NON-CONTACT MEASUREMENT SYSTEM OF FREEFORM SURFACE AND NURBS RECONSTRUCTION OF MEASUREMENT POINTS

Based on the development of the non-contact measurement system of free-formsurface, NURBS reconstruction of measurement points of freeform surface is effectively realized bymodifying the objective function and recursive procedure and calculating the optimum number ofcontrol points. The reconstruction precision is evaluated through Ja-cobi's transformation method.The feasibility of the measurement system and effectiveness of the reconstruction algorithm aboveare proved by experiment.

Self-tuning weighted measurement fusion Kalman filter and its convergence

For multisensor systems,when the model parameters and the noise variances are unknown,the consistent fused estimators of the model parameters and noise variances are obtained,based on the system identification algorithm,correlation method and least squares fusion criterion.Substituting these consistent estimators into the optimal weighted measurement fusion Kalman filter,a self-tuning weighted measurement fusion Kalman filter is presented.Using the dynamic error system analysis （DESA） method,the convergence of the self-tuning weighted measurement fusion Kalman filter is proved,i.e.,the self-tuning Kalman filter converges to the corresponding optimal Kalman filter in a realization.Therefore,the self-tuning weighted measurement fusion Kalman filter has asymptotic global optimality.One simulation example for a 4-sensor target tracking system verifies its effectiveness.

WEIGHTED LASSO ESTIMATES FOR SPARSE LOGISTIC REGRESSION:NON-ASYMPTOTIC PROPERTIES WITH MEASUREMENT ERRORS

For high-dimensional models with a focus on classification performance,the?1-penalized logistic regression is becoming important and popular.However,the Lasso estimates could be problematic when penalties of different coefficients are all the same and not related to the data.We propose two types of weighted Lasso estimates,depending upon covariates determined by the Mc Diarmid inequality.Given sample size n and a dimension of covariates p,the finite sample behavior of our proposed method with a diverging number of predictors is illustrated by non-asymptotic oracle inequalities such as the?1-estimation error and the squared prediction error of the unknown parameters.We compare the performance of our method with that of former weighted estimates on simulated data,then apply it to do real data analysis.

Non-contact measurement and multi-objective analysis of drilling temperature when drilling B_4C reinforced aluminum composites

Non-contact measurements of machining temperatures were performed with optical pyrometer when drilling particle（B4C） reinforced metal matrix composites（MMCs） with different drills. The effect of particle content, cutting speed, feed rate and tool material on the maximum drilling temperature was investigated. The drilling parameters were optimized based on multiple performance characteristics in terms of the maximum cutting temperature and tool wear. According to the results, the most influential control factors on the cutting temperatures are found to be particle fraction, feed rate and interaction between the cutting speed and particle content, respectively. The influences of the cutting speed and drill material on the drilling temperature are found to be relatively lower for the used range of parameters. Minimum cutting temperatures are obtained with lower particle fraction and cutting speed, with relatively higher feed rates and carbide tools. The results reveal that optimal combination of the drilling parameters can be used to obtain both minimum cutting temperature and tool wear.

MEASUREMENT OF NUMBER AVERAGE MOLECULAR WEIGHT OF STYRENE OLIGOMER BY ^(13)C-NMR METHOD

^(13)C-NMR ~1H-decoupled spectra of styrene polymers were assigned by comparison with modelcompounds, then used in measurements of number average molecular weights. The higher limit of an exactdetermination of the end group signal is less than a molecular weight of 10~4. For polymer samples withM_n<10~3, the results obtained from ^(13)C-NMR spectra of saturated carbon region are in excellent agreementwith the values determined by ~1H-NMR, SEC, and VPO methods, while the results from ^(13)C-NMR spectra ofphenyl C-1 carbon region are somewhat higher than the values determined by other methods.

Anthropometric measurements at birth as predictor of low birth weight

In developing countries, low birth weight (BW < 2500 grams) accounts for 60% - 80% of neonatal deaths. Early identification and referral of LBW babies for extra essential newborn care is vital in preventing neonatal deaths. Studies carried out in different populations have suggested that the use of newborn anthropometric surrogates of birth weight may be a simple and reliable method to identify LBW babies. previous studies reported correlation between birth weight to several anthropometric measurements and their predictive value. We aimed to evaluate the correlation between birth length, head, chest, and mid arm circumferences to birth weight. Methods: A cross sectional study has been conducted in SHARIATI Hospital in Tehran, from September 2008 to February 2009. All Consecutive full-term. Single ton, live born babies were included and anthropometric measurements carried out within 48 hours after birth by authors. Birth weight was measured by digital scale within the first 24 hours after delivery. Birth length by somatometer and head, chest, mid arm circumferences were measured 2 times by using plastic measuring tape. Result: Out of 500 newborn studied. 52.2% were male and 47.8% were female. The mean birth weight was 3195.4 ± 399.9 gram and 3.8% of newborns were low birth weight. It was evident a positive correlation of birth weight to all such anthropometric measurements with the highest correlation coefficient for chest circumference (r: 0.74). By ROC- AUC analyses, chest circumference (AUC = 0.91, 95% CI 0.84 to 0.97) and arm circumference (AUC = 0.87, 95% CI 0.79 to 0.95) were identified as the optimal surrogate indicators of LBW babies. The optimal cut-points for chest circumference and arm circumference to identify LBW newborns were ≥31.2 cm and ≥10.2 cm respectively. Conclusions: Chest and mid arm circumferences were the best anthropometric surrogates of LBW among studied Iranian population. Further studies are needed in the field to cross-validate our results. anthropometric values are simple, practicable, quick and reliable indicator for predicting LBW newborns in the community and can be easily measured by paramedical workers in developing nation.

Estimating the Parameters Geographically Weighted Regression (GWR) with Measurement Error

Geographically weighted regression models with the measurement error are a modeling method that combines the global regression models with the measurement error and the weighted regression model. The assumptions used in this model are a normally distributed error with that the expectation value is zero and the variance is constant. The purpose of this study is to estimate the parameters of the model and find the properties of these estimators. Estimation is done by using the Weighted Least Squares (WLS) which gives different weighting to each location. The variance of the measurement error is known. Estimators obtained are . The properties of the estimator are unbiased and have a minimum variance.

Effects of 6-Month Weight Loss New Program on Anthropometric Measurements and Biological Profile

Obesity has become a leading global health problem owing to its strong association with a high incidence of diseases. Obesity is results from the complex interaction of environmental factors that act on a genetic background and led to excess accumulated of body fat. Treatment of obesity includes determination of the degree of obesity, management weight loss programme and maintenance of body weight. To investigate effect 6 months safe weight loss program on anthropometric measurements and biological and metabolic profiles in obese patients. 35 obese patients were enrolled in the present study： 20 female, 15 male. Participants underwent a comprehensive series of biochemical, anthropometrical, physical, and nutritional prior to treatment- at baseline and after the six-month of the obesity treatment program. 6 months weight loss program. Diet plan intervention in small groups. In-person training and individual diet plan intervention. There is significant reduction in weight and high improvement in laboratory parameters. Our data showed that there an improvement in weight loss. These finding may be important for controlling obesity-related co-morbidities. It would appear that moderate weight loss of 8-10 % observed in our study resulted in significant improvements in laboratory parameters

Machine Vision for Non-Contact Automated Countersink Measurement

The slug rivet is widely used in wing assembly due to its longer fatigue life and better sealing performance compared with other connection technologies.As a countersink with dual-angle is widely adopted for this type of connection,the countersink diameter and depth are key factors that affect assembly quality.Therefore,it is of great importance to efficiently inspect the countersink quality to ensure high accuracy.However,contact measurements are susceptible to the loss of accuracy due to cutting debris and lube build-up,while the hole-scanning method using laser profilometry is time consuming and complex.In this paper,a non-contact method for countersink diameter and depth measurement based on a machine vision system is proposed.The countersink diameter can be directly measured by the machine vision system,while the countersink depth is determined through the countersink diameter indirectly.First,by means of image processing technology together with an improved edge detection algorithm,the countersink diameter can be obtained.Then,a 3D microscope is employed to measure the countersink depth,which helps to model the countersink.As a result,once the countersink diameter is measured,so is the depth.The experimentation demonstrated that this method has strong feasibility and enables time saving,which is conducive to improve the riveting efficiency.

A LASER-SCANNING NON-CONTACT MEASURING METHOD FOR ROUNDNESS ERRORS

利用激光狭缝扫描原理和光电传感技术，提出了一种用于测量大型回转体类零件圆度误差的激光扫描非接触测量方法和测量系统。本文详细论述了测量系统及其测量原理、工件安装偏心误差的分离技术和计算机实时数据处理系统，实验结果证实了这种测量方法的可行性。

WEIGHTED ESTIMATES FOR COMMUTATORS OF MULTILINEAR CALDERóN-ZYGMUND OPERATORS WITH NON-DOUBLING MEASURES

Let μ be a nonnegative Radon measure on Rd, which only satisfies the polynomial growth condition. Under this assumption, the authors obtain some weighted weaktype estimates for the commutators generated by the multilinear CalderSn-Zygmund op- erators and RBMO（μ） functions.

Accurate Measurement Method for Tube's Endpoints Based on Machine Vision

Tubes are used widely in aerospace vehicles, and their accurate assembly can directly affect the assembling reliability and the quality of products. It is important to measure the processed tube＇s endpoints and then fix any geometric errors correspondingly. However, the traditional tube inspection method is time-consuming and complex operations. Therefore, a new measurement method for a tube＇s endpoints based on machine vision is proposed. First, reflected light on tube＇s surface can be removed by using photometric linearization. Then, based on the optimization model for the tube＇s endpoint measurements and the principle of stereo matching, the global coordinates and the relative distance of the tube＇s endpoint are obtained. To confirm the feasibility, ll tubes are processed to remove the reflected light and then the endpoint＇s positions of tubes are measured. The experiment results show that the measurement repeatability accuracy is 0.167 mm, and the absolute accuracy is 0.328 ram. The measurement takes less than 1 min. The proposed method based on machine vision can measure the tube＇s endpoints without any surface treatment or any tools and can realize on line measurement.

Spatial Downscaling of the Tropical Rainfall Measuring Mission Precipitation Using Geographically Weighted Regression Kriging over the Lancang River Basin, China

Satellite-based precipitation products have been widely used to estimate precipitation, especially over regions with sparse rain gauge networks. However, the low spatial resolution of these products has limited their application in localized regions and watersheds.This study investigated a spatial downscaling approach, Geographically Weighted Regression Kriging(GWRK), to downscale the Tropical Rainfall Measuring Mission(TRMM) 3 B43 Version 7 over the Lancang River Basin(LRB) for 2001–2015. Downscaling was performed based on the relationships between the TRMM precipitation and the Normalized Difference Vegetation Index(NDVI), the Land Surface Temperature(LST), and the Digital Elevation Model(DEM). Geographical ratio analysis(GRA) was used to calibrate the annual downscaled precipitation data, and the monthly fractions derived from the original TRMM data were used to disaggregate annual downscaled and calibrated precipitation to monthly precipitation at 1 km resolution. The final downscaled precipitation datasets were validated against station-based observed precipitation in 2001–2015. Results showed that: 1) The TRMM 3 B43 precipitation was highly accurate with slight overestimation at the basin scale(i.e., CC(correlation coefficient) = 0.91, Bias = 13.3%). Spatially, the accuracies of the upstream and downstream regions were higher than that of the midstream region. 2) The annual downscaled TRMM precipitation data at 1 km spatial resolution obtained by GWRK effectively captured the high spatial variability of precipitation over the LRB. 3) The annual downscaled TRMM precipitation with GRA calibration gave better accuracy compared with the original TRMM dataset. 4) The final downscaled and calibrated precipitation had significantly improved spatial resolution, and agreed well with data from the validated rain gauge stations, i.e., CC = 0.75, RMSE(root mean square error) = 182 mm, MAE(mean absolute error) = 142 mm, and Bias = 0.78%for annual precipitation and CC = 0.95, RMSE = 25 mm, MAE = 16 mm, and Bias = 0.67% for monthly precipitation.

Deep-Hole Inner Diameter Measuring System Based on Non-contact Capacitance Sensor

A precise aperture measuring system of small deep holes with capacitance sensors is presented. Based on the working principle of non-contact capacitance sensors, influence of the edge effect of gauge head is studied, and one capacitance sensor for measuring the aperture of the small blind holes or through holes is introduced. The system is composed of one positioning device, one aperture measuring capacitance sensor, one measuring circuit, and software. This system employs visual CCD and two-dimensional mic...

Study on Coaxiality Measurement System of Compound Gear Shaft Based on Non⁃contact Optic

Aiming at the shortcomings of traditional contact measurement methods such as low measurement efficiency,high cost and low accuracy,a non-contact optical measurement method based on the laser displacement sensor is proposed.According to the relevant regulations of the coaxiality error evaluation standard and the structural characteristics of the compound gear shaft,we have designed and built a set of supporting software system as well as a hardware test platform.In this paper,the distance difference threshold and scale threshold methods are used to eliminate outlier data.The least squares circle is selected to calculate the center of the circle and the minimum containment cylinder axis method is used as the reference axis of the composite gear shaft.Compensated by the standard step shaft calibration,the coaxiality error of the composite gear shaft can be measured to be within 0.01 mm in less than two minutes.The range value of the multi-section measurement test is 0.065 mm.The average coaxiality error is∅0.476 mm.

Fuzzy-Weighted Similarity Measures for Memory-Based Collaborative Recommender Systems

Memory-based collaborative recommender system (CRS) computes the similarity between users based on their declared ratings. However, not all ratings are of the same importance to the user. The set of ratings each user weights highly differs from user to user according to his mood and taste. This is usually reflected in the user’s rating scale. Accordingly, many efforts have been done to introduce weights to the similarity measures of CRSs. This paper proposes fuzzy weightings for the most common similarity measures for memory-based CRSs. Fuzzy weighting can be considered as a learning mechanism for capturing the preferences of users for ratings. Comparing with genetic algorithm learning, fuzzy weighting is fast, effective and does not require any more space. Moreover, fuzzy weightings based on the rating deviations from the user’s mean of ratings take into account the different rating scales of different users. The experimental results show that fuzzy weightings obviously improve the CRSs performance to a good extent.

Application of Three-dimensional Body Measurement System

The configuration principles and functions of the non-contact three-dimensional （3D） body measurement system （BMS） developed by the Textile/Clothing Technology Corporation （[TC]^2） are described in this paper. The advantages of this new system, compared with traditional contact body measurement instruments （ Martin instruments ） are discussed by selecting 40 female undergraduates of Donghna University as the scan objects. In the experiments both the Martin instruments and [TC]^2 BMS were used respectively. According to the data of different position （Bust Circumference, Full Waist, Full Hips, Bust Height, Front Waist Height and Back Waist Height） obtained from both of the methods we can get the correlation coefficient which is close to 1, indicating that the results of both methods have comparability. Finally some suggestions for the further applications of the non-contact BMS in the apparel development of China are given.

Three-Dimensional Measurement and Reconstruction of Fabric Drape Shape

This paper introduces a new method of measuring the three-dimensional drape shape of fabrics with structural light. First, we apply parallel annular structural light to form light and shade alternating contour stripes on the surface of fabrics. We then collect the images of contour stripes using Charge Coupled Device (CCD). Subsequently, we process the images to identify the contour stripes and edges of fabrics, and obtain the fabric contour lines of curved surfaces. Finally, we apply three-dimensional curved surface modeling method based on a network of polar coordinates, and reconstruct the three-dimensional drape shape of fabrics. Experiments show that our method is effective in testing and reconstructing three-dimensional drape shape of fabrics.

Optimization Study of Outburst Prevention Measures for Tuzhu Coal Mine Based on Fixed Weight Clustering Analysis

Affected by many involved factors, different dimensions, data with large difference, incomplete information and so on, the most optimal selection of regional outburst prevention measures for outburst mine has become a complicated system project. The traditional way of outburst prevention measure selection belongs to qualitative method, which may cause high-cost of gas control, huge quantities of drilling work, long construction time and even secondary disaster. To solve the above-mentioned problems, in light of occurrence status of coal seam gas in No. 21 mining area of Jinzhushan Tuzhu Mine, through grey fixed weight clustering theory and a combination method of qualitative and quantitative analysis, the judging model with multi-objective classification for optimization of outburst prevention measures was established. The three weight coefficients of outburst prevention technology scheme are sorted, in order to determine the advantages and disadvantages of each outburst prevention technology scheme under the comprehensive evaluation of multi-target. Finally, the problem of quantitative selection for regional outburst prevention technology scheme is solved under the situation of multi-factor mode and incomplete information, which provides reasonable and effective technical measures for prevention of coal and gas outburst disaster.

A random forest algorithm based on similarity measure and dynamic weighted voting

The random forest model is universal and easy to understand, which is often used for classification and prediction. However, it uses non-selective integration and the majority rule to judge the final result, thus the difference between the decision trees in the model is ignored and the prediction accuracy of the model is reduced. Taking into consideration these defects, an improved random forest model based on confusion matrix (CM-RF)is proposed. The decision tree cluster is selectively constructed by the similarity measure in the process of constructing the model, and the result is output by using the dynamic weighted voting fusion method in the final voting session. Experiments show that the proposed CM-RF can reduce the impact of low-performance decision trees on the output result, thus improving the accuracy and generalization ability of random forest model.