• Journal of Global Scholars of Marketing Science
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• v.17 no.3
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• pp.133-151
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• 2007

The purpose of this article is to examine the effects of item parceling on the consistency of significance testing of the causal parameters with regard to the relationship between the relevant constructs, as well as the effects of the item parceling on the goodness-of-fit indices of LISREL's general models. Most of the researchers' major purpose of using structural equation modeling (SEM) is to test their research hypotheses associated with the causal parameters. Therefore, we investigated three general models of LISREL, rather than the frequently used confirmatory factor analytic (CFA) models by many other researchers. The results of the study showed that there was a high level of consistency in the calculated test statics of causal parameters between the item-parceled solutions and the item-level solutions, and that the item-parceled solutions had better goodness-of-fit indices, such as GFI, AGFI, CFI, and NFI, than the solutions at the item level. However, in terms of RMSEA, there was no such tendency.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.175-177
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• 2003

연관규칙은 데이터 안에 존재하는 항목들간의 종속 관계를 찾아내는 것이다. 기존의 연구에서는 연관규칙 탐사 과정에서 발견항목 자체에만 관심을 두고 연구되어 왔다. 즉, 연관규칙 생성을 위한 후보 항목은 수량을 배제한 항목 대 수량비가 1:1인 상태에서 규칙을 발견하는 연구였다. 이것은 항목의 구매 수량에 관계없이 같은 가중치로 규칙을 발견하는 문제점을 갖고 있다. 두 번째 문제점은 연관규칙은 시간적 연장선상에서 발견되는 규칙이라 할 수 있다. 즉, 규칙을 발견하는 과정에서 모든 자료를 동일한 시간적 가중치를 두어 취급하는 것이다. 본 논문에서는 각각의 아이템을 (아이템, 수량)의 묶음 단위로 후보항목을 만들어 수량적 속성이 포함된 아이템 대 수량 비 1:n의 관계에서 규칙을 발견하는 방법을 제안한다. 또한 과거의 자료들을 이용하여 예측할 때 모든 자료를 동일하게 취급하기보다는 최근의 자료에 더 큰 비중을 주는 예측법을 사용하여 연관규칙 발견의 신뢰성을 높인다. 성능평가는 기존의 알고리즘과 비교하여 제안한 알고리즘의 성능향상 및 타당성을 보인다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.143-144
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• 2018

Edge Computing은 분담을 통해 네트워크의 부담을 줄일 수 있는 IoT 네트워크에 적합한 방법으로, 데이터를 전송하고 받는 과정에서 네트워크의 대역폭을 사용하는 대신 서로 연결된 노드들이 협력해서 데이터를 처리하고, 네트워크 말단에서의 데이터 처리가 허용되어 데이터 센터의 부담을 줄일 수 있다. 트리구조는 데이터 구조의 하나로, 데이터 항목의 한 묶음인 세그먼트를 나뭇가지처럼 연결한 것을 의미하여 분산된 데이터를 군집할 수 있다. 본 논문에서는 Edge Computing 환경에서 트리 구조를 이용하여 인덱스를 관리하는 모델을 알아보기 위해 이진 탐색 트리 중 AVL tree와 Paged Binary tree에 대해 서술하였다.

• Journal of Yeungnam Medical Science
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• v.24 no.2
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• pp.137-147
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• 2007

Background : Interpretative reporting is an important aspect of laboratory medicine. The large menu of laboratory tests available today makes it increasingly difficult for the non-specialist to order and interpret all laboratory tests. The aim of this study was to determine the usefulness of an expert system to interpret laboratory tests and help physicians order the appropriate tests. Materials and Methods : In order to interpret laboratory tests, a rules-based expert system was developed. In this module, if-then rules were used to interpret the given test result patterns (e.g. urinalysis, anemia, hepatitis B virus, hypercholesterolemia, glucose, syphilis, and tumor markers) and select matching text elements. The system was used to evaluate 535 subjects who visited a health-check program. Results : The overall abnormal rate was 50.5% in the expert system; 34% for cholesterol, 9.9% for urinalysis, 8.0% for anemia, 7.7% for thyroid function tests, 4.5% for tumor marker study, 4.7% for hepatitis virus antigen, 4.3% for serum glucose, and 1.1% for syphilis. Conclusion : These results indicate that the application of the expert system for the interpretation of laboratory tests may provide a useful method for the interpretation of reports. However more rules are needed for the application to in-patients.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.322-332
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• 2011

In this paper, we introduce the 1st performance evaluation of VLBI Correlation Subsystem (VCS) main product, which is core system of Korea-Japan Joint VLBI Correlator (KJJVC). The main goal of the 1st performance evaluation of VCS main product is that the perfection of overall system will be enhanced after checking the unsolved part by performing the experiments towards various test items at the manufacturer before installation of field. The functional test was performed by including the overflow problem occurred in the FFT re-quantization module due to the insufficient of effective bit at the VCS trial product in this performance test of VCS main product. Through the performance test for VCS main product in the factory, the problem such as FFT re-quantization discovered at performance test of VCS trial product in 2008 was clearly solved and the important functions such as delay tracking, daly compensation, and frequency bining were added in this VCS main product. We also confirmed that the predicted correlation results (fringe) was obtained in the correlation test by using real astronomical observed data(wideband/narrow band).

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.521-526
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• 2016

As on-line informal text data have massive in its volume and have unstructured characteristics in nature, there are limitations in applying traditional relational data model technologies for data storage and data analysis jobs. Moreover, using dynamically generating massive social data, social user's real-time reaction analysis tasks is hard to accomplish. In the paper, to capture easily the semantics of massive and informal on-line documents with unsupervised learning mechanism, we design and implement automatic topic extraction systems according to the mass of the words that consists a document. The input data set to the proposed system are generated first, using N-gram algorithm to build multiple words to capture the meaning of the sentences precisely, and Hadoop and Spark (In-memory distributed computing framework) are adopted to run topic model. In the experiment phases, TB level input data are processed for data preprocessing and proposed topic extraction steps are applied. We conclude that the proposed system shows good performance in extracting meaningful topics in time as the intermediate results come from main memories directly instead of an HDD reading.

• Journal of Advanced Technology Convergence
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• v.2 no.3
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• pp.33-41
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• 2023

This study aimed to improve the quality of classes through the application experience analysis after applying the adult nursing simulation practice modules with PBL. Quantitative and qualitative data such as from satisfaction, validity, self-reflection, and lecture evaluation in 68 nursing students were analyzed after the semester. Satisfaction was 4.64 points out of 5 points, and 'I want to recommend this class to other friends' was the highest. It was appropriate for the validity as 64.7% to 100% positve answer. From the qualitative data analysis of lecture evaluation, it was categorized into 5 thematic groups : 'increased immersion related to a lively class environment', 'growth of knowledge and skills through learners' active participation', 'improvement of mutual collaboration skills through team-based problem-solving process', 'Improvement of problem-solving ability through situational crisis coping process' and 'Improvement of individual comprehension through close teaching'. The continuous development of PBL learning strategies and development of various scenarios are required in the future.