the time series analysis method. Second, among the deep learning models, the predictability of the DNN model is slightly superior to that of the LSTM model. Third, the deep learning method and the ARIMA model are the least reliable tools for predicting the housing sales prices index among the real estate price indices. Drawing on the deep learning method, it is hoped that this study will help enhance the accuracy in predicting the real estate market dynamics.

• Korean Management Science Review
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• v.23 no.2
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• pp.175-185
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• 2006

How to efficiently manage assembly blocks at shipyard has been a hot management issue in the shipbuilding Industry, because it has significantly influenced on the productivity of shipbuilding process. This paper introduces the real practice of assembly block operations management in Hyundai Heavy Industries (HHI) and the Ship Assembly Block Operations Optimization (SABOO) project that h3s been launched in HHI as an academy-and-industry collaborative project, aimed to diagnose problems, propose possible solutions, and develop a prototype system in order to search ways of improving the assembly block operations management. Through the field interviews, observations, and benchmarking studies, the SABOO project diagnosed the most rudimental and urgent problem and proposed possible solutions. In addition, the SABOO project developed the prototype system that embodied the visual function of monitoring the shipyard on a real-time and the Interactive block assignment function that utilized the assembly block assignment algorithm developed by the project. As a whole, the SABOO project tested the possibility and gained an insight in extending the functions of block transportation/stockyard management system.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2008.05a
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• pp.147-151
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• 2008

Construction project is completed through several stages and problems of each stage affect directly not only now but also next. Defect of 2D drawings influence in construction phase, and it make many loss on project. Nowadays we practically use real Mock-up test in construction sites to solve the problems. But it also has many problems which are waste much money and time. Therefore, this study tries to analyze effect that is occurred by appling BIM Mock-up simulation instead of real Mock-up execution. These analysis is conducted by comparing two construction building site. These have same shape but one is made for BIM Mock-up, and another is real Mock-up. Comparison points of view are cost, time and operator's satisfaction. It is expect that BIM Mock-up is more effective at low cost and on shorter time. But our analysis show that each are conducted different part of function. So new Mock-up type is required. Hybrid Mock-up is combine real mock-up with BIM simulation and it can minimize risk of project.

• Korean Management Science Review
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• v.13 no.1
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• pp.13-27
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• 1996

This paper considers the sequencing problem in mixed model assembly lines with hybrid workstation types and sequence-dependent setup times. Computation time is often a critical factor in choosing a method of determining the sequence. We develop a mathematical formulation of the problem to minimize the overall length of a line, and present a tabu search technique which can provide a near optimal solution in real time. The proposed technique is compared with a genetic algorithm and a branch-and-bound method. Experimental results are reported to demonstrate the efficiency of the technique.