• Journal of Elementary Mathematics Education in Korea
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• v.19 no.4
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• pp.457-484
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• 2015

This study aims to investigate an approach to teach proportional reasoning in elementary mathematics class by analyzing the proportional strategies the students use to solve the proportional reasoning tasks and their percentages of correct answers. For this research 174 sixth graders are examined. The instrument test consists of various questions types in reference to the previous study; the proportional reasoning tasks are divided into algebraic-geometric, quantitative-qualitative and missing value-comparisons tasks. Comparing the percentages of correct answers according to the task types, the algebraic tasks are higher than the geometric tasks, quantitative tasks are higher than the qualitative tasks, and missing value tasks are higher than the comparisons tasks. As to the strategies that students employed, the percentage of using the informal strategy such as factor strategy and unit rate strategy is relatively higher than that of using the formal strategy, even after learning the cross product strategy. As an insightful approach for teaching proportional reasoning, based on the study results, it is suggested to teach the informal strategy explicitly instead of the informal strategy, reinforce the qualitative reasoning while combining the qualitative with the quantitative reasoning, and balance the various task types in the mathematics classroom.

• Science of Emotion and Sensibility
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• v.21 no.1
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• pp.177-186
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• 2018

The mechanism of emotion is complex and influenced by a variety of factors, so that it is crucial to analyze emotion in broad and diversified perspectives. In this study, we classified neutral and negative emotions(sadness, fear, surprise) using arousal evaluation, which is one of the psychological evaluation scales, as well as physiological signals. We have not only revealed the difference between physiological signals coupled to the emotions, but also assessed how accurate these emotions can be classified by our emotional recognizer based on neural network algorithm. A total of 146 participants(mean age $20.1{\pm}4.0$, male 41%) were emotionally stimulated while their physiological signals of the electrocardiogram, blood flow, and dermal activity were recorded. In addition, the participants evaluated their psychological states on the emotional rating scale in response to the emotional stimuli. Heart rate(HR), standard deviation(SDNN), blood flow(BVP), pulse wave transmission time(PTT), skin conduction level(SCL) and skin conduction response(SCR) were calculated before and after the emotional stimulation. As a result, the difference between physiological responses was verified corresponding to the emotions, and the highest emotion classification performance of 86.9% was obtained using the combined analysis of arousal and physiological features. This study suggests that negative emotion can be categorized by psychological and physiological evaluation along with the application of machine learning algorithm, which can contribute to the science and technology of detecting human emotion.

• Korean Journal of Health Education and Promotion
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• v.14 no.2
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• pp.43-57
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• 1997

Educational goals of SPH were two-fold : One was to train a health professions who should take charge of a leading roles, another were to educate the researchers of public health. There were strong demands to evaluate whether these goals had been effectively achieved through the master's course of SPH or not. According to the educational goals of SPH, public health is an applied science to be applicable to health-related fields. The curriculum of SPH has to be built under this principle and be evaluated by someone regularly. Who evaluates that? The most pertinent appraiser is the graduates of public health currently working at health-related jobs. It was the purpose of the study to let the graduates evaluate their education and the curriculum that they had undertaken during master's course at SNU. If the results of the evaluation by the graduates were not satisfactory, we should find the actual causes of low scored apraisal and reform the curriculum of SPH as the process of problem solving. During September and October 1996, a postal survey was undertaken of the 293 SNU graduates of public health who had been engaged in the health related jobs. As 198 graduates answered out of 293, the response rate was 67.6%. The questionnaire was designed to ascertain how well the SNU master's course of public health had helped their practice. The SAS package was used for statistical analysis and $x^2$-test as a test of statistical significance. Major findings of the study were summarized as follows: $\cdot$ The health related abilities consisted of three categories, which were health administration abilities composed of 14 items, health education abilities composed of 5 items, health research abilities composed of 10 items. $\cdot$ The respondents had acquired 'Worldwide trends of health policy', 'evaluation concepts of health projects', 'interpersonal relationships in professional life', and 'communication through writings' moe than other detailed items in the category of health administration abilities. $\cdot$ 'Establishment of educational and learning golas' was the most acquired item of 5 detailed items of health education abilities. $\cdot$ Respondents indicated that they had acquired ability 'to search reference', ' to understand health problems', 'to establish study plannings', and 'to collect health related data' more than other detailed items in the category of health research abilities.

• Journal of The Korean Association For Science Education
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• v.19 no.1
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• pp.29-40
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• 1999

The purpose of the present study was to test hypothesis that, because it uses tri-dimensional sensory pathway which have been showed a higher rate of neural activities than uni- or bi-dimensional's, lab-activity-based instruction is more effective teaching strategy in learning science than verbal-based instruction. In the present study, manipulative teaching strategy that uses visual, somatosensory and auditory information pathway was regarded as a mode of tri-dimensional sensory inputs. In addition, verbal teaching strategy that uses mainly auditory and a little visual information pathway was used as a mode of bi-dimensional sensory inputs. Fifty-six students who failed to successfully solve two proportional reasoning tasks (i.e., pouring water tasks) were sampled for this research from a junior high school. The subjects were randomly divided into a manipulative or a verbal teaching group, and given manipulative or verbal tutoring on the use of proportional reasoning strategies and a test of proportional reasoning during instruction. The results showed that manipulative group's performance on the test of proportional reasoning during instruction showed significantly higher performance than verbal group's (t=2.45, p<0.02). The present study also discussed some educational implications of the results.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.821-832
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• 1998

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. Fuzzy neuron, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an adaptive learning method by which a membership function and fuzzy rules were adapted for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water supplied to the city of Kwangju. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supplied (b) the mean temperature, and (c)the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.35% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• The Journal of Society for e-Business Studies
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• v.25 no.4
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• pp.77-109
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• 2020

In this paper, we build a gradient Boosting model to predict government SME R&D subsidy, select features of high importance, and measure the impact of each features to the predicted subsidy using PDP and SHAP value. Unlike previous empirical researches, we focus on the effect of the R&D subsidy distribution pattern to the incentive of the firms participating subsidy competition. We used the firm data constructed by KISTEP linking government R&D subsidy record with financial statements provided by NICE, and applied a Gradient Boosting model to predict R&D subsidy. We found that firms with higher R&D performance and larger R&D investment tend to have higher R&D subsidies, but firms with higher operation profit or total asset turnover rate tend to have lower R&D subsidies. Our results suggest that current government R&D subsidy distribution pattern provides incentive to improve R&D project performance, but not business performance.

• Korean journal of food and cookery science
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• v.29 no.2
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• pp.95-104
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• 2013

This study was conducted to investigate the current use and the demand for processed rice food products by full-time and working housewives in a metropolitan area. Out of 330 questionnaires distributed, 300 were analyzed(90.9% response rate). It was revealed that more than half of the respondents(54.0%) had used processed rice food products, regardless of their occupation. Most respondents stated that they used rice food products because of the variety of the products, digestibility and the taste. The development necessity for processed rice food products was analyzed, showing that rice cake(3.86), rice sauce(3.64), and rice cookie(3.89) had the highest score in each category. The average demand for education and promotion of rice food products was 3.89; among 7 items, menu recipe using rice flour was highly demanded(4.18) by the respondents. Approximately 43.0% of the respondents agreed that the internet is the most effective method for learning about rice flour cooking, and the respondents who have used processed rice food products(59.5%) were more likely to attend education programs compared to housewives who have not used processed rice food products (44.5%)(p<.05). Full-time housewife(59.4%) had a greater tendency to participate in the education program than working woman(44.4%)(p<.001). The findings suggested that various processed rice flour products with convenience to use and prolonged shelf-life will be needed.

• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.518-529
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• 2012

Integration of Europe was started when European Union Treaty was concluded at Maastricht for the first time on December, 1991. Europe which may be called as a cradle of modern national state has realized a single Europe not only in the socio-economic integration field but also in the political field. Under this background, it is considered that life-long education policy for developing a new integrated growth engine of EU requires educational response that may get ready for socio-economic environmental transformation more than anything else. In particular, this policy is faced with an important task of having to achieve harmony of efficiency through diversity and mutual coordination in pursuing cooperation and integrated development of life-long education field. However, notwithstanding their efforts, since 2008, some countries of EU were faced with economic crisis due to economic recession and this situation starts to drive the whole Europe even to the point of their financial crisis at last. This crisis is currently shaking socio-economic integration of EU. This study intends to observe a status of establishing life-long education system and promoting a policy for socio-economic integration of EU and to analyze as to what kind of relevance adult participation rate of life-long learning among the countries belonged to EU has with per capita income and to explore as whether socio-economic integration among member countries could be sustained based on problems of integrative life-long education system under the economic crisis of EU. In addition, through this study, an implication required for presenting a new paradigm conversion, policy establishment and development direction for the life-long education of our country is intended to be deduced.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.970-976
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• 2007

In this study, Polynomial Network Pattern Classifier(PNC) based on Fuzzy Inference Mechanism is designed and its parameters such as learning rate, momentum coefficient and fuzzification coefficient are optimized by means of Particle Swarm Optimization. The proposed PNC employes a partition function created by Fuzzy C-means(FCM) clustering as an activation function in hidden layer and polynomials weights between hidden layer and output layer. Using polynomials weights can help to improve the characteristic of the linear classification of basic neural networks classifier. In the viewpoint of linguistic analysis, the proposed classifier is expressed as a collection of "If-then" fuzzy rules. Namely, architecture of networks is constructed by three functional modules that are condition part, conclusion part and inference part. The condition part relates to the partition function of input space using FCM clustering. In the conclusion part, a polynomial function caries out the presentation of a partitioned local space. Lastly, the output of networks is gotten by fuzzy inference in the inference part. The proposed PNC generates a nonlinear discernment function in the output space and has the better performance of pattern classification as a classifier, because of the characteristic of polynomial based fuzzy inference of PNC.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.206-216
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• 2013

The emotion plays a critical role in human's daily life including learning, action, decision and communication. In this paper, emotion discrimination classifier is designed to reduce system complexity through reduced selection of dominant features from biosignals. The photoplethysmography(PPG), skin temperature, skin conductance, fontal and parietal electroencephalography(EEG) signals were measured during 4 types of movie watching associated with the induction of neutral, sad, fear joy emotions. The genetic algorithm with support vector machine(SVM) based fitness function was designed to determine dominant features among 24 parameters extracted from measured biosignals. It shows maximum classification accuracy of 96.4%, which is 17% higher than that of SVM alone. The minimum error features selected are the mean and NN50 of heart rate variability from PPG signal, the mean of PPG induced pulse transit time, the mean of skin resistance, and ${\delta}$ and ${\beta}$ frequency band powers of parietal EEG. The combination of parietal EEG, PPG, and skin resistance is recommendable in high accuracy instrumentation, while the combinational use of PPG and skin conductance(79% accuracy) is affordable in simplified instrumentation.