Search results for: computation physics

Authors: Yiqiong Yuan, Jun Sun, Dongmei Zhou, Jianan Sun

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In this paper, we presented a Multi-Objective Random Drift Particle Swarm Optimization algorithm (MORDPSO-CD) based on RDPSO and crowding distance sorting to improve the convergence and distribution with less computation cost. MORDPSO-CD makes the most of RDPSO to approach the true Pareto optimal solutions fast. We adopt the crowding distance sorting technique to update and maintain the archived optimal solutions. Introducing the crowding distance technique into MORDPSO can make the leader particles find the true Pareto solution ultimately. The simulation results reveal that the proposed algorithm has better convergence and distribution

Keywords: multi-objective optimization, random drift particle swarm optimization, crowding distance sorting, pareto optimal solution

Procedia PDF Downloads 231

Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

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The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: neural network computing, continuous functions generating the input-output mapping, decreasing the training time, machines with big memories

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Authors: Abdulrahman Sumayli, Saad M. AlShahrani

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For the hydrogenation process, knowing the solubility of hydrogen (H2) in hydrocarbons is critical to improve the efficiency of the process. We investigated the H2 solubility computation in four heavy crude oil feedstocks using machine learning techniques. Temperature, pressure, and feedstock type were considered as the inputs to the models, while the hydrogen solubility was the sole response. Specifically, we employed three different models: Support Vector Regression (SVR), Gaussian process regression (GPR), and Bayesian ridge regression (BRR). To achieve the best performance, the hyper-parameters of these models are optimized using the whale optimization algorithm (WOA). We evaluated the models using a dataset of solubility measurements in various feedstocks, and we compared their performance based on several metrics. Our results show that the WOA-SVR model tuned with WOA achieves the best performance overall, with an RMSE of 1.38 × 10− 2 and an R-squared of 0.991. These findings suggest that machine learning techniques can provide accurate predictions of hydrogen solubility in different feedstocks, which could be useful in the development of hydrogen-related technologies. Besides, the solubility of hydrogen in the four heavy oil fractions is estimated in different ranges of temperatures and pressures of 150 ◦C–350 ◦C and 1.2 MPa–10.8 MPa, respectively

Keywords: temperature, pressure variations, machine learning, oil treatment

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Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

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This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system

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Authors: Tingting Lin, Manfred von Willich, Dafu Lou, Phil Eisen

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A white-box implementation of a cryptographic algorithm is a software implementation intended to resist extraction of the secret key by an adversary. To date, most of the white-box techniques are used to protect block cipher implementations. However, a large proportion of the white-box implementations are proven to be vulnerable to affine equivalence attacks and other algebraic attacks, as well as differential computation analysis (DCA). In this paper, we identify a class of block ciphers for which we propose a method of constructing white-box implementations. Our method is based on threshold implementations and operations in composite fields. The resulting implementations consist of lookup tables and few exclusive OR operations. All intermediate values (inputs and outputs of the lookup tables) are masked. The threshold implementation makes the distribution of the masked values uniform and independent of the original inputs, and the operations in composite fields reduce the size of the lookup tables. The white-box implementations can provide resistance against algebraic attacks and DCA-like attacks.

Keywords: white-box, block cipher, composite field, threshold implementation

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Authors: Jindriska Svobodova, Jan Novotny

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A teacher’s attitude to creativity plays an essential role in the thinking development of his/her students. The purpose of this study is to understand if a science teacher's personal creativity can modify his/her ability to produce various kinds of questions. This research used an education activity based on cosmic sketches and pictures by K.E. Tsiolkovsky, the founder of astronautics, to explore if any relationship between individual creativity and the asking questions skill exists. As a screening instrument, which allows an assessment of the respondent's creative potential, a common test of creative thinking was used. The results of the creativity test and the diversity of the questions are mentioned.

Keywords: science education, active learning, physics teaching, religious cosmology

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Authors: Zongjie Wang, Zhizhong Guo

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While the regular optimal power flow model focuses on a single time scan, the optimization of power systems is typically intended for a time duration with respect to a desired objective function. In this paper, a temporal optimal power flow model for a time period is proposed. To reduce the computation burden needed for calculating temporal optimal power flow, a characteristic optimal power flow model is proposed, which employs different characteristic load patterns to represent the objective function and security constraints. A numerical method based on the interior point method is also proposed for solving the characteristic optimal power flow model. Both the temporal optimal power flow model and characteristic optimal power flow model can improve the systems’ desired objective function for the entire time period. Numerical studies are conducted on the IEEE 14 and 118-bus test systems to demonstrate the effectiveness of the proposed characteristic optimal power flow model.

Keywords: optimal power flow, time period, security, economy

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Authors: Francesco Rizzuto, Matthew Stickland, Stephan Hannot

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The simulation of a positive displacement pump system with commercial software for Computer Fluid Dynamics (CFD), will result in an enormous computational effort due to the complexity of the pump system. This drawback restricts the use of it to a specific part of the pump in one simulation. This research focuses on developing an algorithm that provides a suitable result in agreement with experiment data, without that computational effort. The compressible equations are solved with an explicit algorithm. A comparison is presented between the FV method with Monotonic Upwind scheme for Conservative Laws (MUSCL) with slope limiter and experimental results. The source term for cavitation and friction is introduced into the algorithm with a slipping strategy and solved with a 4th order Runge-Kutta scheme (RK4). Different pumps are modeled and analyzed to evaluate the flexibility of the code. The simulation required minimal computation time and resources without compromising the accuracy of the simulation results. Therefore, this algorithm highlights the feasibility of pressure pulsation simulation as a design tool for an industrial purpose.

Keywords: cavitation, diaphragm, DVCM, finite volume, MUSCL, positive displacement pump

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Authors: Piyush Swami, Bijaya Ketan Panigrahi, Sneh Anand, Manvir Bhatia, Tapan Gandhi

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Visual inspection of electroencephalogram (EEG) signals to detect epileptic signals is very challenging and time-consuming task even for any expert neurophysiologist. This problem is most challenging in under-developed and developing countries due to shortage of skilled neurophysiologists. In the past, notable research efforts have gone in trying to automate the seizure detection process. However, due to high false alarm detections and complexity of the models developed so far, have vastly delimited their practical implementation. In this paper, we present a novel scheme for epileptic seizure detection using empirical mode decomposition technique. The intrinsic mode functions obtained were then used to calculate the standard deviations. This was followed by probability density based classifier to discriminate between non-ictal and ictal patterns in EEG signals. The model presented here demonstrated very high classification rates ( > 97%) without compromising the statistical performance. The computation timings for each testing phase were also very low ( < 0.029 s) which makes this model ideal for practical applications.

Keywords: electroencephalogram (EEG), epilepsy, ictal patterns, empirical mode decomposition

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Authors: Ivan Baravy

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Interpolation problem, as it was initially posed in terms of polynomials, is well researched. However, further mathematical developments extended it significantly. Trigonometric interpolation is widely used in Fourier analysis, while its generalized representation as exponential interpolation is applicable to such problem of mathematical physics as modelling of Ziegler-Biersack-Littmark repulsive interatomic potentials. Formulated for finite fields, this problem arises in decoding Reed--Solomon codes. This paper shows the relation between different interpretations of the problem through the class of matrices of special structure - Hankel matrices.

Keywords: Berlekamp-Massey algorithm, exponential interpolation, finite fields, Hankel matrices, Hankel polynomials

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Authors: Punit Kumar, Niraj Kumar

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The traction behavior of lubricants with the linear pressure-viscosity response in EHL line contacts is investigated numerically for smooth as well as rough surfaces. The analysis involves the simultaneous solution of Reynolds, elasticity and energy equations along with the computation of lubricant properties and surface temperatures. The temperature modified Doolittle-Tait equations are used to calculate viscosity and density as functions of fluid pressure and temperature, while Carreau model is used to describe the lubricant rheology. The surface roughness is assumed to be sinusoidal and it is present on the nearly stationary surface in near-pure sliding EHL conjunction. The linear P-V oil is found to yield much lower traction coefficients and slightly thicker EHL films as compared to the synthetic oil for a given set of dimensionless speed and load parameters. Besides, the increase in traction coefficient attributed to surface roughness is much lower for the former case. The present analysis emphasizes the importance of employing realistic pressure-viscosity response for accurate prediction of EHL traction.

Keywords: EHL, linear pressure-viscosity, surface roughness, traction, water/glycol

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Authors: Tejush Badal, Sanaa Alwidian

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Class diagrams are useful tools within the Unified Modelling Language (UML) to model and visualize the relationships between, and properties of objects within a system. As a system evolves over time and space (e.g., products), a series of models with several commonalities and variabilities create what is known as a model family. In circumstances where there are several versions of a model, examining each model individually, becomes expensive in terms of computation resources. To avoid performing redundant operations, this paper proposes an approach for representing a family of class diagrams into Union Models to represent model families using a single generic model. The paper aims to analyze and reason about a family of class diagrams using union models as opposed to individual analysis of each member model in the family. The union algorithm provides a holistic view of the model family, where the latter cannot be otherwise obtained from an individual analysis approach, this in turn, enhances the analysis performed in terms of speeding up the time needed to analyze a family of models together as opposed to analyzing individual models, one model at a time.

Keywords: analysis, class diagram, model family, unified modeling language, union model

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Authors: Konstantin Nefedev, Petr Andriushchenko

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Usually under the frustrated magnetics, it understands such materials, in which ones the interaction between located magnetic moments or spins has competing character, and can not to be satisfied simultaneously. The most well-known and simplest example of the frustrated system is antiferromagnetic Ising model on the triangle. Physically, the existence of frustrations means, that one cannot select all three pairs of spins anti-parallel in the basic unit of the triangle. In physics of the interacting particle systems, the vector models are used, which are constructed on the base of the pair-interaction law. Each pair interaction energy between one-component vectors can take two opposite in sign values, excluding the case of zero. Mathematically, the existence of frustrations in system means that it is impossible to have all negative energies of pair interactions in the Hamiltonian even in the ground state (lowest energy). In fact, the frustration is the excitation, which leaves in system, when thermodynamics does not work, i.e. at the temperature absolute zero. The origin of the frustration is the presence at least of one ''unsatisfied'' pair of interacted spins (magnetic moments). The minimal relative quantity of these excitations (relative quantity of frustrations in ground state) can be used as parameter of frustration. If the energy of the ground state is Egs, and summary energy of all energy of pair interactions taken with a positive sign is Emax, that proposed frustration parameter pf takes values from the interval [0,1] and it is defined as pf=(Egs+Emax)/2Emax. For antiferromagnetic Ising model on the triangle pf=1/3. We calculated the parameters of frustration in thermodynamic limit for different 2D periodical structures of Ising dipoles, which were on the ribs of the lattice and interact by means of the long-range dipolar interaction. For the honeycomb lattice pf=0.3415, triangular - pf=0.2468, kagome - pf=0.1644. All dependencies of frustration parameter from 1/N obey to the linear law. The given frustration parameter allows to consider the thermodynamics of all magnetic systems from united point of view and to compare the different lattice systems of interacting particle in the frame of vector models. This parameter can be the fundamental characteristic of frustrated systems. It has no dependence from temperature and thermodynamic states, in which ones the system can be found, such as spin ice, spin glass, spin liquid or even spin snow. It shows us the minimal relative quantity of excitations, which ones can exist in system at T=0.

Keywords: frustrations, parameter of order, statistical physics, magnetism

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Authors: Sedat Yayla, Azhin Abdullah

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In the process of constructing hydroelectric power plants, the Pelton turbine, which is characterized by its simple manufacturing and construction, is performed in high head and low water flow. Parameters of the turbine have to be comprised in the designing process for obtaining hydraulic turbine with the highest efficiency during different operating conditions. The present investigation applied three-dimensional computational fluid dynamics (CFD). In addition, the bucket of Pelton turbine models with different splitter angle and inlet velocity values were examined for determining the force and visualizing the flow pattern on the bucket. The study utilized two diverse bucket models at various inlet velocities (20, 25, 30,35and 40m/s) and four different splitter angles (55, 75,90and 115 degree) for finding out the impacts of every single parameter on the effective force on the bucket. The acquired outcomes revealed that there is a linear relationship between force and inlet velocity on the bucket. Furthermore, the results also uncovered that the relationship between splitter angle and force on the bucket is linear until 90 degree.

Keywords: bucket design, computational fluid dynamics (CFD), free surface flow, two-phase flow, volume of fluid (VOF)

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Authors: Vijay Kumar Bajpai, Sudhir Kumar Singh

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In this study, the performance analyses of the twenty five coal-fired power plants (CFPPs) used for electricity generation are carried out through various data envelopment analysis (DEA) models. Three efficiency indices are defined and pursued. During the calculation of the operational performance, energy and non-energy variables are used as input, and net electricity produced is used as desired output. CO2 emitted to the environment is used as the undesired output in the computation of the pure environmental performance while in Model-3 CO2 emissions is considered as detrimental input in the calculation of operational and environmental performance. Empirical results show that most of the plants are operating in increasing returns to scale region and Mettur plant is efficient one with regards to energy use and environment. The result also indicates that the undesirable output effect is insignificant in the research sample. The present study will provide clues to plant operators towards raising the operational and environmental performance of CFPPs.

Keywords: coal fired power plants, environmental performance, data envelopment analysis, operational performance

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Authors: Zhen Peng, Baifeng Wu

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Modern computing technology enters the era of parallel computing with the trend of sustainable and scalable parallelism. Single Instruction Multiple Data (SIMD) is an important way to go along with the trend. It is able to gather more and more computing ability by increasing the number of processor cores without the need of modifying the program. Meanwhile, in the field of scientific computing and engineering design, many computation intensive applications are facing the challenge of increasingly large amount of data. Data parallel computing will be an important way to further improve the performance of these applications. In this paper, we take the accurate collision detection in building information modeling as an example. We demonstrate a model for constructing a data parallel algorithm. According to the model, a complex object is decomposed into the sets of simple objects; collision detection among complex objects is converted into those among simple objects. The resulting algorithm is a typical SIMD algorithm, and its advantages in parallelism and scalability is unparalleled in respect to the traditional algorithms.

Keywords: data parallelism, collision detection, single instruction multiple data, building information modeling, continuous scalability

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Authors: Mohammad Arif Khan

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This paper analyzes and presents the development of Artificial Neural Network based controller of space vector modulation (ANN-SVPWM) for a seven-phase voltage source inverter. At first, the conventional method of producing sinusoidal output voltage by utilizing six active and one zero space vectors are used to synthesize the input reference, is elaborated and then new PWM scheme called Artificial Neural Network Based PWM is presented. The ANN based controller has the advantage of the very fast implementation and analyzing the algorithms and avoids the direct computation of trigonometric and non-linear functions. The ANN controller uses the individual training strategy with the fixed weight and supervised models. A computer simulation program has been developed using Matlab/Simulink together with the neural network toolbox for training the ANN-controller. A comparison of the proposed scheme with the conventional scheme is presented based on various performance indices. Extensive Simulation results are provided to validate the findings.

Keywords: space vector PWM, total harmonic distortion, seven-phase, voltage source inverter, multi-phase, artificial neural network

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Authors: Yusuf Ziya Ayık, Ferhat Kahveci

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Currently, database management systems have various tools such as backup and maintenance, and also provide statistical information such as resource usage and security. In terms of query performance, this paper covers query optimization, views, indexed tables, pre-computation materialized view, query performance analysis in which query plan alternatives can be created and the least costly one selected to optimize a query. Indexes and views can be created for related table columns. The literature review of this study showed that, in the course of time, despite the growing capabilities of the database management system, only database administrators are aware of the need for dealing with archival and transactional data types differently. These data may be constantly changing data used in everyday life, and also may be from the completed questionnaire whose data input was completed. For both types of data, the database uses its capabilities; but as shown in the findings section, instead of repeating similar heavy calculations which are carrying out same results with the same query over a survey results, using materialized view results can be in a more simple way. In this study, this performance difference was observed quantitatively considering the cost of the query.

Keywords: cost of query, database management systems, materialized view, query performance

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Authors: Marta Cordero-Gracia, Mariola Gomez, Olivier Blesbois, Marina Carrion

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One of the difficulties in icing simulations is for extended periods of exposure, when very large ice shapes are created. As well as being large, they can have complex shapes, such as a double horn. For icing simulations, these configurations are currently computed in several steps. The icing step is stopped when the ice shapes become too large, at which point a new mesh has to be created to allow for further CFD and ice growth simulations to be performed. This can be very costly, and is a limiting factor in the simulations that can be performed. A way to avoid the costly human intervention in the re-meshing step of multistep icing computation is to use mesh deformation instead of re-meshing. The aim of the present work is to apply an interpolation method based on Radial Basis Functions (RBF) to transfer deformations from surface mesh to volume mesh. This deformation tool has been developed specifically for icing problems. It is able to deal with localized, sharp and large deformations, unlike the tools traditionally used for more smooth wing deformations. This tool will be presented along with validation on typical two-dimensional icing shapes.

Keywords: ice accretion, interpolation, mesh deformation, radial basis functions

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Authors: T. Y. Liu, C. H. Lin, Y. M. Ferng

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Wind energy is one of the clean renewable energy. However, the low frequency (20-200HZ) noise generated from the wind turbine blades, which bothers the residents, becomes the major problem to be developed. It is useful for predicting the aerodynamic noise by flow field and pressure distribution analysis on the wind turbine blades. Therefore, the main objective of this study is to use different turbulence models to analyse the flow field and pressure distributions of the wing blades. Three-dimensional Computation Fluid Dynamics (CFD) simulation of the flow field was used to calculate the flow phenomena for the National Renewable Energy Laboratory (NREL) Phase VI horizontal axis wind turbine rotor. Two different flow cases with different wind speeds were investigated: 7m/s with 72rpm and 15m/s with 72rpm. Four kinds of RANS-based turbulence models, Standard k-ε, Realizable k-ε, SST k-ω, and v2f, were used to predict and analyse the results in the present work. The results show that the predictions on pressure distributions with SST k-ω and v2f turbulence models have good agreements with experimental data.

Keywords: horizontal axis wind turbine, turbulence model, noise, fluid dynamics

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Authors: Hans Marquez Ramos, Cesar Hernandez, Ingrid Páez

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This paper develops a multiple channel assignment model, which allows to take advantage in most efficient way, spectrum opportunities in cognitive radio networks. Developed scheme allows make several available and frequency adjacent channel assignments, which require a bigger wide band, under an equality environment. The hybrid assignment model it is made by to algorithms, one who makes the ranking and select available frequency channels and the other one in charge of establishing an equality criteria, in order to not restrict spectrum opportunities for all other secondary users who wish to make transmissions. Measurements made were done for average bandwidth, average delay, as well fairness computation for several channel assignment. Reached results were evaluated with experimental spectrum occupational data from GSM frequency band captured. Developed model, shows evidence of improvement in spectrum opportunity use and a wider average transmit bandwidth for each secondary user, maintaining equality criteria in channel assignment.

Keywords: bandwidth, fairness, multichannel, secondary users

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Authors: Amrita Das, Abhishek Kumar Singh

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The present paper calibrates the efficacy of corrugated and loosely bonded common interface of a viscoelastic layer and a dry sandy Gibson half-space on the propagation of torsional surface wave. Using suitable boundary conditions, the dispersion relation for the concerned problem is deduced in complex form. Numerical computation of the real part of the obtained dispersion relation gives the dispersion curve whereas the imaginary part bestows the damping curves. The use of Whittaker’s function and Bessel’s functions are among the major concerns of the paper. The investigation of the influence of the affecting parameters viz. heterogeneities, sandiness, Biot’s gravity parameter, initial stresses, loosely bonded interface, corrugation and internal friction on the phase velocity as well as damped velocity of torsional wave, through numerical discussion and graphical illustration, is among the major highlights of the current study.

Keywords: corrugation, dry sandy Gibson half-space, loosely bonded interface, torsional wave, viscoelastic layer

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Authors: Bin Ji, Kai Xu, Shunyu Yao, Jingjing Liu, Ye Pan

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Human pose estimation is a popular research area in computer vision for its important application in human-machine interface. In recent years, 2D human pose estimation based on convolution neural network has got great progress and development. However, in more and more practical applications, people often need to deal with tasks based on video. It’s not far-fetched for us to consider how to combine the spatial and temporal information together to achieve a balance between computing cost and accuracy. To address this issue, this study proposes a new spatiotemporal model, namely Spatiotemporal Net (STNet) to combine both temporal and spatial information more rationally. As a result, the predicted keypoints heatmap is potentially more accurate and spatially more precise. Under the condition of ensuring the recognition accuracy, the algorithm deal with spatiotemporal series in a decoupled way, which greatly reduces the computation of the model, thus reducing the resource consumption. This study demonstrate the effectiveness of our network over the Penn Action Dataset, and the results indicate superior performance of our network over the existing methods.

Keywords: convolutional long short-term memory, deep learning, human pose estimation, spatiotemporal series

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Authors: Andre Peres Ramos, Franklin Cesar Flores

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Colorization is the process of add colors to a monochromatic image or video. Usually, the process involves to segment the image in regions of interest and then apply colors to each one, for videos, this process is repeated for each frame, which makes it a tedious and time-consuming job. We propose a new assisted method for video colorization; the user only has to colorize one frame, and then the colors are propagated to following frames. The user can intervene at any time to correct eventual errors in color assignment. The method consists of to extract intensity and texture descriptors from the frames and then perform a feature matching to determine the best color for each segment. To reduce computation time and give a better spatial coherence we narrow the area of search and give weights for each feature to emphasize texture descriptors. To give a more natural result, we use an optimization algorithm to make the color propagation. Experimental results in several image sequences, compared to others existing methods, demonstrates that the proposed method perform a better colorization with less time and user interference.

Keywords: colorization, feature matching, texture descriptors, video segmentation

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Authors: Yazid Alkraimeen

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Precise prediction of dielectric stresses and high voltages of power transformers require the accurate calculation of frequency-dependent parameters. A lack of accuracy can result in severe damages to transformer windings. Transient conditions is stuided by digital computers, which require the implementation of accurate models. This paper analyzes the computation of frequency-dependent skin and proximity losses included in the transformer winding model, using analytical equations and Finite Element Method (FEM). A modified formula to calculate the proximity and the skin losses is presented. The results of the frequency-dependent parameter calculations are verified using the Finite Element Method. The time-domain transient voltages are obtained using Numerical Inverse Laplace Transform. The results show that the classical formula for proximity losses is overestimating the transient voltages when compared with the results obtained from the modified method on a simple transformer geometry.

Keywords: fast front transients, proximity losses, transformer winding modeling, skin losses

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Authors: Avantika Vats, Kushal Thakur

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This paper displays the point at issue, improvement, and utilization of a Monarch Butterfly Optimization (MBO) rather than a Genetic Algorithm (GA) in cognitive radio for the channel portion. This approach offers a satisfactory approach to get the accessible range of both the users, i.e., primary users (PUs) and secondary users (SUs). The proposed enhancement procedure depends on a nature-inspired metaheuristic algorithm. In MBO, all the monarch butterfly individuals are located in two distinct lands, viz. Southern Canada and the northern USA (land 1), and Mexico (Land 2). The positions of the monarch butterflies are modernizing in two ways. At first, the offsprings are generated (position updating) by the migration operator and can be adjusted by the migration ratio. It is trailed by tuning the positions for different butterflies by the methods for the butterfly adjusting operator. To keep the population unaltered and minimize fitness evaluations, the aggregate of the recently produced butterflies in these two ways stays equivalent to the first population. The outcomes obviously display the capacity of the MBO technique towards finding the upgraded work values on issues regarding the genetic algorithm.

Keywords: cognitive radio, channel allocation, monarch butterfly optimization, evolutionary, computation

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Authors: Mark Anthony Casimiro, Ivan Culaba, Cornelia Soto

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Misconceptions are the wrong concepts understood by the students which may come up based on what they experience and observe around their environment. This seemed to hinder students’ learning. In this study, six different misconceptions were determined by the researcher from the previous researches. Teachers play a vital role in the classroom. The use of appropriate strategies can contribute a lot in the success of teaching and learning Physics. The current study aimed to compare two strategies- Interactive Lecture Demonstration (ILD) and Inquiry-Based Instruction (IBI) in addressing students’ misconceptions in electric circuits. These two strategies are both interactive learning activities and student-centered. In ILD, the teacher demonstrates the activity and the students have their predictions while in IBI, students perform the experiments. The study used the mixed method in which quantitative and qualitative researches were combined. The main data of this study were the test scores of the students from the pretest and posttest. Likewise, an interview with the teacher, observer and students was done before, during and after the execution of the activities. Determining and Interpreting Resistive Electric Circuits Test version 2 (DIRECT v.2) was the instrument used in the study. Two sections of Grade 9 students from Kalumpang National High School were the respondents of the study. The two strategies were executed to each section; one class was assigned as the ILD group and the other class was the IBI group. The Physics teacher of the said school was the one who taught and executed the activities. The researcher taught the teacher the steps in doing the two strategies. The Department of Education level of proficiency in the Philippines was adopted in scoring and interpretation. The students’ level of proficiency was used in assessing students’ knowledge on electric circuits. The pretest result of the two groups had a p-value of 0.493 which was greater than the level of significance 0.05 (p >0.05) and it implied that the students’ level of understanding in the topic was the same before the execution of the strategies. The posttest results showed that the p-value (0.228) obtained was greater than the level of significance which is 0.05 (p> 0.05). This implied that the students from the ILD and IBI groups had the same level of understanding after the execution of the two strategies. This could be inferred that either of the two strategies- Interactive Lecture Demonstration and Inquiry-Based Instruction could be used in addressing students’ misconception in electric circuit as both had similar effect on the students’ level of understanding in the topic. The result of this study may greatly help teachers, administration, school heads think of appropriate strategies that can address misconceptions depending on the availability of their materials of their school.

Keywords: inquiry- based instruction, interactive lecture demonstration, misconceptions, mixed method

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Authors: Lai Junzhe, Wang Lihao, Burra Venkata Durga Kumar

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In recent years, due to today's global technological advances, big data and artificial intelligence technologies have been widely used in various industries and fields, playing an important role in reducing costs and increasing efficiency. Among them, artificial intelligence has derived another branch in its own continuous progress and the continuous development of computer personnel, namely distributed artificial intelligence computing systems. Distributed AI is a method for solving complex learning, decision-making, and planning problems, characterized by the ability to take advantage of large-scale computation and the spatial distribution of resources, and accordingly, it can handle problems with large data sets. Nowadays, distributed AI is widely used in military, medical, and human daily life and brings great convenience and efficient operation to life. In this paper, we will discuss three areas of distributed AI computing systems in vision processing, blockchain, and smart home to introduce the performance of distributed systems and the role of AI in distributed systems.

Keywords: distributed system, artificial intelligence, blockchain, IoT, visual information processing, smart home

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Authors: Saumya Srivastava, Rina Maiti

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In order to achieve a better performance of vehicle detection in a complex environment, we present an efficient approach for a multi-vehicle detection system using an adaptive sliding window technique. For a given frame, image segmentation is carried out to establish the region of interest. Gradient computation followed by thresholding, denoising, and morphological operations is performed to extract the binary search image. Near-region field and far-region field are defined to generate hypotheses using the adaptive sliding window technique on the resultant binary search image. For each vehicle candidate, features are extracted using a histogram of oriented gradients, and a pre-trained support vector machine is applied for hypothesis verification. Later, the Kalman filter is used for tracking the vanishing point. The experimental results show that the method is robust and effective on various roads and driving scenarios. The algorithm was tested on highways and urban roads in India.

Keywords: gradient, vehicle detection, histograms of oriented gradients, support vector machine

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Authors: A. Baviskar, C. Sandeep, K. Shankar

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Solving Multi-objective Optimization Problems requires faster convergence and better spread. Though existing Evolutionary Algorithms (EA's) are able to achieve this, the computation effort can further be reduced by hybridizing them with innovative strategies. This study is focuses on converging to the pareto front faster while adapting the advantages of Strength Pareto Evolutionary Algorithm-II (SPEA-II) for a better spread. Two different approaches based on optimizing the objective functions independently are implemented. In the first method, the decision variables corresponding to the optima of individual objective functions are strategically used to guide the search towards the pareto front. In the second method, boundary points of the pareto front are calculated and their decision variables are seeded to the initial population. Both the methods are applied to different constrained and unconstrained multi-objective test functions. It is observed that proposed guided search based algorithm gives better convergence and diversity than several well-known existing algorithms (such as NSGA-II and SPEA-II) in considerably less number of iterations.

Keywords: boundary points, evolutionary algorithms (EA's), guided search, strength pareto evolutionary algorithm-II (SPEA-II)

Procedia PDF Downloads 248