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bsj-5517
Multifactor Algorithm for Test Case Selection and Ordering
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Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls short. The current research is motivated by this concept and proposes a multifactor algorithm incorporated with genetic operators and powerful features. A factor-based prioritizer is introduced for proper handling of tied test cases that emerged while implementing re-ordering. Besides this, a Cost-based Fine Tuner (CFT) is embedded in the study to reveal the stable test cases for processing. The effectiveness of the outcome procured through the proposed minimization approach is anatomized and compared with a specific heuristic method (rule-based) and standard genetic methodology. Intra-validation for the result achieved from the reduction procedure is performed graphically. This study contrasts randomly generated sequences with procured re-ordered test sequence for over '10' benchmark codes for the proposed prioritization scheme. Experimental analysis divulged that the proposed system significantly managed to achieve a reduction of 35-40% in testing effort by identifying and executing stable and coverage efficacious test cases at an earlier phase.

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
The effects of laser intensities on nonlinear properties for Ag nanoparticles colloid
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A huge potential from researchers was presented for enhancing the nonlinear optical response for materials that interacts by light. In this work, we study the nonlinear optical response for chemically prepared nano- fluid of silver nanoparticles in de-ionized water with TSC (Tri-sodium citrate) protecting agent. By the means of self-defocusing technique and under CW 473 nm blue laser, the reflected diffraction pattern were observed and recorded by CCD camera. The results demonstrate that, the Ag nano-fluid shows a good third order nonlinear response and the magnitude of the nonlinear refractive index was in the order of 10−7 cm2/W. We determine the maximum change of the nonlinear refractive index and the related phase shift for the mat

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Investigation of Doppler broadening Compton scattering for aluminum element at different angles
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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Rapid thermal oxidation of copper nanostructure thin film for solar cell fabrication
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In the present work is the deposition of copper oxide using the pulsed laser deposition technique using Reactive Pulsed Laser as a Deposition technique (RPLD), 1.064μm, 7 nsec Q-switch Nd-YAG laser with 400 mJ/cm2 laser energy’s has been used to ablated high purity cupper target and deposited on the porous silicon substrates recorded and study the effect of rapid thermal annealing on the structural characteristics, morphological, electrical characteristics and properties of the solar cell. Results of AFM likelihood of improved absorption, thereby reducing the reflection compared with crystalline silicon surface. The results showed the characteristics of the solar cell and a clear improvement in the efficiency of the solar cell in the

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Investment Trends for Iraqi Industries in Terms of Clean Production (selected model)
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   Industrial Investment according to Clean Productive methods is an important element in the process of rational use of Economic Resources, and the Iraqi industrial sector relied on traditional production methods; the productive activities in this sector did not take into consideration the environmental dimension, which leads to achieving the optimal use of economic resources, so it was necessary to have new investment trends heading with Clean Production. Therefore, the research is based on the hypothesis that "Clean Production contributes to improving the environment and rational use of Natural Resources." Based on the descriptive - inductive analysis methodology that study of Iraqi industries with Clean Production,

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Publication Date
Mon Jul 01 2019
Journal Name
Journal Of Engineering
Utilizing the Main Outfall Drain-Addalmage Lake System for Hydroelectric Power Generation
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The basic idea of the Main Outfall Drain, MOD, was to construct a main channel to collect saline drained water of the irrigation projects within central and southern parts of Iraq and discharge it down to the Arabian Gulf. The MOD has a navigation lock structures near Addalmage Lake at station 299.4km. This structure is designed to ensure navigation within the MOD. The water level difference upstream the cross regulator and the downstream conjugation structure is about 9m. This head difference can be used to generate electrical power by constricting a low head power plant. This study aimed to utilize the head difference in navigation lock structures for power generation. Different operation condition an

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
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         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

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Publication Date
Sat Jun 29 2013
Journal Name
Wireless Personal Communications
A Low Cost Route Optimization Scheme for Cluster-Based Proxy MIPv6 Protocol
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Publication Date
Sat Dec 05 2015
Journal Name
PrzeglĄd Elektrotechniczny
Power Amplifier Frequency Controller Using feedback control techniques for Bio-implanted Devices
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Publication Date
Tue Jul 01 2014
Journal Name
Political Sciences Journal
For assuming the presidency of the political power in contemporary Islamic thought
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مدة تولي رئاسة السلطة في الفكر السياسي الاسلامي المعاصر

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Positive Definiteness of Symmetric Rank 1 (H-Version) Update for Unconstrained Optimization
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Several attempts have been made to modify the quasi-Newton condition in order to obtain rapid convergence with complete properties (symmetric and positive definite) of the inverse of  Hessian matrix (second derivative of the objective function). There are many unconstrained optimization methods that do not generate positive definiteness of the inverse of Hessian matrix. One of those methods is the symmetric rank 1( H-version) update (SR1 update), where this update satisfies the quasi-Newton condition and the symmetric property of inverse of Hessian matrix, but does not preserve the positive definite property of the inverse of Hessian matrix where the initial inverse of Hessian matrix is positive definiteness. The positive definite prope

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