Polymer electrolytes were prepared using the solution cast technology. Under some conditions, the electrolyte content of polymers was analyzed in constant percent of PVA/PVP (50:50), ethylene carbonate (EC), and propylene carbonate (PC) (1:1) with different proportions of potassium iodide (KI) (10, 20, 30, 40, 50 wt%) and iodine (I2) = 10 wt% of salt. Fourier Transmission Infrared (FTIR) studies confirmed the complex formation of polymer blends. Electrical conductivity was calculated with an impedance analyzer in the frequency range 50 Hz–1MHz and in the temperature range 293–343 K. The highest electrical conductivity value of 5.3 × 10-3 (S/cm) was observed for electrolytes with 50 wt% KI concentration at room temperature. The magnitude of electrical conductivity was increased with the increase in the salt concentration and temperature. The blend electrolytes have a high dielectric constant at lower frequencies which may be attributed to the dipoles providing sufficient time to get aligned with the electric field, resulting in higher polarization. The reduction of activation energy (Ea) suggests that faster-conducting electrolyte ions want less energy to move.
In this paper, the generalized inverted exponential distribution is considered as one of the most important distributions in studying failure times. A shape and scale parameters of the distribution have been estimated after removing the fuzziness that characterizes its data because they are triangular fuzzy numbers. To convert the fuzzy data to crisp data the researcher has used the centroid method. Hence the studied distribution has two parameters which show a difficulty in separating and estimating them directly of the MLE method. The Newton-Raphson method has been used.
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
... Show MoreThe parameter and system reliability in stress-strength model are estimated in this paper when the system contains several parallel components that have strengths subjects to common stress in case when the stress and strengths follow Generalized Inverse Rayleigh distribution by using different Bayesian estimation methods. Monte Carlo simulation introduced to compare among the proposal methods based on the Mean squared Error criteria.
CO2 Gas is considered one of the unfavorable gases and it causes great air pollution. It’s possible to decrease this pollution by injecting gas in the oil reservoirs to provide a good miscibility and to increase the oil recovery factor. MMP was estimated by Peng Robinson equation of state (PR-EOS). South Rumila-63 (SULIAY) is involved for which the miscible displacement by is achievable based on the standard criteria for success EOR processes. A PVT report was available for the reservoir under study. It contains deferential liberation (DL) and constant composition expansion (CCE) tests. PVTi software is one of the (Eclipse V.2010) software’s packages, it has been used to achieve the goal. Many trials have been done to ma
... Show MoreAbstract. Full-waveform airborne laser scanning data has shown its potential to enhance available segmentation and classification approaches through the additional information it can provide. However, this additional information is unable to directly provide a valid physical representation of surface features due to many variables affecting the backscattered energy during travel between the sensor and the target. Effectively, this delivers a mis-match between signals from overlapping flightlines. Therefore direct use of this information is not recommended without the adoption of a comprehensive radiometric calibration strategy that accounts for all these effects. This paper presents a practical and reliable radiometric calibration r
... Show MoreAn experimental study is conducted to investigate the effect of heat flux distribution on the boiling safety factor of its cooling channel. The water is allowed to flow in a horizontal circular pipe whose outlet surface is subjected to different heat flux profiles. Four types of heat flux distribution profiles are used during experiments: (constant distribution profile, type a, triangle distribution profile with its maximum in channel center, type b, triangle distribution profile with its maximum in the channel inlet, type c, and triangle distribution profile with its maximum in the channel outlet, type d). The study is conducted using heat sources of (1000 and 2665W), water flow rates of (5, 7 and 9 lit/min). The water
... Show MoreThe important parameter used for determining the probable application of miscible displacement is the MMP (minimum miscibility pressure). In enhanced oil recovery, the injection of hydrocarbon gases can be a highly efficient method to improve the productivity of the well especially if miscibility developed through the displacement process. There are a lot of experiments for measuring the value of the miscibility pressure, but they are expensive and take a lot of time, so it's better to use the mathematical equations because of it inexpensive and fast. This study focused on calculating MMP required to inject hydrocarbon gases into two reservoirs namely Sadi and Tanomaa/ East Baghdad field. Modified Peng Robenson Equation of State was
... Show MoreBackground/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the
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