abbas fadhil nori Al-rufaye

MATLAB is a good program for dealing with complex variables and simplifying them. This comes mainly or especially with images. The MATLAB program, has an accurate analysis of image data. Therefore, the MATLAB program was used to process medical images of tissues to obtain information of objects, to calculate the number of objects present in the tissue image. The research focused on finding the area of all objects in the image, and then comparing it with the arithmetic average of the large and small objects, to obtain an equation from which can directly extract the number of objects through direct image processing. Three groups of images were used in the research. The first group is experimental images manufactured through the Microsoft Word program in order to ensure the accuracy of the program. The second group is images from Google in order to increase the accuracy of verifying the validity of the program. The third group is the normal tissues for tissues (Rats), the fourth group is the abnormal tissues for tissues (Rats). The last two groups are the ones whose tissues were designed by the program to be examined by knowing the number of the object to determine whether the tissue is normal, abnormal, finished or invalid. It was also found that the best equation to give the number of objects required is the equation in which the area of all objects is divided by the ratio between the average area of the objects and the smallest object.

The study targeted the sea al-Najaf region, because of its geographical value, being an important water resource, as it acts as a large water reservoir, contributes to agriculture, and an important resting point for migratory birds, and has an important role in improving the climate in the region, and there are fish in it, also its Seasonal torrents gathering. Several remote sensing techniques and GIS have been used to track the effects of land cover changes. Knowing and understanding the amount, direction, and causes of land cover changes is critical to planning sustainable management of natural resources. Used ERDAS IMAGINE 2015 to do the supervised classification using maximum probability. Adopting the period from 2005 to 2022 as a period for a study in the study area. Water bodies, agricultural lands, barren lands, and clay soils were determined by multispectral satellite data (Landsat 5 TM images, Landsat 8 / OLI images, and Landsat 9 / OLI images). The results showed an increase for Water Bodies and Barren Land during the approved period by about 33.229% and 1.197% respectively, while a decrease in both agricultural lands and Clay soil was about 8.218% and 26.208%, respectively.

In this work comparison between the results of the first systems is a fixed solar and the second is the sun tracking in an attempt to increase the proportion of electricity production. Here a microcontroller (Arduino) and the light-dependent resistor (LDR) photo detector is used in this tracker. And then compare the results in different weather conditions and on different days to test the efficiency of the two systems. The efficiency of the tracking system is better than the fixed system by 12.3% on a sunny day and 4.9% on a partly cloudy day. However, it failed by 3.3% on a cloudy day. With a sunny day preference in the tracking system at 6.9% of partially cloudy days, and 12.1% with partially cloudy to a cloudy day. And verified from The efficiency of the work of the microcontroller (Arduino) system and the optical detector (LDR).

The world is highly interested in using solar energy as an alternative to fossil energy. Changing the shape of solar systems was adopted to improve its work efficiency. Although the solar tracker is made to be more efficient than the fixed solar system, the work to develop it is yet uncompleted. In this paper, the solar tracker system is used, which works by (LDR) sensors, microcontroller Arduino UNO for controlling the system, and DC motors. The extent of the impact of the solar tracker was studied with its work time. The worked electric circuit for the timer was run the system for one minute and shut-down the system circuit for 29 minutes, the comparison of the work of the tracker was done with a timer and without timer. Finally, according to the amount of gain and loss of energy, it was found that the energy gains about 96.25% from timer system only, and the lost energy from the solar panel because used the timer is about (0.238 to 0.475) % only. The workplace lies in (32o01’49.08” N, 44o22’21.83” E, in Iraq), in August, to real solar panel type.

In this paper, the global model magnetic (WMM2010) was used to study the anomaly Earth's magnetic field of the area between the center of Kufa city and the center of Manathira city in Najaf province (longitude 44.38o - 44.48o east longitude and latitude 32.01o - 32.92o north). In order to find the compounds Earth's magnetic field, a total components, horizontal component, angular inclination, gradient, North component, Eastern component and vertical component. (surfer 9.9) program was used. The results were drawn and compared with global maps. A mismatch was discovered between the graphs, with a slight abnormality in the vertical East. This indicates that a lack of contents of the region of the potential rocks that contain uranium are first found in phosphate rocks, geological breaking, or the presence of oil. This means the validity of this region for environmental perspective

Abstract: In this work , two type of the color space ware used , it is ( YPbPr , YUV ), and Lena color image were used , to test the pest PSNR, CR, ET, by used the fractal image compression by Zero-Mean method. In (YPbPr )color space the calculated results were found to be (PSNR=30.99), (CR=10.52), (ET=63.68), while in (YUV) color space is (PSNR=32.75), (CR=10.52), (ET=70.13). So in (PSNR) the (YPbPr) model is decreases by (1.76%) than (YUV) model, in CR the (YPbPr) model it same in (YUV) model and in ET the (YPbPr) model is decreases by (6.45%) than (YUV) model.