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Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D CNNs have shown improved accuracy in the classification of ASD compared to traditional machine learning algorithms, on all these datasets with higher accuracy of 99.45%, 98.66%, and 90% for Autistic Spectrum Disorder Screening in Data for Adults, Children, and Adolescents respectively as they are better suited for the analysis of time series data commonly used in the diagnosis of this disorder

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Publication Date
Thu Dec 21 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Recovering Time-Dependent Coefficients in a Two-Dimensional Parabolic Equation Using Nonlocal Overspecified Conditions via ADE Finite Difference Schemes
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Publication Date
Fri Jan 01 2021
Journal Name
Review Of International Geographical Education
Evaluating the performance of project management using network diagrams methods: A case study in the Ramadi Municipality
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This study came for the reason that some project administrations still do not follow the appropriate scientific methods that enable them to perform their work in a manner that achieves the goals for which those projects arise, in addition to exceeding the planned times and costs, so this study aims to apply the methods of network diagrams in Planning, scheduling and monitoring the project of constructing an Alzeuot intersection bridge in the city of Ramadi, as the research sample, being one of the strategic projects that are being implemented in the city of Ramadi, as well as being one of the projects that faced during its implementation Several of problems, the project problem was studied according to scientific methods through the applica

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Publication Date
Mon Apr 26 2021
Journal Name
Open Access Macedonian Journal Of Medical Sciences
Three-dimensional printing applications in the neurosurgery: A pilot study
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BACKGROUND: Three-dimensional (3D) printing is an evolving technology that has been used recently in a wide spectrum of applications. AIM: The objective is to evaluate the application of 3D printing in various neurosurgical practice. PATIENTS AND METHODS: This pilot study was conducted in the neurosurgical hospital in Baghdad/Iraq between July 2018 and July 2019. An X, Y, and Z printer was used. The working team included neurosurgeons, biomedical engineers, and bio-technicians. The procedure starts with obtaining Magnetic resonance imaging (MRI) or computed tomography (CT) scan in particular protocols. The MRI, and CT or angiography images were imported into a 3D programmer for DICOM images called 3D slice where these files con

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Publication Date
Wed Jun 27 2018
Journal Name
Iraqi Journal Of Science
Accurate Three Dimensional Coordinates Measurements Using Differential GPS Real Time Kinematic Mode
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The accurate 3-D coordinate's measurements of the global positioning systems are essential in many fields and applications. The GPS has numerous applications such as: Frequency Counters, Geographic Information Systems, Intelligent Vehicle Highway Systems, Car Navigation Systems, Emergency Systems, Aviations, Astronomical Pointing Control, and Atmospheric Sounding using GPS signals, tracking of wild animals, GPS Aid for the Blind, Recorded Position Information, Airborne Gravimetry and other uses. In this paper, the RTK DGPS mode has been used to create precise 3-D coordinates values for four rover stations in Baghdad university camp. The HiPer-II Receiver of global positioning system was used to navigate the coordinate value. The results wil

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Publication Date
Thu Jun 27 2024
Journal Name
Journal Of Image And Graphics
ALL-FABNET: Acute Lymphocytic Leukemia Segmentation Using a Flipping Attention Block Decoder-Encoder Network
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Melanoma, a highly malignant form of skin cancer, affects individuals of all genders and is associated with high mortality rates, especially in advanced stages. The use of tele-dermatology has emerged as a proficient diagnostic approach for skin lesions and is particularly beneficial in rural areas with limited access to dermatologists. However, accurately, and efficiently segmenting melanoma remains a challenging task due to the significant diversity observed in the morphology, pigmentation, and dimensions of cutaneous nevi. To address this challenge, we propose a novel approach called DenseUNet-169 with a dilated convolution encoder-decoder for automatic segmentation of RGB dermascopic images. By incorporating dilated convolution,

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Eye Detection using Helmholtz Principle
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            Eye Detection is used in many applications like pattern recognition, biometric, surveillance system and many other systems. In this paper, a new method is presented to detect and extract the overall shape of one eye from image depending on two principles Helmholtz & Gestalt. According to the principle of perception by Helmholz, any observed geometric shape is perceptually "meaningful" if its repetition number is very small in image with random distribution. To achieve this goal, Gestalt Principle states that humans see things either through grouping its similar elements or recognize patterns. In general, according to Gestalt Principle, humans see things through genera

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Publication Date
Wed Jun 12 2013
Journal Name
International Journal Of Computer Applications
Design and Implementation of a Practical FTTH Network
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Fiber-to-the-Home (FTTH) has long been recognized as a technology that provides future proof bandwidth [1], but has generally been too expensive to implement on a wide scale. However, reductions in the cost of electro-optic components and improvements in the handling of fiber optics now make FTTH a cost effective solution in many situations. The transition to FTTH in the access network is also a benefit for both consumers and service providers because it opens up the near limitless capacity of the core long-haul network to the local user. In this paper individual passive optical components, transceivers, and fibers has been put together to form a complete FTTH network. Then the implementation of the under construction Baghdad/Al

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Automatic voice activity detection using fuzzy-neuro classifier
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Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

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Publication Date
Tue Sep 01 2009
Journal Name
2009 5th International Conference On Wireless Communications, Networking And Mobile Computing
Spectrum Sensing Opportunities in Cognitive Radios
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Cognitive radio is observed as a new approach, which could be cope with the spectral limitations. This approach is designed to detect whether a particular segment of the radio spectrum is currently in use and to jump into the temporarily unused spectrum rapidly without interfering with the transmissions of other users. CR is the promising radio technology which aims to detect and utilize the temporally unused spectrum bands by sensing its radio environment in order to improve spectrum utilization. To enhance the sensing performance, cooperative spectrum sensing has been proposed. However, when the number of cognitive user tends to be very large, the bandwidth for reporting sensing results to the common receiver will be very huge. In this pa

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Publication Date
Sat Dec 24 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
A Comparative Study for the Accuracy of Three Molecular Docking Programs Using HIV-1 Protease Inhibitors as a Model
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Flexible molecular docking is a computational method of structure-based drug design to evaluate binding interactions between receptor and ligand and identify the ligand conformation within the receptor pocket. Currently, various molecular docking programs are extensively applied; therefore, realizing accuracy and performance of the various docking programs could have a significant value. In this comparative study, the performance and accuracy of three widely used non-commercial docking software (AutoDock Vina, 1-Click Docking, and UCSF DOCK) was evaluated through investigations of the predicted binding affinity and binding conformation of the same set of small molecules (HIV-1 protease inhibitors) and a protein target HIV-1 protease enzy

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