حسن السيد عز الدين بحر العلوم العقد الاجتماعي والسلطة الشعبية عند الإمام علي (عليه السلام )

With the development of communication technologies, the use of wireless systems in biomedical implanted devices has become very useful. Bio-implantable devices are electronic devices which are used for treatment and monitoring brain implants, pacemakers, cochlear implants, retinal implants and so on. The inductive coupling link is used to transmit power and data between the primary and secondary sides of the biomedical implanted system, in which efficient power amplifier is very much needed to ensure the best data transmission rates and low power losses. However, the efficiency of the implanted devices depends on the circuit design, controller, load variation, changes of radio frequency coil’s mutual displacement and coupling coef

  In this paper, we investigate the connection between the hierarchical models and the power prior distribution in quantile regression (QReg). Under specific quantile, we develop an expression for the power parameter ( ) to calibrate the power prior distribution for quantile regression to a corresponding hierarchical model. In addition, we estimate the relation between the  and the quantile level via hierarchical model. Our proposed methodology is illustrated with real data example.

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti

As the demands of sixth-generation (6G) networks escalate towards achieving high speeds and improved energy efficiency, there is an increasing need for intelligent and real-time adaptive solutions within the physical processing layer. This study proposes an innovative engineering framework based on an encapsulated architecture utilising FBGA (micro-distributed spherical array) technology, integrated with an internal artificial intelligence module, to achieve adaptive beamforming with high efficiency in dense wireless environments. The primary objective of this research is to develop an intelligent communication architecture that determines the optimal transmission angles and regulates power consumption in real-time by integrating ar

The research deals with solar energy as one of the sources of renewable energies available in Iraq, which can be utilized. The research aims to identify the design pillars of the use of solar energy in street furniture and its relationship to formal variables. The research limits included street furniture manufactured by JCDecaux in Boston during the period 2015-2016, and included the theoretical framework which consists of two sections: solar energy (its beginnings and uses), and solar energy and its uses in Street furniture design.

As far as the research procedures and methodology are concerned, it adopted the descriptive approach in describing and analyzing the sample models in addition to describing and analyzing the sample i

In this work, Pure and Cu: doped titanium dioxide nano-powder was prepared through a solid-state method. the dopant concentration [Cu/TiO₂ in atomic percentage (wt%)] is derived from 0 to 7 wt.%. structural properties of the samples performed with XRD revealed all nanopowders are of titanium dioxide having polycrystalline nature. Physical and Morphological studies were conducted using a scanning electronic microscope SEM test instrument to confirm the grain size and texture. The other properties of samples were examined using an optical microscope, Lee's Disc, Shore D hardness instrument, Fourier-transform infrared spectroscopy (FTIR), and Energy-dispersive X-ray spectroscopy (EDX). Results showed that the thermal conductivity

The thermal performance of indirect expansion solar assisted heat pump, IX-SAHP, was investigated experimentally under Iraqi climate. An Indirect-Solar Assisted Heat Pump system was designed, built, instrumented and tested. Experimental tests were conducted by varying the controlling parameters to investigate their effects on the thermal performance of the IX-SAHP such as cooling water flow rate, heating water flow rate, ambient temperature and solar radiation intensity. The investigation covered values of cooling water flow rate of (2, 3, 4, 5 l/min) and heating water flow rate of (2, 3, 4, 5 l/min) under meteorological condition of Baghdad from November 2014 to January 2015.

The results indicated that the performance of the IX-