The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

Abstract
The current research aims to identify mental health and its role in promoting self-confidence and positive behavior of female university students. The researcher adopted the descriptive analytical approach in this research. The researcher depended on the availability of sources and references, literature, and previous field studies to analyze and study all aspects related to mental health and its role in promoting self-confidence and positive behavior of university students and then expand its importance and identify the areas of mental health, self-confidence, positive behavior, and university. The second chapter included the concept of mental health, the importance of the study, the most important factors of health and psyc

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

Autorías: Mariam Liwa Abdel Fattah, Liqaa Abdullah Ali. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 4, 2023. Artículo de Revista en Dialnet.

The effectiveness inhibitory to extract alcohol for the leaf and flower to plant sage Salvia pratensis each of Staphylococcus aureus, streptococcus epidermidis, Salmonella typhi, Pseudomonas aeroginosa, Escherichia coli, Aspergillus niger and Candida albicans whom had any inhibition to aqueous extracts of the parts itself species bacterial and fungal. The study also demonstrated that the extract of plant containing compounds chemical such as tannins, Alkaloids, Flavonoieds, and saponins, which owns effectiveness of medical. The MIC, MBC and inhibition zones for crud extract were determinated for microbial agents.

In this work four complexes of antimony were prepared ,Na[SbO(gly)2],Na[SbO(Asp)2],Na[SbO(Tyrosin)2], Na [SbO(phen alanin)2]. by reaction SbOCl with salts amino acids identifiefid these complexes by FTIR ,their conductivity was measured and also their biological activity against two types of bacteria was studied ,they were biologically active.

A new series of morpholine derivative were prepared by reacting the morpholine with ethyl chloro acetate in the presence triethylamine as an catalyst and benzene as a solvent gave the ethyl morpholin-4-ylacetate reaction with hydrazine hydrate and ethanol as a solvent gave the 2-(morpholin-4-yl)acetohydrazide gave series of Schiff base were prepared by reacting 2-(morpholin-4- yl)acetohydrazide with different aromatic aldehydes and ketons . The new series of (3-9 )were synthesis by reaction of Schiff base (10-14) with chloroacetyl chloride, triethyl amine as an catalyst and 1,4dioxane as a solvent .The chemical structures of the synthesis compound were identified by spectral methods their [ IR ,1H-NMR and 13C-NMR ].The synthesised compoun

The research aims to demonstrate the impact of TDABC as a strategic technology compatible with the rapid developments and changes in the contemporary business environment) on pricing decisions. As TDABC provides a new philosophy in the process of allocating indirect costs through time directives of resources and activities to the goal of cost, identifying unused energy and associated costs, which provides the management of economic units with financial and non-financial information that helps them in the complex and dangerous decision-making process. Of pricing decisions. To achieve better pricing decisions in light of the endeavor to maintain customers in a highly competitive environment and a variety of alternatives, the resear