Search results for: Schwarz method.

Authors: D. Im, S. Choi, H. Kwon, S. H. Park, J. H. Kwon

Abstract:

This paper is an extension of a previous work where a diagonally implicit harmonic balance method was developed and applied to simulate oscillatory motions of pitching airfoil and wing. A more detailed study on the accuracy, convergence, and the efficiency of the method is carried out in the current paperby varying the number of harmonics in the solution approximation. As the main advantage of the method is itsusage for the design optimization of the unsteady problems, its application to more practical case of rotor flow analysis during forward flight is carried out and compared with flight test data and time-accurate computation results.

Keywords: Design optimization, Implicit harmonic balancemethod, number of harmonics, rotor flows

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Authors: Kirill Trapezon, Alexandr Trapezon

Abstract:

A problem is formulated for the natural oscillations of a circular plate of linearly variable thickness on the basis of the symmetry method. The equations of natural frequencies and forms for a plate are obtained, providing that it is rigidly fixed along the inner contour. The first three eigenfrequencies are calculated, and the eigenmodes of the oscillations of the acoustic element are constructed. An algorithm for applying the symmetry method and the factorization method for solving problems in the theory of oscillations for plates of variable thickness is shown. The effectiveness of the approach is demonstrated on the basis of comparison of known results and those obtained in the article. It is shown that the results are more accurate and reliable.

Keywords: Vibrations, plate, thickness, symmetry, factorization, approximation.

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Authors: Anas M. Fares

Abstract:

The using of finite element programs in analyzing and designing buildings are becoming very popular, but there are many engineers still using the tributary area method (TAM) in designing the structural members such as columns. This study is an attempt to investigate the accuracy of the TAM results with different load condition (gravity and lateral load), different floors numbers, and different columns stiffness's. To conduct this study, linear elastic analysis in ETABS program is used. The results from finite element method are compared to those obtained from TAM. According to the analysis of the data obtained, it can be seen that there is significance difference between the real load carried by columns and the load which is calculated by using the TAM. Thus, using 3-D models are the best choice to calculate the real load effected on columns and design these columns according to this load.

Keywords: Tributary area method, finite element method, ETABS, lateral load, axial loads, reinforced concrete, stiffness, multi-floor buildings.

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Authors: Anupma Bansal, R. K. Gupta

Abstract:

In this paper, we study a new modified Novikov equation for its classical and nonclassical symmetries and use the symmetries to reduce it to a nonlinear ordinary differential equation (ODE). With the aid of solutions of the nonlinear ODE by using the modified (G/G)-expansion method proposed recently, multiple exact traveling wave solutions are obtained and the traveling wave solutions are expressed by the hyperbolic functions, trigonometric functions and rational functions.

Keywords: New Modified Novikov Equation, Lie Classical Method, Nonclassical Method, Modified (G'/G)-Expansion Method, Traveling Wave Solutions.

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Authors: Delaram Jarchi, Reza Boostani

Abstract:

Linear Discrimination Analysis (LDA) is a linear solution for classification of two classes. In this paper, we propose a variant LDA method for multi-class problem which redefines the between class and within class scatter matrices by incorporating a weight function into each of them. The aim is to separate classes as much as possible in a situation that one class is well separated from other classes, incidentally, that class must have a little influence on classification. It has been suggested to alleviate influence of classes that are well separated by adding a weight into between class scatter matrix and within class scatter matrix. To obtain a simple and effective weight function, ordinary LDA between every two classes has been used in order to find Fisher discrimination value and passed it as an input into two weight functions and redefined between class and within class scatter matrices. Experimental results showed that our new LDA method improved classification rate, on glass, iris and wine datasets, in comparison to different versions of LDA.

Keywords: Discriminant vectors, weighted LDA, uncorrelation, principle components, Fisher-face method, Bootstarp method.

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Authors: P. Suriyachai, N. Thavarungkul, P. Sae-oui

Abstract:

In this research sodium bicarbonate (NaHCO3) was introduced to generate carbon dioxide gas (CO2) to the existing nitrogen gas (N2) of elastomeric foam, to lower thermal conductivity (K). Various loadings of NaHCO3 (0 to 60 phr) were added into the azodicarbonamide (AZC)-containing compound and its properties were then determined. Two vulcanization methods, i.e., hot air and infrared (IR), were employed and compared in this study. Results revealed that compound viscosity tended to increase slightly with increasing NaHCO3 content but cure time was delayed. The effect of NaHCO3 content on thermal conductivity depended on the vulcanization method. For hot air method, the thermal conductivity was insignificantly changed with increasing NaHCO3 up to 40 phr whereas it tended to decrease gradually for IR method. At higher NaHCO3 content (60 phr), unexpected increase of thermal conductivity was observed. The water absorption was also determined and foam structures were then used to explain the results.

Keywords: sodium bicarbonate, thermal conductivity, hot airmethod, infrared method

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Authors: Hesheng Wang, Haoyu Wang, Chungang Zhuang

Abstract:

Estimating the 6D pose of objects is a core step for robot bin-picking tasks. The problem is that various objects are usually randomly stacked with heavy occlusion in real applications. In this work, we propose a method to regress 6D poses by predicting three points for each object in the 3D point cloud through deep learning. To solve the ambiguity of symmetric pose, we propose a labeling method to help the network converge better. Based on the predicted pose, an iterative method is employed for pose optimization. In real-world experiments, our method outperforms the classical approach in both precision and recall.

Keywords: Pose estimation, deep learning, point cloud, bin-picking, 3D computer vision.

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Authors: Ioannis Neokosmidis, Nikos Gkekas, Thomas Kamalakis, Thomas Sphicopoulos

Abstract:

In high powered dense wavelength division multiplexed (WDM) systems with low chromatic dispersion, four-wave mixing (FWM) can prove to be a major source of noise. The MultiCanonical Monte Carlo Method (MCMC) and the Split Step Fourier Method (SSFM) are combined to accurately evaluate the probability density function of the decision variable of a receiver, limited by FWM. The combination of the two methods leads to more accurate results, and offers the possibility of adding other optical noises such as the Amplified Spontaneous Emission (ASE) noise.

Keywords: Monte Carlo, Nonlinear optics, optical crosstalk, Wavelength-division Multiplexing (WDM).

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Authors: B. Groß, P. Fronia, P. Nyhuis

Abstract:

In addition to the production, which is already frequently optimized, improving the distribution logistics also opens up tremendous potential for increasing an enterprise’s competitiveness. Here too though, numerous interactions need to be taken into account, enterprises thus need to be able to identify and weigh between different potentials for economically efficient optimizations. In order to be able to assess potentials, enterprises require a suitable method. This paper first briefly presents the need for this research before introducing the procedure that will be used to develop an appropriate method that not only considers interactions but is also quickly and easily implemented.

Keywords: Distribution Logistics, Evaluation of Potential, Methods, Model.

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Authors: M.R. Ebrahimi, Z. Ghofrani, M. Ehsan

Abstract:

One of the major problems in liberalized power markets is loss allocation. In this paper, a different method for allocating transmission losses to pool market participants is proposed. The proposed method is fundamentally based on decomposition of loss function and current projection concept. The method has been implemented and tested on several networks and one sample summarized in the paper. The results show that the method is comprehensive and fair to allocating the energy losses of a power market to its participants.

Keywords: Transmission loss, loss allocation, current projectionconcept, loss function decomposition.

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Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim

Abstract:

The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.

Keywords: Data mining, Korean linguistic feature, literary fiction, relationship extraction.

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Authors: Yu Bin, Zhang Yan

Abstract:

The prediction of transmembrane helical segments (TMHs) in membrane proteins is an important field in the bioinformatics research. In this paper, a method based on discrete wavelet transform (DWT) has been developed to predict the number and location of TMHs in membrane proteins. PDB coded as 1F88 was chosen as an example to describe the prediction of the number and location of TMHs in membrane proteins by using this method. One group of test data sets that contain total 19 protein sequences was utilized to access the effect of this method. Compared with the prediction results of DAS, PRED-TMR2, SOSUI, HMMTOP2.0 and TMHMM2.0, the obtained results indicate that the presented method has higher prediction accuracy.

Keywords: hydrophobicity, membrane protein, transmembranehelical segments, wavelet transform

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Authors: Abdullah H. Özcan, Dilara Hisar, Yetkin Sayar, Cem Ünsalan

Abstract:

In this study, an automated building and tree detection method is proposed using DSM data and true orthophoto image. A multiscale matched filtering is used on DSM data. Therefore, first watershed transform is applied. Then, Otsu’s thresholding method is used as an adaptive threshold to segment each watershed region. Detected objects are masked with NDVI to separate buildings and trees. The proposed method is able to detect buildings and trees without entering any elevation threshold. We tested our method on ISPRS semantic labeling dataset and obtained promising results.

Keywords: Building detection, tree detection, matched filtering, multiscale, local maximum filtering, watershed segmentation.

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Authors: Rahim Jafari, Tuba Okutucu-Özyurt

Abstract:

The hydrodynamics and heat transfer characteristics of a vaporized elongated bubble in a rectangular microchannel have been simulated based on Cahn-Hilliard phase-field method. In the simulations, the initially nucleated bubble starts growing as it comes in contact with superheated water. The growing shape of the bubble compared well with the available experimental data in the literature.

Keywords: Microchannel, boiling, Cahn-Hilliard method, Two-phase flow, Simulation.

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Authors: Sajjad Farashi, Mohammadjavad Abolhassani, Mostafa Taghavi Kani

Abstract:

Information in the nervous system is coded as firing patterns of electrical signals called action potential or spike so an essential step in analysis of neural mechanism is detection of action potentials embedded in the neural data. There are several methods proposed in the literature for such a purpose. In this paper a novel method based on empirical mode decomposition (EMD) has been developed. EMD is a decomposition method that extracts oscillations with different frequency range in a waveform. The method is adaptive and no a-priori knowledge about data or parameter adjusting is needed in it. The results for simulated data indicate that proposed method is comparable with wavelet based methods for spike detection. For neural signals with signal-to-noise ratio near 3 proposed methods is capable to detect more than 95% of action potentials accurately.

Keywords: EMD, neural data processing, spike detection, wavelet decomposition.

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Authors: Min Sun, Jing Liu

Abstract:

In this article, a new inexact alternating direction method(ADM) is proposed for solving a class of variational inequality problems. At each iteration, the new method firstly solves the resulting subproblems of ADM approximately to generate an temporal point ˜xk, and then the multiplier yk is updated to get the new iterate yk+1. In order to get xk+1, we adopt a new descent direction which is simple compared with the existing prediction-correction type ADMs. For the inexact ADM, the resulting proximal subproblem has closedform solution when the proximal parameter and inexact term are chosen appropriately. We show the efficiency of the inexact ADM numerically by some preliminary numerical experiments.

Keywords: variational inequality problems, alternating direction method, global convergence

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Authors: Thashmee Karunaratne, Henrik Böstrom

Abstract:

Logic based methods for learning from structured data is limited w.r.t. handling large search spaces, preventing large-sized substructures from being considered by the resulting classifiers. A novel approach to learning from structured data is introduced that employs a structure transformation method, called finger printing, for addressing these limitations. The method, which generates features corresponding to arbitrarily complex substructures, is implemented in a system, called DIFFER. The method is demonstrated to perform comparably to an existing state-of-art method on some benchmark data sets without requiring restrictions on the search space. Furthermore, learning from the union of features generated by finger printing and the previous method outperforms learning from each individual set of features on all benchmark data sets, demonstrating the benefit of developing complementary, rather than competing, methods for structure classification.

Keywords: Machine learning, Structure classification, Propositionalization.

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Authors: Chechen Liao, Chin Yi Yang

Abstract:

Although several factors that affect learning to program have been identified over the years, there continues to be no indication of any consensus in understanding why some students learn to program easily and quickly while others have difficulty. Seldom have researchers considered the problem of how to help the students enhance the programming learning outcome. The research had been conducted at a high school in Taiwan. Students participating in the study consist of 330 tenth grade students enrolled in the Basic Computer Concepts course with the same instructor. Two types of training methods-instruction-oriented and exploration-oriented were conducted. The result of this research shows that the instruction-oriented training method has better learning performance than exploration-oriented training method.

Keywords: Learning performance, programming learning, TDD, training method.

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Authors: U. Pangnakorn, S. Kanlaya, C. Kuntha

Abstract:

Raw wood vinegar was purified by both standing and filtering methods. Toxicity tests were conducted under laboratory conditions by the topical application method (contact poison) and feeding method (stomach poison). Larvicidal activities of wood vinegar at four different concentrations (10, 15, 20, 25 and 30 %) were studied against second instar larvae of housefly (Musca domestica L.). Four replicates were maintained for all treatments and controls. Larval mortality was recorded up to 96 hours and compared with the larval survivability by two methods of larvicidal bioassay. Percent pupation and percent adult emergence were observed in treated M. domestica. The study revealed that the feeding method gave higher efficiency compared with the topical application method. Larval mortality increased with increasing concentration of wood vinegar and the duration of exposure. No mortality was found in treated M. domestica larvae at minimum 10% concentration of wood vinegar through the experiments. The treated larvae were maintained up to pupa and adult emergence. At 30% maximum concentration larval duration was extended to 11 days in M. domestica for topical application method and 9 days for feeding method. Similarly the pupal durations were also increased with increased concentrations (16 and 24 days for topical application method and feeding method respectively at 30% concentration) of the treatments.

Keywords: Housefly (Musca domestica L.), wood vinegar, mortality, topical application, feeding

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Authors: Rafid Saeed Abdulrazak Alshkaki

Abstract:

In this paper, zero-one inflated negative binomial distribution is considered, along with some of its structural properties, then its parameters were estimated using the method of moments. It is found that the method of moments to estimate the parameters of the zero-one inflated negative binomial models is not a proper method and may give incorrect conclusions.

Keywords: Zero one inflated models, negative binomial distribution, moments estimator, non-negative integer sampling.

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Authors: Tadashi Watanabe

Abstract:

The flow field and the motion of the free surface in an oscillating container are simulated numerically to assess the numerical approach for studying two-phase flows under oscillating conditions. Two numerical methods are compared: one is to model the oscillating container directly using the moving grid of the ALE method, and the other is to simulate the effect of container motion using the oscillating body force acting on the fluid in the stationary container. The two-phase flow field in the container is simulated using the level set method in both cases. It is found that the calculated results by the body force method coinsides with those by the moving grid method and the sloshing behavior is predicted well by both the methods. Theoretical back ground and limitation of the body force method are discussed, and the effects of oscillation amplitude and frequency are shown.

Keywords: Two-phase flow, simulation, oscillation, moving grid, body force

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Authors: Kwangho Cha, Hyeyoung Cho, Sungho Kim

Abstract:

As many scientific applications require large data processing, the importance of parallel I/O has been increasingly recognized. Collective I/O is one of the considerable features of parallel I/O and enables application programmers to easily handle their large data volume. In this paper we measured and analyzed the performance of original collective I/O and the subgroup method, the way of using collective I/O of MPI effectively. From the experimental results, we found that the subgroup method showed good performance with small data size.

Keywords: Collective I/O, MPI, parallel file system.

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Authors: Meemongkol A., Tipsuwanporn V., Numsomran A.

Abstract:

The authors present optimization parameters of rotary positioner controller in hard disk drive servo track writing process using coefficient diagram method; CDM. Due to estimation parameters in PI Positioning Control System by expected ratio method cannot meet the required specification of response effectively, we suggest coefficient diagram method for defining controller parameters under the requirement of the system. Finally, the simulation results show that our proposed method can improve the problem in tuning parameter of rotary positioner controller. It is satisfied specification of performance of control system. Furthermore, it is very convenient as a fast adjustment damping ratio as well as a high speed response.

Keywords: Optimization Parameters, Rotary Positioner, CDM

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Authors: Young Hee Geum

Abstract:

We propose the numerical method defined by

xn+1 = xn − λ[f(xn − μh(xn))/]f'(xn) , n ∈ N,

and determine the control parameter λ and μ to converge cubically. In addition, we derive the asymptotic error constant. Applying this proposed scheme to various test functions, numerical results show a good agreement with the theory analyzed in this paper and are proven using Mathematica with its high-precision computability.

Keywords: Asymptotic error constant, iterative method , multiple root, root-finding.

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Authors: Yanhui Zhang, Wenyu Yang

Abstract:

One of the difficulties of the vibration-based damage identification methods is the nonuniqueness of the results of damage identification. The different damage locations and severity may cause the identical response signal, which is even more severe for detection of the multiple damage. This paper proposes a new strategy for damage detection to avoid this nonuniqueness. This strategy firstly determines the approximates damage area based on the statistical pattern recognition method using the dynamic strain signal measured by the distributed fiber Bragg grating, and then accurately evaluates the damage information based on the Bayesian model updating method using the experimental modal data. The stochastic simulation method is then used to compute the high-dimensional integral in the Bayesian problem. Finally, an experiment of the plate structure, simulating one part of mechanical structure, is used to verify the effectiveness of this approach.

Keywords: Bayesian method, damage detection, fiber Bragg grating, structural health monitoring.

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Authors: Hyun-Koo Kim, Sagong Kuk, MinKwan Kim, Ho-Youl Jung

Abstract:

This paper presents an effective method for detecting vehicles in front of the camera-assisted car during nighttime driving. The proposed method detects vehicles based on detecting vehicle headlights and taillights using techniques of image segmentation and clustering. First, to effectively extract spotlight of interest, a segmentation process based on automatic multi-level threshold method is applied on the road-scene images. Second, to spatial clustering vehicle of detecting lamps, a grouping process based on light tracking and locating vehicle lighting patterns. For simulation, we are implemented through Da-vinci 7437 DSP board with near infrared mono-camera and tested it in the urban and rural roads. Through the test, classification performances are above 97% of true positive rate evaluated on real-time environment. Our method also has good performance in the case of clear, fog and rain weather.

Keywords: Assistance Driving System, Multi-level Threshold Method, Near Infrared Mono Camera, Nighttime Vehicle Detection.

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Authors: Po-Jen Su, Huann-Ming Chou

Abstract:

In this article, we used the residual correction method to deal with transient thermoelastic problems with a hollow spherical region when the continuum medium possesses spherically isotropic thermoelastic properties. Based on linear thermoelastic theory, the equations of hyperbolic heat conduction and thermoelastic motion were combined to establish the thermoelastic dynamic model with consideration of the deformation acceleration effect and non-Fourier effect under the condition of transient thermal shock. The approximate solutions of temperature and displacement distributions are obtained using the residual correction method based on the maximum principle in combination with the finite difference method, making it easier and faster to obtain upper and lower approximations of exact solutions. The proposed method is found to be an effective numerical method with satisfactory accuracy. Moreover, the result shows that the effect of transient thermal shock induced by deformation acceleration is enhanced by non-Fourier heat conduction with increased peak stress. The influence on the stress increases with the thermal relaxation time.

Keywords: Maximum principle, non-Fourier heat conduction, residual correction method, thermo-elastic response.

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Authors: Sang-Hong Park

Abstract:

This paper proposes an efficient method to classify inverse synthetic aperture (ISAR) images. Because ISAR images can be translated and rotated in the 2-dimensional image place, invariance to the two factors is indispensable for successful classification. The proposed method achieves invariance to translation and rotation of ISAR images using a combination of two-dimensional Fourier transform, polar mapping and correlation-based alignment of the image. Classification is conducted using a simple matching score classifier. In simulations using the real ISAR images of five scaled models measured in a compact range, the proposed method yields classification ratios higher than 97 %.

Keywords: Radar, ISAR, radar target classification, radar imaging.

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Authors: Mohamed M. Mousa, Aidarkhan Kaltayev

Abstract:

The equations governing the flow of an electrically conducting, incompressible viscous fluid over an infinite flat plate in the presence of a magnetic field are investigated using the homotopy perturbation method (HPM) with Padé approximants (PA) and 4th order Runge–Kutta method (4RKM). Approximate analytical and numerical solutions for the velocity field and heat transfer are obtained and compared with each other, showing excellent agreement. The effects of the magnetic parameter and Prandtl number on velocity field, shear stress, temperature and heat transfer are discussed as well.

Keywords: Electrically conducting elastico-viscous fluid, symmetry solution, Homotopy perturbation method, Padé approximation, 4th order Runge–Kutta, Maple

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Authors: Samy Sadek, Ayoub Al-Hamadi, Bernd Michaelis, Usama Sayed

Abstract:

In this paper, we propose a supervised method for color image classification based on a multilevel sigmoidal neural network (MSNN) model. In this method, images are classified into five categories, i.e., “Car", “Building", “Mountain", “Farm" and “Coast". This classification is performed without any segmentation processes. To verify the learning capabilities of the proposed method, we compare our MSNN model with the traditional Sigmoidal Neural Network (SNN) model. Results of comparison have shown that the MSNN model performs better than the traditional SNN model in the context of training run time and classification rate. Both color moments and multi-level wavelets decomposition technique are used to extract features from images. The proposed method has been tested on a variety of real and synthetic images.

Keywords: Image classification, multi-level neural networks, feature extraction, wavelets decomposition.

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