This work presents a novel technique for the detection of oil aging in electrical transformers using a single mode optical fiber sensor based on surface plasmon resonance (SPR). The aging of insulating oil is a critical issue in the maintenance and performance of electrical transformers, as it can lead to reduce insulation properties, increase risk of electrical breakdown, and decrease operational lifespan. Many parameters are calculated in this study in order to examine the efficiency of this sensor like sensitivity (S), signal to noise ratio (SNR), resolution (refractive index unit) and figure of merit (FOM) and the values are for figure of merit is 11.05, the signal to noise ratio is 20.3, the sensitivity is 6.63, and the resolution is 3.01*10^-5 .
In this work; copper oxide films (CuO) were fabricated by PLD. The films were analyzed by UV-VIS absorption spectra and their thickness by using profilometer. Pulsed Nd:YAG laser was used for prepared CuO thin films under O2 gas environment with varying both pulse energy and annealing temperature. The optical properties of as-grown film such as optical transmittance spectrum, refractive index and energy gap has been measured experimentally and the effects of laser pulse energy and annealing temperature on it were studied. An inverse relationship between energy gap and both annealing temperature and pulse energy was observed.
In this paper, three tool paths strategies; iso-planar, helical and adaptive have been implemented to investigates their effect on the mechanical properties of Brass 65-35 formed by single point incremental sheet metal forming process. To response this task, a fully digital integrated system from CAD modeling to finished part (CAD/CAM) for SPIF process has been developed in this paper.
The photo-micrographs shows an identical grain formation due to the plastic deformation of the incremental forming process, change in the grain shape and size was observed. It's found that the adaptive tool path play a significant role to increase the hardness of the formed specimen from (48 to 90 HV) and the grain texture of the formed specimen found a
In this research work, a simulator with time-domain visualizers and configurable parameters using a continuous time simulation approach with Matlab R2019a is presented for modeling and investigating the performance of optical fiber and free-space quantum channels as a part of a generic quantum key distribution system simulator. The modeled optical fiber quantum channel is characterized with a maximum allowable distance of 150 km with 0.2 dB/km at =1550nm. While, at =900nm and =830nm the attenuation values are 2 dB/km and 3 dB/km respectively. The modeled free space quantum channel is characterized at 0.1 dB/km at =860 nm with maximum allowable distance of 150 km also. The simulator was investigated in terms of the execution of the BB84 prot
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... Show MoreThe present work aimed to study effect of (N749 & N3) dyes on TiO2 optical and electrical properties for optoelectronic application. The TiO2 paste prepared by using a doctor blade method. The samples were UV-VIS specterophometricall analyzes of TiO2 before and after immersed in dyes (N749 & N3). The results showed absorption spectra shift toward the visible region due to the adsorption of dye molecules on the surface of oxide nanoparticles. It is seen that the Eg determined to give a value of 3.3eV for TiO2 before immersing in dyes, and immersing in dyes (N749 & N3) are (1.4 &1.6 eV) respectively. The structural properties (XRD), (FTIR) and (SEM) for the sample prepared were investigated and (J-V) characteristics was stu
... Show MoreThe study aims to identify the impact of the implementation of the integrated education strategy in the curriculum of the Arabic language for the seventh grade on the academic achievement in the schools of the capital Amman. The researcher adopted the experimental method, where two divisions of the seventh grade students were chosen from the secondary school for girls. The sample of the study was 60 students divided into two equal groups: 30 students represented the experimental group (A) and (30) students represented the control group. To collect the needed data, a test of (40) Multiple Choices was used. The results showed statistically significant differences between the mean scores of the experimental group who were taught acc
... Show MoreHeavy oil is classified as unconventional oil resource because of its difficulty to recover in its natural state, difficulties in transport and difficulties in marketing it. Upgrading solution to the heavy oil has positive impact technically and economically specially when it will be a competitive with conventional oils from the marketing prospective. Developing Qaiyarah heavy oil field was neglected in the last five decades, the main reason was due to the low quality of the crude oil resulted in the high viscosity and density of the crude oil in the field which was and still a major challenge putting them on the major stream line of production in Iraq. The low quality of the crude properties led to lower oil prices in the global markets
... Show MoreIn this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.
Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit
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