Fingerprint recognition is one among oldest procedures of identification. An important step in automatic fingerprint matching is to mechanically and dependably extract features. The quality of the input fingerprint image has a major impact on the performance of a feature extraction algorithm. The target of this paper is to present a fingerprint recognition technique that utilizes local features for fingerprint representation and matching. The adopted local features have determined: (i) the energy of Haar wavelet subbands, (ii) the normalized of Haar wavelet subbands. Experiments have been made on three completely different sets of features which are used when partitioning the fingerprint into overlapped blocks. Experiments are conducted on

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

In this study, four different spectrophotometric methods were applied for determination of cimetidine and erythromycin ethylsuccinate drugs in pure form and in their pharmaceutical preparations. The suggested methods are simple, sensitive, accurate, not time consuming and inexpensive. The results showed the following: The first method: Based on the formation of ion pair complex of each drug with bromothymol blue (BTB) as a chromogenic reagent. The formed complexes were extracted with chloroform and their absorbance values were measured at 427.5 nm for cimetidine and 416.5nm for erythromycin ethylsuccinate; against their reagents blanks. Two different methods, univariate method and multivariate method, were used to obtain the optimum condit

The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone with a slun

Nanostructured photodetectors have garnered great attention due to their enriched electronic and optical properties. In this work, we aim to fabricate a high-performance CeO2/Si photodetector by growing a CeO2 nanostructure film on a silicon substrate using the pulsed laser deposition (PLD) technique at different laser energy densities. The impact of laser energy density and the number of pulses on the morphological, optical, and electrical properties was studied. Field emission scanning electron microscopy (FESEM) results show that the CeO2 film has a spherical grain morphology with an average grain size ranging from 33 to 54 nm, depending on the laser energy density. The film deposited at various numbers of laser pulses also has spherical