• Journal of the Korean association of regional geographers
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• v.2 no.2
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• pp.75-92
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• 1996

Geography education is one of the best ways to improve the understanding of other countries. By analyzing Korean and Japanese textbooks on world geography, I tried to find out how well they explain the other country and to set forth guiding principles for geography education. To achieve these aims, weight analysis are used. The major findings in this study can be summarised as follow. The contents of Korean and Japanese geography textbooks were analyzed deviding into 2 major topics, 6 minor topics, and 20 key concepts. (1) By analyzing Korean geography textbook of the 5th curriculum the weight percentages which had been given to each minor topics were found. They are as follow: resource problem(57.7%), human right problem(21.4%), population problem (9.0%), mutual dependence(6.0%), environmental problem(3.3%), international competition(2.6%). (2) By analyzing Korean geography text-book of the 6th curriculum the weight percentages which had been give to each minor topics were found. They are as follow: resource problem(42.7%), human right problem(21.7%), mutual dependence (20.9%), environmental problem(7.7%), population problem(4.6%), international competition(2.4%) (3) By analyzing Japanise geography text-book of 5th curriculum ammendment the weight percentages which had been give to each minor topics were found. They are as follows: resource problem(49.9%) human right problem(21.7%), mutual dependence(15.5%), population problem (7.1%), international competition(6.2%), environmental problem(3.8%) (4) By analyzing Japanise geography textbook of 6th curriculum ammendment the weight percentages which had been give to each minor topics were found. They are as follows human right problem (31.6%), mutual dependence(22.8%), resource problem(20.7%), population problem(12.7%), environmental problem(8.6%), international competition(3.6%). We can see that in the field of dependence Korea and Japan put the similar weight but in the field of common problem they put the fairly different weight. It can be viewed as the difference of curriculum. That is to say Korea used both the systematic method on the basis of unit but Japan used only topical method on the basis of unit. Therefore Korean geography textbook introduce agriculture, forestry, fishery, mining industry and manufacturing industry. Japanese textbook, however gives a detailed account about residents' lives in specific area. For that reason in Korean textbook, resource was stressed, while in Japanese textbook, culture was stressed.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.3
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• pp.145-154
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• 2016

Because of the recent interest in the u-Health and development of IT technology, a need of utilizing a medical information data has been increased. Among previous studies that utilize various data mining algorithms for processing medical information data, there are studies of association rule analysis. In the studies, an association between the symptoms with specified diseases is the target to discover, however, infrequent terms which can be important information for a disease diagnosis are not considered in most cases. In this paper, we proposed a new association rule mining system considering the importance of each term using TF-IDF weight to consider infrequent but important items. In addition, the proposed system can predict candidate diagnoses from medical text records using term similarity analysis based on medical ontology.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.3
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• pp.457-488
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• 2015

In this study, we analyzed the current research state of Library and Information science in top 20 journals from 1990 to 2015, in subject and method perspectives. We developed weighted subject-method network to investigate on centralities of a subject and a method as well as their relations. This network is composed of subject nodes and method nodes and gives a weight on each node by topic occurrence. As a result, for 25 years, management information system, information need analysis, bibliometrics, information policy were top topics. Modeling, literature review, scientific research impact analysis, web data analysis were top methods. A recent rise of text mining is highlighted. We also analyzed communities made from the past 25 years and the recent 5 years. Bibliometrics is extending its field by applying various network analyzing algorithms. Text mining is specialized in medical information system and user interface. This result identifies the interests of excellent studies in Library and Information Science. It also can be fundamental resource for the development of Library and Information Science.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.1
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• pp.49-55
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• 2013

In this paper, we proposed a good classifier to match different spatial data sets by applying evaluation of classifiers performance in data mining and biometrics. For this, we calculated distances between a pair of candidate features for matching criteria, and normalized the distances by Min-Max method and Tanh (TH) method. We defined classifiers that shape similarity is derived from fusion of these similarities by CRiteria Importance Through Intercriteria correlation (CRITIC) method, Matcher Weighting method and Simple Sum (SS) method. As results of evaluation of classifiers performance by Precision-Recall (PR) curve and area under the PR curve (AUC-PR), we confirmed that value of AUC-PR in a classifier of TH normalization and SS method is 0.893 and the value is the highest. Therefore, to match different spatial data sets, we thought that it is appropriate to a classifier that distances of matching criteria are normalized by TH method and shape similarity is calculated by SS method.

• Geomechanics and Engineering
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• v.22 no.3
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• pp.197-206
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• 2020

Reutilization of solid waste such as Tire Derived Aggregate (TDA) and mixing it with soft soil for backfill material not only reduces the required volume of backfill soil (i.e., sand-mining procedures; reinforcement), but also preserves the environment from pollution by recycling. TDA is a widely-used material that has a good track record for improving sustainable construction. This paper attempted to investigate the performance of Kaolin-TDA mixtures as a backfill material underneath a strip footing and close to a retaining wall. For this purpose, different types of TDA i.e., powdery, shredded, small-size granular (1-4 mm) and large-size granular (5-8 mm), were mixed with Kaolin at 0, 20, 40, and 60% by weight. Static surcharge load with the rate of 10 kPa per min was applied on the strip footing until the failure of footing happened. The behaviour of samples K80-G (1-4 mm) 20 and K80-G (5-8 mm) 20 were identical to that of pure Kaolin, except that the maximum footing stress had grown by roughly three times (300-310 kPa). Therefore, it can be concluded that the total flexibility of the backfill and shear strength of the strip footing have been increased by adding the TDA. The results indicate that, a significant increase in the failure vertical stress of the footing is observed at the optimum mixture content. In addition, the TDA increases the elasticity behaviour of the backfill.

• Geomechanics and Engineering
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• v.13 no.1
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• pp.141-159
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• 2017

A pick cutter is a rock-cutting tool used in partial-face excavation machines such as roadheaders, and its quality is a key element influencing the excavation performance and efficiency of such machines. In this study, pick cutters with hardfacing deposits applied to a tungsten carbide insert were made with aim of increasing their durability and wear resistance. They were field-tested by being installed in a roadheader and compared with conventional pick cutters under the same excavation conditions for 24 hours. The hardfaced pick cutters showed much smaller weight loss after excavation, and therefore better excavation performance, than the conventional pick cutters. In particular, the damage to and detachment (loss) of tungsten carbide inserts was minimal in the hardfaced pick cutters. A detailed inspection using scanning electron microscope-energy dispersive X-ray spectrometry and three-dimensional X-ray computed tomography scanning revealed no macro- or micro-cracks in the pick cutters. The reason for the absence of cracks may be that the heads of pick cutters are mechanically worn after the tungsten carbide inserts have been worn and damaged. However, scanning revealed the presence of voids between tungsten carbide inserts and pick cutter heads. This discovery of voids indicates the need to improve production processes in order to guarantee a higher quality of pick cutters.

• Physical Therapy Korea
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• v.27 no.2
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• pp.140-148
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• 2020

Background: Scapular winging (SW) could be caused by tightness or weakness of the periscapular muscles. Although data mining techniques are useful in classifying or predicting risk of musculoskeletal disorder, predictive models for risk of musculoskeletal disorder using the results of clinical test or quantitative data are scarce. Objects: This study aimed to (1) investigate the difference between young women with and without SW, (2) establish a predictive model for presence of SW, and (3) determine the cutoff value of each variable for predicting the risk of SW using the decision tree method. Methods: Fifty young female subjects participated in this study. To classify the presence of SW as the outcome variable, scapular protractor strength, elbow flexor strength, shoulder internal rotation, and whether the scapula is in the dominant or nondominant side were determined. Results: The classification tree selected scapular protractor strength, shoulder internal rotation range of motion, and whether the scapula is in the dominant or nondominant side as predictor variables. The classification tree model correctly classified 78.79% (p = 0.02) of the training data set. The accuracy obtained by the classification tree on the test data set was 82.35% (p = 0.04). Conclusion: The classification tree showed acceptable accuracy (82.35%) and high specificity (95.65%) but low sensitivity (54.55%). Based on the predictive model in this study, we suggested that 20% of body weight in scapular protractor strength is a meaningful cutoff value for presence of SW.

• Structural Engineering and Mechanics
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• v.63 no.4
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• pp.429-438
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• 2017

Structural design has an imperative role in deciding the failure possibility of a Reinforced Concrete (RC) structure. Recent research works achieved the goal of predicting the structural failure of the RC structure with the assistance of machine learning techniques. Previously, the Artificial Neural Network (ANN) has been trained supported by Particle Swarm Optimization (PSO) to classify RC structures with reasonable accuracy. Though, keeping in mind the sensitivity in predicting the structural failure, more accurate models are still absent in the context of Machine Learning. Since the efficiency of multi-objective optimization over single objective optimization techniques is well established. Thus, the motivation of the current work is to employ a Multi-objective Genetic Algorithm (MOGA) to train the Neural Network (NN) based model. In the present work, the NN has been trained with MOGA to minimize the Root Mean Squared Error (RMSE) and Maximum Error (ME) toward optimizing the weight vector of the NN. The model has been tested by using a dataset consisting of 150 RC structure buildings. The proposed NN-MOGA based model has been compared with Multi-layer perceptron-feed-forward network (MLP-FFN) and NN-PSO based models in terms of several performance metrics. Experimental results suggested that the NN-MOGA has outperformed other existing well known classifiers with a reasonable improvement over them. Meanwhile, the proposed NN-MOGA achieved the superior accuracy of 93.33% and F-measure of 94.44%, which is superior to the other classifiers in the present study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.521-528
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• 2016

Web-based services are used widely in many computer application fields due to the increasing use of PCs and mobile devices. Accordingly, topics on the analysis of access logs generated in the application fields have been researched actively to support personalized services in the field, and analyzing techniques based on the weight differentiation of information in access logs have been proposed. This paper outlines an analysis technique for web-click streams, which is useful for finding high utility old item sets in web-click streams, whose data elements are generated at a rapid rate. Using the technique, interesting information can be found, which is difficult to find in conventional techniques for analyzing web-click streams and is used effectively in target marketing. The proposed technique can be adapted widely to analyzing the data generated in a range of computing application fields, such as IoT environments, bio-informatics, etc., which generated data as a form of data streams.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.4
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• pp.875-885
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• 2010

CBR (Case-Based Reasoning) is a technique to infer the relationships between existing data and case data, and the method to calculate similarity and Euclidean distance is mostly frequently being used. However, since those methods compare all the existing and case data, it also has a demerit that it takes much time for data search and filtering. Therefore, to solve this problem, various researches have been conducted. This paper suggests the method of SE(Speed Euclidean-distance) calculation that utilizes the patterns discovered in the existing process of computing similarity and Euclidean distance. Because SE calculation applies the patterns and weight found during inputting new cases and enables fast data extraction and short operation time, it can enhance computing speed for temporal or spatial restrictions and eliminate unnecessary computing operation. Through this experiment, it has been found that the proposed method improves performance in various computer environments or processing rate more efficiently than the existing method that extracts data using similarity or Euclidean method does.