Search results for: Poisson inverse Gaussian distribution
2346 Segmenting Ultrasound B-Mode Images Using RiIG Distributions and Stochastic Optimization
Abstract:
In this paper, we propose a novel algorithm for delineating the endocardial wall from a human heart ultrasound scan. We assume that the gray levels in the ultrasound images are independent and identically distributed random variables with different Rician Inverse Gaussian (RiIG) distributions. Both synthetic and real clinical data will be used for testing the algorithm. Algorithm performance will be evaluated using the expert radiologist evaluation of a soft copy of an ultrasound scan during the scanning process and secondly, doctor’s conclusion after going through a printed copy of the same scan. Successful implementation of this algorithm should make it possible to differentiate normal from abnormal soft tissue and help disease identification, what stage the disease is in and how best to treat the patient. We hope that an automated system that uses this algorithm will be useful in public hospitals especially in Third World countries where problems such as shortage of skilled radiologists and shortage of ultrasound machines are common. These public hospitals are usually the first and last stop for most patients in these countries.
Keywords: Endorcardial Wall, Rician Inverse Distributions, Segmentation, Ultrasound Images.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15342345 A Combined Approach of a Sequential Life Testing and an Accelerated Life Testing Applied to a Low-Alloy High Strength Steel Component
Authors: D. I. De Souza, D. R. Fonseca, G. P. Azevedo
Abstract:
Sometimes the amount of time available for testing could be considerably less than the expected lifetime of the component. To overcome such a problem, there is the accelerated life-testing alternative aimed at forcing components to fail by testing them at much higher-than-intended application conditions. These models are known as acceleration models. One possible way to translate test results obtained under accelerated conditions to normal using conditions could be through the application of the “Maxwell Distribution Law.” In this paper we will apply a combined approach of a sequential life testing and an accelerated life testing to a low alloy high-strength steel component used in the construction of overpasses in Brazil. The underlying sampling distribution will be three-parameter Inverse Weibull model. To estimate the three parameters of the Inverse Weibull model we will use a maximum likelihood approach for censored failure data. We will be assuming a linear acceleration condition. To evaluate the accuracy (significance) of the parameter values obtained under normal conditions for the underlying Inverse Weibull model we will apply to the expected normal failure times a sequential life testing using a truncation mechanism. An example will illustrate the application of this procedure.
Keywords: Sequential Life Testing, Accelerated Life Testing, Underlying Three-Parameter Weibull Model, Maximum Likelihood Approach, Hypothesis Testing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16072344 On a Class of Inverse Problems for Degenerate Differential Equations
Authors: Fadi Awawdeh, H.M. Jaradat
Abstract:
In this paper, we establish existence and uniqueness of solutions for a class of inverse problems of degenerate differential equations. The main tool is the perturbation theory for linear operators.Keywords: Inverse Problem, Degenerate Differential Equations, Perturbation Theory for Linear Operators
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15972343 Blind Source Separation Using Modified Gaussian FastICA
Authors: V. K. Ananthashayana, Jyothirmayi M.
Abstract:
This paper addresses the problem of source separation in images. We propose a FastICA algorithm employing a modified Gaussian contrast function for the Blind Source Separation. Experimental result shows that the proposed Modified Gaussian FastICA is effectively used for Blind Source Separation to obtain better quality images. In this paper, a comparative study has been made with other popular existing algorithms. The peak signal to noise ratio (PSNR) and improved signal to noise ratio (ISNR) are used as metrics for evaluating the quality of images. The ICA metric Amari error is also used to measure the quality of separation.Keywords: Amari error, Blind Source Separation, Contrast function, Gaussian function, Independent Component Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16972342 Classification of Earthquake Distribution in the Banda Sea Collision Zone with Point Process Approach
Authors: Henry J. Wattimanela, Udjianna S. Pasaribu, Nanang T. Puspito, Sapto W. Indratno
Abstract:
Banda Sea Collision Zone (BSCZ) is the result of the interaction and convergence of Indo-Australian plate, Eurasian plate and Pacific plate. This location is located in eastern Indonesia. This zone has a very high seismic activity. In this research, we will calculate the rate (λ) and Mean Square Error (MSE). By this result, we will classification earthquakes distribution in the BSCZ with the point process approach. Chi-square is used to determine the type of earthquakes distribution in the sub region of BSCZ. The data used in this research is data of earthquakes with a magnitude ≥ 6 SR for the period 1964-2013 and sourced from BMKG Jakarta. This research is expected to contribute to the Moluccas Province and surrounding local governments in performing spatial plan document related to disaster management.Keywords: Banda sea collision zone, earthquakes, mean square error, Poisson distribution, chi-square test.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20462341 A Nano-Scaled SRAM Guard Band Design with Gaussian Mixtures Model of Complex Long Tail RTN Distributions
Authors: Worawit Somha, Hiroyuki Yamauchi
Abstract:
This paper proposes, for the first time, how the challenges facing the guard-band designs including the margin assist-circuits scheme for the screening-test in the coming process generations should be addressed. The increased screening error impacts are discussed based on the proposed statistical analysis models. It has been shown that the yield-loss caused by the misjudgment on the screening test would become 5-orders of magnitude larger than that for the conventional one when the amplitude of random telegraph noise (RTN) caused variations approaches to that of random dopant fluctuation. Three fitting methods to approximate the RTN caused complex Gamma mixtures distributions by the simple Gaussian mixtures model (GMM) are proposed and compared. It has been verified that the proposed methods can reduce the error of the fail-bit predictions by 4-orders of magnitude.Keywords: Mixtures of Gaussian, Random telegraph noise, EM algorithm, Long-tail distribution, Fail-bit analysis, Static random access memory, Guard band design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18012340 Modelling the Occurrence of Defects and Change Requests during User Acceptance Testing
Authors: Kevin McDaid, Simon P. Wilson
Abstract:
Software developed for a specific customer under contract typically undergoes a period of testing by the customer before acceptance. This is known as user acceptance testing and the process can reveal both defects in the system and requests for changes to the product. This paper uses nonhomogeneous Poisson processes to model a real user acceptance data set from a recently developed system. In particular a split Poisson process is shown to provide an excellent fit to the data. The paper explains how this model can be used to aid the allocation of resources through the accurate prediction of occurrences both during the acceptance testing phase and before this activity begins. Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22912339 Design and Fabrication of Stent with Negative Poisson’s Ratio
Authors: S. K. Bhullar, J. Ko, F. Ahmed, M. B. G. Jun
Abstract:
The negative Poisson’s ratios can be described in terms of models based on the geometry of the system and the way this geometry changes due to applied loads. As the Poisson’s ratio does not depend on scale hence deformation can take place at the nano to macro level the only requirement is the right combination of the geometry. Our thrust in this paper is to combine our knowledge of tailored enhanced mechanical properties of the materials having negative Poisson’s ratio with the micromachining and electrospining technology to develop a novel stent carrying a drug delivery system. Therefore, the objective of this paper includes (i) fabrication of a micromachined metal sheet tailored with structure having negative Poisson’s ratio through rotating solid squares geometry using femtosecond laser ablation; (ii) rolling fabricated structure and welding to make a tubular structure (iii) wrapping it with nanofibers of biocompatible polymer PCL (polycaprolactone) for drug delivery (iv) analysis of the functional and mechanical performance of fabricated structure analytically and experimentally. Further, as the applications concerned, tubular structures have potential in biomedical for example hollow tubes called stents are placed inside to provide mechanical support to a damaged artery or diseased region and to open a blocked esophagus thus allowing feeding capacity and improving quality of life.
Keywords: Micromachining, electrospining, auxetic materials, enhanced mechanical properties.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35682338 An Evaluation of Algorithms for Single-Echo Biosonar Target Classification
Authors: Turgay Temel, John Hallam
Abstract:
A recent neurospiking coding scheme for feature extraction from biosonar echoes of various plants is examined with avariety of stochastic classifiers. Feature vectors derived are employedin well-known stochastic classifiers, including nearest-neighborhood,single Gaussian and a Gaussian mixture with EM optimization.Classifiers' performances are evaluated by using cross-validation and bootstrapping techniques. It is shown that the various classifers perform equivalently and that the modified preprocessing configuration yields considerably improved results.
Keywords: Classification, neuro-spike coding, non-parametricmodel, parametric model, Gaussian mixture, EM algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16232337 Electromagnetic Imaging of Inhomogeneous Dielectric Cylinders Buried in a Slab Mediumby TE Wave Illumination
Authors: Chung-Hsin Huang, Chien-Ching Chiu, Chun Jen Lin
Abstract:
The electromagnetic imaging of inhomogeneous dielectric cylinders buried in a slab medium by transverse electric (TE) wave illumination is investigated. Dielectric cylinders of unknown permittivities are buried in second space and scattered a group of unrelated waves incident from first space where the scattered field is recorded. By proper arrangement of the various unrelated incident fields, the difficulties of ill-posedness and nonlinearity are circumvented, and the permittivity distribution can be reconstructed through simple matrix operations. The algorithm is based on the moment method and the unrelated illumination method. Numerical results are given to demonstrate the capability of the inverse algorithm. Good reconstruction is obtained even in the presence of additive Gaussian random noise in measured data. In addition, the effect of noise on the reconstruction result is also investigated.Keywords: Slab Medium, Unrelated Illumination Method, TEWave Illumination, Inhomogeneous Cylinders.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11622336 An Iterative Algorithm for Inverse Kinematics of 5-DOF Manipulator with Offset Wrist
Authors: Juyi Park, Jung-Min Kim, Hee-Hwan Park, Jin-Wook Kim, Gye-Hyung Kang, Soo-Ho Kim
Abstract:
This paper presents an iterative algorithm to find a inverse kinematic solution of 5-DOF robot. The algorithm is to minimize the iteration number. Since the 5-DOF robot cannot give full orientation of tool. Only z-direction of tool is satisfied while rotation of tool is determined by kinematic constraint. This work therefore described how to specify the tool direction and let the tool rotation free. The simulation results show that this algorithm effectively worked. Using the proposed iteration algorithm, error due to inverse kinematics converged to zero rapidly in 5 iterations. This algorithm was applied in real welding robot and verified through various practical works.Keywords: 5-DOF manipulator, Inverse kinematics, Iterative algorithm, Wrist offset.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 40812335 The Gerber-Shiu Functions of a Risk Model with Two Classes of Claims and Random Income
Authors: Shan Gao
Abstract:
In this paper, we consider a risk model involving two independent classes of insurance risks and random premium income. We assume that the premium income process is a Poisson Process, and the claim number processes are independent Poisson and generalized Erlang(n) processes, respectively. Both of the Gerber- Shiu functions with zero initial surplus and the probability generating functions (p.g.f.) of the Gerber-Shiu functions are obtained.
Keywords: Poisson process, generalized Erlang risk process, Gerber-Shiu function, generating function, generalized Lundberg equation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12672334 Recovering the Boundary Data in the Two Dimensional Inverse Heat Conduction Problem Using the Ritz-Galerkin Method
Authors: Saeed Sarabadan, Kamal Rashedi
Abstract:
This article presents a numerical method to find the heat flux in an inhomogeneous inverse heat conduction problem with linear boundary conditions and an extra specification at the terminal. The method is based upon applying the satisfier function along with the Ritz-Galerkin technique to reduce the approximate solution of the inverse problem to the solution of a system of algebraic equations. The instability of the problem is resolved by taking advantage of the Landweber’s iterations as an admissible regularization strategy. In computations, we find the stable and low-cost results which demonstrate the efficiency of the technique.Keywords: Inverse problem, parabolic equations, heat equation, Ritz-Galerkin method, Landweber iterations.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11412333 Optimization of Inverse Kinematics of a 3R Robotic Manipulator using Genetic Algorithms
Authors: J. Ramírez A., A. Rubiano F.
Abstract:
In this paper the direct kinematic model of a multiple applications three degrees of freedom industrial manipulator, was developed using the homogeneous transformation matrices and the Denavit - Hartenberg parameters, likewise the inverse kinematic model was developed using the same method, verifying that in the workload border the inverse kinematic presents considerable errors, therefore a genetic algorithm was implemented to optimize the model improving greatly the efficiency of the model.Keywords: Direct Kinematic, Genetic Algorithm, InverseKinematic, Optimization, Robot Manipulator
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32882332 Neural Adaptive Switching Control of Robotic Systems
Authors: A. Denker, U. Akıncıoğlu
Abstract:
In this paper a neural adaptive control method has been developed and applied to robot control. Simulation results are presented to verify the effectiveness of the controller. These results show that the performance by using this controller is better than those which just use either direct inverse control or predictive control. In addition, they show that the resulting is a useful method which combines the advantages of both direct inverse control and predictive control.Keywords: Neural networks, robotics, direct inverse control, predictive control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21322331 Modeling Default Probabilities of the Chosen Czech Banks in the Time of the Financial Crisis
Authors: Petr Gurný
Abstract:
One of the most important tasks in the risk management is the correct determination of probability of default (PD) of particular financial subjects. In this paper a possibility of determination of financial institution’s PD according to the creditscoring models is discussed. The paper is divided into the two parts. The first part is devoted to the estimation of the three different models (based on the linear discriminant analysis, logit regression and probit regression) from the sample of almost three hundred US commercial banks. Afterwards these models are compared and verified on the control sample with the view to choose the best one. The second part of the paper is aimed at the application of the chosen model on the portfolio of three key Czech banks to estimate their present financial stability. However, it is not less important to be able to estimate the evolution of PD in the future. For this reason, the second task in this paper is to estimate the probability distribution of the future PD for the Czech banks. So, there are sampled randomly the values of particular indicators and estimated the PDs’ distribution, while it’s assumed that the indicators are distributed according to the multidimensional subordinated Lévy model (Variance Gamma model and Normal Inverse Gaussian model, particularly). Although the obtained results show that all banks are relatively healthy, there is still high chance that “a financial crisis” will occur, at least in terms of probability. This is indicated by estimation of the various quantiles in the estimated distributions. Finally, it should be noted that the applicability of the estimated model (with respect to the used data) is limited to the recessionary phase of the financial market.
Keywords: Credit-scoring Models, Multidimensional Subordinated Lévy Model, Probability of Default.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18872330 Mathematical Study for Traffic Flow and Traffic Density in Kigali Roads
Authors: Kayijuka Idrissa
Abstract:
This work investigates a mathematical study for traffic flow and traffic density in Kigali city roads and the data collected from the national police of Rwanda in 2012. While working on this topic, some mathematical models were used in order to analyze and compare traffic variables. This work has been carried out on Kigali roads specifically at roundabouts from Kigali Business Center (KBC) to Prince House as our study sites. In this project, we used some mathematical tools to analyze the data collected and to understand the relationship between traffic variables. We applied the Poisson distribution method to analyze and to know the number of accidents occurred in this section of the road which is from KBC to Prince House. The results show that the accidents that occurred in 2012 were at very high rates due to the fact that this section has a very narrow single lane on each side which leads to high congestion of vehicles, and consequently, accidents occur very frequently. Using the data of speeds and densities collected from this section of road, we found that the increment of the density results in a decrement of the speed of the vehicle. At the point where the density is equal to the jam density the speed becomes zero. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized in a series of intelligent management strategies and especially in noncurrent congestion effect detection and control.
Keywords: Statistical methods, Poisson distribution, car moving techniques, traffic flow.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17742329 Artificial Neural Network with Steepest Descent Backpropagation Training Algorithm for Modeling Inverse Kinematics of Manipulator
Authors: Thiang, Handry Khoswanto, Rendy Pangaldus
Abstract:
Inverse kinematics analysis plays an important role in developing a robot manipulator. But it is not too easy to derive the inverse kinematic equation of a robot manipulator especially robot manipulator which has numerous degree of freedom. This paper describes an application of Artificial Neural Network for modeling the inverse kinematics equation of a robot manipulator. In this case, the robot has three degree of freedoms and the robot was implemented for drilling a printed circuit board. The artificial neural network architecture used for modeling is a multilayer perceptron networks with steepest descent backpropagation training algorithm. The designed artificial neural network has 2 inputs, 2 outputs and varies in number of hidden layer. Experiments were done in variation of number of hidden layer and learning rate. Experimental results show that the best architecture of artificial neural network used for modeling inverse kinematics of is multilayer perceptron with 1 hidden layer and 38 neurons per hidden layer. This network resulted a RMSE value of 0.01474.
Keywords: Artificial neural network, back propagation, inverse kinematics, manipulator, robot.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22372328 A Multigrid Approach for Three-Dimensional Inverse Heat Conduction Problems
Authors: Jianhua Zhou, Yuwen Zhang
Abstract:
A two-step multigrid approach is proposed to solve the inverse heat conduction problem in a 3-D object under laser irradiation. In the first step, the location of the laser center is estimated using a coarse and uniform grid system. In the second step, the front-surface temperature is recovered in good accuracy using a multiple grid system in which fine mesh is used at laser spot center to capture the drastic temperature rise in this region but coarse mesh is employed in the peripheral region to reduce the total number of sensors required. The effectiveness of the two-step approach and the multiple grid system are demonstrated by the illustrative inverse solutions. If the measurement data for the temperature and heat flux on the back surface do not contain random error, the proposed multigrid approach can yield more accurate inverse solutions. When the back-surface measurement data contain random noise, accurate inverse solutions cannot be obtained if both temperature and heat flux are measured on the back surface.
Keywords: Conduction, inverse problems, conjugated gradient method, laser.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7972327 Strip Decomposition Parallelization of Fast Direct Poisson Solver on a 3D Cartesian Staggered Grid
Authors: Minh Vuong Pham, Frédéric Plourde, Son Doan Kim
Abstract:
A strip domain decomposition parallel algorithm for fast direct Poisson solver is presented on a 3D Cartesian staggered grid. The parallel algorithm follows the principles of sequential algorithm for fast direct Poisson solver. Both Dirichlet and Neumann boundary conditions are addressed. Several test cases are likewise addressed in order to shed light on accuracy and efficiency in the strip domain parallelization algorithm. Actually the current implementation shows a very high efficiency when dealing with a large grid mesh up to 3.6 * 109 under massive parallel approach, which explicitly demonstrates that the proposed algorithm is ready for massive parallel computing.
Keywords: Strip-decomposition, parallelization, fast directpoisson solver.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20102326 Prediction of the Thermal Parameters of a High-Temperature Metallurgical Reactor Using Inverse Heat Transfer
Authors: Mohamed Hafid, Marcel Lacroix
Abstract:
This study presents an inverse analysis for predicting the thermal conductivities and the heat flux of a high-temperature metallurgical reactor simultaneously. Once these thermal parameters are predicted, the time-varying thickness of the protective phase-change bank that covers the inside surface of the brick walls of a metallurgical reactor can be calculated. The enthalpy method is used to solve the melting/solidification process of the protective bank. The inverse model rests on the Levenberg-Marquardt Method (LMM) combined with the Broyden method (BM). A statistical analysis for the thermal parameter estimation is carried out. The effect of the position of the temperature sensors, total number of measurements and measurement noise on the accuracy of inverse predictions is investigated. Recommendations are made concerning the location of temperature sensors.
Keywords: Inverse heat transfer, phase change, metallurgical reactor, Levenberg–Marquardt method, Broyden method, bank thickness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16522325 Statistical Modeling of Local Area Fading Channels Based on Triply Stochastic Filtered Marked Poisson Point Processes
Authors: Jihad S. Daba, J. P. Dubois
Abstract:
Fading noise degrades the performance of cellular communication, most notably in femto- and pico-cells in 3G and 4G systems. When the wireless channel consists of a small number of scattering paths, the statistics of fading noise is not analytically tractable and poses a serious challenge to developing closed canonical forms that can be analysed and used in the design of efficient and optimal receivers. In this context, noise is multiplicative and is referred to as stochastically local fading. In many analytical investigation of multiplicative noise, the exponential or Gamma statistics are invoked. More recent advances by the author of this paper utilized a Poisson modulated-weighted generalized Laguerre polynomials with controlling parameters and uncorrelated noise assumptions. In this paper, we investigate the statistics of multidiversity stochastically local area fading channel when the channel consists of randomly distributed Rayleigh and Rician scattering centers with a coherent Nakagami-distributed line of sight component and an underlying doubly stochastic Poisson process driven by a lognormal intensity. These combined statistics form a unifying triply stochastic filtered marked Poisson point process model.
Keywords: Cellular communication, femto- and pico-cells, stochastically local area fading channel, triply stochastic filtered marked Poisson point process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13102324 Design of a 4-DOF Robot Manipulator with Optimized Algorithm for Inverse Kinematics
Authors: S. Gómez, G. Sánchez, J. Zarama, M. Castañeda Ramos, J. Escoto Alcántar, J. Torres, A. Núñez, S. Santana, F. Nájera, J. A. Lopez
Abstract:
This paper shows in detail the mathematical model of direct and inverse kinematics for a robot manipulator (welding type) with four degrees of freedom. Using the D-H parameters, screw theory, numerical, geometric and interpolation methods, the theoretical and practical values of the position of robot were determined using an optimized algorithm for inverse kinematics obtaining the values of the particular joints in order to determine the virtual paths in a relatively short time.Keywords: Kinematics, degree of freedom, optimization, robot manipulator.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 60202323 Statistical Modeling of Constituents in Ash Evolved From Pulverized Coal Combustion
Authors: Esam Jassim
Abstract:
Industries using conventional fossil fuels have an interest in better understanding the mechanism of particulate formation during combustion since such is responsible for emission of undesired inorganic elements that directly impact the atmospheric pollution level. Fine and ultrafine particulates have tendency to escape the flue gas cleaning devices to the atmosphere. They also preferentially collect on surfaces in power systems resulting in ascending in corrosion inclination, descending in the heat transfer thermal unit, and severe impact on human health. This adverseness manifests particularly in the regions of world where coal is the dominated source of energy for consumption. This study highlights the behavior of calcium transformation as mineral grains verses organically associated inorganic components during pulverized coal combustion. The influence of existing type of calcium on the coarse, fine and ultrafine mode formation mechanisms is also presented. The impact of two sub-bituminous coals on particle size and calcium composition evolution during combustion is to be assessed. Three mixed blends named Blends 1, 2, and 3 are selected according to the ration of coal A to coal B by weight. Calcium percentage in original coal increases as going from Blend 1 to 3. A mathematical model and a new approach of describing constituent distribution are proposed. Analysis of experiments of calcium distribution in ash is also modeled using Poisson distribution. A novel parameter, called elemental index λ, is introduced as a measuring factor of element distribution. Results show that calcium in ash that originally in coal as mineral grains has index of 17, whereas organically associated calcium transformed to fly ash shown to be best described when elemental index λ is 7. As an alkaline-earth element, calcium is considered the fundamental element responsible for boiler deficiency since it is the major player in the mechanism of ash slagging process. The mechanism of particle size distribution and mineral species of ash particles are presented using CCSEM and size-segregated ash characteristics. Conclusions are drawn from the analysis of pulverized coal ash generated from a utility-scale boiler.
Keywords: Calcium transformation, Coal Combustion, Inorganic Element, Poisson distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19192322 A Note on Toeplitz Matrices
Authors: Hsuan-Chu Li
Abstract:
In this note, we demonstrate explicit LU factorizations of Toeplitz matrices for some small sizes. Furthermore, we obtain the inverse of referred Toeplitz matrices by appling the above-mentioned results.Keywords: Toeplitz matrices, LU factorization, inverse of amatrix.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11442321 Characterization of 3D Printed Re-Entrant Chiral Auxetic Geometries
Authors: Tatheer Zahra
Abstract:
Auxetic materials have counteractive properties due to re-entrant geometry that enables them to possess Negative Poisson’s Ratio (NPR). These materials have better energy absorbing and shock resistance capabilities as compared to conventional positive Poisson’s ratio materials. The re-entrant geometry can be created through 3D printing for convenient application of these materials. This paper investigates the mechanical properties of 3D printed chiral auxetic geometries of various sizes. Small scale samples were printed using an ordinary 3D printer and were tested under compression and tension to ascertain their strength and deformation characteristics. A maximum NPR of -9 was obtained under compression and tension. The re-entrant chiral cell size has been shown to affect the mechanical properties of the re-entrant chiral auxetics.Keywords: Auxetic materials, 3D printing, Negative Poisson’s Ratio, re-entrant chiral auxetics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6212320 A New Algorithm for Determining the Leading Coefficient of in the Parabolic Equation
Authors: Shiping Zhou, Minggen Cui
Abstract:
This paper investigates the inverse problem of determining the unknown time-dependent leading coefficient in the parabolic equation using the usual conditions of the direct problem and an additional condition. An algorithm is developed for solving numerically the inverse problem using the technique of space decomposition in a reproducing kernel space. The leading coefficients can be solved by a lower triangular linear system. Numerical experiments are presented to show the efficiency of the proposed methods.Keywords: parabolic equations, coefficient inverse problem, reproducing kernel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15342319 Loudspeaker Parameters Inverse Problem for Improving Sound Frequency Response Simulation
Authors: Y. T. Tsai, Jin H. Huang
Abstract:
The sound pressure level (SPL) of the moving-coil loudspeaker (MCL) is often simulated and analyzed using the lumped parameter model. However, the SPL of a MCL cannot be simulated precisely in the high frequency region, because the value of cone effective area is changed due to the geometry variation in different mode shapes, it is also related to affect the acoustic radiation mass and resistance. Herein, the paper presents the inverse method which has a high ability to measure the value of cone effective area in various frequency points, also can estimate the MCL electroacoustic parameters simultaneously. The proposed inverse method comprises the direct problem, adjoint problem, and sensitivity problem in collaboration with nonlinear conjugate gradient method. Estimated values from the inverse method are validated experimentally which compared with the measured SPL curve result. Results presented in this paper not only improve the accuracy of lumped parameter model but also provide the valuable information on loudspeaker cone design.
Keywords: Inverse problem, cone effective area, loudspeaker, nonlinear conjugate gradient method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25032318 Solving Single Machine Total Weighted Tardiness Problem Using Gaussian Process Regression
Authors: Wanatchapong Kongkaew
Abstract:
This paper proposes an application of probabilistic technique, namely Gaussian process regression, for estimating an optimal sequence of the single machine with total weighted tardiness (SMTWT) scheduling problem. In this work, the Gaussian process regression (GPR) model is utilized to predict an optimal sequence of the SMTWT problem, and its solution is improved by using an iterated local search based on simulated annealing scheme, called GPRISA algorithm. The results show that the proposed GPRISA method achieves a very good performance and a reasonable trade-off between solution quality and time consumption. Moreover, in the comparison of deviation from the best-known solution, the proposed mechanism noticeably outperforms the recently existing approaches.
Keywords: Gaussian process regression, iterated local search, simulated annealing, single machine total weighted tardiness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21962317 The Inverse Eigenvalue Problem via Orthogonal Matrices
Authors: A. M. Nazari, B. Sepehrian, M. Jabari
Abstract:
In this paper we study the inverse eigenvalue problem for symmetric special matrices and introduce sufficient conditions for obtaining nonnegative matrices. We get the HROU algorithm from [1] and introduce some extension of this algorithm. If we have some eigenvectors and associated eigenvalues of a matrix, then by this extension we can find the symmetric matrix that its eigenvalue and eigenvectors are given. At last we study the special cases and get some remarkable results.
Keywords: Householder matrix, nonnegative matrix, Inverse eigenvalue problem.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1539