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bsj-1071
Stochastic Non-Linear Pseudo-Random Sequence Generator
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Many of the key stream generators which are used in practice are LFSR-based in the sense that they produce the key stream according to a rule y = C(L(x)), where L(x) denotes an internal linear bit stream, produced by small number of parallel linear feedback shift registers (LFSRs), and C denotes some nonlinear compression function. In this paper we combine between the output sequences from the linear feedback shift registers with the sequences out from non linear key generator to get the final very strong key sequence

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Publication Date
Thu Nov 21 2019
Journal Name
Al-kindy College Medical Journal
Urinary Tract Infection Risk Assessment By Non- Thermal Plasma In Iraqis Patients
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Background: In the present study used device jet plasma needle with atmospheric pressure which  generates non thermal plasma jet to measure treatment potent with plasma against pathogenic bacteria  founded  in UTI  was inactivated with plasma at 10 sec,

Objective:. This work included the application of the plasma produced from the system in the field of bacterial sterilization , where sample of Gram- negative bacteria (Escherichia coli) were exposed to intervals (1-10)second . Midstream Urine samples swabs were obtained from patients with urinary tract infections.

Type of the study: Cross -sectional study.

Methods: The work were used i

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Publication Date
Sun Sep 01 2019
Journal Name
Journal Of Physics: Conference Series
Recovery of temporal coefficient for heat equation from non-local overdetermination conditions
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Abstract<p>Recovery of time-dependent thermal conductivity has been numerically investigated. The problem of identification in one-dimensional heat equation from Cauchy boundary data and mass/energy specification has been considered. The inverse problem recasted as a nonlinear optimization problem. The regularized least-squares functional is minimised through lsqnonlin routine from MATLAB to retrieve the unknown coefficient. We investigate the stability and accuracy for numerical solution for two examples with various noise level and regularization parameter.</p>
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Publication Date
Sat Mar 14 2020
Journal Name
Medico-legal Update,
Fasting Versus Non-Fasting in Assessing Lipid Profile and Complete Blood Picture
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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
An Application of Non-additive Measures and Corresponding Integrals in Tourism Management
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Non-additive measures and corresponding integrals originally have been introduced by Choquet in 1953 (1) and independently defined by Sugeno in 1974 (2) in order to extend the classical measure by replacing the additivity property to non-additive property. An important feature of non –additive measures and fuzzy integrals is that they can represent the importance of individual information sources and interactions among them. There are many applications of non-additive measures and fuzzy integrals such as image processing, multi-criteria decision making, information fusion, classification, and pattern recognition. This paper presents a mathematical model for discussing an application of non-additive measures and corresp

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Publication Date
Tue Jan 17 2017
Journal Name
British Journal Of Cancer
Aurora B expression modulates paclitaxel response in non-small cell lung cancer
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
IFFT-Based Microwave Non-Destructive Testing for Delamination Detection and Thickness Estimation
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Publication Date
Wed May 03 2017
Journal Name
Petroleum Science And Technology
Investigation of non-Newtonian flow characterization and rheology of heavy crude oil
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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Bayesian and Non - Bayesian Inference for Shape Parameter and Reliability Function of Basic Gompertz Distribution
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In this paper, some estimators of the unknown shape parameter and reliability function  of Basic Gompertz distribution (BGD) have been obtained, such as MLE, UMVUE, and MINMSE, in addition to estimating Bayesian estimators under Scale invariant squared error loss function assuming informative prior represented by Gamma distribution and non-informative prior by using Jefferys prior. Using Monte Carlo simulation method, these estimators of the shape parameter and R(t), have been compared based on mean squared errors and integrated mean squared, respectively

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Publication Date
Fri Jul 14 2023
Journal Name
International Journal Of Information Technology &amp; Decision Making
A Decision Modeling Approach for Data Acquisition Systems of the Vehicle Industry Based on Interval-Valued Linear Diophantine Fuzzy Set
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Modeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide mem

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
THE USE OF SIMULATION AND LINEAR PROGRAMMING IN THE PLANNING OF AUDIT WORK (An Empirical Study in the Office of Financial Supervision)
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Research includes three axes, the first is the average estimate time of achievement (day) to work oversight, to five supervisory departments in the Office of Financial Supervision Federal and then choose the three control outputs and at the level of each of the five departments above, and after analyzing the data statistically back to us that the distribution of the times of achievement It is the exponential distribution (Exponential Distribution) a parameter (q), and the distribution of normal (Normal Distribution) with two parameters (μ, σ2), and introduced four methods of parameter estimation (q) as well as four modalities parameter to estimate (

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