• Journal of Information Processing Systems
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• v.15 no.3
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• pp.593-603
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• 2019

In wearable healthcare systems, sensor devices can be deployed in places around the human body such as the stomach, back, arms, and legs. The sensors use tiny batteries, which have limited resources, and old sensor batteries must be replaced with new batteries. It is difficult to deploy sensor devices directly into the human body. Therefore, instead of replacing sensor batteries, increasing the lifetime of sensor devices is more efficient. A transmission power control (TPC) algorithm is a representative technique to increase the lifetime of sensor devices. Sensor devices using a TPC algorithm control their transmission power level (TPL) to reduce battery energy consumption. The TPC algorithm operates on a closed-loop mechanism that consists of two parts, such as sensor and sink devices. Most previous research considered only the sink part of devices in the closed-loop. If we consider both the sensor and sink parts of a closed-loop mechanism, sensor devices reduce energy consumption more than previous systems that only consider the sensor part. In this paper, we propose a new approach to consider both the sensor and sink as part of a closed-loop mechanism for efficient energy management of sensor devices. Our proposed approach judges the current channel condition based on the values of various body sensors. If the current channel is not optimal, sensor devices maintain their current TPL without communication to save the sensor's batteries. Otherwise, they find an optimal TPL. To compare performance with other TPC algorithms, we implemented a TPC algorithm and embedded it into sensor devices. Our experimental results show that our new algorithm is better than other TPC algorithms, such as linear, binary, hybrid, and ATPC.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.1
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• pp.1-8
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• 2019

In this study, a maximum power point tracking (MPPT) algorithm based on the perturb and observe (P&O) method with variable step size is proposed to improve the dynamic response characteristic of MPPT, using the existing P&O method. The proposed algorithm, which we verified by simulation and experiment, can track the maximum power point (MPP) through duty control and consisted of three operation modes, namely, constant voltage mode, fast mode, and variable step mode. When the insolation is constant, the voltage variation of the operating point at the MPP is reduced through the step size reduction of the duty in the variable step mode. Consequently, the vibration of the operating point is reduced, and the power generation efficiency is increased. When the insolation changes, the duty and the photovoltaic (PV) voltage are kept constant through the constant voltage mode. The operating point then rapidly tracks the new MPP through the fast-mode operation at the end of the insolation change. When the MPP is reached, the operation is changed to the variable step mode to reduce the duty step size and track the MPP. The validity of the proposed algorithm is verified by simulation and experiment of a PV system composed of a PV panel and a boost converter.

• The Journal of the Korea Contents Association
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• v.14 no.7
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• pp.253-270
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• 2014

Public awareness campaign is the core factor of the national suicide prevention strategies. Korea's current campaign needs to be more systematically developed. This study analyzed the national-level campaigns for suicide prevention of New Zealand, USA, Ireland, Scotland, and Australia whose campaigns were known to be successful, and compared them with those of Korea. With the analysis framework based on the 'Guideline for Effective Health Communication Campaigns' by the U.S. Department of Health and Human Services, we examined the campaigns from the dimensions of (1) clarity of goals, (2) appropriacy of targeting strategies, (3) suitability of messaging strategies, and (4) efficiency of performance. The results show that effective campaigns for suicide prevention have the following common factors: (1) campaign appellations which include clear goals, (2) targeting at risk groups considering social contexts, (3) slogans which contains specific action guidelines, and (4) close relationships between public and private sectors. On this basis, future directions for more effective suicide prevention media campaigns in Korea are discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.168-175
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• 2020

Recently, there has been an increasing need to expand the supply of renewable energy as a solution to greenhouse gas emissions. Therefore, as a measure to promote domestic renewable energy investment and gradual expansion, this study analyzed the investment value of renewable energy projects utilizing the unoccupied spaces of public enterprise's facilities and presented a strategic decision-making framework to support efficient national land development and government measures. The NPV was estimated to be 286 million won if the expansion of the facility was not considered, but it is reasonable to postpone the expansion decision because the value of -130 million won was calculated if the expansion was considered. On the other hand, the real-option value was estimated to be 444 million won, taking SMP uncertainty, expansion, and abandonment options into account, and an additional value of 288 million won was calculated from an analysis of the expansion project using the existing NPV analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.651-656
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• 2014

Corrosion has a significant influence upon the reliability assessment and the maintenance planning of gas pipeline. Corrosion defects occurred on the underground pipeline can be obtained by conducting periodic in-line inspection (ILI). However, little study has been done for practical use of ILI data. This paper deals with remaining lifetime prediction of the gas pipeline in the presence of corrosion defects. Because a pipeline parameter includes uncertainty in its operation, a probabilistic approach is adopted in this paper. A pipeline fails when its operating pressure is larger than the pipe failure pressure. In order to estimate the failure probability, this paper uses First Order Reliability Method (FORM) which is popular in the field of structural engineering. A well-known Battelle code is chosen as the computational model for the pipe failure pressure. This paper develops a Matlab GUI for illustrating failure probability predictions Our result indicates that clustering of corrosion defects is helpful for improving a prediction accuracy and preventing an unnecessary maintenance.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.19-33
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• 2019

Recently, manufacturers have been struggling to efficiently use production equipment as their production methods become more sophisticated and complex. Typical factors hindering the efficiency of the manufacturing process include setup cost due to job change. Especially, in the process of using expensive production equipment such as semiconductor / LCD process, efficient use of equipment is very important. Balancing the tradeoff between meeting the deadline and minimizing setup cost incurred by changes of work type is crucial planning task. In this study, we developed a scheduling model to achieve the goal of minimizing the duedate and setup costs by using reinforcement learning in parallel machines with duedate and work preparation costs. The proposed model is a Deep Q-Network (DQN) scheduling model and is a reinforcement learning-based model. To validate the effectiveness of our proposed model, we compared it against the heuristic model and DNN(deep neural network) based model. It was confirmed that our proposed DQN method causes less due date violation and setup costs than the benchmark methods.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.209-235
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• 2022

Starting from 2010, blockchain technology, along with the development of artificial intelligence, has been in the spotlight as the latest technology to lead the 4th industrial revolution. Furthermore, previous research regarding blockchain's technological applications has been ongoing ever since. However, few studies have been examined the standards for classifying the blockchain economic ecosystem from a capital market perspective. Our study is classified into a collection of interviews of software developers, entrepreneurs, market participants and experts who use blockchain technology to utilize the blockchain economic ecosystem from a capital market perspective for investing in stocks, and case study methodologies of blockchain economic ecosystem according to application fields of blockchain technology. Additionally, as a way that can be used in connection with equity investment in the capital market, the blockchain economic ecosystem classification methodology was established to form an investment universe consisting of global blue-chip stocks. It also helped construct an intelligent portfolio through quantitative and qualitative analysis that are based on quant and artificial intelligence strategies and evaluate its performances. Lastly, it presented a successful investment strategy according to the growth of blockchain economic ecosystem. This study not only classifies and analyzes blockchain standardization as a blockchain economic ecosystem from a capital market, rather than a technical, point of view, but also constructs a portfolio that targets global blue-chip stocks while also developing strategies to achieve superior performances. This study provides insights that are fused with global equity investment from the perspectives of investment theory and the economy. Therefore, it has practical implications that can contribute to the development of capital markets.

• Korean Journal of Construction Engineering and Management
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• v.16 no.4
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• pp.50-59
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• 2015

While the international construction industry for Korean companies have grown in market size exponentially in the recent years, the profit rate of small and medium sized construction companies (SMCCs) are incomparably lower than those of large construction companies. Furthermore, small and medium size companies, especially subcontractor, lacks the judgement of project involvement appropriateness, which leads to an unpredictable profit rate. Therefore, this research aims to create a profit rate prediction model for the international construction project focusing on SMCCs. First, the factors that influence the profit rate and the area of profit zone are defined by using a total of 8,637 projects since the year 1965. Seconds, an extensive literature review is conducted to derive 10 influencing factors. Multiple regression analysis and corresponding judgement technique are used to derive the weight of each factor. Third, cased based reasoning (CBR) methodology is applied to develop the model for profit rate analysis in the project participation review stage. Using 120 validation data set, the developed model showed 11% (14 data sets) of error rate for type 1 and type 2 error. In utilizing the result, project decision makers are able to make decision based on authentic results instead of intuitive based decisions. The model additionally give guidance to the Korean subcontractors when advancing into the international construction based on the model result that shows the profit distribution and checks in advance for the quality of the project to secure a sound profit in each project.

• Korean Journal of Construction Engineering and Management
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• v.18 no.6
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• pp.3-12
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• 2017

In recent years, Project Management Consultant(PMC) project has been emerging as a high-value-added engineering project. However, domestic engineering firms have difficulties in entering the overseas PMC market because of poor project performance and lack of PMC capabilities. To overcome these limitations, this study analyzes the key competitiveness factors for successfully performing the global PMC projects. PMC competency factors based on Porter's double diamond theory were extracted, and a questionnaire survey was conducted on domestic and overseas engineering firms. In addition, the important PMC competency factors were derived through paired t-test and IPA matrix analysis. As a result, the PMC competitiveness of domestic engineering firms was analyzed as around 60% compared to that of global engineering firms. Furthermore, 'PMC track records' and 'project management/owner response skills' were identified as top priority competency factors which are the most necessary factors for present domestic engineering firms. This study is expected to support to establish the international PMC market entry strategies by providing priorities of key competitiveness factors.

• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.43-50
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• 2017

Embedded System includes touch, GPS, motion, and acceleration sensor, and can communicate with neighbor devices using wireless communication. Because Arduino with embedded system provides good environment for development and application, developers, engineers, designers, as well as artists, students have a great interest. They utilize Arduino in the robot, home appliances, fashion, culture and so on. In this paper, we design and implement a game using Arduino with embedded system which recognizes the human movement by moving away from one-dimensional game of the existing touch method. Implemented embedded system game measures gyro-sensor to recognize human movement and detects the attack success of the opponent by using touch sensor. Moreover, health of the game player is updated in the real time through the android phone-based database. In this paper, implemented embedded system-based game provides GUI screen of android phone. It is possible to select watching mode and competition mode. Also, it has low energy consumption and easy to expand because it send and receive data packet through recent Bluetooth communication.