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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
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
The role of Open Budget in achieving of the transparency and responsibility and Reflect it on the administrative and financial corruption
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Abstract

The open budget means everyone in the society can get information about the government budget in order to watch the governmental works. The aim of the research is to study the concepts of open budget, its advantage, limitations, role of supporting the transparency and questioning the administrative and financial corruption. Thus reflects positively on the national economy by providing governmental information to all users whether they are individuals or belong to the political class, or any other governmental or nongovernmental organizations which are interested in these information.

In order to achieve the objectives of the research aims, we make questionnaire to see aca

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Numerical modeling of single closed and open-ended pipe pile embedded in dry soil layers under coupled static and dynamic loadings
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Abstract<p>For the design of a deep foundation, piles are presumed to transfer the axial and lateral loads into the ground. However, the effects of the combined loads are generally ignored in engineering practice since there are uncertainties to the precise definition of soil–pile interactions. Hence, for technical discussions of the soil–pile interactions due to dynamic loads, a three-dimensional finite element model was developed to evaluate the soil pile performance based on the 1 g shaking table test. The static loads consisted of 50% of the allowable vertical pile capacity and 50% of the allowable lateral pile capacity. The dynamic loads were taken from the recorded data of the Kobe e</p> ... Show More
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Publication Date
Sat Jan 01 2022
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
classification coco dataset using machine learning algorithms
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Network Traffic Prediction Based on Boosting Learning
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Classification of network traffic is an important topic for network management, traffic routing, safe traffic discrimination, and better service delivery. Traffic examination is the entire process of examining traffic data, from intercepting traffic data to discovering patterns, relationships, misconfigurations, and anomalies in a network. Between them, traffic classification is a sub-domain of this field, the purpose of which is to classify network traffic into predefined classes such as usual or abnormal traffic and application type. Most Internet applications encrypt data during traffic, and classifying encrypted data during traffic is not possible with traditional methods. Statistical and intelligence methods can find and model traff

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Reinforcement Learning-Based Television White Space Database
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Television white spaces (TVWSs) refer to the unused part of the spectrum under the very high frequency (VHF) and ultra-high frequency (UHF) bands. TVWS are frequencies under licenced primary users (PUs) that are not being used and are available for secondary users (SUs). There are several ways of implementing TVWS in communications, one of which is the use of TVWS database (TVWSDB). The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. With this in mind, the authors present a reinforcement learning-ba

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Publication Date
Sat Dec 30 2023
Journal Name
Nasaq Journal
Iraqi EFL Students’ Attitudes towards Online Learning
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Online learning is not a new concept in education, but it has been used extensively since the Covid-19 pandemic and is still in use now. Every student in the world has gone through this learning process from the primary to the college levels, with both teachers and students conducting instruction online (at home). The goal of the current study is to investigate college students’ attitudes towards online learning. To accomplish the goal of the current study, a questionnaire is developed and adjusted before being administered to a sample of 155 students. Additionally, validity and reliability are attained. Some conclusions, recommendations, and suggestions are offered in the end.

Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detecting Textual Propaganda Using Machine Learning Techniques
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Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation.  Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota

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Publication Date
Fri Aug 28 2020
Journal Name
Iraqi Journal Of Science
Theoretical and Experimental Study for Corrosion Inhibition of Carbon Steel in Salty and Acidic Media by A New Derivative of Imidazolidine 4-One
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A new imidazolidine 4-one derivative, of namly 2-[2-(4-Bromo-phenyl)-imidazo [1,2-a] pyridine-3-yl]-3-(4-nitro-phenyl)-imidazolidine-4-one (BPIPNP) was investigated as corrosion inhibitor for carbon steel in salty (3.5% NaCl) and acidic (0.5M HCl) solutions using potentiometric polarization measurements. The results revealed that the percentage inhibition efficiencies (%IE) in the salty solution (90.67%) are greater than that in the acidic solution (83.52%). Experimentally, the thermodynamic parameters obtained have supported a physical adsorption mechanism and which followed Langmuir adsorption isotherm. Density Functional Theory (DFT) of quantum mechanical method with B3LYP 6-311++G (2d, 2p) level was used to calculate geometrical stru

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Publication Date
Tue Aug 02 2022
Journal Name
International Journal Of Research In Social Sciences &amp; Humanities
The Making of a Heroine: A Female Character as Portrayed in The English Patient By Michael OndaatjE
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This article discusses how women have significant abilities to cope with the difficulties of war times. They are not the weak and vulnerable victims who are thought to be. On the contrary, they have the power to control over many-sided fronts, like participating in the battlefield as nurses or activists for peace, or even fighters, as well as through the tasks and responsibilities assigned to them to protect and support their families during wartime. The researcher will examine the impact of war upon women. Like men, women suffer during wartime. They are being injured, tortured and killed. Yet, they are able to give examples of love and courage even in the difficult times of war. Hana is one of those women who lived during wartimes,

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