• Title/Summary/Keyword: least squares estimation

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An adaptive delay compensation method based on a discrete system model for real-time hybrid simulation

  • Wang, Zhen;Xu, Guoshan;Li, Qiang;Wu, Bin
    • Smart Structures and Systems
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    • v.25 no.5
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    • pp.569-580
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    • 2020
  • The identification of delays and delay compensation are critical problems in real-time hybrid simulations (RTHS). Conventional delay compensation methods are mostly based on the assumption of a constant delay. However, the system delay may vary during tests owing to the nonlinearity of the loading system and/or the behavioral variations of the specimen. To address this issue, this study presents an adaptive delay compensation method based on a discrete model of the loading system. In particular, the parameters of this discrete model are identified and updated online with the least-squares method to represent a servo hydraulic loading system. Furthermore, based on this model, the system delays are compensated for by generating system commands using the desired displacements, achieved displacements, and previous displacement commands. This method is more general than the existing compensation methods because it can predict commands based on multiple displacement categories. Moreover, this method is straightforward and suitable for implementation on digital signal processing boards because it relies solely on the displacements rather than on velocity and/or acceleration data. The virtual and real RTHS results show that the studied method exhibits satisfactory estimation smoothness and compensation accuracy. Furthermore, considering the measurement noise, the low-order parameter models of this method are more favorable than that the high-order parameter models.

Procedure for the Selection of Principal Components in Principal Components Regression (주성분회귀분석에서 주성분선정을 위한 새로운 방법)

  • Kim, Bu-Yong;Shin, Myung-Hee
    • The Korean Journal of Applied Statistics
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    • v.23 no.5
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    • pp.967-975
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    • 2010
  • Since the least squares estimation is not appropriate when multicollinearity exists among the regressors of the linear regression model, the principal components regression is used to deal with the multicollinearity problem. This article suggests a new procedure for the selection of suitable principal components. The procedure is based on the condition index instead of the eigenvalue. The principal components corresponding to the indices are removed from the model if any condition indices are larger than the upper limit of the cutoff value. On the other hand, the corresponding principal components are included if any condition indices are smaller than the lower limit. The forward inclusion method is employed to select proper principal components if any condition indices are between the upper limit and the lower limit. The limits are obtained from the linear model which is constructed on the basis of the conjoint analysis. The procedure is evaluated by Monte Carlo simulation in terms of the mean square error of estimator. The simulation results indicate that the proposed procedure is superior to the existing methods.

Characterizations and Quantitative Estimation of Alkali-Activated Binder Paste from Microstructures

  • Kar, Arkamitra;Ray, Indrajit;Halabe, Udaya B.;Unnikrishnan, Avinash;Dawson-Andoh, Ben
    • International Journal of Concrete Structures and Materials
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    • v.8 no.3
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    • pp.213-228
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    • 2014
  • Alkali-activated binder (AAB) is recently being considered as a sustainable alternative to portland cement (PC) due to its low carbon dioxide emission and diversion of industrial wastes and by-products such as fly ash and slag from landfills. In order to comprehend the behavior of AAB, detailed knowledge on relations between microstructure and mechanical properties are important. To address the issue, a new approach to characterize hardened pastes of AAB containing fly ash as well as those containing fly ash and slag was adopted using scanning electron microscopy (SEM) and energy dispersive X-ray spectra microanalyses. The volume stoichiometries of the alkali activation reactions were used to estimate the quantities of the sodium aluminosilicate (N-A-S-H) and calcium silicate hydrate (CSH) produced by these reactions. The 3D plots of Si/Al, Na/Al and Ca/Si atom ratios given by the microanalyses were compared with the estimated quantities of CSH(S) to successfully determine the unique chemical compositions of the N-A-S-H and CSH(S) for ten different AAB at three different curing temperatures using a constrained nonlinear least squares optimization formulation by general algebraic modeling system. The results show that the theoretical and experimental quantities of N-A-S-H and CSH(S) were in close agreement with each other. The $R^2$ values were 0.99 for both alkali-activated fly ash and alkali-activated slag binders.

Estimating High-Frequency Damping of a Beam through Electro-Mechanical Signatures of Piezoelectric Wafer Mounted on the Beam (보에 부착된 압전웨이퍼의 전기역학적 신호를 통한 고주파수 대역 감쇠 추정)

  • Shin, Yong Jae;Park, Hyun Woo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.37 no.1
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    • pp.217-229
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    • 2017
  • The high-frequency electro-mechanical signatures, which are excited and received by piezoelectric wafers mounted on a beam, are sensitive to incipient defect in a beam. Predicting the sensing range of the piezoelectric wafers is needed to effectively conduct damage assessment of a beam through utilizing their advantage. Damping of a beam plays the most important role in determining the sensing range among other features. This paper has proposed a scheme for estimating high-frequency damping of a beam through electro-mechanical signatures of piezoelectric wafers mounted on the beam. Considering damping effect while resonance of a beam evolves, wave perspective is adopted to formulate the electro-mechanical signatures of piezoelectric wafers. The damping of a beam is estimated through the least squares method minimizing the difference between the calculated and the measured damping ratio function values which are obtained from formulated and measured electro-mechanical signatures, respectively. The validity of the proposed scheme has been demonstrated through numerical and experimental examples using an aluminum beam with collocated piezoelectric wafers.

Parameters Affecting India Ink Artifacts on Opposed-Phase MR Images

  • Kim, Bo Ra;Ha, Dong-Ho
    • Investigative Magnetic Resonance Imaging
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    • v.23 no.4
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    • pp.341-350
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    • 2019
  • Purpose: To determine the MR parameters affecting India ink artifacts on opposed-phase chemical shift magnetic resonance (MR) imaging. Materials and Methods: The use of a female Sprague-Dawley rat was approved by our Institutional Animal Care and Use Committee. Using an iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) images, which is a modified Dixon method, axial opposed-phase images of the abdominal cavity were obtained with different MR parameters: series 1, different repetition times (TRs; 400, 2000, and 4000 ms); series 2, different echo times (TEs; 10, 50, and 100 ms); series 3, different field of views (FOVs; 6, 8, 16, and 24 cm); series 4, different echo train lengths (ETLs; 2, 4, and 8); series 5, different bandwidths (25, 50, and 85); and series 6, different slice thicknesses (1, 2, 4, 8, and 16 mm). Artifacts on opposed images obtained with different parameters were compared subjectively by two radiologists. For objective analysis, the thickness of the artifact was measured. Spearman's correlation between altered MR parameters and thicknesses of India ink artifact was obtained via objective analysis. Results: India ink artifact was increasingly apparent using shorter TE, larger FOV and ETL, and thicker slices upon subjective analysis. The objective analysis revealed a strong negative correlation between the thickness of the artifact and TE (r = -0.870, P < 0.01); however, strong positive correlations were found between FOV (r = 0.854, P < 0.01) and slice thickness (r = 0.971, P < 0.01). Conclusion: India ink artifact was thicker with shorter TE, larger FOV, and larger slice thickness.

Lessons Learned from a Comparative Analysis of Surgical Outcomes of and Learning Curves for Laparoscopy-Assisted Distal Gastrectomy

  • Moon, Jun-Seok;Park, Man Sik;Kim, Jong-Han;Jang, You-Jin;Park, Sung-Soo;Mok, Young-Jae;Kim, Seung-Joo;Kim, Chong-Suk;Park, Seong-Heum
    • Journal of Gastric Cancer
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    • v.15 no.1
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    • pp.29-38
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    • 2015
  • Purpose: Before expanding our indications for laparoscopic gastrectomy to advanced gastric cancer and adopting reduced port laparoscopic gastrectomy, we analyzed and audited the outcomes of laparoscopy-assisted distal gastrectomy (LADG) for adenocarcinoma; this was done during the adoptive period at our institution through the comparative analysis of short-term surgical outcomes and learning curves (LCs) of two surgeons with different careers. Materials and Methods: A detailed comparative analysis of the LCs and surgical outcomes was done for the respective first 95 and 111 LADGs performed by two surgeons between July, 2006 and June, 2011. The LCs were fitted by using the non-linear ordinary least squares estimation method. Results: The postoperative morbidity and mortality rates were 14.6% and 0.0%, respectively, and there was no significant difference in the morbidity rates (12.6% vs. 16.2%, P=0.467). More than 25 lymph nodes were retrieved by each surgeon during LADG procedures. The LCs of both surgeons were distinct. In this study, a stable plateau of the LC was not achieved by both surgeons even after performing 90 LADGs. Conclusions: Regardless of the experience with gastrectomy or laparoscopic surgery for other organs, or the age of surgeon, the outcome was quite acceptable; the learning process differ according to the surgeon's experience and individual characteristics.

Automatic Object Recognition in 3D Measuring Data (3차원 측정점으로부터의 객체 자동인식)

  • Ahn, Sung-Joon
    • The KIPS Transactions:PartB
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    • v.16B no.1
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    • pp.47-54
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    • 2009
  • Automatic object recognition in 3D measuring data is of great interest in many application fields e.g. computer vision, reverse engineering and digital factory. In this paper we present a software tool for a fully automatic object detection and parameter estimation in unordered and noisy point clouds with a large number of data points. The software consists of three interactive modules each for model selection, point segmentation and model fitting, in which the orthogonal distance fitting (ODF) plays an important role. The ODF algorithms estimate model parameters by minimizing the square sum of the shortest distances between model feature and measurement points. The local quadric surface fitted through ODF to a randomly touched small initial patch of the point cloud provides the necessary initial information for the overall procedures of model selection, point segmentation and model fitting. The performance of the presented software tool will be demonstrated by applying to point clouds.

The Effect of VDI Technical Characteristics on Interaction and Work Performance (VDI 기술특성이 상호작용과 업무성과에 미치는 영향에 관한 실증적 연구)

  • Kwak, Young;Shin, Min Soo
    • Journal of Information Technology Services
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    • v.20 no.4
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    • pp.95-111
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    • 2021
  • Recently, many organizations are actively adopting VDI (Virtual Desktop Infrastructure), an IT-based business system, to build a non-face-to-face business environment for smart-work. However, most of the existing research on VDI has focused on the satisfaction of system service quality or the use of IT resources and investment for VDI introduction. However, research on effective management and utilization of factors according to the characteristics of VDI technology is urgently required. This study is an empirical research study on how VDI technology characteristics affect interactions and work performance by identifying differences in utilization factors between general organization members and IT managers, presenting standards for business utilization and management. This study proposed a model and hypothesis that the system technology characteristics for VDI use are mediated by interactions in which users respond to functions appropriate to their work. In order to verify the hypothesis, a questionnaire survey was conducted on 188 people of companies and institutions that have adopted and used VDI through a questionnaire survey. Data analysis was performed with partial least squares (PLS), a structural equation modeling (SEM) technique that uses a component-based approach to estimation. As a result of the empirical analysis, the same environmental function for performing work, N-th security, and remote access function factors for non-face-to-face work have a significant effect on interactivity, and IT managers have an additional significant effect on the management technology characteristics of resource reallocation. Has been shown to affect. The results of this study aim to minimize trial and error due to new introduction by presenting considerations for future VDI introduction through case analysis.

Variance component analysis of growth and production traits in Vanaraja male line chickens using animal model

  • Ullengala, Rajkumar;Prince, L. Leslie Leo;Paswan, Chandan;Haunshi, Santosh;Chatterjee, Rudranath
    • Animal Bioscience
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    • v.34 no.4
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    • pp.471-481
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    • 2021
  • Objective: A comprehensive study was conducted to study the effects of partition of variance on accuracy of genetic parameters and genetic trends of economic traits in Vanaraja male line/project directorate-1 (PD-1) chicken. Methods: Variance component analysis utilizing restricted maximum likelihood animal model was carried out with five generations data to delineate the population status, direct additive, maternal genetic, permanent environmental effects, besides genetic trends and performance of economic traits in PD-1 chickens. Genetic trend was estimated by regression of the estimated average breeding values (BV) on generations. Results: The body weight (BW) and shank length (SL) varied significantly (p≤0.01) among the generations, hatches and sexes. The least squares mean of SL at six weeks, the primary trait was 77.44±0.05 mm. All the production traits, viz., BWs, age at sexual maturity, egg production (EP) and egg weight were significantly influenced by generation. Model four with additive, maternal permanent environmental and residual effects was the best model for juvenile growth traits, except for zero-day BW. The heritability estimates for BW and SL at six weeks (SL6) were 0.20±0.03 and 0.17±0.03, respectively. The BV of SL6 in the population increased linearly from 0.03 to 3.62 mm due to selection. Genetic trend was significant (p≤0.05) for SL6, BW6, and production traits. The average genetic gain of EP40 for each generation was significant (p≤0.05) with an average increase of 0.38 eggs per generation. The average inbreeding coefficient was 0.02 in PD-1 line. Conclusion: The population was in ideal condition with negligible inbreeding and the selection was quite effective with significant genetic gains in each generation for primary trait of selection. The animal model minimized the over-estimation of genetic parameters and improved the accuracy of the BV, thus enabling the breeder to select the suitable breeding strategy for genetic improvement.

Feasibility Study for an Optical Sensing System for Hardy Kiwi (Actinidia arguta) Sugar Content Estimation

  • Lee, Sangyoon;Sarkar, Shagor;Park, Youngki;Yang, Jaekyeong;Kweon, Giyoung
    • Journal of agriculture & life science
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    • v.53 no.3
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    • pp.147-157
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    • 2019
  • In this study, we tried to find out the most appropriate pre-processing method and to verify the feasibility of developing a low-price sensing system for predicting the hardy kiwis sugar content based on VNIRS and subsequent spectral analysis. A total of 495 hardy kiwi samples were collected from three farms in Muju, Jeollabukdo, South Korea. The samples were scanned with a spectrophotometer in the range of 730-2300 nm with 1 nm spectral sampling interval. The measured data were arbitrarily separated into calibration and validation data for sugar content prediction. Partial least squares (PLS) regression was performed using various combinations of pre-processing methods. When the latent variable (LV) was 8 with the pre-processing combination of standard normal variate (SNV) and orthogonal signal correction (OSC), the highest R2 values of calibration and validation were 0.78 and 0.84, respectively. The possibility of predicting the sugar content of hardy kiwi was also examined at spectral sampling intervals of 6 and 10 nm in the narrower spectral range from 730 nm to 1200 nm for a low-price optical sensing system. The prediction performance had promising results with R2 values of 0.84 and 0.80 for 6 and 10 nm, respectively. Future studies will aim to develop a low-price optical sensing system with a combination of optical components such as photodiodes, light-emitting diodes (LEDs) and/or lamps, and to locate a more reliable prediction model by including meteorological data, soil data, and different varieties of hardy kiwi plants.