The increasing electrical power generation from renewable energy resources poses new challenges to the electrical grid. These challenges are mainly related to the inconsistent nature of renewable energies and the burden on transmission lines due to the increasing generated power. In this paper, the correlation between renewable energy generation and the transmission capability of electrical power lines is studied. In order to facilitate the accommodation of renewable energies the actual dynamic line rating (DLR) is estimated based on actual weather conditions. To achieve this purpose a new DLR estimation method using machine learning is presented. Line rating depends on various meteorological factors (wind speed, wind direction, ambient temperature, and solar radiation). A machine-learning model was trained using Random Forest (RF) regressor to estimate the rating of a transmission line 

This work introduces a new topology for designing low-phase noise (PN) dual-band voltage-controlled oscillator (VCO) by proposing orthogonally located inductors in 0.18-m CMOS. The inductors are implemented using five metal layers keeping the lowest layer empty to maximize the quality ( factor. The first inductor is two halves shunted octagonal loops using the top layer (M and utilized in cross-coupled VCO, while the second inductor is formed by four C-shaped shunted inductors using the lower four layers M and used in current-reuse (CR) VCO. The M inductor improves the -factor by more than 25%over one loop inductor in the frequency band of interest, while the M inductor uses four shunt layers to boost the -factor by 28% in -band compared to the single-layer inductor. The VCO oscillates from 22.36 to 23.4 GHz with PN of 112.4 dBc/Hz at 1 MHz and figure of merit (FoM) of 188.8 dBc/Hz

The fifth-generation (5G) wireless cellular networks aim to increase the users capacities and quality of experience as well as integrating different wireless bands and modes of access. The introduction of cognitive radio technology and heterogeneous networks (HetNets) as part of the architecture of the 5G aims to efficiently reuse the available spectrum. This paper presents a two-stage framework based on matching theory and auction games with the objective of efficiently admitting secondary users in the wireless scene. At the first stage, a fast convergence matching game for the users admission problem in 5G HetNets is considered, where secondary users are associated to appropriate secondary base stations. These base stations access the available primary spectrum on behalf of its associated users in the next stage, namely a repeated modified English auction

This work introduces a low phase-noise (PN) wideband voltage-controlled-oscillator (VCO) by proposing five ports transformer in 0.18-μm CMOS technology. The proposed VCO uses five ports transformer and operates in the low band when all the pMOS-nMOS cross-coupled VCO components are activated, whereas this VCO operates in the high band using only part of the transformer, and an nMOS cross-coupled core. The transformer is designed using the top metal layer (M6) and the first inductor is meander line U-shaped center tap inductor, while the second inductor consists of two shunted octagonal loops to increase the quality (Q-) factor compared with using a single-loop inductor. The wideband switched transformer VCO achieves a measured frequency tuning range (FTR) of 16.4-17.1 GHz with a PN of -113.3 dBc/Hz at 1-MHz offset, and from 17 to 17.9 GHz

Automatic detection and counting of vehicles in a video is a challenging task and has become a key application area of traffic monitoring and management. In this paper, an efficient real-time approach for the detection and counting of moving vehicles is presented based on YOLOv2 and features point motion analysis. The work is based on synchronous vehicle features detection and tracking to achieve accurate counting results. The proposed strategy works in two phases; the first one is vehicle detection and the second is the counting of moving vehicles. Different convolutional neural networks including pixel by pixel classification networks and regression networks are investigated to improve the detection and counting decisions. For initial object detection, we have utilized state-of-the-art faster deep learning object detection algorithm YOLOv2 before refining them using K-means clustering and KLT tracker. 

Voltage source multilevel inverters (MLI) is widely utilized in medium and high-power applications due to their advantages. Here, an 11-level, asymmetrical multilevel inverter topology is proposed. The topology utilizes four unidirectional switches, three bidirectional switches along with two dc sources. The proposed configuration of switches and the concept of the dc-link capacitor is utilized to generate eleven level output voltage. The reduced number of components such as power switches and DC sources, lower control complexity due to capacitors' self-balancing nature, and low total standing voltage (TSV) are the critical features of the proposed topology. Moreover, a reliability assessment of the topology shows that the topology has a high mean time to fault (MTTF), which makes it robust and reliable. Matlab/Simulink environment is used to develop a simulation model of the proposed topology, while PLECS is used for the thermal modelling and analysis of the converter. A prototype is developed and tested in the laboratory to validate the performance for different loading conditions. The proposed topology can be cascaded to produce the ‘n’ number of levels. The critical comparison of the proposed topology shows that the proposed circuit has advantages over other compared topologies.

This article presents the application of model predictive control (MPC) in high-performance drives. A wide variety of machines have been considered: Induction machines, synchronous machines, linear motors, switched reluctance motors, and multiphase machines. The control of these machines has been done by introducing minor and easy-to-understand modifications to the basic predictive control concept, showing the high flexibility and simplicity of the strategy. The second part of the article is dedicated to the performance comparison of MPC with classical control techniques such as field-oriented control and direct torque control. The comparison considers the dynamic behavior of the drive and steady-state performance metrics, such as inverter losses, current distortion in the motor, and acoustic noise. The main conclusion is that MPC is very competitive concerning classic control methods by reducing the inverter losses and the current distortion with comparable acoustic noise.

The application of model predictive control in electrical drives has been studied extensively in the past decade. This article presents what the authors consider the most relevant contributions published in the last years, mainly focusing on three relevant issues: weighting factor calculation when multiple objectives are utilized in the cost function, current/torque harmonic distortion optimization when the power converter switching frequency is reduced, and robustness improvement under parameters uncertainties. Therefore, this article aims to enable readers to have a more precise overview while facilitating their future research work in this exciting area.

This experimental study aims to explore the Lagrangian nature of fluid transport downstream of a bileaflet mechanical aortic valve under different malfunction scenarios that might be encountered clinically. Time-resolved planar particle image velocimetry measurements are performed to extract instantaneous velocity fields downstream of the bileaflet mechanical valve implanted in an elastic aortic model. The results show an increase in particle residence time with the severity of malfunction. This is attributed to the expansion of the recirculation regions downstream of the valve. The time-evolution of Lagrangian coherent structures over one cardiac cycle (using finite-time Lyapunov exponent fields) shows the effect of valve dysfunction on the material transport and its barriers inside the aorta. The unbalanced flow through the dysfunctional leaflets leads to a significant redistribution of the LCS, thus the fluid transport along the ascending aorta. Moreover, a new technique for the evaluation of the highest accumulated shear stresses is applied along the Lagrangian trajectory of particles being released from the extracted Lagrangian coherent structures where the highest stretching occurs. Finally, the induced non-laminar flow behavior by the valve dysfunction is analyzed using the time-frequency spectra of velocity signals at selected points in the ascending aorta.