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Global solar radiation prediction over North Dakota using air temperature: Development of novel hybrid intelligence model
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Publication Date
Sun Sep 05 2010
Journal Name
Baghdad Science Journal
The effect of solar cells distribution on the Performance of solar panel
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Three different distribution modules of silicon solar cells in a panel are used in this study . Each module consists of five identical circular silicon solar cells of radius (5cm) and then the total panel areas are identical. The five solar cells are arranged in the panel in different shapes: circular, triangular and rectangular .The efficiency for these three panel distribution are measured indoor and outdoor. The results show that the efficiency is a function of the cells distribution.

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Fuzzy-assignment Model by Using Linguistic Variables
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      This work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.

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Publication Date
Mon Apr 20 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
A Robust Base-layer Design for Hierarchical IoT Intrusion Detection Using Hybrid Deep Learning
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The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines

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Publication Date
Tue Jun 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Studying the Rheological Properties of Non-Newtonian Fluids under the Effect of temperature Using Different Chemical Additives
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   This research studies the rheological properties ( plastic viscosity, yield point and apparent viscosity) of Non-Newtonian fluids under the effect of temperature using different chemical additives, such as (xanthan gum (xc-polymer), carboxyl methyl cellulose ( High and low viscosity ) ,polyacrylamide, polyvinyl alcohol, starch, Quebracho and Chrome Lignosulfonate). The samples were prepared by mixing 22.5g of bentonite with 350 ml of water and adding the additives in four different concentrations (3, 6, 9, 13) g by using Hamilton Beach mixer. The rheological properties of prepared samples were measured by using Fan viscometer model 8-speeds. All the samples were subjected to Bingham plastic model. The temperature range studi

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Publication Date
Sun Sep 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network
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Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Evaluation Method of Mesh Protocol over ESP32 and ESP8266
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Internet of Things (IoT) is one of the newest matters in both industry and academia of the communication engineering world. On the other hand, wireless mesh networks, a network topology that has been debate for decades that haven’t been put into use in great scale, can make a transformation when it arises to the network in the IoT world nowadays. A Mesh IoT network is a local network architecture in which linked devices cooperate and route data using a specified protocol. Typically, IoT devices exchange sensor data by connecting to an IoT gateway. However, there are certain limitations if it involves to large number of sensors and the data that should be received is difficult to analyze. The aim of the work here is to implement a self-

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Publication Date
Fri Nov 15 2024
Journal Name
Iraqi Journal Of Science
Comparison of the Physical Trace of Global Luminosity Emission at Multiwavelength and Star Formation Rates of Luminous Infrared Galaxies Using Extragalactic Distance Scale Techniques
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This paper aims to study the rate of star formation (SFR) in luminous infrared galaxies at different wavelengths using distance measurement techniques (dl, dm) and to know which methods are the most accurate to determine the rate of star formation as we present through this research the results of the statistical analysis (descriptive statistics) for a sample of luminous infrared galaxies. The data used in this research were collected from the NASA Extragalactic Database (NED) and HYPERLEDA, then used to calculate the star formation rate and indicate the accuracy of the distance methods used (dl, dm). Two methods were tested on Hα, OII, FIR, radio continuum at 1.4 GHz, FUV, NUV, and total (FUV + FIR). The results showed that the dl

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Publication Date
Thu Oct 26 2023
Journal Name
International Journal Of Environment And Waste Management
Novel Poly (3-hydroxybutyrate) production using Bacillus subtilis NG220 and watermelon derived substrates
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Poly (3-hydroxybutyrate) (PHB) is a typical microbial bio-polyester reserve material; known as “green plastics”, which produced under controlled conditions as intracellular products of the secondary metabolism of diverse gram-negative/positive bacteria and various extremophiles archaea. Although PHB has properties allowing being very attractive, it is too expensive to compete with conventional and non-biodegradable plastics. Feasibility of this research to evaluate the suitability of using a watermelon-derived media as an alternative substrate for PHB synthesis under stress conditions was examined. Results, include the most nutrients extraction, indicated that the watermelon seeds contain a high content of nutrients makes them a promisi

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Industrial And Engineering Chemistry
Petroleum refinery wastewater treatment using a novel combined electro-Fenton and photocatalytic process
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