• 응용통계연구
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• 제24권6호
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• pp.1197-1211
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• 2011

The actual power performance of historical structural change tests are compared under various alternatives. The tests of interest are F, CUSUM, MOSUM, Moving Estimates and empirical distribution function tests with both recursive and ordinary least-squares residuals. Our comparison of the structural tests involves limiting distributions under the hypothesis, the ability to detect the alternative hypotheses under one or double structural change, and smooth change in parameters. Even though no version is uniformly superior to the other, the knowledge about the properties of those tests and connections between these tests can be used in practical structural change tests and in further research on other change tests.

• Asian Pacific Journal of Cancer Prevention
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• 제15권12호
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• pp.5097-5105
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• 2014

Knowledge of health and community psychology in health professionals influences psychosocial and community determinants of health and promoting participation in disease prevention at the community level. This paper appraises the potential of knowledge on psychology in health care professionals and its contribution to community empowerment through individual behavior change and health practice. The authors proposed a schematic model for the use of psychological knowledge in health professionals to promote participation in health interventions/disease prevention programs in developing countries. By implication, the paper provides a vision on policies towards supporting breast cancer secondary prevention efforts for community health development in Asian countries.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.410-415
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• 1997

Recently, The manufacturing companies are introducing the CAD/CAM systems to solve problems for the lack of experts, the higher cost of manufacturing and the difficulties of process. Knowledge engineering approach makes it possible to change a know-how of experts to computerized information effectivly. The proposal of this paper is the development of an interactive knowledge-based CAM system to disign and manufacture the mold with non-expert engineers used easily. This system is composed of two functional parts. One is the geometric modeler that used the technique of a feature modeling. The other is the expert system module that composed inference engine and databas which contains characteristics of materials and cutting tools setc.

• 패션비즈니스
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• 제25권6호
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• pp.25-45
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• 2021

Due to the fashion industry taking responsibility for their garment manufacturing, a significant number of UK universities are focusing on combining sustainability in their curriculum to support future employees' skills and knowledge in sustainable fashion. A proper understanding of educational and instructional theories is needed to develop effective teaching and learning materials and environments. Therefore, this study aimed to evaluate the Fashion Design module created with consideration of sustainability using ADDIE instructional model. For evaluation, the teaching materials, including the module brief and the PowerPoint slides for each session, were used. Ten students were interviewed and observed along with two tutors, also interviewed to analyze the strengths and weaknesses of the module from a variety of viewpoints. With sustainable fashion being embedded into specialized higher education courses, tutors decided to incorporate sustainability into the module as an introduction to this topical subject in order to build a stronger foundation of knowledge and challenge traditional ways of working. Results showed that combining sustainability into the design and technical sessions had a positive influence on students who built upon their existing knowledge. Tutors researched the need for change within the industry in line with the Sustainable Development Goals and aligned the content to inform the students of the current crisis. This study could provide a guideline to create instructional material for sustainable fashion design courses.

• 로봇학회논문지
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• 제18권3호
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• pp.346-351
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• 2023

With the release of numerous open driving datasets, the demand for domain adaptation in perception tasks has increased, particularly when transferring knowledge from rich datasets to novel domains. However, it is difficult to solve the change 1) in the sensor domain caused by heterogeneous LiDAR sensors and 2) in the environmental domain caused by different environmental factors. We overcome domain differences in the semi-supervised setting with 3-stage model parameter training. First, we pre-train the model with the source dataset with object scaling based on statistics of the object size. Then we fine-tine the partially frozen model weights with copy-and-paste augmentation. The 3D points in the box labels are copied from one scene and pasted to the other scenes. Finally, we use the knowledge distillation method to update the student network with a moving average from the teacher network along with a self-training method with pseudo labels. Test-Time Augmentation with varying z values is employed to predict the final results. Our method achieved 3rd place in ECCV 2022 workshop on the 3D Perception for Autonomous Driving challenge.

• 한국과학교육학회지
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• 제22권5호
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• pp.1044-1070
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• 2002

Initial science teacher education in Hong Kong is provided by the Post-graduate Diploma in Education Programme (PGDE) for both pre-service and in-service secondary school teachers. This programme includes a balanced treatment of subject curriculum and teaching in science, general pedagogical knowledge and skills, educational psychology and school administration. The science courses in this programme also have some units that equip science teachers with the knowledge and skills that are essential for teaching a science curriculum that emphasises conceptual change and understanding of the nature and methods of science. This emphasis is illustrated by two studies: (1) Developing a conceptual change model of instruction in Biology teachers, and (2) Constructing understanding of the nature and methods of science.

• 한국멀티미디어학회논문지
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• 제20권1호
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• pp.10-16
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• 2017

This paper proposes efficient schemes for image segmentation using the region-based active contour model. The developed methods can approach the boundaries of the desired objects by evolving the curves through minimization of the Mumford-Shah energy functionals, given arbitrary curves as initial conditions. Topological changes such as splitting or merging of curves should be handled for the methods to work properly without prior knowledge of the number of objects to be segmented. This paper introduces how to change topological structure of the curves and shows experimental results by applying the methods to the images.

• 지식경영연구
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• 제15권3호
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• pp.169-188
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• 2014

Big data seems to change knowledge management system and method of enterprises to large extent. Further, the type of method for utilization of unstructured data including image, v ideo, sensor data a nd text may determine the decision on expansion of knowledge management of the enterprise or government. This paper, in this light, attempts to figure out the prediction model of demands and supply for big data market of Korea trough data mining decision making tree by utilizing text bit data generated for 3 years on web and SNS for expansion of form for knowledge management. The results indicate that the market focused on H/W and storage leading by the government is big data market of Korea. Further, the demanders of big data have been found to put important on attribute factors including interest, quickness and economics. Meanwhile, innovation and growth have been found to be the attribute factors onto which the supplier puts importance. The results of this research show that the factors affect acceptance of big data technology differ for supplier and demander. This article may provide basic method for study on expansion of analysis form of enterprise and connection with its management activities.

• 한국초등과학교육학회지:초등과학교육
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• 제38권3호
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• pp.375-386
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• 2019

This study explores how elementary school students construct food pyramid prediction models using scientific reasoning. Thirty small groups of sixth-grade students in the Kyoungki province (n=138) participated in this study; each small group constructed a food pyramid prediction model based on scientific reasoning, utilizing prior knowledge on topics such as biotic and abiotic factors, food chains, food webs, and food pyramid concepts. To understand the scientific reasoning applied by the students during the modeling process, three forms of qualitative data were collected and analyzed: each small group's discourse, their representation, and the researcher's field notes. Based on this data, the researcher categorized the students' model patterns into three categories and identified how the students used scientific reasoning in their model patterns. The study found that the model patterns consisted of the population number variation model, the biological and abiotic factors change model, and the equilibrium model. In the population number variation model, students used phenomenon-based reasoning and relation-based reasoning to predict variations in the number of producers and consumers. In the biotic and abiotic factors change model, students used relation-based reasoning to predict the effects on producers and consumers as well as on decomposers and abiotic factors. In the equilibrium model, students predicted that "the food pyramid would reach equilibrium," using relation-based reasoning and model-based reasoning. This study demonstrates that elementary school students can systematically elaborate on complicated ecology concepts using scientific reasoning and modeling processes.

• Journal of information and communication convergence engineering
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• 제8권1호
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• pp.89-94
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• 2010

The most important of rule-base system is the knowledge base that determines the power of rule-base system. The important form of this knowledge is how to descript kinds of rules. The Rule-Base System (RBS) has been using in many field that need reflect quickly change of business rules in management system. As far, when develop the Rule-Based System, we must make a rule engine with a general language. There are three disadvantage of in this developed method. First, while there are many data that must be processed in the system, the speed of processing data will become very slow so that we cannot accept it. Second, we cannot change the current system to make it adaptive to changes of business rules as quickly as possible. Third, large data make the rule engine become very complex. Therefore, in this paper, we propose the two important methods of raising efficiency of Rule-Base System. The first method refers to using the Relational database technology to process the rules of the Rule-Base System, the second method refers to a algorithm of according to Quine McCluskey formula compress the rows of rule table. Because the expressive languages of rule are still remaining many problems, we will introduce a new expressive language, which is Rule-Base Data Model short as RBDM in this paper.