Search results for: Closeto- convex Function
1711 Reliability Approximation through the Discretization of Random Variables using Reversed Hazard Rate Function
Authors: Tirthankar Ghosh, Dilip Roy, Nimai Kumar Chandra
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Sometime it is difficult to determine the exact reliability for complex systems in analytical procedures. Approximate solution of this problem can be provided through discretization of random variables. In this paper we describe the usefulness of discretization of a random variable using the reversed hazard rate function of its continuous version. Discretization of the exponential distribution has been demonstrated. Applications of this approach have also been cited. Numerical calculations indicate that the proposed approach gives very good approximation of reliability of complex systems under stress-strength set-up. The performance of the proposed approach is better than the existing discrete concentration method of discretization. This approach is conceptually simple, handles analytic intractability and reduces computational time. The approach can be applied in manufacturing industries for producing high-reliable items.
Keywords: Discretization, Reversed Hazard Rate, Exponential distribution, reliability approximation, engineering item.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26041710 Application of Generalized Autoregressive Score Model to Stock Returns
Authors: Katleho Daniel Makatjane, Diteboho Lawrence Xaba, Ntebogang Dinah Moroke
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The current study investigates the behaviour of time-varying parameters that are based on the score function of the predictive model density at time t. The mechanism to update the parameters over time is the scaled score of the likelihood function. The results revealed that there is high persistence of time-varying, as the location parameter is higher and the skewness parameter implied the departure of scale parameter from the normality with the unconditional parameter as 1.5. The results also revealed that there is a perseverance of the leptokurtic behaviour in stock returns which implies the returns are heavily tailed. Prior to model estimation, the White Neural Network test exposed that the stock price can be modelled by a GAS model. Finally, we proposed further researches specifically to model the existence of time-varying parameters with a more detailed model that encounters the heavy tail distribution of the series and computes the risk measure associated with the returns.
Keywords: Generalized autoregressive score model, stock returns, time-varying.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10231709 Utility Assessment Model for Wireless Technology in Construction
Authors: Y. Abdelrazig, A. Ghanem
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Construction projects are information intensive in nature and involve many activities that are related to each other. Wireless technologies can be used to improve the accuracy and timeliness of data collected from construction sites and shares it with appropriate parties. Nonetheless, the construction industry tends to be conservative and shows hesitation to adopt new technologies. A main concern for owners, contractors or any person in charge on a job site is the cost of the technology in question. Wireless technologies are not cheap. There are a lot of expenses to be taken into consideration, and a study should be completed to make sure that the importance and savings resulting from the usage of this technology is worth the expenses. This research attempts to assess the effectiveness of using the appropriate wireless technologies based on criteria such as performance, reliability, and risk. The assessment is based on a utility function model that breaks down the selection issue into alternatives attribute. Then the attributes are assigned weights and single attributes are measured. Finally, single attribute are combined to develop one single aggregate utility index for each alternative.Keywords: Analytic Hierarchy Process, Utility Function, Wireless Technologies, construction management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19101708 An Improved Conjugate Gradient Based Learning Algorithm for Back Propagation Neural Networks
Authors: N. M. Nawi, R. S. Ransing, M. R. Ransing
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The conjugate gradient optimization algorithm is combined with the modified back propagation algorithm to yield a computationally efficient algorithm for training multilayer perceptron (MLP) networks (CGFR/AG). The computational efficiency is enhanced by adaptively modifying initial search direction as described in the following steps: (1) Modification on standard back propagation algorithm by introducing a gain variation term in the activation function, (2) Calculation of the gradient descent of error with respect to the weights and gains values and (3) the determination of a new search direction by using information calculated in step (2). The performance of the proposed method is demonstrated by comparing accuracy and computation time with the conjugate gradient algorithm used in MATLAB neural network toolbox. The results show that the computational efficiency of the proposed method was better than the standard conjugate gradient algorithm.
Keywords: Adaptive gain variation, back-propagation, activation function, conjugate gradient, search direction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15071707 Aircraft Supplier Selection Process with Fuzzy Proximity Measure Method using Multiple Criteria Group Decision Making Analysis
Authors: C. Ardil
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Being effective in every organizational activity has become necessary due to the escalating level of competition in all areas of corporate life. In the context of supply chain management, aircraft supplier selection is currently one of the most crucial activities. It is possible to choose the best aircraft supplier and deliver efficiency in terms of cost, quality, delivery time, economic status, and institutionalization if a systematic supplier selection approach is used. In this study, an effective multiple criteria decision-making methodology, proximity measure method (PMM), is used within a fuzzy environment based on the vague structure of the real working environment. The best appropriate aircraft suppliers are identified and ranked after the proposed multiple criteria decision making technique is used in a real-life scenario.
Keywords: Aircraft supplier selection, multiple criteria decision making, fuzzy sets, proximity measure method, Minkowski distance family function, Hausdorff distance function, PMM, MCDM
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3091706 Development and Control of Deep Seated Gravitational Slope Deformation: The Case of Colzate-Vertova Landslide, Bergamo, Northern Italy
Authors: Paola Comella, Vincenzo Francani, Paola Gattinoni
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This paper presents the Colzate-Vertova landslide, a Deep Seated Gravitational Slope Deformation (DSGSD) located in the Seriana Valley, Northern Italy. The paper aims at describing the development as well as evaluating the factors that influence the evolution of the landslide. After defining the conceptual model of the landslide, numerical simulations were developed using a finite element numerical model, first with a two-dimensional domain, and later with a three-dimensional one. The results of the 2-D model showed a displacement field typical of a sackung, as a consequence of the erosion along the Seriana Valley. The analysis also showed that the groundwater flow could locally affect the slope stability, bringing about a reduction in the safety factor, but without reaching failure conditions. The sensitivity analysis carried out on the strength parameters pointed out that slope failures could be reached only for relevant reduction of the geotechnical characteristics. Such a result does not fit the real conditions observed on site, where a number of small failures often develop all along the hillslope. The 3-D model gave a more comprehensive analysis of the evolution of the DSGSD, also considering the border effects. The results showed that the convex profile of the slope favors the development of displacements along the lateral valley, with a relevant reduction in the safety factor, justifying the existing landslides.
Keywords: Deep seated gravitational slope deformation, Italy, landslide, numerical modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10131705 Investigation of Stoneley Waves in Multilayered Plates
Authors: Bing Li, Tong Lu, Lei Qiang
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Stoneley waves are interface waves that propagate at the interface between two solid media. In this study, the dispersion characteristics and wave structures of Stoneley waves in elastic multilayered plates are displayed and investigated. With a perspective of bulk wave, a reasonable assumption of the potential function forms of the expansion wave and shear wave in nth layer medium is adopted, and the characteristic equation of Stoneley waves in a three-layered plate is given in a determinant form. The dispersion curves and wave structures are solved and presented in both numerical and simulation results. It is observed that two Stoneley wave modes exist in a three-layered plate, that conspicuous dispersion occurs on low frequency band, that the velocity of each Stoneley wave mode approaches the corresponding Stoneley wave velocity at interface between two half infinite spaces. The wave structures reveal that the in-plane displacement of Stoneley waves are relatively high at interfaces, which shows great potential for interface defects detection.
Keywords: Characteristic equation, interface waves, dispersion curves, potential function, Stoneley waves, wave structures.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16721704 Closely Parametrical Model for an Electrical Arc Furnace
Authors: Labar Hocine, Dgeghader Yacine, Kelaiaia Mounia Samira, Bounaya Kamel
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To maximise furnace production it-s necessary to optimise furnace control, with the objectives of achieving maximum power input into the melting process, minimum network distortion and power-off time, without compromise on quality and safety. This can be achieved with on the one hand by an appropriate electrode control and on the other hand by a minimum of AC transformer switching. Electrical arc is a stochastic process; witch is the principal cause of power quality problems, including voltages dips, harmonic distortion, unbalance loads and flicker. So it is difficult to make an appropriate model for an Electrical Arc Furnace (EAF). The factors that effect EAF operation are the melting or refining materials, melting stage, electrode position (arc length), electrode arm control and short circuit power of the feeder. So arc voltages, current and power are defined as a nonlinear function of the arc length. In this article we propose our own empirical function of the EAF and model, for the mean stages of the melting process, thanks to the measurements in the steel factory.Keywords: Modelling, electrical arc, melting, power, EAF, steel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32361703 Improving Image Segmentation Performance via Edge Preserving Regularization
Authors: Ying-jie Zhang, Li-ling Ge
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This paper presents an improved image segmentation model with edge preserving regularization based on the piecewise-smooth Mumford-Shah functional. A level set formulation is considered for the Mumford-Shah functional minimization in segmentation, and the corresponding partial difference equations are solved by the backward Euler discretization. Aiming at encouraging edge preserving regularization, a new edge indicator function is introduced at level set frame. In which all the grid points which is used to locate the level set curve are considered to avoid blurring the edges and a nonlinear smooth constraint function as regularization term is applied to smooth the image in the isophote direction instead of the gradient direction. In implementation, some strategies such as a new scheme for extension of u+ and u- computation of the grid points and speedup of the convergence are studied to improve the efficacy of the algorithm. The resulting algorithm has been implemented and compared with the previous methods, and has been proved efficiently by several cases.Keywords: Energy minimization, image segmentation, level sets, edge regularization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14861702 Evaluation of Edge Configuration in Medical Echo Images Using Genetic Algorithms
Authors: Ching-Fen Jiang
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Edge detection is usually the first step in medical image processing. However, the difficulty increases when a conventional kernel-based edge detector is applied to ultrasonic images with a textural pattern and speckle noise. We designed an adaptive diffusion filter to remove speckle noise while preserving the initial edges detected by using a Sobel edge detector. We also propose a genetic algorithm for edge selection to form complete boundaries of the detected entities. We designed two fitness functions to evaluate whether a criterion with a complex edge configuration can render a better result than a simple criterion such as the strength of gradient. The edges obtained by using a complex fitness function are thicker and more fragmented than those obtained by using a simple fitness function, suggesting that a complex edge selecting scheme is not necessary for good edge detection in medical ultrasonic images; instead, a proper noise-smoothing filter is the key.Keywords: edge detection, ultrasonic images, speckle noise
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14681701 Limits Problem Solving in Engineering Careers: Competences and Errors
Authors: Veronica Diaz Quezada
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In this article, the performance and errors are featured and analysed in the limit problems solving of a real-valued function, in correspondence to competency-based education in engineering careers, in the south of Chile. The methodological component is contextualised in a qualitative research, with a descriptive and explorative design, with elaboration, content validation and application of quantitative instruments, consisting of two parallel forms of open answer tests, based on limit application problems. The mathematical competences and errors made by students from five engineering careers from a public University are identified and characterized. Results show better performance only to solve routine-context problem-solving competence, thus they are oriented towards a rational solution or they use a suitable problem-solving method, achieving the correct solution. Regarding errors, most of them are related to techniques and the incorrect use of theorems and definitions of real-valued function limits of real variable.
Keywords: Engineering education, errors, limits, mathematics competences, problem solving.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13031700 Digital Redesign of Interval Systems via Particle Swarm Optimization
Authors: Chen-Chien Hsu, Chun-Hui Gao
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In this paper, a PSO-based approach is proposed to derive a digital controller for redesigned digital systems having an interval plant based on resemblance of the extremal gain/phase margins. By combining the interval plant and a controller as an interval system, extremal GM/PM associated with the loop transfer function can be obtained. The design problem is then formulated as an optimization problem of an aggregated error function revealing the deviation on the extremal GM/PM between the redesigned digital system and its continuous counterpart, and subsequently optimized by a proposed PSO to obtain an optimal set of parameters for the digital controller. Computer simulations have shown that frequency responses of the redesigned digital system having an interval plant bare a better resemblance to its continuous-time counter part by the incorporation of a PSO-derived digital controller in comparison to those obtained using existing open-loop discretization methods.Keywords: Digital redesign, Extremal systems, Particle swarm optimization, Uncertain interval systems
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12631699 A Study for Carbonation Degree on Concrete using a Phenolphthalein Indicator and Fourier-Transform Infrared Spectroscopy
Authors: Ho Jae Lee, Do Gyeum Kim, Jang Hwa Lee, Myoung Suk Cho
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A concrete structure is designed and constructed for its purpose of use, and is expected to maintain its function for the target durable years from when it was planned. Nevertheless, as time elapses the structure gradually deteriorates and then eventually degrades to the point where the structure cannot exert the function for which it was planned. The performance of concrete that is able to maintain the level of the performance required over the designed period of use as it has less deterioration caused by the elapse of time under the designed condition is referred to as Durability. There are a number of causes of durability degradation, but especially chloride damage, carbonation, freeze-thaw, etc are the main causes. In this study, carbonation, one of the main causes of deterioration of the durability of a concrete structure, was investigated via a microstructure analysis technique. The method for the measurement of carbonation was studied using the existing indicator method, and the method of measuring the progress of carbonation in a quantitative manner was simultaneously studied using a FT-IR (Fourier-Transform Infrared) Spectrometer along with the microstructure analysis technique.Keywords: Concrete, Carbonation, Microsturcture, FT-IR
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 46221698 Power-Efficient AND-EXOR-INV Based Realization of Achilles' heel Logic Functions
Authors: Padmanabhan Balasubramanian, R. Chinnadurai
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This paper deals with a power-conscious ANDEXOR- Inverter type logic implementation for a complex class of Boolean functions, namely Achilles- heel functions. Different variants of the above function class have been considered viz. positive, negative and pure horn for analysis and simulation purposes. The proposed realization is compared with the decomposed implementation corresponding to an existing standard AND-EXOR logic minimizer; both result in Boolean networks with good testability attribute. It could be noted that an AND-OR-EXOR type logic network does not exist for the positive phase of this unique class of logic function. Experimental results report significant savings in all the power consumption components for designs based on standard cells pertaining to a 130nm UMC CMOS process The simulations have been extended to validate the savings across all three library corners (typical, best and worst case specifications).
Keywords: Achilles' heel functions, AND-EXOR-Inverter logic, CMOS technology, low power design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18641697 Operating Conditions Optimization of Steam Injection in Enhanced Oil Recovery Using Duelist Algorithm
Authors: Totok R. Biyanto, Sonny Irawan, Hiskia J. Ginting, Matradji, Ya’umar, A. I. Fitri
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Steam injection is the most suitable of Enhanced Oil Recovery (EOR) methods to recover high viscosity oil. This is due to the capabilities of steam to reduce oil viscosity and increase the sweep capability of oil from the injection well toward the production well. Oil operating conditions in production should be match well with the operating condition target at the bottom of the production well. It is influenced by oil properties and reservoir rock properties. Hence, the operating condition should be optimized. Optimization requires three components i.e., objective function, model, and optimization technique. In this paper, the objective function is to obtain the optimum operating condition at the production well. The model was built using Darcy equation and mass-energy balance. The optimization technique utilizes Duelist Algorithm due to the effectiveness of its algorithm to obtain the desirable optimization results at the optimum operating condition.Keywords: Enhanced oil recovery, steam injection, operating conditions, modeling, optimization, Duelist algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15651696 Application of Artificial Intelligence for Tuning the Parameters of an AGC
Authors: R. N. Patel
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This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute value of the Error (ITAE) are considered for optimization. The effectiveness of an objective function is considered based on the variation in tie line power and change in frequency in both the areas. MATLAB/SIMULINK was used as a simulation tool. Simulation results reveal that ITAE is a better objective function than ISE. Performances of optimization algorithms are also compared and it was found that genetic algorithm gives better results than particle swarm optimization algorithm for the problems of AGC.
Keywords: Area control error, Artificial intelligence, Automatic generation control, Genetic Algorithms and modeling, ISE, ITAE, Particle swarm optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20151695 Perturbation in the Fractional Fourier Span due to Erroneous Transform Order and Window Function
Authors: Sukrit Shankar, Chetana Shanta Patsa, Jaydev Sharma
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Fractional Fourier Transform is a generalization of the classical Fourier Transform. The Fractional Fourier span in general depends on the amplitude and phase functions of the signal and varies with the transform order. However, with the development of the Fractional Fourier filter banks, it is advantageous in some cases to have different transform orders for different filter banks to achieve better decorrelation of the windowed and overlapped time signal. We present an expression that is useful for finding the perturbation in the Fractional Fourier span due to the erroneous transform order and the possible variation in the window shape and length. The expression is based on the dependency of the time-Fractional Fourier span Uncertainty on the amplitude and phase function of the signal. We also show with the help of the developed expression that the perturbation of span has a varying degree of sensitivity for varying degree of transform order and the window coefficients.Keywords: Fractional Fourier Transform, Perturbation, Fractional Fourier span, amplitude, phase, transform order, filterbanks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14571694 Gold Nanoparticle: Synthesis, Characterization, Clinico-Pathological, Pathological, and Bio-Distribution Studies in Rabbits
Authors: M. M. Bashandy, A. R. Ahmed, M. El-Gaffary, Sahar S. Abd El-Rahman
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This study evaluated the acute toxicity and tissue distribution of intravenously administered gold nanoparticles (AuNPs) in male rabbits. Rabbits were exposed to single dose of AuNPs (300 μg/ kg). Toxic effects were assessed via general behavior, hematological parameters, serum biochemical parameters, and histopathological examination of various rabbits’ organs. Inductively coupled plasma–mass spectrometry (ICP-MS) was used to determine gold concentrations in tissue samples collected at predetermined time intervals. After one week, AuNPs exerted no obvious acute toxicity in rabbits. However, inflammatory reactions were observed in liver, lungs and kidneys accompanied with mild absolute neutrophilia and significant monocytosis. The highest gold levels were found in the spleen and liver followed by lungs, and kidneys. These results indicated that AuNPs could be distributed extensively to various tissues in the body, but primarily in the spleen and liver.Keywords: Gold nanoparticles, toxicity, pathology, hematology, liver function, kidney function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18251693 Base Change for Fisher Metrics: Case of the q−Gaussian Inverse Distribution
Authors: Gabriel I. Loaiza O., Carlos A. Cadavid M., Juan C. Arango P.
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It is known that the Riemannian manifold determined by the family of inverse Gaussian distributions endowed with the Fisher metric has negative constant curvature κ = −1/2 , as does the family of usual Gaussian distributions. In the present paper, firstly we arrive at this result by following a different path, much simpler than the previous ones. We first put the family in exponential form, thus endowing the family with a new set of parameters, or coordinates, θ1, θ2; then we determine the matrix of the Fisher metric in terms of these parameters; and finally we compute this matrix in the original parameters. Secondly, we define the Inverse q−Gaussian distribution family (q < 3), as the family obtained by replacing the usual exponential function by the Tsallis q−exponential function in the expression for the Inverse Gaussian distribution, and observe that it supports two possible geometries, the Fisher and the q−Fisher geometry. And finally, we apply our strategy to obtain results about the Fisher and q−Fisher geometry of the Inverse q−Gaussian distribution family, similar to the ones obtained in the case of the Inverse Gaussian distribution family.
Keywords: Base of Changes, Information Geometry, Inverse Gaussian distribution, Inverse q-Gaussian distribution, Statistical Manifolds.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3571692 Probabilistic Characteristics of older PR Frames in the Mid-America Earthquake Region
Authors: Do-Hwan Kim, Roberto Leon
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Probabilistic characteristics of seismic responses of the Partially Restrained connection rotation (PRCR) and panel zone deformation (PZD) installed in older steel moment frames were investigated in accordance with statistical inference in decision-making process. The 4, 6 and 8 story older steel moment frames with clip angle and T-stub connections were designed and analyzed using 2%/50yrs ground motions in four cities of the Mid-America earthquake region. The probability density function and cumulative distribution function of PRCR and PZD were determined by the goodness-of-fit tests based on probabilistic parameters measured from the results of the nonlinear time-history analyses. The obtained probabilistic parameters and distributions can be used to find out what performance level mainly PR connections and panel zones satisfy and how many PR connections and panel zones experience a serious damage under the Mid-America ground motions.Keywords: Mid-America earthquake, Panel zone, PR connection, Probabilistic characteristics, seismic performance
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14001691 Real-time Laser Monitoring based on Pipe Detective Operation
Authors: Mongkorn Klingajay, Tawatchai Jitson
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The pipe inspection operation is the difficult detective performance. Almost applications are mainly relies on a manual recognition of defective areas that have carried out detection by an engineer. Therefore, an automation process task becomes a necessary in order to avoid the cost incurred in such a manual process. An automated monitoring method to obtain a complete picture of the sewer condition is proposed in this work. The focus of the research is the automated identification and classification of discontinuities in the internal surface of the pipe. The methodology consists of several processing stages including image segmentation into the potential defect regions and geometrical characteristic features. Automatic recognition and classification of pipe defects are carried out by means of using an artificial neural network technique (ANN) based on Radial Basic Function (RBF). Experiments in a realistic environment have been conducted and results are presented.Keywords: Artificial neural network, Radial basic function, Curve fitting, CCTV, Image segmentation, Data acquisition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18001690 A Subtractive Clustering Based Approach for Early Prediction of Fault Proneness in Software Modules
Authors: Ramandeep S. Sidhu, Sunil Khullar, Parvinder S. Sandhu, R. P. S. Bedi, Kiranbir Kaur
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In this paper, subtractive clustering based fuzzy inference system approach is used for early detection of faults in the function oriented software systems. This approach has been tested with real time defect datasets of NASA software projects named as PC1 and CM1. Both the code based model and joined model (combination of the requirement and code based metrics) of the datasets are used for training and testing of the proposed approach. The performance of the models is recorded in terms of Accuracy, MAE and RMSE values. The performance of the proposed approach is better in case of Joined Model. As evidenced from the results obtained it can be concluded that Clustering and fuzzy logic together provide a simple yet powerful means to model the earlier detection of faults in the function oriented software systems.
Keywords: Subtractive clustering, fuzzy inference system, fault proneness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25681689 Modelling Conditional Volatility of Saving Rate by a Time-Varying Parameter Model
Authors: Katleho D. Makatjane, Kalebe M. Kalebe
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The present paper used time-varying parameters which are based on the score function of a probability density at time t to model volatility of saving rate. We used a scaled likelihood function to update the parameters of the model overtime. Our results revealed high diligence of time-varying since the location parameter is greater than zero. Furthermore, we discovered a leptokurtic condition on saving rate’s distribution. Kapetanios, Shin-Shell Nonlinear Augmented Dickey-Fuller (KSS-NADF) test showed that the saving rate has a nonlinear unit root; therefore, it can be modeled by a generalised autoregressive score (GAS) model. Additionally, value at risk (VaR) and conditional tail expectation (CTE) indicate that 99% of the time people in Lesotho are saving more than spending. This puts the economy in high risk of not expanding. Therefore, the monetary policy committee (MPC) of Lesotho should revise their monetary policies towards this high saving rates risk.
Keywords: Generalized autoregressive score, time-varying, saving rate, Lesotho.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6041688 About the Instability Modes of Current Sheet in Wide Range of Frequencies
Authors: V. V. Lyahov, V. M. Neshchadim
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We offer a new technique for research of stability of current sheaths in space plasma taking into account the effect of polarization. At the beginning, the found perturbation of the distribution function is used for calculation of the dielectric permeability tensor, which simulates inhomogeneous medium of a current sheath. Further, we in the usual manner solve the system of Maxwell's equations closed with the material equation. The amplitudes of Fourier perturbations are considered to be exponentially decaying through the current sheath thickness. The dispersion equation follows from the nontrivial solution requirement for perturbations of the electromagnetic field. The resulting dispersion equation allows one to study the temporal and spatial characteristics of instability modes of the current sheath (within the limits of the proposed model) over a wide frequency range, including low frequencies.
Keywords: Current sheath, distribution function, effect of polarization, instability modes, low frequencies, perturbation of electromagnetic field dispersion equation, space plasma, tensor of dielectric permeability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16411687 Fragility Analysis of Weir Structure Subjected to Flooding Water Damage
Authors: Oh Hyeon Jeon, WooYoung Jung
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In this study, seepage analysis was performed by the level difference between upstream and downstream of weir structure for safety evaluation of weir structure against flooding. Monte Carlo Simulation method was employed by considering the probability distribution of the adjacent ground parameter, i.e., permeability coefficient of weir structure. Moreover, by using a commercially available finite element program (ABAQUS), modeling of the weir structure is carried out. Based on this model, the characteristic of water seepage during flooding was determined at each water level with consideration of the uncertainty of their corresponding permeability coefficient. Subsequently, fragility function could be constructed based on this response from numerical analysis; this fragility function results could be used to determine the weakness of weir structure subjected to flooding disaster. They can also be used as a reference data that can comprehensively predict the probability of failur,e and the degree of damage of a weir structure.
Keywords: Weir structure, seepage, flood disaster fragility, probabilistic risk assessment, Monte-Carlo Simulation, permeability coefficient.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11421686 Estimating the Effect of Fluid in Pressing Process
Authors: A. Movaghar, R. A. Mahdavinejad
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To analyze the effect of various parameters of fluid on the material properties such as surface and depth defects and/or cracks, it is possible to determine the affection of pressure field on these specifications. Stress tensor analysis is also able to determine the points in which the probability of defection creation is more. Besides, from pressure field, it is possible to analyze the affection of various fluid specifications such as viscosity and density on defect created in the material. In this research, the concerned boundary conditions are analyzed first. Then the solution network and stencil used are mentioned. With the determination of relevant equation on the fluid flow between notch and matrix and their discretion according to the governed boundary conditions, these equations can be solved. Finally, with the variation creations on fluid parameters such as density and viscosity, the affection of these variations can be determined on pressure field. In this direction, the flowchart and solution algorithm with their results as vortex and current function contours for two conditions with most applications in pressing process are introduced and discussed.
Keywords: Pressing, notch, matrix, flow function, vortex.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6911685 Non-equilibrium Statistical Mechanics of a Driven Lattice Gas Model: Probability Function, FDT-violation, and Monte Carlo Simulations
Authors: K. Sudprasert, M. Precharattana, N. Nuttavut, D. Triampo, B. Pattanasiri, Y. Lenbury, W. Triampo
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The study of non-equilibrium systems has attracted increasing interest in recent years, mainly due to the lack of theoretical frameworks, unlike their equilibrium counterparts. Studying the steady state and/or simple systems is thus one of the main interests. Hence in this work we have focused our attention on the driven lattice gas model (DLG model) consisting of interacting particles subject to an external field E. The dynamics of the system are given by hopping of particles to nearby empty sites with rates biased for jumps in the direction of E. Having used small two dimensional systems of DLG model, the stochastic properties at nonequilibrium steady state were analytically studied. To understand the non-equilibrium phenomena, we have applied the analytic approach via master equation to calculate probability function and analyze violation of detailed balance in term of the fluctuation-dissipation theorem. Monte Carlo simulations have been performed to validate the analytic results.Keywords: Non-equilibrium, lattice gas, stochastic process
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17161684 Multinomial Dirichlet Gaussian Process Model for Classification of Multidimensional Data
Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park
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We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods.Keywords: Multinomial dirichlet classification model, Gaussian process priors, variational Bayesian approximation, Importance sampling, approximate posterior distribution, Marginal likelihood evidence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16041683 Carbon Disulfide Production via Hydrogen Sulfide Methane Reformation
Authors: H. Hosseini, M. Javadi, M. Moghiman, M. H. Ghodsi Rad
Abstract:
Carbon disulfide is widely used for the production of viscose rayon, rubber, and other organic materials and it is a feedstock for the synthesis of sulfuric acid. The objective of this paper is to analyze possibilities for efficient production of CS2 from sour natural gas reformation (H2SMR) (2H2S+CH4 =CS2 +4H2) . Also, the effect of H2S to CH4 feed ratio and reaction temperature on carbon disulfide production is investigated numerically in a reforming reactor. The chemical reaction model is based on an assumed Probability Density Function (PDF) parameterized by the mean and variance of mixture fraction and β-PDF shape. The results show that the major factors influencing CS2 production are reactor temperature. The yield of carbon disulfide increases with increasing H2S to CH4 feed gas ratio (H2S/CH4≤4). Also the yield of C(s) increases with increasing temperature until the temperature reaches to 1000°K, and then due to increase of CS2 production and consumption of C(s), yield of C(s) drops with further increase in the temperature. The predicted CH4 and H2S conversion and yield of carbon disulfide are in good agreement with result of Huang and TRaissi.Keywords: Carbon disulfide, sour natural gas, H2SMR, probability density function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 52401682 Capsule-substrate Adhesion in the Presence of Osmosis by the Immersed Interface Method
Authors: P.G. Jayathilake, B.C. Khoo, Zhijun Tan
Abstract:
A two-dimensional thin-walled capsule of a flexible semi-permeable membrane is adhered onto a rigid planar substrate under adhesive forces (derived from a potential function) in the presence of osmosis across the membrane. The capsule is immersed in a hypotonic and diluted binary solution of a non-electrolyte solute. The Stokes flow problem is solved by the immersed interface method (IIM) with equal viscosities for the enclosed and surrounding fluid of the capsule. The numerical results obtained are verified against two simplified theoretical solutions and the agreements are good. The osmotic inflation of the adhered capsule is studied as a function of the solute concentration field, hydraulic conductivity, and the initial capsule shape. Our findings indicate that the contact length shrinks in dimension as capsule inflates in the hypotonic medium, and the equilibrium contact length does not depend on the hydraulic conductivity of the membrane and the initial shape of the capsule.Keywords: Capsule-substrate adhesion, Fluid mechanics, Immersed interface method, Osmosis, Mass transfer.
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