Search results for: Uniform random variable
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1725

Search results for: Uniform random variable

1095 Improved Computational Efficiency of Machine Learning Algorithms Based on Evaluation Metrics to Control the Spread of Coronavirus in the UK

Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

Abstract:

The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning (ML) archetypal that could forecast the COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID-19 cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organization (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data are split into 8:2 ratio for training and testing purposes to forecast future new COVID-19 cases. Support Vector Machine (SVM), Random Forest (RF), and linear regression (LR) algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID-19 cases is evaluated. RF outperformed the other two ML algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n = 30. The mean square error obtained for RF is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis, RF algorithm can perform more effectively and efficiently in predicting the new COVID-19 cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest.

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1094 Synthesis and Characterization of Cu-NanoWire Arrays by EMD Using ITO-Template

Authors: Jyoti Narayan, S. Choudhary

Abstract:

Nanowire arrays of copper with uniform diameters have been synthesized by potentiostatic electrochemical metal deposition (EMD) of copper sulphate and potassium chloride solution within the nano-channels of porous Indium-Tin Oxide (ITO), also known as Tin doped Indium Oxide templates. The nanowires developed were fairly continuous with diameters ranging from 110-140 nm along the entire length. Single as well as poly-crystalline copper wires have been prepared by application of appropriate potential during the EMD process. Scanning electron microscopy (SEM), high resolution transmission electron microscopy (HRTEM), small angle electron diffraction (SAED) and atomic force microscopy (AFM) were used to characterize the synthesized nano wires at room temperature. The electrochemical response of synthesized products was evaluated by cyclic voltammetry while surface energy analysis was carried out using a Goniometer.

Keywords: Electro-deposition, Metallic nano-wires, Nanomaterials, Template synthesis

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1093 The Variable Step-Size Gauss-Seidel Pseudo Affine Projection Algorithm

Authors: F. Albu, C. Paleologu

Abstract:

In this paper, a new pseudo affine projection (AP) algorithm based on Gauss-Seidel (GS) iterations is proposed for acoustic echo cancellation (AEC). It is shown that the algorithm is robust against near-end signal variations (including double-talk).

Keywords: pseudo affine projection algorithm, acoustic echo cancellation, double-talk.

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1092 Contribution to Improving the DFIG Control Using a Multi-Level Inverter

Authors: Imane El Karaoui, Mohammed Maaroufi, Hamid Chaikhy

Abstract:

Doubly Fed Induction Generator (DFIG) is one of the most reliable wind generator. Major problem in wind power generation is to generate Sinusoidal signal with very low THD on variable speed caused by inverter two levels used. This paper presents a multi-level inverter whose objective is to reduce the THD and the dimensions of the output filter. This work proposes a three-level NPC-type inverter, the results simulation are presented demonstrating the efficiency of the proposed inverter.

Keywords: DFIG, multilevel inverter, NPC inverter , THD, Induction machine.

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1091 Formation of Protective Silicide-Aluminide Coating on Gamma-TiAl Advanced Material

Authors: S. Nouri

Abstract:

In this study, the Si-aluminide coating was prepared on gamma-TiAl [Ti-45Al-2Nb-2Mn-1B (at. %)] via liquid-phase slurry procedure. The high temperature oxidation resistance of this diffusion coating was evaluated at 1100 °C for 400 hours. The results of the isothermal oxidation showed that the formation of Si-aluminide coating can remarkably improve the high temperature oxidation of bare gamma-TiAl alloy. The identification of oxide scale microstructure showed that the formation of protective Al2O3+SiO2 mixed oxide scale along with a continuous, compact and uniform layer of Ti5Si3 beneath the surface oxide scale can act as an oxygen diffusion barrier during the high temperature oxidation. The other possible mechanisms related to the formation of Si-aluminide coating and oxide scales were also discussed.

Keywords: Gamma-TiAl alloy, Si-aluminide coating, slurry procedure, high temperature oxidation.

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1090 Variable Regularization Parameter Normalized Least Mean Square Adaptive Filter

Authors: Young-Seok Choi

Abstract:

We present a normalized LMS (NLMS) algorithm with robust regularization. Unlike conventional NLMS with the fixed regularization parameter, the proposed approach dynamically updates the regularization parameter. By exploiting a gradient descent direction, we derive a computationally efficient and robust update scheme for the regularization parameter. In simulation, we demonstrate the proposed algorithm outperforms conventional NLMS algorithms in terms of convergence rate and misadjustment error.

Keywords: Regularization, normalized LMS, system identification, robustness.

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1089 Maxwell-Cattaneo Regularization of Heat Equation

Authors: F. Ekoue, A. Fouache d'Halloy, D. Gigon, G Plantamp, E. Zajdman

Abstract:

This work focuses on analysis of classical heat transfer equation regularized with Maxwell-Cattaneo transfer law. Computer simulations are performed in MATLAB environment. Numerical experiments are first developed on classical Fourier equation, then Maxwell-Cattaneo law is considered. Corresponding equation is regularized with a balancing diffusion term to stabilize discretizing scheme with adjusted time and space numerical steps. Several cases including a convective term in model equations are discussed, and results are given. It is shown that limiting conditions on regularizing parameters have to be satisfied in convective case for Maxwell-Cattaneo regularization to give physically acceptable solutions. In all valid cases, uniform convergence to solution of initial heat equation with Fourier law is observed, even in nonlinear case.

Keywords: Maxwell-Cattaneo heat transfers equations, fourierlaw, heat conduction, numerical solution.

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1088 Capability Investigation of Carbon Sequestration in Two Species (Artemisia sieberi Besser and Stipabarbata Desf) Under Different Treatments of Vegetation Management (Saveh, Iran)

Authors: M. Alizadeh, M. Mahdavi, M.H. Jouri

Abstract:

The rangelands, as one of the largest dynamic biomes in the world, have very capabilities. Regulation of greenhouse gases in the Earth's atmosphere, particularly carbon dioxide as the main these gases, is one of these cases. The attention to rangeland, as cheep and reachable resources to sequestrate the carbon dioxide, increases after the Industrial Revolution. Rangelands comprise the large parts of Iran as a steppic area. Rudshur (Saveh), as area index of steppic area, was selected under three sites include long-term exclosure, medium-term exclosure, and grazable area in order to the capable of carbon dioxide’s sequestration of dominated species. Canopy cover’s percentage of two dominated species (Artemisia sieberi Besser & Stipa barbata Desf) was determined via establishing of random 1 square meter plot. The sampling of above and below ground biomass style was obtained by complete random. After determination of ash percentage in the laboratory; conversion ratio of plant biomass to organic carbon was calculated by ignition method. Results of the paired t-test showed that the amount of carbon sequestration in above ground and underground biomass of Artemisia sieberi Besser & Stipa barbata Desf is different in three regions. It, of course, hasn’t any difference between under and surface ground’s biomass of Artemisia sieberi Besser in long-term exclosure. The independent t-test results indicate differences between underground biomass corresponding each other in the studied sites. Carbon sequestration in the Stipa barbata Desf was totally more than Artemisia sieberi Besser. Altogether, the average sequestration of the long-term exclosure was 5.842gr/m², the medium-term exclosure was 4.115gr/m², and grazable area was 5.975gr/m² so that there isn’t valuable statistical difference in term of total amount of carbon sequestration to three sites.

Keywords: Carbon sequestration, the Industrial Revolution, greenhouse gases, Artemisia sieberi Besser, Stipa barbata Desf, steppic rangelands

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1087 Environmental Impacts of Point and Non-Point Source Pollution in Krishnagiri Reservoir: A Case Study in South India

Authors: N. K. Ambujam, V. Sudha

Abstract:

Reservoirs are being contaminated all around the world with point source and Non-Point Source (NPS) pollution. The most common NPS pollutants are sediments and nutrients. Krishnagiri Reservoir (KR) has been chosen for the present case study, which is located in the tropical semi-arid climatic zone of Tamil Nadu, South India. It is the main source of surface water in Krishnagiri district to meet the freshwater demands. The reservoir has lost about 40% of its water holding capacity due to sedimentation over the period of 50 years. Hence, from the research and management perspective, there is a need for a sound knowledge on the spatial and seasonal variations of KR water quality. The present study encompasses the specific objectives as (i) to investigate the longitudinal heterogeneity and seasonal variations of physicochemical parameters, nutrients and biological characteristics of KR water and (ii) to examine the extent of degradation of water quality in KR. 15 sampling points were identified by uniform stratified method and a systematic monthly sampling strategy was selected due to high dynamic nature in its hydrological characteristics. The physicochemical parameters, major ions, nutrients and Chlorophyll a (Chl a) were analysed. Trophic status of KR was classified by using Carlson's Trophic State Index (TSI). All statistical analyses were performed by using Statistical Package for Social Sciences programme, version-16.0. Spatial maps were prepared for Chl a using Arc GIS. Observations in KR pointed out that electrical conductivity and major ions are highly variable factors as it receives inflow from the catchment with different land use activities. The study of major ions in KR exhibited different trends in their values and it could be concluded that as the monsoon progresses the major ions in the water decreases or water quality stabilizes. The inflow point of KR showed comparatively higher concentration of nutrients including nitrate, soluble reactive phosphorus (SRP), total phosphors (TP), total suspended phosphorus (TSP) and total dissolved phosphorus (TDP) during monsoon seasons. This evidently showed the input of significant amount of nutrients from the catchment side through agricultural runoff. High concentration of TDP and TSP at the lacustrine zone of the reservoir during summer season evidently revealed that there was a significant release of phosphorus from the bottom sediments. Carlson’s TSI of KR ranged between 81 and 92 during northeast monsoon and summer seasons. High and permanent Cyanobacterial bloom in KR could be mainly due to the internal loading of phosphorus from the bottom sediments. According to Carlson’s TSI classification Krishnagiri reservoir was ranked in the hyper-eutrophic category. This study provides necessary basic data on the spatio-temporal variations of water quality in KR and also proves the impact of point and NPS pollution from the catchment area. High TSI warrants a greater threat for the recovery of internal P loading and hyper-eutrophic condition of KR. Several expensive internal measures for the reduction of internal loading of P were introduced by many scientists. However, the outcome of the present research suggests for the innovative algae harvesting technique for the removal of sediment nutrients.

Keywords: Hyper-eutrophication, Krishnagiri reservoir, nutrients, NPS pollution.

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1086 Application of Adaptive Neural Network Algorithms for Determination of Salt Composition of Waters Using Laser Spectroscopy

Authors: Tatiana A. Dolenko, Sergey A. Burikov, Alexander O. Efitorov, Sergey A. Dolenko

Abstract:

In this study, a comparative analysis of the approaches associated with the use of neural network algorithms for effective solution of a complex inverse problem – the problem of identifying and determining the individual concentrations of inorganic salts in multicomponent aqueous solutions by the spectra of Raman scattering of light – is performed. It is shown that application of artificial neural networks provides the average accuracy of determination of concentration of each salt no worse than 0.025 M. The results of comparative analysis of input data compression methods are presented. It is demonstrated that use of uniform aggregation of input features allows decreasing the error of determination of individual concentrations of components by 16-18% on the average.

Keywords: Inverse problems, multi-component solutions, neural networks, Raman spectroscopy.

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1085 Evolutionary Dynamics on Small-World Networks

Authors: Jan Rychtar, Brian Stadler

Abstract:

We study how the outcome of evolutionary dynamics on graphs depends on a randomness on the graph structure. We gradually change the underlying graph from completely regular (e.g. a square lattice) to completely random. We find that the fixation probability increases as the randomness increases; nevertheless, the increase is not significant and thus the fixation probability could be estimated by the known formulas for underlying regular graphs.

Keywords: evolutionary dynamics, small-world networks

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1084 Magnetohydrodynamic Damping of Natural Convection Flows in a Rectangular Enclosure

Authors: M. Battira, R. Bessaih

Abstract:

We numerically study the three-dimensional magnetohydrodynamics (MHD) stability of oscillatory natural convection flow in a rectangular cavity, with free top surface, filled with a liquid metal, having an aspect ratio equal to A=L/H=5, and subjected to a transversal temperature gradient and a uniform magnetic field oriented in x and z directions. The finite volume method was used in order to solve the equations of continuity, momentum, energy, and potential. The stability diagram obtained in this study highlights the dependence of the critical value of the Grashof number Grcrit , with the increase of the Hartmann number Ha for two orientations of the magnetic field. This study confirms the possibility of stabilization of a liquid metal flow in natural convection by application of a magnetic field and shows that the flow stability is more important when the direction of magnetic field is longitudinal than when the direction is transversal.

Keywords: Natural convection, Magnetic field, Oscillatory, Cavity, Liquid metal.

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1083 On Musical Information Geometry with Applications to Sonified Image Analysis

Authors: Shannon Steinmetz, Ellen Gethner

Abstract:

In this paper a theoretical foundation is developed to segment, analyze and associate patterns within audio. We explore this on imagery via sonified audio applied to our segmentation framework. The approach involves a geodesic estimator within the statistical manifold, parameterized by musical centricity. We demonstrate viability by processing a database of random imagery to produce statistically significant clusters of similar imagery content.

Keywords: Sonification, musical information geometry, image content extraction, automated quantification, audio segmentation, pattern recognition.

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1082 A Further Improvement on the Resurrected Core-Spreading Vortex Method

Authors: M-J. Huang, C-J. Huang, L-C. Chen

Abstract:

In a previously developed fast vortex method, the diffusion of the vortex sheet induced at the solid wall by the no-slip boundary conditions was modeled according to the approximation solution of Koumoutsakos and converted into discrete blobs in the vicinity of the wall. This scheme had been successfully applied to a simulation of the flow induced with an impulsively initiated circular cylinder. In this work, further modifications on this vortex method are attempted, including replacing the approximation solution by the boundary-element-method solution, incorporating a new algorithm for handling the over-weak vortex blobs, and diffusing the vortex sheet circulation in a new way suitable for high-curvature solid bodies. The accuracy is thus largely improved. The predictions of lift and drag coefficients for a uniform flow past a NASA airfoil agree well with the existing literature.

Keywords: Resurrected core-spreading vortex method, Boundaryelement method, Vortex sheet, Over-weak vortex blobs.

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1081 Microwave-Assisted Fabrication of Visible-Light Activated BiOBr-Nanoplate Photocatalyst

Authors: Meichen Lee, Michael K. H. Leung

Abstract:

In recent years, visible-light activated photocatalysis has become a major field of intense researches for the higher efficiency of solar energy utilizations. Many attempts have been made on the modification of wide band gap semiconductors, while more and more efforts emphasize on cost-effective synthesis of visible-light activated catalysts. In this work, BiOBr nanoplates with band gap of visible-light range are synthesized through a promising microwave solvothermal method. The treatment time period and temperature dependent BiOBr nanosheets of various particle sizes are investigated through SEM. BiOBr synthesized under the condition of 160°C for 60 mins shows the most uniform particle sizes around 311 nm and the highest surface-to-volume ratio on account of its smallest average particle sizes compared with others. It exhibits the best photocatalytic behavior among all samples in RhB degradation.

Keywords: Microwave solvothermal process, nanoplates, solar energy, visible-light photocatalysis.

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1080 Solar Energy Collection using a Double-layer Roof

Authors: S. Kong Wang

Abstract:

The purpose of this study is to investigate the efficiency of a double-layer roof in collecting solar energy as an application to the areas such as raising high-end temperature of organic Rankine cycle (ORC). The by-product of the solar roof is to reduce building air-conditioning loads. The experimental apparatus are arranged to evaluate the effects of the solar roof in absorbing solar energy. The flow channel is basically formed by an aluminum plate on top of a plywood plate. The geometric configurations in which the effects of absorbing energy is analyzed include: a bare uncovered aluminum plate, a glass-covered aluminum plate, a glass-covered/black-painted aluminum plate, a plate with variable lengths, a flow channel with stuffed material (in an attempt on enhancement of heat conduction), and a flow channel with variable slanted angles. The experimental results show that the efficiency of energy collection varies from 0.6 % to 11 % for the geometric configurations mentioned above. An additional study is carried out using CFD simulation to investigate the effects of fins on the aluminum plate. It shows that due to vastly enhanced heat conduction, the efficiency can reach ~23 % if 50 fins are installed on the aluminum plate. The study shows that a double-layer roof can efficiently absorb solar energy and substantially reduce building air-conditioning loads. On the high end of an organic Rankine cycle, a solar pond is used to replace the warm surface water of the sea as OTEC (ocean thermal energy conversion) is the driving energy for the ORC. The energy collected from the double-layered solar roof can be pumped into the pond and raise the pond temperature as the pond surface area is equivalently increased by nearly one-fourth of the total area of the double-layer solar roof. The effect of raising solar pond temperature is especially prominent if the double-layer solar roofs are installed in a community area.

Keywords: solar energy collection, double-layer solar roof, energy conservation, ORC, OTEC

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1079 Study on the Chaotic Cipher Combined with Mersenne Twister

Authors: Daiki Yoshida, Ariyoshi Nakayama, Hirotaka Watanabe, Taichi Sato, Syuhei Kuriyama, Hiroyuki Kamata

Abstract:

In this study, we propose the chaotic cipher combined with Mersenne Twister that is an extremely good pseudo-random number generator for the secure communications. We investigate the Lyapunov exponent of the proposed system, and evaluate the randomness performance by comparing RC4 and the chaotic cipher. In these results, our proposed system gets high chaotic property and more randomness than the conventional ciphers.

Keywords: Chaos, chaotic property, cipher, Mersenne Twister, Randomness.

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1078 Analytical and Finite Element Analysis of Hydroforming Deep Drawing Process

Authors: Maziar Ramezani, Thomas Neitzert

Abstract:

This paper gives an overview of a deep drawing process by pressurized liquid medium separated from the sheet by a rubber diaphragm. Hydroforming deep drawing processing of sheet metal parts provides a number of advantages over conventional techniques. It generally increases the depth to diameter ratio possible in cup drawing and minimizes the thickness variation of the drawn cup. To explore the deformation mechanism, analytical and numerical simulations are used for analyzing the drawing process of an AA6061-T4 blank. The effects of key process parameters such as coefficient of friction, initial thickness of the blank and radius between cup wall and flange are investigated analytically and numerically. The simulated results were in good agreement with the results of the analytical model. According to finite element simulations, the hydroforming deep drawing method provides a more uniform thickness distribution compared to conventional deep drawing and decreases the risk of tearing during the process.

Keywords: Deep drawing, Hydroforming, Rubber diaphragm

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1077 Heat Transfer in a Parallel-Plate Enclosure with Graded-Index Coatings on its Walls

Authors: Jiun-Wei Chen, Chih-Yang Wu, Ming-Feng Hou

Abstract:

A numerical study on the heat transfer in the thermal barrier coatings and the substrates of a parallel-plate enclosure is carried out. Some of the thermal barrier coatings, such as ceramics, are semitransparent and are of interest for high-temperature applications where radiation effects are significant. The radiative transfer equations and the energy equations are solved by using the discrete ordinates method and the finite difference method. Illustrative results are presented for temperature distributions in the coatings and the opaque walls under various heating conditions. The results show that the temperature distribution is more uniform in the interior portion of each coating away from its boundary for the case with a larger average of varying refractive index and a positive gradient of refractive index enhances radiative transfer to the substrates.

Keywords: Radiative transfer, parallel-plate enclosure, coatings, varying refractive index

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1076 Employee Assessment Systems in the Structures of Corporate Groups

Authors: D. Bąk-Grabowska, K. Grzesik, A. Iwanicka, A. Jagoda

Abstract:

The process of human resources management in the structures of corporate groups demonstrates certain specificity, resulting from the division of decision-making and executive competencies, which occurs within these structures between a parent company and its subsidiaries. The subprocess of employee assessment is considered crucial, since it provides information for the implementation of personnel function. The empirical studies conducted in corporate groups, within which at least one company is located in Poland, confirmed the critical significance of employee assessment systems in the process of human resources management in corporate groups. Parent companies, most often, retain their decision-making authority within the framework of the discussed process and introduce uniform employee assessment and personnel controlling systems to subsidiary companies. However, the instruments for employee assessment applied in corporate groups do not present such specificity.

Keywords: Corporate groups, employee periodical assessment system, holding, human resources management.

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1075 Weight Functions for Signal Reconstruction Based On Level Crossings

Authors: Nagesha, G. Hemantha Kumar

Abstract:

Although the level crossing concept has been the subject of intensive investigation over the last few years, certain problems of great interest remain unsolved. One of these concern is distribution of threshold levels. This paper presents a new threshold level allocation schemes for level crossing based on nonuniform sampling. Intuitively, it is more reasonable if the information rich regions of the signal are sampled finer and those with sparse information are sampled coarser. To achieve this objective, we propose non-linear quantization functions which dynamically assign the number of quantization levels depending on the importance of the given amplitude range. Two new approaches to determine the importance of the given amplitude segment are presented. The proposed methods are based on exponential and logarithmic functions. Various aspects of proposed techniques are discussed and experimentally validated. Its efficacy is investigated by comparison with uniform sampling.

Keywords: speech signals, sampling, signal reconstruction, asynchronousdelta modulation, non-linear quantization.

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1074 Fuel Cell/DC-DC Convertor Control by Sliding Mode Method

Authors: Farzad Abdous

Abstract:

Fuel cell's system requires regulating circuit for voltage and current in order to control power in case of connecting to other generative devices or load. In this paper Fuel cell system and convertor, which is a multi-variable system, are controlled using sliding mode method. Use of weighting matrix in design procedure made it possible to regulate speed of control. Simulation results show the robustness and accuracy of proposed controller for controlling desired of outputs.

Keywords: DC-DC converter, Fuel cell, PEM, Slides mode control.

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1073 Development of a New Method for T-joint Specimens Testing under Shear Loading

Authors: R. Doubrava, R. Růžek

Abstract:

Nonstandard tests are necessary for analyses and verification of new developed structural and technological solutions with application of composite materials. One of the most critical primary structural parts of a typical aerospace structure is T-joint. This structural element is loaded mainly in shear, bending, peel and tension. The paper is focused on the shear loading simulations. The aim of the work is to obtain a representative uniform distribution of shear loads along T-joint during the mechanical testing. A new design of T-joint test procedure, numerical simulation and optimization of representative boundary conditions are presented. The different conditions and inaccuracies both in simulations and experiments are discussed. The influence of different parameters on stress and strain distributions is demonstrated on T-joint made of CFRP (carbon fibre reinforced plastic). A special test rig designed by VZLU (Aerospace Research and Test Establishment) for T-shear test procedure is presented.

Keywords: T-joint, shear, composite, mechanical testing, Finite Element analysis, methodology.

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1072 A Study of Neuro-Fuzzy Inference System for Gross Domestic Product Growth Forecasting

Authors: Ε. Giovanis

Abstract:

In this paper we present a Adaptive Neuro-Fuzzy System (ANFIS) with inputs the lagged dependent variable for the prediction of Gross domestic Product growth rate in six countries. We compare the results with those of Autoregressive (AR) model. We conclude that the forecasting performance of neuro-fuzzy-system in the out-of-sample period is much more superior and can be a very useful alternative tool used by the national statistical services and the banking and finance industry.

Keywords: Autoregressive model, Forecasting, Gross DomesticProduct, Neuro-Fuzzy

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1071 An Efficient Separation for Convolutive Mixtures

Authors: Salah Al-Din I. Badran, Samad Ahmadi, Dylan Menzies, Ismail Shahin

Abstract:

This paper describes a new efficient blind source separation method; in this method we uses a non-uniform filter bank and a new structure with different sub-bands. This method provides a reduced permutation and increased convergence speed comparing to the full-band algorithm. Recently, some structures have been suggested to deal with two problems: reducing permutation and increasing the speed of convergence of the adaptive algorithm for correlated input signals. The permutation problem is avoided with the use of adaptive filters of orders less than the full-band adaptive filter, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each sub-band than the input signal at full-band, and can promote better rates of convergence.

Keywords: Blind source separation (BSS), estimates, full-band, mixtures, Sub-band.

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1070 Turbulent Forced Convection Flow in a Channel over Periodic Grooves Using Nanofluids

Authors: Farshid Fathinia, Mohammad Parsazadeh, Amirhossein Heshmati

Abstract:

Turbulent forced convection flow in a 2-dimensional channel over periodic grooves is numerically investigated. Finite volume method is used to study the effect of turbulence model. The range of Reynolds number varied from 10000 to 30000 for the ribheight to channel-height ratio (B/H) of 2. The downstream wall is heated by a uniform heat flux while the upstream wall is insulated. The investigation is analyzed with different types of nanoparticles such as SiO2, Al2O3, and ZnO, with water as a base fluid are used. The volume fraction is varied from 1% to 4% and the nanoparticle diameter is utilized between 20nm to 50nm. The results revealed 114% heat transfer enhancement compared to the water in a grooved channel by using SiO2 nanoparticle with volume fraction and nanoparticle diameter of 4% and 20nm respectively.

Keywords: Forced convection, Periodic grooves, Nanofluids, Turbulent model, Heat transfer.

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1069 Dispersed Error Control based on Error Filter Design for Improving Halftone Image Quality

Authors: Sang-Chul Kim, Sung-Il Chien

Abstract:

The error diffusion method generates worm artifacts, and weakens the edge of the halftone image when the continuous gray scale image is reproduced by a binary image. First, to enhance the edges, we propose the edge-enhancing filter by considering the quantization error information and gradient of the neighboring pixels. Furthermore, to remove worm artifacts often appearing in a halftone image, we add adaptively random noise into the weights of an error filter.

Keywords: Artifact suppression, Edge enhancement, Error diffusion method, Halftone image

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1068 Packaging in a Multivariate Conceptual Design Synthesis of a BWB Aircraft

Authors: Paul Okonkwo, Howard Smith

Abstract:

A study to estimate the size of the cabin and major aircraft components as well as detect and avoid interference between internally placed components and the external surface, during the conceptual design synthesis and optimisation to explore the design space of a BWB, was conducted. Sizing of components follows the Bradley cabin sizing and rubber engine scaling procedures to size the cabin and engine respectively. The interference detection and avoidance algorithm relies on the ability of the Class Shape Transform parameterisation technique to generate polynomial functions of the surfaces of a BWB aircraft configuration from the sizes of the cabin and internal objects using few variables. Interference detection is essential in packaging of non-conventional configuration like the BWB because of the non-uniform airfoil-shaped sections and resultant varying internal space. The unique configuration increases the need for a methodology to prevent objects from being placed in locations that do not sufficiently enclose them within the geometry.

Keywords: Packaging, Optimisation, BWB, Parameterisation, Aircraft Conceptual Design.

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1067 Developing NAND Flash-Memory SSD-Based File System Design

Authors: Jaechun No

Abstract:

This paper focuses on I/O optimizations of N-hybrid (New-Form of hybrid), which provides a hybrid file system space constructed on SSD and HDD. Although the promising potentials of SSD, such as the absence of mechanical moving overhead and high random I/O throughput, have drawn a lot of attentions from IT enterprises, its high ratio of cost/capacity makes it less desirable to build a large-scale data storage subsystem composed of only SSDs. In this paper, we present N-hybrid that attempts to integrate the strengths of SSD and HDD, to offer a single, large hybrid file system space. Several experiments were conducted to verify the performance of N-hybrid.

Keywords: SSD, data section, I/O optimizations.

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1066 Estimation of Attenuation and Phase Delay in Driving Voltage Waveform of an Ultra-High-Speed Image Sensor by Dimensional Analysis

Authors: V. T. S. Dao, T. G. Etoh, C. Vo Le, H. D. Nguyen, K. Takehara, T. Akino, K. Nishi

Abstract:

We present an explicit expression to estimate driving voltage attenuation through RC networks representation of an ultrahigh- speed image sensor. Elmore delay metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE simulation data, we found a simple expression that significantly improves the accuracy of the approximation. Estimation error of the resultant expression for uniform RC networks is less than 2%. Similarly, another simple closed-form model to estimate 50 % delay through fundamental RC networks is also derived with sufficient accuracy. The framework of this analysis can be extended to address delay or attenuation issues of other VLSI structures.

Keywords: Dimensional Analysis, Elmore model, RC network, Signal Attenuation, Ultra-High-Speed Image Sensor.

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