The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

Geographic Information Systems (GIS) are obtaining a significant role in handling strategic applications in which data are organized as records of multiple layers in a database. Furthermore, GIS provide multi-functions like data collection, analysis, and presentation. Geographic information systems have assured their competence in diverse fields of study via handling various problems for numerous applications. However, handling a large volume of data in the GIS remains an important issue. The biggest obstacle is designing a spatial decision-making framework focused on GIS that manages a broad range of specific data to achieve the right performance. It is very useful to support decision-makers by providing GIS-based decision support syste

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

Amorphization of drug has been considered as an attractive approach in improving drug solubility and bioavailability. Unlike their crystalline counterparts, amorphous materials lack the long-range order of molecular packing and present the highest energy state of a solid material. Co-amorphous systems (CAM) are an innovative formulation technique by where the amorphous drugs are stabilized via powerful intermolecular interactions by means of a low molecular co-former.

This review highlights the different approaches in the preparation of co-amorphous drug delivery system, the proper selection of the co-formers. In addition, the recent advances in characterization, Industrial scale and formulation will be discussed.

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Objective: The approximate life span of a silicone maxillofacial prosthesis is as short as1.5–2 years of clinical service, then a new prosthesis should be fabricated. The most common reasonfor re-making the prosthesis is silicone mechanical properties degradation. The aim of this studywas to assess some mechanical properties of VST-30 silicone for maxillofacial prostheses after addi-tion of intrinsic pigments.Methods: Two types of intrinsic pigments (rayon flocking and burnt sienna); each of them wasincorporated into silicone. One hundred and twenty samples were prepared and split into 4 groupsaccording to the conducted tests (tear strength, hardness, surface roughness, and tensile strengthand elongation percentage) with 30 samples for ea

4,4'-(pyridine-2,6-diylbis(1,3,4-oxadiazole-5,2-diyl))bisphenol monomer (3)was synthesized from cyclization of N'2,N'6-bis(4-hydroxybenzylidene)pyridine-2,6-dicarbohydrazide (2)in the presence of bromine in glacialacetic acid. Newly five polymers (P1-P5) were synthesized from reaction bis-1,3,4-oxadiazole bisphenolmonomer with five different di acid chloride. The antibacterial activity of the synthesized polymers was screened against gram positive and gram negative bacteria. Polymers P4 and P5 exhibited significant antibacterial against all microorganisms, as well these polymers showed highest antifungal activity.

This research includes the synthesis of some new different heterocyclic derivatives of 5-Bromoisatin. New sulfonylamide, diazine, oxazole, thiazole and 1,2,3-triazole derivatives of 5-Bromoisatin have been synthesized. The synthesis process started by the reaction of 5-Bromoisatin with different reagents to obtain schiff bases of 5-Bromoisatin intermediate compounds(1, 8, 19) by using glacial acetic acid as a catalyst in three routes. The first route, 5-Bromoisatin reacted with p-aminosulfonylchloride to product compound(1), then converted to sulfonyl amide derivatives(2-7) by the reaction of compound(1) with different substituted primary aromatic amine in absolute ethanol. The second route includes the reaction of 5-Bromoisatin rea