The objective of the study was to predict crop coefficient (K) values for cucumber inside the greenhouse during the growing season 2014, using watermarks gypsum blocks and atmometer c apparatus during the growing stages and to compare the predicted values of the crop coefficient with different methods and approaches. The study was conducted in the greenhouses field within Al-Mahawil Township, 70 km south of Baghdad, Iraq. The watermarks soil water sensors and atmometer apparatus were used to measure crop evapotranspiration and reference evapotranspiration on daily basis, respectively. The comparison and the statistical analysis between the calculated K in this study and values obtained from greenhouse gave a good agreement. The root mean square difference (RMSD) and relative error (RE) gave an average value of: 0.065 mm/day and 9%, respectively. While, the comparison between the predicted K c values and approaches developed by FAO (modified) and Ministry of Water Resources of Iraq gave less agreement. The values of RMSD and RE gave an average value of: 0.188 mm/day, 27%, and 0.17 mm/day and 26.8%, respectively. The method used by FAO and Ministry of Water Resources of Iraq was conducted on basis of using modified empirical equation suggested by FAO-56.
This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used
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The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It
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Sesame crop, one of the very important oily, industrial, and summer crops that is economically important, has been investigated. The plantation and production of this crop has been studied in Al-Qadisiyah governorate during 2003-218. This is because this governorate is well-known by sesame plantation. Such a study helps to know the geographical distribution of sesame agricultural season in 2017-2018, and explore the most important natural factors that affect its plantation. Different research approaches have been adopted based on that facts that need to be met. A field study approach has been used in studying sesame crop descriptively and conceptually, shedding light on its nutritional and economic importance. Moreover, a descriptive com
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The researcher aims at focusing on the participations of children journalism in supplying the educational values for them. The researcher uses the survey method in addition to the method of content analysis through analyzing the content of two journals (Majalati and The Mezmar). Both of them deal with children issues.
The researcher concludes that the two journals focus on literary arts in a way which surpasses the journalistic arts. Furthermore, the two journals have concerned with showing the positive values as well as insuring the necessity of rectifying the wrong behaviors. Finally, the researcher recommends that it is necessary to improve the employees who work with children j
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