QUALITY CONTROL OF POSITIONAL ACCURACY OF 1:10000 ORTHOPHOTO PRODUCTS IN THE THIRD NATIONAL LAND SURVEY

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 525-528
Author(s):  
X. Ma ◽  
Q. Q. Yan ◽  
X. Wu
Keyword(s):  
Quality Control ◽  
Mean Square Error ◽  
Quality Inspection ◽  
Mean Square ◽  
Positional Accuracy ◽  
The Third ◽  
Land Survey ◽  
Image Edge ◽  
Important Test

Abstract. The third national land survey is based on the orthophotos products. Only by providing 1:10000 orthophoto products that meet the quality requirements can the third national land survey be carried out smoothly, and the third national land survey products can be guaranteed to be accurate and reliable. Positional accuracy as an important quality element of 1:10000 orthophoto products is a key factor affecting the quality of 1:10000 orthophoto products, and directly affects the quality of the third national land survey products.This paper introduces the content of the positional accuracy quality inspection in the 1:10000 orthophoto products of the third national land survey.The mean square error in plane position and the image edge match are two important test entries in the quality control of positional accuracy . The paper specifically elaborates on the quality control of the above two important test entries. The quality control indexes of mean square error in plane position and the image edge match are introduced in detail, and the quality inspection method and quality evaluation method of position accuracy are proposed. And, the main quality problems found in the positional accuracy checking are illustrated by way of case analysis. At the same time, the cause analysis was carried out for these specific quality problems, and corresponding improvement suggestions were also proposed.This paper provides technical support and reference for the quality inspection of 1:10000 orthophoto products, and also has some positive effects on quality improvement.

scholarly journals Quality of wood in the stands of poplar clones

2008 ◽  
Vol 54 (No. 1) ◽  
pp. 9-16
Author(s):  
R. Petráš ◽  
J. Mecko ◽  
V. Nociar
Keyword(s):  
Root Mean Square Error ◽  
Systematic Error ◽  
Mean Square Error ◽  
Statistical Tests ◽  
Mean Square ◽  
Poplar Clones ◽  
Mean Diameter ◽  
Empirical Material ◽  
Relative Root

The results obtained in research on the quality of raw timber by means of the structure of assortments for the stands of poplar clones Robusta and I-214 are presented in the paper. Models for an estimation of the structure of basic assortments of poplar stands were constructed separately for each clone in dependence on mean diameter, quality of stems, and damage to stems in the stand. The clone Robusta has higher proportions of higher-quality assortments than the clone I-214. The accuracy of models was determined on empirical material. It was confirmed by statistical tests that the models did not have a systematic error. The relative root mean-square error for main assortments of the clone I-214 is 15–27% and Robusta 13–24%.

scholarly journals Predicting the discharge coefficient of oblique cylindrical weir using neural network techniques

2021 ◽  
Vol 14 (16) ◽  
Author(s):  
Adnan A. Ismael ◽  
Saleh J. Suleiman ◽  
Raid Rafi Omar Al-Nima ◽  
Nadhir Al-Ansari
Keyword(s):  
Neural Network ◽  
Mean Square Error ◽  
Radial Basis Function Network ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Superior Performance ◽  
Mean Square ◽  
The Third ◽  
Testing Stage ◽  
Inclination Angles

AbstractCylindrical weir shapes offer a steady-state overflow pattern, where the type of weirs can offer a simple design and provide the ease-to-pass floating debris. This study considers a coefficient of discharge (Cd) prediction for oblique cylindrical weir using three diameters, the first is of D1 = 0.11 m, the second is of D2 = 0.09 m, and the third is of D3 = 0.06.5 m, and three inclination angles with respect to channel axis, the first is of θ1 = 90 ͦ, the second is of θ2 = 45 ͦ, and the third is of θ3 = 30 ͦ. The Cd values for total of 56 experiments are estimated by using the radial basis function network (RBFN), in addition of comparing that with the back-propagation neural network (BPNN) and cascade-forward neural network (CFNN). Root mean square error (RMSE), mean square error (MSE), and correlation coefficient (CC) statics are used as metrics measurements. The RBFN attained superior performance comparing to the other neural networks of BPNN and CFNN. It is found that, for the training stage, the RBFN network benchmarked very small RMSE and MSE values of 1.35E-12 and 1.83E-24, respectively and for the testing stage, it also could benchmark very small RMSE and MSE values of 0.0082 and 6.80E-05, respectively.

Comparison of Thresholding and Edge Detection Segmentation Techniques

2013 ◽  
Vol 860-863 ◽  
pp. 2783-2786
Author(s):  
Yu Bing Dong ◽  
Hai Yan Wang ◽  
Ming Jing Li
Keyword(s):  
Image Segmentation ◽  
Root Mean Square Error ◽  
Edge Detection ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Experimental Results ◽  
Mean Square ◽  
Segmentation Method ◽  
Segmentation Algorithms

Edge detection and thresholding segmentation algorithms are presented and tested with variety of grayscale images in different fields. In order to analyze and evaluate the quality of image segmentation, Root Mean Square Error is used. The smaller error value is, the better image segmentation effect is. The experimental results show that a segmentation method is not suitable for all images segmentation.

scholarly journals Rapid determination of tannin in Danshen and Guanxinning injections using UV spectrophotometry for quality control

2018 ◽  
Vol 11 (06) ◽  
pp. 1850034
Author(s):  
Hongxia Huang ◽  
Yuanyuan Lv ◽  
Xiaoyi Sun ◽  
Shuangshuang Fu ◽  
Xuefang Lou ◽  
...  
Keyword(s):  
Quality Control ◽  
Chinese Medicine ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Uv Spectroscopy ◽  
Uv Spectrophotometry ◽  
Mean Square ◽  
Tannin Content

A technique for the determination of tannin content in traditional Chinese medicine injections (TCMI) was developed based on ultraviolet (UV) spectroscopy. Chemometrics were used to construct a mathematical model of absorption spectrum and tannin reference content of Danshen and Guanxinning injections, and the model was verified and applied. The results showed that the established UV-based spectral partial least squares regression (PLS) tannin content model performed well with a correlation coefficient ([Formula: see text]) of 0.952, root mean square error of calibration (RMSEC) of 0.476[Formula: see text][Formula: see text]g/ml, root mean square error of validation (RMSEV) of 1.171[Formula: see text][Formula: see text]g/ml, and root mean square error of prediction (RMSEP) of 0.465[Formula: see text][Formula: see text]g/ml. Pattern recognition models using linear discriminant analysis (LDA) and [Formula: see text] nearest neighbor ([Formula: see text]-NN) classifiers based on UV spectrum could successfully classify different types of injections and different manufacturers. The established method to measure tannin content based on UV spectroscopy is simple, rapid and reliable and provides technical support for quality control of tannin in Chinese medicine injections.

Fast Determination of Active Components in Fructus Corni by Near Infrared Spectroscopy

2013 ◽  
Vol 807-809 ◽  
pp. 2054-2058
Author(s):  
Hai Yan Gong ◽  
Ya Nan Hu ◽  
Cai Xia Xie ◽  
Yong Xia Cui ◽  
Yan Bai
Keyword(s):  
Quality Control ◽  
Infrared Spectroscopy ◽  
Mean Square Error ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Calibration Model ◽  
Mean Square ◽  
Active Components ◽  
Near Infrared Reflectance ◽  
Pharmaceutical Industries

Today, near-infrared (NIR) has been proved to be a powerful analytical tool. It has been applied widely in agricultural, petrochemical, textile and pharmaceutical industries. In this paper, near-infrared spectroscopy (NIRS) combined with partical least square (PLS) was used as a qualitative tool to rapidly determinate two active components in Fructus Corni. The PLS calibration model of NIR Spectroscopy, the correlation coefficients (R2) of Loganin and Morroniside were 0.95895 and 0.98450, the root-mean-square error of cross-validation (RMSECV), the Correction of deviation, the prediction mean square error was 0.0344,0.109;0.0625, 0.2641 and 0.0948, 0.233. The result shows that, the near-infrared Reflectance Spectroscopy could be used to determinate the content of Loganin and Morroniside, and meanwhile as a simple and rapid new method for the quality assessment of Fructus Corni. In addition, the NIRS has a unique advantage in the quality control of traditional Chinese Medicine (TCM), such as rapid, accurate, nondestructive and no pollution. It is expected to be further uses in the quality control of TCM. It is can achieve the requirement of rapid detection of large quantities of Fructus Corni.

Comparison and Evaluation of Edge Detection Segmentation Techniques

2014 ◽  
Vol 889-890 ◽  
pp. 1069-1072
Author(s):  
Yu Bing Dong ◽  
Ming Jing Li ◽  
Hai Yan Wang
Keyword(s):  
Image Processing ◽  
Root Mean Square Error ◽  
Edge Detection ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Basic Problem ◽  
Mean Square ◽  
Detection Techniques ◽  
Image Edge Detection ◽  
Image Edge

Edge detection is the basic problem in the field of image processing. Various image edge detection techniques are introduced. Using various edge detection techniques different images are analyzed and compared by MATLAB7.0. In order to evaluate the effect of edge segmentation, the root mean square error is used. The experimental results show that no an edge detection technique works well for all types of images.

Selecting velocity fields in urban pluvial floods from pre-calculated data

2020 ◽  
Author(s):  
Robert Sämann ◽  
Thomas Graf ◽  
Insa Neuweiler
Keyword(s):  
High Resolution ◽  
Water Level ◽  
Mean Square Error ◽  
Nearest Neighbor ◽  
Calculated Data ◽  
Velocity Fields ◽  
Water Levels ◽  
Mean Square ◽  
Run Off

<p><span>Early warning systems for floods in urban areas should forecast water levels and damage estimation to protect vulnerable regions. To estimate the danger of a flood for buildings and people, the energy of the flood has to be taken into account additionally to the water level. The energy is related to the flow velocity. For directing rescue workers or trace spreading of contaminants through flooded streets, a high resolution of the water’s energy in space and time is required. Direct numerical run-off calculation is too slow for a flood forecast in time. Therefore a database with pre-calculated events is needed and a method to select the water levels and velocity fields that are similar to a forecasted rain event. </span></p><p><span>We present a method, how to create a real-time forecast based on pre-calculated data. The selection and weighting of the pre-calculated data is based on the precipitation pattern in the flood region. A nearest neighbor approach is applied to find water levels and velocity fields from a database that are similar to the forecasting event. For the ranking of similarity, different new metrics are compared against each other. The quality of the metrics is tested with a new approach of comparing velocity fields on the surface and in the pipe system. Considering both domains is crucial for understanding the complex dynamic flow paths on the surface. An urban catchment of 5 km² with high resolution (~3 m³) triangular surface mesh and connected drainage system is used for a hydrodynamic run-off simulation. The 1D-2D coupled software HYSTEM EXTRAN is used to generate the water levels and velocity fields for strong rainfall events of the past 20 years. More than 900 events with a duration between 15 minutes and 24 hours and return periods between 10 and 100 years were calculated and stored as the “pre-calculated” dataset.</span></p><p><span>For comparing two events, the mean square error is calculated between the precipitation patterns with different approaches to select the start index and number of intervals. This number depends on the hydraulic response time, the temporal resolution and the length of the reference pattern. The quality of the nearest neighbor selection is quantified using the Nash–Sutcliffe model efficiency coefficient of pipe flow and the root mean square error of water level and velocity in significant surface cells. Additionally, the transport paths of artificial contamination spills are compared between the events to show the reproducibility of velocity fields for each metric. </span></p><p><span>Results show that the reaction time and the wetting state of the surface is very important. Single cell values correspond well between a forecasted and a dataset event. However, complex transport paths have a very high variability that is not reproducible with similar events. Further research is required to clarify if this is a result of the random walk approach or of the injection time of the particles. </span></p>

Modified No Search Scheme based Domain Blocks Sorting Strategies for Fractal Image Coding

2014 ◽  
Vol 69 (10-11) ◽  
pp. 511-520
Author(s):  
Xing-Yuan Wang ◽  
Dou-Dou Zhang ◽  
Na Wei
Keyword(s):  
Mean Square Error ◽  
Image Coding ◽  
The Other ◽  
Mean Square ◽  
Minimum Value ◽  
Fractal Image ◽  
Fractal Image Coding ◽  
Domain Block ◽  
Partition Method

AbstractA novel fractal image coding algorithm based on domain blocks sorting strategies and modified no search scheme is proposed in this paper. On one hand, in order to improve the encoding time, a modified no search (MNS) scheme is adopted. Firstly, the image is divided into blocks of different size utilizing an adaptive quadtree partition method. Secondly, one finds the location of the best matching domain block using the MNS scheme for the range blocks, whose sizes are larger than the preset minimum value. Thirdly, the types of the range block and domain block are computed employing the proposed approach, and then the corresponding computation of mean square error (MSE) is determined. The computation of the MSE is reduced and the encoding phase speeds up. On the other hand, the range blocks with the minimal sizes are encoded applying the proposed domain blocks sorting (DBS) method. Contrast experiment results show that the proposed algorithm can obtain good quality of the reconstructed images and shorten the encoding time significantly.

An inter- and intralaboratory quality-control survey of radioimmunoassay of insulin, thyroxin, thyrotropin, cortisol, digoxin, gastrin, beta 2-microglobulin, and IgE in Japan with commercially available kits.

1983 ◽  
Vol 29 (8) ◽  
pp. 1501-1507 ◽  
Author(s):  
Y Shishiba ◽  
M Irie ◽  
H Yamada ◽  
F Kinoshita
Keyword(s):  
Quality Control ◽  
External Control ◽  
Mean Square ◽  
Standard Curve ◽  
Accuracy And Precision ◽  
Wide Scatter ◽  
Control Survey ◽  
Beta 2 Microglobulin ◽  
The Individual

Abstract We report results of a quality-control survey of radioimmunoassay (RIA) of eight analytes, participated in by 249 laboratories of various types throughout Japan. For the purpose of the external control survey, lyophilized specimens containing two different concentrations of each analyte were sent to the participating laboratories, which supplied both their assay values and their raw data for the standard curves and for the samples. The individual data for the standard curve were analyzed by the RIA data-processing program described by Faden and Rodbard. The precision profile obtained for the individual assay was used as the estimate of the quality of each assay. Although there was a wide scatter in assay values, the quality of the assay by the individual laboratories was not the major contributor to this scattering, because the values they reported for the assays and precision profiles of the standard curves were almost identical with those obtained from the kit manufacturers. When the reported assay values were analyzed according to the brand of kits, by analysis of variance, the treatment mean square due to difference in the make of the kits significantly exceeded the error mean square due to "within-kit" variation in the assay of insulin, thyroxin, thyrotropin, cortisol, gastrin, and digoxin. The CVs for "between-kit," "within-kit," "between-assay" and "within-assay" variations (the latter two aspects were studied in a representative laboratory, for convenience of comparison) were about 20, 15, 13, and 7%, respectively. Because the observed within-kit variation is of almost the same magnitude as that expected from the combination of within-assay and between-assay variation, the skill of the users probably was equal and the accuracy and precision of the kits probably had the greatest impact on assay variation. This survey also emphasizes the criteria for commercially available RIA kits.

scholarly journals State Estimation and Forecasting of the Ski-Slope Model Using an Improved Shadowing Filter

2016 ◽  
Vol 26 (04) ◽  
pp. 1650056
Author(s):  
Auni Aslah Mat Daud
Keyword(s):  
Root Mean Square Error ◽  
State Estimation ◽  
Mean Square Error ◽  
Gradient Descent ◽  
Slight Modification ◽  
Mean Square ◽  
Step Size ◽  
Adaptive Step Size ◽  
Adaptive Step

In this paper, we present the application of the gradient descent of indeterminism (GDI) shadowing filter to a chaotic system, that is the ski-slope model. The paper focuses on the quality of the estimated states and their usability for forecasting. One main problem is that the existing GDI shadowing filter fails to provide stability to the convergence of the root mean square error and the last point error of the ski-slope model. Furthermore, there are unexpected cases in which the better state estimates give worse forecasts than the worse state estimates. We investigate these unexpected cases in particular and show how the presence of the humps contributes to them. However, the results show that the GDI shadowing filter can successfully be applied to the ski-slope model with only slight modification, that is, by introducing the adaptive step-size to ensure the convergence of indeterminism. We investigate its advantages over fixed step-size and how it can improve the performance of our shadowing filter.

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