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Based on Lyapunov theory, this research demonstrates the stability of the sliding surface in the consensus problem of multi-agent systems. Each agent in this system is represented by the dynamically uncertain robot, unstructured disturbances, and nonlinear friction, especially when the dynamic function of agent is unknown. All system states use neural network online weight tuning algorithms to compensate for the disturbance and uncertainty. Each agent in the system has a different position, and their trajectory approach to the same target is from each distinct orientation.In this research, we analyze the design of the sliding surface for this model and demonstrate which type of sliding surface is the best for the consensus problem. Lastly, simulation results are presented to certify the correctness and the effectiveness of the proposed control method.

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It is very essential to form such high stregth and hard-to-cut materials by using modern machining methods. It is important to introduce the efforts on modification of the process for improving the machining quality. In the present investigation, an effort was made to analyze the effects of micro size aluminium particles mixed dielectric medium under different powder concentration on machining titanium alloy in electro erosion process. The response-surface-methodology(RSM) based algorithm was utilized to analyze the performance measures by considering machinning time with Cost of Goods Manufactured (COGM) method in PMEDM process. It was found that the micron size powders can significantly help to enhance the surface quality of the Ti-6Al-4V surface during machining in EDM process. The presence of carbon, oxygen elements and the formation of surface oxides and carbides has been found due to the decomposition of dielectric fluid in PMEDM process. The lower deep cavities and uniform machining surface have been produced with the aluminum oxide powder EDM process owing to lower surface cracks density, conductivity. To sum up, investigation and comparison of surface scanning showed that this setting has been implied could be considered by the industries needs more precision.

Objective: This retrospective study aimed to assess the risk factors associated with early implant failure using a multivariate logistic regressive model and generalized evaluating equations (GEE) analysis. A total of 892 patients who received 1931 dental implants within the period from 2015 to 2018 at Odonto-Maxillo-Facial Hospital, Ho Chi Minh City, Vietnam were included in this study. Several factors as age, gender, implant placement site, implant length and diameter, sinus lifting technique, the number of implants per patient, and implant brands were recorded. GEE analysis results showed that the implant-based failure rates were 6.1% after an observation period from 3 months to 3 years. Among 118 failed implants, 108 implants were lost before or at the abutment connection stage (91.5%). Male, maxilla implant placement and implant brands were identified as the risk factors for early implant loss. Implant brands which have significantly less early failure rates are Ritter, Nobel, MIS, Osstem, Neo.