This study synthesized polyacetal from the reaction of polyvinyl alcohol with para-nitrobenzaldehyde. Polyacetal/polyvinylpyrrolidone polymer blends were prepared using solution casting. Gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were biosynthesized using onion peel extract as the reducing agent. Nanocomposites were fabricated by blending polyacetal/PVP with AuNPs and AgNPs at different ratios. XRD and FESEM characterized the AuNPs and AgNPs. FTIR, FESEM, TGA, and DSC characterized the polyacetal, polymer blends, and nanocomposites. DSC and TGA confirmed the improved thermal stability of the polymer blends and nanocomposites. Nanocomposites demonstrated higher efficacy in inhibiting lung cancer cell lines compared t

This new azo dye 3-((2-(1H-indol-3-yl) ethyl) diazenyl) quinoline-2-ol was subsequently used to prepare a series of complexes with the metal ions of Cr+3, Cu+2, VO+2, Mn+2and Mo+6. The compounds identified by 1H and 13C-NMR, FT-IR, UV-Vis, mass spectroscopy, as well as TGA, DSC, and C.H.N., conductivity, magnetic susceptibility, metal and chlorine content. The results showed that the ligand behaves in a bidantate, and that the complexes gave octahedral, excepting for VO+2 square pyramid was given, that all complexes are non-electrolytes. The effectiveness of mention the compounds in inhibiting free radicals was evaluated by the ability to act as an antioxidant was measured using DPPH as a free radical and gallic acid as a standard s

This study aims to enhance the RC5 algorithm to improve encryption and decryption speeds in devices with limited power and memory resources. These resource-constrained applications, which range in size from wearables and smart cards to microscopic sensors, frequently function in settings where traditional cryptographic techniques because of their high computational overhead and memory requirements are impracticable. The Enhanced RC5 (ERC5) algorithm integrates the PKCS#7 padding method to effectively adapt to various data sizes. Empirical investigation reveals significant improvements in encryption speed with ERC5, ranging from 50.90% to 64.18% for audio files and 46.97% to 56.84% for image files, depending on file size. A substanti

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system