In this study, the effect of construction joints on the performance of reinforced concrete beams was experimentally investigated. Seven beam specimens, with dimensions of 200×100×1000 mm, were fabricated. The variables were considered including; the location and configuration of the joints. One beam was cast without a joint (Reference specimen), two specimens were fabricated with a one horizontal joint located either at tension, or compression zone. The fourth
beam had two horizontal joints placed at tension, and compression area. The remaining specimens were with one or two inclined joints positioned at the shear span or beam’s mid-span. The specimens were subjected to a monotonic central concentrated loading until the failure. T

This research is devoted to investigate the behavior and performance of reinforced concrete beams strengthened with externally bonded Carbon Fiber Reinforced Polymer (CFRP) laminates under the effect of torsion. In this study a theoretical analysis has been conducted using finite element code ANSYS. Six previously tested beams are used to investigate reinforced concrete beams behavior
under torsion, two of them are solid and the rest are box-section beams. Also, two beams are without CFRP reinforcement, which are used as control beams for the strengthened one, and the other four beams are strengthened with CFRP laminates with different number of layers and spacing. Numerical investigation is conducted on these beams, and comparisons b

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

Purpose: Determining and identifying the relationships of smart strategic education systems and their potential effects on sustainable success in managing clouding electronic business networks according to green, economic and environmental logic based on vigilance and awareness of the strategic mind.

Design: Designing a hypothetical model that reveals the role and investigating audit and cloud electronic governance according to a philosophy that highlights smart strategic learning processes, identifying its assumptions in cloud spaces, choosing its tools, what it costs to devise expert minds, and strategic intelligence.

Methodology:

Objectives: The study aims to assess and evaluate the caregivers  knowledge  about management of the children with growth hormone deficiency and to find out the relationship between caregivers kowledge and caregivers age, gender, number of individual in house hold, Date of treatment started ,Caregivers level education and economic status Methodology: Quazi expermental study design was carried out at (Child's Central Teaching Hospital, Medical City of Al Imamian Al Khadhmain Teaching Hospital, and National Centre for Treatment and Research of Diabetes,Specialized Center for Endocrine Diseases and Diabetes, and Department of Medical City Children Welfare Teaching Hospital started  from