Provably Secure Data Sharing Approach for Personal Health Records in Cloud Storage Using Session Password, Data Access Key, and Circular Interpolation

Personal health record (PHR) system has become the most important platform to exchange health information, in which the patients can share and manage personal health information more effectively in cloud storage. However, the cloud server is unreliable, and the secure data of users may be disclosed. Therefore, a secure data sharing mechanism is developed in this research using the proposed session password, data access key, and circular interpolation (SKC)-based data-sharing approach for the secure sharing of PHR in the cloud. The proposed SKC-based data sharing approach provides high efficiency and high-security guarantee. It effectively satisfies various security properties, such as tamper resistance, openness, and decentralization. The proposed SKC-based data sharing approach is the reliable mechanism created for the doctors to share the PHR and to access the patient historical data while meeting the privacy preservation.

A tolerance constrained robot path circular interpolation method for industrial SCARA robots

The linear robot path is tangential and curvature discontinuity, which will lead to vibration and unnecessary hesitation during execution. Local corner transition method and local spline interpolation method are used in state-of-art industrial robot controller to reduce vibration, while local corner transition method cannot interpolate target points and local spline interpolation method cannot constrain chord errors. This research proposes a robot path local interpolation method that eliminates deficiencies of each method. The smoothing method satisfies all of the following requirements: G1 continuity, target point interpolation and chord tolerance confined, shape-preserving (free of self-intersection), and unified parameterization. The generated smooth path consists of linear path and circular arc path with G1 continuity. A geometric iterative method cooperating with local corner transition method is used to generate local interpolation path. Simulations and actual experiments verify the generated smooth path is G1 continuous, tolerance constrained, shape-preserving, and have high computational efficiency.

The Geometric Error Measurement and Compensation for a Five-Axis Machining Center’s Tilting Rotary Table

The geometric error measurement and compensation for a five-axis machining center’s tilting rotary table is a difficult problem in the machine tool industry. Aiming at this problem, and based on a thorough study of the geometric error of a vertical five-axis machining center’s tilting rotary table, a method has been suggested in this paper to measure the geometric error of the tilting rotary table using the ball bar performing a three-axis circular interpolation. Eight center bias values in the X and Y directions were obtained by the use of four specific three-axis circular interpolation tests. According to the geometric relations of these four specific forms of circular tests, a geometric error separation model of the tilting rotary table was established. The process of circle test of A-axis and C-axis for vertical five-axis machining center is given in detail. The contrast tests, before and after compensation, were carried out in a vertical five-axis machining center. The experimental results showed that the positional errors and angular errors after compensation were much smaller than those before compensation. The positional error decreased from the maximum value of - 0.089 mm before compensation to the maximum value of - 0.004 mm, and the angle error decreased from the maximum value of - 0.012° before compensation to the maximum value of 0.002°. This method has provided an important reference for the geometric error measurement and compensation for a vertical five-axis machining center’s tilting rotary table.