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
... Show MoreThe demand for single photon sources in quantum key distribution (QKD) systems has necessitated the use of weak coherent pulses (WCPs) characterized by a Poissonian distribution. Ensuring security against eavesdropping attacks requires keeping the mean photon number (µ) small and known to legitimate partners. However, accurately determining µ poses challenges due to discrepancies between theoretical calculations and practical implementation. This paper introduces two experiments. The first experiment involves theoretical calculations of µ using several filters to generate the WCPs. The second experiment utilizes a variable attenuator to generate the WCPs, and the value of µ was estimated from the photons detected by the BB
... Show MoreSilybum marianum, from which silymarin (SM) is extracted, is a medicinal herb. In the Biopharmaceutics Classification System, it is of the class II type, meaning it is almost completely insoluble in water. It has a number of therapeutic properties, including anti-inflammatory as well as properties that promote wound healing.
This research target is to promote the dissolution and solubility of SM by employing a technique called solid dispersion and then incorporating the formula of solid dispersion into a topical gel that can be used for wound healing.
Solid dispersion is a technique used to enhance solubility and dissolve pharmaceuticals that are not water-soluble. This method is widely used because of its low cos
... Show MoreThis study describes the preparation of a new bidentate Schiff base derived from the condensation of Isatin-3-hydrazone with 2-acetylthiophene and the preparation of new series of complexes with a good yield. The prepared ligand was characterized by IR, UV-Vis, C.H.N.S elemental analysis, 1H and 13C NMR, LC-Mass spectroscopy, and physical measurements. Its complexes were analyzed by C.H.N.S elemental analyses, UV-Vis., FTIR, NMR, LC-Mass Spectra, atomic absorption spectroscopy, magnetic susceptibility, and conductivity measurements The results from spectroscopy and measurement studies showed that the ligand coordinated to the metal ion as a bidentate ligand via oxygen and nitrogen, forming an octahedral geometry around it. In vitro antimicr
... Show MoreIn this study azo dye was prepared by the reaction of m-phenylendidiazonium chloride with methyl salicylate, the resultant compound was used as a ligand for complex formation with Fe+2, Cu+2, Zn+2, Ni+2 and Co+2 ions. The prepared ligand was characterized by H1NMR, UV-Vis., And FTIR spectroscopy, CHN analysis, in addition the complexes were characterized by TGA, UV-Vis., FTIR and conductivity methods. The results indicate that the ligand chelated through phenoxy and carboxyl groups as a O4 quadra dentate ligand, the Co complex complet its hexagon coordination by bonding with chlorine and the complex wouid be electrolytic in opposite with rest complexes.
Metaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and without memory (memory-less). The absence of memory in some metaheuristics will lead to the loss of the information gained in previous iterations. The metaheuristics tend to divert from promising areas of solutions search spaces which will lead to non-optimal solutions. This paper aims to review memory usage and its effect on the performance of the main SI-based metaheuristics. Investigation has been performed on SI metaheuristics, memory usage and memory-less metaheuristics, memory char
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