Baker's Yeast is an important additive among the substances, which improves bred quality, thus, a consideration has been made to study the conditions and parameters that affecting the production of the yeast in a batch fermenter experimentally and theoretically. Experimental runs were implemented in a 12-liter pilot-scale fermenter to predict the rate of growth and other parameters such as amount of additive consumed and the amount of heat generated. The process is modeled and performed using a computer programming prepped for this purpose, the model gave a good agreement comparing to the experimental work specially in the log phase.

Simple and sensitive spectrophotometric method is described based on the coupling reaction of tetracycline hydrochloride (TC. HCl) with diazotized 4-aminopyridine in bulk and pharmaceutical forms. Colored azo dye formed during this reaction is measured at 433 nm as a function of time. Factors affecting the reaction yield were studied and the conditions were optimized. The kinetic study involves initial rate and fixed time (10 minutes) procedures for constructing the calibration graphs to determine the concentration of (TC. HCl). The graphs were linear for both methods in concentration range of 10.0 to 100.0 μg.mL-1. The recommended procedure was applied successfully in the determination of (TC. HCl) in its commercial formulations.

Simple and sensitive spectrophotometric method is described based on the coupling reaction of tetracycline hydrochloride(TC. HCl) with diazotized 4-aminopyridine in bulk and pharmaceutical forms. Colored azo dye formed during this reaction is measured at 433 nm as a function of time. Factors affecting the reaction yield were studied and the conditions were optimized. The kinetic study involves initial rate and fixed time (10 minutes) procedures for constructing the calibration graphs to determine the concentration of (TC. HCl). The graphs were linear for both methods in concentration range of 10.0 to 100.0 µg.mL-1. The recommended procedure was applied successfully in the determination of (TC. HCl) in itscommercial formulations.

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

This paper presents L₁-adaptive controller for controlling uncertain parameters and time-varying unknown parameters to control the position of a DC servomotor. For the purpose of comparison, the effectiveness of L₁-adaptive controller for position control of studied servomotor has been examined and compared with another adaptive controller; Model Reference Adaptive Controller (MRAC). Robustness of both L₁-adaptive controller and model reference adaptive controller to different input reference signals and different structures of uncertainty were studied. Three different types of input signals are taken into account; ramp, step and sinusoidal. The L₁-adaptive controller ensured uniformly bounded