• Title/Summary/Keyword: vector computer

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A Reference Frame Selection Method Using RGB Vector and Object Feature Information of Immersive 360° Media (실감형 360도 미디어의 RGB 벡터 및 객체 특징정보를 이용한 대표 프레임 선정 방법)

  • Park, Byeongchan;Yoo, Injae;Lee, Jaechung;Jang, Seyoung;Kim, Seok-Yoon;Kim, Youngmo
    • Journal of IKEEE
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    • v.24 no.4
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    • pp.1050-1057
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    • 2020
  • Immersive 360-degree media has a problem of slowing down the video recognition speed when the video is processed by the conventional method using a variety of rendering methods, and the video size becomes larger with higher quality and extra-large volume than the existing video. In addition, in most cases, only one scene is captured by fixing the camera in a specific place due to the characteristics of the immersive 360-degree media, it is not necessary to extract feature information from all scenes. In this paper, we propose a reference frame selection method for immersive 360-degree media and describe its application process to copyright protection technology. In the proposed method, three pre-processing processes such as frame extraction of immersive 360 media, frame downsizing, and spherical form rendering are performed. In the rendering process, the video is divided into 16 frames and captured. In the central part where there is much object information, an object is extracted using an RGB vector per pixel and deep learning, and a reference frame is selected using object feature information.

Research on the Emotion Recognition System based on Electrocardiograph and Pulse Signals (심전도 및 맥파신호 기반의 감정인식 시스템에 관한 연구)

  • Hong, Yoon-Jung;Hwang, Yun-Kyung;Shin, Dong-Kyoo;Kim, Dong-Hyun;Shin, Dong-Il
    • Annual Conference of KIPS
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    • 2008.05a
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    • pp.175-178
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    • 2008
  • 본 논문은 생체 신호들 중 데이터 획득이 간편한 심전도와 맥파를 실시간으로 취득하여 기계학습 기법인 SVM (Support Vector Machine)알고리즘과 클러스터링 기법인 k-NN (Nearest Neighbor)알고리즘을 적용한 인간의 감정을 분석하는 시스템에 대한 연구결과를 제시한다.

High-Secure Multivariable Knapsack Cryptosystem (안전성이 높은 다변수 Knapsack 암호시스템)

  • Lee, Byeong-Su
    • The Transactions of the Korea Information Processing Society
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    • v.2 no.4
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    • pp.611-618
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    • 1995
  • In the high information societies, the requirement of encryption security is increasing so as to protect information from the threat of attacks by illegal changes of data, illegal leakage of data, disorder of data sequences and the unauthorized sender and an unauthorized receiver etc. In this paper, multivariable knapsack crytosystem is proposed for security of computer communication. This system is securer and simpler than the conventional knapsack cryptosystems. And, proposed cryptosystem composed what represented each element of superincreasing vector with multivar able polynomial after transforming it of ciphervector. For the deciphering of ciphertext, the plaintext is determined by using the integers of secret and the superincreasing vector of secret key. Thus, the stability of this cryptosystem is based on the difficulty of obtaining the root that ciphervector becomes the superincreasing vector, in substituting the integers of secret for ciphervector to represent with the miltivariable polynomial. The propriety of proposed multivariable knapsack cryptosystem was proved through computer simulation.

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On Development of the GIS Application Based on Satellite Images (위성영상을 기반으로 한 GIS 응용 시스템 개발)

  • 양인태;최영재
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.1
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    • pp.1-9
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    • 2004
  • Until comparatively lately the use of vector data is the main current in GIS fields. Vector data have many advantages such as easy of scale change, small data volume and so on. But it also has some weak point that can't apply real world. The other hand the satellite images have strong point that can apply real world actually. Recently rapid progress of computer capacity and processing velocity is the current trend of the times. Therefore in this study I intend to develop GIS application based on satellite images with vector data and raster data altogether. This system is developed by using Visual C++ in the personal computer and MS Access's MDB far database management. The LANDSAT, KOMPSAT and IKONOS satellite image database were used in this study. Also, we are studied to set up scale for screen display according to spatial resolution.

Analyzing Errors in Bilingual Multi-word Lexicons Automatically Constructed through a Pivot Language

  • Seo, Hyeong-Won;Kim, Jae-Hoon
    • Journal of Advanced Marine Engineering and Technology
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    • v.39 no.2
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    • pp.172-178
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    • 2015
  • Constructing a bilingual multi-word lexicon is confronted with many difficulties such as an absence of a commonly accepted gold-standard dataset. Besides, in fact, there is no everybody's definition of what a multi-word unit is. In considering these problems, this paper evaluates and analyzes the context vector approach which is one of a novel alignment method of constructing bilingual lexicons from parallel corpora, by comparing with one of general methods. The approach builds context vectors for both source and target single-word units from two parallel corpora. To adapt the approach to multi-word units, we identify all multi-word candidates (namely noun phrases in this work) first, and then concatenate them into single-word units. As a result, therefore, we can use the context vector approach to satisfy our need for multi-word units. In our experimental results, the context vector approach has shown stronger performance over the other approach. The contribution of the paper is analyzing the various types of errors for the experimental results. For the future works, we will study the similarity measure that not only covers a multi-word unit itself but also covers its constituents.

Visualization of Convolution Operation Using Scalable Vector Graphics (SVG를 이용한 컨벌루션 연산의 시각화)

  • Kim, Yeong-Mi;Kang, Eui-Sung
    • The Journal of Korean Association of Computer Education
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    • v.10 no.1
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    • pp.97-105
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    • 2007
  • In this paper, visualization of convolution operation is presented, which is implemented by scalable vector graphics (SVG). Convolution operation is one of the basic essential concepts in the area of signal and image processing. However, it is difficult for students to intuitively understand the operation of convolution since it is mainly based on mathematical representation. We present the visualization of convolution operation and its applications which are implemented by SVG. The effects of the proposed approach have been analyzed by interviews. It has been seen that the proposed visualization of convolution operation could be effectively applied to learn the convolution operation and its applications.

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Tessellation-independent Approximation of Normal Vectors (Tessellation에 독립적인 법선 벡터 근사에 대한 연구)

  • Ahn, Jaewoo;Kim, Woongsoon
    • Journal of the Korea Computer Graphics Society
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    • v.4 no.2
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    • pp.29-32
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    • 1998
  • When rendering polyhedral models, normal vectors at polygon vertices are necessary for smooth shading. The most commonly used technique of approximating a vertex normal vector by averaging normal vectors of faces around the vertex yields, however, different results on different tessellations Further, continuous deformation of models may cause abrupt discontinuous changes in normal vector directions. In this paper, a variation of the above technique is proposed to avoid these problems. Specifically, it uses a weighted average of normal vectors of faces around the vertex, where the weight of a face being the angular span of the two edges incident on the vertex.

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Investigations on the Optimal Support Vector Machine Classifiers for Predicting Design Feasibility in Analog Circuit Optimization

  • Lee, Jiho;Kim, Jaeha
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.15 no.5
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    • pp.437-444
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    • 2015
  • In simulation-based circuit optimization, many simulation runs may be wasted while evaluating infeasible designs, i.e. the designs that do not meet the constraints. To avoid such a waste, this paper investigates the use of support vector machine (SVM) classifiers in predicting the design's feasibility prior to simulation and the optimal selection of the SVM parameters, namely, the Gaussian kernel shape parameter ${\gamma}$ and the misclassification penalty parameter C. These parameters affect the complexity as well as the accuracy of the model that SVM represents. For instance, the higher ${\gamma}$ is good for detailed modeling and the higher C is good for rejecting noise in the training set. However, our empirical study shows that a low ${\gamma}$ value is preferable due to the high spatial correlation among the circuit design candidates while C has negligible impacts due to the smooth and clean constraint boundaries of most circuit designs. The experimental results with an LC-tank oscillator example show that an optimal selection of these parameters can improve the prediction accuracy from 80 to 98% and model complexity by $10{\times}$.