In 1908 , the American poet Ezra Pound (1885-1972) , the central figure in the modern movement who was the driving force behind several movements , notably Imagism and Vorticism , met the Irish poet W. B. Yeats in London . Pound was employed as his secretary and the two soon became close friends . He found Yeats a realist, symbolist and a metaphysical poet with an uncanny power over words and regarded him the greatest living poet .The poetical style and the occult beliefs of the Irish poet drew the attention of the American Imagist .During the war, Pound and Yeats lived together at Stone Cottage in Sussex studying Japanese literature .Speaking of Yeats , T. S. Eliot described him as "one of those few whose history is the history of their own time , who are a part of the consciousness of an age which cannot be understood without them"1.His poems have "passionate thought, consistent technique, controlled concentration , deliberate delight in the exercise of art "2.
It is difficult, in fact , to understand the poetry of Yeats without knowing some of its important clues. His various symbols, visions and mysticism, allusions to people and events, interest in mythology and folklore require a reasonable knowledge of the poet's frame of mind. As a leading symbolist, Yeats used the symbols to convey to others (what he thought) what could not otherwise be communicated. For him the employment of symbols was not only a poetic device; it was a kind of discipline. He asserts that "A symbol is indeed the only expression of some invisible essence, a transparent lamp about a spiritual flame"3. He describes the work of a symbol saying that symbols have the ability to give "dumb things voices and bodiless things bodies"4. It is not surprising then to see him attracted to the poetry of William Blake. He "also found in Blake's writing his idea of paired opposites – soul and self, body and soul, love and death, chance and choice, 'subjective' and 'objective', conflicting yet establishing a unity in a man's life and in history"5. Most of Yeats' poetry is not quietly intelligible without a good reading of his book A Vision which contains his assumptions, visions and the elements of his symbolic system.
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In this paper the variable structure control theory is utilized to derive a discontinuous controller to the magnetic levitation system. The magnetic levitation system model is considered uncertain, which subjected to the uncertainty in system parameters, also it is open-loop unstable and strongly nonlinear. The proposed variable structure control to magnetic levitation system is proved, and the area of attraction is determined. Additionally, the chattering, which induced due to the discontinuity in control law, is attenuated by using a non-smooth approximate. With this approximation the resulted controller is a continuous variable structure controller with a determined steady state error according to the selected control
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With the recent developments of technology and the advances in artificial intelligent and machine learning techniques, it becomes possible for the robot to acquire and show the emotions as a part of Human-Robot Interaction (HRI). An emotional robot can recognize the emotional states of humans so that it will be able to interact more naturally with its human counterpart in different environments. In this article, a survey on emotion recognition for HRI systems has been presented. The survey aims to achieve two objectives. Firstly, it aims to discuss the main challenges that face researchers when building emotional HRI systems. Secondly, it seeks to identify sensing channels that can be used to detect emotions and provides a literature review
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Visible light communication (VLC) is an upcoming wireless technology for next-generation communication for high-speed data transmission. It has the potential for capacity enhancement due to its characteristic large bandwidth. Concerning signal processing and suitable transceiver design for the VLC application, an amplification-based optical transceiver is proposed in this article. The transmitter consists of a driver and laser diode as the light source, while the receiver contains a photodiode and signal amplifying circuit. The design model is proposed for its simplicity in replacing the trans-impedance and transconductance circuits of the conventional modules by a simple amplification circuit and interface converter. Th
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<p>Photovoltaic (PV) systems are becoming increasingly popular; however, arc faults on the direct current (DC) side are becoming more widespread as a result of the effects of aging as well as the trend toward higher DC voltage levels, posing severe risk to human safety and system stability. The parallel arc faults present higher level of current as compared with the series arc faults, making it more difficult to spot the series arc. In this paper and for the aim of condition monitoring, the features of a DC series arc fault are analyzed by analysing the arc features, performing model’s simulation in PSCAD, and carrying out experimental studies. Various arc models are simulated and investigated; for low current arcs, the heur
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This study investigates asset returns within the Iraq Stock Exchange by employing both the Fama-MacBeth regression model and the Fama-French three-factor model. The research involves the estimation of cross-sectional regressions wherein model parameters are subject to temporal variation, and the independent variables function as proxies. The dataset comprises information from the first quarter of 2010 to the first quarter of 2024, encompassing 22 publicly listed companies across six industrial sectors. The study explores methodological advancements through the application of the Single Index Model (SIM) and Kernel Weighted Regression (KWR) in both time series and cross-sectional analyses. The SIM outperformed the K
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In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.
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