Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin’s method), The nonparametric model is estimated by using kernel smoothing (Nadaraya Watson), K-Nearest Neighbor smoothing and Median smoothing. The Flower Pollination algorithms were employed and structured in building the ecological model and estimating the semi-parametric regression function with measurement errors in the explanatory and dependent variables, then compare the models to choose the best model used in the environmental scope measurement errors, where the comparison between the models is done using the mean square error (MSE).
Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w
... Show MoreSediment samples were collected from main water processing and supply plants in Baghdad, and tested for radioactivity from both natural and artificial sources. These stations are: East Dijla (Tigris), Al-Kadisia, Al-Karama, Al-Rasheed, Al-Sader, Al-Wathba, and Al-Wihda supply stations. Qualitative measurements were made, and the results showed that most sediments exhibited natural radioactive level and sometimes less than the international regular standards. Specially, K-40 and Ra-226 results were much less than the standards for radioactive concentrations. Ac-228 concentration was found rather than Th-232 (in Al-Sader and Al-Wihda samples) but with low concentrations of about 10-15 Bg/kg and detection confidence ~45% , and Ce-141 and Be
... Show MoreAt the heart of every robust economy is a vital banking system. The functional banking system can effectively perform several functions such as mobilizing savings, allocating credit, monitoring managers, transforming risks, and facilitating the financial transactions. This paper aims to measure the impact of banking system development on economic growth in Iraq. Credit to private sector divided by GDP used as a proxy of banking development. Real per capita GDP used as a proxy of economic growth. By using Autoregressive Distributed Lag (ARDL) model, the paper finds that the undeveloped Iraqi banking system could not promote economic growth in the country. Therefore, a variety of policies need to be taken to spur the role of bankin
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This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model
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Regression testing is a crucial phase in the software development lifecycle that makes sure that new changes/updates in the software system don’t introduce defects or don’t affect adversely the existing functionalities. However, as the software systems grow in complexity, the number of test cases in regression suite can become large which results into more testing time and resource consumption. In addition, the presence of redundant and faulty test cases may affect the efficiency of the regression testing process. Therefore, this paper presents a new Hybrid Framework to Exclude Similar & Faulty Test Cases in Regression Testing (ETCPM) that utilizes automated code analysis techniques and historical test execution data to
... Show MoreObjective: This research aimed to study the relation between maximal bite force (MBF) and maximum mouth opening among 12-year-old school children. Methods: In this cross-sectional study, a total of 400 children aged 12 years (194 boys and 206 girls) were examined. The MBF for the right and left side, as well as the anterior region, were evaluated for all children. The MMO was measured using an electronic digital caliper. To analyze the data path analysis method was used. Results: Boys showed a higher MMO of 48.797 ± 6.500 than girls (46.710 ± 5.926 mm). The MMO increased with increasing MBF, with significant differences between females and males. Conclusion: The MMO was higher in boys than in girls. Gender plays a significant ro
... Show MoreThis paper deal with the estimation of the shape parameter (a) of Generalized Exponential (GE) distribution when the scale parameter (l) is known via preliminary test single stage shrinkage estimator (SSSE) when a prior knowledge (a0) a vailable about the shape parameter as initial value due past experiences as well as suitable region (R) for testing this prior knowledge.
The Expression for the Bias, Mean squared error [MSE] and Relative Efficiency [R.Eff(×)] for the proposed estimator are derived. Numerical results about beha
... Show MoreA stochastic process {Xk, k = 1, 2, ...} is a doubly geometric stochastic process if there exists the ratio (a > 0) and the positive function (h(k) > 0), so that {α 1 h-k }; k ak X k = 1, 2, ... is a generalization of a geometric stochastic process. This process is stochastically monotone and can be used to model a point process with multiple trends. In this paper, we use nonparametric methods to investigate statistical inference for doubly geometric stochastic processes. A graphical technique for determining whether a process is in agreement with a doubly geometric stochastic process is proposed. Further, we can estimate the parameters a, b, μ and σ2 of the doubly geometric stochastic process by using the least squares estimate for Xk a
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The aim of the study was to examine the level of psychological pollution among Jordanian unemployed faculty of education graduates in public and private universities. The sample of the study consisted of (413) Jordanian male and female unemployed faculty of education graduates in 2017. The researcher administrated the psychological pollution scale on the sample of the study, consisting in the final format of (37) items distributing on (4) domains. Validity and reliability for the scale were obtained. The results of the study indicated that level of psychological pollution among Jordanian unemployed faculty of education graduates in public and private universities was high (M=3.48, SD=0.83). The results
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