• Journal of the Korean School Mathematics Society
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• v.22 no.3
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• pp.241-256
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• 2019

In this paper, we analyzed the types of tasks presented in the 'Probability and Statistics' textbooks and how the cognitive competences required to perform the tasks provide students with opportunity-to-learn. To this end, the analysis of the 9 books of the 'Probability and Statistics' test textbooks according to the 2015 revised mathematics curriculum showed that the context-based tasks(CF type, RE type) ranged from 67.5% to 78.0% of the total number of tasks in each textbook, but the ratio of relevant and essential tasks related to real life is from 0.4% to 2.0%, it was found that most of the context-based tasks presented in the textbooks were disguised as real life materials. The cognitive competences of context-based tasks ranged from 29.6% to 50.0% in reproduction category, from 33.8% to 54.3% in connection category, and from 8.8% to 20.0% in reflection category. As a result, there was not enough opportunity-to-learn for students to experience reflective cognitive processes.

• International Journal of Contents
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• v.15 no.3
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• pp.32-38
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• 2019

We usually suffer from difficulties in treating or managing Big Data generated from various digital media and/or sensors using traditional mining techniques. Additionally, there are many problems relative to the lack of memory and the burden of the learning curve, etc. in an increasing capacity of large volumes of text when new data are continuously accumulated because we ineffectively analyze total data including data previously analyzed and collected. In this paper, we propose a general-purpose classifier and its structure to solve these problems. We depart from the current feature-reduction methods and introduce a new scheme that only adopts changed elements when new features are partially accumulated in this free-style learning environment. The incremental learning module built from a gradually progressive formation learns only changed parts of data without any re-processing of current accumulations while traditional methods re-learn total data for every adding or changing of data. Additionally, users can freely merge new data with previous data throughout the resource management procedure whenever re-learning is needed. At the end of this paper, we confirm a good performance of this method in data processing based on the Big Data environment throughout an analysis because of its learning efficiency. Also, comparing this algorithm with those of NB and SVM, we can achieve an accuracy of approximately 95% in all three models. We expect that our method will be a viable substitute for high performance and accuracy relative to large computing systems for Big Data analysis using a PC cluster environment.

• International Journal of Advanced Culture Technology
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• v.8 no.2
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• pp.209-215
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• 2020

Russia has an interesting history as a donor, recipient and re-emerging donor in international development assistance (IDA). This article introduces the history, policy and challenges of Russian IDA, and provides suggestions for such challenges. The main barrier to Russian IDA is the absence of a central government agency and Russia can learn from other country's experience. Concerning lack of data on the provision of assistance to each sector of IDA and the large number of recipient countries, Russia can learn from Korea particularly in education sector. With respect to building a system ensuring the efficiency of the Russian IDA works, a tool for analysis of the effect of the Russian IDA programmes may be drawn in consultation with international institutions or successful programmes of other donor countries.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.891-902
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• 2020

The Re-Identification(Re-ID) is one of the most popular researches in the field of computer vision due to a variety of applications. To achieve a high-level re-identification performance, recently other methods have developed the deep learning based networks that are specialized for only person or vehicle. However, most of the current methods are difficult to be used in real-world applications that require re-identification of both person and vehicle at the same time. To overcome this limitation, this paper proposes a deep neural network learning method that combines triplet and softmax loss to improve performance and re-identify people and vehicles simultaneously. It's possible to learn the detailed difference between the identities(IDs) by combining the softmax loss with the triplet loss. In addition, weights are devised to avoid bias in one-side loss when combining. We used Market-1501 and DukeMTMC-reID datasets, which are frequently used to evaluate person re-identification experiments. Moreover, the vehicle re-identification experiment was evaluated by using VeRi-776 and VehicleID datasets. Since the proposed method does not designed for a neural network specialized for a specific object, it can re-identify simultaneously both person and vehicle. To demonstrate this, an experiment was performed by using a person and vehicle re-identification dataset together.

• Journal of Korean Home Economics Education Association
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• v.9 no.1
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• pp.19-37
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• 1997

The aim of this study is to research and analyse how junior-high students, both male and female in Inchon area, are recognizing the contents of the curriculum in the subject of home economics and how effectively they are learning and applying it in their actual life. 772 students, both male and female, who started to learn the subject of home economics from the 7th grade as compulsory are the respondents, and the survey is done by using questionnaire. The result shows that after taking the course of home economics, both male and female students have got more positive view on the necessity of learning the subject. But still, on the whole, female students are more intersted and more active than males the subject in learning. As for food and nutrition part, large percentage of the respondents, both male and female, answer that it is very helpful. They tend to be on more balanced diet and when they purchase food or when they eat at restaurant they refer what they learn about nutrition at school more often than not. A number of the students are re-practicing cooking at home after they learn it at school. Also the fact in the survey shows that more and more mothers are getting active in asking their children to re-practice cooking. One of the difficulties for male students to take the course is stereo-typed thinking on the separate role of man and woman in the family. But many of them started cooking some food, even though it is very simple, and the survey shows that their interest in nutrition and health increased after they were initiated into this course.

• The Korean Journal of Emergency Medical Services
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• v.5 no.1
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• pp.73-88
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• 2001

Post these safety tips in any swimming area for all swimmers to read. 1. Always swim with companions. Swim only in area well supervised by lifeguards. 2. Never drink alcohol or use drugs when you're swimming or boating. 3. Always check the water depth. Walk in from shore or ease in from the dock or the edge of the pool. 4. Know the limits of your own swimming abilities. If you're a good swimmer, don't tempt nonswimmers or beginner swimmers to try to keep up with you. 5. Keep any eye on younger swimmers at all times. 6. Learn the proper way to dive in the water safely. Follow guidelines for safe diving. 7. Follow the lifeguards instructions and respect their judgment. Never fake an Emergency. Obey all swimming rules.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.323-332
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• 2005

In this Paper, we design and implement an e-Learning system with dynamic learning contents Providing and re-time assignment system. The learner can select the dynamic learning contents Providing environments with test and Quiz Phase according to the learners' characters and interest to improve the learning effects. Also, we develop the real-time assignment system which is composed of multiple choice and essay test and can provide the interaction between teacher and learner immediately.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.522-531
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• 2021

We describe a new deep learning model - Convolutional eXtreme Gradient Boosting (ConvXGB) for classification problems based on convolutional neural nets and Chen et al.'s XGBoost. As well as image data, ConvXGB also supports the general classification problems, with a data preprocessing module. ConvXGB consists of several stacked convolutional layers to learn the features of the input and is able to learn features automatically, followed by XGBoost in the last layer for predicting the class labels. The ConvXGB model is simplified by reducing the number of parameters under appropriate conditions, since it is not necessary re-adjust the weight values in a back propagation cycle. Experiments on several data sets from UCL Repository, including images and general data sets, showed that our model handled the classification problems, for all the tested data sets, slightly better than CNN and XGBoost alone and was sometimes significantly better.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.135-141
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• 2019

Recently, there has been active researches about building an artificial intelligence agent that can learn how to play a game by using re-enforcement learning. The performance of the learning can be diverse according to what kinds of deep learning activation functions they used when they train the agent. This paper compares the activation functions when we train our agent for learning how to play a 2D shooting game by using re-enforcement learning. We defined performance metrics to analyze the results and plotted them along a training time. As a result, we found ELU (Exponential Linear Unit) with a parameter 1.0 achieved best rewards than other activation functions. There was 23.6% gap between the best activation function and the worst activation function.

• Journal of architectural history
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• v.2 no.1 s.3
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• pp.126-135
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• 1993

Italian Rationalism held a specific position in the Modern Movements of Architecture, due to the fact that Italian Rationalism could not totally escape from the classical tradition of Italy. Until the seventies, Italian Rationalism had been criticized for having made no contribution to the progressive aspects of the Modern Movements owing to the very keeping of tradition. After the seventies, however, there emerged a movement which tries to reinterprete the Modern Movements of Architecture in relation to tradition and under this new situation, Italian Rationalism is believed to have a historical possibility of unifying tradition with modernity. This study is to show how Italian Rationalism struggled with the issue of tradition, why Italian Rationalism was under-evaluated and which historic lesson we can learn from it in the contemporary days of the revivalistic Post-Modernism.