A critics ,Shugaa Muslim Al-Aany, has specific critical principles in his branch
classifications for the type of the novel that is linked with its sources and what is adopted
of critical approaches and curriculums. The novel by its type as a literary one has
occupied Al-Any's critical importance very much ,he has divided it historically according
to its historical development ,the impact of dr.Abd Al-Muhassen Tha Badr's divisions on
Al-Any cannot hidden.
In his speech about the origin of novel and story art generally , Al-Any becomes
between the acknowledgement of the affect of Al-Mgma in rising of this art and denied its
affect at last. He has classified the novel also as a stylistic classification:(an impressionist
novel);(A novel of current of consciousness);( a novel of time density),(a scene novel);(Al-
Musrwah);(a monologue novel) or(a novel of the one sound);(polyphone)or (polyphonies) ;(
a novel of Narcissistic structure) .Besides ,he depends on the social and philosophical
principles when he has classified the novel into (the old social novel)and (the new
dramatic novel).The one can see confusion in his classifications of the novel (Jalel
Khaled),he has classified it as the first artistic analytical novel ,a romantic one once , an
educational in another time, But the critics realize that this confusion that fall within it ,so
he restudies it for decades to prove that it is a intellectual acculturation and rearing
although it violates in its art other novels of the same generation.
Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f
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Test results of six half-scale reinforced concrete flat plates connections with an opening in the vicinity of the column are reported. The test specimens represent a portion of a slab bounded by the lines of contraflexure around the column. The tests were designed to study the effect of openings on the punching shear behavior of the slab-column connections. The test parameters were the location and the size of the openings. One specimen had no opening and the remaining five had various arrangements of openings around the column. All specimens were cast with normal density concrete of approximately 30 MPa compressive strength. The openings in the specimens were square, with the sides parallel to the sides of the column. Three sizes of ope
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There are two main categories of force control schemes: hybrid position-force control and impedance control. However, the former does not take into account the dynamic interaction between the robot’s end effector and the environment. In contrast, impedance control includes regulation and stabilization of robot motion by creating a mathematical relationship between the interaction forces and the reference trajectories. It involves an energetic pair of a flow and an effort, instead of controlling a single position or a force. A mass-spring-damper impedance filter is generally used for safe interaction purposes. Tuning the parameters of the impedance filter is important and, if an unsuitable strategy is used, this can lead to unstabl
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The thermal distribution in the diseased tissue treated by different methods faces the problem of an uncontrollable defused heat. In the present article, we use a plasmonic bowtie nanoantenna working in the near infrared region to enhance the temperature confinement in the tissue. The Computer Simulation Technology Studio Suite package version 2019 was used to execute the design of both plasmonic nanoantenna and the tissue. Gold nanostructure and silicon carbide dioxide are the components the plasmonic nanoantenna in the bowtie shape. The results showed that the distance between the tumor tissue and the antenna is important to determine the intensity field where the maximum field is 5.9*107 V/m at a distance of 100 nm. The maximum
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Copper with different concentrations doped with zinc oxide nanoparticles were prepared from a mixture of zinc acetate and copper acetate with sodium hydroxide in aqueous solution. The structure of the prepared samples was done by X-ray diffraction, atomic force microscopy (AFM) and UV-VIS absorption spectrophotometer. Debye-Scherer formula was used to calculate the size of the prepared samples. The band gap of the nanoparticle ZnO was determined by using UV-VIS optical spectroscopy.
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In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p
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