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Using Sensitivity Analysis in Linear Programming with Practical Physical Applications
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Linear programming currently occupies a prominent position in various fields and has wide applications, as its importance lies in being a means of studying the behavior of a large number of systems as well. It is also the simplest and easiest type of models that can be created to address industrial, commercial, military and other dilemmas. Through which to obtain the optimal quantitative value. In this research, we dealt with the post optimality solution, or what is known as sensitivity analysis, using the principle of shadow prices. The scientific solution to any problem is not a complete solution once the optimal solution is reached. Any change in the values of the model constants or what is known as the inputs of the model that will change the problem of linear programming and will affect the optimal solution, and therefore we need a method that helps us to stand on the impact of changing these constants on the optimal solution that has been reached. General concepts about the binary model and some related theories have also been addressed. By analyzing the sensitivity, we relied on real data for a company that transports crude oil and its derivatives. The mathematical model was formulated for it and the optimal solution was reached using the software. Ready-made sop WINQSB and then calculate the shadow price values for the binding constraints, in addition to what

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Publication Date
Thu Jun 16 2022
Journal Name
Al-khwarizmi Engineering Journal
Estimate and Analysis the Availability of Generator in Electric Power Plant Using ANN
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The large number of failure in electrical power plant leads to the sudden stopping of work. In some cases, the necessary reserve materials are not available for maintenance which leads to interrupt of power generation in the electrical power plant unit. The present study, deals with the determination of availability aspects of generator in unit 5 of Al-Dourra electric power plant. In order to evaluate this generator's availability performance, a wide range of studies have been conducted to gather accurate information at the level of detail considered suitable to achieve the availability analysis aim. The Weibull Distribution is used to perform the reliability analysis via Minitab 17, and Artificial Neural Networks (ANNs) by approaching o

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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Urinary Tract Stones Fragmentation using (2100 nm) Holmium: YAG Laser: (In vitro Analysis)
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Urinary stones are one of the most common painful disorders of the urinary system. Four new technologies have transformed the treatment of urinary stones: Electrohydraulic lithotripsy, ultrasonic lithotripsy, extracorporeal shock wave lithotripsy, and laser lithotripsy.The purpose of this study is to determine whether pulsed holmium laser energy is an effective method for fragmenting urinary tract stones in vitro, and to determine whether stone composition affects the efficacy of holmium laser lithotripsy. Human urinary stones of known composition with different sizes, shapes and colors were used for this study. The weight and the size of each stone were measured. The surgical laser system which used in our study is Ho:YAG laser(2100nm)

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Publication Date
Sat Jul 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Predicting of heavy metals in some areas of Iraq using spectral analysis techniques
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Abstract<p>Soil that has been contaminated by heavy metals is a serious environmental problem. A different approach for forecasting a variety of soil physical parameters is reflected spectroscopy is a low-cost, quick, and repeatable analytical method. The objectives of this paper are to predict heavy metal (Ti, Cr, Sr, Fe, Zn, Cu and Pb) soil contamination in central and southern Iraq using spectroscopy data. An XRF was used to quantify the levels of heavy metals in a total of 53 soil samples from Baghdad and ThiQar, and a spectrogram was used to examine how well spectral data might predict the presence of heavy metals metals. The partial least squares regression PLSR models performed well in pr</p> ... Show More
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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Classification & Evaluation of Evidence of deprivation in Iraq (2009) by using Cluster analysis
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       The study aimed to reach the best rating for the views and variables in the totals characterized by qualities and characteristics common within each group and distinguish them from aggregates other for the purpose of distinguishing between Iraqi provinces which suffer from deprivation, for the purpose of identifying the status of those provinces in the early allowing interested parties and regulators to intervene to take appropriate corrective action in a timely manner. Style has been used cluster analysis Cluster analysis to reach the best rating to those totals from the provinces that suffer from problems, where the provinces were classified, based on the variables (Edu

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Boubaker Wavelets Functions: Properties and Applications
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This paper is concerned with introducing an explicit expression for orthogonal Boubaker polynomial functions with some important properties. Taking advantage of the interesting properties of Boubaker polynomials, the definition of Boubaker wavelets on interval [0,1) is achieved. These basic functions are orthonormal and have compact support. Wavelets have many advantages and applications in the theoretical and applied fields, and they are applied with the orthogonal polynomials to propose a new method for treating several problems in sciences, and engineering that is wavelet method, which is computationally more attractive in the various fields. A novel property of Boubaker wavelet function derivative in terms of Boubaker wavelet themsel

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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
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 11 2021
Journal Name
Nano Express
Near-infrared PbS quantum dots functionalized with affibodies and ZnPP for targeted imaging and therapeutic applications
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Abstract<p>We report a new theranostic device based on lead sulfide quantum dots (PbS QDs) with optical emission in the near infrared wavelength range decorated with affibodies (small 6.5 kDa protein-based antibody replacements) specific to the cancer biomarker human epidermal growth factor receptor 2 (HER2), and zinc(II) protoporphyrin IX (ZnPP) to combine imaging, targeting and therapy within one nanostructure. Colloidal PbS QDs were synthesized in aqueous solution with a nanocrystal diameter of ∼5 nm and photoluminescence emission in the near infrared wavelength range. The Z<sub>HER2:432</sub> affibody, mutated through the introduction of two cysteine residues at the C-terminus (</p> ... Show More
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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Pharmaceutical Research
New method for the evaluation of propranolol with phosphotungstic acidvialong distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis
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A new, simple and sensitive method was used forevaluation of propranolol withphosphotungstic acidto prove the efficiency, reliability and repeatability of the long distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis. The method is based on reaction between propranolol and phosphotungstic acid in an aqueous medium to obtain a yellow precipitate. Optimum parameters was studied to increase the sensitivity for developed method. A linear range for calibration graph was 0.007-13 mmol/L for cell A and 5-15 mmol/L for cell B, and LOD 207.4792 ng/160 µL and 1.2449 µg/160 µL respectively to cell A and cell B with correlation coefficient (r) 0.9988 for cell A, 0.9996 for cell B, RSD% was lower than 1%, (n=8) for the

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Publication Date
Mon Apr 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Design The Modified Multi Practical Swarm Optimization To Enhance Fraud Detection
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     Financial fraud remains an ever-increasing problem in the financial industry with numerous consequences. The detection of fraudulent online transactions via credit cards has always been done using data mining (DM) techniques. However, fraud detection on credit card transactions (CCTs), which on its own, is a DM problem, has become a serious challenge because of two major reasons, (i) the frequent changes in the pattern of normal and fraudulent online activities, and (ii) the skewed nature of credit card fraud datasets. The detection of fraudulent CCTs mainly depends on the data sampling approach. This paper proposes a combined SVM- MPSO-MMPSO technique for credit card fraud detection. The dataset of CCTs which co

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