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THz-TDS for Detecting Glycol Contamination in Engine Oil
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There continues to be a need for an in-situ sensor system to monitor the engine oil of internal combustion engines. Engine oil needs to be monitored for contaminants and depletion of additives. While various sensor systems have been designed and evaluated, there is still a need to develop and evaluate new sensing technologies. This study evaluated Terahertz time-domain spectroscopy (THz-TDS) for the identification and estimation of the glycol contamination of automotive engine oil. Glycol contamination is a result of a gasket or seal leak allowing coolant to enter an engine and mix with the engine oil. An engine oil intended for use in both diesel and gasoline engines was obtained. Fresh engine oil samples were contaminated with four levels of glycol (0 ppm, 150 ppm, 300 ppm, and 500 ppm). The samples were analyzed with THz-TDS and converted to frequency domain parameters of refractive index and absorption coefficient. While both parameters showed potential, the absorption coefficient had the best potential and was able to statistically discriminate among the four contamination levels.

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Study the Inhibition Effect of Amoxicillin Drug for Corrosion of Carbon Steel in Saline Media
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          Potentiostatic polarization and weight loss methods have been used to investigate the corrosion behavior of carbon steel in sodium chloride solution at different concentrations (0.1, 0.4 and 0.6) M under the influence of temperatures ( 293, 298, 303, 308 and 313) K. The inhibition efficiency of the amoxicillin drug on carbon steel in 0.6 M NaCl has also been studied based on concentration and temperature. The corrosion rate showed that all salt concentrations ( NaCl solution) resulted in corrosion of carbon steel in varying ratio and 0.6 M of salt solution  was the highest rate (50.46 g/m².d). The results also indicate that the rate of corrosion increases at a temperature of 313 K.. Potentiodynamic polarization studi

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Publication Date
Mon Jul 18 2022
Journal Name
Ieee Access
Moderately Multispike Return Neural Network for SDN Accurate Traffic Awareness in Effective 5G Network Slicing
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Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

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Publication Date
Thu Jul 01 2021
Journal Name
Solar Energy
A new approach for employing multiple PCMs in the passive thermal management of photovoltaic modules
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Publication Date
Wed Jul 22 2020
Journal Name
International Journal Of Research In Pharmaceutical Sciences
Cloud point extraction method for the sensitive determination of metoclopramide hydrochloride in pharmaceutical dosage forms
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In this work, a simple and very sensitive cloud point extraction (CPE) process was developed for the determination of trace amount of metoclopramide hydrochloride (MTH) in pharmaceutical dosage forms. The method is based on the extraction of the azo-dye results from the coupling reaction of diazotized MTH with p-coumaric acid (p-CA) using nonionic surfactant (Triton X114). The extracted azo-dye in the surfactant rich phase was dissolved in ethanol and detected spectrophotometrically at λmax 480 nm. The reaction was studied using both batch and CPE methods (with and without extraction) and a simple comparison between the two methods was performed. The conditions that may be affected by the extraction process and the sensitivity of m

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Concentrations and Radiation Hazard Indices of Naturally Radioactive Materials for Flour Samples in Baghdad Markets
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In the present work, Uranium (238U), Thorium (232Th) and Potassium (40K) specific activity concentration in (Bq/kg) was measured in five different types for wheat flours that are available in the Iraqi markets. The gamma spectrometry method with an NaI (Tl) detector has been used for radiometric measurements. Calculations of radium equivalent activity, annual effective dose equivalent, external hazard index (Hex), internal hazard index (Hin), representing gamma index and gamma dose rate in all  flour samples were 17.98132 Bq/kg, 0.0100334, 0.04502, 0.04857, 0.06872, 0.125883 and 8.181244 respectively. It is found that the average of specific activity concentration of wheat flour sam

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Publication Date
Sun Jul 31 2022
Journal Name
Iraqi Journal Of Science
Elliptic Curve Cryptography Performance Evaluation for Securing Multi-Factor Systems in a Cloud Computing Environment
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     In the contemporary world, the security of data and privacy policies are major concerns in cloud computing. Data stored on the cloud has been claimed to be unsafe and liable to be hacked. Users have found it difficult to trust their data in the cloud. Users want to know that their data is accessible from anywhere and that an unauthorized user will not be able to access it. Another area of concern is the authentication of users over the cloud. There are a number of security concerns with Cloud Computing which include Distributed Denial of Service, Data leakage, and many more, just to mention a few. In this paper, an Elliptic Curve Cryptography (ECC) algorithm is used for the encryption and decryption of the information stored on

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Publication Date
Thu Oct 13 2022
Journal Name
Computation
A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

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Publication Date
Sun Oct 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A novel data offloading scheme for QoS optimization in 5G based internet of medical things
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The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

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Publication Date
Sat Jul 01 2017
Journal Name
Journal Of Construction Engineering And Management
Identification, Quantification, and Classification of Potential Safety Risk for Sustainable Construction in the United States
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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
User Quality of Experience (QoE) Satisfaction for Video Content Selection (VCS) Framework in Smartphone Devices
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Video streaming is widely available nowadays. Moreover, since the pandemic hit all across the globe, many people stayed home and used streaming services for news, education,  and entertainment. However,   when streaming in session, user Quality of Experience (QoE) is unsatisfied with the video content selection while streaming on smartphone devices. Users are often irritated by unpredictable video quality format displays on their smartphone devices. In this paper, we proposed a framework video selection scheme that targets to increase QoE user satisfaction. We used a video content selection algorithm to map the video selection that satisfies the user the most regarding streaming quality. Video Content Selection (VCS) are classified in

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