Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's performance was evaluated, and tests were run. Line-to-ground faults were examined. The study demonstrates how effective, rapid, and precise this method is at locating faults. The neural network's performance was examined, and tests were run on it. The overall performance of the mean square error in the trained network execution was 0.11792 at 35 epochs. The correlation coefficient at the entire target was 0.99987 percent of an error on the Doukan-Erbil double transmission lines.
A field experiment was conducted at the field of the Dept. of Field Crop Sci. / College of Agriculture / University of Baghdad . The objective was to determine the values of relative constant of three – way and double crosses of maize . Ten inbreds were used and crossed during spring and fall seasons of 2009 to produce three - way and double crosses , and ten hybrids were taken from each group . The ten hybrids were grown and selfed during spring 2010 to produce 2 seed . Three way and double crosses were sown with their parents and 2 seed during fall 2010 in RCBD with four replicates . Leaf area , total dry matter , row/ear , grain/ear , grain weight and grain weight/plant of hybrids , parents and 2 plants were taken . Results showed that
... Show MoreBackground: Poly-ether-ether-ketone(PEEK) has been introduced to many dental fields. Recently it was tested as a retainer wire‎ following orthodontic treatment. This study aimed to investigate the effect of changing the bonding spot size and location on the performance of PEEK retainer wires. Methods: A biomechanical study involving four three-dimensional finite element models was performed. The basic model was with a 0.8 mm cylindrical cross-section PEEK wire, bonded at the center of the lingual surface of the mandibular incisors with 4 mm in diameter composite spots. Two other models were designed with 3 mm and 5 mm composite sizes. The last model was created with the composite bonding spot of the canine away from the center of t
... Show MoreBackground: Poly-ether-ether-ketone(PEEK) has been introduced to many dental fields. Recently it was tested as a retainer wire‎ following orthodontic treatment. This study aimed to investigate the effect of changing the bonding spot size and location on the performance of PEEK retainer wires. Methods: A biomechanical study involving four three-dimensional finite element models was performed. The basic model was with a 0.8 mm cylindrical cross-section PEEK wire, bonded at the center of the lingual surface of the mandibular incisors with 4 mm in diameter composite spots. Two other models were designed with 3 mm and 5 mm composite sizes. The last model was created with the composite bonding spot of the canine away from the center
... Show MoreThe predatory bush crickets Saga ephippigera Fischer Von Waldheim, 1846 is the largest Iraqi orthopterans and one of the most active and successful predators in the Kurdistan region. The nymphs and adults prey on all the stages of various species of insects. Twelve adult specimens were collected from Erbil Province during May 2018 and June 2021. Morphological structures of the adult insects were described and illustrated in details; important taxonomic characteristics of body regions with their appendages were chosen; and the results indicated the importance of morphological characteristics which confirmed the identification of this species correctly.
It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i
... Show MoreIn this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate kp (10-12g2.cm-4.s-1) in Incoloy 800H at 900oC . ANN was used for estimating the predicted values of hot corrosion rate kp (10-12g2.cm-4.s-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic alg
... Show MoreAttention-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 MoreBackground: The rapid evolution of Artificial Intelligence (AI) has significantly influenced Education, demonstrating substantial potential to transform traditional teaching and learning methods. AI reshapes teacher-student interactions and the relationship with knowledge. Objective: To analyze the potential benefits, ethical challenges, and limitations of AI in Education based on recent scientific literature, emphasizing the balance between technology and human interaction. Methods: A documentary research approach with a descriptive focus was employed, following the PRISMA protocol for systematic reviews. The search strategy involved analyzing evidence from 18 scientific articles published within the last six years. Results:AI o
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