The work involves synthesis of new Schiff bases ([V] a, b and [VI] a, b), pyrazoles [VII] a, b and pyrazolines [VIII] a, b derivatives containing isoxazoline unit starting with chalcones. 4-bromoacetophenone was reacted with 4-hydroxybenzaldehyde or 4-hydroxyacetophenone was reacted with 4-bromobenzaldehyde in basic medium to give chalcone by Claisen-Schemidt reaction. The chalcons [I] a, b was reacted with hydroxylamine hydrochloride to form isoxazolines [II] a, b. which were reacted with ethyl chloro acetate in basic medium to get ester compounds [III] a, b. The condensation new ester [III] a, b with hydrazine hydrate80% yieldedacid hydrazide [IV] a, b. The later compound refluxing with 4-substituted benzaldehyde in dry benzene to give Sc

A new series of schiff base and aminothiadiazole derivatives of N- substituted phthalimide (I-VI) were synthesized. In this work, the intermediate 4-(1,3-dioxoisoindolin-2-yl)benzaldehyde compound (I), was formed by reaction of 4-amino benzaldehyde with phthalic anhydride in glacial acetic acid(GAA). A series of Schiff bases (IV-VI) was prepared by the reaction of benzidine with compound (I) in ethanol and presence of GAA as a catalyst to form compound (IV) which react with compound (I) and p-nitro benzyldehyde to give compound (V) and (VI) respectively. A new phthalimide thiosemi-carbazone derivative (ll) was prepared by reaction of compound (l) with thiosemi-carbazide HCl in the presence of equimolar amount of sodium acetate. Fina

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat

This paper describes a practical study on the impact of learning's partners, Bluetooth Broadcasting system, interactive board, Real – time response system, notepad, free internet access, computer based examination, and interaction classroom, etc, had on undergraduate student performance, achievement and involving with lectures. The goal of this study is to test the hypothesis that the use of such learning techniques, tools, and strategies to improve student learning especially among the poorest performing students. Also, it gives some kind of practical comparison between the traditional way and interactive way of learning in terms of lectures time, number of tests, types of tests, student's scores, and student's involving with lectures

The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are