• Journal of the Korean Data and Information Science Society
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• 제22권1호
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• pp.99-105
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• 2011

We propose a semi-supervised learning algorithm based on a form of regularization that incorporates similarity and dissimilarity penalty terms. Our approach uses a graph-based encoding of similarity and dissimilarity. We also present a model-selection method which employs cross-validation techniques to choose hyperparameters which affect the performance of the proposed method. Simulations using two types of dat sets demonstrate that the proposed method is promising.

• 한국과학교육학회지
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• 제28권8호
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• pp.796-813
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• 2008

과학 개념에 대한 높은 이해와 과학 분야에 무한한 가능성과 잠재력을 가지고 있는 과학영재들이 물리 개념 이해 과정 중에 나타내는 사고 모형을 분석하기 위해서 역학 개념 검사인 FCI, MBT와 전자기학 개념검사인 CSEM을 사용하였다. 세 가지의 설문지 필답검사를 실시한 후에는 그룹 토의의 교실 상황 관찰과 개인 면담을 실시하고 그 결과를 종합 분석하였다. 분석 결과에 따르면 과학영재의 물리 개념 이해 과정에서 나타나는 사고 모형은 물리 개념에 대한 정확한 이해와 적용으로 개념의 형성이 안정성과 일관성을 보이는 일관성 사고 모형을 가진 학생과 문제에 적용할 때마다 유동성과 상황 의존성을 보이는 다양성 사고 모형을 가진 학생으로 분류되었고 또한 과학영재이지만 뉴턴의 운동 법칙에 대하여 힘과 운동의 관계를 잘못 이해한 아리스토텔레스 정신모형을 가진 학생과 옳은 과학 개념인 뉴턴 모형을 가진 학생 그리고 문제 상황에 따라 달라지는 두 정신모형이 혼합된 학생으로 분류되어 개인차가 있음을 알 수 있었다.

• 대한의용생체공학회:의공학회지
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• 제45권4호
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• pp.179-186
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• 2024

This paper investigates the impact of Riemannian Procrustes Analysis (RPA) on enhancing the classification performance of SPD-Net when applied to EEG signals across different sessions and subjects. EEG signals, known for their inherent individual variability, are initially transformed into Symmetric Positive Definite (SPD) matrices, which are naturally represented on a Riemannian manifold. To mitigate the variability between sessions and subjects, we employ RPA, a method that geometrically aligns the statistical distributions of these matrices on the manifold. This alignment is designed to reduce individual differences and improve the accuracy of EEG signal classification. SPD-Net, a deep learning architecture that maintains the Riemannian structure of the data, is then used for classification. We compare its performance with the Minimum Distance to Mean (MDM) classifier, a conventional method rooted in Riemannian geometry. The experimental results demonstrate that incorporating RPA as a preprocessing step enhances the classification accuracy of SPD-Net, validating that the alignment of statistical distributions on the Riemannian manifold is an effective strategy for improving EEG-based BCI systems. These findings suggest that RPA can play a role in addressing individual variability, thereby increasing the robustness and generalization capability of EEG signal classification in practical BCI applications.

• 한국멀티미디어학회논문지
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• 제17권1호
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• pp.34-42
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• 2014

본 논문에서는 파형 신호와 이미지 등에서 패치를 추출하고 이를 패치 그래프로 구성한 다음, 이로부터 각 패치 간의 컴뮤트 타임을 구하여 이에 기반한 임베딩 기법을 구현하고, 가장 널리 이용되는 PCA(principal component analysis) 임베딩 결과와 비교 분석한다. 임베딩에서 차원을 줄일 경우 원 임베딩과 축소된 차원의 임베딩 간에는 오차가 크지 않도록 차원을 결정하는 것이 일반적이다. 하지만 본 논문에서 구현한 임베딩 방식은 삼차원 이하로 줄여 오차가 80~90%를 상회하여도 축소된 차원의 임베딩 공간에서 각 신호 고유의 기하 구조를 생성하므로 패턴 분류나 기계 학습 등의 응용 목적에 활용 가능함을 실험으로 확인한다.

• 교육시설
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• 제12권5호
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• pp.13-24
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• 2005

This study is the second that aims at offering the basic information on the appropriate spatial organization of the special classes by looking at the relationship between a group of learning activities and a group of playing activities in Elementary and Middle Schools The learning space unit of the special classes should be more flexible for the various learning activities and be prepared in order to correspond to the needs of a territory for different learning appeared according to the degree of handicap, learning ability and the contents of learning. This study dealt with the learning space unit to tackle the problems of special classes. In fact, it is unwise to offer so many different kinds of learning spaces in every school. Due to the manifold and multiple characteristics of handicap, the problem of special classes should be approached by the overall educational system of special educational facilities rather than by a special classes space alone. In this respect, it can be said that this problem should be tackled by reorganization of the special classes in the community through specialization and network system of special class facilities in order to make more effective educational environment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.103.1-103
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• 2002

In variable structure control algorithms, The control law used to realized the desired sliding mode dynamics is discontinuous on the switching manifold. However, due to imperfections in switching, such as time delays, the system trajectory chatters instead of sliding along the switching manifold. This chattering is undesirable because it may excite unmodeled high frequency dynamics in the physical system. In this paper, to overcome this drawback a self-organizing fuzzy sliding mode control algorithm using gradient descent method is proposed. The proposed method has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbance, parameter variations and uncertainties ill the sliding mode. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum system. The results show that both alleviation of chattering and performance are achieved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권4호
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• pp.1721-1737
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• 2020

Human apparent age estimation has become a popular research topic and attracted great attention in recent years due to its wide applications, such as personal security and law enforcement. To achieve the goal of age estimation, a large number of methods have been pro-posed, where the models derived through the cumulative attribute coding achieve promised performance by preserving the neighbor-similarity of ages. However, these methods afore-mentioned ignore the geometric structure of extracted facial features. Indeed, the geometric structure of data greatly affects the accuracy of prediction. To this end, we propose an age estimation algorithm through joint feature selection and manifold learning paradigms, so-called Feature-selected and Geometry-preserved Least Square Regression (FGLSR). Based on this, our proposed method, compared with the others, not only preserves the geometry structures within facial representations, but also selects the discriminative features. Moreover, a deep learning extension based FGLSR is proposed later, namely Feature selected and Geometry preserved Neural Network (FGNN). Finally, related experiments are conducted on Morph2 and FG-Net datasets for FGLSR and on Morph2 datasets for FGNN. Experimental results testify our method achieve the best performances.

• 교육시설
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• 제12권4호
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• pp.17-29
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• 2005

The purpose of this study is to establish fundamental standards of architectural planning concerning special class facilities in order to offer the basic information on the appropriate spatial organization of the special classroom by looking at the relationship between learning activities and living activities and the existing spatial organization. At present, there are no proper architectural standards which correspond to special class children's handicap and it's various characteristics. The special classes are just using ordinary classrooms without a considerations of the children with manifold handicap. In this sense, this study deals with appropriate special class facilities corresponding to the various characteristics of children's handicap, the contacting activities of special children with ordinary children and finally proper environment for the mainstreaming education which special education pursues.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2007년도 가을 학술발표논문집 Vol.34 No.2 (A)
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• pp.211-212
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• 2007

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.300-303
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• 2003

An Algorithm based on direct implementation of variable structure systems theory approach is proposed for on-line training of multilayer perceptrons. Network structures which have multiple inputs, single output and one hidden layer are considered and the weights are assumed to have capabilities for continuous time adaptation. The zero level set of the network learning error is regarded as a sliding surface in the learning parameters space. A sliding mode trajectory can be brought on and reached in finite time on such a sliding manifold. Results from simulated on-line identification task for a two-link planar manipulator dynamics are also presented.