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.

A rapid, sensitive and without extraction spectrophotometric method for determination of clonazepam (CLO) in pure and pharmaceutical dosage forms has been described. The proposed method was simply depended on charge transfer reaction between reduced CLO (n-donor) and metol (N-methyl-p-aminophenol sulfate) as a chromogenic reagent (π- acceptor). The reduced drug, with zinc and concentrated hydrochloric acid, produced a purple colored soluble charge-transfer complex with metol in the presence of sodium metaperiodate in neutral medium, which has been measured at λmax 532 nm. All the variables which affected the developed and the stability of the colored product such as concentration of reagent and oxidant, temperature and time of rea

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

This approach was developed to achieve an accurate, fast, economic and sensitivity to estimation of diphenhydramine Hydrochloride. The dye that produced via reaction between diphenhydramine HCl with thymol blue in acidic medium pH ≈ 4.0. The ion pair method include an optimization study to formed yellowcolored that extraction by liquid – liquid method. The product separated of complexes by using by chloroform solution measured spectrophotometry at 400 nm. The analysis data at optimum conditions showed that linearity concentration in a range of calibration curve 1.0 – 50 μg /mL, limit of detectionand limit of quantification 0.0786 and 0.2358 μg/mL respectively. The molar absorptivity and Sandell’s sensitivity were 1.8 × 10 -4 L/mo

The research involves preparing gold nanoparticles (AuNPs) and studying the factors that influence the shape, sizes and distribution ratio of the prepared particles according to Turkevich method. These factors include (reaction temperature, initial heating, concentration of gold ions, concentration and quantity of added citrate, reaction time and order of reactant addition). Gold nanoparticles prepared were characterized by the following measurements: UV-Visible spectroscopy, X-ray diffraction and scanning electron microscopy. The average size of gold nanoparticles was formed in the range (20 -35) nm. The amount of added citrate was changed and studied. In addition, the concentration of added gold ions was changed and the calibration cur

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

The synthesis of gold nanoparticles AuNPs was achievedby the reduction of sodium tetrachloroaurate (III) (NaAuCl4) with ceftriaxone sodium (CR) in aqueous solutionswithout the use of other reducing agent. The effect of reactants concentration, temperature and pH on the sizes and morphology of AuNPs were also studied. The synthesized AuNPs were characterized by UV- visible spectroscopy, X-ray diffraction (XRD), scanning electron microscope (SEM), and atomic force microscope (AFM) analysis. Conjugation of antibiotic with the nanoparticles was characterized by FTIR spectrophotometry.

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv