Abstract-Servo motors are important parts of industry automation due to their several advantages such as cost and energy efficiency, simple design, and flexibility. However, the position control of the servo motor is a difficult task because of different factors of external disturbances, nonlinearities, and uncertainties. To tackle these challenges, an adaptive integral sliding mode control (AISMC) is proposed, in which a novel bidirectional adaptive law is constructed to reduce the control chattering. The proposed control has three steps to be designed. Firstly, a full-order integral sliding manifold is designed to improve the servo motor position tracking performance, in which the reaching phase is eliminated to achieve the invariance of

Objective: The objective of this study was to prepare nanosuspension of a practical water insoluble antiulcer drug which is lafutidine to enhance the solubility, dissolution rate with studying the effect of different formulation variables to obtain the best formula with appropriate physical properties and higher dissolution rate.Methods: Nanosuspension of lafutidine was prepared using solvent anti-solvent precipitation method using Polyvinylpyrrolidone K-90(PVP K-90) as the stabilizer. Ten formulations were prepared to show the effect of different variables in which two formulations showed the effect of stabilizer type, three formulations showed the effect of stabilizer concentration, two formulations showed the effect of combinatio

Biodiesel as an attractive energy source; a low-cost and green synthesis technique was utilized for biodiesel preparation via waste cooking oil methanolysis using waste snail shell derived catalyst. The present work aimed to investigate the production of biodiesel fuel from waste materials. The catalyst was greenly synthesized from waste snail shells throughout a calcination process at different calcination time of 2–4 h and temperature of 750–950 ◦C. The catalyst samples were characterized using X-Ray Diffraction (XRD), Brunauer-Emmett-Teller (BET), Energy Dispersive X-ray (EDX), and Fourier Transform Infrared (FT-IR). The reaction variables varying in the range of 10:1–30:1 M ratio of MeOH: oil, 3–11 wt% catalyst loading, 50–

The present study addresses the behavior of gases in cultivation media as an essential factor to develop the relationship between the microorganisms that are present in the same environment. This relationship was explained via mass transfer of those gases to be a reasonable driving force in changing biological trends. Stripping and dissolution of oxygen and carbon dioxide in water and dairy wastewater were investigated in this study. Bubble column bioreactor under thermal control system was constructed and used for these processes. The experimental results showed that the removal of gases from the culture media requires more time than the dissolution. For example, the volumetric mass transfer coefficient for the removal

For a given loading, the stiffness of a plate or shell structure can be increased significantly by the addition of ribs or stiffeners. Hitherto, the optimization techniques are mainly on the sizing of the ribs. The more important issue of identifying the optimum location of the ribs has received little attention. In this investigation, finite element analysis has been achieved for the determination of the optimum locations of the ribs for a given set of design constraints. In the conclusion, the author underlines the optimum positions of the ribs or stiffeners which give the best results. 

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

The electrocoagulation process became one of the most important technologies used for water treatment processes in the last few years. It’s the preferred method to remove suspended solids and heavy metals from water for treating drinking water and wastewater from textile, diary, and electroplating factories. This research aims to study the effect of using the electrocoagulation process with aluminum electrodes on the removal efficiency of suspended solids and turbidity presented in raw water and optimizing by the response surface methodology (RSM). The most important variables studied in this research included electrode spacing, the applied voltage, and the operating time of the electrocoagulation process. The samples

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s