• The Journal of Korean Philosophical History
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• no.29
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• pp.375-396
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• 2010

The aim of this paper is to suggest some ways of moral education for the building of children's social awareness and relationship skills as social and emotional competencies. Based on the social and emotional learning(SEL), this paper is tried to provide the effective ways to develop children's social awareness and relationship skill. According to SEL, social and emotional competence is the ability to understand, manage, and express the social and emotional aspects of one's life in ways that enable the successful management of life tasks such as learning, forming relationships, solving everyday problems, and adapting to the complex demands of growth and development. And it is also the process of acquiring and effectively applying the knowledge, attitudes, and skills necessary to recognize and manage emotions. Five key competencies such as self-awareness, social awareness, responsible decision making, self-management, relationship skills are taught, practiced, and reinforced through SEL programming. Moral education and social and emotional learning have emerged as two prominent formal approaches used schools to provide guidance for students' behavior. social awareness and relationship skills are necessary for succeeding in school, in the family, in the community, in life in general. Equipped with such skills, attitudes and beliefs, young children are more likely to make healty, caring, ethical, and responsible decisions and to avoid engaging in behaviors with negative consequences such as interpersonal violence and bullying.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.418-434
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• 2018

With the increasing use of the Internet and electronic documents, automatic text categorization becomes imperative. Several machine learning algorithms have been proposed for text categorization. The k-nearest neighbor algorithm (kNN) is known to be one of the best state of the art classifiers when used for text categorization. However, kNN suffers from limitations such as high computation when classifying new instances. Instance selection techniques have emerged as highly competitive methods to improve kNN through data reduction. However previous works have evaluated those approaches only on structured datasets. In addition, their performance has not been examined over the text categorization domain where the dimensionality and size of the dataset is very high. Motivated by these observations, this paper investigates and analyzes the impact of instance selection on kNN-based text categorization in terms of various aspects such as classification accuracy, classification efficiency, and data reduction.

• Smart Structures and Systems
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• v.6 no.2
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• pp.147-165
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• 2010

Impact damage detection in composite structures has gained a considerable interest in many engineering areas. The capability to detect damage at the early stages reduces any risk of catastrophic failure. This paper compares two advanced signal processing methods for impact location in composite aircraft structures. The first method is based on a modified triangulation procedure and Genetic Algorithms whereas the second technique applies Artificial Neural Networks. A series of impacts is performed experimentally on a composite aircraft wing-box structure instrumented with low-profile, bonded piezoceramic sensors. The strain data are used for learning in the Neural Network approach. The triangulation procedure utilises the same data to establish impact velocities for various angles of strain wave propagation. The study demonstrates that both approaches are capable of good impact location estimates in this complex structure.

• Journal of The Korean Association For Science Education
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• v.8 no.2
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• pp.17-22
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• 1988

Computer based instruction in the elementary science curriculum will be played an important role through the fifth curriculum reform from the 1989 school year. This is essential for the science instruction because the strategies on the problem-solvings and inquiry approaches can be utilized for the science classroom. Computer education can be thought as the education about the computer and the education using the computer. Of them the education using the computer means the computer assisted instruction(CAI) what is called all the possible activities using the computer in the classroom. Student achievement as the result of CAI depends on the learning activities of students and the instructional techniques and strategies of teachers using the computer. However, computer based education to enhance the student achievement is pointed out the lacks of the standardized Korean alphabet code and the compatibility of qualified software. These problems will be relieved according to the coding for the Korean alphabet of SUPER PILOT program language.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.5
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• pp.812-820
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• 1995

This paper proposes an approach of identifying nonlinear mappings from input/output data. The approach is based on the universal approximation by the fuzzy integration of local affine mappings. A connectionist model realizing the universal approximator is suggested by using a processing unit based on both the radial basis function and the weighted sum scheme. In addition, a learning method with self-organizing capability is proposed for the identifying of nonlinear mapping relationships with the given input/output data. To show the effectiveness of our approach, the proposed model is applied to the function approximation and the prediction of Mackey-Glass chaotic time series, and the performances are compared with other approaches.

• East Asian mathematical journal
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• v.36 no.4
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• pp.455-474
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• 2020

In this study, we investigate the latus rectum, one of the geometric measures of the conics, as one of the ways in which learners harmonize the geometric and algebraic approaches to conics from a pedagogical point of view. We also introduce the conical curve of Biot as presented in 'The Discourse on the Latus Rectum in conics(2013)' by Takeshi Sugimoto and reinterpret it for visualization and use as teaching material. Therefore, we expect that the importance of mathematical concepts will be recognized in conics and students can experience geometry learning that is explored in the school field and have a positive effect in developing the power to apply even in the context of applied problems.

• The Journal of Korean Physical Therapy
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• v.22 no.6
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• pp.91-98
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• 2010

Neurostimulation approaches have been developed and explored to modulate neuroplastic changes of cortical function in human brain. As one of the most primary noninvasive tools, transcranial direct current stimulation (tDCS) was extensively studied in the field of neuroscience. The alternation of cortical neurons depending on the polarity of the tDCS has been used for improving cognitive processing including working memory, learning, and language in normal individuals, as well as in patients with neurological or psychiatric diseases. In addition, tDCS has great advantages: it is a non-invasive, painless, safe, and cost-effective approach to enhance brain function in normal subjects and patients with neurological disorders. Numerous previous studies have confirmed the efficacy of tDCS. However, tDCS has not been considered for clinical applications and research in the field of physical therapy. Therefore, this review will focus on the general principles of tDCS and its related application parameters, and provide consideration of motor behavioral research and clinical applications in physical therapy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05a
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• pp.106-109
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• 2004

Many reported methods assume that the faces in an image or an image sequence have been identified and localization. Face detection from image is a challenging task because of variability in scale, location, orientation and pose. In this paper, we present an efficient linear discriminant for multi-view face detection. Our approaches are based on linear discriminant. We define training data with fisher linear discriminant to efficient learning method. Face detection is considerably difficult because it will be influenced by poses of human face and changes in illumination. This idea can solve the multi-view and scale face detection problem poses. Quickly and efficiently, which fits for detecting face automatically. In this paper, we extract face using fisher linear discriminant that is hierarchical models invariant pose and background. We estimation the pose in detected face and eye detect. The purpose of this paper is to classify face and non-face and efficient fisher linear discriminant..

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.928-940
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• 2017

State-of-the-art speaker recognition systems may work better for the English language. However, if the same system is used for recognizing those who speak different languages, the systems may yield a poor performance. In this work, the decisions of a Gaussian mixture model-universal background model (GMM-UBM) and a learning vector quantization (LVQ) are combined to improve the recognition performance of a multilingual speaker identification system. The difference between these classifiers is in their modeling techniques. The former one is based on probabilistic approach and the latter one is based on the fine-tuning of neurons. Since the approaches are different, each modeling technique identifies different sets of speakers for the same database set. Therefore, the decisions of the classifiers may be used to improve the performance. In this study, multitaper mel-frequency cepstral coefficients (MFCCs) are used as the features and the monolingual and cross-lingual speaker identification studies are conducted using NIST-2003 and our own database. The experimental results show that the combined system improves the performance by nearly 10% compared with that of the individual classifier.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.366-370
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• 2022

The article deals with the theoretical and methodological foundations of innovative approaches in the modern education system. The issues of introducing computerized and telecommunication technologies are characterized, which allow switching to distance learning (DL), which is a promising form of the system of open education support in the modern educational process. Special attention is paid to the study of practical technologies of vocational training and the activities of a teacher and innovative areas of vocational training of students.