Accurate land use and land cover (LU/LC) classification is essential for various geospatial applications. This research applied a Spectral Angle Mapper (SAM) classifier on the Landsat 7 (ETM+ 2010) & 8 (OLI 2020) satellite scenes to identify the land cover materials of the Shatt al-Arab region which is located in the east of Basra province during ten years with an estimate of the spectral signature using ENVI 5.6 software of each cover with the proportion of its area to the area of the study region and produce maps of the classified region. The bands of these datasets were analyzed using the Optimum Index Factor (OIF) statistic. The highest OIF represents the best and most appropriate band combination calculated for the classification process are (SWIR_2, SWIR_1, Blue) and (SWIR_2, SWIR_1, coastal aerosol) bands combination at (100.236 & 104.154) for ETM+, and OLI datasets, respectively, which adopted to obtain the most accurate interpretation of the land cover. The Landsat 7 (ETM+ 2010) is selected as a reference year to study the change in land cover features through ten years for this region using the novel Scene Optimum Index Factor (SOIF), which was suggested in this research. The amount of change for vegetation cover was 34 %, using the SAM classifier. The urban class was the most stable, and the rate of change was 23 %. The most affected were the water bodies, where the rate of change reached 73% due to the region falling into the tails of rivers, as well as the lack of water discharges coming from neighbouring and upstream countries. The research provides important information about land cover changes over the past decade due to the precise spectral analyses, showing the need for monitoring natural resources, especially in environmentally sensitive areas such as water bodies and vegetation cover. Environmental conservation efforts and continuous planning in affected regions may be supported by these findings.
China is moving towards building the largest economic power in the world, so what does this mean economically and politically for Europe, America, the Middle East and the Arab world? This project is called the expansionist Chinese Marshall Plan which is a revival of the old Silk Road in a new way. It represents the aspirations of the Chinese people and their president, Xi Jinping, to build a transport route from Asia to Europe and a railway plan to transport goods. The purpose of this is to develop the economic growth model, expand into new markets, promote the Chinese currency, and expand economic and political influence in the areas covered by the Chinese initiative. Equal opportunities in distributing investments to these countries, a
... Show More The research addresses the feminist lament and its representations in the contemporary Arab theatrical text as one of the purposes of the Arabic poetry and its images, samples, and reasons developed and its incentives multiplied through different time periods in which a dramatic image and representations have been manifested that harmonized with the art of theatre. In order to shed light on these representations, this study has come to look for the representations of lament phenomenon in the Arab theatre texts.
The study consists of an introduction in which the two researchers put forward the research problem, significance and objectives, and a theoretical framework which tackles a theoretical foundation for the research consi
Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
... Show More<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
... Show MoreSensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar
... Show More<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
... Show MoreThe process of stocks evaluating considered as a one of challenges for the financial analysis, since the evaluating focuses on define the current value for the cash flows which the shareholders expected to have. Due to the importance of this subject, the current research aims to choose Fama & French five factors Model to evaluate the common stocks to define the Model accuracy in Fama& French for 2014. It has been used factors of volume, book value to market value, Profitability and investment, in addition to Beta coefficient which used in capital assets pricing Model as a scale for Fama & French five factors Model. The research sample included 11 banks listed in Iraq stock market which have me
... Show MoreThe fish assemblage in the East Hammar marsh was studied during December 2009 to May 2010. The fish fauna of the marsh consisted of 17 native, 23 marine (49%) and seven alien species. The dominant species were Liza abu (14.6%), Carassius auratus (13.4%) and Thryssa mystax (11.2%). The resident species formed 44.7%, occasional species 36.1% and seasonal species 19.2% of the total number of fish species. Fish species diversity index ranged from 1.28 to 2.61, richness from 1.98 to 4.50 and evenness from 0.45 to 0.78. Salinity ranged from 1.45 to 7.74‰. The increase in the proportion of marine species (49%) in the fish assemblage due to marine waters progress from Arabian Gulf had an impact on the values of ecological indices and the
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