• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.419-431
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• 2018

In this paper, we propose a novel method for monitoring mood trend of Twitter users by analyzing their daily tweets for a long period. Then, to more accurately understand their tweets, we analyze all types of content in tweets, i.e., texts and emoticons, and images, thus develop a multimodal sentiment analysis method. In the proposed method, two single-modal analyses first are performed to extract the users' moods hidden in texts and images: a lexicon-based and learning-based text classifier and a learning-based image classifier. Thereafter, the extracted moods from the respective analyses are combined into a tweet mood and aggregated a daily mood. As a result, the proposed method generates a user daily mood flow graph, which allows us for monitoring the mood trend of users more intuitively. For evaluation, we perform two sets of experiment. First, we collect the data sets of 40,447 data. We evaluate our method via comparing the state-of-the-art techniques. In our experiments, we demonstrate that the proposed multimodal analysis method outperforms other baselines and our own methods using text-based tweets or images only. Furthermore, to evaluate the potential of the proposed method in monitoring users' mood trend, we tested the proposed method with 40 depressive users and 40 normal users. It proves that the proposed method can be effectively used in finding depressed users.

• Communications of Mathematical Education
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• v.27 no.4
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• pp.547-566
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• 2013

Education, Science and Technology Department in January 2012, announced the advancement of mathematics education scheme. Select a textbook of storytelling method in policy by this, it is easy to understand the math, and that you can learn happily, was fabricated and spread. In this study, we selected three of the textbook that describes the set to its characteristics the application of storytelling in a textbook of mathematics 13 different middle school that will be used from March 2013. And of research that the textbook is to analyze the reflected reality of storytelling that is part of the advancement scheme of mathematics education content and direction and basic curriculum of current. View by presenting instead I is an object of the present invention. Six components of storytelling in the teaching and learning context that is proposed in the Park's study (2012) are used to analyze. Those are 'Persona', 'empathy', 'analogy', 'aesthetic experience ', 'plot' and 'time'. The data were analyzed storytelling was used to introduce the nature and mathematical concepts in math textbook based on these elements 6. That is looking at the ratio of the presence or absence of reflecting elements of storytelling on teaching and learning context that the data storytelling meets much the elements of storytelling to investigate the characteristics of each textbook. It is expected to provide the information and resources needed to develop methods and materials that can be studied to be interested in conjunction with real life mathematics as a result of this study.

• Journal of The Korean Association of Information Education
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• v.13 no.3
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• pp.383-391
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• 2009

The goal of cyber teaching is to reduce the cost of private lessons, dissipate the educational disparity amongst regions, make classes apt to the given level of every group of students, make up for systematic defects of the public education, and ultimately strengthen its role. This study intends to analyze the capabilities of cyber teachers and clarify their qualifications, as the whole new e-Learning system is about to take root. In this study, the activities of cyber teachers are analyzed and some standards of applicability of cyber teachers, or the so-called ISSCT, are presented. Firstly, the activities are divided into teaching, counselling, process management, development of professionality. Based upon these four activities, nine tasks have been formed and the structure of 22 sub-tasks has been completed. This is the way the standards of applicability of cyber teachers are established in consideration with their activities. Secondly, the standards of information capability of cyber teachers have 53 elements in total, and the aforementioned ISSCT are presented in relation to the ISST, based upon the standards of information capability of cyber teachers.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1077-1093
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• 2020

Sea Surface Temperature (SST) is an important environmental indicator that affects climate coupling systems around the world. In particular, coastal regions suffer from abnormal SST resulting in huge socio-economic damage. This study used Long Short Term Memory (LSTM) and Convolutional Long Short Term Memory (ConvLSTM) to predict SST up to 7 days in the south sea region in South Korea. The results showed that the ConvLSTM model outperformed the LSTM model, resulting in a root mean square error (RMSE) of 0.33℃ and a mean difference of -0.0098℃. Seasonal comparison also showed the superiority of ConvLSTM to LSTM for all seasons. However, in summer, the prediction accuracy for both models with all lead times dramatically decreased, resulting in RMSEs of 0.48℃ and 0.27℃ for LSTM and ConvLSTM, respectively. This study also examined the prediction of abnormally high SST based on three ocean heatwave categories (i.e., warning, caution, and attention) with the lead time from one to seven days for an ocean heatwave case in summer 2017. ConvLSTM was able to successfully predict ocean heatwave five days in advance.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.5
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• pp.277-283
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• 2016

Tetrapod is one of the most widely used concrete armor units for rubble mound breakwaters. The calculation of the stability number of Tetrapods is necessary to determine the optimal weight of Tetrapods. Many empirical formulas have been developed to calculate the stability number of Tetrapods, from the Hudson formula in 1950s to the recent one developed by Suh and Kang. They were developed by using the regression analysis to determine the coefficients of an assumed formula using the experimental data. Recently, software engineering (or machine learning) methods are introduced as a large amount of experimental data becomes available, e.g. artificial neural network (ANN) models for rock armors. However, these methods are seldom used probably because they did not significantly improve the accuracy compared with the empirical formula and/or the engineers are not familiar with them. In this study, we propose an explicit method to calculate the stability number of Tetrapods using the weights and biases of an ANN model. This method can be used by an engineer who has basic knowledge of matrix operation without requiring knowledge of ANN, and it is more accurate than previous empirical formulas.

• Journal of Elementary Mathematics Education in Korea
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• v.14 no.1
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• pp.153-176
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• 2010

The purpose of this study is to rethink the importance of manipulative materials and to extract of manipulative materials program and its application methods. Activity, construction, and operation is stressed in the elementary mathematics. For this, various technological tools and manipulative materials is emphasized in mathematics teaching-learning methods. Applications of manipulative materials in the elementary mathematics is gradually increased together with curriculum revisions and textbook developments. As a result, tangram, geo-board etc., many tools ate introduces to school mathematics. This study is executed in this contexts. To achieve this, We introduce Australian 'Maths With Attitude' program. This program is composed of the primary level and secondary level. Each level consists of four domains - Number & Computation, Space & Logic, Chance & Measurement, Pattern & Algebra -, and each domains is made up of 20 tasks(i.e. manipulative materials) and programs. This study takes the focus to 5-6 grades programs in the mid of the primary level. First, We introduce 'Monkeys & Bananas'(Number & Computation) and 'Triangles & Colours' (Pattern & Algebra) tasks, and investigate the examples of lessons using these tasks. Second, We think the probability of these tasks' application and draw examples in the elementary mathematic textbooks. Through this works, We respect teaching-learning methods is rich and various in the elementary mathematics lessons.

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.270-277
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• 2002

Text filtering is a task of deciding whether a document has relevance to a specified topic. As Internet and Web becomes wide-spread and the number of documents delivered by e-mail explosively grows the importance of text filtering increases as well. The aim of this paper is to improve the accuracy of text filtering systems by using machine learning techniques. We apply AdaBoost algorithms to the filtering task. An AdaBoost algorithm generates and combines a series of simple hypotheses. Each of the hypotheses decides the relevance of a document to a topic on the basis of whether or not the document includes a certain word. We begin with an existing AdaBoost algorithm which uses weak hypotheses with their output of 1 or -1. Then we extend the algorithm to use weak hypotheses with real-valued outputs which was proposed recently to improve error reduction rates and final filtering performance. Next, we attempt to achieve further improvement in the AdaBoost's performance by first setting weights randomly according to the continuous Poisson distribution, executing AdaBoost, repeating these steps several times, and then combining all the hypotheses learned. This has the effect of mitigating the ovefitting problem which may occur when learning from a small number of data. Experiments have been performed on the real document collections used in TREC-8, a well-established text retrieval contest. This dataset includes Financial Times articles from 1992 to 1994. The experimental results show that AdaBoost with real-valued hypotheses outperforms AdaBoost with binary-valued hypotheses, and that AdaBoost iterated with random weights further improves filtering accuracy. Comparison results of all the participants of the TREC-8 filtering task are also provided.

• Journal of the Korean Geographical Society
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• v.51 no.6
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• pp.893-914
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• 2016

This paper describes the development of an inquiry-based fieldwork program based on Yangdong village where students explore the ways that it can develop in a sustainable way. Important considerations in an inquiry-based fieldwork design include what the key inquiry questions should be, the geographical issues of fieldwork location, the potential roles of mobile technologies, design of learning activities and a final product, and the roles of a teacher. Student fieldwork activities, including mapping land-use changes at the building level, detecting what should be changed or remain the same, and conducting interview with residents to examine their perceptions of overall tourism impacts, are supported by mobile technologies (i.e., the Collector for ArcGIS and the Google Forms). Twenty one high school students participated in a field test of the program in February 2016, which allowed authors to evaluate the program. Students' pre-, in-, and post-fieldwork activities were observed and the data and final products which they gathered and producted were analyzed. The post-program survey indicated that the students deepened and expanded their understanding of Yangdong village and expressed their satisfaction with the program in general. Incorporating mobile technologies into inquiry-based geographical fieldwork can help students involved in collaborative problem solving and creative activities in real world settings and create a shareable multimodal product combining maps, photo, and text.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.169-177
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• 2020

In South Korea, the results of R&D in science and technology are submitted to the National Science and Technology Information Service (NTIS) in reports that have Korea national science and technology standard classification codes (K-NSCC). However, considering there are more than 2000 sub-categories, it is non-trivial to choose correct classification codes without a clear understanding of the K-NSCC. In addition, there are few cases of automatic document classification research based on the K-NSCC, and there are no training data in the public domain. To the best of our knowledge, this study is the first attempt to build a highly performing K-NSCC classification system based on NTIS report meta-information from the last five years (2013-2017). To this end, about 210 mid-level categories were selected, and we conducted preprocessing considering the characteristics of research report metadata. More specifically, we propose a convolutional neural network (CNN) technique using only task names and keywords, which are the most influential fields. The proposed model is compared with several machine learning methods (e.g., the linear support vector classifier, CNN, gated recurrent unit, etc.) that show good performance in text classification, and that have a performance advantage of 1% to 7% based on a top-three F1 score.

• Journal of Life Science
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• v.26 no.7
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• pp.812-818
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• 2016

The aim of this study was to investigate the anti-amnesic effect of Stachys sieboldii MIQ. according to the mixing ratio of calcium on scopolamine-induced learning and memory impairment, in vivo. At the end of the adaptation period, SD rats were divided into a normal group (N), a control group (C: scopolamine), a positive control group (PC: scopolamine + tacrine), and a sample group (S: scopolamine + Stachys sieboldii MIQ., 1CS: scopolamine + low calcium-mixed Stachys sieboldii MIQ., 5CS: scopolamine + high calcium-mixed Stachys sieboldii MIQ.), and were tested with learning and memory tests. The C and CS groups were found to have a decreased scopolamine-induced memory deficit in the Y-maze and water maze tests. Brain tissue analysis showed that the CS group decreased acetylcholinesterase (AChE) activity and increased acetylcholine (Ach) content, both of which are indicative of neuronal cell activity. From a light microscopy study, the nucleus of neurons in the hippocampus of the brain was more shrunken or condensed in the C group compared to the CS group. In the CS group, the damage to the neurons in the hippocampus of the brain was suppressed. These results suggest that Stachys sieboldii MIQ. according to the mixing ratio of calcium provides a significant anti-amnesic effect against scopolamine-induced cholinergic system deficits and cognitive impairment.