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FACE IDENTIFICATION USING BACK-PROPAGATION ADAPTIVE MULTIWAVENET
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Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a recognition rate of 97.75% in the presence of facial expression, lighting and pose variations. Results are compared with its wavelet-based counterpart where it obtained a recognition rate of 10.4%. The proposed multiwavenet demonstrated very good recognition rate in the presence of variations in facial expression, lighting and pose and outperformed its wavelet-based counterpart.

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Publication Date
Mon Apr 01 2013
Journal Name
International Journal Of Electrical, Electronics And Telecommunication Engineering
Performance Analysis of xPON Network for Different Queuing Models
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Passive optical network (PON) is a point to multipoint, bidirectional, high rate optical network for data communication. Different standards of PONs are being implemented, first of all PON was ATM PON (APON) which evolved in Broadband PON (BPON). The two major types are Ethernet PON (EPON) and Gigabit passive optical network (GPON). PON with these different standards is called xPON. To have an efficient performance for the last two standards of PON, some important issues will considered. In our work we will integrate a network with different queuing models such M/M/1 and M/M/m model. After analyzing IPACT as a DBA scheme for this integrated network, we modulate cycle time, traffic load, throughput, utilization and overall delay

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Publication Date
Fri Feb 17 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Deploying Facial Segmentation Landmarks for Deepfake Detection
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Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

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Publication Date
Thu Jun 20 2024
Journal Name
Fizjoterapia Polska
Development Artificial Neural Network (ANN) computing model to analyses men's 100¬meter sprint performance trends
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Coaches and analysts face a significant challenge of inaccurate estimation when analyzing Men's 100 Meter Sprint Performance, particularly when there is limited data available. This necessitates the use of modern technologies to address the problem of inaccurate estimation. Unfortunately, current methods used to estimate Men's 100 Meter Sprint Performance indexes in Iraq are ineffective, highlighting the need to adopt new and advanced technologies that are fast, accurate, and flexible. Therefore, the objective of this study was to utilize an advanced method known as artificial neural networks to estimate four key indexes: Accelerate First of 10 meters, Speed Rate, Time First of 10 meters, and Reaction Time. The application of artifi

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Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science & Technology
The Effect of Classification Methods on Facial Emotion Recognition ‎Accuracy
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The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

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Publication Date
Wed May 04 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature
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The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
The Mutual Interaction effects between Array Antenna Parameters and Receiving Signals Bandwidth
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The presence of a single complex adaptive weight in each element channel of an adaptive array antenna is sufficient for processing of narrowband signals. The ability of an adaptive array antenna to null interference deteriorates rapidly as the interference bandwidth increases. The performance of narrowband adaptive array antenna with LMCV Beamforming algorithm is examined. The interaction effects between received signal angle of arrival and array parameters like the interelement spacing and the number of array element and the received signal bandwidth were studied. The output Signal to Interference plus Noise Ratio (SINR) and Interference to Noise Ratio (INR) are used as performance parameters for evaluation of these effects. It is found

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Publication Date
Sun Feb 01 2015
Journal Name
Journal Of Engineering
Planning of Distribution Networks in Baghdad City
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Planning of electrical distribution networks is considered of highest priority at the present time in Iraq, due to the huge increase in electrical demand and expansions imposed on distribution networks as a result of the great and rapid urban development.

Distribution system planning simulates and studies the behavior of electrical distribution networks under different operating conditions. The study provide understanding of the existing system and to prepare a short term development plan or a long term plan used to guide system expansion and future investments needed for improved network performance.

The objective of this research is the planning of Al_Bayaa 11 kV distribution network in Baghdad city bas

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
Cross Dipole Antennas Solution for Angle of Arrival Estimation
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The Multiple Signal Classification (MUSIC) algorithm is the most popular algorithm to estimate the Angle of Arrival (AOA) of the received signals. The analysis of this algorithm (MUSIC) with typical array antenna element ( ) shows that there are two false direction indication in the plan
aligned with the axis of the array. In this paper a suggested modification on array system is proposed by using two perpendiculars crossed dipole array antenna in spite of one array antenna. The suggested modification does not affect the AOA estimation algorithm. The simulation and results shows that the proposed solution overcomes the MUSIC problem without any effect on the performance of the system.

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Publication Date
Tue Jul 11 2023
Journal Name
Journal Of Educational And Psychological Researches
A Sociocultural Perspective on Iraqi EFL Learners Reading Comprehension Development
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 Improving speaking skills of Iraqi EFL students was the main purpose of the current research. Thirty EFL students were selected as the research participants for achieving this aim. All students completed the pretest and then spent the next 25 weeks meeting for 90 minutes each to present their nine lectures, answer difficult questions, and get feedback on their use of language in context. Progressive-tests, posttests and delayed post-tests followed every three courses. The researcher utilized SPSS 22 to anal Analyze the data descriptively and inferentially after doing an ANOVA on repeated measurements. It has been shown that using the ideas of sociocultural theory in the classroom has an important and positive impact on students of

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Publication Date
Thu Jan 05 2023
Journal Name
International Journal Of Building Pathology And Adaptation
Adaptation re-use of traditional cafés in Erbil, Iraq
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Purpose

This paper aims to shed light on adaptive reuse in traditional architecture (TA) in Erbil, Iraq.

Design/methodology/approach

An inductive approach and qualitative method were used in this study. The inductive research approach was used because there was no clear image of adaptive reuse in traditional cafés (TCs) in Erbil. Besides, there are no studies of TCs in Erbil particularly. Thus, there is a lack of knowledge about what adaptations took place in TCs in Erbil. The qualitative method extracted themes and issues from case studies of four TCs in Erbil citadel'

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