• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.243-248
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• 2011

According to increasing of accessing multimedia stream contents, Web services have become popular. However, these Web services are not supported with the same quality to Web clients who frequently access multimedia services. This paper proposes ontological technique to apply client level Quality of Service(QoS) that provides two different levels to serve Web service with proper quality by contribution value. And, it describes with UML(Unified Modeling Language) how to relate QoS and SLA(Service Level Agreement). Main contribution of this paper is to support client level QoS and SLA and to use Ontology for it. Therefore, this work uses an ontology-based approach to organize QoS and SLA, enabling semantic classification of all Web services based on domains and QoS and SLA attributes.

• Journal of Engineering Education Research
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• v.9 no.4
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• pp.71-82
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• 2006

To accomplish the educational objectives of a department, a system for CQI(Continuous Quality Improvement) is necessary. Improving the educational system by survey analysis is one of the most important factors for accomplishing the educational objectives. In general, survey analysis is carried out by using statistical distribution on an attribute or correlation analysis between two attributes. However, these analysis schemes have a limitation that they cannot find relations among various attributes. In this paper, an in-depth survey analysis method applying data mining techniques is presented. Data mining is a technique for extracting interesting knowledges from a large set of data. Survey from undergraduate students in the School of Computing of Soongsil University is analyzed in this paper by using a data mining tool, called Clementine. Results of Clementine analysis show the relationship between 'grade', and other attributes hierarchically, and provide useful information that can be applied in student consulting and program improvement.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.5 s.164
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• pp.765-776
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• 2007

Customer expectations and requirements for products play an important role in product planning for companies and decision making process for the consumer. These expectations are expressed by product qualities that consumers consider important when they purchase. Therefore, to identify quality elements that reflect consumer requirements would be a useful guide for companies. The purposes of this study are to find out quality factors of apparel product, to identify apparel product quality elements using Kano's theory, to find attributes of product which improvement are required. Women over 20 years-old from metropolitan areas in South Korea participated in the study and a quota sampling method was used. A questionnaire was arranged with four separate subject sections, importance of quality, Kano's questionnaires, and demographics. Data from 525 questionnaires were used for the statistical analysis. The results were as follows: Six dimensions of product quality(i.e., usefulness, performance, aesthetic, symbol, individuality and appearance) were identified. According to Kano's quality elements, performance was categorized into must-be quality which could lead to product dissatisfaction. Usefulness and appearance were categorized into one-dimensional quality which lead to both satisfaction and dissatisfaction. Aesthetic, symbol, and individuality was categorized into attractive quality which could lead to satisfaction. Findings of this study provide both industry and academic researchers with a guide to increase customer satisfaction in the product development process.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.270-278
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• 2022

This study was conducted using deep learning technology to classify for 'Mihwang' peach maturity with RGB images and fruit quality attributes during fruit development and maturation periods. The 730 images of peach were used in the training data set and validation data set at a ratio of 8:2. The remains of 170 images were used to test the deep learning models. In this study, among the fruit quality attributes, firmness, Hue value, and a^* value were adapted to the index with maturity classification, such as immature, mature, and over mature fruit. This study used the CNN (Convolutional Neural Networks) models for image classification; VGG16 and InceptionV3 of GoogLeNet. The performance results show 87.1% and 83.6% with Hue left value in VGG16 and InceptionV3, respectively. In contrast, the performance results show 72.2% and 76.9% with firmness in VGG16 and InceptionV3, respectively. The loss rate shows 54.3% and 62.1% with firmness in VGG16 and InceptionV3, respectively. It considers increasing for adapting a field utilization with firmness index in peach.

• Food Science and Preservation
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• v.16 no.2
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• pp.204-210
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• 2009

This study investigated consumer grape recognition and preference, to improve grape quality. The questionnaire explored consumption frequency, purchasing locations, amounts purchased, general preferences, seedless/seeded preference, and external/internal quality factors. Answers to 519 questionnaires were analyzed both descriptively and quantitatively using SPSS for Windows(Version 14.0). The principal results were as follows: 46.1% of respondents purchased at wholemarket; 38.5% purchased 3-5 bunches at any one time; 76% preferred grapes to other fruits; and 49.8% purchased bigger(and not smaller) grapes. Most customers preferred seedless grapes. The most important external quality factor was bunch fullness and the most significant internal factor was sweetness.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1246-1246
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• 2001

The quality of meat is highly variable in many properties. This variability originates from both animal production and meat processing. At the pre-slaughter stage, animal factors such as breed, sex, age contribute to this variability. Environmental factors include feeding, rearing, transport and conditions just before slaughter (Hildrum et al., 1995). Meat can be presented in a variety of forms, each offering different opportunities for adulteration and contamination. This has imposed great pressure on the food manufacturing industry to guarantee the safety of meat. Tissue and muscle speciation of flesh foods, as well as speciation of animal derived by-products fed to all classes of domestic animals, are now perhaps the most important uncertainty which the food industry must resolve to allay consumer concern. Recently, there is a demand for rapid and low cost methods of direct quality measurements in both food and food ingredients (including high performance liquid chromatography (HPLC), thin layer chromatography (TLC), enzymatic and inmunological tests (e.g. ELISA test) and physical tests) to establish their authenticity and hence guarantee the quality of products manufactured for consumers (Holland et al., 1998). The use of Near Infrared Reflectance Spectroscopy (NIRS) for the rapid, precise and non-destructive analysis of a wide range of organic materials has been comprehensively documented (Osborne et at., 1993). Most of the established methods have involved the development of NIRS calibrations for the quantitative prediction of composition in meat (Ben-Gera and Norris, 1968; Lanza, 1983; Clark and Short, 1994). This was a rational strategy to pursue during the initial stages of its application, given the type of equipment available, the state of development of the emerging discipline of chemometrics and the overwhelming commercial interest in solving such problems (Downey, 1994). One of the advantages of NIRS technology is not only to assess chemical structures through the analysis of the molecular bonds in the near infrared spectrum, but also to build an optical model characteristic of the sample which behaves like the “finger print” of the sample. This opens the possibility of using spectra to determine complex attributes of organic structures, which are related to molecular chromophores, organoleptic scores and sensory characteristics (Hildrum et al., 1994, 1995; Park et al., 1998). In addition, the application of statistical packages like principal component or discriminant analysis provides the possibility to understand the optical properties of the sample and make a classification without the chemical information. The objectives of this present work were: (1) to examine two methods of sample presentation to the instrument (intact and minced) and (2) to explore the use of principal component analysis (PCA) and Soft Independent Modelling of class Analogy (SIMCA) to classify muscles by quality attributes. Seventy-eight (n: 78) beef muscles (m. longissimus dorsi) from Hereford breed of cattle were used. The samples were scanned in a NIRS monochromator instrument (NIR Systems 6500, Silver Spring, MD, USA) in reflectance mode (log 1/R). Both intact and minced presentation to the instrument were explored. Qualitative analysis of optical information through PCA and SIMCA analysis showed differences in muscles resulting from two different feeding systems.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.103-119
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• 2023

Since the Korean government has decided to apply the policy of BIM (Building Information Modeling) to the entire construction industry, it has experienced a positive trend in adoption and utilization. BIM can reduce workloads by building model objects into libraries that conform to standards and enable consistent quality, data integrity, and compatibility. In the domestic architecture, civil engineering, and the overseas landscape architecture sectors, many BIM library standardization studies have been conducted, and guidelines have been established based on them. Currently, basic research and attempts to introduce BIM are being made in Korean landscape architecture field, but the diffusion has been delayed due to difficulties in application. This can be addressed by enhancing the efficiency of BIM work using standardized libraries. Therefore, this study aims to provide a starting point for discussions and present a classification system for objects and attribute information that can be referred to when creating landscape libraries in practice. The standardization of landscape BIM library was explored from two directions: object classification and attribute information items. First, the Korean construction information classification system, product inventory classification system, landscape design and construction standards, and BIM object classification of the NLA (Norwegian Association of Landscape Architects) were referred to classify landscape objects. As a result, the objects were divided into 12 subcategories, including 'trees', 'shrubs', 'ground cover and others', 'outdoor installation', 'outdoor lighting facility', 'stairs and ramp', 'outdoor wall', 'outdoor structure', 'pavement', 'curb', 'irrigation', and 'drainage' under five major categories: 'landscape plant', 'landscape facility', 'landscape structure', 'landscape pavement', and 'irrigation and drainage'. Next, the attribute information for the objects was extracted and structured. To do this, the common attribute information items of the KBIMS (Korean BIM Standard) were included, and the object attribute information items that vary according to the type of objects were included by referring to the PDT (Product Data Template) of the LI (UK Landscape Institute). As a result, the common attributes included information on 'identification', 'distribution', 'classification', and 'manufacture and supply' information, while the object attributes included information on 'naming', 'specifications', 'installation or construction', 'performance', 'sustainability', and 'operations and maintenance'. The significance of this study lies in establishing the foundation for the introduction of landscape BIM through the standardization of library objects, which will enhance the efficiency of modeling tasks and improve the data consistency of BIM models across various disciplines in the construction industry.

• Korean small business review
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• v.43 no.4
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• pp.95-115
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• 2021

Quality is an important factor influencing organizational performance, so it should be possible to accurately and effectively measure the quality perceived by members. The Consumer Cooperative can be seen as a retail industry by industry classification, and there are various studies based on the dimension of retail quality, but compared to the general retail industry, few studies have been conducted based on the quality level perceived by members. The purpose of this study is to develop quality dimensions and sub-attributes by analyzing in detail and elaborately how the quality of cooperative is viewed from the perspective of members who are both consumers and owners. To this end, the quality dimension of cooperative quality is needed to be newly developed and quality components are demonstrated based on previous studies on the quality dimension. The quality dimension of the cooperative was developed through prior research to suit the value of the cooperative in product, service, and social responsibility, and a survey was conducted to demonstrate the four major cooperative members in Korea. Through this, sub-dimensions were constructed and the quality dimension of the high-order model was demonstrated through exploratory factor analysis and confirmatory factor analysis. It aims to discover key management elements in terms of quality management and provide practical implications to management.

• Journal of KIISE
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• v.42 no.11
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• pp.1349-1360
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• 2015

In order to improve software quality, it is necessary to efficiently and effectively remove software defects in source codes. In the development field, defects are removed according to removal ratio or severity of defects. There are several studies on the removal of defects based on software quality attributes, and several other studies have been done to improve the software quality using classification of the severity of defects, when working on projects. These studies have thus far been insufficient in terms of identifying if there exists relationships between defects or whether any type of defect is more important than others. Therefore, in this study, we collected various types of software defects, standards organization, companies, and researchers. We modeled the defects types using an ANP model, and developed the weighted severities of the defects types, with respect to the general application software, using the ANP model. When general application software is developed, we will be able to use the weight for each severity of defect type, and we expect to be able to remove defects efficiently and effectively.

• Journal of Korean Society of Rural Planning
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• v.30 no.2
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• pp.79-96
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• 2024

The purpose of this study is to analyze the factors affecting residential mobility between urban and rural. After classifying urban and rural region based on discriminatory attributes of the regions, we applied a multinomial logistic model, using the sample data of 2020 Korea Population and Housing Census. The major findings are as follows. The young highly educated in cities avoided rural. The young less educated in rural engaged in 2, 3th industries as well as agricultural industry, but remained in low-paying and unstable jobs. In addition, various classes moved to rural and rising house prices in cities pushed people to rural. Therefore, it is necessary to develop diversified regional industry models and provide opportunities for high quality and stable jobs in rural by linking industrial demand, education and jobs. Also, preserving the rural environment, settlement conditions and residential environment are needed for satisfying various needs of urban residents who migrate to rural areas. While regional policies so far have focused on maintaining the population size and promoting a population influx, rural development and population policies should be established in a way that responds to diverse population classes in an era of population decline.