• Architectural research
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• 제23권4호
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• pp.67-73
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• 2021

An efficient demolition process requires the optimum method selection considering stability, economic feasibility, environment, and workability. In reality the construction cost and period are priority concerns, and safe construction methods are neglected. In addition, the choosing demolition method is often determined subjectively by experienced field engineers. This research paper presents a multi-criteria decision-making method using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to select the optimum demolition method. Three experienced demolition engineers' opinions were used to develop the TOPSIS model. The case study showed that the preferences of ten attribute measurements for demolition method selection. Authors suggested the most preferable demolition method for the case study project.

• 디지털융복합연구
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• 제13권9호
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• pp.201-208
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• 2015

SNS와 페이스북과 같은 서비스가 대중화되면서 마이크로블로그와 같은 작은 크기의 빅 데이터 사용이 증대되고 있다. 그러나, 현재까지 작은 크기의 빅 데이터의 탐색 결과의 정확성과 계산비용은 미해결 상태로 남아있다. 본 논문에서는 빅 데이터 환경에서 마이크로블러그와 같은 작은 크기의 텍스트 정보의 탐색 속도를 향상시키기 위한 확률기반의 서브넷 선택 기법을 제안한다. 제안 기법은 데이터의 속성 정보에 확률값을 부여하여 서브넷을 구성하여 데이터 탐색 속도를 높였다. 또한, 제안 기법은 분산된 데이터를 손쉽게 접근하기 위해서 서브넷을 구성하는 데이터 의확률값 간 연계 정보를 쌍으로 처리함으로써 데이터의 접근성을 향상시켰다. 실험결과, 제안 기법은 CELF 알고리즘보다 평균 6.8% 높은 탐지율을 보였으며, 처리시간은 평균 8.2% 단축시켰다.

• Journal of Computing Science and Engineering
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• 제1권2호
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• pp.177-194
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• 2007

Index selection is one of the most important decisions to take in the physical design of relational data warehouses. Indices reduce significantly the cost of processing complex OLAP queries, but require storage cost and induce maintenance overhead. Two main types of indices are available: mono-attribute indices (e.g., B-tree, bitmap, hash, etc.) and multi-attribute indices (join indices, bitmap join indices). To optimize star join queries characterized by joins between a large fact table and multiple dimension tables and selections on dimension tables, bitmap join indices are well adapted. They require less storage cost due to their binary representation. However, selecting these indices is a difficult task due to the exponential number of candidate attributes to be indexed. Most of approaches for index selection follow two main steps: (1) pruning the search space (i.e., reducing the number of candidate attributes) and (2) selecting indices using the pruned search space. In this paper, we first propose a data mining driven approach to prune the search space of bitmap join index selection problem. As opposed to an existing our technique that only uses frequency of attributes in queries as a pruning metric, our technique uses not only frequencies, but also other parameters such as the size of dimension tables involved in the indexing process, size of each dimension tuple, and page size on disk. We then define a greedy algorithm to select bitmap join indices that minimize processing cost and verify storage constraint. Finally, in order to evaluate the efficiency of our approach, we compare it with some existing techniques.

• 한국식품영양학회지
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• 제35권6호
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• pp.481-490
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• 2022

The influence of the food value consumption type of MZ generation on food choice attribute and sustainable food consumption behavior was studied using structural equation modeling. A survey was conducted on April 11~17, 2022, among panels aged 20 to 39. A total of 350 valid replicates (100%) were analyzed using statistical program SPSS The validity of the measurement instrument was verified through exploratory factor analysis and confirmatory factor analysis. The data reliability was confirmed using Cronbach's alpha coefficient. The hypothesis was verified by performing path analysis through structural equation modeling using AMOS. Regarding the influence of food choice characteristics on sustainable food consumption behavior, health has a significant positive (+) effect on the selection consumption behavior of certified food and local food. Among food value consumption categories social value consumption has a significant negative (-) influence on the consumption behavior of certified food and the choice of local food. Ethical value consumption has a significant positive (+) influence on the selection consumption behavior of certified food and local food. This study is significant because it has identified sustainable food consumption behaviors that domestic consumers can adopt daily. It can use as baseline data for preparing political and institutional measures.

• 한국조리학회지
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• 제24권3호
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• pp.25-34
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• 2018

The purposes of this study were to examine the effect of Home Meal Replacement (HMR) selection attributes on attitude and repurchase intention and to investigate the moderating role of brand trust between attitude and repurchase intention. This study surveyed the customers who have purchased HMR in Seoul and Gyeonggi area using a convenience sampling method. The survey was conducted from September 15, 2017 to October 25, 2017. A total of 250 questionnaires were distributed, and 237 copies were collected. Of these, 228 copies were used as valid data. The results of the analysis were as follows. First, convenience of the HMR selection attribute had a significant effect on attitude, and food quality and packaging had no significant effect on attitude. Second, attitude toward HMR had a significant effect on repurchase intention. Third, brand trust played a moderating role between HMR attitude and repurchase intention. Therefore, it is necessary for HTMcompanies to understand consumers' attitudes and consumption behaviors accurately by recognizing the selection attributes that consumers consider important By gaining strong brand trust, companies could increase repurchase intention.

• 한국식품조리과학회지
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• 제27권2호
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• pp.83-94
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• 2011

The purpose of this study was to analyze the structural relationships among selection attributes, satisfaction, and loyalty of green tea consumers, including their moderating effect of involvement. Questionnaires were administered to residents of Seoul and Gyeonggi-do province, who were 20 years old and older and who had purchased green tea. A total of 700 questionnaires were distributed, and 658 were finally used in the analysis. SPSS 15.0 and LISREL 8.80 were used for the analysis. Selection attributes had a significant effect on satisfaction, and statistical significance was observed with regard to factors such as marketing, production, sensory evaluation, and brand. No significant direct effect was observed between selection attributes and loyalty. Additionally, satisfaction had a significant effect on loyalty. The marketing factor had a negative effect on satisfaction in both the low- and high-involvement groups. The brand factor had a positive effect on satisfaction in the low involvement group, suggesting that developing and promoting a popular brand is essential. Sensory and utility factors had a positive effect on satisfaction in the high involvement group.

• 융합경영연구
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• 제11권1호
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• pp.13-19
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• 2023

Purpose: This study aims to determine which optional attributes are more important for the MZ generation when purchasing luxury fashion goods. Although sales are slowing down in all industries due to COVID-9, sales of luxury fashion goods are instead increasing, centered on the MZ generation. Companies are expanding online sales channels and transforming to gain more attention. Research design, data and methodology: Selection attributes are considered to be more crucial, when customers select luxury fashion products such as prestige image, brand awareness, reasonable price, and product quality, were researched and also find the correlation between satisfaction and purchase intention were analyzed. A survey was conducted focusing on the MZ generation, and the contents of the survey were analyzed using the SPSS 22.0 program and the Amos 26.0 program. Results: As a result of the study, selection attributes as prestige image, brand awareness, and product quality were proved to influence significantly on satisfaction. Moreover, the path of satisfaction to purchase intention proved significant. But reasonable price did not influence on MZ generations satisfaction. Conclusions: The research results present the selection attributes of luxury fashion products and provide significant implications when the MZ generation selects the attributes of luxury fashion products.

• 한국국방경영분석학회지
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• 제30권1호
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• pp.1-14
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• 2004

In this paper, we propose a new data-mining-based methodology for military occupational specialty assignment. The proposed methodology consists of two phases, feature selection and man-power assignment. In the first phase, the k-means partitioning algorithm and the optimal variable weighting algorithm are used to determine attribute weights. We address limitations of the optimal variable weighting algorithm and suggest a quadratic programming model that can handle categorical variables and non-contributory trivial variables. In the second phase, we present an integer programming model to deal with a man-power assignment problem. In the model, constraints on demand-supply requirements and training capacity are considered. Moreover, the attribute weights obtained in the first phase for each specialty are used to measure dissimilarity. Results of a computational experiment using real-world data are provided along with some analysis.

• 한국생활과학회지
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• 제9권1호
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• pp.63-70
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• 2000

The purpose of this study is The results was that consumers who like to the top brand's commodities, had commonly high tendency to and fro its trademark and store allegiance. Furthermore, they have usually bought something following on their inclination what they had purchased as well as the store decoration character and the marketing promotion attribute. The other consumers who prefer to the discount store's merchandises, had also high propensity and the biggest influence on buying something which were those factors; their instance shopping habit, utility-economy trait, follow the fashion character and strong circumspection tendency besides using the mass media Info., personal data and commodities' attribute.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권1호
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• pp.1-12
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• 2016

In this paper, we propose an approach that efficiently builds regional hazardous weather prediction models based on past weather data. Doing so requires finding the proper weather attributes that strongly affect hazardous weather for each region, and that requires a large number of experiments to build and test models with different attribute combinations for each kind of hazardous weather in each region. Using our proposed method, we reduce the number of experiments needed to find the correct weather attributes. Compared to the traditional method, our method decreases the number of experiments by about 45%, and the average prediction accuracy for all hazardous weather conditions and regions is 79.61%, which can help forecasters predict hazardous weather. The Korea Meteorological Administration currently uses the prediction models given in this paper.