• 한국전자거래학회:학술대회논문집
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• 한국전자거래학회 2000년도 종합학술대회발표논문집
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• pp.207-214
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• 2000

Over the last several decades, the topic of the source selection and evaluation has gained a great attention in the information systems community as an effective tool to acquire information systems in an organization. The source selection and evaluation process is a multiple-criteria decision-making problem associated with several evaluation issues. In this case study, evaluation issues include management, technologies, logistics, and cost. This case study was conducted to compare a new source selection and evaluation process by using the analytic hierarchy process with the traditional approach. This study provides useful insight about how to apply the analytic hierarchy process technique to the traditional approach.

• 한국과학교육학회지
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• 제12권3호
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• pp.91-107
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• 1992

The Purpose of this study was to present the procedures and methods of ordering theory,and to search for a learning hierarchy among science process skills in each Piagetian cognitive reasoning level. One of the purpose of this is not to determine the clear and exact hierarchy but rather to demonstrate how ordering theoretic methods and procedures can be used to determine the hierarchy of logical relationships among a set of test items or the testing of a hypothesized hierarchy. Ordering theory was used to analyze five science process skills collected from 509 high school students. Ordering Theory has as its primary intent either the testing of hypothesized hierarchies among items at the determination of hierchies among items. Hierarchical relationships were identified within five science process skills. The results will be helpful in giving useful inform at ions to classroom teachers and science curriculum developer.

• 대한안전경영과학회지
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• 제11권2호
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• pp.153-158
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• 2009

An optimal selection problem of SCM system is one of the critical issues for the company's competitiveness and performance under global economy. This paper presents a hierarchy model consisted of characteristic factors for introducing SCM system and an AHP (Analytic Hierarchy Process) based decision-making model for SCM system evaluation and selection. The proposed model can systematically construct the objectives of SCM system selection to meet the business goals. This paper focuses on selecting an optimal SCM system considering both all decision factors and sub-decision factors of a hierarchy model. Especially, the benefit/cost analysis is applied to choose SCM system. A case study shows the feasibility of the proposed model and the model can help a company to make better decision-making in the SCM system selection problem.

• 패션비즈니스
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• 제13권6호
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• pp.137-146
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• 2009

This study analyzed hierarchy of image for visual evaluation of flare skirt. This study analyzed expression words about flare skirt with frequency data of image expression words with different length and volume of flare. Stimuli for the study were set to be 4 different volume of flare ($90^{\circ}$, $180^{\circ}$, $270^{\circ}$, $360^{\circ}$) and 3 different length of skirt(48cm, 58cm, 68cm). Stimuli were made by using I-Designer which is Virtual Sewing System. From simulation of flare skirt, the subjects were asked to write down suggested adjective freely and selected 210 adjectives. With this, we chose total 38 adjectives considering frequencies in the pre-study. And we analyzed the combination process of expression words according to construction factor of flare skirt and hierarchy of image from dendrogram which was resulted by hierarchical cluster analysis. 'Feminine' got high score in all 12 flare skirt. When the skirt was short, it was vivid, and as the skirt got longer, ordinary and pure image showed. Also, as the volume of flare got larger, the average of visual effect was higher than visual image. Visual hierarchy construction according to construction factors of flare skirt could be divided into visual image and visual effect, and visual image was shown to be form 'A type - large volume of flare and short skirt length', 'H type-small volume of flare and short skirt length' and 'X type - large volume of flare and long skirt length'.

• 전기전자학회논문지
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• 제19권4호
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• pp.590-595
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• 2015

본 논문은 타일 기반 레스터라이져에서 연산이 필요하지 않은 하위 계층에 대한 호출을 막아 연산의 효율을 올릴수 있는 계층 구조의 설계를 제안한다. 제안하는 계층 구조는 내외부 판정과 각 하위 계층이 가지는 타일의 최대 좌표값, 최소 좌표값을 이용하여 하위 계층을 3가지 형태로 분류한다. 각 하위 계층이 분류되는 형태에 따라 해당 계층의 연산의 필요 여부를 구분할 수 있으며 연산이 필요하지 않는 하위 계층에 대한 호출을 수행하지 않는 것으로 그래픽 처리과정의 전체 연산량을 줄일 수 있다. 제안하는 구조를 이용하여 하위 계층의 분류를 통해 그래픽 처리의 연산 시간을 줄일 수 있으며 3D 모델을 구성하는 정점의 밀집도가 클수록 높은 효율을 보인다.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2006년도 추계 학술대회
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• pp.236-242
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• 2006

세계적으로 각 분야에서 SERVQUAL 모형과 SERVPERF 모형 등을 이용한 서비스품질에 대한 측정과 관련된 연구들이 많이 수행되어 오고 있지만 서비스품질을 계량화시키기 위한 연구는 활성화되고 있지 못하는 상황이다. 따라서, 본 연구의 목적은 불확실하고 주관적인 환경에서 서비스품질을 객관성있게 측정하고 계량화시키기 위해서 L.A. Zadeh가 제안한 퍼지이론의 Triangular Fuzzy Number(TFN) 와 T.L. Saaty가 제안한 Analytic Hierarchy Process (AHP)를 이용하여 서비스품질을 측정하기 위한 방법을 제안하는 것이고, 본 연구를 통해서 조직의 제한적 자원으로 고객만족 극대화를 실현하기 위한 경쟁우위적 전략의 일환으로써 서비스품질을 제고시키는데 효율적이며 효과적인 의사결정안이 도출될 것으로 사료된다.

• 대한예방한의학회지
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• 제13권1호
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• pp.105-115
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• 2009

Background: The resource-based relative value scale has been applied to Korean medicine services as part of the National Health Insurance, yet the proper scoring method for physician's work needs to be developed. Objectives: To measure physician's work for Korean medicine services using Analytical Hierarchy Process(AHP) and to compare results abstracted by AHP with those by Magnitude Estimation method. Methods: We developed the AHP questionnaires for Korean Medicine services and administered it to 12 Korean medicine insurance experts. Weighted scores were calculated and were converted into physician's work scores. Results: In AHP measurement, the physician's work scores for acupuncture activities, especially special acupunctures, far increased, while those for diagnosis and basic consultations decreased. Variations in the scores enlarged. Conclusions: As an alternative, AHP method can be considered for measuring the physician's work for Korean medicine services with careful management of scoring variation.

• 산업경영시스템학회지
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• 제43권2호
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• pp.110-119
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• 2020

In order to provide priorities of the factors affecting the introduction of Smart Factory, This study reconstructed the factors and calculated the priorities through AHP (Analytic Hierarchy Process). The first layer of the hierarchy have 4 factors; productivity increase, brand image improve, marketing improve, cost reduction. The second layer of the hierarchy have 3 factors belong to the first layer, so the total number of second layer is 12. We divided the characteristics of enterprises into type of manager and age. The C.R. (consistency ratio) values of the respondents were found to be less than 0.1 and were judged to be a 'reasonable test'. As a result, the weights of the higher layer and the lower layer were obtained respectively, and then the weights of the higher layer and the weights of the lower layer were multiplied to obtain the total weights. Unlike previous studies that only surveyed factors that companies consider when introducing smart factory, (1) weighing and prioritizing factors were achieved. There are differences in priorities, (2) smart factory can be studied with the type of manager and firm age. When establishing policies, it is a practical implication (3) to assess its strategy not only for government officials but also for executives.

• 대한인간공학회지
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• 제31권4호
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• pp.507-513
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• 2012

Objective: This study developed a hierarchy of conditions of applications(devices), situations and functions which are applicable to gesture interface. Background: Gesture interface is one of the promising interfaces for our natural and intuitive interaction with intelligent machines and environments. Although there were many studies related to developing new gesture-based devices and gesture interfaces, it was little known which applications, situations and functions are applicable to gesture interface. Method: This study searched about 120 papers relevant to designing and applying gesture interfaces and vocabulary to find the gesture applicable conditions of applications, situations and functions. The conditions which were extracted from 16 closely-related papers were rearranged, and a hierarchy of them was developed to evaluate the applicability of applications, situations and functions to gesture interface. Results: This study summarized 10, 10 and 6 conditions of applications, situations and functions, respectively. In addition, the gesture applicable condition hierarchy of applications, situation and functions were developed based on the semantic similarity, ordering and serial or parallel relationship among them. Conclusion: This study collected gesture applicable conditions of application, situation and functions, and a hierarchy of them was developed to evaluate the applicability of gesture interface. Application: The gesture applicable conditions and hierarchy can be used in developing a framework and detailed criteria to evaluate applicability of applications situations and functions. Moreover, it can enable for designers of gesture interface and vocabulary to determine applications, situations and functions which are applicable to gesture interface.

• 한국경영과학회지
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• 제29권2호
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• pp.59-75
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• 2004

Recommendation is a personalized information filtering technology to help customers find which products they would like to purchase. Collaborative filtering works by matching customer preferences to other customers in making recommendations. But collaborative filtering based recommendations have two major limitations, sparsity and scalability. To overcome these problems we suggest using adjusted product hierarchy, grain. This methodology focuses on dimensionality reduction and uses a marketer's specific knowledge or experience to improve recommendation quality. The qualify of recommendations using each grain is compared with others by several experimentations. Experiments present that the usage of a grain holds the promise of allowing CF-based recommendations to scale to large data sets and at the same time produces better recommendations. In addition. our methodology is proved to save the computation time by 3∼4 times compared with collaborative filtering.