• Title/Summary/Keyword: KLD

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Damage detection using the improved Kullback-Leibler divergence

  • Tian, Shaohua;Chen, Xuefeng;Yang, Zhibo;He, Zhengjia;Zhang, Xingwu
    • Structural Engineering and Mechanics
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    • v.48 no.3
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    • pp.291-308
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    • 2013
  • Structural health monitoring is crucial to maintain the structural performance safely. Moreover, the Kullback-Leibler divergence (KLD) is applied usually to asset the similarity between different probability density functions in the pattern recognition. In this study, the KLD is employed to detect the damage. However the asymmetry of the KLD is a shortcoming for the damage detection, to overcoming this shortcoming, two other divergences and one statistic distribution are proposed. Then the damage identification by the KLD and its three descriptions from the symmetric point of view is investigated. In order to improve the reliability and accuracy of the four divergences, the gapped smoothing method (GSM) is adopted. On the basis of the damage index approach, the new damage index (DI) for detect damage more accurately based on the four divergences is developed. In the last, the grey relational coefficient and hypothesis test (GRCHT) is utilized to obtain the more precise damage identification results. Finally, a clear remarkable improvement can be observed. To demonstrate the feasibility and accuracy of the proposed method, examples of an isotropic beam with different damage scenarios are employed so as to check the present approaches numerically. The final results show that the developed approach successfully located the damaged region in all cases effect and accurately.

A Study on Particle Filter based on KLD-Resampling for Wireless Patient Tracking

  • Ly-Tu, Nga;Le-Tien, Thuong;Mai, Linh
    • Industrial Engineering and Management Systems
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    • v.16 no.1
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    • pp.92-102
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    • 2017
  • In this paper, we consider a typical health care system via the help of Wireless Sensor Network (WSN) for wireless patient tracking. The wireless patient tracking module of this system performs localization out of samples of Received Signal Strength (RSS) variations and tracking through a Particle Filter (PF) for WSN assisted by multiple transmit-power information. We propose a modified PF, Kullback-Leibler Distance (KLD)-resampling PF, to ameliorate the effect of RSS variations by generating a sample set near the high-likelihood region for improving the wireless patient tracking. The key idea of this method is to approximate a discrete distribution with an upper bound error on the KLD for reducing both location error and the number of particles used. To determine this bound error, an optimal algorithm is proposed based on the maximum gap error between the proposal and Sampling Important Resampling (SIR) algorithms. By setting up these values, a number of simulations using the health care system's data sets which contains the real RSSI measurements to evaluate the location error in term of various power levels and density nodes for all methods. Finally, we point out the effect of different power levels vs. different density nodes for the wireless patient tracking.

Selective Feature Extraction Method Between Markov Transition Probability and Co-occurrence Probability for Image Splicing Detection (접합 영상 검출을 위한 마르코프 천이 확률 및 동시발생 확률에 대한 선택적 특징 추출 방법)

  • Han, Jong-Goo;Eom, Il-Kyu;Moon, Yong-Ho;Ha, Seok-Wun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.4
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    • pp.833-839
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    • 2016
  • In this paper, we propose a selective feature extraction algorithm between Markov transition probability and co-occurrence probability for an effective image splicing detection. The Features used in our method are composed of the difference values between DCT coefficients in the adjacent blocks and the value of Kullback-Leibler divergence(KLD) is calculated to evaluate the differences between the distribution of original image features and spliced image features. KLD value is an efficient measure for selecting Markov feature or Co-occurrence feature because KLD shows non-similarity of the two distributions. After training the extracted feature vectors using the SVM classifier, we determine whether the presence of the image splicing forgery. To verify our algorithm we used grid search and 6-folds cross-validation. Based on the experimental results it shows that the proposed method has good detection performance with a limited number of features compared to conventional methods.

Effects of Corporate Social Responsibility on Financial Performancein the U.S. Hotel Industry (미국 호텔의 사회적 책임이 재무적 성과에 미치는 영향)

  • Kim, Woo-Hyuk
    • Journal of Service Research and Studies
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    • v.8 no.3
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    • pp.25-35
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    • 2018
  • Initiatives for corporate social responsibility (CSR) have often served as sources of competitive advantage in the business world. Although the adoption of CSR practices in the hotel industry continues to increase, empirical research on the relationship between them and financial performance in the industryremains scarce. The purpose of this study was to ascertain the effects of various dimensions of CSR on the financial performance of corporations in the U.S. hotel industry. Data include Kinder, Lydenburg & Domini social performance scores and Compustat data of hotels from 1991 to 2015 identified using a Standard Industrial Classification code. Results of ordinary least squares regression using Stata revealed that efforts toward CSR have significantly affected the financial performance of numerous hotels. Such findings can initiate discussions and inspire future research on CSR in the hospitality industry.

An Input System to Prevent Keylog-Hacking for User Information Based on Web (웹기반 사용자 정보 키로그해킹 방지를 위한 입력 시스템)

  • Jang Uk;Choi Hyon-Young;Min Sung-Gi
    • Proceedings of the Korea Information Processing Society Conference
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    • 2006.05a
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    • pp.959-962
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    • 2006
  • 최근 고객의 컴퓨터와 개인 정보를 보호하기 위하여 개인용 컴퓨터 방화벽과 바이러스 백신의 사용이 점차 증가하고 있다. 그러나 개인용 컴퓨터 방화벽과 바이러스 백신은 이미 존재하거나 발견된 해킹 툴과 바이러스에 대해서만 개인 정보를 보호하기 때문에 한계가 존재한다. 따라서 원천적으로 개인 정보의 유출을 막을 수 있는 솔루션이 필요하다. 그 대표적인 것이 키로그(Keylog) 해킹방지 시스템이다. 이 시스템에서는 키보드의 입력을 암호화하거나 별도의 키보드 드라이버를 생성하여 개인 정보를 보호한다. 하지만 암호화하기 전 단계인 하드웨어 단계에서 개인 정보 유출과 오류로 인한 시스템의 미설치의 문제점이 여전히 존재한다. 본 논문에서는 웹사이트에서 발생하는 이러한 문제점들을 극복하기 위한 하나의 방법으로 KLD(Keyboard Logger Defense) 시스템을 제안하였다. 이 시스템은 키보드 사용으로 발생되는 근본적인 문제점을 해결하기 위하여 웹기반 마우스 입력방식을 사용하였고, 테스트 결과 기존 키로거(Keylogger) 프로그램에 대해서 입력한 키 데이터가 보호됨을 알 수 있었다.

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Factor Graph-based Multipath-assisted Indoor Passive Localization with Inaccurate Receiver

  • Hao, Ganlin;Wu, Nan;Xiong, Yifeng;Wang, Hua;Kuang, Jingming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.2
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    • pp.703-722
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    • 2016
  • Passive wireless devices have increasing civilian and military applications, especially in the scenario with wearable devices and Internet of Things. In this paper, we study indoor localization of a target equipped with radio-frequency identification (RFID) device in ultra-wideband (UWB) wireless networks. With known room layout, deterministic multipath components, including the line-of-sight (LOS) signal and the reflected signals via multipath propagation, are employed to locate the target with one transmitter and a single inaccurate receiver. A factor graph corresponding to the joint posterior position distribution of target and receiver is constructed. However, due to the mixed distribution in the factor node of likelihood function, the expressions of messages are intractable by directly applying belief propagation on factor graph. To this end, we approximate the messages by Gaussian distribution via minimizing the Kullback-Leibler divergence (KLD) between them. Accordingly, a parametric message passing algorithm for indoor passive localization is derived, in which only the means and variances of Gaussian distributions have to be updated. Performance of the proposed algorithm and the impact of critical parameters are evaluated by Monte Carlo simulations, which demonstrate the superior performance in localization accuracy and the robustness to the statistics of multipath channels.

Development of a Traffic Simulation Program for Uninterrupted Traffic Flow Facilities (연속류 도로의 한국형 모의실험 프로그램 개발)

  • 최대순
    • Proceedings of the Korea Society for Simulation Conference
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    • 1997.04a
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    • pp.45-60
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    • 1997
  • 본연구의 목적은 1994년과 1995년의 연구 결과를 토대로 고속국도 교통류의 차량 추종, 차선 변경 특성을 현장 조사 자료를 통하여 분석·규명하고, 국내 고속도로의 교통류 특성을 반영할 수 있는 한국형 고속국도 모의실험 모형을 개발하는데 있다. 본 연구의 주요 결과는 다음과 같다. ▶ 국내 고속국도 교통류의 차두시간, 속도, 차량군의 크기, 차선 변 경, 중차량의 영향 등의 특성을 조사·분석하여 관련 매개변수와 모형식을 도출하였다. ▶ 차량 생성 모형은 개별 차량의 차두시간, 속도를 이용하여 구축하였으며, 중차량의 구성 비 율에 따른 속도 변화를 연구하여 그 결과를 모형 구축에 응용하였다. ▶ 차량 추종 모형은 1995년 연구에서 검증된 PITT-KLD 모형에 기반을 두었으며, 현장 실측 자료를 분석하여 차량 추종과 관련된 매개변수들을 설정하였다. ▶ 차선 변경 모형은 기본적으로 간격 수락 모형을 이용하였으며, 차선 변경시 임계 간격을 국내 운전자들의 유형에 따라 10가지로 설 정하였다. 차선 변경 확률은 현장 조사 자료를 기초로 한 경험적 모형을 구축하여 선정하였 으며, 마코프 연쇄 기법과도 비교·검토하였다. ▶ 개발된 모의실험 모형을 비교·평가하기 위 해 고속국도 합류부의 현장 조사 자료와 모의실험 모형을 비교·평가한 결과, 합류 이전 단 계에서는 실측치와 모형의 통계량이 어느 정도 유사한 양상을 보이지만 합류 이후 단계에서 는 차이를 나타내고 잇다.

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Distributed Target Localization with Inaccurate Collaborative Sensors in Multipath Environments

  • Feng, Yuan;Yan, Qinsiwei;Tseng, Po-Hsuan;Hao, Ganlin;Wu, Nan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.5
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    • pp.2299-2318
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    • 2019
  • Location-aware networks are of great importance for both civil lives and military applications. Methods based on line-of-sight (LOS) measurements suffer sever performance loss in harsh environments such as indoor scenarios, where sensors can receive both LOS and non-line-of-sight (NLOS) measurements. In this paper, we propose a data association (DA) process based on the expectation maximization (EM) algorithm, which enables us to exploit multipath components (MPCs). By setting the mapping relationship between the measurements and scatters as a latent variable, coefficients of the Gaussian mixture model are estimated. Moreover, considering the misalignment of sensor position, we propose a space-alternating generalized expectation maximization (SAGE)-based algorithms to jointly update the target localization and sensor position information. A two dimensional (2-D) circularly symmetric Gaussian distribution is employed to approximate the probability density function of the sensor's position uncertainty via the minimization of the Kullback-Leibler divergence (KLD), which enables us to calculate the expectation step with low computational complexity. Moreover, a distributed implementation is derived based on the average consensus method to improve the scalability of the proposed algorithm. Simulation results demonstrate that the proposed centralized and distributed algorithms can perform close to the Monte Carlo-based method with much lower communication overhead and computational complexity.

Centroid-model based music similarity with alpha divergence (알파 다이버전스를 이용한 무게중심 모델 기반 음악 유사도)

  • Seo, Jin Soo;Kim, Jeonghyun;Park, Jihyun
    • The Journal of the Acoustical Society of Korea
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    • v.35 no.2
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    • pp.83-91
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    • 2016
  • Music-similarity computation is crucial in developing music information retrieval systems for browsing and classification. This paper overviews the recently-proposed centroid-model based music retrieval method and applies the distributional similarity measures to the model for retrieval-performance evaluation. Probabilistic distance measures (also called divergence) compute the distance between two probability distributions in a certain sense. In this paper, we consider the alpha divergence in computing distance between two centroid models for music retrieval. The alpha divergence includes the widely-used Kullback-Leibler divergence and Bhattacharyya distance depending on the values of alpha. Experiments were conducted on both genre and singer datasets. We compare the music-retrieval performance of the distributional similarity with that of the vector distances. The experimental results show that the alpha divergence improves the performance of the centroid-model based music retrieval.

A Study on the Effect of Residential Environment Characteristics on Residential Satisfaction, Residential Ownership Consciousness, and Housing Movement: Focusing on MZ Generation in the COVID-19 Period (주거환경특성이 주거만족도, 주거보유의식과 주거이동에 미치는 영향 연구: 코로나19 시기의 MZ세대를 중심으로)

  • Yun-Hui, Hwang;Jaeho, Chung
    • Land and Housing Review
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    • v.14 no.1
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    • pp.47-66
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    • 2023
  • This study reviews prior studies on the residential environment characteristics, residential satisfaction, residential ownership consciousness and housing movement of MZ generation and analyze the structural equation models using the 2020 Korea Housing Survey data. Using 14 residential characteristics based on three classifications, we explore the effects on residential satisfaction, residential ownership consciousness, and housing movement. The empirical results are summarized as follows. First, based on factor analysis with Varimax of principal component analysis, parking facility items were excluded from the analysis by hindering validity, and as a result, KMO was 0.925 and Bartlett's test result showed a significant probability of less than 0.01. This indicates that the factor analysis model was suitable. Second, the results of the structural equation analysis for the MZ generation show that the surrounding environment, which is a potential variable of the residential environment characteristics, was statistically significant, but the accessibility and convenience were not statistically significant. Third, we find that the higher the satisfaction with the accessibility of commercial facilities, the more significant the sense of housing ownership appears. This suggests that the younger generation such as the MZ generation has a stronger desire for consumption. Fourth, the overall housing satisfaction of the MZ generation was significant for housing movement, but not for housing ownership. Compared to the industrialized generation, the baby boom generation, and the X generation, MZ generation shows distinct factors for housing satisfaction, housing ownership, and housing movement. Therefore, the residential environment characteristics of the residential survey should be improved and supplemented following the trend of the times. In addition, the government and local governments should prioritize actively participating in the housing market that suits the environment and characteristics of the target generation. Finally, our study provides implications regarding the need for housing-related research on how differ in special temporal situations such as COVID-19 in the future.