The segmentation of aerial images using different clustering techniques offers valuable insights into interpreting and analyzing such images. By partitioning the images into meaningful regions, clustering techniques help identify and differentiate various objects and areas of interest, facilitating various applications, including urban planning, environmental monitoring, and disaster management. This paper aims to segment color aerial images to provide a means of organizing and understanding the visual information contained within the image for various applications and research purposes. It is also important to look into and compare the basic workings of three popular clustering algorithms: K-Medoids, Fuzzy C-Mean (FCM), and Gaussian Mixture Model (GMM). This will help find the best way to separate colors in aerial images. According to a thorough comparative study, PSNR and correlation metrics show that K-Medoids outperform other clustering techniques in terms of segmentation quality. Also, the effect of changing the number of clusters on the image quality was studied; when the number of clusters increases, the image quality increases. It was found that when K-Medoids were used, the PSNR and correlation were 35.57 and 0.99, respectively. When FCM and GMM were used, they were 35.54, 0.99, 31.67, and 0.97, respectively, when the number of clusters was 12.
There are serious environmental problems in all countries of the world, due to the waste material such as crushed clay bricks (CCB) and in huge quantities resulting from the demolition of buildings. In order to reduce the effects of this problem as well as to preserve natural resources, it is possible to work on recycling (CCB) and to use it in the manufacture of environmentally friendly loaded building units by replacing percentages in coarse aggregate by volume. It can be used as a powder and replacing of percentages in cement by weight and study the effect on the physical and mechanical properties of the concrete and the masonry unit. Evaluation of its performance through workability, dry density, compressive strength, thermal conduct
... Show MorePhosphorus is usually the limiting nutrient for eutrophication in inland receiving waters; therefore, phosphorus concentrations must be controlled. In the present study, a series of jar test was conducted to evaluate the optimum pH, dosage and performance parameters for coagulants alum and calcium chloride. Phosphorus removal by alum was found to be highly pH dependent with an optimum pH of 5.7-6. At this pH an alum dosage of 80 mg/l removed 83 % of the total phosphorus. Better removal was achieved when the solution was buffered at pH = 6. Phosphorus removal was not affected by varying the slow mixing period; this is due to the fact that the reaction is relatively fast.
The dosage of calcium chloride and pH of solution play an importa
This research has come out with that strategies made by Porter as generally strategies applicable to any size and type of economic units cannot be applied to many of the economic units in the world in generally and in Iraq especially not a lot of economic units have the resources and competencies that enable them to provide a unique product of its kind in the minds of customers and then adopt a differentiation strategy and not a lot of economic units have the resources and competencies that make them the cost leader. Differentiators and cost leaders are minority in the world while not differentiators and not cost leaders are majority in the world.
The economic units are not differentiators and not c
... Show MoreAccurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct
The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be
... Show MorePurpose This study investigated periodontal ligament (PDL) restoration in osseointegrated implants using stem cells. Methods Commercial pure titanium and zirconium oxide (zirconia) were coated with beta-tricalcium phosphate (β-TCP) using a long-pulse Nd:YAG laser (1,064 nm). Isolated bone marrow mesenchymal cells (BMMSCs) from rabbit tibia and femur, isolated PDL stem cells (PDLSCs) from the lower right incisor, and co-cultured BMMSCs and PDLSCs were tested for periostin markers using an immunofluorescent assay. Implants with 3D-engineered tissue were implanted into the lower right central incisors after extraction from rabbits. Forty implants (Ti or zirconia) were subdivided according to the duration of implantation (healing period: 45 o
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