In this work, an inventive photovoltaic evaporative cooling (PV/EC) hybrid system was constructed and experimentally investigated. The PV/EC hybrid system has the prosperous advantage of producing electrical energy and cooling the PV panel besides providing cooled-humid air. Two cooling techniques were utilized: backside evaporative cooling (case #1) and combined backside evaporative cooling with a front-side water spray technique (case #2). The water spraying on the front side of the PV panel is intermittent to minimize water and power consumption depending on the PV panel temperature. In addition, two pad thicknesses of 5 cm and 10 cm were investigated at three different water flow rates of 1, 2, and 3 lpm. In Case #1,

This study deals with the serviceability of reinforced concrete solid and perforated rafters with openings of different shapes and sizes based on an experimental study that includes 12 post-fire non-prismatic reinforced concrete beams (solid and perforated). Three groups were formed based on heating temperature (room temperature, 400 °C, and 700 °C), each group consisting of four rafters (solid, rafters with 6 and 8 trapezoidal openings, and rafter with eight circular openings) under static loading. A developed unified calculation technique for deflection and crack widths under static loading at the service stage has been provided, which comprises non-prismatic beams with or without opening exposed to flexure concentra

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Congenital adrenal hyperplasia is a group of autosomal recessive disorders. The most frequent one is 21-hydroxylase deficiency. Analyzing CYP21A2 gene mutations was so far not reported in Iraq. This work aims to analyze the spectrum and frequency of CYP21A2 mutations among Iraqi CAH patients. Sixty-two children were recruited from the Pediatric Endocrine Consultation Clinic, Children Welfare Teaching Hospital, Baghdad, Iraq, from September 2014 till June 2015. Their ages ranged between one day and 15 years. They presented with salt wasting, simple virilization, or pseudoprecocious puberty. Cytogenetic study was performed for cases with ambiguous genitalia. Molecular analysis of