• Title/Summary/Keyword: Loss parameter

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High Efficiency and High Power-Factor Power Supply for LED Lighting Equipment (고효율 고역률 LED 조명장치용 전원공급장치)

  • Jeong, Gang-Youl
    • The Journal of Korean Institute of Information Technology
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    • v.16 no.11
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    • pp.23-34
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    • 2018
  • This paper presents the high efficiency and high power-factor power supply for LED lighting equipment. The proposed power supply is the single-stage power structure consisted of the full-bridge diode rectifier and flyback converter, and thus the power-factor correction and output voltage regulation are performed simultaneously using only one controller IC and one power semiconductor switch. Furthermore, the proposed power supply reduces the voltage stress and switching loss of main switch using the regenerative snubber, and it improves the system efficiency using the synchronous rectifier. The applied synchronous rectifier is the new voltage-driven type and its operation and construction are simple. In this paper, the operation principle of proposed power supply is explained through the operation analyses of its power-factor correction and main power conversion parts and the operation of synchronous rectifier is described, briefly. Also, a design example of the power circuit of 40W-class prototype is shown and the operation characteristics of proposed power supply are validated through the experimental results of the implemented prototype by the designed circuit parameter.

Goodness of Fit Tests for the Exponential Distribution based on Multiply Progressive Censored Data (다중 점진적 중도절단에서 지수분포의 적합도 검정)

  • Yun, Hyejeong;Lee, Kyeongjun
    • Journal of the Korean Data Analysis Society
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    • v.20 no.6
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    • pp.2813-2827
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    • 2018
  • Progressive censoring schemes have become quite popular in reliability study. Under progressive censored data, however, some units can be failed between two points of observation with exact times of failure of these units unobserved. For example, loss may arise in life-testing experiments when the failure times of some units were not observed due to mechanical or experimental difficulties. Therefore, multiply progressive censoring scheme was introduced. So, we derives a maximum likelihood estimator of the parameter of exponential distribution. And we introduced the goodness-of-fit test statistics using order statistic and Lorenz curve. We carried out Monte Carlo simulation to compare the proposed test statistics. In addition, real data set have been analysed. In Weibull and chi-squared distributions, the test statistics using Lorenz curve are more powerful than test statistics using order statistics.

Metal Foam Flow Field Effect on PEMFC Performance (금속 폼 유로가 고분자전해질 연료전지 성능에 미치는 영향)

  • Kim, Junseob;Kim, Junbom
    • Applied Chemistry for Engineering
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    • v.32 no.4
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    • pp.442-448
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    • 2021
  • Flow field is an important parameter for polymer electrolyte membrane fuel cell (PEMFC) performance to have an effect on the reactant supply, heat and water diffusion, and contact resistance. In this study, PEMFC performance was investigated using Cu foam flow field at the cathode of 25 cm2 unit cell. Polarization curve and electrochemical impedance spectroscopy were performed at different pressure and relative humidity conditions. The Cu foam showed lower cell performance than that of serpentine type due to its high ohmic resistance, but lower activation and concentration loss due to the even reactant distribution of porous structure. Cu foam has the advantage of effective water transport because of its hydrophobicity. However, it showed low membrane hydration at low humidity condition. The metal foam flow field could improve fuel cell performance with a uniform pressure distribution and effective water management, so future research on the properties of metal foam should be conducted to reduce electrical resistance of bipolar plate.

Application and optimal design of the bionic guide vane to improve the safety serve performances of the reactor coolant pump

  • Liu, Haoran;Wang, Xiaofang;Lu, Yeming;Yan, Yongqi;Zhao, Wei;Wu, Xiaocui;Zhang, Zhigang
    • Nuclear Engineering and Technology
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    • v.54 no.7
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    • pp.2491-2509
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    • 2022
  • As an important device in the nuclear island, the nuclear coolant pump can continuously provide power for medium circulation. The vane is one of the stationary parts in the nuclear coolant pump, which is installed between the impeller and the casing. The shape of the vane plays a significant role in the pump's overall performance and stability which are the important indicators during the safety serve process. Hence, the bionic concept is firstly applied into the design process of the vane to improve the performance of the nuclear coolant pump. Taking the scaled high-performance hydraulic model (on a scale of 1:2.5) of the coolant pump as the reference, a united bionic design approach is proposed for the unique structure of the guide vane of the nuclear coolant pump. Then, a new optimization design platform is established to output the optimal bionic vane. Finally, the comparative results and the corresponding mechanism are analyzed. The conclusions can be gotten as: (1) four parameters are introduced to configure the shape of the bionic blade, the significance of each parameter is herein demonstrated; (2) the optimal bionic vane is successfully obtained by the optimization design platform, the efficiency performance and the head performance of which can be improved by 1.6% and 1.27% respectively; (3) when compared to the original vane, the optimized bionic vane can improve the inner flow characteristics, namely, it can reduce the flow loss and decrease the pressure pulsation amplitude; (4) through the mechanism analysis, it can be found out that the bionic structure can induce the spanwise velocity and the vortices, which can reduce drag and suppress the boundary layer separation.

Genetic Variation of Flower Production in Breeding Seedling Seed Orchards of Quercus acuta and Q. glauca

  • Jeon, Koeun;Ro, Hee Seung;Kim, Ye-Ji;Gu, Da-Eun;Park, Ji-Min;Ryu, Sungryul;Kang, Kyu-Suk
    • Journal of Forest and Environmental Science
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    • v.38 no.2
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    • pp.102-109
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    • 2022
  • This study was conducted to test the significant difference of fertility variation among families and to select superior families for acorn production in the breeding seedling seed orchards (BSSOs) of Quercus acuta and Quercus glauca. The seed orchards were located in Jeju island and established by seedlings raised from selected parents for genetic testing in 2006. In the spring of 2021, the numbers of female and male flower were counted from 5 to 10 individuals per family in the BSSOs. To test statistical significance of which parameter is not satisfied through the normality test, we used a nonparametric analysis. Correlation analysis was performed to quantify the association between female and male flower production. As the results, the significant difference of flower production among families was found in both seed orchards. The averages of female flower production were 65.3 and 181.9 in Q. acuta and Q. glauca. The positive Spearman's rank correlation was existed between male and female flower production. Broad-sense heritability on female and male flower production were 0.191 and 0.147 in Q. acuta, and 0.285 and 0.068 in Q. glauca, respectively. Sexual asymmetry (e.g., maleness index) between female and male, and contribution variation among families (e.g., parental balance) were analyzed to find reasonable alternatives in the management of seed orchards. Effective population size of seed crops was predicted as a concept of status number. Loss of gene diversity (accumulation of group coancestry) would not be alarming in the BSSOs. Our results would be helpful to select breeding materials for establishing new seed orchards and to supply genetically improved seeds of evergreen oaks, which is one of the backbones of the strategy of carbon sink in the 2050 Carbon Neutrality of Korea Forest Service.

Sensitivity Analysis of Debris Flow Simulation in Flo-2D Using Flow Discharge and Topographic Information (유량과 지형조건에 따른 Flo-2D에서의 토석류 확산 민감도 분석)

  • Kim, Namgyun;Jun, Byonghee
    • The Journal of Engineering Geology
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    • v.32 no.4
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    • pp.547-558
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    • 2022
  • In August 2020, a debris flow occurred in Gokseon, Jeollanam-do, that resulted in the death of five residents. In this study area, high-resolution 0.03 m topographic information was generated through photogrammetry, and the amount of soil movement/loss was measured. In addition, sensitivity analysis was performed for flow depth, flow velocity, and debris flow area with the program Flo-2D using the difference in simulation parameter that discharge and topographic information. Wth increasing debris flow input discharge, increases were seen in flow depth, flow velocity, and debris flow area, as ell as in the gap in results from high-resolution topographic information and low-resolution topographic information. Also, when high-resolution topographic information was used, the results were similar to the actual (measured) flow direction of the debris flow. Therefore, the application of high-resolution topographic information increases the accuracy of the debris flow analysis results compared with low-resolution information. Results could be further imporved in the future by considering geological information such as yield stress and viscosity.

A Ppoisson Regression Aanlysis of Physician Visits (외래이용빈도 분석의 모형과 기법)

  • 이영조;한달선;배상수
    • Health Policy and Management
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    • v.3 no.2
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    • pp.159-176
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    • 1993
  • The utilization of outpatient care services involves two steps of sequential decisions. The first step decision is about whether to initiate the utilization and the second one is about how many more visits to make after the initiation. Presumably, the initiation decision is largely made by the patient and his or her family, while the number of additional visits is decided under a strong influence of the physician. Implication is that the analysis of the outpatient care utilization requires to specify each of the two decisions underlying the utilization as a distinct stochastic process. This paper is concerned with the number of physician visits, which is, by definition, a discrete variable that can take only non-negative integer values. Since the initial visit is considered in the analysis of whether or not having made any physician visit, the focus on the number of visits made in addition to the initial one must be enough. The number of additional visits, being a kind of count data, could be assumed to exhibit a Poisson distribution. However, it is likely that the distribution is over dispersed since the number of physician visits tends to cluster around a few values but still vary widely. A recently reported study of outpatient care utilization employed an analysis based upon the assumption of a negative binomial distribution which is a type of overdispersed Poisson distribution. But there is an indication that the use of Poisson distribution making adjustments for over-dispersion results in less loss of efficiency in parameter estimation compared to the use of a certain type of distribution like a negative binomial distribution. An analysis of the data for outpatient care utilization was performed focusing on an assessment of appropriateness of available techniques. The data used in the analysis were collected by a community survey in Hwachon Gun, Kangwon Do in 1990. It was observed that a Poisson regression with adjustments for over-dispersion is superior to either an ordinary regression or a Poisson regression without adjustments oor over-dispersion. In conclusion, it seems the most approprite to assume that the number of physician visits made in addition to the initial visist exhibits an overdispersed Poisson distribution when outpatient care utilization is studied based upon a model which embodies the two-part character of the decision process uderlying the utilization.

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A Study on Peak Load Prediction Using TCN Deep Learning Model (TCN 딥러닝 모델을 이용한 최대전력 예측에 관한 연구)

  • Lee Jung Il
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.6
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    • pp.251-258
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    • 2023
  • It is necessary to predict peak load accurately in order to supply electric power and operate the power system stably. Especially, it is more important to predict peak load accurately in winter and summer because peak load is higher than other seasons. If peak load is predicted to be higher than actual peak load, the start-up costs of power plants would increase. It causes economic loss to the company. On the other hand, if the peak load is predicted to be lower than the actual peak load, blackout may occur due to a lack of power plants capable of generating electricity. Economic losses and blackouts can be prevented by minimizing the prediction error of the peak load. In this paper, the latest deep learning model such as TCN is used to minimize the prediction error of peak load. Even if the same deep learning model is used, there is a difference in performance depending on the hyper-parameters. So, I propose methods for optimizing hyper-parameters of TCN for predicting the peak load. Data from 2006 to 2021 were input into the model and trained, and prediction error was tested using data in 2022. It was confirmed that the performance of the deep learning model optimized by the methods proposed in this study is superior to other deep learning models.

Performance Evaluation of ResNet-based Pneumonia Detection Model with the Small Number of Layers Using Chest X-ray Images (흉부 X선 영상을 이용한 작은 층수 ResNet 기반 폐렴 진단 모델의 성능 평가)

  • Youngeun Choi;Seungwan Lee
    • Journal of radiological science and technology
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    • v.46 no.4
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    • pp.277-285
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    • 2023
  • In this study, pneumonia identification networks with the small number of layers were constructed by using chest X-ray images. The networks had similar trainable-parameters, and the performance of the trained models was quantitatively evaluated with the modification of the network architectures. A total of 6 networks were constructed: convolutional neural network (CNN), VGGNet, GoogleNet, residual network with identity blocks, ResNet with bottleneck blocks and ResNet with identity and bottleneck blocks. Trainable parameters for the 6 networks were set in a range of 273,921-294,817 by adjusting the output channels of convolution layers. The network training was implemented with binary cross entropy (BCE) loss function, sigmoid activation function, adaptive moment estimation (Adam) optimizer and 100 epochs. The performance of the trained models was evaluated in terms of training time, accuracy, precision, recall, specificity and F1-score. The results showed that the trained models with the small number of layers precisely detect pneumonia from chest X-ray images. In particular, the overall quantitative performance of the trained models based on the ResNets was above 0.9, and the performance levels were similar or superior to those based on the CNN, VGGNet and GoogleNet. Also, the residual blocks affected the performance of the trained models based on the ResNets. Therefore, in this study, we demonstrated that the object detection networks with the small number of layers are suitable for detecting pneumonia using chest X-ray images. And, the trained models based on the ResNets can be optimized by applying appropriate residual-blocks.

Model Tests Investigating the Ground Movements Associated with Twin Side-by-Side Tunnel Construction in Clay (점성토 트윈 병렬 터널로 인한 지반침하 연구를 위한 모형실험)

  • Ahn, Sung-Kwon
    • Journal of the Korean Geotechnical Society
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    • v.25 no.10
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    • pp.77-85
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    • 2009
  • This paper describes the findings obtained from a research project aimed at investigating, via 1 g laboratory model tests, the ground movements caused by multiple side-by-side (sbs) tunnel construction in clay. The ground movements above a second tunnel showed different trends from those observed above a first tunnel. These trends include an increase in the overall volume loss, and a widening of the settlement troughs on the near limb of the trough accompanied by a shift of the maximum settlement towards existing tunnel. This would suggest that the use of simple predictive methods of adopting a Gaussian curve for analysing the ground settlements associated with twin (sbs) tunnel construction is not appropriate. Therefore the current paper adopts a method that modifies the Gaussian curve approach in order to improve the predictions. This paper comments on the parameter selection involved with adopting this new method to apply it to full-scale field situations, and also discusses its limitations.