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A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking desired voltage and less energy consumption through investigating and comparing under random current variations with the minimum number of fitness evaluation less than 20 iterations.

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Unifying The Evaluation Criteria Of Many Objectives Optimization Using Fuzzy Delphi Method
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Many objective optimizations (MaOO) algorithms that intends to solve problems with many objectives (MaOP) (i.e., the problem with more than three objectives) are widely used in various areas such as industrial manufacturing, transportation, sustainability, and even in the medical sector.  Various approaches of MaOO algorithms are available and employed to handle different MaOP cases. In contrast, the performance of the MaOO algorithms assesses based on the balance between the convergence and diversity of the non-dominated solutions measured using different evaluation criteria of the quality performance indicators. Although many evaluation criteria are available, yet most of the evaluation and benchmarking of the MaOO with state-of-art a

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Publication Date
Wed Feb 02 2022
Journal Name
Iraqi Journal Of Science
Effect of growth media components and growth condition on indole – 3 – acetic acid (IAA) production by Pseudomonas putida isolated from soil
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Pseudomonas putidaPST-1 isolate isolated from soil of plant root was used for high production of indole acetic acid. Indole acetic acid (IAA) production is a major property of rhizosphere bacteria that stimulate and facilitate plant growth. Optimization of indole acetic acid production was carried out at different cultural conditions of pH temperature, incubation period, and the amount of inoculum of bacteria. The best chemical medium for high IAA production (82 Mg/ml) was Luria-Bertani broth medium consisted of 1.2gm tryptophan and 10gm peptone in their components, while the cheese whey medium was the best natural medium for IAA production was (66 Mg/ml). IAA production byPseudomonas putida PST-1 was optimized by studying some factors t

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Publication Date
Mon Jan 27 2020
Journal Name
Iraqi Journal Of Science
Optimal Robot Path Planning using Enhanced Particle Swarm Optimization algorithm
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The aim of robot path planning is to search for a safe path for the mobile robot. Even though there exist various path planning algorithms for mobile robots, yet only a few are optimized. The optimized algorithms include the Particle Swarm Optimization (PSO) that finds the optimal path with respect to avoiding the obstacles while ensuring safety. In PSO, the sub-optimal solution takes place frequently while finding a solution to the optimal path problem. This paper proposes an enhanced PSO algorithm that contains an improved particle velocity. Experimental results show that the proposed Enhanced PSO performs better than the standard PSO in terms of solution’s quality. Hence, a mobile robot implementing the proposed algorithm opera

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Monitoring of environmental variations of marshes in Iraq using Adaptive classification method.
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The object of the presented study was to monitor the changes that had happened
in the main features (water, vegetation, and soil) of Al-Hammar Marsh region. To
fulfill this goal, different satellite images had been used in different times, MSS
1973, TM 1990, ETM+ 2000 and MODIS 2010. K-Means which is unsupervised
classification and Neural Net which is supervised classification was used to classify
the satellite images 0Tand finally by use 0Tadaptive classification 0Twhich is0T3T 0T3Tapply
s0Tupervised classification on the unsupervised classification. ENVI soft where used
in this study.

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Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
Effect of Successive Convolution Layers to Detect Gender
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Image classification can be defined as one of the most important tasks in the area of machine learning. Recently, deep neural networks, especially deep convolution networks, have participated greatly in end-to-end learning which reduce need for human designed features in the image recognition like Convolution Neural Network. It is offers the computation models which are made up of several processing layers for learning data representations with several abstraction levels. In this work, a pre-trained deep CNN is utilized according to some parameters like filter size, no of convolution, pooling, fully connected and type of activation function which includes 300 images for training and predict 100 image gender using probability measures. Re

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Effective Digital Image Colors Reduction/Quantization Method
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In the current research work, a method to reduce the color levels of the pixels within digital images was proposed. The recent strategy was based on self organization map neural network method (SOM). The efficiency of recent method was compared with the well known logarithmic methods like Floyd-Steinberg (Halftone) dithering and Octtrees (Quadtrees) methods. Experimental results have shown that by adjusting the sampling factor can produce higher-quality images with no much longer run times, or some better quality with shorter running times than existing methods. This observation refutes the repeated neural networks is necessarily slow but have best results. The generated quantization map can be exploited for color image compression, clas

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Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
Diagnoses System of Varicose Disease
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The diagnoses system of varicose disease has a good level of performance due to the complexity and uniqueness in patterns of vein of the leg. In addition, the patterns of vein are internal of the body, and its features are hard to duplicate, this reason make this method not easy to fake, and thus make it contains of a good features for varicose disease diagnoses. The proposed system used more than one type of algorithms to produce diagnoses system of varicose disease with high accuracy, in addition, this multi-algorithm technique based on veins as a factor to recognize varicose infection. The obtained results indicate that the design of varicose diagnoses system by applying multi- algorithms (Naïve Bayes and Back-Propagation) produced n

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agriculture And Statistical Science
COMPARISON OF FORECASTING OF THE RISK OF CORONAVIRUS (COVID-19) IN HIGH-QUALITY AND LOW-QUALITY HEALTHCARE SYSTEMS, USING ANN MODELS
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COVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduce

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Publication Date
Sun Jan 13 2019
Journal Name
Iraqi Journal Of Physics
Porous Silicon effect on the performance of CdS nanoparticles photodetector
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Cadmium sulfide photodetector was fabricated. The CdS nano
powder has been prepared by a chemical method and deposited as a
thin film on both silicon and porous p- type silicon substrates by spin
coating technique. Structural, morphological, optical and electrical
properties of the prepared CdS nano powder are studied. The X-ray
analysis shows that the obtained powder is CdS with predominantly
hexagonal phase. The Hall measurements show that the nano powder
is n-type with carrier concentration of about (-5.4×1010) cm-3. The
response time of fabricated detector was measured by illuminating
the sample with visible radiation and its value was 5.25 msec. The
specific detectivity of the fabricated det

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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Science And Research (ijsr
Interaction of Alpha Particles with Breast Tissue
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As modern radiotherapy technology advances, radiation dose and dose distribution have improved significantly. As part of a natural evolution, there has recently been renewed interest in therapy, particularly in the use of heavy charged particles, because these types of radiation serve theoretical advantages in all biological and physical aspects. The interactions of alpha particle with matter were studied and the stopping powers of alpha particle with Breast Tissue were calculated by using Beth-Bloch equation, Zeigler's formula and SRIM software, also the Range and Liner Energy Transfer (LET) and Breast Thickness As well as Dose and Dose equivalent for this particle were calculated by using Mat lab language for (0.01-200) MeV alpha ene

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