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A hybrid approach based on multiple Eigenvalues selection (MES) for the automated grading of a brain tumor using MRI
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Publication Date
Mon Jan 01 2024
Journal Name
5th International Conference On Biomedical And Health Sciences
Exploiting Vpusm 8 Lytic Phage for The Bio- Control of V. Cholerae: A Novel Approach Against Cholera in The Era of Antibiotic Resistance
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Objective: The purpose of this study was to assess the effectiveness of Vibriophage Universiti Sains Malaysia 8 (VPUSM 8), a bacteriophage that destroys bacteria, in managing the proliferation of Vibrio cholerae, specifically the El Tor serotype, as an alternate therapeutic strategy. Methods: The study entailed subjecting water samples from Kelantan, Malaysia, to reproduce the natural circumstances that promote the growth of V. cholerae. Subsequently, the samples were contaminated with the V. cholerae O1 El Tor Inaba strain and treated using VPUSM 8. The study employed a controlled experimental design, wherein the samples were divided into three groups, each experiencing different treatment methods. Quantifying the number of colony-

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Publication Date
Sat Oct 01 2016
Journal Name
Gjra - Global Journal For Research Analysis
Inclination of the Lumbosacral angle in normal individuals: An MRI study
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Inclination Of The Lumbosacral Angle In Normal Individuals: An Mri Study,GJRA - Global Journal For Research Analysis(GJRA) GJRA is a double reviewed monthly print journal that accepts research works. 36572+ Manuscript submission, 9855+ Research Paper Published, 100+ Articles from over 100 Countries

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Publication Date
Mon Dec 31 2018
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Dyslipidemia and CA15-3 serum level in Iraqi Women with Breast Tumor: A Comparative Study
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Publication Date
Sat Feb 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Revealing the potentials of 3D modelling techniques; a comparison study towards data fusion from hybrid sensors
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Abstract<p>The vast advantages of 3D modelling industry have urged competitors to improve capturing techniques and processing pipelines towards minimizing labour requirements, saving time and reducing project risk. When it comes to digital 3D documentary and conserving projects, laser scanning and photogrammetry are compared to choose between the two. Since both techniques have pros and cons, this paper approaches the potential issues of individual techniques in terms of time, budget, accuracy, density, methodology and ease to use. Terrestrial laser scanner and close-range photogrammetry are tested to document a unique invaluable artefact (Lady of Hatra) located in Iraq for future data fusion sc</p> ... Show More
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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
MR Brain Image Segmentation Using Spatial Fuzzy C- Means Clustering Algorithm
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conventional FCM algorithm does not fully utilize the spatial information in the image. In this research, we use a FCM algorithm that incorporates spatial information into the membership function for clustering. The spatial function is the summation of the membership functions in the neighborhood of each pixel under consideration. The advantages of the method are that it is less
sensitive to noise than other techniques, and it yields regions more homogeneous than those of other methods. This technique is a powerful method for noisy image segmentation. 

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Publication Date
Sat Oct 01 2016
Journal Name
2016 6th International Conference On Information Communication And Management (icicm)
Enhancing case-based reasoning retrieval using classification based on associations
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Publication Date
Fri May 31 2019
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Algorithms based Path Planning for Mobile Robots
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In general, path-planning problem is one of most important task in the field of robotics. This paper describes the path-planning problem of mobile robot based on various metaheuristic algorithms. The suitable collision free path of a robot must satisfies certain optimization criteria such as feasibility, minimum path length, safety and smoothness and so on. In this research, various three approaches namely, PSO, Firefly and proposed hybrid FFCPSO are applied in static, known environment to solve the global path-planning problem in three cases. The first case used single mobile robot, the second case used three independent mobile robots and the third case applied three follow up mobile robot.  Simulation results, whi

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Publication Date
Sun Jun 01 2025
Journal Name
Chemical Engineering And Processing - Process Intensification
Wastewater treatment through a hybrid electrocoagulation and electro-Fenton process with a porous graphite air-diffusion cathode
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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
A Nonlinear MIMO-PID Neural Controller Design for Vehicle Lateral Dynamics model based on Modified Elman Neural Network
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This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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