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Go to Editorial ManagerKidney disease is a global health concern, often leading to kidney failure and impaired function. Artificial intelligence and deep learning have been extensively researched, with numerous proposed models and methods to improve kidney disease diagnosis. This work aims to enhance the efficiency and accuracy of the diagnostic system for kidney disease by using Deep Learning, thereby contributing to effective healthcare delivery. This work proposed three models: CNN, CNN-XGBoost and CNN-RF to extract features and classify kidney Ultrasound images into four categories: three abnormal cases (stones, hydronephrosis, and cysts) and one normal case. The models were tested on a real dataset of 1260 kidney ultrasound images (from 1000 patients) collected from the Lithotripsy Centre in Iraq. CNN models are often viewed as black boxes due to the challenge of understanding their learned behaviors, Visualizing Intermediate Activations (VIA) was used to address this issue. The proposed framework was assessed based on precision, recall, F1-score, and accuracy. CNN-RF is the most accurate model, with an accuracy of 99.6%. This study can potentially assist radiologists in high-volume medical facilities and enhance the accuracy of the diagnostic system for kidney disease.
Mesopotamian cities were formed sometime during the fourth millennium BCE, and many of them continued to be inhabited as much as 3000 years. While urban characteristics of these cities has been extensively studied, the current article is concerned with exploring the inhabitants' daily experience in the city; a subject that has not been sufficiently explored despite its importance in urban studies. The objective is to expand the understanding of the relation between the ancient city and its occupants. The paper adopts the concept of the City Image as introduced in the seminal work of Kevin Lunch "Image of The City" in investigating aspects of the Mesopotamian city that qualifies it to form a strong mental Image for her citizens, derived from the legibility of its elements and the structure they form. Using a descriptive analytical method in reviewing previous literature, the research first clarifies the shared characters of Mesopotamian cities, and addresses the stature of the city in Mesopotamians' culture. I then specify the five urban elements of the city image as categorised by Lynch; paths, nodes, edges, districts and landmarks, in addition to addressing manifestations of the citizens' urban life in the Mesopotamian city. Afterward, visualization of the citizen's daily experience through the urban fabric of the city is provided, to arrive at a conclusion of the Legibility of the mental image of the Mesopotamian city in the perception of its citizens.
The non-woven materials industry is one of the fastest-growing industries in the world with the ability to produce materials in less time, specifications, and better prices. nonwoven materials are defined as a web of guided or random fibers that are bonded by friction, interlacement or adhesion. In this research, the rotary electrospinning system was used and a prototype was made to study the process and the complete visualization in terms of the correlation of the electrostatic forces to the formation of nanofibers by preparing polymeric solutions and exposing them to the electric field between the positive electrode (the serrated cylinder) and the Grounded electrode (plate) and produced high-precision fibers with a diameter (185nm) at 25 kV, whereas the installation of polyvinyl alcohol (PVA) was with different concentrations and the formed fibers possessed an effective surface and deposited on a collector electrode forming nonwoven webs and high productivity is the most important feature of this system compared with the traditional electrospinning system.
The solar vortex engine (SVE) has been investigated to generate power using renewable energy. The SVE was constructed from a vortex generation engine (VGE) and solar air collector (SAC). The SVE system primarily utilizes vertical air movement. However, the airflow entering the VGE experiences an obstruction. The purpose of this paper is to propose a new design for the VGE that creates a swirling updraft capable of overcoming air obstruction and reducing energy losses. A 3D numerical model of VGE was developed to visualize vortex generation. The modeling of the VGE is carried using SOLIDWORKS software and ANSYS-FLUENT 18. The improved VGE has six vertical twisted convergence blades connected to six guide vanes to direct updraft air in an anticlockwise swirl. All blades and vanes are housed in a VGE cylinder with a diameter of 20cm and a height of 30cm. The simulation results were validated by comparing with the results obtained from the present experimental model. The simulation results match with a mean difference of less than 5% with the experimental measurements. The results of the current CFD investigation indicate that there is a gradient in air temperature and pressure within the VGE, ranging from the highest values of 314 K and 3.85 Pa to the lowest values of 308 K and 2.42 Pa, respectively. The CFD visualization shows a threefold increase in axial velocity and a fivefold increase in tangential velocity within an artificial vortex. Therefore, it can be concluded that the new VGE construction is highly efficient in generating a vortex.