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alkej-137
Design a Security Network System against Internet Worms
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 Active worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.

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Publication Date
Wed Jan 01 2020
Journal Name
Materials Chemistry And Physics
Natural dye extracted from Areca catechu fruits as a new sensitiser for dye-sensitised solar cell fabrication: Optimisation using D-Optimal design
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Publication Date
Wed Jun 10 2026
Journal Name
Modern Sport
Design and standardization of two scoring tests for the initial selection of people with simple mental disabilities in five-a- Side Soccer
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The five-a- Side Soccer for simple mental disability is as interesting and caring as many other sporting events. Therefore, the researchers believe that their basic skills tests are compatible with then level of the tested individuals in terms of age and mental ability. As a means of selecting those who are qualified to practice this game in a simple way, the problem of research has been identified in the design and standardization of two scoring skills that belong to this category and are approved by the training staff during the initial selection process. The research community is determined by people with mental disabilities who belong to the governmental and private institutes and the Special Olympics Union in Baghdad and for the year 2

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Publication Date
Fri Apr 01 2022
Journal Name
Separation And Purification Technology
Application of central composite design approach for optimisation of zinc removal from aqueous solution using a Flow-by fixed bed bioelectrochemical reactor
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Publication Date
Fri Apr 01 2022
Journal Name
Separation And Purification Technology
Application of central composite design approach for optimisation of zinc removal from aqueous solution using a Flow-by fixed bed bioelectrochemical reactor
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Publication Date
Mon Apr 15 2019
Journal Name
Proceedings Of The International Conference On Information And Communication Technology
Re-evaluation of the stable improved LEACH routing protocol for wireless sensor network
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
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Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
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Publication Date
Tue Jul 01 2003
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
OCCURRENCE OF SOME FISH PARASITES IN AL-MADAEN DRAINAGE NETWORK, SOUTH OF BAGHDAD
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Seven fish species were collected from the drainage network at Al-Madaen region, south of
Baghdad with the aid of a cast net during the period from March to August 1993. These fishes
were infected with 22 parasite species (seven sporozoans, three ciliated protozoans, seven
monogeneans, two nematodes, one acanthocephalan and two crustaceans) and one fungus
species. Among such parasites, Chloromyxum wardi and Cystidicola sp. are reported here for
the first time in Iraq. In addition, 11 new host records are added to the list of parasites of
fishes of Iraq.

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Publication Date
Thu Jun 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Performance Improvement of Neural Network Based RLS Channel Estimators in MIMO-OFDM Systems
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The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

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Publication Date
Wed Feb 27 2019
Journal Name
Journal Of Low Power Electronics And Applications
Tolerating Permanent Faults in the Input Port of the Network on Chip Router
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Deep submicron technologies continue to develop according to Moore’s law allowing hundreds of processing elements and memory modules to be integrated on a single chip forming multi/many-processor systems-on-chip (MPSoCs). Network on chip (NoC) arose as an interconnection for this large number of processing modules. However, the aggressive scaling of transistors makes NoC more vulnerable to both permanent and transient faults. Permanent faults persistently affect the circuit functionality from the time of their occurrence. The router represents the heart of the NoC. Thus, this research focuses on tolerating permanent faults in the router’s input buffer component, particularly the virtual channel state fields. These fields track packets f

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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