Search results for: Boolean functions representation

Authors: Shende Suraj Balu, A. B. Deoghare, K. M. Pandey

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The human middle ear (ME) is a delicate and vital organ. It has a complex structure that performs various functions such as receiving sound pressure and producing vibrations of eardrum and propagating it to inner ear. It consists of Tympanic Membrane (TM), three auditory ossicles, various ligament structures and muscles. Incidents such as traumata, infections, ossification of ossicular structures and other pathologies may damage the ME organs. The conditions can be surgically treated by employing prosthesis. However, the suitability of the prosthesis needs to be examined in advance prior to the surgery. Few decades ago, this issue was addressed and analyzed by developing an equivalent representation either in the form of spring mass system, electrical system using R-L-C circuit or developing an approximated CAD model. But, nowadays a three-dimensional ME model can be constructed using micro X-Ray Computed Tomography (μCT) scan data. Moreover, the concern about patient specific integrity pertaining to the disease can be examined well in advance. The current research work emphasizes to develop the ME model from the stacks of μCT images which are used as input file to MIMICS Research 19.0 (Materialise Interactive Medical Image Control System) software. A stack of CT images is converted into geometrical surface model to build accurate morphology of ME. The work is further extended to understand the dynamic behaviour of Harmonic response of the stapes footplate and umbo for different sound pressure levels applied at lateral side of eardrum using finite element approach. The pathological condition Cholesteatoma of ME is investigated to obtain peak to peak displacement of stapes footplate and umbo. Apart from this condition, other pathologies, mainly, changes in the stiffness of stapedial ligament, TM thickness and ossicular chain separation and fixation are also explored. The developed model of ME for pathologies is validated by comparing the results available in the literatures and also with the results of a normal ME to calculate the percentage loss in hearing capability.

Keywords: Computed tomography, human middle ear, harmonic response, pathologies, tympanic membrane.

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Authors: Mikhail Vladimirovich Deryabin, Morten Willatzen

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In this work, we address theoretically the influence of red and white Gaussian noise for electronic energies and eigenstates of cylindrically shaped quantum dots. The stochastic effect can be imagined as resulting from crystal-growth statistical fluctuations in the quantum-dot material composition. In particular we obtain analytical expressions for the eigenvalue shifts and electronic envelope functions in the k . p formalism due to stochastic variations in the confining band-edge potential. It is shown that white noise in the band-edge potential leaves electronic properties almost unaffected while red noise may lead to changes in state energies and envelopefunction amplitudes of several percentages. In the latter case, the ensemble-averaged envelope function decays as a function of distance. It is also shown that, in a stochastic system, constant ensembleaveraged envelope functions are the only bounded solutions for the infinite quantum-wire problem and the energy spectrum is completely discrete. In other words, the infinite stochastic quantum wire behaves, ensemble-averaged, as an atom.

Keywords: cylindrical quantum dots, electronic eigen energies, red and white Gaussian noise, ensemble averaging effects.

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Authors: Vera Varazashvili, Murman Tsarakhov, Tamar Mirianashvili, Teimuraz Pavlenishvili, Tengiz Machaladze, Mzia Khundadze

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Standard Gibbs energy of formation ΔGfor(298.15) of lanthanide-iron double oxides of garnet-type crystal structure R3Fe5O12 - RIG (R – are rare earth ions) from initial oxides are evaluated. The calculation is based on the data of standard entropies S298.15 and standard enthalpies ΔH298.15 of formation of compounds which are involved in the process of garnets synthesis. Gibbs energy of formation is presented as temperature function ΔGfor(T) for the range 300-1600K. The necessary starting thermodynamic data were obtained from calorimetric study of heat capacity – temperature functions and by using the semi-empirical method for calculation of ΔH298.15 of formation. Thermodynamic functions for standard temperature – enthalpy, entropy and Gibbs energy - are recommended as reference data for technological evaluations. Through the structural series of rare earth-iron garnets the correlation between thermodynamic properties and characteristics of lanthanide ions are elucidated.

Keywords: Calorimetry, entropy, enthalpy, heat capacity, gibbs energy of formation, rare earth iron garnets.

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Authors: Jiann-Ming Wu, Hsiao-Chang Chen, Chun-Chang Wu, Pei-Hsun Hsu

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This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.

Keywords: Blind image deconvolution, linear shift-invariant(LSI), linear image degradation model, radial basis functions (rbf), recursive function, annealed Hopfield neural networks.

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Authors: Banaja Mohanty, Prakash Kumar Hota

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This paper represents performance of particle swarm optimisation (PSO) algorithm based integral (I) controller and proportional-integral controller (PI) for interconnected hydro-thermal automatic generation control (AGC) with generation rate constraint (GRC) and Thyristor controlled phase shifter (TCPS) in series with tie line. The control strategy of TCPS provides active control of system frequency. Conventional objective function integral square error (ISE) and another objective function considering square of derivative of change in frequencies of both areas and change in tie line power are considered. The aim of designing the objective function is to suppress oscillation in frequency deviations and change in tie line power oscillation. The controller parameters are searched by PSO algorithm by minimising the objective functions. The dynamic performance of the controllers I and PI, for both the objective functions, are compared with conventionally optimized I controller.

Keywords: Automatic generation control (AGC), Generation rate constraint (GRC), Thyristor control phase shifter (TCPS), Particle swarm optimization (PSO).

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Authors: A. Habibizad Navin, A. Sadighi, M. Naghian Fesharaki, M. Mirnia, M. Teshnelab, R. Keshmiri

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This paper presents a new data oriented model of image. Then a representation of it, ADBT, is introduced. The ability of ADBT is clustering, segmentation, measuring similarity of images etc, with desired precision and corresponding speed.

Keywords: Data oriented modelling, image, clustering, segmentation, classification, ADBT and image processing.

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Authors: Hany Alashwal, Safaai Deris, Razib M. Othman

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Understanding proteins functions is a major goal in the post-genomic era. Proteins usually work in context of other proteins and rarely function alone. Therefore, it is highly relevant to study the interaction partners of a protein in order to understand its function. Machine learning techniques have been widely applied to predict protein-protein interactions. Kernel functions play an important role for a successful machine learning technique. Choosing the appropriate kernel function can lead to a better accuracy in a binary classifier such as the support vector machines. In this paper, we describe a Bayesian kernel for the support vector machine to predict protein-protein interactions. The use of Bayesian kernel can improve the classifier performance by incorporating the probability characteristic of the available experimental protein-protein interactions data that were compiled from different sources. In addition, the probabilistic output from the Bayesian kernel can assist biologists to conduct more research on the highly predicted interactions. The results show that the accuracy of the classifier has been improved using the Bayesian kernel compared to the standard SVM kernels. These results imply that protein-protein interaction can be predicted using Bayesian kernel with better accuracy compared to the standard SVM kernels.

Keywords: Bioinformatics, Protein-protein interactions, Bayesian Kernel, Support Vector Machines.

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Authors: M.Suganthi, M.Madheswaran

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This paper presents a novel approach to finding a priori interesting regions in mammograms. In order to delineate those regions of interest (ROI-s) in mammograms, which appear to be prominent, a topographic representation called the iso-level contour map consisting of iso-level contours at multiple intensity levels and region segmentation based-thresholding have been proposed. The simulation results indicate that the computed boundary gives the detection rate of 99.5% accuracy.

Keywords: Breast Cancer, Mammogram, and Segmentation.

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Authors: Tao Zou, Zhengnan Zhou

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In the context of global climate change, flooding and sea level rise is increasingly threatening coastal urban areas, in which large population is continuously concentrated. Dutch experiences in urban water system management provide high reference value for sustainable coastal urban development projects. Preliminary studies shows the urban water system in Almere, a typical Dutch polder city, have three kinds of operational modes, achieving functions as: (1) coastline control – strong multiple damming system prevents from storm surges and maintains sufficient capacity upon risks; (2) high flexibility – large area and widely scattered open water system greatly reduce local runoff and water level fluctuation; (3) internal water maintenance – weir and sluice system maintains relatively stable water level, providing excellent boating and landscaping service, coupling with water circulating model maintaining better water quality. Almere has provided plenty of hints and experiences for ongoing development of coastal cities in emerging economies.

Keywords: Coastal area, resilience, sustainable urban watersystem, water circulation.

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Authors: Apoorva Vinod, Archana Mathur, Snehanshu Saha

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Though there exists a plethora of Activation Functions (AFs) used in single and multiple hidden layer Neural Networks (NN), their behavior always raised curiosity, whether used in combination or singly. The popular AFs – Sigmoid, ReLU, and Tanh – have performed prominently well for shallow and deep architectures. Most of the time, AFs are used singly in multi-layered NN, and, to the best of our knowledge, their performance is never studied and analyzed deeply when used in combination. In this manuscript, we experiment on multi-layered NN architecture (both on shallow and deep architectures; Convolutional NN and VGG16) and investigate how well the network responds to using two different AFs (Sigmoid-Tanh, Tanh-ReLU, ReLU-Sigmoid) used alternately against a traditional, single (Sigmoid-Sigmoid, Tanh-Tanh, ReLU-ReLU) combination. Our results show that on using two different AFs, the network achieves better accuracy, substantially lower loss, and faster convergence on 4 computer vision (CV) and 15 Non-CV (NCV) datasets. When using different AFs, not only was the accuracy greater by 6-7%, but we also accomplished convergence twice as fast. We present a case study to investigate the probability of networks suffering vanishing and exploding gradients when using two different AFs. Additionally, we theoretically showed that a composition of two or more AFs satisfies Universal Approximation Theorem (UAT).

Keywords: Activation Function, Universal Approximation function, Neural Networks, convergence.

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Authors: Saeed Sarabadan, Mehran Nikarya, Kouroah Parand

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The magnetohydrodynamic (MHD) Falkner-Skan equations appear in study of laminar boundary layers flow over a wedge in presence of a transverse magnetic field. The partial differential equations of boundary layer problems in presence of a transverse magnetic field are reduced to MHD Falkner-Skan equation by similarity solution methods. This is a nonlinear ordinary differential equation. In this paper, we solve this equation via spectral collocation method based on Bessel functions of the first kind. In this approach, we reduce the solution of the nonlinear MHD Falkner-Skan equation to a solution of a nonlinear algebraic equations system. Then, the resulting system is solved by Newton method. We discuss obtained solution by studying the behavior of boundary layer flow in terms of skin friction, velocity, various amounts of magnetic field and angle of wedge. Finally, the results are compared with other methods mentioned in literature. We can conclude that the presented method has better accuracy than others.

Keywords: MHD Falkner-Skan, nonlinear ODE, spectral collocation method, Bessel functions, skin friction, velocity.

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Authors: P. Sowa

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The new idea of analyze of power system failure with use of artificial neural network is proposed. An analysis of the possibility of simulating phenomena accompanying system faults and restitution is described. It was indicated that the universal model for the simulation of phenomena in whole analyzed range does not exist. The main classic method of search of optimal structure and parameter identification are described shortly. The example with results of calculation is shown.

Keywords: Dynamic equivalents, Network reduction, Neural networks, Power system analysis.

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Authors: Anil Kumar

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Supersymmetric Quantum Mechanics is an interesting framework to analyze nonrelativistic quantal problems. Using these techniques, we construct a family of strictly isospectral Hulth´en potentials. Isospectral wave functions are generated and plotted for different values of the deformation parameter.

Keywords: Hulth´en potential, Isospectral Hamiltonian.

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Authors: Ali Keshavarzi, Fereydoon Sarmadian

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Investigation of soil properties like Cation Exchange Capacity (CEC) plays important roles in study of environmental reaserches as the spatial and temporal variability of this property have been led to development of indirect methods in estimation of this soil characteristic. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. Then, multivariate regression and neural network model (feedforward back propagation network) were employed to develop a pedotransfer function for predicting soil parameter using easily measurable characteristics of clay and organic carbon. The performance of the multivariate regression and neural network model was evaluated using a test data set. In order to evaluate the models, root mean square error (RMSE) was used. The value of RMSE and R2 derived by ANN model for CEC were 0.47 and 0.94 respectively, while these parameters for multivariate regression model were 0.65 and 0.88 respectively. Results showed that artificial neural network with seven neurons in hidden layer had better performance in predicting soil cation exchange capacity than multivariate regression.

Keywords: Easily measurable characteristics, Feed-forwardback propagation, Pedotransfer functions, CEC.

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Authors: Anupama Pande, Ashok Kumar Thakur, Swapnoneel Roy

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A complex valued neural network is a neural network which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in signal processing. In Neural networks, generalized mean neuron model (GMN) is often discussed and studied. The GMN includes a new aggregation function based on the concept of generalized mean of all the inputs to the neuron. This paper aims to present exhaustive results of using Generalized Mean Neuron model in a complex-valued neural network model that uses the back-propagation algorithm (called -Complex-BP-) for learning. Our experiments results demonstrate the effectiveness of a Generalized Mean Neuron Model in a complex plane for signal processing over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error required on a Generalized Mean neural network model. Some inherent properties of this complex back propagation algorithm are also studied and discussed.

Keywords: Complex valued neural network, Generalized Meanneuron model, Signal processing.

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Authors: R. Mofeed, N. Elgendy

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Cinema constructs mind-spaces that reflect inherent human thoughts and emotions. As a representational art, Cinema would introduce comprehensive images of life phenomena in different ways. The term “represent” suggests verity of meanings; bring into presence, replace or typify. In that sense, Cinema may present a phenomenon through direct embodiment, or introduce a substitute image that replaces the original phenomena, or typify it by relating the produced image to a more general category through a process of abstraction. This research is interested in questioning the type of images that Egyptian Cinema introduces to informal urbanism and how these images were conditioned and reshaped in the last twenty years. The informalities/slums phenomenon first appeared in Egypt and, particularly, Cairo in the early sixties, however, this phenomenon was completely ignored by the state and society until the eighties, and furthermore, its evident representation in Cinema was by the mid-nineties. The Informal City represents the illegal housing developments, and it is a fast growing form of urbanization in Cairo. Yet, this expanding phenomenon is still depicted as the minority, exceptional and marginal through the Cinematic lenses. This paper aims at tracing the forms of representations of the urban informalities in the Egyptian Cinema between 1994 and 2014, and how did that affect the popular mind and its perception of these areas. The paper runs two main lines of inquiry; the first traces the phenomena through a chronological and geographical mapping of the informal urbanism has been portrayed in films. This analysis is based on an academic research work at Cairo University in Fall 2014. The visual tracing through maps and timelines allowed a reading of the phases of ignorance, presence, typifying and repetition in the representation of this huge sector of the city through more than 50 films that has been investigated. The analysis clearly revealed the “portrayed image” of informality by the Cinema through the examined period. However, the second part of the paper explores the “perceived image”. A designed questionnaire is applied to highlight the main features of that image that is perceived by both inhabitants of informalities and other Cairenes based on watching selected films. The questionnaire covers the different images of informalities proposed in the Cinema whether in a comic or a melodramatic background and highlight the descriptive terms used, to see which of them resonate with the mass perceptions and affected their mental images. The two images; “portrayed” and “perceived” are then to be encountered to reflect on issues of repetitions, stereotyping and reality. The formulated stereotype of informal urbanism is finally outlined and justified in relation to both production consumption mechanisms of films and the State official vision of informalities.

Keywords: Cairo, cinema, informal urbanism, representation, stereotype.

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Authors: D. R. Jain

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The aim of this paper is to use matrix representation of Fuzzy soft sets for proving some equalities connected with Fuzzy soft sets based on set-operations.

Keywords: Equality, Fuzzy soft matrix, Fuzzy soft sets, operations.

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Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

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Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: Artificial Immune System, Breast Cancer Diagnosis, Euclidean Function, Gaussian Function.

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Authors: Guolong Zhong, Venkatesh Chennam Vijay, Ilias Oraifige

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In the last 20 years, Knowledge Based Engineering (KBE) has shown its advantages in product development in different engineering areas such as automation, mechanical, civil and aerospace engineering in terms of digital design automation and cost reduction by automating repetitive design tasks through capturing, integrating, utilising and reusing the existing knowledge required in various aspects of the product design. However, in primary design stages, the descriptive information of a product is discrete and unorganized while knowledge is in various forms instead of pure data. Thus, it is crucial to have an integrated product model which can represent the entire product information and its associated knowledge at the beginning of the product design. One of the shortcomings of the existing product models is a lack of required knowledge representation in various aspects of product design and its mapping to an interoperable schema. To overcome the limitation of the existing product model and methodologies, two key factors are considered. First, the product model must have well-defined classes that can represent the entire product information and its associated knowledge. Second, the product model needs to be represented in an interoperable schema to ensure a steady data exchange between different product modelling platforms and CAD software. This paper introduced a method to provide a general product model as a generative representation of a product, which consists of the geometry information and non-geometry information, through a product modelling framework. The proposed method for capturing the knowledge from the designers through a knowledge file provides a simple and efficient way of collecting and transferring knowledge. Further, the knowledge schema provides a clear view and format on the data that needed to be gathered in order to achieve a unified knowledge exchange between different platforms. This study used a game-based platform to make product modelling environment accessible for non-engineers. Further the paper goes on to test use case based on the proposed game-based product modelling environment to validate the effectiveness among non-engineers.

Keywords: Game-based learning, knowledge based engineering, product modelling, design automation.

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Authors: Asfar Ali Khan

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Analytical expression for maximum power transfer through a transmission line limited by voltage stability has been formulated using exact representation of transmission line with ABCD parameters. The expression has been used for plotting PV curve at different power factors of a radial transmission line. Limiting values of reactive power have been obtained.

Keywords: Power Transfer, PV Curve, Voltage Stability.

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Authors: H. B. Mehta, Vipul M. Patel, Jyotirmay Banerjee

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The present paper discusses the prediction of gas-liquid two-phase frictional pressure drop in a 2.12 mm horizontal circular minichannel using Artificial Neural Network (ANN). The experimental results are obtained with air as gas phase and water as liquid phase. The superficial gas velocity is kept in the range of 0.0236 m/s to 0.4722 m/s while the values of 0.0944 m/s, 0.1416 m/s and 0.1889 m/s are considered for superficial liquid velocity. The experimental results are predicted using different Artificial Neural Network (ANN) models. Networks used for prediction are radial basis, generalised regression, linear layer, cascade forward back propagation, feed forward back propagation, feed forward distributed time delay, layer recurrent, and Elman back propagation. Transfer functions used for networks are Linear (PURELIN), Logistic sigmoid (LOGSIG), tangent sigmoid (TANSIG) and Gaussian RBF. Combination of networks and transfer functions give different possible neural network models. These models are compared for Mean Absolute Relative Deviation (MARD) and Mean Relative Deviation (MRD) to identify the best predictive model of ANN.

Keywords: Minichannel, Two-Phase Flow, Frictional Pressure Drop, ANN, MARD, MRD.

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Authors: J.-C. Cexus, A.O. Boudraa

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In this paper, a new approach for target recognition based on the Empirical mode decomposition (EMD) algorithm of Huang etal. [11] and the energy tracking operator of Teager [13]-[14] is introduced. The conjunction of these two methods is called Teager-Huang analysis. This approach is well suited for nonstationary signals analysis. The impulse response (IR) of target is first band pass filtered into subsignals (components) called Intrinsic mode functions (IMFs) with well defined Instantaneous frequency (IF) and Instantaneous amplitude (IA). Each IMF is a zero-mean AM-FM component. In second step, the energy of each IMF is tracked using the Teager energy operator (TEO). IF and IA, useful to describe the time-varying characteristics of the signal, are estimated using the Energy separation algorithm (ESA) algorithm of Maragos et al .[16]-[17]. In third step, a set of features such as skewness and kurtosis are extracted from the IF, IA and IMF energy functions. The Teager-Huang analysis is tested on set of synthetic IRs of Sonar targets with different physical characteristics (density, velocity, shape,? ). PCA is first applied to features to discriminate between manufactured and natural targets. The manufactured patterns are classified into spheres and cylinders. One hundred percent of correct recognition is achieved with twenty three echoes where sixteen IRs, used for training, are free noise and seven IRs, used for testing phase, are corrupted with white Gaussian noise.

Keywords: Target recognition, Empirical mode decomposition, Teager-Kaiser energy operator, Features extraction.

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Authors: Ilona Copik

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The aim of this study is to analyze the representation of memories of the forced displacement of Poles and Germans from the eastern territories in 1945 as depicted by Polish and German feature films between the years 1945-1960. The aftermath of World War II and the Allied agreements concluded at Yalta and Potsdam (1945) resulted in changes in national borders in Central and Eastern Europe and the large-scale transfer of civilians. The westward migration became a symbol of the new post-war division of Europe, new spheres of influence separated by the Iron Curtain. For years it was a controversial topic in both Poland and Germany due to the geopolitical alignment (the socialist East and capitalist West of Europe), as well as the unfinished debate between the victims and perpetrators of the war. The research premise is to take a comparative view of the conflicted cultures of Polish and German memory, to reflect on the possibility of an international dialogue about the past recorded in film images, and to discover the potential of film as a narrative warning against totalitarian inclinations. Until now, films made between 1945 and 1960 in Poland and the German occupation zones have been analyzed mainly in the context of artistic strategies subordinated to ideology and historical politics. In this study, the intention is to take a critical approach leading to the recognition of how films work as collective memory media, how they reveal the mechanisms of memory/ forgetting, and what settlement topoi and migration myths they contain. The main hypothesis is that feature films about forced displacement, in addition to the politics of history - separate in each country - reveal comparable transnational individual experiences: the chaos of migration, the trauma of losing one's home, the conflicts accompanying the familiar/foreign, the difficulty of cultural adaptation, the problem of lost identity, etc.

Keywords: Forced displacement, Polish and German cinema, war victims, World War II.

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Authors: Marcus Banda

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In this article the influence of higher frequency effects in addition to a special damper design on the electrical behavior of a synchronous generator main exciter machine is investigated. On the one hand these machines are often highly stressed by harmonics from the bridge rectifier thus facing additional eddy current losses. On the other hand the switching may cause the excitation of dangerous voltage peaks in resonant circuits formed by the diodes of the rectifier and the commutation reactance of the machine. Therefore modern rotating exciters are treated like synchronous generators usually modeled with a second order equivalent circuit. Hence the well known Standstill Frequency Response Test (SSFR) method is applied to a test machine in order to determine parameters for the simulation. With these results it is clearly shown that higher frequencies have a strong impact on the conventional equivalent circuit model. Because of increasing field displacement effects in the stranded armature winding the sub-transient reactance is even smaller than the armature leakage at high frequencies. As a matter of fact this prevents the algorithm to find an equivalent scheme. This issue is finally solved using Laplace transfer functions fully describing the transient behavior at the model ports.

Keywords: Synchronous exciter machine, Linear transfer function, SSFR, Equivalent Circuit

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Authors: Érica Lima

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In the digital era, in which we have an avalanche of information, it is not new that the Internet has brought new modes of communication and knowledge access. Characterized by the multiplicity of discourses, opinions, beliefs and cultures, the web is a space of political-ideological dimensions where people (who often do not know each other) interact and create representations, deconstruct stereotypes, and redefine identities. Currently, the translator needs to be able to deal with digital spaces ranging from specific software to social media, which inevitably impact on his professional life. One of the most impactful ways of being seen in cyberspace is the participation in social networking groups. In addition to its ability to disseminate information among participants, social networking groups allow a significant personal and social exposure. Such exposure is due to the visibility of each participant achieved not only on its personal profile page, but also in each comment or post the person makes in the groups. The objective of this paper is to study the representations of translators and translation process on the Internet, more specifically in publications in two Brazilian groups of great influence on the Facebook: "Translators/Interpreters" and "Translators, Interpreters and Curious". These chosen groups represent the changes the network has brought to the profession, including the way translators are seen and see themselves. The analyzed posts allowed a reading of what common sense seems to think about the translator as opposed to what the translators seem to think about themselves as a professional class. The results of the analysis lead to the conclusion that these two positions are antagonistic and sometimes represent conflict of interests: on the one hand, the society in general consider the translator’s work something easy, therefore it is not necessary to be well remunerated; on the other hand, the translators who know how complex a translation process is and how much it takes to be a good professional. The results also reveal that social networking sites such as Facebook provide more visibility, but it takes a more active role from the translator to achieve a greater appreciation of the profession and more recognition of the role of the translator, especially in face of increasingly development of automatic translation programs.

Keywords: Facebook, social representation, translation, translator.

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Authors: Boutahar Lhoucine, El Bikri Khalid, Benamar Rhali

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The effects of large vibration amplitudes on the first axisymetric mode shape of thin isotropic annular plates having both edges clamped are examined in this paper. The theoretical model based on Hamilton’s principle and spectral analysis by using a basis of Bessel’s functions is adapted اhere to the case of annular plates. The model effectively reduces the large amplitude free vibration problem to the solution of a set of non-linear algebraic equations.

The governing non-linear eigenvalue problem has been linearised in the neighborhood of each resonance and a new one-step iterative technique has been proposed as a simple alternative method of solution to determine the basic function contributions to the non-linear mode shape considered.

Numerical results are given for the first non-linear mode shape for a wide range of vibration amplitudes. For each value of the vibration amplitude considered, the corresponding contributions of the basic functions defining the non-linear transverse displacement function and the associated non-linear frequency, the membrane and bending stress distributions are given. By comparison with the iterative method of solution, it was found that the present procedure is efficient for a wide range of vibration amplitudes, up to at least 1.8 times the plate thickness,

Keywords: Non-linear vibrations, Annular plates, Large vibration amplitudes.

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Authors: Khalid Ali, Manar Jammal

Abstract:

In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity.

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Authors: Ioannis Pratikakis, Anna Karahaliou, Katerina Vassiou, Vassilis Virvilis, Dimitrios Kosmopoulos, Stavros Perantonis

Abstract:

In this paper, a Web-based e-Training platform that is dedicated to multimodal breast imaging is presented. The assets of this platform are summarised in (i) the efficient representation of the curriculum flow that will permit efficient training; (ii) efficient tagging of multimodal content appropriate for the completion of realistic cases and (iii) ubiquitous accessibility and platform independence via a web-based approach.

Keywords: Breast imaging, e-Training, web-based learning.

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Authors: R. Fan, Q. Wan, H. Chen, Y.L. Liu, Y.P. Liu

Abstract:

This paper considers a robust recovery of sparse frequencies from partial phase-only measurements. With the proposed method, sparse frequencies can be reconstructed, which makes full use of the sparse distribution in the Fourier representation of the complex-valued time signal. Simulation experiments illustrate the proposed method-s advantages over conventional methods in both noiseless and additive white Gaussian noise cases.

Keywords: Sparse signal recovery, phase-only measurements, Compressive sensing, convex relaxation.

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Authors: B. A. Gobin, R. K. Subramanian

Abstract:

This paper gives an overview of how an OWL ontology has been created to represent template knowledge models defined in CML that are provided by CommonKADS. CommonKADS is a mature knowledge engineering methodology which proposes the use of template knowledge model for knowledge modelling. The aim of developing this ontology is to present the template knowledge model in a knowledge representation language that can be easily understood and shared in the knowledge engineering community. Hence OWL is used as it has become a standard for ontology and also it already has user friendly tools for viewing and editing.

Keywords: Ontology, OWL, Template Knowledge Models, CommonKADS

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