• Title/Summary/Keyword: Random Response

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Implementation of Random Carrier-Frequency Modulation Scheme for a DSP based PWM Inverter for Acoustic Noise Reduction of Induction Motors (유도전동기의 소음저감을 위한 DSP기반 PWM인버터의 랜덤 캐리어 주파수 변조기법의 구현)

  • 정영국;나석환;임영철;정성기
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.52 no.12
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    • pp.608-615
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    • 2003
  • This paper describes an implementation of a DSP (Digital Signal Processor) controlled random carrier frequency modulation for the PWM inverter for acoustic noise reduction of induction motors. Real-time generation of the random variable and RPWM(Random PWM) along with the speed control was achieved by DSP TMS320C31. The experimental results show that the voltage and current harmonics are spread to a wide band area and the power spectrum of the acoustic switching noise was spread to create a more appealing, less annoying sound. Also, the speed response of the implemented method and the conventional method is nearly similar to each other from the viewpoint of the v/f constant control.

The Effect of Random Point Excitation on the Vibration Level of Plates

  • Park, Myung-Jin;Yoo, Song-Min;Kim, Chang-Nyung
    • Journal of Mechanical Science and Technology
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    • v.16 no.5
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    • pp.583-590
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    • 2002
  • When a mechanical structure is driven by stationary wide band random point forces, the resulting vibration depends upon the number, location, and joint statistical properties of the exciting forces. In this study, under the assumption of light damping, an approximate procedure for analyzing plates is briefly outlined. The effects of number, location and correlation of the force field on the vibration level are then investigated for various cases in which random point forces with band limited white noise are applied, and the optimal spacing between input forces that produces a relative minimum in the vibration response is predicted.

A HGLM framework for Meta-Analysis of Clinical Trials with Binary Outcomes

  • Ha, Il-Do
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.4
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    • pp.1429-1440
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    • 2008
  • In a meta-analysis combining the results from different clinical trials, it is important to consider the possible heterogeneity in outcomes between trials. Such variations can be regarded as random effects. Thus, random-effect models such as HGLMs (hierarchical generalized linear models) are very useful. In this paper, we propose a HGLM framework for analyzing the binominal response data which may have variations in the odds-ratios between clinical trials. We also present the prediction intervals for random effects which are in practice useful to investigate the heterogeneity of the trial effects. The proposed method is illustrated with a real-data set on 22 trials about respiratory tract infections. We further demonstrate that an appropriate HGLM can be confirmed via model-selection criteria.

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Random loading identification of multi-input-multi-output structure

  • Zhi, Hao;Lin, Jiahao
    • Structural Engineering and Mechanics
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    • v.10 no.4
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    • pp.359-369
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    • 2000
  • Random loading identification has long been a difficult problem for Multi-Input-Multi-Output (MIMO) structure. In this paper, the Pseudo Excitation Method (PEM), which is an exact and efficient method for computing the structural random response, is extended inversely to identify the excitation power spectral densities (PSD). This identified method, named the Inverse Pseudo Excitation Method (IPEM), resembles the general dynamic loading identification in the frequency domain, and can be used to identify the definite or random excitations of complex structures in a similar way. Numerical simulations are used to reveal the the difficulties in such problems, and the results of some numerical analysis are discussed, which may be very useful in the setting up and processing of experimental data so as to obtain reasonable predictions of the input loading from the selected structural responses.

Performance of Random Forest Classifier for Flood Mapping Using Sentinel-1 SAR Images

  • Chu, Yongjae;Lee, Hoonyol
    • Korean Journal of Remote Sensing
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    • v.38 no.4
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    • pp.375-386
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    • 2022
  • The city of Khartoum, the capital of Sudan, was heavily damaged by the flood of the Nile in 2020. Classification using satellite images can define the damaged area and help emergency response. As Synthetic Aperture Radar (SAR) uses microwave that can penetrate cloud, it is suitable to use in the flood study. In this study, Random Forest classifier, one of the supervised classification algorithms, was applied to the flood event in Khartoum with various sizes of the training dataset and number of images using Sentinel-1 SAR. To create a training dataset, we used unsupervised classification and visual inspection. Firstly, Random Forest was performed by reducing the size of each class of the training dataset, but no notable difference was found. Next, we performed Random Forest with various number of images. Accuracy became better as the number of images in creased, but converged to a maximum value when the dataset covers the duration from flood to the completion of drainage.

Korean Text Classification Using Randomforest and XGBoost Focusing on Seoul Metropolitan Civil Complaint Data (RandomForest와 XGBoost를 활용한 한국어 텍스트 분류: 서울특별시 응답소 민원 데이터를 중심으로)

  • Ha, Ji-Eun;Shin, Hyun-Chul;Lee, Zoon-Ky
    • The Journal of Bigdata
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    • v.2 no.2
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    • pp.95-104
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    • 2017
  • In 2014, Seoul Metropolitan Government launched a response service aimed at responding promptly to civil complaints. The complaints received are categorized based on their content and sent to the department in charge. If this part can be automated, the time and labor costs will be reduced. In this study, we collected 17,700 cases of complaints for 7 years from June 1, 2010 to May 31, 2017. We compared the XGBoost with RandomForest and confirmed the suitability of Korean text classification. As a result, the accuracy of XGBoost compared to RandomForest is generally high. The accuracy of RandomForest was unstable after upsampling and downsampling using the same sample, while XGBoost showed stable overall accuracy.

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Response Variability of Laminated Composite Plates with Random Elastic Modulus (탄성계수의 불확실성에 의한 복합적층판 구조의 응답변화도)

  • Noh, Hyuk-Chun
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.21 no.4
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    • pp.335-345
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    • 2008
  • In this study, we suggest a stochastic finite element scheme for the probabilistic analysis of the composite laminated plates, which have been applied to variety of mechanical structures due to their high strength to weight ratios. The applied concept in the formulation is the weighted integral method, which has been shown to give the most accurate results among others. We take into account the elastic modulus and in-plane shear modulus as random. For individual random parameters, independent stochastic field functions are assumed, and the effect of these random parameters on the response are estimated based on the exponentially varying auto- and cross-correlation functions. Based on example analyses, we suggest that composite plates show a less coefficient of variation than plates of isotropic and orthotropic materials. For the validation of the proposed scheme, Monte Carlo analysis is also performed, and the results are compared with each other.

Application of Control Variable with Routing Probability to Queueing Network Simulation (대기행렬 네트워크 시뮬레이션에서 분지확률 통제변수의 응용)

  • Kwon, Chi-Myung;Lim, Sang-Gyu
    • Journal of the Korea Society for Simulation
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    • v.21 no.3
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    • pp.71-78
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    • 2012
  • This research discusses the application of the control variables to achieve a more precise estimation for the target response in queueing network simulation. The efficiency of control variable method in estimating the response depends upon how we choose a set of control variables strongly correlated with the response and how we construct a function of selected control variables. For a class of queuing network simulations, the random variables that drive the simulation are basically the service-time and routing probability random variables. Most of applications of control variable method focus on utilization of the service time random variables for constructing a controlled estimator. This research attempts to suggest a controlled estimator which uses these two kinds of random variables and explore the efficiency of these estimators in estimating the reponses for computer network system. Simulation experiments on this model show the promising results for application of routing probability control variables. We consider the applications of the routing probability control variables to various simulation models and combined control variables using information of service time and routing probability together in constructing a control variable as future researches.

Evaluation and Combination of Correlation Coefficient for Response Variable of Seismic Fragility Curve (지진취약도 곡선의 응답변수에 대한 상관계수 평가 및 변수별 조합)

  • Kim, Si Young;Kim, Jung Han
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.33 no.6
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    • pp.401-409
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    • 2020
  • Seismic fragility assessments include a procedure to combine the random variables of response and capacity to produce the relationship between failure probability and seismic intensity. The evaluation of the failure probability of simultaneous multiple failures of two or more components assumes that the failure probability of each component is independent of those of the others. However, a correlation is expected to exist because several random factors have the same cause. The multiple-failure probability can differ depending on this correlation and may be unconservative without considering the seismic correlation. Therefore, a practical methodology for fragility assessment should be evaluated using the seismic correlation and correlation coefficient for each random variable. In this study, several random variables were selected for numerical evaluation of the correlation coefficient. The correlation coefficient was then compared with each variable and the combined variables. The correlation coefficient using simplified and complex models were also compared to determine and analyze the differences between each of the approaches.

A Stratified Unknown Repeated Trials in Randomized Response Sampling

  • Singh, Housila P.;Tarray, Tanveer Ahmad
    • Communications for Statistical Applications and Methods
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    • v.19 no.6
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    • pp.751-759
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    • 2012
  • This paper proposes an alternative stratified randomized response model based on the model of Singh and Joarder (1997). It is shown numerically that the proposed stratified randomized response model is more efficient than Hong et al. (1994) (under proportional allocation) and Kim and Warde (2004) (under optimum allocation).