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Smart Routing Management Framework Exploiting Dynamic Data Resources of Cross-Layer Design and Machine Learning Approaches for Mobile Cognitive Radio Networks: A Survey
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Publication Date
Sun Apr 24 2022
Journal Name
Egyptian Journal Of Chemistry
A novel Tubular Electrochemical Reactor with a Spiral Design of Anode for Treatment of Petroleum Refinery Wastewater
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Publication Date
Tue Jan 02 2024
Journal Name
Medical Oncology
COX 2-inhibitors; a thorough and updated survey into combinational therapies in cancers
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Publication Date
Sat Oct 18 2025
Journal Name
Pattern Recognition And Artificial Intelligence
Utilizing Energy-Efficient Deep Learning Technique for Age Estimation Through a Hybrid Methodology
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This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

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Publication Date
Wed Aug 27 2025
Journal Name
2025 International Conference On Electrical, Communication And Computer Engineering (icecce)
A Hybrid Deep Learning Approach for Fault Classification in Electric Vehicle Drive Motors
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A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
ESTIMATED NON-PARAMETRIC AND SEMI-PARAMETRIC MODEL FOR LONGITUDINAL DATA
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Publication Date
Sat Jul 22 2023
Journal Name
Journal Of Engineering
Data Acquisition System for Wind Speed, Direction and Temperature Measurements
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This paper describes the use of microcomputer as a laboratory instrument system. The system is focused on three weather variables measurement, are temperature, wind speed, and wind direction. This instrument is a type of data acquisition system; in this paper we deal with the design and implementation of data acquisition system based on personal computer (Pentium) using Industry Standard Architecture (ISA)bus. The design of this system involves mainly a hardware implementation, and the software programs that are used for testing, measuring and control. The system can be used to display the required information that can be transferred and processed from the external field to the system. A visual basic language with Microsoft foundation cl

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Self-Efficacy and its Relation to the Cognitive Assessment for the Daily Disturbances for the University of Baghdad Students
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The current research tackles the self-efficacy and its relation to the cognitive assessment for the daily disturbances for the University of Baghdad students. Two criteria have been adopted to achieve the objectives of the research. The sample of this study consists of 200 male and female students who were chosen randomly. The data were analyzed statistically, revealing that the university students owned their own self-efficacy as well as a cognitive assessment for the daily disturbances and they recognized them as self-threatening. The results also indicated the existence of a prediction activity in the field of the cognitive assessment to the daily disturbances selection. In light of the acquired results, the study recommends the neces

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Distributed Heuristic Algorithm for Migration and Replication of Self-organized Services in Future Networks
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Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject

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Publication Date
Wed Sep 16 2020
Journal Name
International Journal Of Dentistry And Oral Science
Attitude and Knowledge of Orthodontics among General Dentists and Non-Orthodontic Specialists: A Questionnaire Based Survey
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Aim: This study aimed to assessing orthodontic knowledge and attitude among general dentists and non-orthodontic specialists. Background: Early detection of orthodontic disorders is essentialin motivating patients to intervene prior to long term complications when the disorders are not recongised. Methods: A questionnaire was distributed amongst dentistsother than orthodontists. This questionnaire consisted of three sections. The first one aimed to collect demographic, educational level and practice type information. Further two sections consisted of closed-end questions designed to evaluateknowledge and attitude of orthodontics. Results: A total of 313 responses to the survey were submitted. No significant correlation was observed, e

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
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         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

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