Average per capita GDP income is an important economic indicator. Economists use this term to determine the amount of progress or decline in the country's economy. It is also used to determine the order of countries and compare them with each other. Average per capita GDP income was first studied using the Time Series (Box Jenkins method), and the second is linear and non-linear regression; these methods are the most important and most commonly used statistical methods for forecasting because they are flexible and accurate in practice. The comparison is made to determine the best method between the two methods mentioned above using specific statistical criteria. The research found that the best approach is to build a model for predicting Iraq’s average GDP per capita income by relying on the amounts of average GDP per capita income in the past years (1981-2020). The researcher found that in a second way, it became clear that the non-linear regression model of the Asian model was the best model representing (average per capita GDP income) in Iraq, and this model was used to predict the period (20221-2027). When comparing the two methods of projected amounts up to 2027, it was found that the best method was the second based on the indicator mean absolute percentage error (MAPE) because he has the least value.
The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.
During more than (50) years past, India has achieved considerable social and economic progress. It is also generally assumed that the future progress will be even more rapid and that India will be an important player in the global market. India has only (2.5) percent of global land whereas it has to provide home for one-sixth of world's population .On examining the past trends of India's population ,it may be observed that during the latter half of the twentieth century ,about (650) million populations were added to the country ,thus living in a country with a high population density and high growth rate , India in need a transition from high fertility high mortality to a low fertility low mortality and towards stable population situatio
... Show MoreFree boundary problems with nonlinear diffusion occur in various applications, such as solidification over a mould with dissimilar nonlinear thermal properties and saturated or unsaturated absorption in the soil beneath a pond. In this article, we consider a novel inverse problem where a free boundary is determined from the mass/energy specification in a well-posed one-dimensional nonlinear diffusion problem, and a stability estimate is established. The problem is recast as a nonlinear least-squares minimisation problem, which is solved numerically using the
ان الغرض من هذا البحث هو المزج بين القيود الضبابية والاحتمالية. كما يهدف الى مناقشة اكثر حالات مشكلات البرمجة الضبابية شيوعا وهي عندما تكون المشكلة الضبابية تتبع دالة الانتماء مرة دالة الاتنماء المثلثية مرة اخرى، من خلال التطبيق العملي والتجريبي. فضلا عن توظيف البرمجة الخطية الضبابية في معالجة مشكلات تخطيط وجدولة الإنتاج لشركة العراق لصناعة الأثاث، وكذلك تم استخدام الطرائق الكمية للتنبؤ بالطلب واعتماده
... Show MoreEnvironmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutant
... Show MoreThe major mortality factor for women globally is breast cancer, and current treatments have several adverse effects. Hesperetin (HSP) is a flavone that occurs naturally with anti-tumor capabilities and has been investigated as a potential treatment for cancer. This study aimed to investigate the cytotoxic and anti-malignant potential of HSP on breast cancer cells (BT-474) and normal cells (MCF-10a). The results indicated that HSP has dose-dependent cytotoxicity in BT-474 and MCF-10a cells. The elevated concentration of HSP lowered cell viability and proliferation. The half-maximal inhibitory concentration (IC50) of HSP in BT-
The aim of this study is to utilize the behavior of a mathematical model consisting of three-species with Lotka Volterra functional response with incorporating of fear and hunting cooperation factors with both juvenile and adult predators. The existence of equilibrium points of the system was discussed the conditions with variables. The behavior of model referred by local stability in nearness of any an equilibrium point and the conditions for the method of approximating the solution has been studied locally. We define a suitable Lyapunov function that covers every element of the nonlinear system and illustrate that it works. The effect of the death factor was observed in some periods, leading to non-stability. To confirm the theore
... Show MoreThyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
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