IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING

This research presents the development of a parallel robot designed for the rehabilitation of upper and lower limbs following medical conditions such as strokes, spinal cord injuries, or heart attacks. The robot’s manufacturing process included constructing a frame with varying numbers of links and joints, accompanied by a control system comprising DC motors, motor drivers, and sensors, including the MPU6050 accelerometer and gyroscope. Experimental results demonstrated the robot’s capability to perform precise and repeatable rehabilitation exercises, with consistent alignment between programmed trajectories and physical implementation. The system’s design and functionality offer a cost-effective and scalable solution for enhancing patient recovery outcomes.

Power management aims to maximize energy use while saving building expenses and raising their efficiency. Minimizing energy consumption and supporting environmental preservation by automation depends on intelligent power management systems in buildings. This paper presents a performance evaluation to assess the deep learning approach using an intelligent model that preserves power consumption in smart buildings. A deep Neural Network (DNN) model is presented to manage building power usage by utilizing three classes named “modes”. Full mode is where the power is in full usage, Select mode presents power in selective consumption, and Shutdown mode is when there is no power consumption. Moreover, Boruta and Principal Component Analysis (PCA) feature reduction techniques were employed to minimize the complexity of the approach. The suggested model is trained and tested using a measured dataset taken from a university building over one year. The DNN paired with the Boruta feature reduction approach grabs greater consideration for classification accuracy of 99.8% and a classification duration of 1.19 seconds according to the results of the suggested model. The high accuracy results for DNN-Bourta prove that this model is an ideal approach to be implemented in real-time intelligent power management systems.

COMSOL software is used to build and quantify optical logic circuits using plasmonic square ring resonators. An operation utilizing constructive and destructive control along with input port interferences as inputs results in the proposed gates. At 1010 nm resonance wavelength, the transmission threshold is 30% at a single interface, the ratio of input power to output optical power. All plasmonic gates are executed within a singular structure measuring 150 nm by 150 nm. The OR gate and the AND gate exhibit transmission rates exceeding 100%, with both reporting a rate of 221%. The OR and AND gates exhibit modulation depth (MD) values of 96.38 percent, whereas the NOR gate demonstrates a value of 99.8 percent, these optical gates are used in transceivers for communication systems