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Hybrid Methodology for Image Segmentation Based on Active Contour Module and Alpha-Shape Theory
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The concept of the active contour model has been extensively utilized in the segmentation and analysis of images. This technology has been effectively employed in identifying the contours in object recognition, computer graphics and vision, biomedical processing of images that is normal images or medical images such as Magnetic Resonance Images (MRI), X-rays, plus Ultrasound imaging. Three colleagues, Kass, Witkin and Terzopoulos developed this energy, lessening “Active Contour Models” (equally identified as Snake) back in 1987. Being curved in nature, snakes are characterized in an image field and are capable of being set in motion by external and internal forces within image data and the curve itself in that order. The present study proposes the use of a hybrid image segmentation technique to acquire precise segmentation outcomes, while engaging “Alpha Shape (α-Shape)” in supposition to derive the original contour, followed by a refining process through engaging a conventional active contour model. Empirical results show high potential in the suggested computational method. Trials indicate that the primary contour is capable of being precisely set next to the objective contour and effectively have these objective contours extracted, devoid of any contour instigation. Some of the benefits associated with the novel hybrid contour include minimized cost of computation, enhanced anti-jamming capability, as well as enlarged utilization array of snake model.

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
Thu Sep 01 2022
Journal Name
Journal Of Engineering
Design and Implementation of Active Noise Cancellation for Car Cabin on Sulaimania Roads Using Arduino Embedded System
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Car drivers hear many kinds of noise inside their vehicles' cabins, and the most annoying ones are the noise generated by tires, engines, and outside winds. Noise affects the comfort of the passengers inside the cabin, and it’s sad to say that modern cars are noisier in many kinds of noise signals due to using a lot of plastic materials in new budget cars. For expensive and luxury cars, the problem is solved by using better sound insulation materials, but for the budget ones, the approach used here is effective. It is called Active Noise Cancellation and can be done using analog or digital electronics. An operational amplifier and filters are used for the analog one, and in the digital one, signal processor chips are used. In engineeri

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Publication Date
Sun Sep 27 2026
Journal Name
Journal Of Physical Education
Analytical Study Of Teaching Efficiency According To Herman Module For Baghdad Governorate Physical Educators
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The importance of the current research lies in the importance of teaching competencies and the ability of the teacher to deal and success in his educational career. The research aimed to identify the degree of teaching competencies according to Hermann model of physical education teachers in Baghdad governorate. The descriptive method using the survey method was used on a randomly selected sample of 462 teachers and 314 school principals. After the completion of the survey, the Hermann scale forms were distributed to the teachers. The forms of the teaching competency scale were distributed to their school principals as the direct supervisors of the teachers' evaluation. After completing the survey, the results of each scale were classified

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Publication Date
Tue Apr 01 2003
Journal Name
Abhath Al- Yarmouk [basic Sciences And Engineering]
Methodology for selecting Nonprestressed Steel in Post- Tensioning Beams
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Publication Date
Sun Jan 01 2017
Journal Name
البحوث التربوية والنفسية
The effectiveness of an educational design based on Herman’s total brain theory on the achievement of chemistry among fifth-grade female students
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Publication Date
Mon Dec 01 2014
Journal Name
Ain Shams University
New Studies for Topological Generalizations and Uncertainty in Graph Theory
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Topology and its applications occupy the interest of many researching centers in the advanced world. From this point of view and because the near open sets play a very important role in general topology and they are now the research topics of many topologists worldwide and its sets doesn’t enter in fibrewise topology yet. Therefore, we use some of the near open sets to be model for introduce results and new spaces in fibrewise topological spaces. Also, there is a very important role of closure operators in constructing a topological spaces, so we introduce a new closure operators on the power set of vertices on graphs and conclusion theorems and new spaces from it. Furthermore, we discuss the relationships of connectedness between some ty

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Image data compression by using multiwavelete for color image
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There are many images you need to large Khoznah space With the continued evolution of storage technology for computers, there is a need nailed required to reduce Alkhoznip space for pictures and image compression in a good way, the conversion method Alamueja

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Publication Date
Fri Apr 30 2021
Journal Name
Al-kindy College Medical Journal
Immunological aspects of Alpha 1 Antitrypsin in COVID-19 infection among the Populace and Pregnant Women: Alpha 1 Antitrypsin and COVID-19
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Since the COVID-19 pandemic alarm was made by the severe acute respiratory syndrome (SARS)-coronavirus (CoV) 2, several institutions and agencies have pursued to clarify the viral virulence and infectivity. The fast propagation of this virus leads to an unprecedented rise in the number of cases worldwide. COVID-19 virus is exceptionally contagious that spreads through droplets, respiratory secretions, and direct contact. The enveloped, single-stranded RNA virus has a specific envelop region called (S) region encoding (S protein) that specifically binds to the host cell receptor. Viral infection requires receptors' participation on the host cell membrane's surface, a  key- step for the viral invasion of susceptible cells.

Rec

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Publication Date
Wed Jan 02 2019
Journal Name
Journal Of Educational And Psychological Researches
An Instructional Design According to the Active Learning Model and Its Effect on Students' Achievement in Chemistry for Fifth Intermediate Stage
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The objective of the research is to identify the effect of an instructional design according to the active learning modelsالباحثين in the achievement of the students of the fifth grade, the instructional design was constructed according to the active learning models for the design of education. The research experience was applied for a full academic year (the first & the second term of 2017-2018). The sample consisted of 58 students, 28 students for the experimental group and 30 students for the control group. The experimental design was adopted with partial and post-test, the final achievement test consisted of (50) objectives and essays items on two terms, the validity of the test was verified by the adoption of the Kudoric

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Publication Date
Wed Jan 01 2025
Journal Name
Transactions Of The Chinese Society Of Agricultural Machinery
Evaluating Tillage Quality under Varying Speed and Depth Using YOLOv7-Based Image Analysis
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Soil tillage is a critical agricultural practice that creates favorable conditions for seedbed preparation and plant growth. This study presents an innovative application of artificial intelligence (AI) in agriculture by employing the YOLOv7 algorithm to classify and assess post-tillage soil surface conditions, a domain underexplored in current research. The integration of mechanical operation parameters with AI-based image classification enables optimization of tillage quality and mitigation of soil compaction, highlighting the novelty of this approach. The study aims to improve the efficiency of moldboard plow operations by examining the effects of tillage speed and depth on soil clod distribution, fuel consumption, and power requ

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