• Journal of Fashion Business
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• v.12 no.5
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• pp.155-167
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• 2008

With globalization and competitive market environment, companies realize how marketing channels are important in order to survive and succeed the business. The importance of information management among channels is getting increased, and is needed for SCM. Nevertheless having hard situation to implement SCM, SCM for textile fashion industry engaged in small business mostly is the way to break through the difficulty on so many channels to go through from fiber to retail. Therefore, the purpose of this case study to L firm by using questionnaire based interviewing method was to investigate how textile fashion small business can implement the SCM with their own differentiated strategy differed from a large corporation. L firm conducted SCM-ISN (Information Service Network) under the restructuring project. So they could use electronic bidding system via internet and have information sharing with their partners such as retailers. Therefore, they could expand market share to Seoul and reduce inventory and manage their customer more effectively than before.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.3
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• pp.757-764
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• 2008

It is important to know the activities itself exactly and to control the activities correctly so as to assure timely progress and the quality of any project. In order to progress smoothly in accordance with construction schedule, it is important to systematize the preliminary arrangements necessary for each process and then manage them. In this study, in order to progress smoothly the qualify and schedule management of the construction, We can make systematically preliminary works in accordance with construction schedule by the architecture construction items of the apartment house construction. We suggested important preliminary control item by the workers through experiential method of construction engineers in accordance with network schedule. should not use "we" in technical sentence.

• Computers and Concrete
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• v.21 no.6
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• pp.697-703
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• 2018

Compressive strength is one of the most important engineering properties of concrete, and testing of the compressive strength of concrete specimens is often costly and time consuming. In order to provide the time for concrete form removal, re-shoring to slab, project scheduling and quality control, it is necessary to predict the concrete strength based upon the early strength data. However, concrete compressive strength is affected by many factors, such as quality of raw materials, water cement ratio, ratio of fine aggregate to coarse aggregate, age of concrete, compaction of concrete, temperature, relative humidity and curing of concrete. The concrete compressive strength is a quite nonlinear function that changes depend on the materials used in the concrete and the time. This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for the prediction of concrete compressive strength. The training of fuzzy system was performed by a hybrid method of gradient descent method and least squares algorithm, and the subtractive clustering algorithm (SCA) was utilized for optimizing the number of fuzzy rules. Experimental data on concrete compressive strength in the literature were used to validate and evaluate the performance of the proposed ANFIS model. Further, predictions from three models (the back propagation neural network model, the statistics model, and the ANFIS model) were compared with the experimental data. The results show that the proposed ANFIS model is a feasible, efficient, and accurate tool for predicting the concrete compressive strength.

• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.40-49
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• 2019

Reinforcement learning has been applied to various problems in robotics. However, it was still hard to train complex robotic manipulation tasks since there is a few models which can be applicable to general tasks. Such general models require a lot of training episodes. In these reasons, deep neural networks which have shown to be good function approximators have not been actively used for robot manipulation task. Recently, some of these challenges are solved by a set of methods, such as Guided Policy Search, which guide or limit search directions while training of a deep neural network based policy model. These frameworks are already applied to a humanoid robot, PR2. However, in robotics, it is not trivial to adjust existing algorithms designed for one robot to another robot. In this paper, we present our implementation of Guided Policy Search to the robotic arms of the Baxter Research Robot. To meet the goals and needs of the project, we build on an existing implementation of Baxter Agent class for the Guided Policy Search algorithm code using the built-in Python interface. This work is expected to play an important role in popularizing robot manipulation reinforcement learning methods on cost-effective robot platforms.

• Journal of Urban Science
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• v.7 no.2
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• pp.37-46
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• 2018

The purpose of this study is to review and evaluate the proper planning for 2030 Incheon Urban Parks & Green Space Master Plan. Some of the plans are aimed at multiple small districts within the city's old town, as local governments are planned to be sub-subsidized by Incheon Metropolitan City. However, these plans have become simple plans for each district and therefore find it difficult to collect from the perspective of the using system of the residents who are directly used. First, the construction of the urban park and green space network requires the construction of a service using system that can be felt by the users. Second, the basic idea of each district planned as the detailed strategy of the master plan should be planned through consultation with nearby the district. Third, specific targets and directions for the urban park and green space plan through the urban development project are needed.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.27-38
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• 2019

Sensors collect information for Internet of Things (IoT)-based services. However, indoor construction sites have a poor communication environment and many interfering elements that make it difficult to collect sensor information. In this study, a network was constructed between a Bluetooth Low Energy (BLE)-based IoT device based on a serverless IoT framework and a router. This experimental environment was applied to large- and small-scale indoor construction sites. Experiments were performed to test the communication performance of BLE-based IoT devices and routers at indoor construction sites. An analysis of the received signal strength indication (RSSI) graph patterns collected from the communication between the BLE-based IoT devices and routers for different testbed site situation revealed areas with good communication performance and poor communication performance due to interfering factors. The results confirmed that structural components of the building as well as the materials, equipment, and temporary facilities used in indoor construction interfere with the communication performance. Construction project managers will require improved technical knowledge of IoT, such as optimizing the router placement and matching communication between the router and workers, to improve the communication performance for large-scale indoor construction.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.63.2-63.2
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• 2019

Eight hundred thousand asteroids in the solar system have been identified so far under extensive sky surveys. Kilometer to sub-km sized asteroids, however, are still waiting for discovery, and their size and orbital distribution will provide a better understanding of the collisional and dynamical evolution of the solar system. In order to study the number of asteroids which is detectable with 1.6 m telescope and their orbital distribution, we conducted a small observation campaign as a part of Deep Ecliptic Patrol of the Southern Sky (DEEP-South) project, which is an asteroid survey in the southern hemisphere with Korea Microlensing Telescope Network (KMTNet). We observed the ecliptic plane near opposition ($2^{\circ}{\times}2^{\circ}$ field of view centering on ${\alpha}=22h40m31s$, ${\delta}=-08^{\circ}22^{\prime}58^{{\prime}{\prime}}$) in August 2018, and identified 464 moving objects by visual inspection. As a result, 266 of 464 moving objects turn out to be previously unknown asteroids, and their signal to noise ratio is below two on numerous occasions. Most of the newly detected objects are main belt asteroids (MBAs), while three Hildas, one Jupiter trojan, and two Hungarias are also identified. In this meeting, we report the differences in the orbital distributions between the previously known asteroids and newly discovered ones using statistical methods. We also talk about the observational bias of this survey and suggest future works.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.63.1-63.1
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• 2019

Solar system small bodies are unusual objects in astronomical survey data in that they are moving on the celestial sphere. In addition, even in a normal status, their magnitudes are changing over time, firstly because their relative positions with respect to the Sun and Earth are continually changing, secondly because they are rotating bodies with non-spherical shapes. Furthermore, some of them might exhibit unexpected activities, which could be caused by mass ejection or disintegration. Detections and observations of such activities are challenging due to their abrupt nature. Therefore, continuous monitoring observations of large number of Solar system small bodies are required to systematically obtain detailed/transient information about them. Since 2018/2019 winter, we have launched a new project using Korea Microlensing Telescope Network (KMTNet) for detecting such transient phenomena of Solar system objects. Our main goal is to monitor the magnitudes and detect sudden brightness changes. We also plan to discover interesting new objects, and monitor rotational brightness oscillations of asteroids. We intend to monitor the magnitudes of ~ 20,000 known Solar system small bodies per night, and acquire lightcurves of ~ 1,000 asteroids.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.333-339
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• 2021

The study seeks to identify the determinants of the adoption of e-commerce by small and medium-sized enterprises (SMEs) in developing countries, in our case, in Indonesia. The aim of this study is to examine the factors influencing e-commerce adoption. This study uses the method of quantitative data collection based on a questionnaire survey of SMEs in Indonesia. The research relies on Regional Project stipulations regarding Business Development in Indonesia, to capture businesses with a range of 5 to 100 employees that are classified as SMEs. This study randomly chose 100 SMEs in Indonesia from the IndoNetwork database. Partial least square (PLS) structural model data processing was used for path coefficients analysis. Structural equation modeling is applied in this study to analyze the determinant factors on the e-commerce adoption. The study findings reveal that four factors, namely, perceived benefits, compatibility, technology readiness, and government support, significantly influence the adoption of e-commerce, whereas customer/supplier pressure does not have influence. So, this study concludes that perceived benefits, compatibility, technology readiness, and government support had a significant and positive relationship with e-commerce adoption. Meanwhile, customer/supplier pressure had no effect on the e-commerce adoption of by Indonesia SMEs.

• The Journal of Industrial Distribution & Business
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• v.11 no.12
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• pp.7-15
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• 2020

Purpose: This study aims to explore the feasibility of expanding complex wards to provide efficient hospital management and high-quality medical services to local residents of Gangneung Medical Center (GMC). Research Design, Data and Methodology: There are four research designs to achieve the research objectives. We analyzed Big Data for 3 months on Social Network Services (SNS). A questionnaire survey conducted on 219 patients visiting the GMC. Surveys of 20 employees of the GMC applied. The feasibility to expand the GMC ward measured through Focus Group Interview by 12 internal and external experts. Data analysis methods derived from various surveys applied with data mining technique, frequency analysis, and Importance-Performance Analysis methods, and IBM SPSS statistical package program applied for data processing. Results: In the result of the big data analysis, the GMC's recognition on SNS is high. 95.9% of the residents and 100.0% of the employees required the need for the complex ward extension. In the analysis of expert opinion, in the future functions of GMC, specialized care (△3.3) and public medicine (△1.4) increased significantly. Conclusion: GMC's complex ward extension is an urgent and indispensable project to provide efficient hospital management and service quality.