• Journal of Korean Society of Rural Planning
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• v.26 no.3
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• pp.91-102
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• 2020

The purpose of study was analyze the pumping characteristics, Irrigation Efficiency(IE), and irrigation pattern by period of rice growing stage with based on the performance of design irrigation water requirement and operational Galshin Pumping(GP) station in GP irrigation district constructed under rural water development project master plan. GP station was located in Yedang reservoir, Yesan-gun, Chungcheongnam-do and has been supplying irrigation water since 2006. The research data are the Irrigation Water Requirement(IWR) and the Pumping Water Amount(PWA) from 2006 to 2015 at the GP station, which is the supplied amount. The IWR were calculated using the Blaney-Criddle formula of the HOMWRS program, Hydrological Operation Model for Water Resource System, developed by Korea Rural Community Corporation. The Blaney-Criddle formula was used to calculate design irrigation water requirement of Galshin rural water development project master plan. During 2006-2015, the study period, the annual average IWR is 763.2(±149.1)mm, the annual PWA of the GP station is 397.4mm to 1,056.9mm, and those average annual PWA is 643.4(±208.4)mm. The annual IE of GP station 96.5% to 169.0%, and the average annual IE is 124.3%, which is higher than the research results conducted in other pumping stations. Analyzing the irrigation patterns of the GP irrigation district, the IWR Ratio per 10days(IWRR) and the PWA Ratio per 10days(PWAR) of the G P station were obtained. The IWRR is the percentage of IWR for each 10 days of a month to total IWR per year, and the PWAR is the percentage of PWA for each 10 days of a month to total PWA per year. The Kolmogorov- Smirnov(K-S) test results of IWRR and PWAR showed the characteristics classification by rice growing stage and stable normal distribution characteristics. Average IWRR(AIWRR) and Average PWAR(APWAR) are presented as irrigation patterns. Irrigation pattern analysis will be able to standardize comparison, analysis and probability calculation of the pumping station characteristics of different pumping stations and apply to objective evaluation of the pumping station district.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6A
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• pp.458-467
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• 2009

Long Tenn Evolution (LTE) is the next generation mobile phone technology which has being standardized by the Third Generation Partnership Project (3GPP). In the existing mobile communication networks, voice traffic is delivered through circuit switched networks. In LTE, however, all kinds of traffic are transferred through IP based packet switched networks which has best-effort characteristic. Therefore, providing QoS in LTE system is difficult. In order to provide QoS in LTE, RRM is very important. Especially, in part of RRM, call admission control (CAC) performs an important function to reduce network congestion and guarantee a certain level of QoS for on-going calls. In this paper, we propose a CAC algorithm in order to provide QoS for various kinds of services in LTE system. The performance of the proposed algorithm is evaluated with various simulation environments. The results show that the proposed algorithm provides QoS through rejections of requested calls. Especially, the proposed CAC algorithm can be satisfied with packet delay requirement defined in LTE specification.

• Journal of the Korean Society of Propulsion Engineers
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• v.15 no.3
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• pp.15-21
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• 2011

With petroleum reserves dwindling, interest has been increasing worldwide in Fischer-Tropsch synthesis (FT) as a method of producing synthetic liquid fuels and chemicals from coal, natural gas or biomass. In general, FT synthesis is operated through the gas phase fixed-bed reaction system. Recently, there are lots of study in supercritical fluid due to unique characteristics such as the quick diffusion of reactant gas, effective removal of reaction heat, and the in-situ extraction of high molecular weight hydrocarbon, such as wax. In this study, our major aim is to obtain a deeper insight into the effect of the type of support on the reaction performance over a supported cobalt catalyst in a fixed bed reactor.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.28-34
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• 2021

In the case of object detection using deep learning, both accuracy and real-time are required. However, it is difficult to use a deep learning model that processes a large amount of data in a limited resource environment. To solve this problem, this paper proposes an object detection model for small embedded devices. Unlike the general detection model, the model size was minimized by using a structure in which the pre-trained feature extractor was removed. The structure of the model was designed by repeatedly stacking lightweight convolution blocks. In addition, the number of region proposals is greatly reduced to reduce detection overhead. The proposed model was trained and evaluated using the public dataset PASCAL VOC. For quantitative evaluation of the model, detection performance was measured with average precision used in the detection field. And the detection speed was measured in a Raspberry Pi similar to an actual embedded device. Through the experiment, we achieved improved accuracy and faster reasoning speed compared to the existing detection method.

• Journal of KIBIM
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• v.11 no.3
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• pp.45-54
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• 2021

The augmented reality (AR) has recently became an attractive technology in construction industry, which can play a critical role in realizing smart construction concepts. The AR has a great potential to help construction workers access digitalized information about design and construction more flexibly and efficiently. Though several AR applications have been introduced for on-site made to enhance on-site and off-site tasks, few are utilized in actual construction fields. This paper proposes a new AR framework that provides on-site managers with an opportunity to easily access the information about construction resources such as workers and equipment. The framework records videos with the camera installed on a wearable AR device and streams the video in a server equipped with high-performance processors, which runs an object detection algorithm on the streamed video in real time. The detection results are sent back to the AR device so that menu buttons are visualized on the detected objects in the user's view. A user is allowed to access the information about a worker or equipment appeared in one's view, by touching the menu button visualized on the resource. This paper details implementing parts of the framework, which requires the data transmission between the AR device and the server. It also discusses thoroughly about accompanied issues and the feasibility of the proposed framework.

• The Journal of the Korea Contents Association
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• v.19 no.4
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• pp.79-90
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• 2019

As an increasing number of cloud service providers begin to provide cloud computing services, they form a competitive market to compete for users. Due to different resource configurations and service workloads, users may observe different response times for their service requests and experience different levels of service quality. To compete for cloud users, it is crucial for each cloud service provider to determine an optimal price that best corresponds to their service qualities while also guaranteeing maximum profit. To achieve this goal, the underlying rationale and characteristics in this competitive market must be clarified. In this paper, we analyze price competition in the multimedia cloud service market with two service providers. We characterize the nature of non-cooperative games in a duopoly multimedia cloud service market with the goal of capturing how each cloud service provider determines its optimal price to compete with the other and maximize its own profit. To do this, we introduce a queueing model to characterize the service process in a multimedia cloud data center. Based on performance measures of the proposed queueing model, we suggest a price competition problem in a duopoly multimedia cloud service market. By solving this problem, we can obtain the optimal equilibrium prices.

• Smart Media Journal
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• v.8 no.2
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• pp.21-28
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• 2019

Recent research on energy harvesting wireless sensor networks focuses on the development of techniques to solve the limited energy resource problem and to extend the whole network life efficiently. Energy harvesting technology can increase the lifetime of a network, but data transmission becomes unavailable when it harvests energy from radio frequency, resulting longer network delay with respect to the increased time in energy harvesting. Therefore, building energy harvesting wireless sensor network should consider the possible network delay as well as the network lifetime problem. In this paper, we propose a new MAC protocol that minimizes end-to-end network delay by adjusting the data transmission time for a packet based on estimating the energy for data transmission along with the amount of traffic flowing into the network and harvested energy. For this goal, it engineers an energy management mechanism that adjusts the sleep time of the network by measuring energy harvesting time. In addition, with simulation results it shows that the proposed MAC protocol improves the performance in terms of energy consumption and end-to-end delay, compared to the existing MAC protocols.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.207-223
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• 2019

This study aims to explore the casual relation between construction company employees' Self-Leadership and two variables: Organization Citizenship Behaviour and Organizational Trust through Psychology Empowerment. To explain in details, this study examines how the independent variable, Self Leadership, with its behavior-focused, natural reward and constructive thought pattern strategies, affects the dependent variable, Organization Citizenship Behavior and Organizational Trust through the intervening variable, Psychology Empowerment. A survey was conducted on current employees of construction companies in metropolitan areas to empirically examine the research model. The result of study hypothesis on Self-Leadership is as follows; first, Self-Leadership showed a positive effect on Psychology Empowerment, Organization Citizenship Behaviour and Organizational Trust. Second, Psychology Empowerment showed a positive effect on Organization Citizenship Behaviour. Third, Psychology Empowerment showed a positive effect on Organizational Trust. The capacity of individuals is critical when it comes to competitiveness of construction companies. When employees willingly participate in building trust within the company, the work place will become more and more constructive; based on trust, efficiency will increase because people from different processes can work together and performance will also improve even when project managers are absent because others could help their role instead, thus driving more efficient human resource management to the company. To conclude, a company's vision can be spread wide and far when their employees engage themselves in Learning Organization with Self Leadership. They will also be satisfied with their work through improving interpersonal relationship at work.

• Journal of IKEEE
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• v.23 no.3
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• pp.852-857
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• 2019

In order to manage the demand resources of project participants and to provide appropriate strategies in the virtual power plant's power trading platform for consumers or operators who want to participate in the distributed resource collective trading market, it is very important to forecast the next day's demand of individual participants and the overall system's electricity demand. This paper developed a power demand forecasting model for the next day. For the model, we used LSTM algorithm of deep learning technique in consideration of time series characteristics of power demand forecasting data, and new scheme is applied by applying one-hot encoding method to input/output values such as power demand. In the performance evaluation for comparing the general DNN with our LSTM forecasting model, both model showed 4.50 and 1.89 of root mean square error, respectively, and our LSTM model showed high prediction accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.100-103
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• 2019

Due to the fourth industrial revolution called 'fusion and connection', interest in 'high connectivity society' and 'highland society' is increasing, and related objects are not limited to automation and connected cars. The Internet of Things is the main concern of the 4th Industrial Revolution and it is expected to play an important role in establishing the basis of the next generation mobile communication service. Several domestic and foreign companies have been studying various types of LPWANs for the construction of the Internet based on things, and there is Semtech's LoRaWAN technology as representative. LoRaWAN is a long-distance, low-power network designed to manage a large number of devices and sensors, with communications from hundreds to thousands to thousands of devices and sensors. In this paper, we analyze the optimum node capacity of gateway for maximum performance while reducing resource waste in using LoRaWAN.