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.
An analytical and clinical study has been applied for measure the bioavailability of Zinc in serum of twenty adults healthy volunteers, using flame atomic absorption spectrophotometer (FAAS) at 213.9 nm. The calibration graph is linear in the ranges of 0.25-1.5 μg.mL-1 with correlation coefficient (R) 0.09996)μg.mL1-and molar absorpitivites 22957.76(L.mol1-cm-1.The concentration of Zinc determined in serum of all volunteers before and after administered orally a tablet of 50 mg zinc sulphate, produced by Samara drugs company (SDI). All data were subjected to statistical analysis by calculating accuracy, precision in addition to other parameters. The results indicate that the average maximum concentration (C-max ± SD) of blood zinc was 0.
... Show MoreThe developments accelerated in technology and rapid changes in the environment and increase numbers industrial countries and different desires and requirements of customers, lead to be produced in large quantities is not feasible due to changes listed above as well as the need to product variety and change in tastes and desires of consumers, all above led not to enable companies to discharge their products in the case of mass production and created the need to devise ways and new methods fit with the current situation, and accounting point no longer the traditional accounting systems able to meet the requirements needed by the companies to make decisions and know where waste and loss of resources resulting to invent new style away from
... Show MoreThe accuracy of the Moment Method for imposing no-slip boundary conditions in the lattice Boltzmann algorithm is investigated numerically using lid-driven cavity flow. Boundary conditions are imposed directly upon the hydrodynamic moments of the lattice Boltzmann equations, rather than the distribution functions, to ensure the constraints are satisfied precisely at grid points. Both single and multiple relaxation time models are applied. The results are in excellent agreement with data obtained from state-of-the-art numerical methods and are shown to converge with second order accuracy in grid spacing.
The background subtraction is a leading technique adopted for detecting the moving objects in video surveillance systems. Various background subtraction models have been applied to tackle different challenges in many surveillance environments. In this paper, we propose a model of pixel-based color-histogram and Fuzzy C-means (FCM) to obtain the background model using cosine similarity (CS) to measure the closeness between the current pixel and the background model and eventually determine the background and foreground pixel according to a tuned threshold. The performance of this model is benchmarked on CDnet2014 dynamic scenes dataset using statistical metrics. The results show a better performance against the state-of the art
... Show MoreThe cost of pile foundations is part of the super structure cost, and it became necessary to reduce this cost by studying the pile types then decision-making in the selection of the optimal pile type in terms of cost and time of production and quality .So The main objective of this study is to solve the time–cost–quality trade-off (TCQT) problem by finding an optimal pile type with the target of "minimizing" cost and time while "maximizing" quality. There are many types In the world of piles but in this paper, the researcher proposed five pile types, one of them is not a traditional, and developed a model for the problem and then employed particle swarm optimization (PSO) algorithm, as one of evolutionary algorithms with t
... Show MoreThe importance of this study stems from the importance of preserving the environment and creating a clean sustainable environment from waste and emissions and all the operations of industrial companies in general and cement companies in particular by activating sustainability accounting standards. The research aims to identify and diagnose deviations in violation of sustainability standards by employing the non-renewable resources standard (NR0401) For the construction industries to create a sustainable audit environment, the deductive approach was followed in the theoretical side and the inductive and descriptive approach to the practical side. The most important results of the research were the possibility of applying sustainab
... Show MoreThe aim of the research to apply TD-ABC technology to determine the idle capacity of the central oil companies (oil field east of Baghdad), as a modern cost management technology based on time-oriented activities (TD-ABC) is used by industrial companies in general and oil companies on In particular to build a sustainable Calvinist pillar and make future decisions by identifying idle energy to gain it a competitive advantage, the descriptive analytical approach has been adopted in calculating and analyzing the company’s data for 2018, and the most prominent conclusions of this research are managing idle energy and the task of applying cost technology on the basis of time-oriented activities and providing Convenient spatial infor
... Show MoreThis paper reports test results and describes a numerical investigation of the effectiveness of using carbon fibre reinforced polymer (CFRP) fabrics for strengthening concrete cylinders that have been undamaged and damaged due to heating under preload. The purpose of this research was to investigate whether there is any difference in the performance of CFRP-wrapped cylinders if the wrapping is done under preload, and those for which neither heating, cooling nor wrapping was done under preload. The cylinders were exposed to 30% of maximum load at ambient temperature during heating and cooling before being wrapped under preload. Of 18 Ø 100 × 200 mm identical cylinders, 6 were left as control samples without heating, 12 were exposed t
... Show MoreSupport vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
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