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A Study of the generation of laser soliton from spontaneous emission by ring cavity with carbon nanotube
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We demonstrate a behavior of laser pulse grows through fiber laser inside and output cavity with a soliton fiber laser based on the multi-wall carbon nanotube saturable absorber (SA), we investigate the effects of a saturable absorber parameter on the mode-locking of a realistic Erbium fiber ring laser. Generalized nonlinear Schrodinger equation including the nonlinear effects as gain dispersion, second anomalous group velocity dispersion (GVD), self phase modulation (SPM), and two photon absorption used to describe pulse evolution. An analytical method has been used to understand and to quantify the role of the SA parameter on the propagation dynamics of pulse laser. We compute the chirp, power, width and phase of the soliton for range of SA parameters and we studied stability against nonlinear effects at different SA parameter ranges.

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Publication Date
Sun Jan 01 2023
Journal Name
Inorganic Chemistry Communications
Detection of nitrotyrosine (Alzheimer's agent) by B24N24 nano cluster: A comparative DFT and QTAIM insight
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A nano-sensor for nitrotyrosine (NT) molecule was found by studying the interactions of NT molecule with new B24N24 nanocages. It was calculated using density functionals in this case. The predicted adsorption mechanisms included physical and chemical adsorption with the adsorption energy of −2.76 to −4.60 and −11.28 to −15.65 kcal mol−1, respectively. The findings show that an NT molecule greatly increases the electrical conductivity of a nanocage by creating electronic noise. Moreover, NT adsorption in the most stable complexes significantly affects the Fermi level and the work function. This means the B24N24 nanocage can detect NT as a Φ–type sensor. The recovery time was determined to be 0.3 s. The sensitivity of pure BN na

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Sat Apr 01 2023
Journal Name
Chemical Methodologies
A Novel Design for Gas Sensor of Zinc Oxide Nanostructure Prepared by Hydrothermal Annealing Technique
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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of The College Of Languages (jcl)
A Pragmatic Analysis of Implied Meaning in Selected Poems by T.S. Eliot and Al-Sayyab
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In addition to its basic communicative function, language can be used to imply information that is not actually stated, i.e. addressers do not always state exactly (or directly) what they mean. Such instances fall within the domain of pragmatics in that they have to do with how addressers use language to communicate in a particular situation by implication rather than by direct statement. The researcher attempts to demonstrate that the beauty and the multiple layers of meaning in poetry can be better explored if the addressee looks at the lines from a pragmatic perspective in search for implied meaning. There are many devices that can convey implied meaning in poetry, among which are 'rhetorical', 'figurative' or 'literary' devices. But

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
ADJUSTING OFF – CENTERING PROCESS FOR A BLOW MOLDED PLASTIC PRODUCT BY USE OF WINQSB SOFTWARE
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In most manufacturing processes, and in spite of statistical control, several process capability indices refer to non conformance of the true mean (µc ) from the target mean ( µT ), and the variation is also high. In this paper, data have been analyzed and studied for a blow molded plastic product (Zahi Bottle) (ZB). WinQSB software was used to facilitate the statistical process control, and process capability analysis and some of capability indices. The relationship between different process capability indices and the true mean of the process were represented, and then with the standard deviation (σ ), of achievement of process capability value that can reduce the standard deviation value and improve production out of theoretical con

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Publication Date
Mon Feb 01 2021
Journal Name
Proceedings Of The Institution Of Civil Engineers - Structures And Buildings
Effect of soil saturation on load transfer in a pile excited by pure vertical vibration
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A comparison between the resistance capacity of a single pile excited by two opposite rotary machines embedded in dry and saturated sandy soil was considered experimentally. A small-scale physical model was manufactured to accomplish the experimental work in the laboratory. The physical model consists of: two small motors supplied with eccentric mass 0·012 kg and eccentric distance 20 mm representing the two opposite rotary machines, an aluminum shaft with 20 mm in diameter as the pile, and a steel plate with dimensions of (160 × 160 × 20 mm) as a pile cap. The experimental work was achieved taking the following parameters into consideration, pile embedment depth ratio (L/d; length to diameter) and operating freq

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Publication Date
Sat Apr 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

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Publication Date
Tue Jun 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Treatment of Al-Muthanna Petroleum Refinery Wastewater by Electrocoagulation Using a Tubular batch Electrochemical Reactor
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Abstract<p>An electrocoagulation process has been used to eliminate the chemical oxygen demand (COD) from wastewaters discharged from the Al-Muthanna petroleum refinery plant. In this process, a circular aluminum bar was used as a sacrificial anode, and hallow cylinder made from stainless steel was used as a cathode in a tubular batch electrochemical Reactor. Impacts of the operating factors like current density (5-25mAcm<sup>-2</sup>), NaCl addition at concentrations (0-2g/l), and pH at values (3-11) on the COD removal efficiency were studied.</p><p>Results revealed that the increase in current density increases the COD removal efficiency, whereas an increase</p> ... Show More
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Publication Date
Sat Jan 12 2019
Journal Name
Journal Of The College Of Education For Women
Strategic Analysis for the Grain Grinders' establishments in Baghdad governorate and problems suffered by the industry, along with the possibility to predict its products
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Geography of industry has been considered a branch of important economic geographical branches. This importance has been regarded as a reflection on the industrial sector contribution in economies of any state since they contribute into the total national product ; it also assimilates a huge number of labor hands . The industry of grains grinding has been considered as one of the main food industries having a main role in satisfying the need of the population from the foods. The industry is continued to use the food as daily meal . Here, it should predict the population in Baghdad and for every district until the end of 2025 and knowing either these grains grinders are able to meet and satisfy the needs of populations of flours, making s

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