The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

This paper presents a nonlinear finite element modeling and analysis of steel fiber reinforced concrete (SFRC) deep beams with and without openings in web subjected to two- point loading. In this study, the beams were modeled using ANSYS nonlinear finite element
software. The percentage of steel fiber was varied from 0 to 1.0%.The influence of fiber content in the concrete deep beams has been studied by measuring the deflection of the deep beams at mid- span and marking the cracking patterns, compute the failure loads for each deep beam, and also study the shearing and first principal stresses for the deep beams with and without openings and with different steel fiber ratios. The above study indicates that the location of openings an

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

In recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

The preparation of activated carbon (AC) from date stones by using microwave assisted K2CO3 activation was investigated in this paper. The influence of radiation time, radiation power, and impregnation ratio on the yield and methylene blue (MB) uptake of such carbon were studied. Based on Box-Wilson central composite design, two second order polynomial models were developed to correlate the process variables to the two responses. From the analysis of variance the significant variables on each response were identified. Optimum coditions of 8 min radiation time, 660 W radiation power and 1.5 g/g impregnation ratio gave 460.123 mg/g MB uptake and 19.99 % yield. The characteristics of the AC were examined by pore structure analysis, and scan

In cooling water systems, cooling towers play a critical role in removing heat from the water. Cooling water systems are commonly used in industry to dispose the waste heat. An upward spray cooling water systems was especially designed and investigated in this work. The effect of two nanofluids (Al₂O₃/ water, black carbon /water) on velocity and temperature distributions along reverse spray cooling tower at various concentrations (0.02, 0.08, 0.1, 0.15, and 0.2 wt.%) were investigated, beside the effect of the inlet water temperature (35 ,40, and 45 ͦ C) and water to air flow ratio (L/G) of 0.5, 0.75, and 1.  The best thermal performance was found when the working solution contained 0.1 wt.% for each of Al₂

The need for renewable energy sources is higher than ever due to rising global warming, climate change, and ozone depletion. For refrigeration and air conditioning applications, adsorption refrigeration systems are viable alternatives cooling techniques. This study is a topic and part of the M.Sc. thesis. A field solar-powered ice maker unit was created, studied, tested, and evaluated on the 13^th and 30^th of May, 2022. Activated carbon and methanol pair was used to set up a refrigeration system in Baghdad (Al Dora). Experimental tests were carried out outdoors to determine the coefficient of performance COP and specific cooling power SCP of the system. The results showed that the lowest temperature

An innovative desalination method called electrosorption or capacitive deionization (CDI) has significant benefits for wastewater treatment. This process is performed by using a carbon fiber electrode as a working electrode to remove hexavalent chromium ions from an aqueous solution. The pH, NaCl concentration, and cell voltage were optimized using the Box-Behnken experimental design (BDD) in response surface methodology (RSM) to study the effects and interactions of selected variables. To attain the relationship between the process variables and chromium removal, the experimental data were subjected to an analysis of variance and fitted with a quadratic model. The optimum conditions to remove Cr(VI) ions were: pH of 2, a cell voltage of 4.

The corrosion behavior of low carbon steel in washing water of crude oil solution has been studied potentiostatically at five temperatures in the range (30–70)°C .The corrosion potential shifted to more negative values with increasing temperature and the corrosion current density increased with increasing temperature. Folic acid had on inhibiting effect on the corrosion of low carbon steel in washing water at a concentration (5× 10-4-- 5× 10-3 ) mol/dm3 over the temperature range (30–70)°C. Values of the protection efficiency were calculated from the corrosion current density .From the general results for this study, it can be seen that thermodynamic and kinetic function were also calculated (?G, ?S, ?H and Ea )