Novel azo ligand based on tryptamine, and its metal complexes with antioxidant properties were synthesized through chemical methods and characterized through various techniques, including IR, Mass, UV-Vis spectroscopy, elemental analysis, conductivity, magnetic sensitivity, and thermogravimetric analysis. According to the IR spectra of the complexes, the azo-ligand, [5-(2-(3H- 1-indol-3-yl) ethyl) diazenyl) quinolin-8-ol] coordinates with metal ions through the nitrogen atom in the quinoline ring and the oxygen atom of the hydroxyl group. Thermal analysis techniques were employed to investigate the thermal behavior of the compounds. The results revealed that the metal complexes possess higher thermal stability compared to the free ligand. T

Proxy-based sliding mode control PSMC is an improved version of PID control that combines the features of PID and sliding mode control SMC with continuously dynamic behaviour. However, the stability of the control architecture maybe not well addressed. Consequently, this work is focused on modification of the original version of the proxy-based sliding mode control PSMC by adding an adaptive approximation compensator AAC term for vibration control of an Euler-Bernoulli beam. The role of the AAC term is to compensate for unmodelled dynamics and make the stability proof more easily. The stability of the proposed control algorithm is systematically proved using Lyapunov theory. Multi-modal equation of motion is derived using the Galerkin metho

In this work, wide band range photo detector operating in UV, Visible and IR was fabricated using carbon nanotubes (MWCNTs, SWCNTs) decorated with silver nanoparticles (Ag NPs). Silicon was used as a substrate to deposited CNTs/Ag NPs by the drop casting technique. Polyamide nylon polymer was used to coat CNTs/Ag NPs to enhance the photo-response of the detector. The electro-exploding wire technology was used to synthesize Ag NPs. Good dispersion of silver NPs achieved by a simple chemistry process on the surface of CNTs. The optical, structure and electrical characteristic of CNTs decorated with Ag NPs were characterized by X-Ray diffraction and Field Emission Scanning Electron Microscopy.  X-ray diffra

     A geographic information system (GIS) is a very effective management and analysis tool. Geographic locations rely on data. The use of artificial neural networks (ANNs) for the interpretation of natural resource data has been shown to be beneficial. Back-propagation neural networks are one of the most widespread and prevalent designs. The combination of geographic information systems with artificial neural networks provides a method for decreasing the cost of landscape change studies by shortening the time required to evaluate data. Numerous designs and kinds of ANNs have been created; the majority of them are PC-based service domains. Using the ArcGIS Network Analyst add-on, you can locate service regions around any network

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce