Power switches require snubbing networks for driving single – phase industrial heaters. Designing these networks, for controlling the maximum allowable rate of rise of anode current (di/dt) and excessive anode – cathode voltage rise (dv/dt) of power switching devices as thyristors and Triacs, is usually achieved using conventional methods like Time Constant Method (TCM), resonance Method (RM), and Runge-Kutta Method (RKM). In this paper an alternative design methodology using Fuzzy Logic Method (FLM) is proposed for designing the snubber network to control the voltage and current changes. Results of FLM, with fewer rules requirements, show the close similarity with those of conventional design methods in such a network of a Triac driving 1.2 kW heater of an industrial plastic extruder machine. The similarity, between Fuzzy Logic results and conventional techniques results, is confirming the applicability of the fuzzy logic in designing these snubbing networks.
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The purpose of this study was to investigate the difference in mandibular trauma caused by two mechanisms for the delivery of missile injuries: firearms and improvised explosive devices (IEDs). The data investigated included sex, age, mechanism of injury, and other clinical and radiographic manifestations. Seventy consecutive patients, predominantly male, with a mean age of 28.6 ± 14 years (range 2–60 years) were enrolled: 38 patients (54.3%) sustained mandibular fractures caused by bullet injuries and 32 patients (45.7%) had mandibular fractures caused by IED explosion injuries. The study revealed that the differences in most of the investigated variables were not statistically significant; the only significant differences were the inci
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The present study was conducted to estimate the antimicrobial activity and the potential biological control of the killer toxin produced by
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Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
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Many faces are exposed to degradation, discoloration, changes in humidity. The primary objective has improved some properties of hybrid nanocomposites materials that used for restoring of the function maxillofacial prosthesis and improving the esthetic. In the present research different lengths chopped and continuous of ultrahigh molecular weight polyethylene (UHMWPE) fiber was added at selected percentage (0.0, 0.2% and 1%) to polymer blend composite (95%SR /5%PMMA: 0.2% Pomegranate Peels Powder (PPP)) for developing the properties of silicone rubber used for the maxillofacial prosthesis applications. Some mechanical and physical properties were done on the all prepared samples. The results showed that all properties have improved when add
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KE Sharquie, AA Noaimi, HA Al-Mudaris, Journal of Cosmetics, Dermatological Sciences and Applications, 2012 - Cited by 6