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Features Selection for Intrusion Detection System Based on DNA Encoding
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Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system. A new features selection method is proposed based on DNA encoding and on DNA keys positions. The current system has three phases, the first phase, is called pre-processing phase, which is used to extract the keys and their positions, the second phase is training phase; the main goal of this phase is to select features based on the key positions that gained from pre-processing phase, and the third phase is the testing phase, which classified the network traffic records as either normal or attack by using specific features. The performance is calculated based on the detection rate, false alarm rate, accuracy, and also on the time that include both encoding time and matching time. All these results are based on using two or three keys, and it is evaluated by using two datasets, namely, KDD Cup 99, and NSL-KDD. The achieved detection rate, false alarm rate, accuracy, encoding time, and matching time for all corrected KDD Cup records (311,029 records) by using two and three keys are equal to 96.97, 33.67, 91%, 325, 13 s, and 92.74, 7.41, 92.71%, 325 and 20 s, respectively. The results for detection rate, false alarm rate, accuracy, encoding time, and matching time for all NSL-KDD records (22,544 records) by using two and three keys are equal to 89.34, 28.94, 81.46%, 20, 1 s and 82.93, 11.40, 85.37%, 20 and 1 s, respectively. The proposed system is evaluated and compared with previous systems and these comparisons are done based on encoding time and matching time. The outcomes showed that the detection results of the present system are faster than the previous ones.

Scopus
Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Numerical Investigation for Simulation of Thermophysical Properties for Polypropylene 575 Polymer Melts in Single Screw Extruder
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A numerical model for Polypropylene 575 polymer melts flow along the solid conveying screw of a single screw extruder under constant heat flux using ANSYS-FLUENT 17.2 software has been conducted. The model uses the thermophysical properties such as Viscosity, thermal conductivity, Specific heat and density of polypropylene 575 that measured as a function of temperature, and residence time data for process simulation. The numerical simulation using CFD models for single screw extruder and the polymer extrusion was analysed for parameters such as (thermal conductivity, specific heat, density and viscosity) reveals a high degree of similarity to experimental data measured. The most important outcome of this study is that geometrical, parame

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Crossref
Publication Date
Sat Feb 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Assessing the efficiency Economic performance of the diyala General company for electrical industries for the Period (2000-2010)
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     Facing industrial companies many pressures and challenges due to rapid changes in the business environment of contemporary, which requires them to do their performance look more inclusive rather than limiting performance evaluation on the financial perspective in spite of its importance, prompting companies to rethink their reality competitive through the adoption of methodologies and new philosophies to manage competitiveness of total quality management, and re-engineering of production processes, and knowledge management,... etc., as This study framework cognitive and practical "to evaluate the performance of a company Diyala General Electric Industries and how to rehabilitate

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Crossref
Publication Date
Sun Mar 04 2012
Journal Name
Baghdad Science Journal
Double Stage Cumulative Shrunken Bayes Estimator for the variance of Normal distribution for equal volume of two sample
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In this article we study the variance estimator for the normal distribution when the mean is un known depend of the cumulative function between unbiased estimator and Bays estimator for the variance of normal distribution which is used include Double Stage Shrunken estimator to obtain higher efficiency for the variance estimator of normal distribution when the mean is unknown by using small volume equal volume of two sample .

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Crossref
Publication Date
Wed Jan 24 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
FOOD APPLICATIONS FOR OIL AND CHIA SEEDS SALVIA HISPANICA: FOOD APPLICATIONS FOR OIL AND CHIA SEEDS SALVIA HISPANICA
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The extracted oil from the Chia seeds white and black were used in the manufacture of certain foods such as mayonnaise. The results of the sensory evaluation showed that the product was acceptable except for the flavor of white chia seed oil. The seeds were fully used in the manufacture of the nutella. The results of the sensory evaluation were encouraging the use of the extracted oil from the black chia seeds in the production of the nutella except the spread property. Chia seeds were also used in the manufacture of pudding. The results of the sensory evaluation showed an excellent and acceptable product of black chia seeds oil can be obtained, while the white seeds did not receive the acceptance in terms of color and flavor.

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Publication Date
Thu Nov 02 2023
Journal Name
Journal Of Engineering
Prediction Unconfined Compressive Strength for Different Lithology Using Various Wireline Type and Core Data for Southern Iraqi Field
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Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

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Crossref
Publication Date
Fri Jul 01 2022
Journal Name
Advanced Powder Technology
Modification of FAU zeolite as an active heterogeneous catalyst for biodiesel production and theoretical considerations for kinetic modeling
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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
The effect of increasing the volume of debt on the volume of trading (applied research on a sample of private banks listed on the Iraq Stock Exchange)
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This research worked on identifying the effect of increasing the volume of indebtedness by companies listed on the Iraq Stock Exchange on the trading volume of those companies, and this research included some theoretical concepts related to both debt financing and trading volume, and it represents the research community of the joint-stock companies listed in The Iraq Stock Exchange (the banking sector). As for the research sample, it was deliberately chosen represented by companies with continuous trading without stopping, which reached 10 joint-stock companies, and the period of research was extended during the period 2011-2015, and a set of indicators and financial methods were used In measuring research v

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Crossref
Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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Scopus (5)
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Publication Date
Wed Sep 01 2021
Journal Name
Iraqi Journal Of Physics
Effect of π-conjugated molecules on electronics properties of benzene-diamine derivatives
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The present work shows a theoretical results that have been used the functional Hybrid of three parameters Lee-Yang-Parr (B3LYP) of the quantum mechanical approach for density functional theory with (Spanish Initiative for Electronic Simulations with Thousands of Atoms) SIESTA code. All calculations were carried out employing the used method at the Gaussian 09 package of programs. It was reported the main point for research on dominance of the bandgap of elongated pi-conjugated molecules by using different chemical groups replacing hydrogen atom in the most molecules that used in this work. The side groups creates another factor that controls the value of the band gap. The dihedral angle between the two pheny

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Crossref
Publication Date
Wed Jan 05 2022
Journal Name
Journal Of Positive School Psychology
Influence Of Variance In Rest Interval For The Explosive Power Training For The Arms And Legs In The Light Of Some Biochemical Indicators For The Cellular Equilibrium Of The Volleyballers
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