scholarly journals Development and Implementation of Calibration Mathematical Models and Procedures for Precise Digital Level

2020 ◽  
Vol 1 (4) ◽  
Author(s):  
Ashraf A. A. Beshr ◽  
Raphael Ehigiator-Irughe
Keyword(s):  
Weather Condition ◽  
Least Square ◽  
Structural Deformation ◽  
Industrial Building ◽  
Engineering Project ◽  
Engineering Structures ◽  
Calibration Models ◽  
Standard Calibration ◽  
Technical Specifications ◽  
Digital Levels

Achieving the desired results and safety for any engineering project requires regularly review and check the technical specifications and accuracy of the geodetic instruments. Standard calibration models and procedures are exist for all geodetic instruments but it must be developed and modified to meet the standard for advanced precise digital level especially for deformation measurements. Digital levels are widely used for setting out engineering structures and monitoring the structural deformation because of their accuracy, in addition to the possibility of automatically collecting and storing data, which save time and effort required for observations. When performing measurements for an industrial building or construction site, due to the operation of various mechanisms and equipment, vibration occurs on the surface of the earth or on the concrete base, on which a tripod with a digital level is mounted. Under these conditions, the frequency and amplitude of the oscillations has a great effect on the observations of modern digital geodetic instruments. This paper investigates the accuracy of precise digital level observations (height differences and distances) for two cases which are: observations in laboratory and observations in the field (open area - outdoors observations with sun light and different weather condition than laboratory). The paper presents also two new suggested observations techniques for determining the collimation error (angle (θ)) of precise levels depending on least square theory which in turn provide a significant improvement of the suggested methods for determining the characteristic of digital levels. The research presents also experimentally the results of investigating the effect of (level – tripod) vibration on the digital level observations accuracy and suggest a practical technique to reduce the influence of the tripod-level vibration system on the resulted observations.

scholarly journals Competitive Binding Investigations and Quantitation in Surface-Enhanced Raman Spectra of Binary Dye Mixtures

2017 ◽  
Vol 72 (1) ◽  
pp. 60-68 ◽  
Author(s):  
Mircea A. Comanescu ◽  
Cyril Muehlethaler ◽  
John R. Lombardi ◽  
Marco Leona ◽  
Thomas A. Kubic
Keyword(s):  
Spectral Characteristics ◽  
Synthesis Method ◽  
Nanoparticle Synthesis ◽  
Peak Height ◽  
Calibration Models ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Standard Calibration ◽  
One Year ◽  
Selection Of

This research presents a study in surface-enhanced Raman quantitation of dyes present in mixtures of alizarin and purpurin using standard calibration curves and Langmuir isotherm calibration models. Investigations of the nature of competitive adsorption onto silver nanoparticles by centrifugation indicates that both dyes in the mixture interact with the nanoparticles simultaneously, but only the stronger adsorbing one is seen to dominate the spectral characteristics. Calibration can be carried out by careful selection of peaks characteristic to each dye in the mixture. Comparisons of peak height and peak area calibrations reveal that peak heights, when selected by the maximum value and accounting for peak shifts, prove the better model for quantitation. It is also shown that the microwave nanoparticle synthesis method produces stable nanoparticles with a shelf-life of at least one year that give very little variation within and between uses.

scholarly journals Different spectrophotometric and TLC-densitometric methods for determination of olmesartan medoxomil and hydrochlorothiazide and their degradation products

2018 ◽  
Vol 9 (4) ◽  
pp. 400-407 ◽  
Author(s):  
Selvia Maged Adly ◽  
Maha Mohamed Abdelrahman ◽  
Nada Sayed Abdelwahab ◽  
Nourudin Wageh Ali
Keyword(s):  
Multivariate Calibration ◽  
Degradation Products ◽  
External Validation ◽  
Olmesartan Medoxomil ◽  
Partial Least Square ◽  
Least Square ◽  
Pharmaceutical Dosage Form ◽  
Calibration Models ◽  
Significant Difference

In this work, multivariate calibration models and TLC-densitometric methods have been developed and validated for quantitative determination of olmesartan medoxomil (OLM) and hydrochlorothiazide (HCZ) in presence of their degradation products, olmesartan (OL) and salamide (SAL), respectively. In the first method, multivariate calibration models including principal component regression (PCR) and partial least square (PLS) were applied. The wavelength range 210-343 nm was used and data was auto-scaled and mean centered as pre-processing steps for PCR and PLS models, respectively. These models were tested by application to external validation set with mean percentage recoveries 99.78, 100.01, 100.41 and 100.46% for OLM, HCZ, OL and SAL, respectively, for PLS model and also, 100.22, 100.40, 102.25 and 100.13% for them, respectively, for PCR model. The second method is TLC-densitometry at which the chromatographic separation was carried out using silica gel 60F254 TLC plates and the developing system consisted of a mixture of ethyl acetate:chloroform:methanol: formic acid:tri-ethylamine (60:40:4:4:1, by volume) with UV-scanning at 254 nm. The developed methods were successfully applied for determination of OLM and HCZ in their pharmaceutical dosage form. Also, statistical comparison was made between the developed methods and the reported method using student’s-t test and F-test and results showed that there was no significant difference between them concerning both accuracy and precision.

Accuracy of Static Differential GPS Techniques; Implications for Structural Deformation Monitoring

2009 ◽  
Vol 62-64 ◽  
pp. 31-38
Author(s):  
J.O. Ehiorobo
Keyword(s):  
Carrier Phase ◽  
Reference Frames ◽  
Phase Measurement ◽  
Sampling Rate ◽  
Tall Buildings ◽  
Deformation Monitoring ◽  
Structural Deformation ◽  
Control Network ◽  
Differential Gps ◽  
Engineering Structures

In recent years, the need to monitor for Deformation in Engineering Structures such as Dams, Bridges and Tall buildings have become more necessary as a result of reported failures of many of these structures with catastrophic consequences globally. Global Positioning System (GPS) is highly automated and less labour intensive than other conventional techniques used in structural deformation monitoring. For most applications, such as National Geodetic Control Network, Urban Control Network and other Engineering Control Network, an accuracy in the cm level for most GPS work is quite adequate. For Structural deformation monitoring however, the required accuracy is in millimeters. In this paper, the use of Static Differential GPS method with multiple receivers for high precision measurement was investigated using the monitoring Stations at Ikpoba Dam as case study Scenerio. Four units of LEICA 300 Dual Frequency GPS receivers were deployed for code and carrier phase measurements with observation session of 1hr at a sampling rate of 15 sec. Baseline Processing and Least Squares Adjustment of observation was carried out in WGS 84 and NTM reference frames using the LEICA SKI-PRO Processing software and Move. Analysis of the results revealed that the number of outliers in the observation were <5% and the accuracy of horizontal and vertical coordinates were 4mm maximum for horizontal and 2mm maximum for vertical. The study revealed that in areas with favourable satellite constellation and appropriate reduction or elimination of multipath and other noise like errors, Static Differential GPS techniques with a combination of code and carrier phase measurement gives good results for structural deformation monitoring.

scholarly journals Prediction of Soil Organic Carbon for Ethiopian Highlands Using Soil Spectroscopy

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Tadele Amare ◽  
Christian Hergarten ◽  
Hans Hurni ◽  
Bettina Wolfgramm ◽  
Birru Yitaferu ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Diffuse Reflectance ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Calibration Models ◽  
The Stability

Soil spectroscopy was applied for predicting soil organic carbon (SOC) in the highlands of Ethiopia. Soil samples were acquired from Ethiopia’s National Soil Testing Centre and direct field sampling. The reflectance of samples was measured using a FieldSpec 3 diffuse reflectance spectrometer. Outliers and sample relation were evaluated using principal component analysis (PCA) and models were developed through partial least square regression (PLSR). For nine watersheds sampled, 20% of the samples were set aside to test prediction and 80% were used to develop calibration models. Depending on the number of samples per watershed, cross validation or independent validation were used. The stability of models was evaluated using coefficient of determination (R2), root mean square error (RMSE), and the ratio performance deviation (RPD). The R2 (%), RMSE (%), and RPD, respectively, for validation were Anjeni (88, 0.44, 3.05), Bale (86, 0.52, 2.7), Basketo (89, 0.57, 3.0), Benishangul (91, 0.30, 3.4), Kersa (82, 0.44, 2.4), Kola tembien (75, 0.44, 1.9), Maybar (84. 0.57, 2.5), Megech (85, 0.15, 2.6), and Wondo Genet (86, 0.52, 2.7) indicating that the models were stable. Models performed better for areas with high SOC values than areas with lower SOC values. Overall, soil spectroscopy performance ranged from very good to good.

Determine of Moisture Content for Rough Rice Single Kernel by Visible/NIR Spectroscopy

2014 ◽  
Vol 931-932 ◽  
pp. 1549-1554 ◽  
Author(s):  
Adcha Heman ◽  
Ching Lu Hsieh
Keyword(s):  
Moisture Content ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Regression Methods ◽  
Average Accuracy ◽  
Rough Rice ◽  
Calibration Models ◽  
Plsr Model

Moisture content (MC) of rough rice directly affects rice quality and its market value. This study applied spectroscopy both in visible 400-700 nm and NIR 700-1050 nm bands to record spectrum of rough rice single kernel (SK). Tainan No.11 medium rice randomly collected from field. After machine harvested, it was used in the tests and they were conditioned by oven to five MC levels ranging from 10.2 to 35.9%. Two regression methods, multiple linear regressions (MLR) and partial least square regression (PLSR), were applied to develop calibration models. Among 7 tested models were found that PLSR model of first differential with 21 gap points, which are rc=0.98, SEC=1.1% for calibration and rp=0.96, SEP=1.9% for prediction. The results suggested average accuracy for the best model was about 98.4% in 400-1050 nm wavelength.

Recursive PLS Modeling of Aromatics and Olefins in Gasoline

2013 ◽  
Vol 740 ◽  
pp. 267-272 ◽  
Author(s):  
Jing Fang Wang
Keyword(s):  
Near Infrared ◽  
Partial Least Square ◽  
Least Square ◽  
Oil Refining ◽  
Enterprise Application ◽  
Calibration Models ◽  
Recursive Pls ◽  
Comparison Of The Results ◽  
Pls Method ◽  
Separate Calibration

The separate calibration models of aromatics and olefins were established for gasoline through recursive partial least square (R-PLS) method in this paper.The some oil refining enterprise application has achieved better effect on the software being realized by R-PLS method. The calibration models were validated through comparison of the results determined by fluorescent indicator adsorption (FIA) and near infrared spectroscopy (NIR) methods.The NIR analysis results were well coincident with those of FIA method.The NIR can not only raise the analysis efficiency and lower the analysis cost,but also has better precision compared with FIA method.

scholarly journals PLS-R Calibration Models for Wine Spirit Volatile Phenols Prediction by Near-Infrared Spectroscopy

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 286
Author(s):  
Ofélia Anjos ◽  
Ilda Caldeira ◽  
Tiago A. Fernandes ◽  
Soraia Inês Pedro ◽  
Cláudia Vitória ◽  
...  
Keyword(s):  
Near Infrared ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Volatile Phenols ◽  
Near Ir ◽  
Liquid Liquid Extraction ◽  
Calibration Models ◽  
First Time

Near-infrared spectroscopic (NIR) technique was used, for the first time, to predict volatile phenols content, namely guaiacol, 4-methyl-guaiacol, eugenol, syringol, 4-methyl-syringol and 4-allyl-syringol, of aged wine spirits (AWS). This study aimed to develop calibration models for the volatile phenol’s quantification in AWS, by NIR, faster and without sample preparation. Partial least square regression (PLS-R) models were developed with NIR spectra in the near-IR region (12,500–4000 cm−1) and those obtained from GC-FID quantification after liquid-liquid extraction. In the PLS-R developed method, cross-validation with 50% of the samples along a validation test set with 50% of the remaining samples. The final calibration was performed with 100% of the data. PLS-R models with a good accuracy were obtained for guaiacol (r2 = 96.34; RPD = 5.23), 4-methyl-guaiacol (r2 = 96.1; RPD = 5.07), eugenol (r2 = 96.06; RPD = 5.04), syringol (r2 = 97.32; RPD = 6.11), 4-methyl-syringol (r2 = 95.79; RPD = 4.88) and 4-allyl-syringol (r2 = 95.97; RPD = 4.98). These results reveal that NIR is a valuable technique for the quality control of wine spirits and to predict the volatile phenols content, which contributes to the sensory quality of the spirit beverages.

scholarly journals Development of calibration models for rapid determination of moisture content in rubber sheets using portable near-infrared spectrometers

2020 ◽  
Vol 13 (02) ◽  
pp. 2050009
Author(s):  
Amorndej Puttipipatkajorn ◽  
Amornrit Puttipipatkajorn
Keyword(s):  
Moisture Content ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Near Infrared ◽  
Least Square ◽  
Mean Square ◽  
Ann Model ◽  
Rubber Sheet ◽  
Calibration Models

Rubber sheets are one of the primary products of natural rubber and are the main raw material in various rubber industries. The quality of a rubber sheet can be visually examined by holding it against clear light to inspect for any specks and impurities inside, but its moisture content is difficult to evaluate based on a visual inspection and this might lead to unfair trading. Herein, we developed a rapid, robust and nondestructive near-infrared spectroscopy (NIRS)-based method for moisture content determination in rubber sheets. A set of 300 rubber sheets were divided into a calibration (200 samples) and prediction groups (100 samples). The calibration set was used to develop NIRS calibration equation using different calibration models, Partial Least Square Regression (PLSR), Least Square Support Vector Machine (LS-SVM) and Artificial Neural Network (ANN). Among the models investigated, the ANN model with the first derivative of spectral preprocessing presented the best prediction with a coefficient of determination ([Formula: see text] of 0.993, root mean square error of calibration (RMSEC) of 0.126% and root mean square error of prediction (RMSEP) of 0.179%. The results indicated that the proposed NIRS-ANN model will be able to reduce human error and provide a highly accurate estimate of the moisture content in a rubber sheet compared to traditional wet chemistry estimation methods according to AOAC standards.

scholarly journals Modeling directional distributions of wind data in the United Arab Emirates at different elevations

2021 ◽  
Vol 14 (9) ◽  
Author(s):  
Aishah Al Yammahi ◽  
Prashanth R. Marpu ◽  
Taha B. M. J. Ouarda
Keyword(s):  
Wind Speed ◽  
United Arab Emirates ◽  
Wind Direction ◽  
Least Square Method ◽  
Least Square ◽  
Distribution Model ◽  
Long Term Effects ◽  
Energy Potential ◽  
Engineering Structures ◽  
Von Mises

AbstractModeling wind speed and direction are crucial in several applications such as the estimation of wind energy potential and the study of the long-term effects on engineering structures. While there have been several studies on modeling wind speed, studies on modeling wind direction are limited. In this work, we use a mixture of von Mises distributions to model wind direction. Finite mixtures of von Mises (FMVM) distributions are used to model wind directions at two sites in the United Arab Emirates. The parameters of the FMVM distribution are estimated using the least square method. The results of the research show that the FMVM is the best suited distribution model to fit wind direction at these two sites, compared to other distributions commonly used to model wind direction.

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