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Laminar convective heat transfer of hexylamine-treated MWCNTs-based turbine oil nanofluid
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Multi-walled carbon nanotubes (MWCNTs) were functionalized by hexylamine (HA) in a promising, cost-effective, rapid and microwave-assisted approach. In order to decrease defects and remove acid-treatment stage, functionalization of MWCNTs with HA was carried out in the presence of diazonium reaction. Surface functionality groups and morphology of chemically-functionalized MWCNTS were characterized by FTIR, Raman spectroscopy, thermogravimetric analysis (DTG), and transmission electron microscopy (TEM). To reach a promising dispersibility in oil media, MWCNTs were functionalized with HA. While the cylindrical structures of MWCNTs were remained reasonably intact, characterization results consistently confirmed the sidewall-functionalization of MWCNTs with HA functionalities. Then, HA-treated MWCNTs-based turbine oil nanofluids (HA-MWCNTs/TO) with different volume fractions were synthesized and employed to be investigated in terms of heat transfer potential. Convective heat transfer coefficient of HA-MWCNTs/TO as a positive parameter and pressure drop as a negative factor were investigated for various volume fractions. While results suggested a weak increase in the pressure drop by MWCNTs loading into the TO, lack of acidic agents, the performance index higher than 1 and a significant increase in the convective heat transfer open a new gateway for introducing this economical product for industrial applications in turbines and can be a capable alternative for conventional TO.

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Publication Date
Tue Mar 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Influence of Coating with Some Natural Based Materials on the Erosion Wear Behavior of Glass Fiber Reinforced Epoxy Resin
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Abstract 

In the present study, composites were prepared by Hand lay-up molding. The composites constituents were epoxy resin as a matrix, 6% volume fractions of glass fibers (G.F) as reinforcement and 3%, 6% volume fractions of preparation natural material (Rice Husk Ash, Carrot Powder, and Sawdust) as filler. Studied the erosion wear behavior and coating by natural wastes (Rice Husk Ash) with epoxy resin after erosion. The results showed the non – reinforced epoxy have lower resistance erosion than natural based material composites and the specimen (Epoxy+6%glass fiber+6%RHA) has higher resistance erosion than composites reinforced with carrot powder and sawdust  at 30cm , angle 60

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Publication Date
Sun Dec 22 2019
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Assessment of Causality, Severity and Seriousness of Adverse Event Following Immunization in Iraq: A Retrospective Study Based on Iraqi
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Immunization is one of the most cost-effective and successful public health applications. The results of immunization are difficult to see as the incidence of disease occurrence is low while adverse effects following the immunization are noticeable, particularly if the vaccine was given to apparently healthy person. High safety expectations of population regarding the vaccines so they are more prone to hesitancy regarding presence of even small risk of adverse events which may lead to loss of pub

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT
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Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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Publication Date
Wed May 15 2024
Journal Name
Ieee Sensors Journal
Surface Crack Size Estimation Based on Quantification and Decoupling of Magnetic Flux Leakage (MFL) Signals of Circular Array Sensors
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Publication Date
Thu Dec 31 2020
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
SYNTHESIS OF THE NEW NAPROXEN SELECTIVE ELECTRODE BASED ON IMPRINTED POLYMER USING DIFFERENT MONOMERS AND ITS DETERMINATION AT PHARMACEUTICAL PREPARATION: SYNTHESIS OF THE NEW NAPROXEN SELECTIVE ELECTRODE BASED ON IMPRINTED POLYMER USING DIFFERENT MONOMERS AND ITS DETERMINATION AT PHARMACEUTICAL PREPARATION
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ABSTRACT

Naproxen(NPX) imprinted liquid electrodes of polymers are built using polymerization precipitation. The molecularly imprinted (MIP) and non imprinted (NIP) polymers were synthesized using NPX as a template. In the polymerization precipitation involved, styrene(STY) was used as monomer, N,N-methylenediacrylamide (N,N-MDAM) as a cross-linker and benzoyl peroxide (BPO) as an initiator. The molecularly imprinted membranes and the non-imprinted membranes were prepared using acetophenone(AOPH) and di octylphathalate(DOP)as plasticizers in PVC matrix. The slopes and detection limits of the liquid electrodes ranged from)-18.1,-17.72 (mV/decade and )4.0 x 10-

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Publication Date
Mon Apr 04 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of Electronic System Based on Cloud Computing to Develop Electronic Tasks for Students of the University of Mosul
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The present research aims to design an electronic system based on cloud computing to develop electronic tasks for students of the University of Mosul. Achieving this goal required designing an electronic system that includes all theoretical information, applied procedures, instructions, orders for computer programs, and identifying its effectiveness in developing Electronic tasks for students of the University of Mosul. Accordingly, the researchers formulated three hypotheses related to the cognitive and performance aspects of the electronic tasks. To verify the research hypotheses, a sample of (91) students is intentionally chosen from the research community, represented by the students of the college of education for humanities and col

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Publication Date
Wed Dec 11 2019
Journal Name
Journal Of The College Of Education For Women
The Effectiveness of Teaching Program Based on The Theory of Multiple Intelligence in the Development of Literary Thinking Among Students
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The research aims to know the effectiveness of a training program based on multiple intelligence theory in developing literary thinking among students of the Arabic Language Department at Ibn Rushd School of Humanities and to achieve the goal of research, the Safaris Research Institute, and the research community of Arabic language students in the Faculty of Education the third section of Arabic Language: The research sample consists of (71) students. Divided into (35) students in the experimental group and (36) students in the control group, the researcher balanced between the two groups with variables (intelligence, testing of tribal literary thinking, and time age in months), and after using the T-test for two independent samples, the

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Publication Date
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

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