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Using Nonparametric Procedure to Develop an OCMT Estimator for Big Data Linear Regression Model with Application Chemical Pollution in the Tigris River
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Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemical pollution and profoundly have an effect on the life of the Iraqi people. The SICA estimator were chosen to analyze data and the MSE were used to make a comparison between the two methods and we determine that NP estimator is more effective than the other estimators under Big Data circumstances.

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Publication Date
Fri Nov 03 2023
Journal Name
Karbala International Journal Of Modern Science
Synthesis and characterization of zirconium oxide nanoparticles using Z. officinale and S. aromaticum plant extracts for antibacterial application
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Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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Publication Date
Mon Apr 01 2019
Journal Name
Biochemical And Cellular Archives
Influence of chemical fertilizers and foliar spraying with humic acid in growth and yield of red cabbage
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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Construct an efficient distributed denial of service attack detection system based on data mining techniques
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<span>Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynami

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
Oscillations of First Order Linear Delay Differential Equations with positive and negative coefficients
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Oscillation criteria are obtained for all solutions of the first-order linear delay differential equations with positive and negative coefficients where we established some sufficient conditions so that every solution of (1.1) oscillate. This paper generalized the results in [11]. Some examples are considered to illustrate our main results.

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
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Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

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Publication Date
Wed Jan 01 2014
Journal Name
Proceedings Of The Aintec 2014 On Asian Internet Engineering Conference - Aintec '14
LTE Peak Data Rate Estimation Using Modified alpha-Shannon Capacity Formula
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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Characterization Performance of Monocrystalline Silicon Photovoltaic Module Using Experimentally Measured Data
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Solar photovoltaic (PV) system has emerged as one of the most promising technology to generate clean energy. In this work, the performance of monocrystalline silicon photovoltaic module is studied through observing the effect of necessary parameters: solar irradiation and ambient temperature. The single diode model with series resistors is selected to find the characterization of current-voltage (I-V) and power-voltage (P-V) curves by determining the values of five parameters ( ). This model shows a high accuracy in modeling the solar PV module under various weather conditions. The modeling is simulated via using MATLAB/Simulink software. The performance of the selected solar PV module is tested experimentally for differ

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Publication Date
Thu Dec 01 2022
Journal Name
Int. J. Agricult. Stat. Sci.
STRAWBERRY CV. FESTIVAL GROWTH IN RESPONSES TO MAGNETIC WATER AND FOLIAR APPLICATION OF COCONUT EXTRACT
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This study was carried out to study effect of magnetic water ( M0 and M) and different concentrations of coconut extract in Fragaria x ananassa (Duch) C.V Festival. The results showed significant differences in the plants treated with magnetic water ( 0.12 Tesla) and different concentrations of coconut extract C1 (0%), C2 (2.5%), C3 (5%), C4 (7.5%) and C5 (10%) in vegetative parameters as in leaf area and chlorophyll in treatment M0C3 was (53.72 Dcm2, 50.00), respectively, highest leaf number and plant dry weight in MC4 (12.77,14.22 gm), respectively. Results recorded significant differences in fruit parameters such as weight in MC1 (18.97 gm). The maximum fruit number was in MC3 (110), the greatest fruit size was in MC4 (15.78 cm3) and the

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Publication Date
Fri Dec 30 2011
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Improved Method to Correlate and Predict Isothermal VLE Data of Binary Mixtures
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Accurate predictive tools for VLE calculation are always needed. A new method is introduced for VLE calculation which is very simple to apply with very good results compared with previously used methods. It does not need any physical property except each binary system need tow constants only. Also, this method can be applied to calculate VLE data for any binary system at any polarity or from any group family. But the system binary should not confirm an azeotrope. This new method is expanding in application to cover a range of temperature. This expansion does not need anything except the application of the new proposed form with the system of two constants. This method with its development is applied to 56 binary mixtures with 1120 equili

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