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A New Abnormality Detection Approach for T1-Weighted Magnetic Resonance Imaging Brain Slices Using Three Planes
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Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, coronal plane, and sagittal plane. Three different thresholds, which are based on texture features: mean, energy and entropy, are obtained automatically. This allowed to accurately separating the MRI slice into normal and abnormal one. However, the abnormality detection contained some normal blocks assigned wrongly as abnormal and vice versa. This problem is surmounted by applying the fine-tuning mechanism. Finally, the MRI slice abnormality detection is achieved by selecting the abnormal slices along its tumour region (Region of Interest-ROI).

Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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Publication Date
Mon Sep 15 2025
Journal Name
Alustath Journal For Human And Social Sciences
Searching for Meaning in a Chaotic World: An Analysis of Tina Howe’s Birth and After Birth
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Publication Date
Wed Aug 18 2021
Journal Name
Chemical Papers
Analytical methods for the identification of micro/nano metals in e-cigarette emission samples: a review
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Engineering
Efficient Energy Management for a Proposed Integrated Internet of Things-Electric Smart Meter (2IOT-ESM) System
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In this work, an efficient energy management (EEM) approach is proposed to merge IoT technology to enhance electric smart meters by working together to satisfy the best result of the electricity customer's consumption. This proposed system is called an integrated Internet of things for electrical smart meter (2IOT-ESM) architecture. The electric smart meter (ESM) is the first and most important technique used to measure the active power, current, and energy consumption for the house’s loads. At the same time, the effectiveness of this work includes equipping ESM with an additional storage capacity that ensures that the measurements are not lost in the event of a failure or sudden outage in WiFi network. Then then these

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Publication Date
Fri Aug 05 2016
Journal Name
Wireless Communications And Mobile Computing
A comparison study on node clustering techniques used in target tracking WSNs for efficient data aggregation
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Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati

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Publication Date
Mon Apr 27 2020
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
A COMPARISON OF TOPOLOGICAL KRIGING AND AREA TO POINT KRIGING FOR IRREGULAR DISTRICT AREA IN IRAQ
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Publication Date
Tue Jan 27 2026
Journal Name
Al–bahith Al–a'alami
HUMAN MODELING IN THE IRAQI PRESS: (A Survey of Human Modeling for March And April 2011)
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This research deals with what so called concept of The Human Model and how Iraqi Media concerns of this concept practically as it plays a key role in attracting readers, on the first hand. On the second, it is important to shed light on the scientific desire of the Iraqi Media and how it deals with this contemporary trend especially in editorial media.

The importance of the research stems from the fact that it alerts to a new stream of modern trends in journalistic writing, according to many modern Arab and foreign media studies; and to the importance of employing human modeling in dealing with facts, events, issues and problems in various editorial arts within their effective influence in concilia

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Publication Date
Sun Jan 30 2022
Journal Name
Heat Transfer
Theoretical and experimental investigation of a heat pipe heat exchanger for energy recovery of exhaust air
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Heat pipes and two‐phase thermosyphon systems are passive heat transfer systems that employ a two‐phase cycle of a working fluid within a completely sealed system. Consequently, heat exchangers based on heat pipes have low thermal resistance and high effective thermal conductivity, which can reach up to the order of (105 W/(m K)). In energy recovery systems where the two streams should be unmixed, such as airconditioning systems of biological laboratories and operating rooms in hospitals, heat pipe heat exchangers (HPHEs) are recommended. In this study, an experimental and theoretical study was carried out on the thermal performance of an air‐to‐air HPHE filled with two refrigerants as working fluids, R22 and R407c. The heat pipe he

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Publication Date
Thu Jun 01 2017
Journal Name
Nuclear Physics A
Alpha-cluster preformation factor within cluster-formation model for odd-A and odd–odd heavy nuclei
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Publication Date
Sat Oct 25 2025
Journal Name
Iet Networks
An Effective Technique of Zero‐Day Attack Detection in the Internet of Things Network Based on the Conventional Spike Neural Network Learning Method
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ABSTRACT<p>The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t</p> ... Show More
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