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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 Sep 22 2021
Journal Name
Samarra Journal Of Pure And Applied Science
Toward Constructing a Balanced Intrusion Detection Dataset
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Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff

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Publication Date
Sun Jan 01 2023
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees22fr
Investigate the structural properties of Tl1-xHgxSr2Ca2Cu3O8+δ compound by using Scherrer modified equation
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Publication Date
Sun Jan 01 2023
Journal Name
Second International Conference On Innovations In Software Architecture And Computational Systems (isacs 2022)
Structural flexibility and its impact on contemporary architecture
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. The concepts of structural flexibility became one of the important goals in the design phases to reach high performance in architecture. The pioneering projects and ideas that linked architecture with technologies and scientific innovations appeared, with the aim of reaching projects that mix the concepts of flexibility with the development of machine thought and modern technology to meet the functional, environmental, and aesthetic requirements for human wellbeing. The aim of this paper is to identify the mechanisms used in order to reach flexible structural systems capable of accommodating technological changes and developments. The research hypothesizes that the structural design according to the concepts of flexibility achieves high s

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Publication Date
Fri Apr 16 2021
Journal Name
Turkish Journal Of Computer And Mathematics Education (turcomat)
The Impact Of Reflexive Learning Strategy On Mathematics Achievement By First Intermediate Class Students And Their Attitudes Towards E-Learning
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Publication Date
Sat May 02 2020
Journal Name
Plant Archives
MEASUREMENT OF ASBESTOS FIBERS CONCENTRATIONS IN SOME DENSE AREAS IN BAGHDAD, IRAQ, IN WINTER 2020
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Asbestos is a hazard pollutant to human health, exposure to asbestos cause serious health effects and wide range of asbestos-related diseases such as asbestosis, lung cancer and malignant mesothelioma and it has been classified as carcinogen by the World Health Organization WHO which cause a carcinogenic effects. Fibers of asbestos are mainly released from friction product in brakes and clutch linings and from reinforce agent in the asbestos cement industry. The aim of this was to evaluate the levels of asbestos fibers in surroundings air of some dense traffic points in Baghdad, through winter 2020. Materials and Methods: Samples of airs was carried out by directing air flow to a mixed cellulose ester membrane filter mounted on an open face

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Publication Date
Sat Jan 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
Residual post fire strength of non-prismatic perforated beams
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Abstract<p>The main aim of this study is to assess the performance and residual strength of post-fire non-prismatic reinforced concrete beams (NPRC) with and without openings. To do this, nine beams were cast and divided into three major groupings. These groups were classified based on the degrees of heating exposure temperature chosen (ambient, 400, and 700°C), with each group containing three non-prismatic beams (solid, 8 trapezoidal openings, and 8 circular openings). Experimentally, given the same beam geometry, increasing burning temperature caused degradation in NPRC beams, which was reflected in increased mid-span deflection throughout the fire exposure period and also residual deflectio</p> ... Show More
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Sun Jun 11 2017
Journal Name
Al-academy
Directorial Vision Between The Closed And Open In The Iraqi Theater Space
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This research deals with the concept of space in the theatrical performance and how the director works between two different spaces, the closed space and the open space. The question was how to use space according to the director's vision in the presentation. The problem of the research was whether the director of the Iraqi filmmaker could see the variable in the architectural space Or the place or space within the exhibition between open and closed, through the formation of the vision of the external components of intellectual and aesthetic and aesthetic, and impact on the relationship between the actor and the recipient to produce a new aesthetic space, and then the purpose of research and importance and limits and terminology The seco

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Publication Date
Sun Jan 01 2023
Journal Name
Lecture Notes In Networks And Systems
Advanced Security Technique in Presence of Open Communication System and Cyber Era
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