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Profile measurement with boundary information plays a vital role in the detection of quality in the assembly of aviation parts. The purpose of this paper is to improve the evaluation accuracy of the aerodynamic shapes of airplanes, the profiles of large-sized parts need to be measured accurately.

In this paper, an accurate profile measurement method based on boundary reference points is proposed for the industrial stereo-vision system. Based on the boundary-reference points, the authors established a priori constraint for extracting the boundary of the measured part. Combining with the image features of background and the measured part, an image-edge compensation model is established to extract the boundary of the measured part. The critical point of a laser stripe on the edge of the measured part is extracted corresponding to the boundary constraint. Finally, as per the principle of binocular vision, the profile of the measured part is reconstructed.

Laboratory experiments validate the measurement accuracy of the proposed method which is 0.33 mm. In the analysis of results between the measured data and the theoretical model, the measuring accuracy of the proposed method was found to be significantly higher than that of the other traditional methods.

An aviation part was measured in the part-assembly shop by the proposed method, which verified the feasibility and effectiveness of this method. The research can realize the measurement of smooth surface boundary which can solve existing profile reconstruction problems for aviation parts.

According to the two-dimensional contour constraint, critical points of the laser strip sequence at the edge of measured part are extracted and the accurate profile reconstruction with the boundary is realized.

This paper aims to propose an elementary approach towards the measurement of a globoidal cam profile used in an automatic tool changer (ATC) of computer numerical control (CNC) machines.

A simple and unique online method has been designed for the profile metrology of the cam. This simple methodology will replace the traditional methodology of profile metrology of cam by coordinate measuring machine (CMM). A globoidal cam with an indexable turret and roller follower (rotating in an enclosed track) has been evaluated in our analysis. This analysis plays a significant role in the performance determination of the cam as well as the ATC of CNC machines.

A novel model has been designed and implemented to investigate the profile of a globoidal cam. The proposed methodology becomes an enhancement over the old methodology, i.e. measurement through CMM. Theoretical analysis and practical implementation prove the significance of the method.

An enhanced methodology to effectively measure the globoidal cam profile has been proposed. The practical implication of the proposed methodology remains for the CNC machine tool and ATC manufacturers. Finally, analytical explorations have been carried out to prove the validity of the proposal.

This study aims to determine the correlation of anthropometric measurements with serum lipid profile among Malay subjects in Kuala Terengganu, Malaysia.

This cross-sectional study was conducted in Kuala Terengganu on a total of 193 individuals aged 18-60 years. Subjects were recruited via direct interview as per inclusion criteria and anthropometric measurements, i.e. body mass index (BMI), waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), waist-to-height ratio, abdominal volume index and conicity index, were taken using International Standards for Anthropometric Assessment Guidelines. Fasting blood samples were collected for serum lipid profile analysis that measures triglyceride (TG), total cholesterol (TC), high-density lipoproteins (HDL), low-density lipoproteins (LDL), TG/HDL, TC/HDL and LDL/HDL. Besides socio-demographic characteristics, means and association of anthropometric parameters with lipid profiles were performed using simple linear regression and multivariate-adjusted regression analysis.

The mean age of obese (male [39.2 ± 8.7] and female [41.1 ± 1.0]) and non-obese (male [29.8 ± 1.3] and female [33.3 ± 1.3]) respondents was compared. Means of anthropometric indices and lipid profile were significantly (p < 0.001) higher in obese than in non-obese group. Multivariate-adjusted regression showed that weight and BMI increased risks for prevalent high TC, TG, LDL, TC/HDL, TG/HDL, LDL/HDL, hypercholesterolemia, hypertriglyceridemia and dyslipidemia. Regardless of sex, age and prevalent obese status, WHR increased risks for high prevalence of TC, TG, LDL, TC/HDL and LDL/HDL, and presents an independent risk factor for hypercholesterolemia and dyslipidemia. WC was highly associated with TG, while HC was associated with atherogenic lipid profile ratios: TC/HDL, TG/HDL and LDL/HDL.

In conclusion, the lipid profile (TC, TG and TG/HDL) of triglyceridemia and hypercholesteremia is highly correlated with anthropometric measurements (BMI, WC and WHR) of central obesity that predict obesity-associated cardiac risks.

The asymmetry of the velocity profile caused by geometric deformation, complex turbulent motion and other factors must be considered to effectively use the flowmeter on any section. This study aims to better capture the flow field information and establish a model to predict the profile velocity, we take the classical double elbow as the research object and propose to divide the flow field into three categories with certain common characteristics.

The deep learning method is used to establish the model of multipath linear velocity fitting profile average velocity. A total of 480 groups of data are taken for training and validation, with ten integer velocity flow fields from 1 m/s to 10 m/s. Finally, accuracy research with relative error as standard is carried out.

The numerical experiment yielded the following promising results: the maximum relative error is approximately 1%, and in the majority of cases, the relative error is significantly lower than 1%. These results demonstrate that it surpasses the classical optimization algorithm Equal Tab (5%) and the traditional artificial neural network (3%) in the same scenario. In contrast with the previous research on a fixed profile, we focus on all the velocity profiles of a certain length for the first time, which can expand the application scope of a multipath ultrasonic flowmeter and promote the research on flow measurement in any section.

This work proposes to divide the flow field of double elbow into three categories with certain common characteristics to better capture the flow field information and establish a model to predict the profile velocity.

Utilizing datasets of Ecuador, Hungary, Kazakhstan, Mexico and Peru from the Programme for the International Assessment of Adult Competencies survey from 2017 to 2018, this study aimed to develop and validate a profile indicating core workplace skills in developing countries.

DeVellis' guide of scale development navigated the development of the profile. Multiple techniques including item analysis, exploratory factor analysis, confirmatory factor analysis and multigroup confirmatory factor analysis were used on a sample of 7,166 participants to validate the profile of core workplace skills in developing countries.

A resultant five-dimensional profile with 18 items was developed: oral communication skills, reading skills, math skills, information and communication technology skills and learning skills. The estimates of composite reliability showed the profile was reliable. The validity estimates of the profile were obtained from several sources including content, convergent, discriminative and construct validity. The measurement invariance was also held for the profile.

Based on the researcher's knowledge, the study is the first attempt to develop a profile to indicate core workplace skills in developing countries. The profile theoretically framed the core workplace skills in developing countries and provides a new measure for identifying, evaluating and thus improving core workplace skills in developing countries for different stakeholders in the era of Education 4.0.

The purpose of this paper is to conduct an independent analysis of all existing geographic profiling software packages to determine if any one is more accurate than the others or if any of the software systems are any more accurate than simple spatial distribution strategies at locating the home base of serial offenders.

An analysis was conducted of all existing geographic profiling software as well as three spatial distribution methods of profiling. Differences in accuracy were assessed using four different methods; dichotomous profile accuracy, simple error measurement, profile error distance, and average top profile area.

Results indicate that not only are the different profiling software systems no more accurate than the spatial distribution control methods, but that accuracy in general was marginal at best. In addition results indicated that certain crimes, such as commercial robbery, were particularly difficult to profile and that the number of crimes in a series was not by itself a good indicator of success of a profile.

The paper shows that future research needs to focus more on determining how various factors such as city type, crime type, road network and spatial aspects of a crime series (dispersion and search area) impact profiling accuracy. In addition future research should also endeavor to determine whether these advanced strategies are substantially more accurate than other simple profiling strategies such as human prediction. Finally, future research should also seek to examine geographic profiling in a real world setting and how geographic profiling impacts the success of open investigations.

Practically, this study casts doubt not only on the overall accuracy of profiling strategies in predicting the likely home location of an offender, but also on whether probability strategies are substantially better than spatial distribution strategies.

This research was the first to independently analyze all of the existing geographic profiling systems against control methods for the purpose of determining the accuracy of these different methods.

Existing calibration methods mainly focus on the camera laser-plane calibration of a single laser-line length, which is not convenient and cannot guarantee the consistency of the results when several three-dimensional (3D) scanners are involved. Thus, this study aims to provide a unified step for different laser-line length calibration requirements for laser profile measurement (LPM) systems.

3D LPM is the process of converting physical objects into 3D digital models, wherein camera laser-plane calibration is critical for ensuring system precision. However, conventional calibration methods for 3D LPM typically use a calibration target to calibrate the system for a single laser-line length, which needs multiple calibration patterns and makes the procedure complicated. In this paper, a unified calibration method was proposed to automatically calibrate the camera laser-plane parameters for the LPM systems with different laser-line lengths. The authors designed an elaborate planar calibration target with different-sized rings that mounted on a motorized linear platform to calculate the laser-plane parameters of the LPM systems. Then, the camera coordinates of the control points are obtained using the intersection line between the laser line and the planar target. With a new proposed error correction model, the errors caused by hardware assembly can be corrected. To validate the proposed method, three LPM devices with different laser-line lengths are used to verify the proposed system. Experimental results show that the proposed method can calibrate the LPM systems with different laser-line lengths conveniently with standard steps.

The repeatability and accuracy of the proposed calibration prototypes were evaluated with high-precision workpieces. The experiments have shown that the proposed method is highly adaptive and can automatically calibrate the LPM system with different laser-line lengths with high accuracy.

In the repeatability experiments, there were errors in the measured heights of the test workpieces, and this is because the laser emitter had the best working distance and laser-line length.

By using this proposed method and device, the calibration of the 3D scanning laser device can be done in an automatic way.

The calibration efficiency of a laser camera device is increased.

The authors proposed a unified calibration method for LPM systems with different laser-line lengths that consist of a motorized linear joint and a calibration target with elaborately designed ring patterns; the authors realized the automatic parameter calibration.

The purpose of this paper is to propose an automatic optical inspection system for measuring the surface profile of a microlens array.

The system set‐up was constructed according to the principle of the Fizeau interferometer. After capturing the ring interference fringe images of the microlens with a camera, the diameter, profile information and optical properties were analyzed through a microlens surface profile algorithm using innovative image pre‐processing with a precision of less than 0.09 micron.

By integrating with the genetic algorithm, the XY‐Table shortest moving path of the system is calculated to achieve the purpose of high‐speed inspection and automatic microlens array surface profile measurement.

The measurement results of this system were also compared with other systems, including the atomic force microscope and stylus profiler, to verify the measurement precision and accuracy of this system.

The main aim of this paper is description of new apparatus and approach for contact less evaluation of surface roughness. For characterization of surface roughness, the procedures based on classical and non‐classical (complexity) parameters are proposed.

For obtaining the roughness profile in the selected direction (on the line transect of the surface), the special arrangements of textile bend around sharp edge is used. The image analysis is used for extraction of surface profile. The system of controlled movement allows one to obtain surface roughness profile in two dimensions.

By using aggregation (cut length principle), the roughness resolution is decreased and roughness profile is created without local roughness variation. After application of cut length principle, the direct combination of slices leads to the creation of roughness surface.

There exists plenty of roughness characteristics based on standard statistics or analysis of spatial processes. For evaluation of suitability of these characteristics, it will be necessary to compare results from sets of textile surfaces.

The measurement of fabric roughness by an RCM device is useful as simple tool for description of roughness in individual slices and in the whole rough plane. This method replaces the traditional contact stylus profiling methods

The reconstruction of surface roughness from individual slices. The utilization of aggregation principle for creation of micro and macro roughness. The evaluation of roughness parameters based on the geometrical characteristics, harmonic analysis and complexity indices.

The purpose of this paper is to present a framework for maintenance analytics that is useful for the assessment of rail condition and for maintenance decision support. The framework covers three essential maintenance aspects: diagnostic, prediction and prescription. The paper also presents principal component analysis (PCA) and local outlier factor methods for detecting anomalous rail wear occurrences using field measurement data.

The approach used in this paper includes a review of the concept of analytics and appropriate adaptation to railway infrastructure maintenance. The diagnostics aspect of the proposed framework is demonstrated with a case study using historical rail profile data collected between 2007 and 2016 for nine sharp curves on the heavy haul line in Sweden.

The framework presented for maintenance analytics is suitable for extracting useful information from condition data as required for effective rail maintenance decision support. The findings of the case study include: combination of the two statistics from PCA model (T² and Q) can help to identify systematic and random variations in rail wear pattern that are beyond normal: the visualisation approach is a better tool for anomaly detection as it categorises wear observations into normal, suspicious and anomalous observations.

A practical implication of this paper is that the framework and the diagnostic tool can be considered as an integral part of e-maintenance solution. It can be easily adapted as online or on-board maintenance analytic tool with data from automated vehicle-based measurement system.

This research adapts the concept of analytics to railway infrastructure maintenance for enhanced decision making. It proposes a graphical method for combining and visualising different outlier statistics as a reliable anomaly detection tool.