• Title/Summary/Keyword: Entropy loss

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Off-design Performance Prediction of Centrifugal Pumps by Using TEIS model and Two-zone model (TEIS 모델과 두 영역 모델을 이용한 원심 펌프의 탈 설계 성능 예측)

  • Yoon, In-Ho;Baek, Je-Hyun
    • Proceedings of the KSME Conference
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    • 2000.04b
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    • pp.574-579
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    • 2000
  • In this study. an off-design performance prediction program for centrifugal pumps is developed. To estimate the losses in an impeller flow passage, two-zone model and two-element in series(TEIS) model are used. At impeller exit. the mixing process occurs with an increase in entropy. In two-zone model. there are both primary zone and secondary zone for an isentropic core flow and an average of all non-isentropic streamtubes respectively. The level of the core flow diffusion in an impeller was calculated by using TEIS model. While internal losses in an impeller an automatically estimated by using the above models, some empirical correlations far estimating external losses. far example, disk friction loss, recirculation loss and leakage loss are used. In order to analyze the vaneless diffuser flow. the momentum equations for the radial and tangential directions are used and solved together with continuity and energy equations.

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A Study on Bayes and Empirical Bayes Estimates of Poisson Means under Asymmetric Loss Functions (비대칭 손실함수 아래서 포아송평균의 베이즈와 경험적베이즈 추정의 연구)

  • Youn Shik Chung;Chan Soo Kim
    • The Korean Journal of Applied Statistics
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    • v.7 no.2
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    • pp.131-143
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    • 1994
  • Under the asymmetric losses (entropy loss and Stein loss), we find the classes of Bayes and empiricla Bayes estimates for estimating the Poisson means when the distributin of means are believed a priori. Following the idea of Efron and Morris (1973), we have a computer simulation to compute a relative savings loss of proposed estimates as compared to the classical estimates.

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One-step deep learning-based method for pixel-level detection of fine cracks in steel girder images

  • Li, Zhihang;Huang, Mengqi;Ji, Pengxuan;Zhu, Huamei;Zhang, Qianbing
    • Smart Structures and Systems
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    • v.29 no.1
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    • pp.153-166
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    • 2022
  • Identifying fine cracks in steel bridge facilities is a challenging task of structural health monitoring (SHM). This study proposed an end-to-end crack image segmentation framework based on a one-step Convolutional Neural Network (CNN) for pixel-level object recognition with high accuracy. To particularly address the challenges arising from small object detection in complex background, efforts were made in loss function selection aiming at sample imbalance and module modification in order to improve the generalization ability on complicated images. Specifically, loss functions were compared among alternatives including the Binary Cross Entropy (BCE), Focal, Tversky and Dice loss, with the last three specialized for biased sample distribution. Structural modifications with dilated convolution, Spatial Pyramid Pooling (SPP) and Feature Pyramid Network (FPN) were also performed to form a new backbone termed CrackDet. Models of various loss functions and feature extraction modules were trained on crack images and tested on full-scale images collected on steel box girders. The CNN model incorporated the classic U-Net as its backbone, and Dice loss as its loss function achieved the highest mean Intersection-over-Union (mIoU) of 0.7571 on full-scale pictures. In contrast, the best performance on cropped crack images was achieved by integrating CrackDet with Dice loss at a mIoU of 0.7670.

A new Ensemble Clustering Algorithm using a Reconstructed Mapping Coefficient

  • Cao, Tuoqia;Chang, Dongxia;Zhao, Yao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.7
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    • pp.2957-2980
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    • 2020
  • Ensemble clustering commonly integrates multiple basic partitions to obtain a more accurate clustering result than a single partition. Specifically, it exists an inevitable problem that the incomplete transformation from the original space to the integrated space. In this paper, a novel ensemble clustering algorithm using a newly reconstructed mapping coefficient (ECRMC) is proposed. In the algorithm, a newly reconstructed mapping coefficient between objects and micro-clusters is designed based on the principle of increasing information entropy to enhance effective information. This can reduce the information loss in the transformation from micro-clusters to the original space. Then the correlation of the micro-clusters is creatively calculated by the Spearman coefficient. Therefore, the revised co-association graph between objects can be built more accurately because the supplementary information can well ensure the completeness of the whole conversion process. Experiment results demonstrate that the ECRMC clustering algorithm has high performance, effectiveness, and feasibility.

Analysis of the Irreversibilities of a Vapor Compression Type Refrigerator (증기 압축식 냉동기의 비가역성 분석)

  • Shin, K.Y.;Jung, P.S.;Kim, S.Y.;Lee, S.C.
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.7 no.1
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    • pp.30-41
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    • 1995
  • The present paper investigated irreversibilities and energy flow of a vapor compression refrigerator. The entropy generation and the available energy dissipation in components of the system were analyzed by using experimental data. It was shown that the dissipated available energy in the compressor including electric motor was much more than those in other components. The effects of the pressure drop and heat loss on irreversibilities in the condenser and the evaporator were small in comparison with heat transfer.

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Extended Information Entropy via Correlation for Autonomous Attribute Reduction of BigData (빅 데이터의 자율 속성 감축을 위한 확장된 정보 엔트로피 기반 상관척도)

  • Park, In-Kyu
    • Journal of Korea Game Society
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    • v.18 no.1
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    • pp.105-114
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    • 2018
  • Various data analysis methods used for customer type analysis are very important for game companies to understand their type and characteristics in an attempt to plan customized content for our customers and to provide more convenient services. In this paper, we propose a k-mode cluster analysis algorithm that uses information uncertainty by extending information entropy to reduce information loss. Therefore, the measurement of the similarity of attributes is considered in two aspects. One is to measure the uncertainty between each attribute on the center of each partition and the other is to measure the uncertainty about the probability distribution of the uncertainty of each property. In particular, the uncertainty in attributes is taken into account in the non-probabilistic and probabilistic scales because the entropy of the attribute is transformed into probabilistic information to measure the uncertainty. The accuracy of the algorithm is observable to the result of cluster analysis based on the optimal initial value through extensive performance analysis and various indexes.

Prioritization decision for hazard ranking of water distribution network by cluster using the Entropy-TOPSIS method (Entropy-TOPSIS 기법을 활용한 군집별 상수도관망 위험도 관리순위 결정)

  • Park, Haekeum;Kim, Kibum;Hyung, Jinseok;Kim, Taehyeon;Koo, Jayong
    • Journal of Korean Society of Water and Wastewater
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    • v.35 no.6
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    • pp.517-531
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    • 2021
  • The water supply facilities of Korea have achieved a rapid growth, along with the other social infrastructures consisting a city, due to the phenomenon of urbanization according to economic development. Meanwhile, the level of water supply service demanded by consumer is also steadily getting higher in keeping with economic growth. However, as an adverse effect of rapid growth, the quantity of aged water supply pipes are increasing rapidly, Bursts caused by pipe aging brought about an enormous economic loss of about 6,161 billion won as of 2019. These problems are not only worsening water supply management, also increasing the regional gap in water supply services. The purpose of this study is to classify hazard evaluation indicators and to rank the water distribution network hazard by cluster using the TOPSIS method. In conclusion, in this study, the entropy-based multi-criteria decision-making methods was applied to rank the hazard management of the water distribution network, and the hazard management ranking for each cluster according to the water supply conditions of the county-level municipalities was determined according to the evaluation indicators of water outage, water leakage, and pipe aging. As such, the hazard ranking method proposed in this study can consider various factors that can impede the tap water supply service in the water distribution network from a macroscopic point of view, and it can be reflected in evaluating the degree of hazard management of the water distribution network from a preventive point of view. Also, it can be utilized in the implementation of the maintenance plan and water distribution network management project considering the equity of water supply service and the stability of service supply.

A Study on The Velocity Distribution in Closed Conduit by Using The Entropy Concept (엔트로피 개념을 이용한 관수로내의 유속분포에 관한 연구)

  • Choo, Tai Ho;Ok, Chi Youl;Kim, Jin Won;Maeng, Seung Jin
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.4B
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    • pp.357-363
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    • 2009
  • When yields the mean velocity of the closed conduit which is used generally, it is available to use Darcy Weisbach Friction Loss Head equation. But, it is inconvenient very because Friction Loss coefficient f is the function of Reynolds Number and Relative roughness (${\varepsilon}$/d). So, it is demanded more convenient equation to estimate. In order to prove the reliability and an accuracy of Chiu's velocity equation from the research which sees hereupon, proved agreement very well about measured velocity measurement data by using Laser velocimeter which is a non-insertion velocity measuring equipment from the closed conduit (Laser Doppler Velocimeter: LDV) and an insertion velocity measuring equipment and the Pitot tube which is a supersonic flow meter (Transit-Time Flowmeters). By proving theoretical linear-relation between maximum velocity and mean velocity in laboratory flume without increase and decrease of discharge, the equilibrium state of velocity in the closed conduit which reachs to equilibrium state corresponding to entropy parameter M value has a trend maintaining consistently this state. If entropy M value which is representing one section is determinated, mean velocity can be gotten only by measuring the velocity in the point appearing the maximum velocity. So, it has been proved to estimate simply discharge and it indicates that this method can be a theoretical way, which is the most important in the future, when designing, managing and operating the closed conduit.

Analysis of Change Detection Results by UNet++ Models According to the Characteristics of Loss Function (손실함수의 특성에 따른 UNet++ 모델에 의한 변화탐지 결과 분석)

  • Jeong, Mila;Choi, Hoseong;Choi, Jaewan
    • Korean Journal of Remote Sensing
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    • v.36 no.5_2
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    • pp.929-937
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    • 2020
  • In this manuscript, the UNet++ model, which is one of the representative deep learning techniques for semantic segmentation, was used to detect changes in temporal satellite images. To analyze the learning results according to various loss functions, we evaluated the change detection results using trained UNet++ models by binary cross entropy and the Jaccard coefficient. In addition, the learning results of the deep learning model were analyzed compared to existing pixel-based change detection algorithms by using WorldView-3 images. In the experiment, it was confirmed that the performance of the deep learning model could be determined depending on the characteristics of the loss function, but it showed better results compared to the existing techniques.

Numerical Study on Tip Clearance Effect on Performance of a Centrifugal Compressor (익단간극이 원심압축기 성능에 미치는 영향에 관한 수치해석적 연구)

  • Eum, Hark-Jin;Kang, Shin-Hyoung
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.27 no.3
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    • pp.389-397
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    • 2003
  • Effect of tip leakage flow on through flow and performance of a centrifugal compressor impeller was numerically studied using CFX-TASC flow. Seven different tip clearances were used to consider the influence of tip clearance on performance. Secondary flow and loss factor were evaluated to understand the loss mechanism inside the impeller due to tip leakage flow. The calculated results were circumferentially averaged along the passage and at the impeller exit for quantitative discussion. Tip clearance effect on Performance could be decomposed into inviscid and viscous components using one dimensional equation. The inviscid component is related with the specific work reduction and the viscous component is related with the additional entropy generation. Two components affected Performance equally. while efficiency drop was mainly influenced by viscous loss. Performance and efficiency drop due to tip clearance were proportional to the ratio of tip clearance to exit blade height. A simple model suggested in the present study predict performance and efficiency drop quite successfully.