Mohamed Khalaf, Ahmed Fawzi, Ahmed Yahya,
Volume 20, Issue 1 (March 2024)
Abstract
Cognitive radio (CR) is an effective technique for dealing with scarcity in spectrum resources and enhancing overall spectrum utilization. CR attempts to enhance spectrum sensing by detecting the primary user (PU) and allowing the secondary user (SU) to utilize the spectrum holes. The rapid growth of CR technology increases the required standards for Spectrum Sensing (SS) performance, especially in regions with low Signal-to-Noise Ratios (SNRs). In Cognitive Radio Networks (CRN), SS is an essential process for detecting the available spectrum. SS is divided into sensing time and transmission time; the more the sensing time, the higher the detection probability) and the lower the probability of a false alarm). So, this paper proposes a novel two-stage SS optimization model for CR systems. The proposed model consists of two techniques: Interval Dependent De-noising (IDD) and Energy Detection (ED), which achieve optimum sensing time, maximum throughput, lower and higher. The Simulation results demonstrated that the proposed model decreases the, achieves a higher especially at low SNRs ranging, and obtains the optimum sensing time, achieving maximum throughput at different numbers of sensing samples (N) and different SNRs from -10 to -20 dB in the case of N = 1000 to 10000 samples. The proposed model achieves a throughput of 5.418 and 1.98 Bits/Sec/HZ at an optimum sensing time of 0.5ms and 1.5ms respectively, when N increases from 10000 to 100000 samples. The proposed model yields an achievable throughput of 5.37 and 4.58 Bits/Sec/HZ at an optimum sensing time of 1.66ms and 13ms respectively. So, it enhances the SS process than previous related techniques.
Yanawati Yahya, Nor Shafiqin Shariffuddin, Muhammad Khairul Hisyam Jarail, Dina Maizana, Phd Ibrahim Alhamrouni, Mohd Khairil Rahmat,
Volume 21, Issue 2 (Special Issue on the 1st International Conference on ELECRiS 2024 Malaysia - June 2025)
Abstract
Induction motors are highly favored in industrial applications for their ease of operation, compactness, lightweight, efficiency, low maintenance, and cost-effectiveness. They are widely used in conveyors, compressors, crushers, drills, fans, escalators, refrigerators, and electric vehicles. In Malaysia, industrial motors account for about 48% of energy consumption. This research introduces an improved rotor design with optimized rotor bars. Using MotorSolve (IM) software and theoretical calculations, the study found that the new design boosts energy efficiency. The new rotor bar design achieved an energy efficiency of 76.92%, compared to 74% for the current design. In terms of energy efficiency, this research found that adopting high-efficiency motors in industrial applications can save a significant amount of energy. These motors can also be used in a variety of horsepower ranges. The research suggests a maintenance plan for malfunctioning motors that attempts to reduce energy consumption, motor losses, and CO2 emissions in any apparatus. These results offer valuable insights for policymakers to refine energy policies for induction motors. In the future, real-time estimation of the motor's actual operating loss will be required to properly predict the trend in motor efficiency loss under various failure scenarios, which is consistent with the research goal of reducing energy losses in induction motors.
