• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1229-1244
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• 2017

In recent years, as demand for data-based analytical methodologies increases in various fields, optimization methods have been developed to handle them. In particular, various constraints required for problems in statistics and machine learning can be solved by convex optimization. Alternating direction method of multipliers (ADMM) can effectively deal with linear constraints, and it can be effectively used as a parallel optimization algorithm. ADMM is an approximation algorithm that solves complex original problems by dividing and combining the partial problems that are easier to optimize than original problems. It is useful for optimizing non-smooth or composite objective functions. It is widely used in statistical and machine learning because it can systematically construct algorithms based on dual theory and proximal operator. In this paper, we will examine applications of ADMM algorithm in various fields related to statistics, and focus on two major points: (1) splitting strategy of objective function, and (2) role of the proximal operator in explaining the Lagrangian method and its dual problem. In this case, we introduce methodologies that utilize regularization. Simulation results are presented to demonstrate effectiveness of the lasso.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.431-437
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• 2016

Since the game is industrialized in the 1970s, efforts to study attributions throughout the definition of the game has been continued. This study analyzed the importance of 7 attributions including rule, goal, conflict, activity, decision-making, voluntary, art that were collectively organized by Katie Salen & Eric Zimmerman using AHP. For this, we analyzed the data after subjected to pair-wise comparison survey through the gaming industry experts, and the result was confirmed that match the analysis model comparing with the survey of game players. In this analysis of the importance, Goal(24%) is the greatest important in the seven factors mentioned above. Art(16%),Voluntary(15%), Rule(13%) followed after it. So, We can find out which attributes are considered important in the game development process through this Research.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.75-81
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• 2021

The purpose of this research is to derive and evaluate priorities for critical factors that must be determined before an enterprise adopts a cloud computing service. AHP analysis techniques were used to reflect decisions made by experts as research methods. AHP is a decision-making technique that expresses complex decision-making problems hierarchically and derives the best alternatives through pairwise comparison between the items of the hierarchy. Compared to the existing statistical decision making techniques, the decision making process is systematic and simple, making it easy to understand. In addition, the procedure is also reasonable by providing an indicator to determine the consistency of the decision maker in the analysis process. The analysis results of this research showed that security was the first priority, reliability was the second priority, and economic efficiency was the third priority. Among the factors in the first-priority security items, the access control rights and the safety factors of external threats are the most important factors. Research results can be used as a guideline in future practice, and it is necessary to evaluate, compare and analyze the satisfaction of companies that have adopted cloud computing services in the future.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.319-325
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• 2021

The urban regeneration project is an activity that promotes the economy in underdeveloped commercial or residential areas and maintains urban communities through improvement of living in residential areas. Through this study, various successful cases of urban regeneration at home and abroad and surveys related to urban regeneration in Bongsan Village, Yeongdo, Busan were collected and analyzed. Key keywords for each case were derived, grouped, and top keywords were created. The 13 top keywords were evaluated using Likert's 5-point scale, and AHP was conducted for the 10 keywords that were finally selected. As a result of AHP analysis, the preference for "spatial and physical properties" was derived in the order of "publicity", "sustainability", and "identity". The preference of "content and system properties" was derived in the order of "resident participation", "convenience", "locality", and "local government participation". It is necessary to present a role as a design guideline for establishing urban regeneration designs in relation to various urban regeneration projects that will become more active in the future through the analysis of preferences of urban regeneration keywords derived through this study.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.3
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• pp.234-243
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• 2012

In this paper, a sound quality indices for the evaluation of vehicle intake and exhaust noise were developed through a correlation analysis of objective measurement data and subjective evaluation data. At first, intake and exhaust orifice noise were measured at the wide-open throttle sweep condition. And then, acoustic transfer function between intake orifice noise and interior noise at the steady state condition was measured. Also, acoustic transfer function for exhaust system was measured as the same method. Simultaneously, subjective evaluation was carried out by the paired comparison and semantic differential method by 27 engineers. Next, the correlation analysis between the psycho-acoustic parameters derived from the measured data and the subjective evaluation was performed. The most critical factor was determined and the corresponding sound quality index for the intake and exhaust noise was obtained from the multiple factor regression method. At last, the effectiveness of the proposed index was investigated.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.8 s.101
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• pp.945-953
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• 2005

The purpose of this paper is to develop a linear regression model for the sound quality index of vehicle Interior noise. For this, objective measurement data of the vehicles driving in acceleration was measured. On the basis of analysis, psychoacoustic parameters were extracted and subjective evaluation was performed by noise and vibration expert evaluators. For the subjective evaluation, the paired comparisons and the semantic differential methods were used to evaluate sound quality of vehicle interior noise. By the paired comparison which evaluate two pairs of vehicle interior noise, the preference was estimated. With the semantic differential and the factor analysis, it was evaluated words of two pairs which expressed appropriately the sense of evaluator about noise source. Therefore the characteristics of the sound qualify for the vehicle were differentiated. From the results of both the correlation analysis and the multiple factor regression analysis, the sound quality evaluation model for the sense of human hearing was derived and indexed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1297-1301
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• 2007

The Conventional noise control attempts to simply reduce the level of product noise. But it is very straight forward way that we have consider human perception on noise. Since human listening is very sensitive to sound. Evaluation of the sound quality of a Vacuum Cleaner is studied base on human sensibility engineering. In this paper, we choose two Vacuum Cleaners that are sold in Korea and reduced noise control. Comparison Method is used to evaluate noise and preference of Vacuum Cleaner by steps. The sound quality of Vacuum Cleaner noise is analyzed by employing the subjective evaluation and by representing them in terms of the objective quantities. Semantic Differential Method is used to study sound quality Evaluation. To analyze the sound quality of Vacuum Cleaner noise, consider the coefficients of correlation between sound metrics and subjective rating. The linear regression models were obtained for the subjective evaluation and sound quality metrics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.64-68
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• 2005

Reed-Solomon code is one of the most versatile channel codes. The encoder can be implemented with two famous structures: ordinary and bit-serial. The ordinary encoder is generally known to be complex and fast, while the bit-serial encoder is simple and not so fast. However, it may not be true for a longer codeword length at least in VHDL implementation. In this letter, it is shown that, when the encoder is implemented with VHDL, the number of logic gates of the bit-serial encoder might be larger than that of the ordinary encoder if the dual basis conversion table has to be used. It is also shown that the encoding speeds of the two VHDL implemented encoders are exactly same.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.361-366
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• 2013

Prediction of process parameters is very important in parameter design. If predictions are fairly accurate, the quality improvement process will be useful to save time and reduce cost. The concept of dual response approach based on response surface methodology has widely been investigated. Dual response approach may take advantages of optimization modeling for finding optimum setting of input factor by separately modeling mean and variance responses. This study proposes an alternative dual response approach based on machine learning techniques instead of statistical analysis tools. A hybrid neural network-genetic algorithm has been proposed for the purpose of parameter design. A neural network is first constructed to model the relationship between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Using empirical process data, process parameters can be predicted without performing real experimentations. A genetic algorithm is then applied to find the optimum settings of input factors, where the neural network is used to evaluate the mean and variance response. A drug formulation example from pharmaceutical industry has been studied to demonstrate the procedures and applicability of the proposed approach.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10d
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• pp.112-117
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• 2007

사이버 침해란 정보시스템의 취약한 부분을 공격하여 시스템 내부에 침입하거나 시스템을 마비/파괴하는 등의 사고를 유발하는 모든 행위를 말한다. 이러한 사이버 침해의 피해를 줄이기 위해 국내외 많은 연구 기관과 업체에서는 침입탐지시스템과 같은 정보보호 기술을 연구 개발하여 상용화하고 있다. 그러나 기존의 정보보호 기술은 이미 발생한 침해를 탐지하여 피해의 확산을 막는 데만 한정적으로 사용되고, 침해의 발생 가능성을 예측하지는 못하기 때문에 점차 첨단화, 다양화되고 있는 사이버 침해에 대응하기 힘들다는 문제점을 갖는다. 본 논문에서는 보안 취약점을 이용한 사이버 침해를 대상으로 전문가 설문을 통해 사이버 침해의 발생 가능성을 예측하는 방법을 제안하고, 이를 위한 사이버 침해 예측 항목을 추출하였다. 예측 항목 추출은 3 단계로 구성되며, 첫 번째 단계에서는 기존 연구와 사례 분석을 통해 예측 항목의 계층 구조를 생성한다. 두 번째 단계에서는 첫 번째 단계를 통해 생성된 예측 항목들을 델파이 방법을 통해 개선하여 최적의 예측 항목을 결정한다. 마지막 단계에서는 각 항목들에 대한 쌍대 비교 설문을 진행하여 항목 간 가중치를 추출한다.