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A modified Mobilenetv2 architecture for fire detection systems in open areas by deep learning
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

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Publication Date
Wed Nov 29 2023
Journal Name
International Journal Of Advances In Scientific Research And Engineering (ijasre), Issn:2454-8006, Doi: 10.31695/ijasre
Yolo Versions Architecture: Review
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Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Advances In Scientific Research And Engineering
Yolo Versions Architecture: Review
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Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec

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Publication Date
Tue Jul 02 2013
Journal Name
Journal Of Baghdad College Of Dentistry
Local Drug Delivery Systems for Treating Periodontal Diseases: A Review of Literature
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Publication Date
Fri Feb 05 2010
Journal Name
Etri Journal
MC-MIPOG: A Parallel t-Way Test Generation Strategy for Multicore Systems
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Publication Date
Sat Aug 23 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Local drug delivery systems for treating periodontal diseases (A review of literature)
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In this review of literature, the light will be concentrated on the local drugs delivery systems for treating the periodontal diseases. Principles, types, advantages and indications of each type will be discussed in this paper.

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Publication Date
Mon Aug 01 2016
Journal Name
2016 38th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Changes in the EEG amplitude as a biomarker for early detection of Alzheimer's disease
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The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which ca

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Sun May 03 2020
Journal Name
Journal Of Advanced Laboratory Research In Biology
Hepatitis B Virus (HBV): A Review on its Prevalence and Infection in different areas of Iraq
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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Engineering
Flow Measurements in Open Channels Using Integrating-Floats
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The flow measurements have increased importance in the last decades due to the shortage of water resources resulting from climate changes that request high control of the available water needed for different uses. The classical technique of open channel flow measurement by the integrating-float method was needed for measuring flow in different locations when there were no available modern devices for different reasons, such as the cost of devices. So, the use of classical techniques was taken place to solve the problem. The present study examines the integrating float method and defines the parameters affecting the acceleration of floating spheres in flowing water that was analyzed using experimental measurements. The me

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Publication Date
Fri Dec 30 2011
Journal Name
Al-kindy College Medical Journal
Laparoscopic versus open appendectomy in patients with acuteappendicitis
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Background: Laparoscopic surgery for
appendicitis is now a well established and
advanced method of performing general surgical
procedures.
Objectives: To compare the outcome of
laparoscopic and open appendectomies in terms
of operative time, analgesic requirement,
postoperative complications, hospital stay, return
to normal activity and condition of scar.
Methods: This prospective study was carried
out from 1stMay 2008-1st January 2010, involving
110 patients (45 male and 65 female) with
features suggestive of acute appendicitis were
divided into 45 patients laparoscopic
appendectomy (LA) group and 65 patients open
appendectomy (OA) group, after taking informed
consent. LA was done with the

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