In science and technology diplomacy, major countries actively utilize their capabilities in science and technology for public diplomacy, especially for promoting diplomatic relations with politically sensitive regions and countries. Recently, with an increase in the influence of science and technology on national development, interest in science and technology diplomacy has increased. So far, science and technology diplomacy has relied on experts to find research topics that are of common interest to both the countries. However, this method has various problems such as the bias arising from the subjective judgment of experts, the attribution of the halo effect to famous researchers, and the use of different criteria for different experts. This paper presents an objective data-based approach to identify and recommend research topics to support science and technology diplomacy without relying on the expert-based approach. The proposed approach is based on big data analysis that uses deep-learning techniques and bibliometric methods. The Scopus database is used to find proper topics for collaborative research between two countries. This approach has been used to support science and technology diplomacy between Korea and Hungary and has raised expectations of policy makers. This paper finally discusses aspects that should be focused on to improve the system in the future.
Proceedings of the Korea Database Society Conference
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1999.06a
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pp.175-186
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1999
Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.
Journal of the Korea Academia-Industrial cooperation Society
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v.21
no.11
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pp.510-518
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2020
With the promotion of digitalization in the construction industry, BIM has become an indispensable technology. On the other hand, it has not been actively utilized in practice because of the difficulty of BIM modeling. The reason is that 3D modeling is less productive not only because of the difficulty of learning BIM software but also the modeling work is done manually. Therefore, this study proposes a method and system that can improve the productivity of BIM-based modeling. For this reason, in the study, a slit caisson, which is a typical structure of a port, was selected as a development target, and various parameters were derived through interviews with experts so that it could be used in practice. This study presents a UI construction plan that considers user convenience for efficient management and operation of diverse and complex parameters. Based on this, this study used visual programming and Excel VBA to develop a BIM-based design automation system for slit caissons. The developed system can use many parameters to quickly develop slit caisson models suitable for various design conditions that can contribute to BIM-based modeling and productivity improvement.
A fully automatic and computationally efficient method is proposed for intelligent display of soccer video on small multimedia mobile devices. The rapid progress of the multimedia signal processing has contributed to the extensive use of multimedia devices with a small LCD panel. With these emerging small mobile devices, the video sequences captured for standard- or HDTV broadcasting may give the small-display-viewers uncomfortable experiences in understanding what is happening in a scene. For instance, in a soccer video sequence taken by a long-shot camera technique, the tiny objects (e.g., soccer ball and players) may not be clearly viewed on the small LCD panel. Thus, an intelligent display technique is needed for small-display-viewers. To this end, one of the key technologies is to determine region of interest (ROI), which is a part of the scene that viewers pay more attention to than other regions. In this paper, the focus is on soccer video display for mobile devices. Instead of taking visual saliency into account, we take domain-specific approach to exploit the characteristics of the soccer video. The proposed scheme includes three modules; ground color learning, shot classification, and ROI determination. The experimental results show the propose scheme is capable of intelligent video display on mobile devices.
Journal of The Korean Association For Science Education
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v.23
no.2
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pp.155-164
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2003
The purpose of the current study was to investigate the effects of explanations about physical phenomena given in non-physics textbooks on the formation of student physical conceptions. Two classes, 39 students in each, were sampled from two middle schools in Pusan, Korea, and two kinds of test tools for investigating student conceptions were developed for the study. The first test tool(a) investigated student conceptions after reading explanations about physical phenomena in non-physics textbooks, while the second(b) investigated student conceptions after reading explanations revised by physics education experts about the same physical phenomena. The two test tools were applied to each class, and for a fair invetigation, test(a) followed by test(b) was applied to one class, while test(b) followed by test(a) was applied to the other class. The results were as follows: In both classes, the students' level of understanding from explanations revised by physics education experts was significantly (p < .01) higher than that from explanations in non-physics textbooks. As such, it is feasible that false or inappropriate explanations in non-physics textbooks can cause student misconceptions. Moreover, the improper expression of physical science concepts, improper choice of scientific terms, and incorrect grammatical structures, along with the use of unsuitable examples and improper model pictures can make it difficult for students to understand physics concepts. Furthermore, differences in the terms used in physics textbook and those used in other textbooks can also confuse students' learning.
Journal of The Korean Association For Science Education
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v.34
no.1
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pp.10-20
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2014
This study compares the perceptions of elementary gifted child and science teacher in a science class for the gifted. In order to explore the research problem, students and teachers answered a written semi-structured questionnaire and participated in interviews regarding the gifted science class. The data was collected and analyzed. Science teachers recognized the characteristics of a good science class, especially in terms of educational content and teaching methodology. First, they suggested promoting inquiry skills, presenting a challenging task in atypical topic selection, student-centered curriculum, and controlling the pace of learning to recognize individual differences. Second, in terms of the science class skills and attitudes category, teachers recommended raising mutual satisfaction through vigorous interaction within a permissible atmosphere. Finally, science teachers need to strive for continued professional growth. Gifted children, meanwhile, want to investigate a wide range of topics without time constraints. Additionally, they may have to explore challenging topics further. They prefer to act like scientists in that they enjoy group activities, communication and cooperation. In particular, they want to be evaluated by others in a totally embedded assessment. Gifted children also expect teachers to understand the life circumstances and needs of the students. In addition, they asked for teachers to respect individual experiments and to show them how to safely use new equipment or research methods. As a result, gifted children and science teachers have to recognize the differences of opinion concerning a good science class for the gifted. This study can help formulate strategies to establish quality management of materials in gifted science classes.
Journal of The Korean Association For Science Education
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v.34
no.8
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pp.755-765
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2014
The convergence and consilience in education (hereafter, interdisciplinary education) is receiving great attention from societies. This study aims to investigate the works of scientists and artists who have intended to combine science with the arts in the modern era, to take into account the socio-philosophical setbacks during the period, and to suggest pedagogical implications of science education as interdisciplinary education. The concept of interdisciplinary education stems from Plato's thought, idea, as a comprehensive and invariant truth. The renaissance, full of enrichment about scientific achievement, was based on Neo-Platonism pursuing holistic-synthetic approach. During the time, scientists presented in this study tried to find comprehensive principles and borrow useful method from the arts. In such a context, scientists not only made use of the arts for expression of scientific knowledge, but also drew conclusion by analogical reasoning between science and the arts. Artists, as well, relied upon anatomy and optics especially, to elaborate linear perspective and even developed their own scientific knowledge through personal experience. Hence, contemporary science education should encourage students to hold a holistic viewpoint about science and the arts, articulate explicit goals and outcomes as interdisciplinary education, implement meta-disciplinary instruction about science and the arts, and develop assessment framework for collaborative learning. There may be good examples for inter-disciplinary education as listed: illustrating scientific ideas through the arts and vice versa, organizing collaborative works and evaluations criteria for them, and stressing problem solving on a daily basis.
This study proposes a Korean sentimental analysis algorithm that utilizes a letter-unit embedding and convolutional neural networks. Sentimental analysis is a natural language processing technique for subjective data analysis, such as a person's attitude, opinion, and propensity, as shown in the text. Recently, Korean sentimental analysis research has been steadily increased. However, it has failed to use a general-purpose sentimental dictionary and has built-up and used its own sentimental dictionary in each field. The problem with this phenomenon is that it does not conform to the characteristics of Korean. In this study, we have developed a model for analyzing emotions by producing syllable vectors based on the onset, peak, and coda, excluding morphology analysis during the emotional analysis procedure. As a result, we were able to minimize the problem of word learning and the problem of unregistered words, and the accuracy of the model was 88%. The model is less influenced by the unstructured nature of the input data and allows for polarized classification according to the context of the text. We hope that through this developed model will be easier for non-experts who wish to perform Korean sentimental analysis.
Journal of Korea Spatial Information System Society
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v.10
no.2
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pp.63-79
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2008
With the recent development of advanced GIS and complex spatial analysis technologies, the more sophisticated technologies are being required to support the advanced knowledge for solving geographical or spatial problems in various decision support systems. In addition, necessity for research on scientific crime investigation and forensic science is increasing particularly at law enforcement agencies and investigation institutions for efficient investigation and the prevention of crimes. There are active researches on geographic profiling to predict the base location such as criminals' residence by analyzing the spatial patterns of serial crimes. However, as previous researches on geographic profiling use simply statistical methods for spatial pattern analysis and do not apply a variety of spatial and temporal analysis technologies on serial crimes, they have the low prediction accuracy. Therefore, this paper identifies the typology the spatio-temporal patterns of serial crimes according to spatial distribution of crime sites and temporal distribution on occurrence of crimes and proposes STA-BLP(Spatio-Temporal Analysis based Base Location Prediction) algorithm which predicts the base location of serial crimes more accurately based on the patterns. STA-BLP improves the prediction accuracy by considering of the anisotropic pattern of serial crimes committed by criminals who prefer specific directions on a crime trip and the learning effect of criminals through repeated movement along the same route. In addition, it can predict base location more accurately in the serial crimes from multiple bases with the local prediction for some crime sites included in a cluster and the global prediction for all crime sites. Through a variety of experiments, we proved the superiority of the STA-BLP by comparing it with previous algorithms in terms of prediction accuracy.
Journal of The Korean Association For Science Education
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v.32
no.4
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pp.717-728
/
2012
The purpose of this study is to analyze the argumentation of gifted students in the perspective of rebuttal. Rebuttal is a significant indicator of argumentation quality; it is also an essential component for science learning through interaction. However, most previous research point out insufficient use of rebuttal in student's argumentation. The argumentation of 37 8th grade students, enrolled in institutes for the scientifically gifted in Seoul, are observed and recorded for 4 hours. The argumentation topic is about how to measure the brightness of the sun. Based on Verheij's (2005) five types of rebuttal patterns, the features of rebuttal are analyzed. It is found that students' argumentation include all of the five rebuttal types: rebuttal of the data, the claim, the warrant, warrant's applicability, and connection between data and claim. It is also found that these five types can be categorized in two groups. The first group consists of first three types and is characterized by the disagreement with the validity of what has been said. The second group consists of the last two types and is characterized by the suggestion or additional information for missing links in argumentation.
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