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Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq
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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
New Robust Estimation in Compound Exponential Weibull-Poisson Distribution for both contaminated and non-contaminated Data
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Abstract

The research Compared two methods for estimating fourparametersof the compound exponential Weibull - Poisson distribution which are the maximum likelihood method and the Downhill Simplex algorithm. Depending on two data cases, the first one assumed the original data (Non-polluting), while the second one assumeddata contamination. Simulation experimentswere conducted for different sample sizes and initial values of parameters and under different levels of contamination. Downhill Simplex algorithm was found to be the best method for in the estimation of the parameters, the probability function and the reliability function of the compound distribution in cases of natural and contaminateddata.

 

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Publication Date
Sat Aug 01 2015
Journal Name
2015 Ieee Conference On Computational Intelligence In Bioinformatics And Computational Biology (cibcb)
Granular computing approach for the design of medical data classification systems
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Publication Date
Mon Oct 09 2023
Journal Name
2023 Ieee 34th International Symposium On Software Reliability Engineering Workshops (issrew)
Semantics-Based, Automated Preparation of Exploratory Data Analysis for Complex Systems
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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Cathodic Protection for Above Ground Storage Tank Bottom Using Data Acquisition
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Impressed current cathodic protection controlled by computer gives the ideal solution to the changes in environmental factors and long term coating degradation. The protection potential distribution achieved and the current demand on the anode can be regulated to protection criteria, to achieve the effective protection for the system.

In this paper, cathodic protection problem of above ground steel storage tank was investigated by an impressed current of cathodic protection with controlled potential of electrical system to manage the variation in soil resistivity. Corrosion controller has been implemented for above ground tank in LabView where tank's bottom potential to soil was manipulated to the desired set poi

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Publication Date
Mon Dec 25 2023
Journal Name
Ieee Access
ITor-SDN: Intelligent Tor Networks-Based SDN for Data Forwarding Management
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Tor (The Onion Routing) network was designed to enable users to browse the Internet anonymously. It is known for its anonymity and privacy security feature against many agents who desire to observe the area of users or chase users’ browsing conventions. This anonymity stems from the encryption and decryption of Tor traffic. That is, the client’s traffic should be subject to encryption and decryption before the sending and receiving process, which leads to delay and even interruption in data flow. The exchange of cryptographic keys between network devices plays a pivotal and critical role in facilitating secure communication and ensuring the integrity of cryptographic procedures. This essential process is time-consuming, which causes del

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Perceptually Important Points-Based Data Aggregation Method for Wireless Sensor Networks
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The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

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Publication Date
Sat Nov 02 2013
Journal Name
International Journal Of Computer Applications
Mixed Transforms Generated by Tensor Product and Applied in Data Processing
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Finding orthogonal matrices in different sizes is very complex and important because it can be used in different applications like image processing and communications (eg CDMA and OFDM). In this paper we introduce a new method to find orthogonal matrices by using tensor products between two or more orthogonal matrices of real and imaginary numbers with applying it in images and communication signals processing. The output matrices will be orthogonal matrices too and the processing by our new method is very easy compared to other classical methods those use basic proofs. The results are normal and acceptable in communication signals and images but it needs more research works.

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Publication Date
Sun Jun 23 2019
Journal Name
Arma
Safe Mud Weight Window Determination: A Case Study from Southern Iraq
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ABSTRACT:. The Lower Cretaceous Zubair formation is comprised of sandstones intercalated with shale sequences. The main challenges that were encountered while drilling into this formation included severe wellbore instability-related issues across the weaker formations overlaying the reservoir section (pay zone). These issues have a significant impact on well costs and timeline. In this paper, a comprehensive geomechanical study was carried out to understand the causes of the wellbore failure and to improve drilling design and drilling performance on further development wells in the field. Failure criteria known as Mogi-Coulomb was used to determine an operating mud weight window required for safe drilling. The accuracy of the geomechanical

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Publication Date
Tue Mar 03 2009
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of repetitive estimation methodsSelf-data
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In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation)  structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of  these procedures and compare them using generated data.

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Data Classification using Quantum Neural Network
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In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

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