This research represents a practical attempt applied to calibrate and verify a hydraulic model for the Blue Nile River. The calibration procedures are performed using the observed data for a previous period and comparing them with the calibration results while verification requirements are achieved with the application of the observed data for another future period and comparing them with the verification results. The study objective covered a relationship of the river terrain with the distance between the assumed points of the dam failures along the river length. The computed model values and the observed data should conform to the theoretical analysis and the overall verification performance of the model by comparing it with another set of data. The model was calibrated using data from gauging stations (Khartoum, Wad Medani, downstream Sennar, and downstream Roseires) during the period from the 1st of May to 31 of October 1988 and the verification was done using the data of the same gauging stations for years 2003 and 2010 for the same period. The required available data from these stations were collected, processed and used in the model calibration. The geometry input files for the HEC-RAS models were created using a combination of ArcGIS and HEC-GeoRAS. The results revealed high correlation (R2 ˃ 0.9) between the observed and calibrated water levels in all gauging stations during 1988 and also high correlation between the observed and verification water levels was obtained in years 2003 and 2010. Verification results with the equation and degree of correlation can be used to predict future data of any expected data for the same stations.
Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
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Stroke is the second largest cause of death worldwide and one of the most common causes of disability. However, several approaches have been proposed to deal with stroke patient rehabilitation like robotic devices and virtual reality systems, researchers have found that the brain-computer interfaces (BCI) approaches can provide better results. In this study, the electroencephalography (EEG) dataset from post-stroke patients were investigated to identify the effects of the motor imagery (MI)-based BCI therapy by investigating sensorimotor areas using frequency and time-domain features and to select particular methods that help in enhancing the MI-based BCI systems for stroke patients using EEG signal processing. Therefore, to detect
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Elzaki Transform Adomian decomposition technique (ETADM), which an elegant combine, has been employed in this work to solve non-linear Riccati matrix differential equations. Solutions are presented to demonstrate the relevance of the current approach. With the use of figures, the results of the proposed strategy are displayed and evaluated. It is demonstrated that the suggested approach is effective, dependable, and simple to apply to a range of related scientific and technical problems.
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
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The study aimed to examine the sensitivity to stress and its relation to positive mood among educational supervisors. The researcher used the descriptive approach as more an appropriate method for the current study. The sample is composed of (200) educational supervisor. To collect study data, two scales have been used: one scale to measure the sensitivity to stress and the other to measure the positive mood. The results indicated that a high level of sensitivity to stress with low level of positive mood among educational supervisors, sensitivity to stress showed significant differences among the sample regarding to major. There is no correlation between sensitivity to stress and positive mood, and finally, there are no significant diffe
... Show MoreSolid waste generation and composition in Baghdad is typically affected by population growth, urbanization, improved economic conditions, changes in lifestyles and social and cultural habits.
A burning chamber was installed to burn cellulosic waste only. It was found that combustion reduced the original volume and weight of cellulosic waste by 97.4% and 85% respectively.
A batch composting study was performed to evaluate the feasibility of co-composting organic food waste with the cellulosic bottom ash in three different weight ratios (w/w) [95/5, 75/25, 50/50].
The composters were kept in controlled aerobic conditions for 7 days. Temperature, moisture, and pH were measured hourly as process succe
... Show More<div><p><em>This study investigates the use of the speech act of request by </em><em>Iraqi EFL (English as a foreign language) learners </em><em>in student-professor e-mail communication. It aims to examine request strategies and internal modifications in academic requests in e-mail. There has been little investigation of the issue of an academic request made by Arab EFL learners to a higher status person via an authentic data. Thus, this study intends to provide more investigation of the strategies and internal modifiers that are produced by Iraqi EFL learners when they interact with their professors via e-mail. However, this study adapts the CCSARP (cross-cultural speech act realization pr
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In this paper, the concept of fully stable Banach Algebra modules relative to an ideal has been introduced. Let A be an algebra, X is called fully stable Banach A-module relative to ideal K of A, if for every submodule Y of X and for each multiplier ?:Y?X such that ?(Y)?Y+KX. Their properties and other characterizations for this concept have been studied.
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This research aims to determine the importance of the role that agile leadership plays in supporting programs and areas of investment in human capital, as it is the most important type of capital that the organization possesses and achieves returns that are many times the cost it bears, due to its rare and valuable characteristics. Through six behaviours: (humility behaviour, calm behaviour, wisdom behaviour, patience behaviour, objectivity behaviour, trust behaviour). As for investment in human capital, it was measured through its four elements (skills, knowledge, capabilities, experiences). Despite this, the researched organizations suffer from a decrease in awareness of the importance of this type of investment and the role of
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