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Human Face Recognition Using GABOR Filter And Different Self Organizing Maps Neural Networks
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This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20 people with six images for each person and a measure of the time differences between the methods is given.

 

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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
Self-Reliance and Relation to Human Relations with Riyadh Teachers
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The research aims to identify the correlation between self-reliance and human relationship of kindergartens’ teachers. Total of (120) kindergarten teachers at Baghdad city. To collect needed data, two scales were administered to the research sample consisted of (25) items of each scale with (five) alternatives. The results revealed that teachers have good level of self-reliance and human relationship. There is a positive correlation between self-reliance and human relationship.

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Publication Date
Tue Jun 22 2021
Journal Name
Expert Systems
Hybrid intelligent technology for plant health using the fusion of evolutionary optimization and deep neural networks
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Publication Date
Wed Oct 17 2018
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
ESTIMATION OF MUNICIPAL SOLID WASTE GENERATION AND LANDFILL VOLUME GENERATION AND LANDFILL VOLUME USING ARTIFICIAL NEURAL NETWORKS
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Publication Date
Thu Jun 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Performance Improvement of Neural Network Based RLS Channel Estimators in MIMO-OFDM Systems
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The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

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Publication Date
Mon Dec 28 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Predicting the Sporting Achievement in the Pole Vault for Men Using Artificial Neural Networks
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The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t

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Publication Date
Wed May 03 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Enhancing smart home energy efficiency through accurate load prediction using deep convolutional neural networks
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The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

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Publication Date
Wed Jun 12 2024
Journal Name
مجلة كلية الكوت الجامعة للعلوم الانسانية
التنظيم القانوني للشرط المانع من التأجير (دراسة مقارنة)
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الشرط المانع من التأجير هو عبارة عن قيد اتفاقي يرد في عقد الإيجار مقتضاه تقييد حرية المستأجر من التصرف في حقه بالإيجار من الباطن أو التنازل عن الإيجار إلا بموافقة المؤجر.وهو بذلك قيد إرادي يرد على حرية المستأجر في التصرف بحقه الناشئ عن عقد الإيجار استثناءً من الأصل العام، وهذا الشرط أما ان يرد على منع المستأجر من التنازل عن الإيجار إلى الغير أو الإيجار إلى الغير من الباطن أو كلا الحالتين، وهو أما أن يظهر بصورة

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Publication Date
Sun Nov 26 2017
Journal Name
Journal Of Engineering
Compression Index and Compression Ratio Prediction by Artificial Neural Networks
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Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

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Publication Date
Tue Jul 01 2025
Journal Name
Mastering The Minds Of Machines
Recurrent Neural Networks and its Applications in Time Series Data
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Publication Date
Mon Mar 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
The economic feasibility of substituting different residues replaces part of the barley In the fattening of the Arabian lambs
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This experiment was carried out at the Grdarash field belongs to the Agricultural researches directorate/general Agriculture directorate-Erbil in September (2007)، 27 Arabic lambs aged (5-6 months) With average initial weight (39.178 Kg/lamb) were used. Lambs were divided in to (3) groups (9 lambs/group). Control group was fed on (85% barely، 10% bran and 5% straw)، and second and third groups were fed on various by-product in replacement with barely in loss and block shape respectively.

The total gain of three groups were (392708.32، 634826.52 & 445613.72 ID resp

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