Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm

The implementation of decentralization in Iraq was asymmetrical, leading to different forms and paces of implementation. Comparing four cases of Basra, Kirkuk, Nineveh, and Sulaymaniyah indicate that these cases differ in their political stability and autonomy in a way that led to a different forms of decentralization. This paper argues that the higher the level of political autonomy from the federal government, the more efficient the governance model, and the more efficient the governance model, the more legitimate the system (trust), and the more legitimate a system, the more accountable elected officials. Therefore, it recommends reforming the institutional setup of decentralization by having districts, instead of provinces, as t

The implementation of decentralization in Iraq was asymmetrical, leading to different forms and paces of implementation. Comparing four cases of Basra, Kirkuk, Nineveh, and Sulaymaniyah indicate that these cases differ in their political stability and autonomy in a way that led to a different forms of decentralization. This paper argues that the higher the level of political autonomy from the federal government, the more efficient the governance model, and the more efficient the governance model, the more legitimate the system (trust), and the more legitimate a system, the more accountable elected officials. Therefore, it recommends reforming the institutional setup of decentralization by having districts, instead of provinces, as the bu

Aromaticity reversals between the electronic ground (S0) and low-lying singlet (S1, S2) and triplet (T1, T2, T3) states of naphthalene and anthracene are investigated by calculating the respective off-nucleus isotropic magnetic shielding distributions using complete-active-space self-consistent field (CASSCF) wavefunctions involving gauge-including atomic orbitals (GIAOs). The shielding distributions around the aromatic S0, antiaromatic S1 (1Lb), and aromatic S2 (1La) states in naphthalene are found to resemble the outcomes of fusing together the respective S0, S1, and S2 shielding distributions of two benzene rings. In anthracene, 1La is lower in energy than 1Lb, and as a result, the S1 state becomes aromatic, and the S2 state becomes anti

The research aim to know the effect of note–taking by computer method as amentalactivators in achievement of physics subject for the first intermediate class students.

To investigate from aim of the research the research sample was chosen from the first intermediate class students in Al–mutamyzat secondary school for girls. Which belongs to the general administration for the second karkh education which randomly chosen from (9) schools for distinct female students in Baghdad. Then randomly chosen two sections form three about (80) female students at (66.667%) from total sample it’s about (120) female student in the three sections. The randomly chosen too, section (a) to represent experimental group it’s about (41) female

Numerical study has been conducted to investigate the thermal performance enhancement of flat plate solar water collector by integrating the solar collector with metal foam blocks.The flow is assumed to be steady, incompressible and two dimensional in an inclined channel. The channel is provided with eight foam blocks manufactured form copper. The Brinkman-Forchheimer extended Darcy model is utilized to simulate the flow in the porous medium and the Navier-Stokes equation in the fluid region. The energy equation is used with local thermal equilibrium (LTE) assumption to simulate the thermofield inside the porous medium. The current investigation covers a range of solar radiation intensity at 09:00 AM, 12:00 PM, and 04:00

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings