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Convolutional Multi-Spike Neural Network as Intelligent System Prediction for Control Systems
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The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed structure has the ability to predict the response of dynamical systems more powerful than with the CNN. The proposed structure is more powerful than the CNN by 28.33% in terms of minimizing the root mean square error.  

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Publication Date
Tue Sep 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Time Prediction of Dynamic Behavior of Glass Fiber Reinforced Polyester Composites Subjected to Fluctuating Varied Temperatures
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The reduction of vibration properties for composite material (woven roving E-glass fiber plies in thermosetting polyester matrix) is investigated at the prediction time under varied combined temperatures (60  to -15) using three types of boundary conditions like (CFCF, CCCF, and CFCC). The vibration properties are the amplitude, natural frequency, dynamic elastic moduli (young modulus in x, y directions and shear modulus in 1, 2 plane) and damping factor. The natural frequency of a system is a function of its elastic properties, dimensions, and mass. The woven roving glass fiber has been especially engineered for polymer reinforcement; but the unsaturated thermosetting polyester is widely used, offering a good balance of vibration p

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Publication Date
Thu Oct 31 2019
Journal Name
Asian Journal Of Pharmaceutical And Clinical Research
DESIGN, SYNTHESIS, DOCKING, ANTITUMOR SCREENING, AND ABSORPTION, DISTRIBUTION, METABOLISM, AND EXCRETION PREDICTION OF NEW HESPERDIN DERIVATIVE
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Objective: Hesperidin (HSP) is a pharmacologically active organic compound found in citrus fruits and peppermint. We synthesized a new HSP derivative by reacting it with 5-Amino-1,3,4-thiadiazole-2-thiol in acetic acid. Methods: This compound was characterized by Fourier-transform infrared, proton nuclear magnetic resonance, and electron impact mass spectra. A molecular docking study explores the predicted binding of the compound and its possible mode of action. Bioavailability, site of absorption, drug mimic, and topological polar surface was predicted using absorption, distribution, metabolism, and excretion (ADME) studies. Results: The docking study predicts that the new compound binds to the active sites of Aurora-B

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Publication Date
Wed Mar 29 2023
Journal Name
Materials
Prediction of the Bending Strength of a Composite Steel Beam–Slab Member Filled with Recycled Concrete
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This study investigated the structural behavior of a beam–slab member fabricated using a steel C-Purlins beam carrying a profile steel sheet slab covered by a dry board sheet filled with recycled aggregate concrete, called a CBPDS member. This concept was developed to reduce the cost and self-weight of the composite beam–slab system; it replaces the hot-rolled steel I-beam with a steel C-Purlins section, which is easier to fabricate and weighs less. For this purpose, six full-scale CBPDS specimens were tested under four-point static bending. This study investigated the effect of using double C-Purlins beams face-to-face as connected or separated sections and the effect of using concrete material that contains different recycled

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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Compare Prediction by Autoregressive Integrated Moving Average Model from first order with Exponential Weighted Moving Average
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The prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff

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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Prediction of pore and fracture pressure using well logs in Mishrif reservoir in an Iraqi oilfield
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Publication Date
Mon Nov 01 2021
Journal Name
Energy Reports
Global solar radiation prediction over North Dakota using air temperature: Development of novel hybrid intelligence model
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Publication Date
Fri Jan 01 2021
Journal Name
Environmental Pollution
Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models
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Publication Date
Sun Feb 24 2019
Journal Name
Iraqi Journal Of Physics
Design and evalution of a solar PV system
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PV connected systems are worldwide installed because it allows consumer to reduce energy consumption from the electricity grid. This paper presents the results obtained from monitoring a 1.1 kWp. The system was monitored for nine months and all the electricity generated was fed to the fifth floor for physics and renewable energy building   220 V, 50 Hz. Monthly, and daily performance parameters of the PV system are evaluated which include: average generated of system Ah per day, average system efficiency, solar irradiation around these months. The average generated kWh per day was 8 kWh/day, the average solar irradiation per day was 5.6 kWh/m2/day, the average inverter efficiency was 95%, the average modules efficien

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Heave Behavior of Granular Pile Anchor-Foundation System (GPA-Foundation System) in Expansive Soil
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Granular  Pile  Anchor  (GPA)  is  one  of  the  innovative  foundation  techniques,  devised  for mitigating heave of footing resulting from the expansive soils. This research attempts to study the heave behavior of (GPA-Foundation System) in expansive soil. Laboratory tests have been conducted on an experimental model in addition to a series of numerical modeling and analysis using the finite element package PLAXIS software. The effects of different parameters, such as (GPA) length (L) and diameter (D), footing diameter (B), expansive clay layer thickness (H) and presence of non-expansive clay are studied. The results proved the efficiency of (GPA) in reducing the heave of exp

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Publication Date
Tue Dec 30 2025
Journal Name
Iraqi Journal Of Science
The Prognostic Value for Tissue Inhibitor of Metalloproteinase-2 and Fatty Acid-Binding Protein-1 as Biomarkers for Chronic Kidney Disease
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Globally, chronic kidney disease (CKD) has emerged as a significant public health concern, characterized by high rates of morbidity and mortality. To assess the risk of kidney damage, researchers have identified tissue inhibitor of matrix metalloproteinase-2 (TIMP-2) and fatty acid-binding protein-1 (FABP-1) as valuable biomarkers. This study aims to analyse the effectiveness of specific biomarkers in assessing CKD and its associated mechanisms in Iraqi patients. The study was conducted from December 2023 to May 2024. Ninety subjects, aged 48–65 years; including 60 patients with CKD (38 male and 22 female) attended the Baghdad Teaching Hospital/ Medical City/ Dialysis Unit- Baghdad, Iraq. In addition, 30 healthy people (15 male an

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