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Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning
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In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poor settings of lighting, background, distance and camera resolution. Experimental results implied that the system was able to show high accuracies above 90% at very bad settings and around 99% at good settings, which assures that an inspection system with good performance can be built at low costs.  

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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Risk-Based Inspection Due to Corrosion Consequences for Oil and Gas Flowline: A Review
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   The petroleum industry, which is one of the pillars of the national economy, has the potential to generate vast wealth and employment possibilities. The transportation of petroleum products is complicated and changeable because of the hazards caused by the corrosion consequences. Hazardous chemical leaks caused by natural disasters may harm the environment, resulting in significant economic losses. It significantly threatens the aim for sustainable development. When a result, determining the likelihood of leakage and the potential for environmental harm, it becomes a top priority for decision-makers as they develop maintenance plans. This study aims to provide an in-depth understanding of the risks associated with oil and gas pipeli

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Publication Date
Thu Apr 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Effect of Rotation on the Heat Transfer of a Couple Stress Fluid in A Nonuniform Inclined Asymmetrical Channel with Inclined MHD
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 The purpose of this research is to investigate the effects of rotation on heat transfer using
inclination magnetohydrodynamics for a couple-stress fluid in a non-uniform canal. When the
Reynolds number is low and the wavelength is long, math formulas are used to describe the stream
function, as well as the gradient of pressure, temperature, pressure rise and axial velocity per
wavelength, which have been calculated analytically. The many parameters in the current model
are assigned a definite set of values. It has been noticed that both the pressure rise and the pressure
gradient decrease with the rise of the rotation and couple stress, while they increase with an
increase in viscosity and Hartmann nu

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
" The Effect of the Auditor's Experience on the Quality of Internal Audit "
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The importance of internal audit in the growing demand for services in the public and private economic units, and in the rapid growth of its systems professional, has also been recognition of the importance of internal audit quality and the quality of information provided in a long time, as well as the importance of achieving the greatest possible quality in his work to reduce accounting risks of financial reports misleading or fraudulent, which is one of the important features of the audit.

The internal audit quality are linked with the ability of auditors to detect errors in the financial statements, and their willingness to express an opinion technical neutral and non-aligned based on the results of th

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Design and Implementation of a Telemetry System for Environmental Applications
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The Environmental Data Acquisition Telemetry System is a versatile, flexible and economical means to accumulate data from multiple sensors at remote locations over an extended period of time; the data is normally transferred to the final destination and saved for further analysis.

This paper introduces the design and implementation of a simplified, economical and practical telemetry system to collect and transfer the environmental parameters (humidity, temperature, pressure etc.) from a remote location (Rural Area) to the processing and displaying unit.

To get a flexible and practical system, three data transfer methods (three systems) were proposed (including the design and implementation) for rural area services, the fi

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Publication Date
Wed Mar 16 2022
Journal Name
International Journal Of Recent Contributions From Engineering, Science & It
Smart Learning based on Moodle E-learning Platform and Digital Skills for University Students
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Publication Date
Tue Jun 01 2021
Journal Name
Bulletin Of Electrical Engineering And Informatics
A new pseudorandom bits generator based on a 2D-chaotic system and diffusion property
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A remarkable correlation between chaotic systems and cryptography has been established with sensitivity to initial states, unpredictability, and complex behaviors. In one development, stages of a chaotic stream cipher are applied to a discrete chaotic dynamic system for the generation of pseudorandom bits. Some of these generators are based on 1D chaotic map and others on 2D ones. In the current study, a pseudorandom bit generator (PRBG) based on a new 2D chaotic logistic map is proposed that runs side-by-side and commences from random independent initial states. The structure of the proposed model consists of the three components of a mouse input device, the proposed 2D chaotic system, and an initial permutation (IP) table. Statist

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Engineering
Intelligent Dust Monitoring System Based on IoT
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Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

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Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Emotion Recognition System Based on Hybrid Techniques
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Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

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Publication Date
Mon Aug 29 2016
Journal Name
World Journal Of Experimental Biosciences (issn: 2313-3937)
Effect of lead on biofilm formation by environmental isolates of Bacillus spp.
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Biofilm formation is one of the biggest challenges of scientists. Role of heavy metals in forming biofilm is not clear enough. Here, the effect of lead on biofilm formation by Bacillus spp. isolated from soil in terms of biofilm formation and remove was studied. In present study, 10 isolates of Bacillus spp were isolated from soil. The ability of all isolates to form biofilm was evaluated. The effect of lead on biofilm formation was studied by adding lead (pb) before forming biofilm. In another experiment the lead was added after biofilm formation to study the effect of lead on biofilm remove. The current study, showed the ability of all studied isolates to form biofilm. Maximum biofilm formation by Bacillus spp isolate number 8 (B8) follow

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