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Detection and Diagnosis of Induction Motor Faults by Intelligent Techniques
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This paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and  two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosis system is developed to determine the status of the motor without the need for an expert. This system is based on artificial neural network (ANN) and it is characterized by speed and accuracy and the ability to detect more than one fault at the same time.
 

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Immunological and Molecular Diagnosis of Cytomegalovirus Infection between Aborted & Pregnant Women in Babylon City
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Human cytomegalovirus (CMV) is the globally highly prevalent herpesvirus worldwide. CMV infects populations of all ages according to the Center for Disease Control and Prevention (CDC) and World Health Organization (WHO). CMV infections remain the most common viral complication potentially multiple in humans and are a major cause of congenital normality in women, which is why they are critical for diagnosis in several times when it happens during pregnancy. Pregnant women with CMV infection can be in charge of abortion or congenital expandaedby. This study involves the collection a total of (90) samples taken from each aborted and pregnant woman (70 with abortion cases and 20 of pregnant without history of abortion as control subjects) r

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Publication Date
Fri May 31 2019
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Algorithms based Path Planning for Mobile Robots
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In general, path-planning problem is one of most important task in the field of robotics. This paper describes the path-planning problem of mobile robot based on various metaheuristic algorithms. The suitable collision free path of a robot must satisfies certain optimization criteria such as feasibility, minimum path length, safety and smoothness and so on. In this research, various three approaches namely, PSO, Firefly and proposed hybrid FFCPSO are applied in static, known environment to solve the global path-planning problem in three cases. The first case used single mobile robot, the second case used three independent mobile robots and the third case applied three follow up mobile robot.  Simulation results, whi

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Intelligent Congestion Control of 5G Traffic in SDN using Dual-Spike Neural Network
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Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification. Different

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

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Publication Date
Tue Aug 01 2017
Journal Name
Iosr Journal Of Dental And Medical Sciences (iosr-jdms)
Utilizing Home Pregnancy Test Kits for Diagnosis of Leaking Liquor
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Before the start of delivery, any membranes rupture could be named as a premature rupture of membranes (PROM), which may need special obstetrical interactions to minimize perinatal complications, it is important topromptly diagnose PROM, the method used should be accurate, cheap, simple, and widely available. This was exactly the idea behind this study to use an ordinary pregnancy test kit aiming to confirm presence of PROM.Over a 6 months’ period, 60 pregnant women with a history of leaking liquor and a positive speculum examination for amniotic fluid pooling were collected prospectively and compared with other 60 women (control group) with uneventful pregnancy. Majority of patients with positive leaking liquor signs and symptoms had a p

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Publication Date
Mon Aug 01 2011
Journal Name
International Journal Of Research And Reviews In Computer Science
Detection of the photon number splitting attack by using decoy states quantum key distribution system
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The goal of this work is to check the presence of PNS (photon number splitting) attack in quantum cryptography system based on BB84 protocol, and to get a maximum secure key length as possible. This was achieved by randomly interleaving decoy states with mean photon numbers of 5.38, 1.588 and 0.48 between the signal states with mean photon numbers of 2.69, 0.794 and 0.24. The average length for a secure key obtained from our system discarding the cases with Eavesdropping was equal to 125 with 20 % decoy states and 82 with 50% decoy states for mean photon number of 0.794 for signal states and 1.588 for decoy states.

Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Tue May 01 2012
Journal Name
Iraqi Journal Of Physics
Early detection of breast cancer mass lesions by mammogram segmentation images based on texture features
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Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

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Publication Date
Sat Jul 19 2025
Journal Name
Annals Of Applied Sport Science
A Comparative Study of the Average Motor Response Time for the Arms and Legs of Handball, Basketball, and Volleyball Players Aged 14-16 Years
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Background. The motor response is a fundamental ability that is evident during any physical or motor activity. However, the need for this ability varies from one sport to another and depends on the specific skills required in each sport. Objectives. This study aims to compare the average motor reaction times of the arm and leg among handball, basketball, and volleyball players aged 14 to 16 years. Methods. The sample included 30 players aged 14-16 years from the sports talent care center, evenly distributed on handball, basketball, and volleyball. Standardized tests were used to measure the speed of motor response, including the Batak Micro test for hands, which records the number of responses to light stimuli in 30 seconds, and the Saqer t

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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Natural Gas Science And Engineering
Experimental determination of hydrate phase equilibrium for different gas mixtures containing methane, carbon dioxide and nitrogen with motor current measurements
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Hydrate dissociation equilibrium conditions for carbon dioxide + methane with water, nitrogen + methane with water and carbon dioxide + nitrogen with water were measured using cryogenic sapphire cell. Measurements were performed in the temperature range of 275.75 K–293.95 K and for pressures ranging from 5 MPa to 25 MPa. The resulting data indicate that as the carbon dioxide concentration is increased in the gas mixture, the gas hydrate equilibrium temperature increases. In contrast, by increasing the nitrogen concentration in the gas mixtures containing methane or carbon dioxide decreased the gas hydrate equilibrium temperatures. Furthermore, the cage occupancies for the carbon dioxide + methane system were evaluated using the Van der Wa

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