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Spatial Prediction of Monthly Precipitation in Sulaimani Governorate using Artificial Neural Network Models
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ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data set sub-division into training, testing and holdout data sub-sets, and different number of hidden nodes in the hidden layer. It is found that it is not necessary that the nearest station to the station under prediction has the highest effect; this may be attributed to the high differences in elevation between the stations. It can also found that the variance is not necessary has effect on the correlation coefficient obtained.

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Publication Date
Fri Sep 26 2025
Journal Name
Applied Data Science And Analysis
Deep Learning in Genomic Sequencing: Advanced Algorithms for HIV/AIDS Strain Prediction and Drug Resistance Analysis
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Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

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Publication Date
Wed Dec 29 2021
Journal Name
Modern Sport
Creative behavior and its relationship to the administrative leadership of secondary school principals in Al- Karkh/2 district in Baghdad governorate
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The importance of research lies in the school administration and that the school is the main cell of the educational system and its ultimate goal, and therefore modern education requires the presence of sophisticated leaders represented in educational administration at various levels. Administrative leaderships and the two researchers' belief that the institution’s ability and success or failure depend on a special type of leader who is highly effective and efficient, directing workers ’behavior towards creativity and achievement in order to achieve the goals of the institution in serving the educational bodies, increasing the effectiveness of leadership and developing the creative behavior of secondary school principals in

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Publication Date
Tue Dec 31 2019
Journal Name
Iraqi Geological Journal
CLIMATIC WATER BALANCE FOR ISHAQI AREA, SALAH AL-DEAN GOVERNORATE, IRAQ
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In any natural area or water body, evapotranspiration is one of the main outcomes in the water balance equation. It is also a crucial component of the hydrologic cycle and considers as the main requirement in the planning and designing of any irrigation project. The climatic parameters for the Ishaqi area are calculated from the available date of Samarra and Al-Khlais meteorological stations according to a method for the period (1982–2017) according to Fetter method. The results of the mean of rainfall, relative humidity temperature, evaporation, sunshine, and wind speed of the Ishaqi area are 171.96 mm, 49.67%, 24.86 C°, 1733.61 mm, 8.34 h/day, and 2.3 m/sec, respectively. Values of Potential Evapotranspiration are determined by

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Engineering
Seismic Effects and Static Analysis for the Artificial Damped Outrigger Systems in Tall R.C Buildings
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This paper studies the combination fluid viscous dampers in the outrigger system to add supplementary damping into the structure, which purpose to remove the dependability of the structure to lower variable intrinsic damping. It works by connecting the central core, comprising either shear walls or braced frames, to the outer perimeter columns.

     The modal considered is a 36 storey square high rise reinforced concrete building. By constructing a discrete lumped mass model, and using frequency-based response function, two systems of dampers, parallel and series systems are studied. The maximum lateral load at the top of the building is calculated, and  this load  w

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Publication Date
Mon Mar 10 2025
Journal Name
Proceedings On Engineering Sciences
WAREHOUSE IN INDUSTRY 4.0 BASED DRONE, COMPUTER VISION, AND ARTIFICIAL INTELLIGENCE TECHNOLOGIES: A LITERATURE REVIEW
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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Effect of Laser Surface Modification on the Corrosion Resistance of Dental Alloys in Artificial Saliva Containing Alcoholic Beverages
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The objective of this study is to demonstrate the corrosion behavior of dental alloys Co-Cr-Mo, Ni-Cr-Mo and Ti-Al-V in artificial saliva at pH=4 and 37oC enriched with ethyl alcohol at 8% percentage. The linear and cyclic polarizations were investigated by electrochemical measurements. Laser surface modification was achieved for the three dental alloys to improve corrosion resistance. The results show that corrosion resistance of Co-Cr-Mo and Ni-Cr-Mo alloys only were increased after laser treatment due to the fact that laser radiation has caused a smoother surface, in addition to the decrement in corrosion current densities (icorr) for Co-Cr-Mo and Ni-Cr-Mo alloys and the reverse scan in cyclic polarization became in the wider range of

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Publication Date
Thu Apr 04 2024
Journal Name
Journal Of Electrical Systems
AI-Driven Prediction of Average Per Capita GDP: Exploring Linear and Nonlinear Statistical Techniques
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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 predi

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Publication Date
Tue Aug 01 2023
Journal Name
Journal Of Engineering
An Extensive Literature Review on Risk Assessment Models (Techniques and Methodology) for Construction Industry
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This study looks into the many methods that are used in the risk assessment procedure that is used in the construction industry nowadays. As a result of the slow adoption of novel assessment methods, professionals frequently resort to strategies that have previously been validated as being successful. When it comes to risk assessment, having a precise analytical tool that uses the cost of risk as a measurement and draws on the knowledge of professionals could potentially assist bridge the gap between theory and practice. This step will examine relevant literature, sort articles according to their published year, and identify domains and qualities. Consequently, the most significant findings have been presented in a manne

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Publication Date
Wed Mar 01 2017
Journal Name
International Communications In Heat And Mass Transfer
Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al 2 O 3 nanofluids by NSGA-II using ANN
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In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

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Publication Date
Sat Dec 01 2018
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Design and Implementation of a Contactless Smart House Network System
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The Internet of Things (IoT) technology is every object around us and it is used to connect these objects to the Internet to verify Machine to Machine (M2M) communication. The smart house system is the most important application of IoT technology; it is increase the quality of life and decrease the efforts. There were many problems that faced the existing smart house networking systems, including the high cost of implementation and upgrading, high power consumption, and supported limited features. Therefore, this paper presents the design and implementation of smart house network system (SHNS) using Raspberry Pi and Arduino platforms as network infrastructure with ZigBee technology as wireless communication. SHNS consists of two mai

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