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Content Based Image Clustering Technique Using Statistical Features and Genetic Algorithm
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Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering. The extraction of features gave a high distinguishability and helped GA reach the solution more accurately and faster.

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Delivery Route Management based on Dijkstra Algorithm
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For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers

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Publication Date
Sun Mar 04 2018
Journal Name
Baghdad Science Journal
Using Texture Analysis Image Processing Technique to Study the Effect of Microwave Plasma on the Living Tissue
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The present study is a hybrid method of studying the effect of plasma on the living tissue by using the image processing technique. This research explains the effect of microwave plasma on the DNA cell using the comet score application, texture analysis image processing and the effect of microwave plasma on the liver using texture analysis image processing. The study was applied on the mice cells. The exposure to the plasma is done by dividing the mice for four groups, each group includes four mice (control group, 20, 50, 90 second exposure to microwave plasma). The exposure to microwave plasma was done with voltage 175v and gas flow on 2 with room temperature; the statistical features are obtained from the comet score images and the textur

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
A Digital-Based Optimal AVR Design of Synchronous Generator Exciter Using LQR Technique
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In this paper a new structure for the AVR of the power system exciter is proposed and designed using digital-based LQR. With two weighting matrices R and Q,  this method produces an optimal regulator that is used to generate the feedback control law. These matrices are called state and control weighting matrices and are used to balance between the relative importance of the input and the states in the cost function that is being optimized. A sample power system composed of single machine connected to an infinite- bus bar (SMIB) with both a conventional and a proposed Digital AVR (DAVR) is simulated. Evaluation results show that the DAVR damps well the oscillations of the terminal voltage and presents a faster respo

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modified Grid Clustering Technique to Predict Heat Transfer Coefficient in a Duct of Arbitrary Cross Section Area
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A simple straightforward mathematical method has been developed to cluster grid nodes on a boundary segment of an arbitrary geometry that can be fitted by a relevant polynomial. The method of solution is accomplished in two steps. At the first step, the length of the boundary segment is evaluated by using the mean value theorem, then grids are clustered as desired, using relevant linear clustering functions. At the second step, as the coordinates cell nodes have been computed and the incremental distance between each two nodes has been evaluated, the original coordinate of each node is then computed utilizing the same fitted polynomial with the mean value theorem but reversibly.

The method is utilized to predict

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Genetic Algorithm Optimization Model for Central Marches Restoration Flows with Different Water Quality Scenarios
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A Genetic Algorithm optimization model is used in this study to find the optimum flow values of the Tigris river branches near Ammara city, which their water is to be used for central marshes restoration after mixing in Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim of this model is to enhance the water quality in Maissan River, hence provide acceptable water quality for marsh restoration. The model is applied for different water quality change scenarios ,i.e. , 10%,20% increase in EC,TDS and BOD. The model output are the optimum flow values for the three rivers while, the input data are monthly flows(1994-2011),monthly water requirements and water quality parameters (EC, TDS, BOD, DO and

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Publication Date
Sun Mar 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Employment of the genetic algorithm in some methods of estimating survival function with application
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Intended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted

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Publication Date
Fri May 17 2019
Journal Name
Lecture Notes In Networks And Systems
Features Selection for Intrusion Detection System Based on DNA Encoding
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Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

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Publication Date
Wed Apr 28 2021
Journal Name
2021 1st Babylon International Conference On Information Technology And Science (bicits)
Enhanced Twitter Community Detection using Node Content and Attributes
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Publication Date
Tue Jul 01 2025
Journal Name
International Journal Of Data And Network Science
Multi-objective of wind-driven optimization as feature selection and clustering to enhance text clustering
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Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t

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Publication Date
Wed Jan 01 2020
Journal Name
Studies In Big Data
COVID-19 Diagnostics from the Chest X-Ray Image Using Corner-Based Weber Local Descriptor
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Corona Virus Disease-2019 (COVID-19) is a novel virus belongs to the corona virus's family. It spreads very quickly and causes many deaths around the world. The early diagnosis of the disease can help in providing the proper therapy and saving the humans' life. However, it founded that the diagnosis of chest radiography can give an indicator of coronavirus. Thus, a Corner-based Weber Local Descriptor (CWLD) for COVID-19 diagnostics based on chest X-Ray image analysis is presented in this article. The histogram of Weber differential excitation and gradient orientation of the local regions surrounding points of interest are proposed to represent the patterns of the chest X-Ray image. Support Vector Machine (SVM) and Deep Belief Network (DBN)

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