• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.600-610
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• 2022

While Korean piano pedagogy has seen a remarkable growth, the relatively weak attention to intermediate level has emerged as a pending problem. The limited literature review, specifically the lack of playing Korean original works, has been considered as a serious issue. To emphasize the usefulness of Kim Kukjin's "Pieces of Korean Melody for Piano" as an intermediate work, this study presents practical teaching guidelines by classifying of difficulty in his 25 pieces and providing step by step learning goals and teaching plan. The difficulty stage was based on Jane Magret's 10-step classification table for comparison with other intermediate piano literature, and this study more specifically classified Kim's pieces according to Korean melody, rhythm, and texture. As a result of the difficulty classification, it was found that the pieces from stages 4 to 10 was organized to systematically and comprehensively learn step by step from the most basic progression to Korean 'Jangdan' rhythm patterns, various articulations and decorations that express 'Sigimsae' of Korean Traditional Music, and heterophony texture. In addition, this study proposed the order of pieces for the effective teaching according to the characteristics and difficulty of the pieces. This study suggests that the findings lead to the expansion of Korean intermediate literature study and the revitalization of Korean original works teaching method.

• Journal of the Ergonomics Society of Korea
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• v.23 no.3
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• pp.13-24
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• 2004

Anthropometric data is a fundamental resource in developing ergonomic products and workplaces. However, designers often experience difficulty in searching anthropometric data relevant to the design due to the technicality of anthropometric terminologies, ambiguity in the description of measurement method for some anthropometric variables, and inefficiency of existing search methods for anthropometric data. The present study suggests a method to develop a classification system of anthropometric variables for systematic, efficient search of anthropometric data. The proposed method first classifies anthropometric variables according to body segment and type of variable, and then arranges anthropometric variables of the same body segment and variable type by comparing the heights of their reference points. The proposed classification method was applied to establish a classification system of 66 anthropometric variables that were selected for an automotive interior design. Then the established anthropometric classification system was utilized to design a search interface of a web-based anthropometric data retrieval system.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1261-1267
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• 2015

The problem of underwater target detection and classification has been attracted a substantial amount of attention and studied from many researchers for both military and non-military purposes. The difficulty is complicate due to various environmental conditions. In this paper, we study classifier ensemble methods for active sonar target classification to improve the classification performance. In general, classifier ensemble method is useful for classifiers whose variances relatively large such as decision trees and neural networks. Bagging, Random selection samples, Random subspace and Rotation forest are selected as classifier ensemble methods. Using the four ensemble methods based on 31 neural network classifiers, the classification tests were carried out and performances were compared.

• Korean Journal of Child Studies
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• v.9 no.2
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• pp.133-156
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• 1988

This study investigated developmental change with reference to continuity theory in the acquisition of concepts of kin relation, task difficulty with reference to cognitive complexity, and interrelationships in the performance of cognitive tasks of kinship concepts with reference to cognitive parallelism. The subjects consisted of 6-, 8-, 10, and 12-year-old randomly selected children attending kindergartens or elementary schools in Seoul. The schools were located in various residental areas regarded as either middle or lower class. The 81 boys and 80 girls participated in 3 experiments on classification, seriation, and grouping. The instrument for the classification, seriation, and grouping tasks was composed of 10 10cm black on white line drawings of the head and upper torso area of persons in kin relationship. The data was analyzed with MANOVA. A significant age effect was found in the 3 quasi- experiments. There were significant effects on task difficulty. The biosocial power distribution indirectly influenced children's acquisition of kin relational concepts; that is, children performed better in male-kin than in female-kin tasks. There was a high correlation in performance between the 3 cognitive tasks. These findings support the continuity theory (except for seriation), a model which arranges kin-names in order of cognitive load, the centric status of men in society, and the theory of cognitive developmental parallelism.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.11-24
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• 2022

For the questions asked for LMS-based online evaluation the professor directly set exam questions, or use the automatic question-taking method according to the level of difficulty using the question bank divided by category. Among them, it is important to manage the difficulty of questions in an objective and efficient way, above all, in the automatic question-taking method according to difficulty. Because the questions presented to the evaluators may be different. In this paper, we propose an difficulty re-adjustment algorithm that considers not only the correct rate of a problem but also the time taken to solve the problem. For this, a logistic regression classification algorithm was used of machine learning, and a reference threshold was set based on the predicted probability value of the learning model and used to readjust the difficulty of each item. As a result, it was confirmed that there were many changes in the difficulty of each item that depended only on the existing correct rate. Also, as a result of performing group evaluation using the adjustment difficulty problem, it was confirmed that the average score improved in most groups compared to the difficulty problem based on the percentage of correct answers.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.309-319
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• 2016

This paper presents a new recognition and classification method for power quality (PQ) disturbances on the basis of pattern linguistic values. This method solves the difficulty of recognizing disturbances rapidly and accurately by using fuzzy logic. This method uses classification disturbance patterns to define the linguistic values of fuzzy input variables and used the input variables of corresponding disturbance pattern to set membership functions. This method also sets the fuzzy rules by analyzing the distribution regularities of the input variable values. One characteristic of this method is that the linguistic values of fuzzy input variables and the setting of membership functions are not only related to the input variables but also to the character of classification disturbance and the classification results. Furthermore, the number of fuzzy rules is equal to the number of disturbance patterns. By using this method for disturbance classification, the membership function and design of fuzzy rules are directly related to the objective of classification, thus effectively reducing the complexity of the design process and yielding accurate classification results. The classification results of the simulation and measured data verify the feasibility and effectiveness of this method.

• Physical Therapy Korea
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• v.20 no.3
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• pp.89-99
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• 2013

The purposes of this study were: 1) to show the item difficulty hierarchy of walking/moving construct of the International Classification of Functioning, Disability and Health-Activity Measure (ICF-AM), 2) to evaluate the item-level psychometrics for model fit, 3) to describe the relevant physical activity defined by level of activity intensity expressed as Metabolic Equivalent of Tasks (MET), and 4) to explore what extent the empirical activity hierarchy of the ICF-AM is linked to the conceptual model based on the level of energy expenditure described as MET. One hundred and eight participants with lower extremity impairments were examined for the present study. A newly created activity measure, the ICF-AM using an item response theory (IRT) model and computer adaptive testing (CAT) method, has a construct on walking/moving construct. Based on the ICF category of walking and moving, the instrument comprised items corresponding to: walking short distances, walking long distances, walking on different surfaces, walking around objects, climbing, and running. The item difficulty hierarchy was created using Winstep software for 20 items. The Rasch analyses (1-parameter IRT model) were performed on participants with lower extremity injuries who completed the paper and pencil version of walking/moving construct of the ICF-AM. The classification of physical activity can also be performed by the use of METs that is often preferred to determine the level of physical activity. The empirical item hierarchy of walking, climbing, running activities of the ICF-AM instrument was similar to the conceptual activity hierarchy based on the METs. The empirically derived item difficulty hierarchy of the ICF-AM may be useful in developing MET-based activity measure questionnaires. In addition to convenience of applying items to questionnaires, implications of the finding could lead to the use of CAT method without sacrificing the objectivity of physiologic measures.

• Journal of Korean Library and Information Science Society
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• v.21
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• pp.459-483
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• 1994

The purpose of the study is to design and implement a prototype expert system for library classification in the literature field of the DDC 20. The system was largely consisted of a knowledge base, an inference engine, a knowledge acquisition facility, an explanation facility and an user interface facility. The knowledge base was represented by inference rules and frames. The name file for authors and titles was designed separately. The forward chaining technique was chosen for the inference engine and the menu-driven dialog technique was also taken for the user interface. The conclusions of the study can be summarized as follows: 1) The difficulty of document classification work is due to the complex and stringent classification rules. Such problems can be considerably alleviated by using the present system. 2) Even the novice with a knowledge about the DDC 20 can easily access the system. And also librarian other than the professional classifier can easily be accustomed to the classification work. 3) The system can be used as an online classification scheme. 4) By adding any local language other than English or Hangeul on the menu screen, the language problem relating classification can be overcome. 5) The system can be employed as the intensification tool for the education of classification as well as library automation.

• International Journal of Contents
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• v.12 no.3
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• pp.12-16
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• 2016

Brain computer interfaces (BCI) usually have focused on classifying the explicitly-expressed intentions of humans. In contrast, implicit intentions should be considered to develop more intelligent systems. However, classifying implicit intention is more difficult than explicit intentions, and the difficulty severely increases for subject independent classification. In this paper, we address the subject independent classification of implicit intention based on electroencephalography (EEG) signals. Among many machine learning models, we use the support vector machine (SVM) with radial basis kernel functions to classify the EEG signals. The Fisher scores are evaluated after extracting the gamma, beta, alpha and theta band powers of the EEG signals from thirty electrodes. Since a more discriminant feature has a larger Fisher score value, the band powers of the EEG signals are presented to SVM based on the Fisher score. By training the SVM with 1-out of-9 validation, the best classification accuracy is approximately 65% with gamma and theta components.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.267-275
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• 2015

Those land cover maps have widely been used in various fields, such as environmental studies, military strategies as well as in decision-makings. This study proposes a method to extract training data, automatically and classify the cover using ingle satellite images and national land cover maps, provided by the Ministry of Environment. For this purpose, as the initial training data, those three were used; the unsupervised classification, the ISODATA, and the existing land cover maps. The class was classified and named automatically using the class information in the existing land cover maps to overcome the difficulty in selecting classification by each class and in naming class by the unsupervised classification; so as achieve difficulty in selecting the training data in supervised classification. The extracted initial training data were utilized as the training data of MLC for the land cover classification of target satellite images, which increase the accuracy of unsupervised classification. Finally, the land cover maps could be extracted from updated training data that has been applied by an iterative method. Also, in order to reduce salt and pepper occurring in the pixel classification method, the MRF was applied in each repeated phase to enhance the accuracy of classification. It was verified quantitatively and visually that the proposed method could effectively generate the land cover maps.