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Plain, Edge, and Texture Detection Based on Orthogonal Moment
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Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOMs). Therefore, finding a fast PET classification method that accurately classify image pattern is crucial. To this end, this paper proposes a new scheme for accurate and fast image pattern classification using an efficient DOM. To reduce the computational complexity of feature extraction, an election mechanism is proposed to reduce the number of processed block patterns. In addition, support vector machine is used to classify the extracted features for different block patterns. The proposed scheme is evaluated by comparing the accuracy of the proposed method with the accuracy achieved by state-of-the-art methods. In addition, we compare the performance of the proposed method based on different DOMs to get the robust one. The results show that the proposed method achieves the highest classification accuracy compared with the existing methods in all the scenarios considered.

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Publication Date
Thu Oct 21 2021
Journal Name
The 3rd Al-noor International Conference Of Science And Technology 2021 Muscat-oman
Gama Platform Survey for Agent-Based Modelling
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The agent-based modeling is currently utilized extensively to analyze complex systems. It supported such growth, because it was able to convey distinct levels of interaction in a complex detailed environment. Meanwhile, agent-based models incline to be progressively complex. Thus, powerful modeling and simulation techniques are needed to address this rise in complexity. In recent years, a number of platforms for developing agent-based models have been developed. Actually, in most of the agents, often discrete representation of the environment, and one level of interaction are presented, where two or three are regarded hardly in various agent-based models. The key issue is that modellers work in these areas is not assisted by simulation plat

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Publication Date
Tue Jun 30 2015
Journal Name
International Journal Of Computer Techniques
Multifractal-Based Features for Medical Images Classification
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This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

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Publication Date
Fri Jan 01 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Genetic--Based Face Retrieval Using Statistical Features
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Publication Date
Sat Dec 03 2022
Journal Name
Tikrit Journal Of Pure Science
A Pixel Based Method for Image Compression
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The basic solution to overcome difficult issues related to huge size of digital images is to recruited image compression techniques to reduce images size for efficient storage and fast transmission. In this paper, a new scheme of pixel base technique is proposed for grayscale image compression that implicitly utilize hybrid techniques of spatial modelling base technique of minimum residual along with transformed technique of Discrete Wavelet Transform (DWT) that also impels mixed between lossless and lossy techniques to ensure highly performance in terms of compression ratio and quality. The proposed technique has been applied on a set of standard test images and the results obtained are significantly encourage compared with Joint P

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Publication Date
Thu Jun 04 2020
Journal Name
Journal Of Discrete Mathematical Sciences And Cryptography
User authentication system based specified brain waves
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A security system can be defined as a method of providing a form of protection to any type of data. A sequential process must be performed in most of the security systems in order to achieve good protection. Authentication can be defined as a part of such sequential processes, which is utilized in order to verify the user permission to entree and utilize the system. There are several kinds of methods utilized, including knowledge, and biometric features. The electroencephalograph (EEG) signal is one of the most widely signal used in the bioinformatics field. EEG has five major wave patterns, which are Delta, Theta, Alpha, Beta and Gamma. Every wave has five features which are amplitude, wavelength, period, speed and frequency. The linear

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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Reservoir permeability prediction based artificial intelligence techniques
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   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Reinforcement Learning-Based Television White Space Database
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Television white spaces (TVWSs) refer to the unused part of the spectrum under the very high frequency (VHF) and ultra-high frequency (UHF) bands. TVWS are frequencies under licenced primary users (PUs) that are not being used and are available for secondary users (SUs). There are several ways of implementing TVWS in communications, one of which is the use of TVWS database (TVWSDB). The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. With this in mind, the authors present a reinforcement learning-ba

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Publication Date
Fri Jun 18 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Quadtree partitioning scheme of color image based
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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of a Training Program for Children with Autism and their Mothers Based on the Picture Exchange Commination System to Confront Some of Basic Disorders for these Children
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Abstract

The current research aims to examine the effectiveness of a training program for children with autism and their mothers based on the Picture Exchange Communication System to confront some basic disorders in a sample of children with autism. The study sample was (16) children with autism and their mothers in the different centers in Taif city and Tabuk city. The researcher used the quasi-experimental approach, in which two groups were employed: an experimental group and a control group. Children aged ranged from (6-9) years old. In addition, it was used the following tools: a list of estimation of basic disorders for a child with autism between (6-9) years, and a training program for children with autism

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Publication Date
Thu Apr 07 2016
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
DETECTION OF MICROBIAL CONTAMINATION IN SOME TYPES OF FLOUR THAT AVAILABLE IN LOCAL MARKETS USING BACTRAC DEVICE 3400: DETECTION OF MICROBIAL CONTAMINATION IN SOME TYPES OF FLOUR THAT AVAILABLE IN LOCAL MARKETS USING BACTRAC DEVICE 3400
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A microbial study conducted for a number of flour samples (30 samples) Uses in the bakery ovens in various areas of the city of Baghdad, by used the conventional methods used in laboratories in microbial tests and compared with the modern techniqueby usedof BacTrac Device 3400 equipped from SY-LAB Impedance analysersAustrian company.The results of two ways showed (The conventional way and BacTrac Device test)that the total counts of aerobic bacteria, coliform bacteria, StaphylococcusSpp. bacteria, Bacillus cereus bacteria and yeasts and molds,Most of them were within the permissible borders in the Iraqi standard for grain and its products With free samples from SalmonellaSpp. bacteria, and that the screening by BacTrac device are shorten

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