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jcoeduw-1361
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Convolutional Neural Network (CNN) has been chosen as a better option for the training process because it produces a high accuracy. The final accuracy has reached 91.18% in five different classes. The results are discussed in terms of the probability of accuracy for each class in the image classification in percentage. Cats class got 99.6 %, while houses class got 100 %.Other types of classes were with an average score of 90 % and above.

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Solid Waste Treatment Using Multi-Criteria Decision Support Methods Case Study Lattakia City
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Lattakia city faces many problems related to the mismanagement of solid waste, as the disposal process is limited to the random Al-Bassa landfill without treatment. Therefore, solid waste management poses a special challenge to decision-makers by choosing the appropriate tool that supports strategic decisions in choosing municipal solid waste treatment methods and evaluating their management systems. As the human is primarily responsible for the formation of waste, this study aims to measure the degree of environmental awareness in the Lattakia Governorate from the point of view of the research sample members and to discuss the effect of the studied variables (place of residence, educational level, gender, age, and professional status) o

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Molecular Identification of Methylorubrum extorquens using PCR-Amplified MxaF Gene Fragments as A Molecular Marker
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  Methylotrophs bacteria are ubiquitous, and they have the ability to consume single carbon (C1) which makes them biological conversion machines. It is the first study to find facultative methylotrophic bacteria in contaminated soils in Iraq. Conventional PCR was employed to amplify MxaF that encodes methanol dehydrogenase enzyme. DNA templates were extracted from bacteria isolated from five contaminated sites in Basra. The gene specific PCR detected Methylorubrum extorquens as the most dominant species in these environments. The ability of M. extorquens to degrade aliphatic hydrocarbons compound was tested at the laboratory. Within 7 days, gas chromatographic (GC) studies of remaining utilize

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Publication Date
Fri Feb 01 2019
Journal Name
Environmental Technology & Innovation
The use of Artificial Neural Network (ANN) for modeling of Cu (II) ion removal from aqueous solution by flotation and sorptive flotation process
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Publication Date
Mon Oct 30 2023
Journal Name
Aro-the Scientific Journal Of Koya University
Enhancing Upper Limb Prosthetic Control in Amputees Using Non-invasive EEG and EMG Signals with Machine Learning Techniques
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Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Estimating the Parameters of Exponential-Rayleigh Distribution for Progressively Censoring Data with S- Function about COVID-19
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The two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival

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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Fusion Splicing for a Large Mode Area Photonic Crystal Fiber with Conventional Single Mode Fiber
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In this paper the experimentally obtained conditions for the fusion splicing with photonic crystal fibers (PCF) having large mode areas were reported. The physical mechanism of the splice loss and the microhole collapse property of photonic crystal fiber (PCF) were studied. By controlling the arc-power and the arc-time of a conventional electric arc fusion splicer (FSM-60S), the minimum loss of splicing for fusion two conventional single mode fibers (SMF-28) was (0.00dB), which has similar mode field diameter. For splicing PCF (LMA-10) with a conventional single mode fiber (SMF-28), the loss was increased due to the mode field mismatch.

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Publication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Development of Intelligent Control Strategy for an Anesthesia System Based on Radial Basis Function Neural Network Like PID Controller
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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
The effect of the Iraqi dinar exchange rate on inflation and economic growth using the joint integration methodology "a standard study"
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The exchange rate is of great importance at the global and local levels alike, as this importance increases with the increasing rates of development of economic relations between countries of the world due to openness and integration into the global economy, expressed by the expansion of the volume of trade and financial relations between countries. The Central Bank of Iraq has set the need to stabilize this price as a goal to reduce inflation rates and reduce them to the internationally accepted rates by using the foreign currency sale window to achieve a balance between the forces of supply and demand for foreign currency and to preserve the value of the Iraqi dinar. The research concluded that the central bank was It has a maj

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Determination of Nickel and Cobalt in Cosmetic Products Marketed in Iraq Using Spectrophotometric and Microfluidic Paper-based Analytical Device (µPADs) Platform
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Two quantitative, environment-friendly and easily monitored assays for Ni (II) and Co (III) ions analysis in different lipstick samples collected from 500-Iraqi dinars stores located in Baghdad were introduced. The study was based on the reaction of nickel (II) ions with dimethylglyoxime (DMG) reagent and the reaction of cobalt (III) ions with 1-nitroso-2-naphthol (NN) reagent to produce colored products. The color change was measured by spectrophotometric method at 565 nm and 430 nm for Ni and Co, respectively, with linear calibration graphs in the concentration range 0.25-100 mg L-1 (Ni) and 0.5-100 mg L-1 (Co) and LOD and LOQ of 0.11 mg L-1 and 0.36 mg L-1 (Ni), and 0.15 mg L-1 an

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Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of the relationship between the prices of wheat and rice importer in Iraq and crude oil prices and the exchange rate using the ARDL model
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Since the beginning of 21st century, the prices of Agricultural crops have increased. This Increases is accompanied with that increases of crude oil prices and fluctuation of a dollar exchange rate as a dominant currency used in the global trade. The paper aimed to analysis the short run and long run cointegration relationships between prices of some of Agricultural crops imported by Iraq such as wheat and rice crops and both the crude oil prices and the Iraq dinar exchange rate a gained America dollar using ARDL model. The results show the long run equilibrium between they three variable throng the error correction mechanizem. The results also show the significant and economically sound effects of cru

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