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Hybrid Framework To Exclude Similar and Faulty Test Cases In Regression Testing
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Regression testing is a crucial phase in the software development lifecycle that makes sure that new changes/updates in the software system don’t introduce defects or don’t affect adversely the existing functionalities. However, as the software systems grow in complexity, the number of test cases in regression suite can become large which results into more testing time and resource consumption. In addition, the presence of redundant and faulty test cases may affect the efficiency of the regression testing process. Therefore, this paper presents a new Hybrid Framework to Exclude Similar & Faulty Test Cases in Regression Testing (ETCPM) that utilizes automated code analysis techniques and historical test execution data to identity and exclude redundant, similar and faulty test cases from the given regression suite. Our experimental results clearly show the benefits of the ETCPM framework in terms of reduction in the testing time, optimization of the resource allocation, and improvement in the overall quality of regression test suite. ETCPM enables software development teams to achieve faster and reliable regression testing by intelligent exclusion of similar and fault test cases, which yields in reduction in the software delivery cycles and better end user satisfaction.

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Publication Date
Tue Sep 01 2020
Journal Name
Acta Polytechnica
COMPLEXITY REDUCTION OF CYCLOSTATIONARY SENSING TECHNIQUE USING IMPROVED HYBRID SENSING METHOD
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In cognitive radio system, the spectrum sensing has a major challenge in needing a sensing method, which has a high detection capability with reduced complexity. In this paper, a low-cost hybrid spectrum sensing method with an optimized detection performance based on energy and cyclostationary detectors is proposed. The method is designed such that at high signal-to-noise ratio SNR values, energy detector is used alone to perform the detection. At low SNR values, cyclostationary detector with reduced complexity may be employed to support the accurate detection. The complexity reduction is done in two ways: through reducing the number of sensing samples used in the autocorrelation process in the time domain and through using the Slid

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Publication Date
Wed Jul 05 2017
Journal Name
Neural Computing And Applications
Hybrid soft computing approach for determining water quality indicator: Euphrates River
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Thu Dec 16 2021
Journal Name
Translational Vision Science & Technology
A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps
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Publication Date
Mon Nov 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
The Use of Auto-Regressive Distributed Lag Method in Investigating The Impact of Interest Rate on Foreign Direct Investment in Yemen for the Period 1990-2018
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 Foreign direct investment has seen increasing interest worldwide, especially in developing economies. However, statistics have shown that Yemen received fluctuating FDI inflows during the period under study. Against this background, this research seeks to determine the relationship and impact of interest rates on FDI flows. The study also found other determinants that greatly affected FDI inflows in Yemen for the period 1990-2018. Study data collected from the World Bank and International Monetary Fund databases. It also ensured that the time series were made balanced and interconnected, and then the Auto Regressive Distributed Lag method used in the analysis. The results showed that the interest rates and

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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Towards building an educational system free of scientific corruption (Applied study in a sample of colleges of higher education in Iraq within the framework of the government program and the directions of the Supreme Council for Combating Corruption)
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Nations are developed with education and knowledge that raise the status of society in its various segments, beyond that it leads to underdevelopment and deterioration in various sectors, whether economic, health, social, etc. If we considered the general name of The ministry of Education & Scientific Studies, then the second part seems to be not functioning, since scientific research has no material allocation and remains based on the material potential of the university professor. As for the first half of the topic, the reality of the situation reveals problems related to the Holy Trinity of Education which is (Professor - Student - the scientific method) where universities suffer at the present time from this problem, and

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Publication Date
Sun Nov 01 2020
Journal Name
2020 8th Ieee Ras/embs International Conference For Biomedical Robotics And Biomechatronics (biorob)
Estimating Wrist Joint Torque Using Regression Ensemble of Bagged Trees under Multiple Wrist Postures
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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index
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Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of eac

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Publication Date
Thu Apr 04 2024
Journal Name
Iraqi Journal Of Applied Physics
Experimental Investigation on Mechanical and Physical Properties of Hybrid Plastic/Wood Composites as Echo-friendly Structural and Decorative Materials
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This study focuses on producing wood-plastic composites using unsaturated polyester resin reinforced with Pistacia vera shell particles and wood industry waste powder. Composites with reinforcement ratios of 0%, 20%, 30%, and 40% were prepared and tested for thermal conductivity, impact strength, hardness, and compressive strength. The results revealed that thermal conductivity increases with reinforcement, while maintaining good thermal insulation, reaching a peak value of 0.633453 W/m·K. Hardness decreased with increased reinforcement, reaching a minimum nominal hardness value of 0.9479. Meanwhile, impact strength and compressive strength improved, with peak values of 14.103 k/m² and 57.3864568 MPa, respectively. The main aim is to manu

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Publication Date
Thu Sep 06 2018
Journal Name
Al-khwarizmi Engineering Journal
Bone Defect Animal Model for Hybrid Polymer Matrix Nano Composite as Bone Substitute Biomaterials
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Addition of bioactive materials such as Titanium oxide (TiO2), and incorporation of bio inert ceramic such as alumina (Al2O3), into polyetheretherketone (PEEK) has been adopted as an effective approach to improve bone-implant interfaces. In this paper, hot pressing technique has been adopted as a production method. This technique gave a homogenous distribution of the additive materials in the proposed composite biomaterial. Different compositions and compounding temperatures have been applied to all samples. Mechanical properties and animal model have been studied in all different production conditions. The results of these new TiO2/Al2O3/PEEK biocomposites with different

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