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Optimization of Digital Histopathology Image Quality
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One of the biomedical image problems is the appearance of the bubbles in the slide that could occur when air passes through the slide during the preparation process. These bubbles may complicate the process of analysing the histopathological images. The objective of this study is to remove the bubble noise from the histopathology images, and then predict the tissues that underlie it using the fuzzy controller in cases of remote pathological diagnosis. Fuzzy logic uses the linguistic definition to recognize the relationship between the input and the activity, rather than using difficult numerical equation. Mainly there are five parts, starting with accepting the image, passing through removing the bubbles, and ending with predict the tissues. These were implemented by defining membership functions between colours range using MATLAB. Results: 50 histopathological images were tested on four types of membership functions (MF); the results show that (nine-triangular) MF get 75.4% correctly predicted pixels versus 69.1, 72.31 and 72% for (five- triangular), (five-Gaussian) and (nine-Gaussian) respectively. Conclusions: In line with the era of digitally driven e-pathology, this process is essentially recommended to ensure quality interpretation and analyses of the processed slides; thus overcoming relevant limitations.

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Time and finance optimization model for multiple construction projects using genetic algorithm
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Abstract<p>Construction contractors usually undertake multiple construction projects simultaneously. Such a situation involves sharing different types of resources, including monetary, equipment, and manpower, which may become a major challenge in many cases. In this study, the financial aspects of working on multiple projects at a time are addressed and investigated. The study considers dealing with financial shortages by proposing a multi-project scheduling optimization model for profit maximization, while minimizing the total project duration. Optimization genetic algorithm and finance-based scheduling are used to produce feasible schedules that balance the finance of activities at any time w</p> ... Show More
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Publication Date
Sat Dec 01 2018
Journal Name
2018 Third Scientific Conference Of Electrical Engineering (scee)
An Intelligent Cognitive System Design for Mobile Robot based on Optimization Algorithm
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Publication Date
Tue Jul 01 2025
Journal Name
South African Journal Of Chemical Engineering
Electrocoagulation process for cobalt removal from industrial wastewater: Optimization and kinetic study
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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Sun Mar 28 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
A Light Weight Multi-Objective Task Offloading Optimization for Vehicular Fog Computing
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Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mo

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Publication Date
Mon Jun 15 2020
Journal Name
Al-academy
Aesthetics of the Sufi Image and its Representations in Post-Modern Theater Show
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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
COMPARATIVE STUDY FOR EDGE DETECTION OF NOISY IMAGE USING SOBEL AND LAPLACE OPERATORS
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Many approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good

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Publication Date
Thu Jun 01 2017
Journal Name
International Journal Of Engineering Research And Advanced Technology
The Use of First Order Polynomial with Double Scalar Quantization for Image Compression
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Publication Date
Sun Oct 01 2017
Journal Name
Al–bahith Al–a'alami
Fear manufacture in the propaganda discourse image of terrorist ISIS «Daesh» via websites
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This study aims to observe and analysis the propaganda discourse image for Daesh, and know how it marketing the fear due to symbols structure, and discover the straight meanings and hidden inspiration, with the ideology that the image presented.
The study is descriptive and qualitative, and the method is analytic survey used semiotic approach.
The most important results of the study refer to:
- Daesh functioning the image in fear manufacture in all it components: the symbol of savageness, body language, color, clothes uniform and professionally shot.
- The indicative meaning of fear promoted by Daesh based of the manufacturing «Holy», and that mean places non-touchable and non-insulted.
- Daesh used in its propagand

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Publication Date
Mon Mar 01 2021
Journal Name
Iraqi Journal Of Physics
Enhancement CT Scan Image and Study Electronic, Structural and Vibrational Properties of Iobenguane
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This work is divided into two parts first part study electronic structure and vibration properties of the Iobenguane material that is used in CT scan imaging. Iobenguane, or MIBG, is an aralkylguanidine analog of the adrenergic neurotransmitter norepinephrine and a radiopharmaceutical. It acts as a blocking agent for adrenergic neurons. When radiolabeled, it can be used in nuclear medicinal diagnostic techniques as well as in neuroendocrine antineoplastic treatments. The aim of this work is to provide general information about Iobenguane that can be used to obtain results to diagnose the diseases. The second part study image processing techniques, the CT scan image is transformed to frequency domain using the LWT. Two methods of contrast

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