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Accurate feature localization is a fundamental problem in computer vision and visual measurement. In a perspective projection model of the camera, the projected center of a spatial circle and the center of the projection ellipse are not identical. This paper aims to show how to locate the real projection center precisely in the perspective projection of a space circle target.

By analyzing the center deviation caused by projection transformation, a novel method is presented to precisely locate the real projection center of a space circle using projective geometry. Solution distribution of the center deviation is analyzed, and the quadratic equation for determining the deviation is derived by locating vanishing points. Finally, the actual projected center of the circular target is achieved by solving the deviation quadratic equations.

The procedures of the author’s method are simple and easy to implement. Experimental data calculated that maximum deviation occurs at approximately between 3π/10 and 2π/5 of the angle between the projection surface and the space target plane. The absolute reduction in error is about 0.03 pixels; hence, it is very significant for a high-accuracy solution of the position of the space circle target by minimizing systematic measurement error of the perspective projection.

The center deviation caused by the space circle projection transformation is analyzed, and the detailed algorithm steps to locate the real projection center precisely are described.

Laser absolute distance measurement has the characteristics of high precision, wide range and non-contact. In laser ranging system, tracking and aiming measurement point is the precondition of automatic measurement. To solve this problem, this paper aims to propose a novel method.

For the central point of the hollow angle coupled mirror, this paper proposes a method based on correlation filtering and ellipse fitting. For non-cooperative target points, this paper proposes an extraction method based on correlation filtering and feature matching. Finally, a visual tracking and aiming system was constructed by combining the two-axis turntable, and experiments were carried out.

The target tracking algorithm has an accuracy of 91.15% and a speed of 19.5 frames per second. The algorithm can adapt to the change of target scale and short-term occlusion. The mean error and standard deviation of the center point extraction of the hollow Angle coupling mirror are 0.20 and 0.09 mm. The mean error and standard deviation of feature points matching for non-cooperative target were 0.06 mm and 0.16 mm. The visual tracking and aiming system can track a target running at a speed of 0.7 m/s, aiming error mean is 1.74 pixels and standard deviation is 0.67 pixel.

The results show that this method can achieve fast and high precision target tracking and aiming and has great application value in laser ranging.

The purpose of this paper is to use vision stereo to simultaneously acquire image pairs under a normal environment. Then the methods of moving edges detection and moving target shifting are applied to reduce noise error in order to position a target efficiently. The target is then double confirmed via image merge and alignment. After positioning, the visual difference between the target and the image created by the stereo vision system is measured for alignment. Finally, the image depth of the target is calculated followed by real-time target tracking.

This study mainly applies Sobel image principle. In addition, moving edges detection and moving target shifting are also used to work with system multi-threading for improving image identification efficiency.

The results of the experiment suggest that real-time image tracking and positioning under a pre-set environment can be effectively improved. On the other hand, tracking and positioning are slightly affected under a normal environment. Errors of distance measurements occur because there is more noise existing.

This study mainly determines the movements and positioning of an object or a target via image. However, the stability of moving edges detection executed by the stereo vision system can be affected if the light sources in an environment are too strong or extreme.

So far the method of tracking and positioning a moving object has been applied to surveillance systems or the application which requires measuring and positioning under a normal environment. The method proposed by this study can also be used to construct a 3D environment.

The method proposed by this study can also be used to construct a 3D environment or tracking moving object to measure the distance.

The purpose of this paper is to propose a defect detection method of silicone caps positional deviation on flexible printed circuit board (FPCB) of keyboard based on automatic optical inspection.

First, the center of silicone caps of target keyboard FPCB image was extracted as feature points for generating the feature image which is used for registration rigidly with the reference feature image generated from the CAD drawings. Then, a flexible image registration method based on the surrounding-control-center B-splines (SCCB) strategy was proposed, which could correct the flexible deformation of the image generated by FPCB substrate while keeping the pasting deviation information about silicone caps unchanged. Finally, on this basis, a nearest neighbor strategy was proposed to detect the positional deviation of silicone caps.

Experimental results show that the proposed method can effectively detect the positional deviation defect of silicone caps. The G-mean value of the proposed method is 0.941746, which is 0.3 higher compared to that of similar research.

This paper presents a method to detect positional deviation defect of silicone caps on keyboard FPCB. Different from the classic B-spline image registration method, the proposed SCCB method used the neighborhood information of the pixel to be registered selectively to calculate the displacement vector needed for its registration, which overcame the problem that the silicone cap pasting deviation information disappears with the correction of the flexible deformation of the image.

This paper aims to comprehensively achieve the requirements of high assembly precision and low cost, a precision-cost model of assembly based on three-dimensional (3D) tolerance is established in this paper.

The assembly precision is related to the tolerance of parts and the deformation of matching surfaces under load. In this paper, the small displacement torsor (SDT) theory is first utilized to analyze the manufacturing tolerances of parts and the assembly deformation deviation of matching surface. In the meanwhile, the extracting method of SDT parameters is proposed and the assembly precision calculation model based on the 3D tolerance is established. Second, an integrated optimization model based on the machining cost, assembly cost (mapping the deviation domain to the SDT domain) and quality loss cost is built. Finally, the practicability of the precision-cost model is verified by optimizing the horizontal machining center.

The assembly deviation has a great influence on cost fluctuation. By setting the optimization objective to maximize the assembly precision, the optimal total cost is CNY 72.77, decreasing by 16.83 per cent from the initial value, which meets economical requirements. Meanwhile, the upper bound of each processing tolerance is close to the maximum value of 0.01 mm, indicating that the load deformation can be offset by appropriately increasing the upper bound of the tolerance, but it is necessary to strictly restrict the manufacturing tolerances of lower parts in a reasonable range.

In this paper, a 3D deviation precision-cost model of assembly is established, which can describe the assembly precision more accurately and achieve a lower cost compared with the assembly precision model based on rigid parts.

The traditional precision design only takes the influence of geometric tolerance of the parts and does not involve the load deformation in the assembly process. This paper aims to analyze the influence mechanism of flexible parts deformation on the geometric precision, and then to ensure the reliability and stability of the mechanical system.

Firstly, this paper adopts the N-GPS to analyze the influence mechanism of flexible parts deformation on the geometric precision and constructs a coupling 3D tolerance mathematical model of the geometric tolerance and the load deformation deviation based on the SDT theory, homogeneous coordinate transformation theory and surface authentication idea. Secondly, the least square method is used to fit the deformation surface of the mating surface under load so as to complete the conversion from the non-ideal element to the ideal element.

This paper takes the horizontal machining center as a case to obtain the deformation information of the mating surface under the self-weight load. The results show that the deformation deviation of the parts has the trend of transmission and accumulation under the load. The terminal deformation cumulative amount of the system is up to –0.0249 mm, which indicated that the influence of parts deformation on the mechanical system precision cannot be ignored.

This paper establishes a comprehensive 3D tolerance mathematical model, which comprehensively considers the effect of the dimensional tolerance, geometric tolerance and load deformation deviation. By this way, the assembly precision of mechanical system can be accurately predicted.

The purpose of this study is to establish a method for accurately extracting torch and seam features. This will improve the quality of narrow gap welding. An adaptive deflection correction system based on passive light vision sensors was designed using the Halcon software from MVtec Germany as a platform.

This paper proposes an adaptive correction system for welding guns and seams divided into image calibration and feature extraction. In the image calibration method, the field of view distortion because of the position of the camera is resolved using image calibration techniques. In the feature extraction method, clear features of the weld gun and weld seam are accurately extracted after processing using algorithms such as impact filtering, subpixel (XLD), Gaussian Laplacian and sense region for the weld gun and weld seam. The gun and weld seam centers are accurately fitted using least squares. After calculating the deviation values, the error values are monitored, and error correction is achieved by programmable logic controller (PLC) control. Finally, experimental verification and analysis of the tracking errors are carried out.

The results show that the system achieves great results in dealing with camera aberrations. Weld gun features can be effectively and accurately identified. The difference between a scratch and a weld is effectively distinguished. The system accurately detects the center features of the torch and weld and controls the correction error to within 0.3mm.

An adaptive correction system based on a passive light vision sensor is designed which corrects the field-of-view distortion caused by the camera’s position deviation. Differences in features between scratches and welds are distinguished, and image features are effectively extracted. The final system weld error is controlled to 0.3 mm.

This paper aims to propose a novel model predictive control (MPC) with time varying weights to develop a lateral control law in an automatic carrier landing system (ACLS), which minimizes landing risk and improves flight quality.

First, a nonlinear mathematic model of an F/A-18 aircraft during lateral landing is established. Then the landing model is linearized in the form of state deviations on the equilibrium points. Second, landing risk windows are proposed and a high-dimensional landing risk model is addressed through a back propagation (BP) neural network. The trained samples are acquired based on a pilot behavior model. Third, time varying weights created from the lateral landing risk are introduced into the performance function of MPC. Optimal solution is solved quicker and some state deviations are focused on and eliminated. Fourth, the algebraic inequalities are substituted by the linear matrix inequalities (LMIs), which are easily calculated by the computers.

On a semi-physical platform, the proposed method compares with a traditional MPC algorithm and a modified MPC with an additional term. The test results indicate that the proposed algorithm brings about an excellent landing performance as well as an ability of eliminating landing risk.

The landing phase of a carrier-based aircraft is one of the most dangerous and complicated stages, and the algorithm proposed by this paper plays a vital role in the lateral landing.

This paper establishes a lateral landing risk model, which considers not only the current landing state but also the future touchdown point. This lateral landing risk is integrated into the time varying weights of the MPC algorithm so that the state deviations and landing risk can be both reduced in the rolling optimization.

The purpose of this paper (the first of two) is to consider measures of risk commonly used in the analysis of both investment and insurance portfolios, and argue that there is a need for more appropriate measures to capture the uncertainty inherent in non‐normal (i.e. asymmetric and/or long tailed) probability distributions.

In Part 1, the risk measures used most frequently in finance and insurance – i.e. the standard deviation (variance), value at risk, tail value at risk, default value, etc. – are reviewed and then the paper explores whether such measures are sufficient for all contexts, including those in which the subject random variable is characterized by asymmetry and/or long tails. As an alternative to conventional measures, the paper assesses the potential of a general p‐norm‐based definition of “risk”.

Virtually, all commonly used risk measures, even those designed specifically to capture the behavior of asymmetric randomness, require that the underlying random variable possess a finite variance, or at least a finite mean. To overcome such difficulties, the paper considers a general definition of “risk” based upon a quantity closely related to the p‐norm – the p‐mean of absolute‐centered deviations (of which the standard deviation is a special case) – and show that this approach yields a single, but degenerate, result for all distributions.

The paper explores the use of p‐norm‐based measures in constructing a general definition of “risk” that is equally applicable to asymmetric and long‐tailed random variables as to normal random variables.

The purpose of this paper is to propose a new approach to talent management that consists of averaging performance appraisal and assessment center ratings for in-depth identification of lawyers’ talents.

The approach’s adjustment was examined using a 61 senior-lawyer sample from a Portuguese law firm. Comparisons between assessment center and performance appraisal ratings were analyzed using paired-sample t-tests and a kernel density function, and predictive validity was assessed with Pearson correlations. Evidence of both a general performance factor and two additional factors was verified using principal component analysis. Varimax rotation was used to verify three broad factors with job profile’s three broad areas.

Results suggest support for the assessment center’s predictive validity. Its lower and more variable ratings overcome performance appraisal rating bias. Adjustment of the new approach to lawyers’ overall talent identification (the general factor) and each lawyer’s relative talents (three broad factors) was observed.

This study contributes to the body of knowledge regarding the substantive existence of a general performance factor, and adds to empirical research concerning talent management, which is lacking. However, generalizability requires broader samples and replication.

The approach is a methodology that informs career management, high-flyers’ identification, talent mapping, development, succession planning, team composition, and diversity analysis. For lawyers, objective feedback allows benchmarking talent and managing one’s career.

This study pioneers empirical research that develops methods for identifying talent in law firms, vital for firm sustainability.