• Korean journal of food and cookery science
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• v.29 no.5
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• pp.489-500
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• 2013

This study was conducted to establish an effective palate cleanser when conducting descriptive analysis for gochujang products. In addition, descriptive analysis procedure for gochujang products was optimized. A generic descriptive analysis was performed on 4 types of gochujang samples varying in hot and spicy levels. The sensory attributes developed were 9 odors, 13 flavors, 4 texture and mouth feel attributes, and 4 appearance attributes. In order to select an effective palate cleanser for gochujang, 5 types of cleansers were tested (water, water+bread, water+cucumber, water+milk, water+cracker). Correct answering rate, significant numbers of product effect on sensory attributes, and the mean hot and spicy intensity values were considered to select the optimal palate cleanser. Results showed that as the hot & spicy level increased, red pepper odor and flavor significantly increased whereas umami taste intensity decreased. When comparing the efficiencies of various palate cleanser, the correct answer rates were the highest when warm water was used with either cucumber or cracker. Additionally, the attribute intensities were better differentiated between gochujang samples when cracker, white wheat bread, or cucumber were used. Overall, warm water with cucumber or cracker were shown to be the most effective cleansers.

• Journal of Broadcast Engineering
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• v.10 no.1 s.26
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• pp.103-118
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• 2005

Since the introduction of digital broadcasting, an additional advanced service called EPG has been brought to viewers. EPG (Electronic Program Guide) helps people select channels or programs. But existing user Interfaces for EPG are not convenient enough for the viewer. TV is the media anyone can access. Therefore, the 'look and feel' user interface is needed to guide the viewer to select their favorite programs without any difficulties. Generally, TV programs can be categorized by their attributes such as genre, broadcasting hours, and TV ratings. At the present moment, those attributes are not categorized systematically enough for easy program navigation. This paper presents how to organize the attributes of TV programs systematically and offers a user friendly interface to help the viewer access their favorite programs by specifying the values of the attributes in any order comfortable to them.

• The KIPS Transactions:PartD
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• v.19D no.1
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• pp.1-14
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• 2012

As the size of the data warehouse is large, the selection of indices on the data warehouse affects the efficiency of the query processing of the data warehouse. Indices induce the lower query processing cost, but they occupy the large storage areas and induce the index maintenance cost which are accompanied by database updates. The bitmap join indices are well applied when we optimize the star join queries which join a fact table and many dimension tables and the selection on dimension tables in data warehouses. Though the bitmap join indices with the binary representations induce the lower storage cost, the task to select the indexing attributes among the huge candidate attributes which are generated is difficult. The processes of index selection are to reduce the number of candidate attributes to be indexed and then select the indexing attributes. In this paper on bitmap join index selection problem we reduce the number of candidate attributes by the data mining techniques. Compared to the existing techniques which reduce the number of candidate attributes by the frequencies of attributes we consider the frequencies of attributes and the size of dimension tables and the size of the tuples of the dimension tables and the page size of disk. We use the mining of the frequent itemsets as mining techniques and reduce the great number of candidate attributes. We make the bitmap join indices which have the least costs and the least storage area adapted to storage constraints by using the cost functions applied to the bitmap join indices of the candidate attributes. We compare the existing techniques and ours and analyze them in order to evaluate the efficiencies of ours.

• Journal of the military operations research society of Korea
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• v.22 no.1
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• pp.81-96
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• 1996

In a relational database environment, partitioning of data is directly concerned with the amount of data that needs to be required in a query or transaction. In this paper, we consider non-overlapping, vertical partitioning. Vertical partitioning algorithm in this paper is composed of two phases. In phase 1, we cluster the attributes with zero-one integer program that maximize affinity among attributes. The result of phase 1 is called 'Initial Fragments'. In phase 2, we modify Initial Fragments that is not directly considered by cost factors, making use of a transaction-based partitioning method. A transaction-based partitioning method is partitioning attributes according to a set of transactions. In this phase we select logical accesses which needs to be required in a transaction as comparison criteria. In phase 2, proposed algorithm consider only small number of modification of Initial Fragments in phase 1. This algorithm is so insensible to number of transactions and of attributes that it can applied to relatively large problems easily.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.31
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• pp.99-114
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• 1994

The introduction of new equipments to strengthen the competitiveness of enterprises is one of pretty important factors. Enterprises introducing new equipments strengthen competitiveness through productivity increasing, high quality maintenance, inventory reduction, improved design and production interface, simple scheduling process, low scrap rate, rework reduction, etc. Managers will work out the best equipment-replacing strategy through the appropriate combination of potential cost attributes and qualitative attributes difficult to quantify in accordance with the business purpose. This study is to present a method to select an equipment-replacing alternative through the decision-making model of Analytic Hierarchy Process in consideration of the differences of cost flow of the alternatives, taking into consideration tangible attributes and strategic intangible attributes.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.375-382
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• 2021

The paper introduces a model for evaluating and prioritizing mobile quality attributes and refactoring techniques through the examination of their effectiveness during the mobile application development process. The astonishing evolution of software and hardware has increased the demand for techniques and best practices to overcome the many challenges related to mobile devices, such as those concerning device storage, network bandwidth, and energy consumption. A number of studies have investigated the influence of refactoring, leading to the enhancement of mobile applications and the overcoming of code issues as well as hardware issues. Furthermore, rapid and continuous mobile developments make it necessary for teams to apply effective techniques to produce reliable mobile applications and reduce time to market. Thus, we investigated the influence of various refactoring techniques on mobile applications to understand their effectiveness in terms of quality attributes. First, we extracted the most important mobile refactoring techniques and a set of quality attributes from the literature. Then, mobile application developers from nine mobile application teams were recruited to evaluate and prioritize these quality attributes and refactoring techniques for their projects. A prioritization-based model is examined that integrates the lightweight multi-criteria decision making method, called the best-worst method, with the process of refactoring within mobile applications. The results prove the applicability and suitability of adopting the model for the mobile development process in order to expedite application production while using well-defined procedures to select the best refactoring techniques. Finally, a variety of quality attributes are shown to be influenced by the adoption of various refactoring techniques.

• The Journal of Economics, Marketing and Management
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• v.11 no.1
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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.

• Journal of Service Research and Studies
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• v.6 no.2
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• pp.83-97
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• 2016

Smart car is a vehicle which maximizes convenience, safety, and user experience. The traditional vehicle style will be replaced by a smart car. The objective of this paper is to find essential quality attributes that consumers want. We provide a method to select a best smart car reflecting their preference based on the quality attributes. We derive Kano's quality attributes by an exploratory survey and show an example to implement their decision using the Analytic Hierarchy Process method. As a result, the quality attributes were classified into two groups of attractive quality and indifference quality. The respondents evaluated that the safety of smart cars was more important than the convenience and user experience. However, the smart car was required more functions related to the convenience criteria. These results will provide important implications for smart car design.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.8
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• pp.1128-1140
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• 2002

As consumers' alternatives in fashion store selection increase, they select different store types to purchase different product types. Therefore, the probability of patronage mix behavior according to product type increases. Understanding consumers patronage mix behavior, finding out the determinant attributes of fashion stores for each product type are important to retailers and marketers for building a successful merchandising and marketing strategies. Most of the previous researches in store selection and patronage assume consumer behavior as single store patronage, and thus relatively little is known about patronage mix behavior. Also, little attention has been given to product characteristics as an important variable in store patronage behavior. The purposes of this study were to determine the effects of product characteristics in consumers patronage mix behavior. In this study, a theoretical model including product characteristics as an intervening variable between store attributes and patronage behavior was developed. A Questionnaire was developed and data were collected form 464 adult women living in Seoul area in Korea. Factor analysis, paired t-test, ANOVA, Duncan test and discriminant analysis were employed to analyze the data. As a result, the suggested model was partially verified. First, the product characteristic was found to have an effect on perceived importance of store attributes and on determinant attributes of stores. Consumers were found to use different evaluative criteria for store attributes when they purchase different product types. Second, the perceived importance of store attributes was determined by consumer characteristics as well as product characteristics. Third, the determinant attributes in store selection were affected not only by the perceived importance of store attributes but also by the type of product to be purchased.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.796-801
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• 2009

In medical practice, the diagnosis or prediction models requiring complicated computations are not widely recognized due to difficulty in interpreting the course of reasoning and the complexity of computations. Medical personnel have used the nomograms which are a graphical representation for numerical relationships that enables to easily compute a complicated function without help of computation machines. It has been widely paid attention in diagnosing diseases or predicting the progress of diseases. A nomogram is constructed from a set of clinical data which contain various attributes such as symptoms, lab experiment results, therapy history, progress of diseases or identification of diseases. It is of importance to select effective ones from available attributes, sometimes along with parameters accompanying the attributes. This paper introduces a nomogram construction method that uses a naive Bayesian technique to construct a nomogram as well as a genetic algorithm to select effective attributes and parameters. The proposed method has been applied to the construction of a nomogram for a real clinical data set.