It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in

Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

The content of fatty acid methyl esters (FAME) is a crucial property of biodiesel and serves as an indicator of the transesterification reaction that converts vegetable oil into biodiesel. To facilitate the rapid estimation of FAME quickly in the biodiesel industries, simple methods such as measuring refractive index, density, and dynamic viscosity measurements were employed to monitor the progress of transesterification of castor oil to biodiesel. Blends of castor oil and biodiesel were mixed at different weights to find correlations between FAME content and refractive index, density, and dynamic viscosity measurements. The transesterification of castor oil with methanol was carried out to examine how the refractive index, density,

The goals of endodontic preparation were to shape and clean the space of the root canal and remove microorganisms, affected dentin and pulp, the apical foramen and the canal curve should be protected from being transported during endodontic canal preparation. The aim of this study was to evaluate the curve straightening of curved root canals and apical transportation after preparation with four rotary systems. Forty mesial roots of the lower 1st molars teeth only the mesiobuccal canals were used, these roots were immersed into cold clear acrylic , the teeth roots divided into four groups according to rotary system used for preparation of the canals (ten roots for each group):. group I: ProTaper Next rotary system, group II: IRaCe Plus rotar

An experimental study on a KIA pride (SAIPA 131) car model with scale of 1:14 in the wind tunnel was made beside the real car tests. Some of the modifications to passive flow control which are (vortex generator, spoiler and slice diffuser) were added to the car to reduce the drag force which its undesirable characteristic that increase fuel consumption and exhaust toxic gases. Two types of calculations were used to determine the drag force acting on the car body. Firstly, is by the integrating the values of pressure recorded along the pressure taps (for the wind tunnel and the real car testing), secondly, is by using one component balance device (wind tunnel testing) to measure the force. The results show that, the avera

In this paper, 3D simulation of the global coronal magnetic field, which use observed line of sight component of the photosphere magnetic field from (MDI/SOHO) was carried out using potential field model. The obtained results, improved the theoretical models of the coronal magnetic field, which represent a suitable lower boundary conditions (Bx, By, Bz) at the base of the linear force-free and nonlinear force free models, provides a less computationally expensive method than other models. Generally, very high speed computer and special configuration is needed to solve such problem as well as the problem of viewing the streamline of the magnetic field. For high accuracy special mathematical treatment was adopted to solve the computation comp

Abstract:

      In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach

An experimental study on a KIA pride (SAIPA 131) car model with scale of 1:14 in the wind tunnel was made beside the real car tests. Some of the modifications to passive flow control which are (vortex generator, spoiler and slice diffuser) were added to the car to reduce the drag force which its undesirable characteristic that increase fuel consumption and exhaust toxic gases. Two types of calculations were used to determine the drag force acting on the car body. Firstly, is by the integrating the values of pressure recorded along the pressure taps (for the wind tunnel and the real car testing), secondly, is by using one component balance device (wind tunnel testing) to measure the force. The results show that, the average drag estimated on

In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.