• Title/Summary/Keyword: Distance measures

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Two model comparisons of software reliability analysis for Burr type XII distribution

  • An, Jeong-Hyang
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.4
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    • pp.815-823
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    • 2012
  • In this paper reliability growth model in which the operating time between successive failure is a continuous random variable is proposed. This model is for Burr type XII distribution with two parameters which is discussed in two versions: the order statistics and non-homogeneous Poisson process. The two software reliability measures are obtained. The performance for two versions of the suggested model is tested on real data set by U-plot and Y-plot using Kolmogorov distance.

Study on the Development of Sensors for Distance Measure Using Ultrasonic (초음파 이용 거리측정을 위한 센서 개발에 관한 연구)

  • Park, Geun Chul;Lee, Seung Hee;Park, Chang Soo;Kim, Dong Won;Kim, Won Taek;Jeon, Gye Rok
    • Journal of Sensor Science and Technology
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    • v.23 no.1
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    • pp.46-50
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    • 2014
  • In this paper, we report a novel algorithm based on phase displacement, which supplements conventional TOF methods for distance measurement using an ultrasonic wave. The proposed algorithm roughly measures the distance between the transmission part and the receiving part by using the initial TOF. Thereafter, the precise distance is determined by measuring the phase displacement value between the synchronizing transmission signal and the signal obtained at the receiving end. A distance measurement experiment using a micrometer was performed to verify the accuracy of the ultrasonic wave sensor system. We found that the mean errors from the one adopting the distance measurement algorithm based on phase displacement varied from a minimum of 0.03 mm to a maximum of 0.09 mm. In addition, the standard deviation varied from a minimum of 0.04 mm to a maximum of 0.07 mm, thus giving a precision of ${\pm}0.1$ mm.

Numerical Performance Analysis of Obstacle Avoidance Method for a Mobile Robot (이동 로봇 장애물 회피 방법의 수치적 성능 분석)

  • Kim, Kwang-Jin;Ko, Nak-Yong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.2
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    • pp.401-407
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    • 2012
  • This paper analyzes performance of major obstacle avoidance methods. For the analysis, numerical performance indexes are proposed: motion distance to goal point, motion time, distance to obstacles, and smoothness of the motion. Especially, the index of smoothness measures efficiency of the motion using the angular acceleration and jerk of the robot heading. Four major obstacle avoidance methods are compared in terms of the performance indexes. The four methods are artificial potential field(APF) method, elastic force(EF) method, APF with virtual distance, and EF with virtual distance. Through simulation, the four methods are compared and features of the methods are explored.

An Efficient Color Edge Detection Using the Mahalanobis Distance

  • Khongkraphan, Kittiya
    • Journal of Information Processing Systems
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    • v.10 no.4
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    • pp.589-601
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    • 2014
  • The performance of edge detection often relies on its ability to correctly determine the dissimilarities of connected pixels. For grayscale images, the dissimilarity of two pixels is estimated by a scalar difference of their intensities and for color images, this is done by using the vector difference (color distance) of the three-color components. The Euclidean distance in the RGB color space typically measures a color distance. However, the RGB space is not suitable for edge detection since its color components do not coincide with the information human perception uses to separate objects from backgrounds. In this paper, we propose a novel method for color edge detection by taking advantage of the HSV color space and the Mahalanobis distance. The HSV space models colors in a manner similar to human perception. The Mahalanobis distance independently considers the hue, saturation, and lightness and gives them different degrees of contribution for the measurement of color distances. Therefore, our method is robust against the change of lightness as compared to previous approaches. Furthermore, we will introduce a noise-resistant technique for determining image gradients. Various experiments on simulated and real-world images show that our approach outperforms several existing methods, especially when the images vary in lightness or are corrupted by noise.

Categorical Data Clustering Analysis Using Association-based Dissimilarity (연관성 기반 비유사성을 활용한 범주형 자료 군집분석)

  • Lee, Changki;Jung, Uk
    • Journal of Korean Society for Quality Management
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    • v.47 no.2
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    • pp.271-281
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    • 2019
  • Purpose: The purpose of this study is to suggest a more efficient distance measure taking into account the relationship between categorical variables for categorical data cluster analysis. Methods: In this study, the association-based dissimilarity was employed to calculate the distance between two categorical data observations and the distance obtained from the association-based dissimilarity was applied to the PAM cluster algorithms to verify its effectiveness. The strength of association between two different categorical variables can be calculated using a mixture of dissimilarities between the conditional probability distributions of other categorical variables, given these two categorical values. In particular, this method is suitable for datasets whose categorical variables are highly correlated. Results: The simulation results using several real life data showed that the proposed distance which considered relationships among the categorical variables generally yielded better clustering performance than the Hamming distance. In addition, as the number of correlated variables was increasing, the difference in the performance of the two clustering methods based on different distance measures became statistically more significant. Conclusion: This study revealed that the adoption of the relationship between categorical variables using our proposed method positively affected the results of cluster analysis.

Video Content Indexing using Kullback-Leibler Distance

  • Kim, Sang-Hyun
    • International Journal of Contents
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    • v.5 no.4
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    • pp.51-54
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    • 2009
  • In huge video databases, the effective video content indexing method is required. While manual indexing is the most effective approach to this goal, it is slow and expensive. Thus automatic indexing is desirable and recently various indexing tools for video databases have been developed. For efficient video content indexing, the similarity measure is an important factor. This paper presents new similarity measures between frames and proposes a new algorithm to index video content using Kullback-Leibler distance defined between two histograms. Experimental results show that the proposed algorithm using Kullback-Leibler distance gives remarkable high accuracy ratios compared with several conventional algorithms to index video content.

Statistical Fingerprint Recognition Matching Method with an Optimal Threshold and Confidence Interval

  • Hong, C.S.;Kim, C.H.
    • The Korean Journal of Applied Statistics
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    • v.25 no.6
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    • pp.1027-1036
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    • 2012
  • Among various biometrics recognition systems, statistical fingerprint recognition matching methods are considered using minutiae on fingerprints. We define similarity distance measures based on the coordinate and angle of the minutiae, and suggest a fingerprint recognition model following statistical distributions. We could obtain confidence intervals of similarity distance for the same and different persons, and optimal thresholds to minimize two kinds of error rates for distance distributions. It is found that the two confidence intervals of the same and different persons are not overlapped and that the optimal threshold locates between two confidence intervals. Hence an alternative statistical matching method can be suggested by using nonoverlapped confidence intervals and optimal thresholds obtained from the distributions of similarity distances.

Improving measurement range of infrared proximity sensor using multiple exposure output and HDR technique (다중노출 출력과 HDR 기법을 이용한 적외선 근접센서 측정 범위 향상 방법)

  • Cho, Se-Hyoung
    • Journal of IKEEE
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    • v.22 no.4
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    • pp.907-915
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    • 2018
  • This paper proposes a method to improve the performance of low cost infrared distance sensor. Infrared distance sensor measures the intensity of reflected light and converts it into distance. The proposed method improves the sensing distance of the sensor and makes it operate robustly in various lighting environments. This is achieved by extracting the characteristic curves of the sensor and applying the HDR (High Dynamic Range) technique. The output value of the sensor was obtained by varying the intensity of the infrared input and the exposure time, and the characteristic curve of the sensor was extracted from it.

Widerange Microphone System Using 3D Range Sensor (3D 거리 센서를 이용한 강의용 광역 마이크 시스템)

  • Oh, Woojin
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.10
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    • pp.1448-1451
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    • 2021
  • In this paper, 3D range sensor is applied to the sensor-based widerange microphone system for lectures. Since the 2D range sensor measures the shortest distance of the speaker, an error occurs and the performance is degraded. The 3D sensor provides a 160×60 distance image so that the position of the speaker can be obtained with accuracy. We propose a method for obtaining the distance per pixel required to determine the absolute position of the speaker from the distance image. The proposed array microphone system using the 3D sensor shows the improvement of 0.8~1.5dB compared to the previous works using 2D sensor.

Locational Characteristics of Highly Pathogenic Avian Influenza(HPAI) Outbreak Farm (고병원성 조류인플루엔자(HPAI) 발생농가 입지특성)

  • KIM, Dong-Hyeon;BAE, Sun-Hak
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.4
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    • pp.140-155
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    • 2020
  • This study was conducted to identify the location characteristics of infected farms in the areas where livestock diseases were clustered(southern Gyeonggi-do and Chungcheong-do), analyze the probability of disease occurrence in poultry farms, find out the areas corresponding to the conditions, and use them as the basis for prevention of livestock diseases, selection of discriminatory prevention zones, and establishment of prevention strategies and as the basic data for complementary measures. The increase of one poultry farm within a radius of 3-kilometers increases the risk of HPAI infection by 10.9% compared to the previous situation. The increase of 1m in distance from major roads with two lanes or more reduces the probability of HPAI infection by 0.001% compared to the previous situation. If the distance of the poultry farm located with 15 kilometers from a major migratory bird habitat increases by 15 to 30 kilometers, the chance of infection with HPAI is reduced by 46.0%. And if the distance of the same poultry farm increase by more than 30 kilometers, the chances of HPAI infection are reduced by 88.5%. Based on the results of logistic regression, the predicted probability was generated and the actual area of the location condition with 'more than 15 poultry farms within 3km a radius of, within 1km distance from major roads, and within 30km distance from major migratory birds habitat was determined and the infection rate was measured. It is expected that the results of this study will be used as basic data for preparing the data and supplementary measures when the quarantine authorities establish discriminatory quarantine areas and prevention strategies, such as preventive measures for the target areas and farms, or control of vehicles, by identifying the areas where livestock diseases are likely to occur in the region.