Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area, distance to a river, distance to main roads, distance to heritage locations, distance to historical mosques, distance to commercial locations, distance to educational locations, and distance to hospital and clinics. Our findings showed that the SVR model had outperformed the LR model, where SVR achieved an accuracy of 82.9%.In contrast, LR has achieved 75.40%. Therefore, the presented models can assess land prices in holly cities like Al-Kufa. Furthermore, this tool can retain land pricing, land management, and urban planning in Iraq.
This study is dedicated to solving multicollinearity problem for the general linear model by using Ridge regression method. The basic formulation of this method and suggested forms for Ridge parameter is applied to the Gross Domestic Product data in Iraq. This data has normal distribution. The best linear regression model is obtained after solving multicollinearity problem with the suggesting of 10 k value.
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Recently new and multiple concepts emerged in the sustainability issues ,which transformed into number of planning and designing policies and strategies that must be committed by the designers and the relevant trends in building ,regarding Iraq and the reality of industrial areas ,especially in Baghdad, which helped to sustain few of it & emerged another with bad reflect ,which for that made it clear the importance of implicating sustainable ecological planning and designing strategies provided by the concept of Eco-industrial parks and the concept of Ecotowns and the future potentials provided ,and the easiness of carrying it out which made it flexible and away to provide a base supported by it for rebuilding and rehabilitation and
... Show MoreOne of the most significant elements influencing weather, climate, and the environment is vegetation cover. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) over the years 2019–2022 were estimated based on four Landsat 8 TIRS’s images covering Duhok City. Using the radiative transfer model, the city's land surface temperature (LST) during the next four years was calculated. The aim of this study is to compute the temperature at the land's surface (LST) from the years 2019-2022 and understand the link, between LST, NDVI, and NDBI and the capability for mapping by LANDSAT-8 TIRS's. The findings revealed that the NDBI and the NDVI had the strongest correlation with the
... Show MoreObjectives: To determine the effectiveness of the instructional program on patients’ knowledge about home safety while receiving anti-cancer treatment at Al- Karama Teaching Hospital in Al-Kut City.
Methodology: A quasi-experimental design is conducted through the application of a pre-test and post-test approach for the study and control groups from February 5th, 2020 to April 25th, 2020. A non–probability (purposive) sample of (50) patients treated at the Blood Disease and Oncology Center is selected and divided into two groups. Each group contains (25) patients as control and study groups. An instrument is constructed that is comprised of two parts; t
... Show MoreThe current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances. From the diversity of Big Data variables comes many challenges that can be interesting to the researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter
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Background: Animal bite is one of the public health problems all over the world, especially in poor countries. Animal bites have an impact on human health due to rabies disease, which is a viral transmitted disease from animal to human with a high mortality rate.
Objective: To determine the epidemiological characteristics of animal bite cases by person, time, and place.
Method: Descriptive cross sectional study was done by reviewing cases caused by animal bites., Data including the demographic characteristics of age, gender, occupation, site of bite, and attending health institutions searching treatment were all included.
Results: There were 11600 animal bite cases. Most of bites caused by stray dogs 11577(99.8%), and the males
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The research aims to provide a method to measure the fair value of the most environmentally friendly of Iraq and through the application of method of measuring the fair value of the company garments contribute to mixed as the company is of the economic units of the industrial sector and included in the Iraqi market for securities as a profit and distributes profits to shareholders since the method of measurement of the fair value based on the divided profits as toxic in a deduction of Cash Dividends cash for measuring fair value, and will also be in this research to clarify the disclosure of accounting for fair value and choose the method of disclosure most appropriate to the beneficiaries of accounting disclosure, as will be cho
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Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m
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Monitoring lotic ecosystems is vital for addressing sustainability issues. The Al-Shamiyah River is the primary source of water for various daily activities in the Al-Shamiyah district. This study assessed the pollution levels of the river by measuring the concentration and distribution of heavy metals—specifically chromium, cadmium, manganese, copper, zinc, and lead—in both the river's water and sediments. The concentrations of heavy metals in the water ranged from 0.05 to 1.44µg/ L for copper (Cu), 1.57 to 7.25µg/ L for manganese (Mn), 0 to 1.7µg/ L for cadmium (Cd), 0.02 to 1.33µg/ L for lead (Pb), 0.08 to 2.74µg/ L for zinc (Zn), and 0.44 to 1.84µg/ L for chromium (Cr). In the particulate phase, the concentrations ranged from
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The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co
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