The performance of a solar assisted desiccant cooling system for a meeting-hall located in the College of Engineering/University of Baghdad was evaluated theoretically. The system was composed of four components; a solar air heater, a desiccant dehumidifier, a heat exchanger and an evaporative cooler. A computer simulation was developed by using MATLAB to assess the effect of various design and operating conditions on the performance of the system and its components. The actual weather data on recommended days were used to assess the load variation and the system performance during those days. The radiant time series method (RTS) was used to evaluate the hourly variation of the cooling load. Four operation modes were employed for performance evaluation. A 100 % ventilation mode and 3 recirculation modes, 30 % , 60 % and 100 % recirculation of room air. The concept of variable air volume was employed as a control strategy over the day, by changing the supply airflow rate to match the variation in the cooling load.
The results showed that the reduction in moisture content at regeneration temperatures from 55 o C to 75 o C lead to adequate removal of the high latent load in the meeting-hall. Also, the 30 % recirculation of return air resulted in comfortable indoor conditions satisfying the ventilation requirements for most periods of system operation. In addition, the COP of the system was high compared with the conventional vapor compression system. It varied from 1 to 13, when considering solar energy used to regenerate the
desiccant material as free energy.
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreBackground: Bimaxillary protrusion is considered as one of the most important causes to seek the orthodontic treatment to get better esthetics. This study aimed to test the effect of orthodontic treatment in improvement the facial esthetics. Materials and Methods: Ten Iraqi Arab females having bimaxillary protrusion based on Class I malocclusions treated with fixed orthodontic appliance and extraction of the maxillary and mandibular 1st permanent premolars. Pre and post-treatment facial profile photographs were taken for each patients and the effect of treatment was tested in comparison with the pre-treatment photographs by using seven angular measurements. Results: After treatment, the upper and lower lip projections were decreased signifi
... Show MoreThe development of the television industry has led to the emergence of a new type of entertainment program in which producers have abandoned stereotypes in traditional programs, known as (Reality TV show). This type of program has spread rapidly in America, (where there are more than 40 series of these programs), as well as Europe and more than twenty countries around the world, including the Arab countries, where the number of these programs today to about 1000 programs and the number is increasing , Especially with the readiness of the production networks to produce more of these programs for the huge profits they derive from them (because of the high viewing rates and the large number of ads broadcast through them) in return for low prod
... Show MoreBrain Fingerprinting (BF) is one of the modern technologies that rely on artificial intelligence in the field of criminal evidence law. Brain information can be obtained accurately and reliably in criminal procedures without resorting to complex and multiple procedures or questions. It is not embarrassing for a person or even violates his human dignity, as well as gives immediate and accurate results. BF is considered one of the advanced techniques related to neuroscientific evidence that relies heavily on artificial intelligence, through which it is possible to recognize whether the suspect or criminal has information about the crime or not. This is done through Magnetic Resonance Imaging (EEG) of the brain and examining
... Show MoreDouble-layer micro-perforated panels (MPPs) have been studied extensively as sound absorption systems to increase the absorption performance of single-layer MPPs. However, existing proposed models indicate that there is still room for improvement regarding the frequency bands of absorption for the double-layer MPP. This study presents a double-layer MPP formed with two single MPPs with inhomogeneous perforation backed by multiple cavities of varying depths. The theoretical formulation is developed using the electrical equivalent circuit method to calculate the absorption coefficient under a normal incident sound. The simulation results show that the proposed model can produce absorption coefficient with wider absorption bandwidth compared w
... Show MoreA comparison between the resistance capacity of a single pile excited by two opposite rotary machines embedded in dry and saturated sandy soil was considered experimentally. A small-scale physical model was manufactured to accomplish the experimental work in the laboratory. The physical model consists of: two small motors supplied with eccentric mass 0·012 kg and eccentric distance 20 mm representing the two opposite rotary machines, an aluminum shaft with 20 mm in diameter as the pile, and a steel plate with dimensions of (160 × 160 × 20 mm) as a pile cap. The experimental work was achieved taking the following parameters into consideration, pile embedment depth ratio (L/d; length to diameter) and operating freq
... Show MoreDeep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
... Show MoreThe aim of the present study is to evaluate the effectiveness of using Art as therapy to reduce the symptoms of Attention Deficit Hyper Activity Disorder (ADHD), in primary school children.
A clinical approach was used to test the validity of the hypothesis of our study, conducted on two second and fourth-year primary school pupils from Algiers, aged 7 and 9 years respectively.
In addition to the clinical observation and interview, we made use of the "Conners" scale for a (pre and post intervention) ADHD assessment, consisting of a combination of Art media in the form of mosaic works on purposely prepared panels. After 10 therapy sessions, results revealed the effectiveness of Art therapy in reducing ADHD in primary education