scholarly journals Adjustment Of Single And Double Braced Quadrilateral Using Least Square Condition Equation

2020 ◽  
Vol 1 (4) ◽  
Author(s):  
R. Ehigiator-Irughe ◽  
B. M. Mohammad Muhajir
Keyword(s):  
Least Square ◽  
Base Line ◽  
Triangular Structure ◽  
Four Corners ◽  
Angular Measurements ◽  
Condition Equation

Quadrilateral is a single or double triangulation system consisting of figures with four corners  stations. It consist of two known stations and a base line. Other corners of the triangles are measured using precise instrument. The systems is treated as the strongest with the best arranged triangular structure which provides adequate means of determining the lengths of other sides of the triangle whose length, bearings and positions are required. In this  four sided polygon with four (4) points were established. The coordinate of two points (A and B) are known while the coordinates of points (C and D) are required. The purpose of the exercise was to use least square condition equation to determine and adjust coordinates of the two unknown points using the Angular measurements of quadrilateral. Two separate measurements were taken (observation 1 and observation 2) forming a network of a single and double braced quadrilateral respectively. After which, the data obtained were reduced and then adjusted using least square condition equation.

scholarly journals PSXI-6 Calculating energy efficiency use for Nellore bulls divergent in residual feed intake

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 393-394
Author(s):  
Camila D A Batalha ◽  
Fabiana L De Araújo ◽  
Renata H Branco ◽  
Luis O Tedeschi ◽  
Sarah F Bonilha
Keyword(s):  
Energy Efficiency ◽  
Feed Intake ◽  
Subcutaneous Fat ◽  
Residual Feed Intake ◽  
Efficiency Index ◽  
Least Square ◽  
Metabolic Energy ◽  
Energetic Efficiency ◽  
Base Line ◽  
Ad Libitum

Abstract Retained energy (RE) and energetic efficiency index were measured in Nellore bulls from divergent classes of residual feed intake (RFI). Thirty-four Nellore bulls (15 low RFI-LRFI and 19 high RFI-HRFI) were feedlot finished and slaughtered with 385 ± 40 kg of body weight (BW) and 520 ± 26.2 days of age. At the beginning of the experiment, five LRFI and three HRFI were slaughtered and used as base line. Individual dry matter intake was recorded daily; initial and final BW were recorded after 16 h of fasting. Eight bulls, four LRFI and four HRFI, were fed at maintenance, receiving 65 g of DM/kg0.75 BW, and 18 bulls (10 LRFI and eight HRFI) were fed ad libitum. Diet had 19:81 roughage:concentrate, 88% of DM and 15% of crude protein. Ultrasound measurements on the Longissimus muscle were performed at intervals of 28 days. When two ad libitum bulls reached 4 mm of subcutaneous fat thickness, one maintenance bull was randomly chosen and slaughtered on the same day. After slaughter, the centesimal composition of the empty body and carcass was measured. Data were analyzed using a random coefficients model, and RFI class was included as a fixed effect. Least-square means were used to compare the means, and significance was declared for P ≤ 0.05. The LRFI had greater protein retention than HRFI (248 vs. 142 g/d; P = 0.009), and same fat and energy retention (313 g/d and 4.12 Mcal/d, respectively). The energy efficiency indexes, heat production per metabolic energy intake (Mcal/Mcal) and gain-to-feed (kg/kg) ratio, did not differ between RFI classes. Though LRFI had the same energy efficiency index, they were leaner. These results indicated an association of RFI and maturity patterns. Further research is needed to estimate the net energy requirements of Nellore bulls classified according to RFI. Acknowledgments: FAPESP Processes 2017/06709-2, 2018/20080–2 and 2019/17714-2.

scholarly journals A Sort of New Improved Algorithm For Total Least Square

2015 ◽  
Vol 9 (1) ◽  
pp. 238-247
Author(s):  
Deng Yonghe
Keyword(s):  
Least Square ◽  
New Method ◽  
Unknown Parameters ◽  
Error Equation ◽  
Virtual Observation ◽  
Condition Equation ◽  
Total Least Square ◽  
Improved Algorithm

Aim to blemish of total least square algorithm based on error equation of virtual observation, this paper put forward and deduced a sort of new improved algorithm which selects essential unknown parameters among designing matrix, and then, doesn’t consider condition equation of unknown parameters among designing matrix. So, this paper perfected and enriched algorithm, and sometimes, new method of this paper is better. Finally, the results of examples showed that new mothod is viable and valid.

Reliability and Usefulness of the Fitting of a Modified Gamma Function to Time-Activity Curves by Means of a Non-Linear Iterative Least-Square Method

1981 ◽  
Vol 20 (04) ◽  
pp. 195-197
Author(s):  
J. M. Fránquiz
Keyword(s):  
Gamma Function ◽  
Least Square Method ◽  
Least Square ◽  
Base Line ◽  
Time Activity ◽  
Appearance Time ◽  
Least Square Fitting ◽  
Fitting Method ◽  
Non Linear ◽  
Least Square Fitting Method

A non-linear iterative least-square fitting method is presented for calculating the parameters of a modified gamma function. The method permits the correction of the appearance time (AT) and the curve parameters in those situations in which AT cannot be estimated with accuracy. The reliability and accuracy of the method is studied in experimental and simulated curves by means of a computer, comparing the results with those obtained by the method of Starmer and Clark for different initial selections of AT and noise at the base line. The usefulness of the method is shown in situations where the curves are distorted in their initial part.

scholarly journals Improved Total Least Square Algorithm

2015 ◽  
Vol 9 (1) ◽  
pp. 394-399 ◽  
Author(s):  
Deng Yonghe
Keyword(s):  
Dimensional Space ◽  
Three Dimensional ◽  
Least Square ◽  
Error Equation ◽  
Virtual Observation ◽  
Straight Line ◽  
Condition Equation ◽  
Total Least Square ◽  
Three Dimensional Space ◽  
Improved Algorithm

Aim to blemish of total least square algorithm based on error equation of virtual observation,this paper proposed a sort of improved algorithm which doesn’t neglect condition equation of virtual observation,and considers both error equation and condition equation of virtual observation.So,the improved algorithm is better.Finally,this paper has fitted a straight line in three-dimensional space based on the improved algorithm.The result showed that the improved algorithm is viable and valid.

scholarly journals Assessment of Adjustments Methods in Traverse Networks for Positioning

2021 ◽  
Vol 5 (2) ◽  
pp. 354-364
Author(s):  
L. Hart ◽  
D.D. Basil ◽  
T. Oba
Keyword(s):  
Spatial Information ◽  
Least Square ◽  
Random Errors ◽  
Approximate Methods ◽  
Reliability Indicators ◽  
Adjustment Model ◽  
Least Squares Adjustment ◽  
Condition Equation ◽  
Model Adjustment

Various factors contribute to the degree of accuracy of the adjusted parameter (coordinate), one of which is the choice of adjustment model. Adjustment models seeks to eliminate (accounts) for the presence of random errors present in a given observations. The choice is critical for surveyors and other spatial analysts for optimal positioning and mapping projects since different adjustment models will yield different level of accuracy of spatial information generated irrespective of the quality of observations. For a traversing network, various adjustment models have been put forward which include; the Transit, the Bowditch, and the Crandels models. In spite of these models, internal consistency and reliability indicators of the network of positions are determined using the least squares adjustment model (observation equation and condition equation models). The aim of this work is to analyze the various traverse adjustment models. The approach deployed in this work was to compute the provisional coordinate of six traverse stations using the approximate methods of adjustment i.e., Bowditch and transit methods of traverse adjustment models. In addition, the least square adjustment models were deployed to minimize the propagation of residuals of the obtained values. The adjusted distances and directions were then compared with the observed distances and directions to obtain the residuals. The coordinate of positions was determined and the Root Mean Square Error (RMSE) associated with the traverse adjustment models are given as 0.128702264 and 0.008560954. Similarly, the RMSE of the adjusted values using the least square models are given as 0.007181432, and 0.005763969 for the observation and condition equation models respectively. The analysis of these results reveals that the traverse adjustment models are unique with capabilities embedded in the determination of the observables during data acquisition. However, for mapping and engineering survey of small locations, the transit method is more preferable to the Bowditch method.

scholarly journals On application of algorithms on the basis of least-square and end formula methods in the trajectory measurement processing problems

2016 ◽  
pp. 74-80
Author(s):  
Yu. K. Kisin
Keyword(s):  
Mathematical Simulation ◽  
Stochastic Simulation ◽  
Functional Relationship ◽  
Least Square ◽  
Mean Square ◽  
Measurement Processing ◽  
Angular Measurements ◽  
Measurement Vector ◽  
The Mean ◽  
Trajectory Measurement

In this research we obtained an estimate of mean-square deviations in the trajectory measurement processing problem when the estimated trajectory parameters were determined by the end formulas according to the minimum set of parameters measured, and in this case there was no explicit functional relationship between these parameters and the measurement vector. To estimate the mean-square deviations of determining the trajectory according to the end formulas, we proposed to implement the stochastic simulation. We obtained end formulas for the trajectory problems when making angular measurements. The work provides the results of mathematical simulation.

scholarly journals Improving the Performance of Finger-Vein Recognition System Using A New Scheme of Modified Preprocessing Methods

2020 ◽  
Vol 9 (3) ◽  
pp. 397
Author(s):  
Ahmed A. Mustafa ◽  
Ahmed AK. Tahir
Keyword(s):  
Feature Extraction ◽  
Recognition System ◽  
Extraction Methods ◽  
Error Rates ◽  
Least Square ◽  
Base Line ◽  
Finger Vein ◽  
Roi Extraction ◽  
Vein Recognition ◽  
Finger Vein Recognition

This paper aims at improving the performance of finger-vein recognition system using a new scheme of image preprocessing. The new scheme includes three major steps, RGB to Gray conversion, ROI extraction and alignment and ROI enhancement. ROI extraction and alignment includes four major steps. First, finger-vein boundaries are detected using two edge detection masks each of size (4 x 6). Second, the correction for finger rotation is done by calculating the finger base line from the midpoints between the upper and lower boundaries using least square method. Third, ROI is extracted by cropping a rectangle around the center of the finger-vein which is determined using the first and second invariant moments. Forth, the extracted ROI is normalized to a unified size of 192 x 64 in order to compensate for scale changes. ROI enhancement is done by applying the technique of Contrast-Limited Adaptive Histogram Equalization (CLAHE), followed by median and modified Gaussian high pass filters. The application of the given preprocessing scheme to a finger-vein recognition system revealed its efficiency when used with different methods of feature extractors and with different types of finger-vein database. For the University of Twente Finger Vascular Pattern (UTFVP) database, the achieved Identification Recognition Rates (IRR) for identification mode using three feature extraction methods Local Binary Pattern (LBP), Local Directional Pattern (LDP) and Local Line Binary Pattern (LLBP) are (99.79, 99.86 and 99.86) respectively, while the achieved Equal Error Rates (EER) for verification mode for the same feature extraction methods are (0.139, 0.069 and 0.035). For the Shandong University Machine Learning and Applications - Homologous Multi-modal Traits (SDUMLA-HMT) database, the achieved Identification Recognition Rates (IRR) for identification mode using three feature extraction methods LBP, LDP and LLBP are (99.57, 99.73 and 99.65) respectively, while the achieved Equal Error Rates (EER) for verification mode for the same feature extraction methods are (0.419, 0.262 and 0.341). These results outrage those of the previous state-of-art methods.

Least-square refinement of structure parameters from CBED integrated intensities: application to determination of temperature factors in Y BA2CU3O7

1992 ◽  
Vol 50 (2) ◽  
pp. 1456-1457
Author(s):  
Kjersti Gjønnes ◽  
Jon Gjønnes
Keyword(s):  
Least Square ◽  
Measured Intensity ◽  
Structure Information ◽  
Accurate Temperature ◽  
Least Square Fit ◽  
Case Application ◽  
Integrated Intensities ◽  
Temperature Factors ◽  
Narrow Bands

Electron diffraction intensities can be obtained at large scattering angles (sinθ/λ ≥ 2.0), and thus structure information can be collected in regions of reciprocal space that are not accessable with other diffraction methods. LACBED intensities in this range can be utilized for determination of accurate temperature factors or for refinement of coordinates. Such high index reflections can usually be treated kinematically or as a pertubed two-beam case. Application to Y Ba2Cu3O7 shows that a least square refinememt based on integrated intensities can determine temperature factors or coordinates.LACBED patterns taken in the (00l) systematic row show an easily recognisable pattern of narrow bands from reflections in the range 15 < l < 40 (figure 1). Integrated intensities obtained from measured intensity profiles after subtraction of inelastic background (figure 2) were used in the least square fit for determination of temperature factors and refinement of z-coordinates for the Ba- and Cu-atoms.

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