• Educational Technology International
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• v.21 no.2
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• pp.217-247
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• 2020

Many developing countries consider ICT as a key enabler to improve their educational systems and teachers are viewed as change agents. This paper aims to present policy suggestions concerning how to foster teachers' ICT competencies in developing countries based on the outcomes of an ODA project case in Peru. This study was conducted through three stages: Literature survey, site visit, and policy suggestions. To draw relevant policy suggestions, we employed the framework of the 'macro-meso-micro' level of teacher professional development. The following policy suggestions are discussed: (a) macro level: to develop the national framework of teacher ICT competencies and competency-based teacher training, (b) meso-level: to promote teacher communities of practices and school-based research programs, and (c) micro-level: to redesign teacher professional development programs to help teachers better understand the complex relationships between content, pedagogy, and technology, beyond learning about basic ICT literacy skills. This study contributes to the understanding of how ODA projects can approach the issue of teacher ICT capacity building at multiple levels.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.685-687
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• 2021

본 논문에서는 플랜트 배관의 기체 누출 탐지방안에 대하여 기술한다. 배관 누출 발생 시 배관 내부 압력과 누출부 크기의 조합에 따라 누출 초음파 발생 여부가 결정되는데, 누출 시 초음파가 발생하는 경우와 그렇지 않은 경우에 대하여 배관 누출을 탐지하는 방안과 보온재 배관의 누출탐지 방안에 대하여 설명한다. 또한 배관 파단을 상시감시하기 위한 대량의 무선센서 운용에 따른 대량 누출탐지신호의 실시간 처리를 위한 쿠버네티스 기반의 분산처리형 진단 시스템 구현 방안에 대하여 기술한다.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.318-326
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• 2022

Marketing stress testing is a new method of identifying the company's strengths and weaknesses in a turbulent environment. Technically, this is a complex procedure, so it involves artificial intelligence and machine learning. The main problem is currently the development of methodological approaches to the development of the company's digital model, which will provide a framework for machine learning. The aim of the study was to identify and develop an author's approach to the parameterization of the company's business processes for machine learning-based marketing stress testing. This aim provided the company's activities to be considered as a set of elements (business processes, products) and factors that affect them (marketing environment). The article proposes an author's approach to the parameterization of the company's business processes for machine learning-based marketing stress testing. The proposed approach includes four main elements that are subject to parameterization: elements of the company's internal environment, factors of the marketing environment, the company' core competency and factors impacting the company. Matrices for evaluating the results of the work of expert groups to determine the degree of influence of the marketing environment factors were developed. It is proposed to distinguish between mega-level, macro-level, meso-level and micro-level factors depending on the degree of impact on the company. The methodological limitation of the study is that it involves the modelling method as the only one possible at this stage of the study. The implementation limitation is that the proposed approach can only be used if the company plans to use machine learning for marketing stress testing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.228-234
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• 2021

Real estate market participants need to have a sense of predicting real estate prices in decision-making. Commonly used methodologies, such as regression analysis, ARIMA, and VAR, have limitations in predicting the value of an asset, which fluctuates due to unknown variables. Therefore, to mitigate the limitations, an artificial neural was is used to predict the price trend of apartments in Seoul, the hottest real estate market in South Korea. For artificial neural network learning, the learning model is designed with 12 variables, which are divided into macro and micro factors. The study was conducted in three ways: (Ed note: What is the difference between case 1 and 2? Is case 1 micro factors?)CASE1 with macro factors, CASE2 with macro factors, and CASE3 with the combination of both factors. As a result, CASE1 and CASE2 show 87.5% predictive accuracy during the two-year experiment, and CASE3 shows 95.8%. This study defines various factors affecting apartment prices in macro and microscopic terms. The study also proposes an artificial network technique in predicting the price trend of apartments and analyzes its effectiveness. Therefore, it is expected that the recently developed learning technique can be applied to the real estate industry, enabling more efficient decision-making by market participants.

• Composites Research
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• v.36 no.1
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• pp.48-52
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• 2023

Fiber-reinforced composites have anisotropic material properties, so the mechanical properties of composite structures can vary depending on the stacking sequence. Therefore, it is essential to design the proper stacking sequence of composite structures according to the functional requirements. However, depending on the manufacturing condition or the shape of the structure, there are many cases where the designed stacking angle is out of range, which can affect structural performance. Accordingly, it is important to analyze the stacking angle in order to confirm that the composite structure is correctly fabricated as designed. In this study, the stacking angle was predicted from real cross-sectional images of fiber-reinforced composites using convolutional neural network (CNN)-based deep learning. Carbon fiber-reinforced composite specimens with several stacking angles were fabricated and their cross-sections were photographed on a micro-scale using an optical microscope. The training was performed for a CNN-based deep learning model using the cross-sectional image data of the composite specimens. As a result, the stacking angle can be predicted from the actual cross-sectional image of the fiber-reinforced composite with high accuracy.

• Journal of Computing Science and Engineering
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• v.6 no.2
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• pp.151-160
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• 2012

We present a methodology that automatically selects indexing algorithms for each heading in Medical Subject Headings (MeSH), National Library of Medicine's vocabulary for indexing MEDLINE. While manually comparing indexing methods is manageable with a limited number of MeSH headings, a large number of them make automation of this selection desirable. Results show that this process can be automated, based on previously indexed MEDLINE citations. We find that AdaBoostM1 is better suited to index a group of MeSH hedings named Check Tags, and helps improve the micro F-measure from 0.5385 to 0.7157, and the macro F-measure from 0.4123 to 0.5387 (both p < 0.01).

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.1014-1023
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• 2016

In this study, we presented a method for non-square Differential LBP operation that can well describe the micro pattern in the horizontal and vertical component. We proposed a way to represent a LBP operation with various direction components as well as the diagonal component. In order to verify the validity of the proposed operation, Differential LBP was investigated with respect to accuracy, sensitivity, and specificity for the classification of facial expression. In accuracy comparison proposed LBP operation obtains better results than Square LBP and LBP-CS operations. Also, Proposed Differential LBP gets better results than previous two methods in the sensitivity and specificity indicators 'Neutral', 'Happiness', 'Surprise', and 'Anger' and excellence Differential LBP was confirmed.

• The Mathematical Education
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• v.43 no.2
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• pp.177-186
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• 2004

In this paper, we introduce new functional definitions for school geometry based on DGS (dynamic geometry system) teaching-learning environment. For the vertices forming a geometric figure, we first consider the relationship between the independent vertices and dependent vertices, and using this relationship and educational considerations in DGS, we introduce functional definitions for the geometric figures in terms of its independent vertices. For this purpose, we design a new DGS called JavaMAL MicroWorld. Based on the needs of new definitions in DGS environment for the student's construction activities in learning geometry, we also design a new DGS based geometry curriculum in which the definitions of the school geometry are newly defined and reconnected in a new way. Using these funct onal definitions, we have taught the new geometry contents emphasizing the sequential expressions for the student's geometric activities.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.190-194
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• 1998

In this paper, we introduce the micro robot soccer playing system as a standard test bench for the study on the multiple agent system. Our method is based on following viewpoints. They are (1) any complex behavior such as cooperation among agents must be completed by sequential basic actions of concerned agents. (2) those basic actions can be well defined, but (3) how to organize those actions in current time point so as to result in a new stale beneficial to the end aim ought to be achieved by a kind of self-learning self-organization strategy.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.775-777
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• 2003

miRNA(microRNA)는 길이가 약 22nt 정도 되는 작은 ncRNA로서 유전자 작용을 조절하는데 중요한 역할을 하는 것으로 알려져 있다. 다이서(dicer)에 의해 성숙한 miRNA(mature miRNA)를 계산학적(computational)방법으로 학습하여 인간 miRNA의 구조를 예측하였다. miRNA에 관한 구체적인 기작은 아직 확실히 밝혀지지 않았기 때문에 서열 기반과 구조 기반 모두를 포함 하는 모델을 구현 하였으며 ambiguity code를 씀으로써 정보의 손실을 최소화 하도록 하였다. miRNA와 비슷한 구조를 가진 인간 EST로부터 데이터를 무작위 추출하여 실제 인간 miRNA 데이터와 비교함으로써 학습된 결과의 성능을 평가하였다.