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Human recognition by utilizing voice recognition and visual recognition
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Audio-visual detection and recognition system is thought to become the most promising methods for many applications includes surveillance, speech recognition, eavesdropping devices, intelligence operations, etc. In the recent field of human recognition, the majority of the research be- coming performed presently is focused on the reidentification of various body images taken by several cameras or its focuses on recognized audio-only. However, in some cases these traditional methods can- not be useful when used alone such as in indoor surveillance systems, that are installed close to the ceiling and capture images right from above in a downwards direction and in some cases people don't look straight the cameras or it cannot be added in some area such as W.C. or sleeping room. Thus, its commonly difficult to identify any movement or breakthrough process, on the other hand when need to pursue suspect when enter a building or party to identify his location and/or listen to his speech only and isolate it from other voices or noises, the other. Hence, the use of the hybrid combination technique is very effective. In this work, we proposed a multimodal human recognition approach that utilizes both the face and audio and is based upon a deep convolutional neural network (CNN). Mainly, to solve the challenge of not capturing part of the body, final results of recognizing via separate CNNs of VGG Face16 and ResNet50 are joined together depending on the score-level combination by Weighted Sum rule to enhance recognition performance. The results show that the proposed system success to recognise each person from his voice and/or his face captured. In addition, the system can separate the person voice and isolate it from noisy environment and determine the existence of desired person.

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
The Effect Of Optimizers On The Generalizability Additive Neural Attention For Customer Support Twitter Dataset In Chatbot Application
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When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

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Publication Date
Wed Jan 13 2021
Journal Name
Iraqi Journal Of Science
Smart Routing Protocol Algorithm Using Fuzzy Artificial Neural Network OSPF
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The OSPF cost is proportionally indicated the transmitting packet overhead through a certain interface and inversely proportional to the interface bandwidth. Thus, this cost may minimized by direct packet transmitting to the other side via various probable paths simultaneously. Logically, the minimum weight path is the optimum path. This paper propose a novel Fuzzy Artificial Neural Network to create Smart Routing Protocol Algorithm. Consequently, the Fuzzy Artificial Neural Network Overlap has been reduced from (0.883 ms) to (0.602 ms) at fuzzy membership 1.5 to 4.5 respectively. This indicated the transmission time is two-fold faster than the standard overlapping time (1.3 ms).

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Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
Diagnoses System of Varicose Disease
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The diagnoses system of varicose disease has a good level of performance due to the complexity and uniqueness in patterns of vein of the leg. In addition, the patterns of vein are internal of the body, and its features are hard to duplicate, this reason make this method not easy to fake, and thus make it contains of a good features for varicose disease diagnoses. The proposed system used more than one type of algorithms to produce diagnoses system of varicose disease with high accuracy, in addition, this multi-algorithm technique based on veins as a factor to recognize varicose infection. The obtained results indicate that the design of varicose diagnoses system by applying multi- algorithms (Naïve Bayes and Back-Propagation) produced n

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Publication Date
Thu May 04 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Design Feed Forward Neural Network to Determine Doses of the Decongestant for Cold Pills
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The aim of this paper is to design feed forward neural network to determine the effects of
cold pills and cascades from simulation the problem to system of first order initial value
problem. This problem is typical of the many models of the passage of medication throughout
the body. Designer model is an important part of the process by which dosage levels are set.
A critical factor is the need to keep the levels of medication high enough to be effective, but
not so high that they are dangerous.

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Publication Date
Mon Jul 01 2019
Journal Name
Journal Of Physics: Conference Series
Effect of Nickel Substitution On Structural and Electrical Properties of Hg<sub>0.5</sub>Pb<sub>0.5</sub>Ba<sub>2</sub>Ca<sub>2</sub>Cu<sub>3-y</sub>Ni<sub>y</sub>O<sub>8+δ</sub> Superconductor Composite
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Abstract<p>six specimens of the Hg<sub>0.5</sub>Pb<sub>0.5</sub>Ba<sub>2</sub>Ca<sub>2</sub>Cu<sub>3-y</sub> <italic>Ni<sub>y</sub> </italic>O<sub>8+δ</sub> (y=0.2,0.4,0.6,0.8,1.0) superconducting compound were prepared by solid state reaction method, with sintering temperature equal to 1123K for 24 hours. The electrical resistivity was examined by the four probe technique, It was found that all the specimens have metallic behavior and increasing the critical temperature with increasing nickel concentration. The optimum critical temperature T<sub>c</sub> was found equal </p> ... Show More
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Publication Date
Wed Oct 01 2008
Journal Name
Journal Of The Faculty Of Medicine Baghdad
INCIDENCE OF POST-OPERATIVE DEEP VEIN THROMBOSIS IN PATIENTS WITH LOWER LIMB OPEN FRACTURE
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Background: Venous thromboembolic (VTE) disease with i t ' s h i g h morbidity and mo r t a l i t y is currently one of the most serious postoperative complication, (DVT) can lead to
fatal pulmonary embolism (PE). or the development of post thrombotic syndrome.
Patients and methods: This is a prospective study which was carried on 85 patients had s i n g l e lower l i m b open fracture with no other major i n j u r i e s in other sites of body
(with the exception of superficial wounds or b r u i s e s ) .They were d i v i d e d i n t o groups according to age, gender, weight, type of fracture, methods of immobilization, duration of
h o s p i t a l i z a t i o n , duration of operation. All the patients includin

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Publication Date
Wed Sep 08 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Obstacles facing the application of electronic banking An exploratory: study of the opinions of a sample of bank employees operating in the city of Nasiriyah
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Electronic banking plays a prominent role in providing the best banking services and upgrading the banking sector for the better, so this study aimed to shed light on the most prominent obstacles that prevent the application of electronic banking in banks operating in the city of Nasiriyah, and in order to achieve this goal the researcher used the descriptive analytical approach And through a questionnaire form that was distributed to a group of employees, numbering (60) employees in the upper, middle and operational departments in a number of branches of private banks operating in the city of Nasiriyah, namely (the Iraqi Trade Bank, the Gulf Commercial Bank, the Bank of Baghdad, the Union Bank of Iraq), which represented The stu

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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Chromosomal Aberrations in Peripheral Blood Lymphocytes in Brick Kilns Workers
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This study was conducted on the workers of the brick kilns at Al- Nahrawan area south-east of Baghdad city to investigate the effect of the pollutant emissions (fumes and gases) released from the burned fuel in this kiln. Blood samples were taken from group individuals of workers at this brick kilns and non-working individuals as a control. The influence of these emissions on the workers' health was measured by examining certain chromosomal aberrations among the workers. These aberrations were a formation of: chromosomal rings, dicentric chromosomes, breaks arm and acentric fragments. It has been observed that most of these aberrations were found within workers of age 40 years and above, represented by formations of averages 1.50 and 1.0

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Publication Date
Thu Jul 13 2023
Journal Name
International Journal Of Research In Social Sciences &amp; Humanities
Subject Review: Blogs as Learning Tools in EFL Classrooms
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Blogs have emerged as a powerful technology tool for English as a Foreign Language (EFL) classrooms. This literature review aims to provide an overview of the use of blogs as learning tools in EFL classrooms. The study examines the benefits and challenges of using blogs for language learning and the different types of blogs that can be used for language learning. It provides suggestions for teachers interested in using blogs as learning tools in their EFL classrooms. The findings suggest that blogs are a valuable and effective tool for language learning, particularly in promoting collaboration, communication, and motivation.

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Review of Smishing Detection Via Machine Learning
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     Smishing is a cybercriminal attack targeting mobile Short Message Service (SMS) devices that contains a malicious link, phone number, or email. The attacker intends to use this message to steal the victim's sensitive information, such as passwords, bank account details, and credit cards. One method of combating smishing is to raise awareness and educate users about the various tactics used by SMS phishers. But even so, this method has been criticized for becoming inefficient because smishing tactics are continually evolving. A more promising anti-smishing method is to use machine learning. This paper introduces a number of machine learning algorithms that can be used for detecting smishing. Furthermore, the differences and simil

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