• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.18 no.12
• /
• pp.1256-1261
• /
• 2008

This paper proposes a way to measure the displacement of a multi-point by using a pattern recognition from video signal. Generally in measuring displacement, gab sensor, which is a displacement sensor, is used. However, it is difficult to measure displacement by using a common sensor in places where it is unsuitable to attach a sensor, such as high-temperature areas or radioactive places. In this kind of places, non-contact methods should be used to measure displacement and in this study, images of CCD camera were used. When multi-point is measure by using a pattern recognition, it is possible to measure displacement with a non-contact method. It is simple to install and multi-point displacement measuring device so that it is advantageous to solve problems of spatial constraints.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.1
• /
• pp.29-34
• /
• 2015

Brain-computer interface (BCI) is being studied for convenient life in various application fields. The purpose of this study is to investigate a changing electroencephalography (EEG) for precise motion of a robot or an artificial arm. Three subjects who participated in this experiment performed three-task: Grip, Move, Relax. Acquired EEG data was extracted feature data using two feature extraction algorithm (power spectrum analysis and multi-common spatial pattern). Support vector machine (SVM) were applied the extracted feature data for classification. The classification accuracy was the highest at Grip class of two subjects. The results of this research are expected to be useful for patients required prosthetic limb using EEG.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.15 no.4
• /
• pp.277-282
• /
• 2015

Braincomputer interface (BCI) technology is making advances in the field of humancomputer interaction (HCI). To improve the BCI technology, we study the changes in the electroencephalogram (EEG) signals for six levels of grip strength: 10%, 20%, 40%, 50%, 70%, and 80% of the maximum voluntary contraction (MVC). The measured EEG data are categorized into three classes: Weak, Medium, and Strong. Features are then extracted using power spectrum analysis and multiclass-common spatial pattern (multiclass-CSP). Feature datasets are classified using a support vector machine (SVM). The accuracy rate is higher for the Strong class than the other classes.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2008.11a
• /
• pp.675-680
• /
• 2008

This paper proposes a way to measure the displacement of a multi-point by using a pattern recognition from video signal. Generally in measuring displacement, gab sensor, which is a displacement sensor, is used. However, it is difficult to measure displacement by using a common sensor in places where it is unsuitable to attach a sensor, such as high-temperature areas or radioactive places. In this kind of places, non-contact methods should be used to measure displacement and in this study, images of CCD camera were used. When displacement is measure by using camera images, it is possible to measure displacement with a non-contact method. It is simple to install and multi-point displacement measuring device so that it is advantageous to solve problems of spatial constraints.

• Journal of architectural history
• /
• v.14 no.2 s.42
• /
• pp.71-88
• /
• 2005

This study aims at clarifying the spatial generative process of Borromini's architecture. The close examination of his sketches and the analysis of his major four works such as San Carlo alle Quattro Fontane (1634-1667), Sant'Ivo della Sapienza (1642-1660), Santa Maria dei Sette Dolori, Chapel (1643-1646), Collegio di Propaganda Fide, Chapel (1652-1667) show common features in the generation of space as follow. 1) The spatial generative process of Borromini's architecture is dominated by the plan of main space which is formulated from simple geometric elements into complexly folded space by mean of union, addition, copy and warping. 2) Borromini made various kinds of annexed space around the main space to create long and continuous circulation. 3) Borromini's architecture has a tendency to divide interior elevation into two parts, wall part and roof part by thick entablature. Moreover the entablature play important role to copy the figure of the plan of main space three-dimensionally. 4) Borromini tried to create the sense of depth through perspectival distortion and multi-focal space through the ceiling pattern.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.10
• /
• pp.5015-5038
• /
• 2018

In this paper, a novel spectral-spatial joint sparse representation algorithm for hyperspectral image classification is proposed based on multi-layer superpixels in various scales. Superpixels of various scales can provide complete yet redundant correlated information of the class attribute for test pixels. Therefore, we design a joint sparse model for a test pixel by sampling similar pixels from its corresponding superpixels combinations. Firstly, multi-layer superpixels are extracted on the false color image of the HSI data by principal components analysis model. Secondly, a group of discriminative sampling pixels are exploited as reconstruction matrix of test pixel which can be jointly represented by the structured dictionary and recovered sparse coefficients. Thirdly, the orthogonal matching pursuit strategy is employed for estimating sparse vector for the test pixel. In each iteration, the approximation can be computed from the dictionary and corresponding sparse vector. Finally, the class label of test pixel can be directly determined with minimum reconstruction error between the reconstruction matrix and its approximation. The advantages of this algorithm lie in the development of complete neighborhood and homogeneous pixels to share a common sparsity pattern, and it is able to achieve more flexible joint sparse coding of spectral-spatial information. Experimental results on three real hyperspectral datasets show that the proposed joint sparse model can achieve better performance than a series of excellent sparse classification methods and superpixels-based classification methods.

• Korean Institute of Interior Design Journal
• /
• v.21 no.1
• /
• pp.228-239
• /
• 2012

This study aims to propose the improvement direction of spatial organization of orphanage facilities by reflecting the international trend of child welfare facilities including 'enhancement of habitability', 'opening to the local community' and 'multi-functionality' on the basis of ideas of 'right of housing' and 'normalization'. Orphanage facilities are evolving from 'facilities' to accommodate unfortunate children to the concept of the 'community-care', and the residential space is also rapidly shifting to 'cottage' type resembling a residential type of ordinary family so as to enhance the self-esteem and relationship. To suggest the future-oriented changeability of current orphanage facilities, the present study conducted a nationwide survey of child welfare facilities and four Visiting researches of cottage type orphanage with different locations to investigate the appropriateness of housing type, organization of common use space, mode of management and facilities criteria. The results of this study are following: 1) For enhancement of habitability it is suggested that cottage type with various plans in the form of ordinary housing is appropriate, that the number of children per cottage is six or so, and that the number of less than two or three children per room is recommended. At the same time the adjustment of facilities criteria, simplified or complex, is suggested to support a similar residence pattern to ordinary home. 2) Specialized programs must be introduced to establish a base of welfare-network for community children according to features of location and a complex management must be sought in the connection with neighboring public facilities. 3) To secure the residential environment and quality of life for children, the concept of a simple playground space by the current facilities criteria must be broken away to reinforce the network of various outdoor spaces closely connected with living space.

• Journal of KIISE
• /
• v.44 no.9
• /
• pp.887-892
• /
• 2017

Brain-computer interface (BCI) is a technology that controls computer and transmits intention by measuring and analyzing electroencephalogram (EEG) signals generated in multi-channel during mental work. At this time, optimal EEG channel selection is necessary not only for convenience and speed of BCI but also for improvement in accuracy. The optimal channel is obtained by removing duplicate(redundant) channels or noisy channels. This paper propose a dual filter-based channel selection method to select the optimal EEG channel. The proposed method first removes duplicate channels using Spearman's rank correlation to eliminate redundancy between channels. Then, using F score, the relevance between channels and class labels is obtained, and only the top m channels are then selected. The proposed method can provide good classification accuracy by using features obtained from channels that are associated with class labels and have no duplicates. The proposed channel selection method greatly reduces the number of channels required while improving the average classification accuracy.