Describing a Set of Points with Elliptical Areas: Mathematical Description and Verification on Operational Tests of Technical Devices

The purpose of this article was to present an algorithm for creating an ellipse for any data set represented on a two-dimensional reference frame. The study objective was to verify the developed method on real results of experimental tests with different subject matter. This article contains a mathematical algorithm to describe a set of points with elliptical areas. In addition, four results of tests with different subject matter are cited, based on which the developed method was verified. The verification of the method included checking the deviation of the geometric dimensions of the ellipse, the number of points contained within the ellipse, and the area of the ellipse. The implemented research methodology allowed to demonstrate the possibility of using the method of describing a set of points with elliptical areas, in order to determine quantitative parameters evaluating the results of the test. The presented results show the method’s applicability for the results obtained in four different operational tests: measurement of the human body’s gravity center position for a person propelling a wheelchair, measurement of marker position using motion capture methods, measurement of particulate emissions when using equipment powered by an internal combustion engine, and measurement of the muscle activity of the upper limb when propelling a hybrid manual-electric wheelchair. The performed experiments demonstrated that the method allows to describe about 85% of all measurement points with an ellipse.

IMPROVED BIOLOGICAL IMAGE TRACKING ALGORITHM OF ATHLETE’S CERVICAL SPINE HEALTH

ABSTRACT Introduction This paper research an improved biological image tracking algorithm of athlete’s cervical spine health under color feedback. Objective A new algorithm is proposed to improve the accuracy of detection and tracking. Methods In this study, the first thing is to apply the color feedback algorithm to improve and optimize the Improved Camshift algorithm. The optimized algorithm was used to track the center of the image, and the video was processed frame by frame. The center position of the tracking frame was obtained. Results The average number of head twists per person is 39 times. Among the three groups, children twisted the least, and older adults twisted the most. Conclusion The algorithm proposed in this study has certain effectiveness and superiority and can be well applied to detecting the number of head twists during exercise. Level of evidence II; Therapeutic studies - investigation of treatment results.

Effects of Microstructure on the Low-Temperature Toughness of an X80 × D1422 mm Heavy-Wall Heat-Induced Seamless Bend

The relationship between the microstructure and the low-temperature toughness of an X80 × D1422 mm heavy-wall heat-induced seamless bend was investigated, including the influence of microstructure on crack initiation and crack propagation. Using optical microscopy, scanning electron microscopy, transmission electron microscopy, and electron backscattered diffraction, the microstructure and crystallographic orientation characteristics were studied. An instrumented impact tester was used to investigate the impact toughness. The results showed that during the hot bending process, there was a difference in the induction heating temperature and the cooling rate results in the uneven microstructure of the inner surface, center position, and outer surface of the bend. The center position was mainly composed of granular bainite and exhibited the best combination of strength and toughness. The ductile–brittle transition temperatures of the inner surface, center position, and outer surface were −88, −85, and −60 °C, respectively. In the process of impact deformation, the non-uniformly distributed strain concentration regions are likely to cause uneven distribution of plastic deformation and the nucleation of microcracks. The high ratio of high-angle grain boundaries and the smaller effective grain size of the inner surface and center position lead to higher crack growth absorption energy. The low crack propagation energy of the outer surface is attributed to the fact that the high-angle grain boundary does not effectively deviate or arrest the crack propagation, and multiple microcracks are connected to one another and cause fracture failure.

A New Method for Detecting Compensation Hole Parameters of Automobile Brake Master Cylinder Based on Machine Vision

The machining accuracy of the compensation hole of the automobile brake master cylinder directly determines the safety of the automobile and the reliability of parking. How to detect the parameters of the compensation hole with high precision becomes a crucial issue. In this paper, by analyzing the principle of Hough transform detection technology and several optimization algorithms, a new method combining Zernike moment and improved gradient Hough transform is proposed to detect the circular hole parameters. The simulation experiment shows that the proposed algorithm satisfies 0.1 pixels in the coordinate detection of the center position, and the radius detection accuracy is 0.05 pixels, with fast detection speed and good robustness. Compared with the random Hough transform algorithm and the gradient Hough transform algorithm, the algorithm proposed in this paper has higher detection accuracy, faster detection speed, and better robustness, which meets the online detection accuracy requirements of the brake master cylinder compensation hole.

BP neural Network-Kalman filter fusion method for unmanned aerial vehicle target tracking

The poor real-time performance and target occlusion occurred easily when the UAV was tracking the target. In this paper, a target tracking method based on the Back Propagation neural network fusion Kalman filter algorithm was developed to solve the position prediction problem of the UAV target tracking in real time. Firstly, the target tracking algorithm was used to acquire the center position coordinates of the target on the onboard computer, and then the coordinate difference matrix was constructed to train the BP neural network in real time. Secondly, when the target was occluded by the obstacles judged by the Bhattacharyya coefficient, the BP neural network fusion Kalman filter algorithm was used to accurately predict the center position coordinates of the occluded target. Then the flight speed of UAV was calculated by the deviation between the coordinates of the target and the image center. Finally, the velocity command was sent to the UAV by the onboard computer. The experimental results shown that the target position predicted by BP neural network fusion Kalman filter algorithm was more accurate and robust in predicting the center position coordinates of the target, and the UAV can track the moving target on the ground stably.

Lysosome function in glomerular health and disease

The lysosome represents an important regulatory platform within numerous vesicle trafficking pathways including the endocytic, phagocytic, and autophagic pathways. Its ability to fuse with endosomes, phagosomes, and autophagosomes enables the lysosome to break down a wide range of both endogenous and exogenous cargo, including macromolecules, certain pathogens, and old or damaged organelles. Due to its center position in an intricate network of trafficking events, the lysosome has emerged as a central signaling node for sensing and orchestrating the cells metabolism and immune response, for inter-organelle and inter-cellular signaling and in membrane repair. This review highlights the current knowledge of general lysosome function and discusses these findings in their implication for renal glomerular cell types in health and disease including the involvement of glomerular cells in lysosomal storage diseases and the role of lysosomes in nongenetic glomerular injuries.