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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
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Reconstruction of Three-Dimensional Object from Two-Dimensional Images by Utilizing Distance Regularized Level Algorithm and Mesh Object Generation
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Three-dimensional (3D) reconstruction from images is a most beneficial method of object regeneration by using a photo-realistic way that can be used in many fields. For industrial fields, it can be used to visualize the cracks within alloys or walls. In medical fields, it has been used as 3D scanner to reconstruct some human organs such as internal nose for plastic surgery or to reconstruct ear canal for fabricating a hearing aid device, and others. These applications need high accuracy details and measurement that represent the main issue which should be taken in consideration, also the other issues are cost, movability, and ease of use which should be taken into consideration. This work has presented an approach for design and construc

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Publication Date
Sun Jul 01 2012
Journal Name
2012 International Symposium On Innovations In Intelligent Systems And Applications
Edge detection for fast block-matching motion estimation to enhance Mean Predictive Block Matching algorithm
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Publication Date
Wed Jun 29 2022
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
The Use Of Genetic Algorithm In Estimating The Parameter Of Finite Mixture Of Linear Regression
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The estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To

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Publication Date
Sun Aug 24 2014
Journal Name
Wireless Personal Communications
Multi-layer Genetic Algorithm for Maximum Disjoint Reliable Set Covers Problem in Wireless Sensor Networks
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Publication Date
Mon Jan 01 2018
Journal Name
Internet And Distributed Computing Systems
A Proposed Adaptive Rate Algorithm to Administrate the Video Buffer Occupancy for Smooth Video Streaming
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Publication Date
Sun Jan 01 2017
Journal Name
International Journal Of Advanced Computer Science And Applications
Fast Hybrid String Matching Algorithm based on the Quick-Skip and Tuned Boyer-Moore Algorithms
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Publication Date
Thu Dec 05 2019
Journal Name
Advances In Intelligent Systems And Computing
An Enhanced Evolutionary Algorithm for Detecting Complexes in Protein Interaction Networks with Heuristic Biological Operator
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Publication Date
Sun Jun 05 2022
Journal Name
Network
A Computationally Efficient Gradient Algorithm for Downlink Training Sequence Optimization in FDD Massive MIMO Systems
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Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date ve

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Publication Date
Sat Aug 25 2012
Journal Name
Wireless Personal Communications
Multi-Objective Evolutionary Algorithm Based on Decomposition for Energy Efficient Coverage in Wireless Sensor Networks
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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
Common Fixed Point of a Finite-step Iteration Algorithm Under Total Asymptotically Quasi-nonexpansive Maps
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      Throughout this paper, a generic iteration algorithm for a finite family of total asymptotically quasi-nonexpansive maps in uniformly convex Banach space is suggested. As well as weak / strong convergence theorems of this algorithm to a common fixed point are established. Finally, illustrative numerical example by using Matlab is presented.

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