In this paper, a novel flow control strategy which is the inlet throttled pump was used to design an angular velocity control system for rotary actuator. Inlet throttled systems have good performance in addition to their high efficiency compared to traditional valve controlled systems. The flow in the proposed system is adjusted by a valve that is positioned at the pump inlet with the purpose of reducing the energy loses across the valve. This regulated flow is used then to control the actuator angular velocity. The system was modeled and the open loop stability and performance were studied. In order to improve the system performance, Robust-Proportional-Integral-Derivative (RPID) and structured singular value (M@#@) controllers have been d

PID (proportional-integral-derivative) and Mu controllers are widely used in electro-hydraulic servo systems due to their effectiveness and ease of implementation. This paper explores using particle swarm optimization (PSO) for tuning traditional and robust PID controllers, along with D-K iteration for Mu controller tuning. Three controller types: conventional PID (CPID), robust PID (RPID), and structured singular value controllers are developed, while analyzing multiplicative uncertainty with six uncertain coefficients. Their findings indicated that both PID (CPID and RPID) and Mu controllers maintained system stability. Notably, the Mu controller can handle coefficient uncertainty without a pure integral term, while the RPID controller de

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.

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

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

Automatic license plate recognition (ALPR) used for many applications especially in security applications, including border control. However, more accurate and language-independent techniques are still needed. This work provides a new approach to identifying Arabic license plates in different formats, colors, and even including English characters. Numbers, characters, and layouts with either 1-line or 2-line layouts are presented. For the test, we intend to use Iraqi license plates as there is a wide range of license plate styles written in Arabic, Kurdish, and English/Arabic languages, each different in style and color. This variety makes it difficult for recent traditional license plate recognition systems and algorithms to recogn

The software-defined network (SDN) is a new technology that separates the control plane from data ‎plane for the network devices. One of the most significant issues in the video ‎surveillance system is the link failure. When the path failure occurs, the monitoring center cannot receive the ‎video from the cameras. In this paper, two methods are proposed to solve this problem.  The first ‎method uses the Dijkstra algorithm to re-find the path at the source node switch. The second method ‎uses the Dijkstra algorithm to re-find the path at the ingress node switch (or failed link).

This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH₂) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue