• Journal of Digital Convergence
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• v.17 no.1
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• pp.43-53
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• 2019

This study has explored the trajectory of the development and diffusion of the CTLs in the Korean universities by using isomorphism theory of neo-institutionalism. Neo-institutional theorists believe that organizational structure and behavior reflects the norms and values recognized in the society rather than the organization's autonomous and rational choices. Based on the isomorphism framework, the introduction and diffusion of the CTLs in the Korean universities have been led by the government. In addition, the CTLS(Korean Association of Center for Teaching & Learning) has served as a direct basis for the normative pressures. In other words, the CTLs have been securing devices for the universities to acquire external justification by the environment, and they have been able to confirm that the system was isomorphed, in particular by meeting and agreeing with the government-set university evaluation criteria. Efforts should be made to develop unique values and strategies that enable CTLs to become engines of the development of university education in response to rapid changes in the academic environment.

• Journal of the Korean Geographical Society
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• v.37 no.2
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• pp.177-190
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• 2002

In this article, I intended to develop the contents of regional learning in social studies and in geography education. In achieving the goal of regional teaming, we have to investigate three facets, i .e. theoretical, organizational, and practical facet. In particular, practical facet is very important one in that it is directly related to content development. As the criteria of content constitution, I proposed two elements, 'historical-geographical landscape'and 'region-related discourse' which are pertinent to the case region, Yonsan in Chungcheongnam-do, Korea. And then, on the basis of disciplinary results in geography, I developed the scope and sequence of contents by utilizing three lagers of space which are 'habitat space', 'social space', and 'power space', three geographical concepts of 'site→symbolic landscape→territoriality', and three spatial scales of 'local→inter-local →regional one'correspondingly.

• Archives of design research
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• v.14
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• pp.43-51
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• 1996

To analyze the design education of elementary school in the united states, the content of Discover art, one of the popular art textbooks for elementary school student, has been examined. Focusing on the developmental stage and sequential curriculum across all grades, design principles, color and criteria of design are investigated. The subjects studied are as follows: an introduction of new word or concept of design principles and color, repetition of the learning, the number of color taught, looking at products of design and making design at each grade level. The curriculum of design principles is well composed, but line, shape and form parts are redundant throughout all grades. The learning order of the color at one grade is well organized but the repetition is too much. The portion of design part is too small. It is adequate that the history of design is introduced at grade 5 where children start to learn history. However, it should be more strengthened for the continuous development of design ability. Looking at product design is introduced before grade 4, and making product design is taught just once at grade 4, although sequential learning is necessary in late elementary grades.

• Journal of Educational Research in Mathematics
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• v.12 no.1
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• pp.145-162
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• 2002

In this study, on the basis of the seventh national mathematics curriculum, the achievement standards were developed to specify the objectives and contents of teaching-learning and the assessment standards were also developed to differentiate students' levels of achievement at school mathematics. The achievement standards were developed on the following guidelines; 1) to present the minimum standards based on the national curriculum, 2) to develop the standards based on the order of curriculum, 3) to suggest the minimum but ultimate achievement target, 4) to comprise not only of the intellectual but also of psychological spheres such as knowledge, function, attitude, aptitude, etc., and 5) to suggest the standards comprehensively and concretely. The standards were developed on the basis of the middle areas of contents of the curriculum in order not to be too comprehensive, nor to be too detailed. Learning activities, on the other hand, were provided for the assistance of instructions with emphasis on creativity rather than on the routine instruction. The assessment standards were established based on the following principles; 1) to establish the assessment methods, contents, and situations which are to be used for assessment, 2) to establish the criteria of classifying the assessed into the upper, intermediate and lower levels, 3) to develop the assessment standards in a proportionate balance to achievement standards, 4) to establish the intermediate level as a standard, and 5) to establish the minimum level in the contents, concepts, values and attitudes of basic learning. This study also suggested the exemplary test items including short-answer and open-ended questions while putting emphasis on students' real performance to increase their ability in solving problems rather than in calculating. In addition to the test items, it introduced the grading system developed to grade the items with concrete guidelines and to report students' achievement on doing mathematics.

• The Journal of Korean Association of Computer Education
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• v.8 no.6
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• pp.45-53
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• 2005

In this paper, we propose an improved method of differentiated curriculum in social studies class that can be immediately used in the class. There are two major reasons that differentiated curriculum has not been applied to actual educational programs. One reason is the inefficient progress of differentiated curriculum derived from students' self-study based on individual projects and teacher's excessive investment of time in the development and management of individual researches. The other attribute is the difficulty in distinguishing students' academic level due to the lake of distinct criteria, because students are classified into merely two groups, in-depth group and supplementary class. To cope with these problems, we adopted a cooperative learning to enhance the educational effect of students of the similar level. Experimental results validate that the proposed method is effective in the course of social studies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.63-77
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• 2023

This study applies reinforcement learning to effectively operate expressway hard shoulder running (HSR). An HSR algorithm was developed, and its effectiveness was evaluated using the VISSIM microscopic simulation program. The simulation evaluated two aspects: mobility and safety. The DQN-based HSR algorithm found speed improvement of up to 26 km/h. Compared to the current method, the difference in the number of conflicts was not significant. Considering the results, a DQN-based HSR operation has a clear effect, and it is necessary to consider adjusting the current operational criteria.

• Journal of Information Technology Services
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• v.12 no.3
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• pp.273-287
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• 2013

The objective of this study is to empirically develop performance evaluation measures for LIS (logistics information systems) based upon BSC (balanced scorecard) model and determine the relative importance among four perspectives of BSC using AHP (analytic hierarchy process) methodology. Above all, forty nine probable measures for evaluating LIS performance were identified through reviewing the previous research related with SCM (supply chain management), logistics management, and information systems evaluation. And then, these probable measures were examined by means of coincidence analyses using three mutually exclusive criteria(validity of content, ease of measurement and reliability of measurement). Data for conducting the coincidence analyses were collected from LIS users and LIS development personnel. As the results of the coincidence analyses, it was found that 31 ones among 49 probable performance evaluation measures theoretically derived could be qualified for LIS performance evaluation. And AHP analysis showed that the weight of each perspective was respectively as follows : 46.8% for financial perspective, 31.3% for customer perspective, 14.8% for internal business process perspective, and 7.1% for learning and growth perspective. The academic contribution of this study is that performance evaluation measures for LIS could be systematically and empirically developed on the basis of BSC. Also, the results of this study are expected to be used as a practice guideline of evaluating and improving LIS.

• Korean Journal of Radiology
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• v.22 no.3
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• pp.344-353
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• 2021

Objective: The mitotic count of gastrointestinal stromal tumors (GIST) is closely associated with the risk of planting and metastasis. The purpose of this study was to develop a predictive model for the mitotic index of local primary GIST, based on deep learning algorithm. Materials and Methods: Abdominal contrast-enhanced CT images of 148 pathologically confirmed GIST cases were retrospectively collected for the development of a deep learning classification algorithm. The areas of GIST masses on the CT images were retrospectively labelled by an experienced radiologist. The postoperative pathological mitotic count was considered as the gold standard (high mitotic count, > 5/50 high-power fields [HPFs]; low mitotic count, ≤ 5/50 HPFs). A binary classification model was trained on the basis of the VGG16 convolutional neural network, using the CT images with the training set (n = 108), validation set (n = 20), and the test set (n = 20). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated at both, the image level and the patient level. The receiver operating characteristic curves were generated on the basis of the model prediction results and the area under curves (AUCs) were calculated. The risk categories of the tumors were predicted according to the Armed Forces Institute of Pathology criteria. Results: At the image level, the classification prediction results of the mitotic counts in the test cohort were as follows: sensitivity 85.7% (95% confidence interval [CI]: 0.834-0.877), specificity 67.5% (95% CI: 0.636-0.712), PPV 82.1% (95% CI: 0.797-0.843), NPV 73.0% (95% CI: 0.691-0.766), and AUC 0.771 (95% CI: 0.750-0.791). At the patient level, the classification prediction results in the test cohort were as follows: sensitivity 90.0% (95% CI: 0.541-0.995), specificity 70.0% (95% CI: 0.354-0.919), PPV 75.0% (95% CI: 0.428-0.933), NPV 87.5% (95% CI: 0.467-0.993), and AUC 0.800 (95% CI: 0.563-0.943). Conclusion: We developed and preliminarily verified the GIST mitotic count binary prediction model, based on the VGG convolutional neural network. The model displayed a good predictive performance.

• 대한공업교육학회지
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• v.38 no.2
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• pp.89-113
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• 2013

The study started from the point that learners should be basically equipped to quickly respond to changes in demand for future human resources efficiently and effectively, and an attitude to take part in learning voluntarily should thus be cultivated. To this end, the author applied the TAI model based on a module as a class strategy to solve problems related to several classes occurred in specialized high schools. This application of the TAI model was also motivated by the necessity for designing an appropriate teaching-learning method that encourages improvement of self-learning capacity, consistent learning motivation, and willingness rather than external factors. Through this work, the author aims to heighten the interest of learners and improve endurance in learning. The study results are as follows. First, the learning unit was structuralized as a module and then learning stages were proceeded with so that capacity to adapt to learning would improve. The achievement standard (learning goal) was structuralized in a module type by analyzing and reorganizing the textbook considering the link between the actual practice field and a curriculum based on subject characteristics. Through the process of module type learning stages, the student's capacity to ascertain characteristics of units and to adapt to learning both improved. Second, through application of a TAI model based on a module, Self-Directed Learning capacity and capacity to adapt to a new field improved. By applying the module, Self-Directed Learning could be accomplished more effectively than in the existing passive learning environment. By grafting cooperative learning of the TAI model, students had greater interest and achievement in classes, self-confidence and community consciousness, and an opportunity to broaden their thinking. In particular, improvement of self-confidence is effective in cultivating the capacity required in industrial society to transcend the learning of simple functions and knowledge, as well as the capacity to adapt to new environments. Third, by solving tasks focused on fields related to industrial sites, not only actual survey capacity but also additional capacity to identify and solve tasks through various experiences improved. Furthermore, it was helpful for students to have interest and motivation about their own life and learning to cultivate the qualities and capacity to adapt to the working world where new knowledge and technology rapidly change. Fourth, by applying a standard-based assessment system for technical subjects introduced in 2012 to model design for learning plans, clearer and more objective assessment criteria were arranged, and individual learning through instruction at each achievement level could be accomplished. This improved achievement level of individual learners was helpful in reaching achievement goals at specific levels by overcoming the disadvantages of cooperative learning in each group.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.1-17
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• 2017

The deep learning framework is software designed to help develop deep learning models. Some of its important functions include "automatic differentiation" and "utilization of GPU". The list of popular deep learning framework includes Caffe (BVLC) and Theano (University of Montreal). And recently, Microsoft's deep learning framework, Microsoft Cognitive Toolkit, was released as open-source license, following Google's Tensorflow a year earlier. The early deep learning frameworks have been developed mainly for research at universities. Beginning with the inception of Tensorflow, however, it seems that companies such as Microsoft and Facebook have started to join the competition of framework development. Given the trend, Google and other companies are expected to continue investing in the deep learning framework to bring forward the initiative in the artificial intelligence business. From this point of view, we think it is a good time to compare some of deep learning frameworks. So we compare three deep learning frameworks which can be used as a Python library. Those are Google's Tensorflow, Microsoft's CNTK, and Theano which is sort of a predecessor of the preceding two. The most common and important function of deep learning frameworks is the ability to perform automatic differentiation. Basically all the mathematical expressions of deep learning models can be represented as computational graphs, which consist of nodes and edges. Partial derivatives on each edge of a computational graph can then be obtained. With the partial derivatives, we can let software compute differentiation of any node with respect to any variable by utilizing chain rule of Calculus. First of all, the convenience of coding is in the order of CNTK, Tensorflow, and Theano. The criterion is simply based on the lengths of the codes and the learning curve and the ease of coding are not the main concern. According to the criteria, Theano was the most difficult to implement with, and CNTK and Tensorflow were somewhat easier. With Tensorflow, we need to define weight variables and biases explicitly. The reason that CNTK and Tensorflow are easier to implement with is that those frameworks provide us with more abstraction than Theano. We, however, need to mention that low-level coding is not always bad. It gives us flexibility of coding. With the low-level coding such as in Theano, we can implement and test any new deep learning models or any new search methods that we can think of. The assessment of the execution speed of each framework is that there is not meaningful difference. According to the experiment, execution speeds of Theano and Tensorflow are very similar, although the experiment was limited to a CNN model. In the case of CNTK, the experimental environment was not maintained as the same. The code written in CNTK has to be run in PC environment without GPU where codes execute as much as 50 times slower than with GPU. But we concluded that the difference of execution speed was within the range of variation caused by the different hardware setup. In this study, we compared three types of deep learning framework: Theano, Tensorflow, and CNTK. According to Wikipedia, there are 12 available deep learning frameworks. And 15 different attributes differentiate each framework. Some of the important attributes would include interface language (Python, C ++, Java, etc.) and the availability of libraries on various deep learning models such as CNN, RNN, DBN, and etc. And if a user implements a large scale deep learning model, it will also be important to support multiple GPU or multiple servers. Also, if you are learning the deep learning model, it would also be important if there are enough examples and references.