• Title/Summary/Keyword: 유클리드 거리

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An Efficient Multidimensional Scaling Method based on CUDA and Divide-and-Conquer (CUDA 및 분할-정복 기반의 효율적인 다차원 척도법)

  • Park, Sung-In;Hwang, Kyu-Baek
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.4
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    • pp.427-431
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    • 2010
  • Multidimensional scaling (MDS) is a widely used method for dimensionality reduction, of which purpose is to represent high-dimensional data in a low-dimensional space while preserving distances among objects as much as possible. MDS has mainly been applied to data visualization and feature selection. Among various MDS methods, the classical MDS is not readily applicable to data which has large numbers of objects, on normal desktop computers due to its computational complexity. More precisely, it needs to solve eigenpair problems on dissimilarity matrices based on Euclidean distance. Thus, running time and required memory of the classical MDS highly increase as n (the number of objects) grows up, restricting its use in large-scale domains. In this paper, we propose an efficient approximation algorithm for the classical MDS based on divide-and-conquer and CUDA. Through a set of experiments, we show that our approach is highly efficient and effective for analysis and visualization of data consisting of several thousands of objects.

Fingerprint-Based Personal Authentication Using Directional Filter Bank (방향성 필터 뱅크를 이용한 지문 기반 개인 인증)

  • 박철현;오상근;김범수;원종운;송영철;이재준;박길흠
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.4
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    • pp.256-265
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    • 2003
  • To improve reliability and practicality, a fingerprint-based biometric system needs to be robust to rotations of an input fingerprint and the processing speed should be fast. Accordingly, this paper presents a new filterbank-based fingerprint feature extraction and matching method that is robust to diverse rotations and reasonably fast. The proposed method fast extracts fingerprint features using a directional filter bank, which effectively decomposes an image into several subband outputs Since matching is also performed rapidly based on the Euclidean distance between the corresponding feature vectors, the overall processing speed is so fast. To make the system robust to rotations, the proposed method generates a set of feature vectors considering various rotations of an input fingerprint and then matches these feature vectors with the enrolled single template feature vector. Experimental results demonstrated the high speed of the proposed method in feature extraction and matching, along with a comparable verification accuracy to that of other leading techniques.

Operation Modes Classification of Chemical Processes for History Data-Based Fault Diagnosis Methods (데이터 기반 이상진단법을 위한 화학공정의 조업모드 판별)

  • Lee, Chang Jun;Ko, Jae Wook;Lee, Gibaek
    • Korean Chemical Engineering Research
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    • v.46 no.2
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    • pp.383-388
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    • 2008
  • The safe and efficient operation of the chemical processes has become one of the primary concerns of chemical companies, and a variety of fault diagnosis methods have been developed to diagnose faults when abnormal situations arise. Recently, many research efforts have focused on fault diagnosis methods based on quantitative history data-based methods such as statistical models. However, when the history data-based models trained with the data obtained on an operation mode are applied to another operating condition, the models can make continuous wrong diagnosis, and have limits to be applied to real chemical processes with various operation modes. In order to classify operation modes of chemical processes, this study considers three multivariate models of Euclidean distance, FDA (Fisher's Discriminant Analysis), and PCA (principal component analysis), and integrates them with process dynamics to lead dynamic Euclidean distance, dynamic FDA, and dynamic PCA. A case study of the TE (Tennessee Eastman) process having six operation modes illustrates the conclusion that dynamic PCA model shows the best classification performance.

Robust Planar Shape Recognition Using Spectrum Analyzer and Fuzzy ARTMAP (스펙트럼 분석기와 퍼지 ARTMAP 신경회로망을 이용한 Robust Planar Shape 인식)

  • 한수환
    • Journal of the Korean Institute of Intelligent Systems
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    • v.7 no.2
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    • pp.34-42
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    • 1997
  • This paper deals with the recognition of closed planar shape using a three dimensional spectral feature vector which is derived from the FFT(Fast Fourier Transform) spectrum of contour sequence and fuzzy ARTMAP neural network classifier. Contour sequences obtained from 2-D planar images represent the Euclidean distance between the centroid and all boundary pixels of the shape, and are related to the overall shape of the images. The Fourier transform of contour sequence and spectrum analyzer are used as a means of feature selection and data reduction. The three dimensional spectral feature vectors are extracted by spectrum analyzer from the FFT spectrum. These spectral feature vectors are invariant to shape translation, rotation and scale transformation. The fuzzy ARTMAP neural network which is combined with two fuzzy ART modules is trained and tested with these feature vectors. The experiments including 4 aircrafts and 4 industrial parts recognition process are presented to illustrate the high performance of this proposed method in the recognition problems of noisy shapes.

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Perceptual and Adaptive Quantization of Line Spectral Frequency Parameters (선 스펙트럼 주파수의 청각 적응 부호화)

  • 한우진;김은경;오영환
    • The Journal of the Acoustical Society of Korea
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    • v.19 no.8
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    • pp.68-77
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    • 2000
  • Line special frequency (LSF) parameters have been widely used in low bit-rate speech coding due to their efficiency for representing the short-time speech spectrum. In this paper, a new distance measure based on the masking properties of human ear is proposed for quantizing LSF parameters whereas most conventional quantization methods are based on the weighted Euclidean distance measure. The proposed method derives the perceptual distance measure from the definition of noise-to-mask ratio (NMR) which has high correspondence with the actual distortion received in the human ear and uses it for quantizing LSF parameters. In addition, we propose an adaptive bit allocation scheme, which allocates minimal bits to LSF parameters maintaining the perceptual transparency of given speech frame for reducing the average bit-rates. For the performance evaluation, we has shown the ratio of perceptually transparent frames and the corresponding average bit-rates for the conventional and proposed methods. By jointly combining the proposed distance measure and adaptive bit allocation scheme, the proposed system requires only 770 bps for obtaining 95.5% perceptually transparent frames, while the conventional systems produce 89.9% at even 1800 bps.

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Measuring Similarity Between Movies Based on Sentiment of Tweets (트위터를 활용한 감성 기반의 영화 유사도 측정)

  • Kim, Kyoungmin;Kim, Dong-Yun;Lee, Jee-Hyong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.3
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    • pp.292-297
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    • 2014
  • As a Social Network Service (SNS) has become an integral part of our everyday lives, millions of users can express their opinion and share information regardless of time and place. Hence sentiment analysis using micro-blogs has been studied in various field to know people's opinion on particular topics. Most of previous researches on movie reviews consider only positive and negative sentiment and use it to predict movie rating. As people feel not only positive and negative but also various emotion, the sentiment that people feel while watching a movie need to be classified in more detail to extract more information than personal preference. We measure sentiment distributions of each movie from tweets according to the Thayer's model. Then, we find similar movies by calculating similarity between each sentiment distributions. Through the experiments, we verify that our method using micro-blogs performs better than using only genre information of movies.

Complexity Limited Sphere Decoder and Its SER Performance Analysis (스피어 디코더에서 최대 복잡도 감소 기법 및 SER 성능 분석)

  • Jeon, Eun-Sung;Yang, Jang-Hoon;Kim, Bong-Ku
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.6A
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    • pp.577-582
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    • 2008
  • In this paper, we present a scheme to overcome the worst case complexity of the sphere decoder. If the number of visited nodes reaches the threshold, the detected symbol vector is determined between two candidate symbol vectors. One candidate symbol vector is obtained from the demodulated output of ZF receiver which is initial stage of the sphere decoder. The other candidate symbol vector consists of two sub-symbol vectors. The first sub-symbol vector consists of lately visited nodes running from the most upper layer. The second one contains corresponding demodulated outputs of ZF receiver. Between these two candidate symbol vectors, the one with smaller euclidean distance to the received symbol vector is chosen as detected symbol vector. In addition, we show the upper bound of symbol error rate performance for the sphere decoder using the proposed scheme. In the simulation, the proposed scheme shows the significant reduction of the worst case complexity while having negligible SER performance degradation.

Non-Metric Multidimensional Scaling using Simulated Annealing (담금질을 사용한 비계량 다차원 척도법)

  • Lee, Chang-Yong;Lee, Dong-Ju
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.6
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    • pp.648-653
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    • 2010
  • The non-metric multidimensional scaling (nMDS) is a method for analyzing the relation among objects by mapping them onto the Euclidean space. The nMDS is useful when it is difficult to use the concept of distance between pairs of objects due to non-metric dissimilarities between objects. The nMDS can be regarded as an optimization problem in which there are many local optima. Since the conventional nMDS algorithm utilizes the steepest descent method, it has a drawback in that the method can hardly find a better solution once it falls into a local optimum. To remedy this problem, in this paper, we applied the simulated annealing to the nMDS and proposed a new optimization algorithm which could search for a global optimum more effectively. We examined the algorithm using benchmarking problems and found that improvement rate of the proposed algorithm against the conventional algorithm ranged from 0.7% to 3.2%. In addition, the statistical hypothesis test also showed that the proposed algorithm outperformed the conventional one.

Augmented Reality Using Projective Information (비유클리드공간 정보를 사용하는 증강현실)

  • 서용덕;홍기상
    • Journal of Broadcast Engineering
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    • v.4 no.2
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    • pp.87-102
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    • 1999
  • We propose an algorithm for augmenting a real video sequence with views of graphics ojbects without metric calibration of the video camera by representing the motion of the video camera in projective space. We define a virtual camera, through which views of graphics objects are generated. attached to the real camera by specifying image locations of the world coordinate system of the virtual world. The virtual camera is decomposed into calibration and motion components in order to make full use of graphics tools. The projective motion of the real camera recovered from image matches has a function of transferring the virtual camera and makes the virtual camera move according to the motion of the real camera. The virtual camera also follows the change of the internal parameters of the real camera. This paper shows theoretical and experimental results of our application of non-metric vision to augmented reality.

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User control based OTT content search algorithms (사용자 제어기반 OTT 콘텐츠 검색 알고리즘)

  • Kim, Ki-Young;Suh, Yu-Hwa;Park, Byung-Joon
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.5
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    • pp.99-106
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    • 2015
  • This research is focused on the development of the proprietary database embedded in the OTT device, which is used for searching and indexing video contents, and also the development of the search algorithm in the form of the critical components of the interface application with the OTT's database to provide video query searching, such as remote control smartphone application. As the number of available channels has increased to anywhere from dozens to hundreds of channels, it has become increasingly difficult for the viewer to find programs they want to watch. To address this issue, content providers are now in need of methods to recommend programs catering to each viewer's preference. the present study aims provide of the algorithm which recommends contents of OTT program by analyzing personal watching pattern based on one's history.