• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1203-1208
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• 2016

For young children who are not spontaneous or not accurate in verbal communication of their emotions and experiences, drawing is a good means of expressing their status in mind and thus drawing analysis with chromatics is a traditional tool for art therapy. Recently, children enjoy digital drawing via painting tools thus there is a growing needs to develop an automatic digital drawing analysis tool based on chromatics and art therapy theory. In this paper, we propose such an analyzing tool based on dominant color analysis. Technically, we use ART2 clustering and fuzzy logic to understand the fuzziness of subjects' status of mind expressed in their digital drawings. The frequency of color usage is fuzzified with respect to the membership functions. After applying fuzzy logic to this fuzzified central vector, we determine the dominant color and supporting colors from the digital drawings and children's status of mind is then analyzed according to the color-personality relationships based on Alschuler and Hattwick's historical researches.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.10
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• pp.836-843
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• 2017

In lunar exploration, the necessity of utilizing rover is verified by the examples of the Soviet Union and China and the similar Mars missions of the United States. In order to achieve the successful management of a lunar rover, a high precision navigation technique is required, and accordingly, high precision initial alignment is essential. Even though it is general to perform initial alignment in a steady state, a multiposition alignment technique is applied when high performance is needed. On the lunar surface, however, the performance of initial alignment decreases from that on Earth, and it cannot be improved by applying multiposition alignment method owing to certain constraints of lunar environment. In this paper, a sun sensor aided multiposition alignment technique is proposed. The measurement model for a sun vector is established, and its observability analysis is performed. The performance of the proposed algorithm is verified through computer simulations, and the results show the estimation performance is improved dramatically.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1011-1019
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• 2015

CAPTCHA(Completely Automated Public Turing test to tell Computers and Humans Apart) is a test used in computing to distinguish whether or not the user is computer or human. Many web sites mostly use the character-based CAPTCHA consisting of digits and characters. Recently, with the development of OCR technology, simple character-based CAPTCHA are broken quite easily. As an alternative, many web sites add noise to make it harder for recognition. In this paper, we analyzed the most recent CAPTCHA, which incorporates the addition of the natural images to obfuscate the characters. We proposed an efficient method using support vector machine to separate the characters from the background image and use convolutional neural network to recognize each characters. As a result, 368 out of 1000 CAPTCHAs were correctly identified, it was demonstrated that the current CAPTCHA is not safe.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.11
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• pp.675-690
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• 2003

In this paper, we present the virtual dancing studio for distributed virtual environment. In this system, geographically distributed user shares the virtual dancing hall and interacts with each other. The participating object can be a graphical avatar or a live video stream. It allows the coexistence of graphic objects and real images in the shared virtual space. One of the main technical challenges in developing the distributed virtual environment is to handle excessive network traffic. In an effort to effectively reduce the network traffic, we propose a scheme to adjust the QoS of each object with respect to the distance from the observer in the virtual space. The server maintains the QoS vector for each client's shared space and controls the packet traffic to individual clients based on its QoS vectors. We develop a proto-type virtual dancing environment. Java based development enables the client to be platform independent. The result of experiment shows that the adoption of hierarchical QoS management significantly reduces the overall network traffic.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.6
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• pp.344-353
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• 2006

In this paper, we present a new algorithm which imitate real pencil strokes. The purpose of research on NPR(Non-Photorealistic Rendering) is simulating automatically manmade artistic expressions such as pen-and-ink illustrations, watercolor paintings, pencil sketches and pastel drawings with computers. Recently, there has been a great deal of research works on NPR. One of them is researching in pencil illustration methods for NPR, and a lot of researchers have investigated into the LIC(Linear Integral Convolution) techniques which would change the initial images into the output images by directional vector field images for generating effects of pencil. However, the LIC techniques can not be applied to real-time drawing tools because they are post processing techniques. This paper presents a real-time pencil strokes algorithm which is based on an observation of how pencils(from 6B to 6H) draw lines. Although this algorithm using some pencil variables and noise generation is simple, it is fast and also can draw real-time pencil strokes similar to real manmade pencil strokes in a GUI drawing tool.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.538-547
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• 2001

Currently, 2D real-time image coding techniques had great developments and many related products were commercially developed. However, these techniques lack the capability of handling 3D actuality, occurred by the advent of virtual reality, because they handle only the temporal transmission for 2D image. Besides, many 3D virtual reality researches have been studied in computer graphics. Since the graphical researches were limited to the application of artificial models, the 3D actuality for real scene images could not be managed also. Therefore, a new 3D model extraction method based on stereo vision, that can deal with real scene virtual reality, is proposed in this paper. The proposed method adapted a compact genetic algorithm using population-based incremental learning (PBIL) to matching environments, in order to reduce memory consumption and computational time of conventional genetic algorithms. Since the PBIL used a probability vector and competitive learning, the matching algorithm became simple and the computation load was considerably reduced. Moreover, the matching quality was superior than conventional methods. Even if the characteristics of images are changed, stable outputs were obtained without the modification of the matching algorithm.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.3
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• pp.141-145
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• 2006

The line current problem(2-dimensional space : point source) is not easy to analyze the magnetic field using the standard finite element method(FEM), such as overhead trolley line or transmission line. To supplement such a defect this paper is proposed the coupling scheme of analytical solution and FEM. In analysis of the magnetic field using the standard FEM. If the current region is a relatively small compared to the whole region. Therefore the current region must be finely divided using a large number of elements. And the large number of elements increase the number of unknown variables and the use of computer memories. In this paper, an analytical solution is suggested to supplement this weak points. When source is line current and the part of interest is far from line current, the analytical solution can be coupling with FEM at the boundary. Analytical solution can be described by the multiplication of two functions. One is power function of radius, the other is a trigonometric function of angle in the cylindrical coordinate system. There are integral constants of two types which can be established by fourier series expansion. Also fourier series is represented as the factor to apply the continuity of the magnetic vector potential and magnetic field intensity with tangential component at the boundary. To verify the proposed algorithm, we chose simplified model existing magnetic material in FE region. The results are compared with standard FE solution. And it is good agreed by increasing harmonic order.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.2
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• pp.60-67
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• 2000

When the eigenvalues of the input covariance matrix of an array system spread by orders of magnitude, conventional adaptive arrays can't remove all the interference signals effectively In this paper, an Applebaum array adopting an adaptive gain controller (AGC) in the feedback loop of the array is proposed When eigenvalue spreaded interferences are incident to an array, a high power interference is removed easily in several iterations while a relative low power interference which is a cause of eigenvalue spread is still remained In the array output After some initial iterations, the proposed array increases the correlation between the low power interference and the array output by amplifying the output signal of the array As a result, the weights vector adapts to the direction of the low power interference as well as that of the high power interference Computer simulation results show that the proposed array gives high output signal to interference plus noise ratio (SINR) and a fast convergence speed.

• Journal of Broadcast Engineering
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• v.9 no.3
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• pp.196-206
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• 2004

This paper presents an efficient joint disparity-motion estimation algorithm for stereo sequence CODEC. Disparity vectors are estimated by the left and right motion vectors and previous disparity vectors for every frame. In order to obtain more accurate disparity vectors. we include a spatial prediction Process after the feint estimation. From joint estimation and spatial prediction, we can obtain accurate disparity vectors and then Increase coding efficiency. Finally, we proposed the backward quadtree decomposition. which helps the encoder to have a more detailed disparity vector map without transmitting additional coding bits for quadtree information. We confirmed superior performance of the proposed method through computer simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1543-1561
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• 2020

Taxonomy of human brain activity is a complicated rather challenging procedure. Due to its multifaceted aspects, including experiment design, stimuli selection and presentation of images other than feature extraction and selection techniques, foster its challenging nature. Although, researchers have focused various methods to create taxonomy of human brain activity, however use of multivariate pattern analysis (MVPA) for image recognition to catalog the human brain activities is scarce. Moreover, experiment design is a complex procedure and selection of image type, color and order is challenging too. Thus, this research bridge the gap by using MVPA to create taxonomy of human brain activity for different categories of images, both colored and gray scale. In this regard, experiment is conducted through EEG testing technique, with feature extraction, selection and classification approaches to collect data from prequalified criteria of 25 graduates of University Technology PETRONAS (UTP). These participants are shown both colored and gray scale images to record accuracy and reaction time. The results showed that colored images produces better end result in terms of accuracy and response time using wavelet transform, t-test and support vector machine. This research resulted that MVPA is a better approach for the analysis of EEG data as more useful information can be extracted from the brain using colored images. This research discusses a detail behavior of human brain based on the color and gray scale images for the specific and unique task. This research contributes to further improve the decoding of human brain with increased accuracy. Besides, such experiment settings can be implemented and contribute to other areas of medical, military, business, lie detection and many others.