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An integrated multi layers approach for detecting unknown malware behaviours
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Malware represents one of the dangerous threats to computer security. Dynamic analysis has difficulties in detecting unknown malware. This paper developed an integrated multi – layer detection approach to provide more accuracy in detecting malware. User interface integrated with Virus Total was designed as a first layer which represented a warning system for malware infection, Malware data base within malware samples as a second layer, Cuckoo as a third layer, Bull guard as a fourth layer and IDA pro as a fifth layer. The results showed that the use of fifth layers was better than the use of a single detector without merging. For example, the efficiency of the proposed approach is 100% compared with 18% and 63% of Virus Total and Bellegarde respectively.  

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Publication Date
Tue Dec 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Applying Trade-off Curve to Support Set-Based Design application at an Aerospace Company
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Companies compete greatly with each other today, so they need to focus on innovation to develop their products and make them competitive. Lean product development is the ideal way to develop product, foster innovation, maximize value, and reduce time. Set-Based Concurrent Engineering (SBCE) is an approved lean product improvement mechanism that builds on the creation of a number of alternative designs at the subsystem level. These designs are simultaneously improved and tested, and the weaker choices are removed gradually until the optimum solution is reached finally. SBCE implementations have been extensively performed in the automotive industry and there are a few case studies in the aerospace industry. This research describe the use o

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Publication Date
Wed Jan 28 2026
Journal Name
F1000research
Enhancing Solar Power Forecasting Accuracy Using HMPCS and Machine Learning Techniques: An Applied Study
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Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti

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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
An Analysis of a Partial Temporary Immunity SIR Epidemic Model with Nonlinear Treatment Rate
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     A partial temporary immunity SIR epidemic model involv nonlinear treatment rate is proposed and studied. The basic reproduction number  is determined. The local and global stability of all equilibria of the model are analyzed. The conditions for occurrence of local bifurcation in the proposed epidemic model are established. Finally, numerical simulation is used to confirm our obtained analytical results and specify the control set of parameters that affect the dynamics of the model.

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Publication Date
Mon Jan 29 2024
Journal Name
Polymer Bulletin
An experimental study to investigate the effect of aluminum nanorod-reinforced epoxy matrix nanocomposites
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Publication Date
Wed Jan 18 2017
Journal Name
International Journal Of Pharmacy Practice
Antimicrobial utilization in an Iraqi province: a comprehensive evaluation of antibiotic source and cost
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Publication Date
Sun Jan 01 2023
Journal Name
International Conference Of Computational Methods In Sciences And Engineering Iccmse 2021
Synthesis, description and bacteriological valuation of metal complexes including an amoxicillin−based Schiff base
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Publication Date
Fri Sep 06 2024
Journal Name
Brazilian Journal Of Physics
Effect of the Fear Factor and Prey Refuge in an Asymmetric Predator–Prey Model
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This study investigates the influence of fear, refuge, and migration in a predator–prey model, where the interactions between the species follow an asymmetric function response. In contrast to some other findings, we propose that prey develop an anti-predator response in response to a concentration of predators, which in turn increases the fear factor of the predators. The conditions under which all ecologically meaningful equilibrium points exist are discussed in detail. The local and global dynamics of the model are determined at all equilibrium points. The model admits several interesting results by changing the rate of fear of predators and predator aggregate sensitivity. Numerical simulations have been performed to verify our theoret

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Publication Date
Tue Aug 01 2023
Journal Name
European Heart Journal
Routine electronic health record-based clinical trials: what should an early-career trialist know?
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Publication Date
Thu Feb 19 2026
Journal Name
International Journal Of Surgery Open
Secondary trigeminal neuralgia: an in-depth review of etiopathology, clinical manifestations, and management approaches
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Secondary trigeminal neuralgia (STN) results from an identifiable underlying pathology, including tumor compression, multiple sclerosis, arteriovenous malformations, hypertension, structural lesions, inflammation, trauma, or familial genetic conditions. This study, through a comprehensive review of the literature in PubMed, Google Scholar, Web of Science, and the Cochrane Library, explores the multifaceted aspects of STN. This study delves into the diverse etiological factors, focusing on the pathophysiological mechanisms that lead to trigeminal nerve dysfunction. The clinical manifestations of STN often overlap with those of primary trigeminal neuralgia, creating diagnostic challenges and necessitating a thorough evaluation that in

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Publication Date
Sat Sep 26 2026
Journal Name
International Journal Of Low-carbon Technologies
Spatiotemporal patterns of bifacial and monofacial photovoltaic energy potential in an arid climate zone
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Abstract<p>Climate change significantly affects photovoltaic (PV) energy potential in arid regions. This study quantifies climate change impacts on both monofacial and bifacial PV energy potential across Iraq using Community Climate System Model (CCSM4) projections under Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios spanning 2020–2100. Specific mathematical frameworks accounting for thermal and irradiance characteristics were applied across 18 representative regions covering Iraq’s diverse climatic zones, with bifacial systems modeled using dual-surface irradiance capture incorporating ground reflection and thermal dynamics. Results reveal distinct northwest–southe</p> ... Show More
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