• Journal of The Korean Association For Science Education
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• v.37 no.5
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• pp.799-812
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• 2017

Energy as a powerful and unifying concept to understand natural world has been regarded as one of the key concepts of the science curricula in many countries. However, concerning learning and teaching of energy, various difficulties have been reported widely. This study aimed at analyzing and comparing science curricula of Korea, the U.S., England, and Singapore regarding energy to identify the potential issues for energy curriculum in the future. 2015 revised Korean science curriculum, Next Generation Science Standards of the U.S., Science programmes of study of England, and the Science syllabus of Singapore were compared based on six basic elements of the concept of energy: energy form, energy resource, energy transfer, energy transformation, energy conservation, and energy dissipation. Achievement criteria that include energy were extracted from all curricula and categorized into the six elements. The frequency and distribution of the six elements in the four curricula were compared in terms of school levels and disciplinary areas. Contents of six energy elements were also compared. Though all curricula emphasized energy as a key science concept, we found many differences in the degree of emphasis of basic ideas and specific contents and approaches. Korean curriculum is characterized by 1) high frequency concerning energy form among the elements of the concept of energy, 2) introducing energy forms of unclear meaning, which are not linked with other physical quantities, 3) emphasis on energy conversion in comparison of energy transfer, 4) focusing on mechanical energy conservation instead of more general energy conservation, and 5) absence of the concept of 'system' concerning energy. Issues for energy curriculum development were discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Journal of the Korean association of regional geographers
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• v.14 no.5
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• pp.521-535
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• 2008

This paper aims to explore the spatial distribution and locational characteristics of the shipbuilding industry in the south-east region of Korea. The geography of the Korea's shipbuilding industry illustrates an absolute spatial concentration into the south-east region, including Gyeongnam, Busan and Ulsan. In view of the type of agglomeration, it is argued that the south-east region's shipbuilding industry has been evolved as an Advanced Hub & Spoke cluster, which is characterized by interconnected relationships between a couple of gigantic customer firms and the majority of small and medium-sized supplier firms. A survey on the locational factors of the firms presents that traditional locational factors, such as physical infrastructure, land, labour and industrial linkages, are more important than new economic geographical locational factors, such as knowledge, learning, innovation and networks. According to firm's evaluation of the Gyeongnam region's locational environments for the shipbuilding industry is, however, rather different to the result of firm's location decision factors. The shipbuilding firms in Gyeongnam see that the Gyeongnam region retains regional advantages in terms of agglomeration economies, geographical proximity to customers, the infrastructure of transportation and communication and the quality of life. On the contrary, firms recognize that the Gyeongnam region suffers from the lack of R&D and production workforce and a weak basis of industry-university -government networks.

• Education of Primary School Mathematics
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• v.21 no.4
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• pp.445-459
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• 2018

The purpose of this study is to provide a method to help elementary school students learn ratio-related concepts effectively through visual representations. This study was conducted to identify the differences in the composition of ratio-related concepts between Korean and Singaporean textbooks, reconstruct a unit of proportional expressions and distributions by using visual representations and confirm the differences in performance between an experimental and a comparison group of 6th grade students. While the experimental group mathematics lessons is from the reconstructed textbook, the comparison group lessons is from an existing textbook that does not include any reconstructive representations. A t-test of mean was applied to determine the differences between the experimental and comparison group. Analysis revealed significant differences in the mean between the experimental group and the comparison group, and the intermediate level group showed more improvement compared to the higher and lower level groups. An implication of this study is that the application of visual representations can assist students' understanding of ratio-related concepts.

• The Korean Journal of Food And Nutrition
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• v.34 no.5
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• pp.487-497
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• 2021

To investigate the industrial availability of liquid fermentation (PL-ferment) by Phellinus linteus mycelium as a postbiotics for the inhibition of inflammation, PL-ferment was fractionated into culture supernatant (CS), hot-water extract (HW) from PL-ferment, EtOH-precipitate (CP) fractionated from HW, and the dialysate (DCP) of CP. Compared to the other fractions, DCP which is expected to contain exopolysaccharide (EPS) as the major component, significantly decreased the production of NO, IL-6, and MCP-1 in LPS-induced RAW 264.7 cells, and IL-6 and IL-8 in TNF-α and IFN-γ-induced HaCaT cells. The general component analysis results showed that no significant difference in components was observed between the fractions, whereas sugar composition analysis revealed that DCP had decreased glucose and increased mannose contents compared to the other fractions. This suggests that mannose played an important role in the anti-inflammatory activity of the active fraction, DCP. Molecular weight distribution analysis revealed that DCP was mainly composed of low-molecular-weight material-removed high-molecular-weight polysaccharides of 18-638 kDa, suggesting that EPS originated from P. linteus EPS. In conclusion, our results suggest that the DCP of P. linteus mycelium fermentation using the anti-inflammatory activity could be used industrially as postbiotic material.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1307-1315
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• 2021

The Changjiang Diluted Water (CDW) spreads over the East China Sea every summer and significantly affects the sea surface salinity changes in the seas around Jeju Island and the southern coast of Korea peninsula. Sometimes its effect extends to the eastern coast of Korea peninsula through the Korea Strait. Specifically, the CDW has a significant impact on marine physics and ecology and causes damage to fisheries and aquaculture. However, due to the limited field surveys, continuous observation of the CDW in the East China Sea is practically difficult. Many studies have been conducted using satellite measurements to monitor CDW distribution in near-real time. In this study, an algorithm for estimating Sea Surface Salinity (SSS) in the East China Sea was developed using the Geostationary Ocean Color Imager (GOCI). The Multilayer Perceptron Neural Network (MPNN) method was employed for developing an algorithm, and Soil Moisture Active Passive (SMAP) SSS data was selected for the output. In the previous study, an algorithm for estimating SSS using GOCI was trained by 2016 observation data. By comparison, the train data period was extended from 2015 to 2020 to improve the algorithm performance. The validation results with the National Institute of Fisheries Science (NIFS) serial oceanographic observation data from 2011 to 2019 show 0.61 of coefficient of determination (R²) and 1.08 psu of Root Mean Square Errors (RMSE). This study was carried out to develop an algorithm for monitoring the surface salinity of the East China Sea using GOCI and is expected to contribute to the development of the algorithm for estimating SSS by using GOCI-II.

• Journal of the Korean earth science society
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• v.42 no.3
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• pp.296-310
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• 2021

El Niño is a typical ocean and atmospheric interaction phenomenon that causes climate variability on a global scale, so it has been used as a very important teaching and learning material in the field of earth science. This study summarized the distribution and dynamics of the equatorial current system. The variability of the equatorial current system during the El Niño period and the associated misconceptions were also investigated. The North Equatorial Current, South Equatorial Current, and Equatorial Under Current significantly weaken during El Niño years. However, the variability of the North Equatorial Counter Current (NECC) during the El Niño period cannot be generalized because the NECC shows southward movement with weakening in the northern area and strengthening in the southern area, along its central axis. In the western Pacific, the NECC is further south during El Niño years, and thus, it has an eastward flow in the equatorial western Pacific. Our analysis of a mass media science article, a secondary school exam, and a survey for incumbent teachers confirmed disparate ideas about the equatorial current system's variability during El Niño periods. This is likely due to inaccurate interpretations of the existing El Niño schematic diagram and insufficient understanding of the equatorial current and wave dynamics.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.839-850
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• 2018

The flood damage in urban areas due to torrential rain is increasing with urbanization. For this reason, accurate and rapid flooding forecasting and expected inundation maps are needed. Predicting the extent of flooding for certain rainfalls is a very important issue in preparing flood in advance. Recently, government agencies are trying to provide expected inundation maps to the public. However, there is a lack of quantifying the extent of inundation caused by a particular rainfall scenario and the real-time prediction method for flood extent within a short time. Therefore the real-time prediction of flood extent is needed based on rainfall-runoff-inundation analysis. One/two dimensional model are continued to analyize drainage network, manhole overflow and inundation propagation by rainfall condition. By applying the various rainfall scenarios considering rainfall duration/distribution and return periods, the inundation volume and depth can be estimated and stored on a database. The Rainfall-Duration-Flooding Quantity (RDF) relationship curve based on the hydraulic analysis results and the Self-Organizing Map (SOM) that conducts unsupervised learning are applied to predict flooded area with particular rainfall condition. The validity of the proposed methodology was examined by comparing the results of the expected flood map with the 2-dimensional hydraulic model. Based on the result of the study, it is judged that this methodology will be useful to provide an unknown flood map according to medium-sized rainfall or frequency scenario. Furthermore, it will be used as a fundamental data for flood forecast by establishing the RDF curve which the relationship of rainfall-outflow-flood is considered and the database of expected inundation maps.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.11
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• pp.435-442
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• 2018

Outlier detection means to detect data samples that deviate significantly from the distribution of normal data. Most outlier detection methods calculate an outlier score that indicates the extent to which a data sample is out of normal state and determine it to be an outlier when its outlier score is above a given threshold. However, since the range of an outlier score is different for each data and the outliers exist at a smaller ratio than the normal data, it is very difficult to determine the threshold value for an outlier score. Further, in an actual situation, it is not easy to acquire data including a sufficient amount of outliers available for learning. In this paper, we propose a clustering-based outlier detection method by constructing a model representing a normal data region using only normal data and performing binary classification of outliers and normal data for new data samples. Then, by dividing the given normal data into chunks, and constructing a clustering model for each chunk, we expand it to the ensemble method combining the decision by the models and apply it to the streaming data with dynamic changes. Experimental results using real data and artificial data show high performance of the proposed method.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.561-566
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• 2021

Schools are highly feared to spread widely in the event of an infectious disease, and systematic management and prompt response are needed as it can undermine students' health and learning rights. This study was conducted to identify the current status of infectious diseases common to elementary, middle and high school students and to provide basic data to protect students and faculty from the threat of infectious diseases and maintain normal school functions. Sejong City was selected for investigation. The three major infectious diseases are influenza, chickenpox and aquarium, all of which are classified as acute viral infectious diseases and have fast propagation speed and strong propagation power, which can have fatal consequences for students living in groups. The research data were analyzed using the 2019 infectious disease report data from the Education Ministry's Education Administration Information Network (NEIS), and the current status data reported by elementary, middle and high schools nationwide were analyzed. The research method was to compare the current status of infectious diseases across the country and Sejong City, compare the status of issuance by each school level, compare the status of infectious diseases by item, and analyze the status of infectious diseases by time. The results of the survey on the status of the three major infectious diseases are expected to be used as basic data for managing infectious diseases not only in Sejong City but also in the nation, so that they can be used to establish measures to manage student infectious diseases in the future.