• Title/Summary/Keyword: Structural Discrimination

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Blind Image Quality Assessment on Gaussian Blur Images

  • Wang, Liping;Wang, Chengyou;Zhou, Xiao
    • Journal of Information Processing Systems
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    • v.13 no.3
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    • pp.448-463
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    • 2017
  • Multimedia is a ubiquitous and indispensable part of our daily life and learning such as audio, image, and video. Objective and subjective quality evaluations play an important role in various multimedia applications. Blind image quality assessment (BIQA) is used to indicate the perceptual quality of a distorted image, while its reference image is not considered and used. Blur is one of the common image distortions. In this paper, we propose a novel BIQA index for Gaussian blur distortion based on the fact that images with different blur degree will have different changes through the same blur. We describe this discrimination from three aspects: color, edge, and structure. For color, we adopt color histogram; for edge, we use edge intensity map, and saliency map is used as the weighting function to be consistent with human visual system (HVS); for structure, we use structure tensor and structural similarity (SSIM) index. Numerous experiments based on four benchmark databases show that our proposed index is highly consistent with the subjective quality assessment.

Nonlinear damage detection using linear ARMA models with classification algorithms

  • Chen, Liujie;Yu, Ling;Fu, Jiyang;Ng, Ching-Tai
    • Smart Structures and Systems
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    • v.26 no.1
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    • pp.23-33
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    • 2020
  • Majority of the damage in engineering structures is nonlinear. Damage sensitive features (DSFs) extracted by traditional methods from linear time series models cannot effectively handle nonlinearity induced by structural damage. A new DSF is proposed based on vector space cosine similarity (VSCS), which combines K-means cluster analysis and Bayesian discrimination to detect nonlinear structural damage. A reference autoregressive moving average (ARMA) model is built based on measured acceleration data. This study first considers an existing DSF, residual standard deviation (RSD). The DSF is further advanced using the VSCS, and then the advanced VSCS is classified using K-means cluster analysis and Bayes discriminant analysis, respectively. The performance of the proposed approach is then verified using experimental data from a three-story shear building structure, and compared with the results of existing RSD. It is demonstrated that combining the linear ARMA model and the advanced VSCS, with cluster analysis and Bayes discriminant analysis, respectively, is an effective approach for detection of nonlinear damage. This approach improves the reliability and accuracy of the nonlinear damage detection using the linear model and significantly reduces the computational cost. The results indicate that the proposed approach is potential to be a promising damage detection technique.

Insulation Diagnostics and Maintenance of Submarine Medium Voltage Power Cable Systems (해저 케이블 시스템의 열화진단 및 유지보수)

  • 이동영
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.17 no.3
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    • pp.80-86
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    • 2003
  • A study on the insulation aging assessment and maintenance for submarine medium voltage power cable systems has been performed The purpose of this work is the economic discrimination and maintenance of bad cables which is likely to cause cable system failure. 1 have found that aging status of submarine cable systems are very poor and in progress. Therefore, we have the replacement of cable terminations and repeat the diagnostic measurement Insulation status were improved with the replacement of cable terminations. I have confirmed, with the electrical md structural analysis of terminations, that the poor aging status of cables are mainly caused not by the cable insulations but by the aging of cable terminations. From the above results, I have also confirmed that the domestic diagnostic system is successful and convenient for the discrimination and maintenance of the damaged cables economically.

A Study on the Factors Affecting the Success of Intelligent Public Service: Information System Success Model Perspective (판별시스템 중심의 지능형공공서비스 성공에 영향을 미치는 요인 연구: 정보시스템성공모형을 중심으로)

  • Kim, Jung Yeon;Lee, Kyoung Su;Kwon, Oh Byung
    • The Journal of Information Systems
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    • v.32 no.1
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    • pp.109-146
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    • 2023
  • Purpose With Intelligent public service (IPS), it is possible to automate the quality of civil affairs, provide customized services for citizens, and provide timely public services. However, empirical studies on factors for the successful use of IPS are still insufficient. Hence, the purpose of this study is to empirically analyze the factors that affect the success of IPS with classification function. ISSM (Information System Success Model) is considered as the underlying research model, and how the algorithm quality, data quality, and environmental quality of the discrimination system affect the relationship between utilization intentions is analyzed. Design/methodology/approach In this study, a survey was conducted targeting users using IPS. After giving them a preliminary explanation of the intelligent public service centered on the discrimination system, they briefly experienced two types of IPS currently being used in the public sector. Structural model analysis was conducted using Smart-PLS 4.0 with a total of 415 valid samples. Findings First, it was confirmed that algorithm quality and data quality had a significant positive (+) effect on information quality and system quality. Second, it was confirmed that information quality, system quality, and environmental quality had a positive (+) effect on the use of IPS. Thirdly, it was confirmed that the use of IPS had a positive (+) effect on the net profit for the use of IPS. In addition, the moderating effect of the degree of knowledge on AI, the perceived accuracy of discriminative experience and IPS, and the user was analyzed. The results suggest that ISSM and TOE framework can expand the understanding of the success of IPS.

Structural Quality Defect Discrimination Enhancement using Vertical Energy-based Wavelet Feature Generation (구조물의 품질 결함 변별력 증대를 위한 수직 에너지 기반의 웨이블릿 Feature 생성)

  • Kim, Joon-Seok;Jung, Uk
    • Journal of Korean Society for Quality Management
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    • v.36 no.2
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    • pp.36-44
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    • 2008
  • In this paper a novel feature extraction and selection is carried out in order to improve the discriminating capability between healthy and damaged structure using vibration signals. Although many feature extraction and selection algorithms have been proposed for vibration signals, most proposed approaches don't consider the discriminating ability of features since they are usually in unsupervised manner. We proposed a novel feature extraction and selection algorithm selecting few wavelet coefficients with higher class discriminating capability for damage detection and class visualization. We applied three class separability measures to evaluate the features, i.e. T test statistics, divergence, and Bhattacharyya distance. Experiments with vibration signals from truss structure demonstrate that class separabilities are significantly enhanced using our proposed algorithm compared to other two algorithms with original time-based features and Fourier-based ones.

Insulation Aging Diagnostics of Submarine Medium Voltage Power Cables (배전급 해저케이블의 절연열화진단)

  • Mo, Jong-Myung;Yi, Dong-Young;Song, Kwang-Yong
    • Proceedings of the KIEE Conference
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    • 2001.11b
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    • pp.149-152
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    • 2001
  • In this work, we have conducted insulation aging assessment and maintenance for submarine medium voltage power cable systems to discriminate and maintain bad cables economically. We have found that aging status of submarine cable systems are very poor and in progress. We have found that insulation status were improved with the replacement of cable terminations. We have confirmed with the electrical and structural analysis of terminations, that the poor aging status of cables are mainly caused not by the cable insulations but by the aging of cable terminations. From the above results, we have also confirmed that the domestic diagnostic system is successful and convenient for the discrimination and maintenance of the damaged cables economically.

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Artificial Neural Network Discrimination of Multi-PD Sources Detected by UHF Sensor

  • Lee, Kang-Won;Jang, Dong-Uk;Park, Jae-Yeol;Kang, Seong-Hwa;Lim, Kee-Joe
    • KIEE International Transactions on Electrophysics and Applications
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    • v.3C no.1
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    • pp.5-9
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    • 2003
  • The waveforms of partial discharges (PDs) imply physical and structural properties of PD sources, so analyzing them give us information on the kind of PD sources and the location. Waveforms of PD as a time series function have variable amplitudes but sustain a certain uniform shape, which shows well the characteristics of the waveforms and frequency region. They can also be used as parameters having time and frequency information of PD signals and applied to classification of multiple PDs sources via Artificial Neural Network with back propagation (BP) learning.

A Positive Analysis of Housing Price Model in Seoul: Applications of Structural Equation Modeling

  • Kim, Kyong-Hoon;Lee, Yoon-Sun;Ahn, Byung-Ju;Kim, Jae-Jun
    • Architectural research
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    • v.9 no.2
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    • pp.27-35
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    • 2007
  • Our nation has a problem with discrimination of income distribution and inefficient of resources distribution caused by real estate price rising from a sudden economy growth and industrialization. Specially, in recent years, there is a great disparity of apartment price between the north and south of the Han river. Because the housing price is decided by the immanent value of a house and neighborhood effects of the regional where the house is situated, the housing price is occurred difference. The purpose of study was to analyze the influence of various factors of housing price. Also, this study tried to predict real estate market and to establish previous effective real estate policy. In this study, we analyzed the differences of housing price determinants about apartment developments between the north and south of the Han river, and found the important factors that affect the housing price using Structural Equation Modeling(SEM). As a result of this study, the older the buildings are, the more the housing price and the housing price rising ratio have increased, in Gang Nam area. This reason is that these have large possibility to be reconstructed and many convenient facilities, in this area. In the case of Kang Buk area, the increase rate of housing price are so low that they couldn't take effect on the housing price and they were declined. So to speak, constructing the infrastructure which takes effect on the increase rate of housing price is very urgent.

A Study on the Influence of Gender Gap on Economic Structural Improvement and Economic Growth (성별 격차가 경제구조 고도화 및 경제성장에 미치는 영향에 관한 연구)

  • Kim, Sangyoon;Seo, Jonggook
    • Journal of the Society of Disaster Information
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    • v.13 no.4
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    • pp.499-510
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    • 2017
  • Based on "The Global Gender Gap Report" by World Economic Forum, this study identified factors of gender gap and analyzed a relationship between income growth and economic structural improvement with 145 countries. Consequently, sex ratio has a positive relationship with GNI growth rate and ICT development index. Female illiteracy has a negative relationship with only GNI growth rate, and female seat of parliament has a positive relationship with only with only GNI growth rate. Female labor participation rate has a positive relationship with inly ICT development index. These results confirmed the importance of future female labor force. With these results, many countries will need to reconsider discrimination against women and establish strategy based on an institution and a policy to prepare the 4th industrial revolution.

Comparison of Customer Satisfaction Indices Using Different Methods of Weight Calculation (가중치 산출방법에 따른 고객만족도지수의 비교)

  • Lee, Sang-Jun;Kim, Yong-Tae;Kim, Seong-Yoon
    • Journal of Digital Convergence
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    • v.11 no.12
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    • pp.201-211
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    • 2013
  • This study compares Customer Satisfaction Index(CSI) and the weight for each dimension by applying various methods of weight calculation and attempts to suggest some implications. For the purpose, the study classified the methods of weight calculation into the subjective method and the statistical method. Constant sum scale was used for the subjective method, and the statistical method was again segmented into correlation analysis, principal component analysis, factor analysis, structural equation model. The findings showed that there is difference between the weights from the subjective method and the statistical method. The order of the weights by the analysis methods were classified with similar patterns. Besides, the weight for each dimension by different methods of weight calculation showed considerable deviation and revealed the difference of discrimination and stability among the dimensions. Lastly, the CSI calculated by various methods of weight calculation showed to be the highest in structural equation model, followed by in the order of regression analysis, correlation analysis, arithmetic mean, principal component analysis, constant sum scale and factor analysis. The CSI calculated by each method showed to have statistically significant difference.