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Evolutionary multi-objective set cover problem for task allocation in the Internet of Things
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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Minimum Spanning Tree Algorithm for Skin Cancer Image Object Detection
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This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Fri Mar 20 2009
Journal Name
Ijcsns International Journal Of Computer Science And Network Security
Pre-processing Importance for Extracting Contours from Noisy Echocardiographic Images
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Contours extraction from two dimensional echocardiographic images has been a challenge in digital image processing. This is essentially due to the heavy noise, poor quality of these images and some artifacts like papillary muscles, intra-cavity structures as chordate, and valves that can interfere with the endocardial border tracking. In this paper, we will present a technique to extract the contours of heart boundaries from a sequence of echocardiographic images, where it started with pre-processing to reduce noise and produce better image quality. By pre-processing the images, the unclear edges are avoided, and we can get an accurate detection of both heart boundary and movement of heart valves.

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Publication Date
Fri Apr 01 2011
Journal Name
Al-mustansiriyah Journal Of Science
A Genetic Algorithm Based Approach For Generating Unit Maintenance Scheduling
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Publication Date
Sat Jan 01 2022
Journal Name
Webology
Efficient Eye Recognition for Secure Systems Using Convolutional Neural Network
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AA Abbass, HL Hussein, WA Shukur, J Kaabi, R Tornai, Webology, 2022 Individual’s eye recognition is an important issue in applications such as security systems, credit card control and guilty identification. Using video images cause to destroy the limitation of fixed images and to be able to receive users’ image under any condition as well as doing the eye recognition. There are some challenges in these systems; changes of individual gestures, changes of light, face coverage, low quality of video images and changes of personal characteristics in each frame. There is a need for two phases in order to do the eye recognition using images; revelation and eye recognition which will use in the security systems to identify the persons. The mai

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Publication Date
Sat Mar 26 2022
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn: 2789-3219 )
Major Drivers for COVID-19 Vaccine Acceptance: A Scoping Review
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Objective: To review and identify the major drivers for COVID-19 vaccine acceptance. Methods: A scoping review of studies of COVID-19 vaccine perceptions and barriers to using the COVID-19 vaccines. Two search engines, including PubMed and Google Scholar, were purposefully searched. Results: Eight studies from different countries were reviewed to categorize factors influencing people's acceptance of COVID-19 according to the Health Belief Model (HBM). Perceived susceptibility, and severity of the disease (COVID-19), in addition to perceived benefits of COVID-19 vaccination and "cues to action", can enhance vaccination acceptance. In contrast, perceived barriers to the COVID-19 vaccine can increase people's hesitancy to be vaccinated

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Publication Date
Sun Sep 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Estimation for Carbonate Reservoir (Case Study/ South Iraqi Field)
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     The heterogeneity nature of carbonate reservoirs shows sever scattering of the data, therefore, one has to be cautious in using the permeability- porosity correlation for calculating permeability unless a good correlation coefficient is available. In addition, a permeability- porosity correlation technique is not enough by itself since simulation studies also require more accurate tools for reservoir description and diagnosis of flow and non-flow units. Evaluation of reservoir characterization  was conducted by this paper for Mishrif Formation in south Iraqi oil field (heterogeneous carbonate reservoir), namely the permeability-porosity correlation, the hydraulic units (HU’s) and global hydraulic elements (GHE

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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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Scopus
Publication Date
Sat Sep 01 2018
Journal Name
Journal Of Engineering
Buckling Loads and Effective Length Factor for Non-Prismatic Columns
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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Al-mansoor College
An Improvement to Face Detection Algorithm for Non-Frontal Faces
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