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Optimum Efficiency of PV Panel Using Genetic Algorithms to Touch Proximate Zero Energy House (NZEH)
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By optimizing the efficiency of a modular simulation model of the PV module structure by genetic algorithm, under several weather conditions, as a portion of recognizing the ideal plan of a Near Zero Energy Household (NZEH), an ideal life cycle cost can be performed. The optimum design from combinations of NZEH-variable designs, are construction positioning, window-to-wall proportion, and glazing categories, which will help maximize the energy created by photovoltaic panels. Comprehensive simulation technique and modeling are utilized in the solar module I-V and for P-V output power. Both of them are constructed on the famous five-parameter model.  In addition, the efficiency of the PV panel is established by the genetic algorithm under the standard test conditions (STC) and a comparison between the theoretical and experimental results is done to achieve maximum performance ranging from 0.15 to 0.16, particularly with an error of about - 0.333 for an experimental power of 30 Watts compared with the theoretical power of 30.1 Watts.  The results obtained by the genetic algorithm give the best value for efficiency at the range of 16% to 17% of solar radiation, from 500–600 W/m2. These values are almost identical to the efficiency obtained from the results of the operation, where the best value for efficiency in the experimental results was seen to be 15.7%.

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Publication Date
Fri Sep 08 2023
Journal Name
International Journal Of Scientific Trends
The Role of Renewable Energy in the Protection of the Iraqi Environment
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In this article, the types of renewable energies and the environmental effects of consuming these energies are studied. Energy is one of the things necessary for economic and social development and improving the quality of life, and the presence of continuous and sustainable economic energy is essential for any economic development and growth. Humankind has been aware of renewable energies such as biomass and geothermal energy for a long time and has used these energies as heat sources for shelter. With the beginning of the extraction of fossil fuels such as oil and coal and unlimited access to these products, the use of renewable energy sources, except in remote places and forest areas, has become limited and forgotten. Currently in Iraq,

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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Optimization Algorithms Based on Path Planning and Neural Controller for Mobile Robot
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In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

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Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Health Sciences
Molecular assessment of some cardiovascular genetic risk factors among Iraqi patients with ischemic heart diseases
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Abstract Objective: The underlying molecular basis of ischemic heart diseases (IHDs) has not yet been studied among Iraqi people. This study determined the frequency and types of some cardiovascular genetic risk factors among Iraqi patients with IHDs. Methods: This is a cross-sectional study recruiting 56 patients with acute IHD during a 2-month period excluding patients >50 years and patients with documented hyperlipidemia. Their ages ranged between 18 and 50 years; males were 54 and females were only 2. Peripheral blood samples were aspirated from all patients for troponin I and DNA testing. Molecular analysis to detect 12 common cardiovascular genetic risk factors using CVD StripAssay® (ViennaLab Diagnostics GmbH, Austria) was performed

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Publication Date
Wed Aug 01 2018
Journal Name
Parasitology International
Genetic polymorphism of Baylisascaris procyonis in host infrapopulations and component populations in the Central USA
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Publication Date
Thu Jun 29 2023
Journal Name
Journal Of University Of Babylon For Pure And Applied Sciences
Genetic Detection of IMP-1 Gene and its Relationship with Biofilm Formation in Klebsiella pneumonia
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Background: Klebsiella pneumoniae were considered as normal flora of skin, and intestine. It can cause damage to human lungs; the danger of this bacterium is related to exposure to the hospital surroundings. materials and methods: the detection of Klebsiella pneumoniae on morphological and biochemical tests and then assured with VITEK 2 system. Resistance to antibiotics was determined by Kirby-Baeur method. And genotyping of IMP-1 in isolates was done by PCR technique, then biofilm formation was identified by Micro titer plate method. Results: The present study included a collecting of 50 specimens from different clinical specimens, (blood 40%, urine 30%, sputum 20%, wound infection 10%); 10 isolates were identified as K

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Publication Date
Sun Mar 06 2016
Journal Name
Baghdad Science Journal
Association of Glutathione–S-Transferase (GSTP1) Genetic Polymorphism in Iraqi Patients with Diabetes Mellitus Type2
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Glutathione S-transferases (GSTs) are enzymes that included, in a more range of detoxifying reactions by conjugation of glutathione, to electrophilic material. Polymorphisms n the genes that responsible of GSTs affect, the function of the GSTs. GSTs play an active role in protection of cell against oxidative stress mechanism. Polymorphisms of GSTP1 at codon 105 amino acids forms GSTP1 important site for bind of hydrophobic electrophiles and the substitution of Ile/Val affect substrate specially catalytic activity of the enzyme and may correlate with reach to different diseases in human like diabetes mellitus type2 disease. Correlation between these polymorphisms and changes in the parameters file of diabetic patients has also bee

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Publication Date
Sun Dec 01 2002
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
PREDATION BY THE MITE MACROCHELES GLABER (MÜLLER) (ACARINA: MACROCHELIDAE) ON THE HOUSE FLY MUSCA DOMESTICA L. WITH SOME NOTES ON ITS BIOLOGY
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Macrocheles glaber (Müller) is one of several mites that feeds on eggs, newly hatched &
small larvae of house fly Musca domestica L. This mite was reared in the laboratory on house
fly frozen eggs at constant conditions of 28°C±1 and 90% relative humidity using sterilized
horse dung substrate. The predation rate of adult female and male on frozen eggs was (18, 3)
eggs/mite/day respectively, the number of frozen eggs destroyed by adult female through its
life was 185.6 eggs.
The mean duration of adult female from egg to adult stage was 2.67 days, the longevity of
female was 27.8 days, the mean daily egg production was 2.7 egg with total egg productivity
of 72.1 egg.

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Developing Load Balancing for IoT - Cloud Computing Based on Advanced Firefly and Weighted Round Robin Algorithms
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The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities.   Cloud computing can be used to store big data.  The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r

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Publication Date
Thu Mar 01 2018
Journal Name
2018 International Conference On Computing Sciences And Engineering (iccse)
Comparison between Epsilon Normalized Least Means Square (ϵ-NLMS) and Recursive Least Squares (RLS) Adaptive Algorithms
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There is an evidence that channel estimation in communication systems plays a crucial issue in recovering the transmitted data. In recent years, there has been an increasing interest to solve problems due to channel estimation and equalization especially when the channel impulse response is fast time varying Rician fading distribution that means channel impulse response change rapidly. Therefore, there must be an optimal channel estimation and equalization to recover transmitted data. However. this paper attempt to compare epsilon normalized least mean square (ε-NLMS) and recursive least squares (RLS) algorithms by computing their performance ability to track multiple fast time varying Rician fading channel with different values of Doppler

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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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