• Convergence Security Journal
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• v.13 no.3
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• pp.71-77
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• 2013

In our country security industry biz model analysis methodology fragmentary theory exists, but it is hard to find a comprehensive analysis methodology. Biz model analysis IT companies the external factors and internal factors to integrate the information gathered about the comprehensive analysis of the development of an information system are required. Information support system early in the software architecture of the system design decisions early decision as the design, development, testing, maintenance, has a lasting impact on the project as a guideline in the development of a framework of design abstraction. BMO evaluation support information systems architecture designs system purposes. The mission must support the execution. Information system stakeholders to determine the mission and the environment. All information systems architecture shall have architecture. Technology architecture should be documented with each other can be used. Determine the architecture based architecture descriptions are presented.

• The Journal of the Korea Contents Association
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• v.16 no.4
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• pp.36-44
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• 2016

This article serves as a guideline to the policy on Korea brain science program. Given limited resources within Korea, setting priorities in brain science topics is important in science policy. In this study, we determined the priorities of important brain science topics based on the frontier properties, innovativeness, and prospective outcome. Firstly, the significant topics were chosen after the interview with the top nationwide brain scientists, which were neuroglia, brain precision medicine, neuromorphic engineering, neuroepigenetics, and brain oscillation. Secondly, the analytic hierarchy process (AHP) survey were conducted to prioritize and assign the important weight for not only the criteria but also the research topics in pair choice evaluation. In regards to the importance among the criteria, prospects of the topic was determined to be the top criterion to ranked criterion to consider in the government investment. The priority of the research topics was determined by the order for the project to be considered in national science policy in a comparative way.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.2
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• pp.129-134
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• 2008

In this paper, we carry out the simulation for an optimal solution of one-dimensional nonlinear photonic crystal structure using Genetic algorithm, and show the proposed method to apply for photonic transistors. Unlike a conventional steepest descent method for an optimization, the proposed method based on Genetic Algorithm has advantages for finding out excellent solutions without any analytic forms, which can easily apply to other applications. Also, as several solutions around global minimum solution can be obtained, it is very good optimization tool to give us the patterns about the optimal structure of a photonic crystal transistor. To design an all-optical filter transistor, Neural network algorithm is firstly performed for an initial design and then Genetic Algorithm is finally used to get the optimal solution. From the simulation of one-dimensional photonic crystal transistor, 27dB of the switching On/Off ratio is obtained.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7C
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• pp.642-650
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• 2010

Collaborative spectrum sensing allows secondary users scattered in location to work together to detect the activity of primary users and has been shown to significantly reduce the performance degradation due to fading phenomenon. Most previous works on collaborative spectrum sensing are based on the assumption that local spectrum sensing decisions of secondary users are statistically independent. However, it may not hold in some practical situations with shadowing effect. In this paper, we consider the case that the secondary users are evenly spaced in the form of a linear array and only adjacent secondary users are statistically correlated, and analyze the effect of the statistical correlation on the performance of collaborative spectrum sensing and the throughput of a cognitive radio network. Here we assumed the AND and OR fusion rules for combining the local decisions of secondary users. The analysis showed that the AND fusion rule achieves higher throughput than the OR fusion rule.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.439-449
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• 2020

This study aimed to identify factors influencing the preferences for end-of-life (EOL) care among undergraduate nursing students. In this cross-sectional study, data were collected from December 2017 to February 2018. This study included 217 undergraduate nursing students. Factors influencing the preference for 'autonomous physiological decision-making' were the following: education level(by grade), having biomedical education, attitude towards death, and attitude towards life-sustaining treatments (LSTs). Preference for 'decision-making by healthcare professionals' was related to having a religion. Factors influencing the preference for 'spirituality' were education level, having a religion, and academic major satisfaction. Preference for 'pain control' was associated with education level, experience with dying patients, bad self-rated health, attitude towards death, and attitude towards LSTs. The study findings suggest that education regarding LSTs, EOL care, and EOL decision-making in nursing curricula is essential.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.219-225
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• 2021

As for the battery package method, a prismatic package method is preferred for stability reasons, but it is rapidly expanding due to the stability verification of a pouch type package. The pouch type using the lamination process has an advantage of high battery energy density because it can reduce space waste, but has a disadvantage of low productivity. Therefore, in this paper, by extracting edge detection algorithm precision, pattern algorithm precision, and motion controller recall rate by improving backlight lighting fixtures to minimize light diffusion, securing standards for stereo camera position relationship displacement monitoring, and securing standards for lens release monitoring. We propose to implement a system that ensures accuracy and reliability in positioning. As a result of the experiment, the proposed system shows an average error range of 0.032mm for edge detection, 0.02mm for pattern algorithm, and 0.014mm for motion controller, thus ensuring the accuracy and reliability of the positioning mechanism.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.69-76
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• 2020

In this paper, the problem of determining the optimal time to market of software was studied using error correction time, an indicator of error correction difficulty. In particular, it was intended to modify the assumption that error detection time and correction time are independent in the software reliability growth model considering the existing error correction time, and to establish a general framework model that expresses the correlation between error detection time and correction time to determine when the software will be released. The results showed that it was important from an economic perspective to detect errors that took time to correct early in the test. It was concluded that it was very important to analyze the correlation between error detection time and error correction time in determining when to release the optimal software.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.117-125
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• 2017

People believe that they make a rational decision. But the results of behavioral economics research show that people make a emotional decision at many times. The perception of fairness is one of the example in emotional decision. Sometimes people give up their monetary profit and revenge counterpart when they feel unfair. So the perception of fairness is very important. Two experiment was conducted. In experiment 1, researcher studied the effect of the pre-investment cost in perception of fairness. The result showed people who had pre-investment cost thought more unfair but were more likely to continue prior decision. In experiment 2, researcher studied the effect of type of CEO and message frame in perception of fairness. The results showed that people thought the proposal was more unfair when CEO was son of founder and message was gain and loss framing message.

• Information Systems Review
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• v.22 no.4
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• pp.41-58
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• 2020

This study addresses the issue of which factors make domestic works have turnover intention. To pursue this research issue, we utilized a public database "2017 Occupational Migration Path Survey", administerd by Korea Employment Information Service (KEIS). Decision tree method was applied to extract crucial factors influencing workers' turnover intention. They include 'the degree of matching the level of education with the level of work', 'the possibility of individual development', 'the job-related education and training', 'the promotion system', 'wage and income', 'social reputation for work' and 'the stability of employment'.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.186-191
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• 2023

Data processing techniques play a critical role in decision-making, including handling missing and outlier data, prediction, and recommendation models. This requires a clear explanation of the validity, reliability, and accuracy of all processes and results. In addition, it is necessary to solve data problems through explainable models using decision trees, inference, etc., and proceed with model lightweight by considering various types of learning. The multi-layer mining classification method that applies the sixth principle is a method that discovers multidimensional relationships between variables and attributes that occur frequently in transactions after data preprocessing. This explains how to discover significant relationships using mining on transactions and model the data through regression analysis. It develops scalable models and logistic regression models and proposes mining techniques to generate class labels through data cleansing, relevance analysis, data transformation, and data augmentation to make explanatory decisions.