• Journal of Korean Elementary Science Education
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• v.37 no.4
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• pp.372-390
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• 2018

The purpose of this research is to know the scientific reasoning ability of elementary students. In order to find it, 320 elementary students wrote a report about germination of the 700 or 2,000 years old seeds. Their writings were analyzed by scientific writing analysis frameworks, Scientific Reasoning Types and Scientific Reasoning Level Criteria developed by Lim (2018). Minto Pyramid Principles was used to show statements and relations of statements related to scientific reasoning. This paper showed scientific reasoning statements of elementary students about germination of seeds. The characteristics of scientific reasoning of elementary students were as follows. In the process of logical writing by the types of scientific reasoning, many students showed various characteristics and different levels. In the writings based on inductive reasoning, they did not distinguish between common features and differences of cases, and did not derive the rules based on common features and differences of the cases. In the writings based on deductive reasoning, there were cases where the major premise corresponding to the principle or rule was omitted and only the phenomenon was described, or the rule was presented but not connected with the case. In the writings based on abductive reasoning, the ability to selectively use the background knowledge related to the question situation was not sufficient, and borrowing of similar background knowledge, which was commonly used in other situations, was very rare.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.220-225
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• 2021

Human population growth rate is an important parameter for real-world planning. Common approaches rely upon fixed parameters like human population, mortality rate, fertility rate, which is collected historically to determine the region's population growth rate. Literature does not provide a solution for areas with no historical knowledge. In such areas, machine learning can solve the problem, but a multitude of machine learning algorithm makes it difficult to determine the best approach. Further, the missing feature is a common real-world problem. Thus, it is essential to compare and select the machine learning techniques which provide the best and most robust in the presence of missing features. This study compares 17 machine learning techniques (base learners and ensemble learners) performance in predicting the human population growth rate of the country. Among the 17 machine learning techniques, random forest outperformed all the other techniques both in predictive performance and robustness towards missing features. Thus, the study successfully demonstrates and compares machine learning techniques to predict the human population growth rate in settings where historical data and feature information is not available. Further, the study provides the best machine learning algorithm for performing population growth rate prediction.

• Korean Journal of Radiology
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• v.23 no.6
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• pp.581-597
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• 2022

Left ventricular (LV) wall thickening, or LV hypertrophy (LVH), is common and occurs in diverse conditions including hypertrophic cardiomyopathy (HCM), hypertensive heart disease, aortic valve stenosis, lysosomal storage disorders, cardiac amyloidosis, mitochondrial cardiomyopathy, sarcoidosis and athlete's heart. Cardiac magnetic resonance (CMR) imaging provides various tissue contrasts and characteristics that reflect histological changes in the myocardium, such as cellular hypertrophy, cardiomyocyte disarray, interstitial fibrosis, extracellular accumulation of insoluble proteins, intracellular accumulation of fat, and intracellular vacuolar changes. Therefore, CMR imaging may be beneficial in establishing a differential diagnosis of LVH. Although various diseases share LV wall thickening as a common feature, the histologic changes that underscore each disease are distinct. This review focuses on CMR multiparametric myocardial analysis, which may provide clues for the differentiation of thickened myocardium based on the histologic features of HCM and its phenocopies.

• Journal of KIISE
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• v.44 no.6
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• pp.587-594
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• 2017

Recently, motor imagery electroencephalogram(EEG) based Brain-Computer Interface(BCI) systems have received a significant amount of attention in various fields, including medicine and engineering. The Common Spatial Pattern(CSP) algorithm is the most commonly-used method to extract the features from motor imagery EEG. However, the CSP algorithm has limited applicability in Small-Sample Setting(SSS) situations because these situations rely on a covariance matrix. In addition, large differences in performance depend on the frequency bands that are being used. To address these problems, 4-40Hz band EEG signals are divided using nine filter-banks and Regularized CSP(R-CSP) is applied to individual frequency bands. Then, the Mutual Information-Based Individual Feature(MIBIF) algorithm is applied to the features of R-CSP for selecting discriminative features. Thereafter, selected features are used as inputs of the classifier Least Square Support Vector Machine(LS-SVM). The proposed method yielded a classification accuracy of 87.5%, 100%, 63.78%, 82.14%, and 86.11% in five subjects("aa", "al", "av", "aw", and "ay", respectively) for BCI competition III dataset IVa by using 18 channels in the vicinity of the motor area of the cerebral cortex. The proposed method improved the mean classification accuracy by 16.21%, 10.77% and 3.32% compared to the CSP, R-CSP and FBCSP, respectively The proposed method shows a particularly excellent performance in the SSS situation.

• Korean Journal of Cognitive Science
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• v.28 no.4
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• pp.329-347
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• 2017

Early research into category-based feature inference reported various phenomena in human thinking including typicality, diversity, similarity effects, etc. Later research discovered that participants' prior knowledge has an extensive influence on these sorts of reasoning. The current research tested the effects of causal knowledge on feature inference and conducted modeling on the results. Participants performed feature inference for categories consisted of four features where the features were connected either in common cause or common effect structure. The results showed typicality effects along with violations of causal Markov condition in common cause structure and causal discounting in common effect structure. To model the results, it was assumed that participants perform feature inference based on the difference between the probabilities of an exemplar with the target feature and an exemplar without the target feature (that is, $p(E_{F(X)}{\mid}Cat)-p(E_{F({\sim}X)}{\mid}Cat)$). Exemplar probabilities were computed based on causal model theory (Rehder, 2003) and applied to inference for target features. The results showed that the model predicts not only typicality effects but also violations of causal Markov condition and causal discounting observed in participants' data.

• Journal of The Korean Association For Science Education
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• v.23 no.2
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• pp.144-154
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• 2003

This study investigated the common features of the best practices in the science classroom, which is the core of school education. The underlying assumption of this research is that the fulfillment of school education is possible with substantial instruction of school curricular areas. The substantial learning of any curricular area depends on each classroom lesson. Data from classroom observations in-depth interviews with teachers and a group of students, a collection of instructional materials were used to extract common characteristics of best practices implemented by 10 exemplary secondary-school science teachers. Common features of best science practices were analyzed in terms of (1)reorganization of science content, (2)pedagogical skills, (3)evaluation, and (4)teachers' efforts for professional development. Results indicated that exemplary science teachers adapted curriculum and textbook content according to students' level and learning context, were able to use a variety of instructional methods and strategies, provided cooperative and intellectually challenging learning environment, and improved their instruction based on assessment results. Also, these exemplary teachers not only improved their own classroom practices, but also participated actively in various professional community of science teachers to share their practical knowledge with their colleagues. They took an active role in teachers' in-service education.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2007.05a
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• pp.255-259
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• 2007

Contemporary society is a digital and information-oriented society and a change by digital and information-oriented has made a new society principle and creature. The principle and creature has made society changed having influence on office space. The 21st century business space attachs great importance to the public space as the value of work place, namely, the place of gathering and client meeting which is society space and a thing which grants it with the biggest investment worth is a new order. This kind of society change has been making an appearance in contemporary office space as features of Narrative, Nodal, Neighbourly, Nomadic. These kinds of trends which are not exclusive mutually are stipulated as new trials to business space holding a lot of overriding features in common. These kinds of features brought into relief according to society change can be seen as key words speaking for contemporary office space and have a significance to contemplate and study for the office space of a new concept made an appearance together with society change. It is expected to contribute to revitalization programs with the far-reaching effect of understanding about ideal office work circumstances and work shape which the 21st century wants standing on the features of these new concepts.

• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.53-61
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• 2017

The preferred feature selection methods for text classification are filter-based. In a common filter-based feature selection scheme, unique scores are assigned to features; then, these features are sorted according to their scores. The last step is to add the top-N features to the feature set. In this paper, we propose an improved global feature selection scheme wherein its last step is modified to obtain a more representative feature set. The proposed method aims to improve the classification performance of global feature selection methods by creating a feature set representing all classes almost equally. For this purpose, a local feature selection method is used in the proposed method to label features according to their discriminative power on classes; these labels are used while producing the feature sets. Experimental results obtained using the well-known 20 Newsgroups and Reuters-21578 datasets with the k-nearest neighbor algorithm and a support vector machine indicate that the proposed method improves the classification performance in terms of a widely known metric ($F_1$).

• The Research Journal of the Costume Culture
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• v.22 no.6
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• pp.873-889
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• 2014

The goals of this study are to analyze how fashion professionals' attitudes toward Grunge style have changed since the 1990s and to compare aesthetic features of 1990s Grunge style and the style since 2000. By searching Vogue and Women's Wear Daily articles from 1992 to 2014 according to the keyword "Grunge", three collections from the 1990s and 59 collections since 2000 were selected for analysis. Although Grunge collections of the 1990s were harshly criticized by critics and retailers as ugly, the more recent collections have been highly praised for both design and profitability. The common aesthetic features of Grunge style in the 1990s and beyond include loose silhouettes, mix-and-match layerings, plaid patterns, floral prints, and striped patterns. However, Grunge style since 2000 has new features such as ornate fabrics, handcrafted details, a formal and dressy look, and faux plaid flannel shirts in chiffon or organza. These features give the style a more luxurious, feminine, and refined appearance. The results of this study indicate that Grunge style of the 1990s changed high fashion beauty standards and today's designers and consumers prefer to mix various styles to create new ones. They typically do not consider the original spirit or identities of the varied styles.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.37-44
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• 2006

To use surveying data obtained from different sensors and different techniques, it is a pre-requite step that register them in a common coordinate system. For this purpose, we developed methodologies to register airborne photos, ALS (Airborne Laser Scanning) data and digital maps. To achieve this, conjugate features from these data should be extracted in advance. In this study, linear features are chosen as conjugate features. Based on such a selection strategy, a simple and robust algorithm is proposed for extracting such features from ALS data. Then, to register them, observation equations are established from similarity measurements of the extracted features and the results was evaluated statistically. The results clearly demonstrate that the proposed algorithms are appropriate to register these data.