Search results for: matched field processing; Dopplerlet transform; motion parameter estimation; piecewise strategy

Authors: Huan-Chieh Chiu, Hung-Shuo Wu, Chien-Hao Wang, Yu-Cheng Yang, Ching-Ya Tseng, Joe-Air Jiang

Abstract:

Power failure resulting from tower collapse due to violent seismic events might bring enormous and inestimable losses. The Chi-Chi earthquake, for example, strongly struck Taiwan and caused huge damage to the power system on September 21, 1999. Nearly 10% of extra high voltage (EHV) transmission towers were damaged in the earthquake. Therefore, seismic hazards of EHV transmission towers should be monitored and evaluated. The ultimate goal of this study is to establish a damage level assessment model for EHV transmission towers. The data of earthquakes provided by Taiwan Central Weather Bureau serve as a reference and then lay the foundation for earthquake simulations and analyses afterward. Some parameters related to the damage level of each point of an EHV tower are simulated and analyzed by the data from monitoring stations once an earthquake occurs. Through the Fourier transform, the seismic wave is then analyzed and transformed into different wave frequencies, and the data would be shown through a response spectrum. With this method, the seismic frequency which damages EHV towers the most is clearly identified. An estimation model is built to determine the damage level caused by a future seismic event. Finally, instead of relying on visual observation done by inspectors, the proposed model can provide a power company with the damage information of a transmission tower. Using the model, manpower required by visual observation can be reduced, and the accuracy of the damage level estimation can be substantially improved. Such a model is greatly useful for health and construction monitoring because of the advantages of long-term evaluation of structural characteristics and long-term damage detection.

Keywords: Smart grid, EHV transmission tower, response spectrum, damage level monitoring.

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Authors: Akinola Ikudayisi, Josiah Adeyemo

Abstract:

The correct estimation of reference evapotranspiration (ETₒ) is required for effective irrigation water resources planning and management. However, there are some variables that must be considered while estimating and modeling ETₒ. This study therefore determines the multivariate analysis of correlated variables involved in the estimation and modeling of ETₒ at Vaalharts irrigation scheme (VIS) in South Africa using Principal Component Analysis (PCA) technique. Weather and meteorological data between 1994 and 2014 were obtained both from South African Weather Service (SAWS) and Agricultural Research Council (ARC) in South Africa for this study. Average monthly data of minimum and maximum temperature (°C), rainfall (mm), relative humidity (%), and wind speed (m/s) were the inputs to the PCA-based model, while ETₒ is the output. PCA technique was adopted to extract the most important information from the dataset and also to analyze the relationship between the five variables and ETₒ. This is to determine the most significant variables affecting ETₒ estimation at VIS. From the model performances, two principal components with a variance of 82.7% were retained after the eigenvector extraction. The results of the two principal components were compared and the model output shows that minimum temperature, maximum temperature and windspeed are the most important variables in ETₒ estimation and modeling at VIS. In order words, ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity are less important and cannot be used to provide enough information about ETₒ estimation at VIS. The outcome of this study has helped to reduce input variable dimensionality from five to the three most significant variables in ETₒ modelling at VIS, South Africa.

Keywords: Irrigation, principal component analysis, reference evapotranspiration, Vaalharts.

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

Abstract:

Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: Deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator.

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Authors: N. Q. Bau, N. V. Nghia

Abstract:

The acoustomagnetoelectric (AME) field in a rectangular quantum wire with an infinite potential (RQWIP) is calculated in the presence of an external magnetic field (EMF) by using the quantum kinetic equation for the distribution function of electrons system interacting with external phonons and electrons scattering with internal acoustic phonon in a RQWIP. We obtained ananalytic expression for the AME field in the RQWIP in the presence of the EMF. The dependence of AME field on the frequency of external acoustic wave, the temperature T of system, the cyclotron frequency of the EMF and the intensity of the EMF is obtained. Theoretical results for the AME field are numerically evaluated, plotted and discussed for a specific RQWIP GaAs/GaAsAl. This result has shown that the dependence of the AME field on intensity of the EMF is nonlinearly and it is many distinct maxima in the quantized magnetic region. We also compared received fields with those for normal bulk semiconductors, quantum well and quantum wire to show the difference. The influence of an EMF on AME field in a RQWIP is newly developed.

Keywords: Rectangular quantum wire, acoustomagnetoelectric field, electron-phonon interaction, kinetic equation method.

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Authors: Evariste Norbert Boj, Jan Schee

Abstract:

We present the calculations of the temperature anisotropy of the cosmic microwave background radiation (CMBR) caused by an inhomogeneous region (the clump) within the Friedmann-Lemaitre-Robertson-Walker (FLRW) model of the Universe build in the framework of the Randall-Sundrum one brane model. We present two spherically symmetrical and statical models of the clump, the braneworld Reissner-Nordstrom black hole (bRNBH) and the perfect fluid sphere of uniform density matched to the FLRW spacetime via an external bRNBH. The boundary of the vacuum region expands, which induces an additional frequency shift to a photon of the CMBR passing through this inhomogeneity in comparison to the case of a photon propagating through a pure FLRW spacetime. This frequency shift is associated with an effective change of temperature of the CMBR in the corresponding direction. We give estimates on the changes of the effective temperature of the CMBR’s photon with the change of parameters describing the brane and the induced tidal forces from the bulk.

Keywords: Braneworld, CMBR, Randall-Sundrum model, Rees-Sciama effect, Reissner-Nordstrom black hole.

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Authors: Changjin Xu, Qianhong Zhang

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In this paper, a delayed competitive system with the effect of toxic substances is investigated. With the aid of differential equations with piecewise constant arguments, a discrete analogue of continuous non-autonomous delayed competitive system with the effect of toxic substances is proposed. By using Gaines and Mawhin,s continuation theorem of coincidence degree theory, a easily verifiable sufficient condition for the existence of positive solutions of difference equations is obtained.

Keywords: Competitive system, periodic solution, discrete time delay, topological degree.

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Authors: Andreas Theissler, Ian Dear

Abstract:

The one-class support vector machine “support vector data description” (SVDD) is an ideal approach for anomaly or outlier detection. However, for the applicability of SVDD in real-world applications, the ease of use is crucial. The results of SVDD are massively determined by the choice of the regularisation parameter C and the kernel parameter  of the widely used RBF kernel. While for two-class SVMs the parameters can be tuned using cross-validation based on the confusion matrix, for a one-class SVM this is not possible, because only true positives and false negatives can occur during training. This paper proposes an approach to find the optimal set of parameters for SVDD solely based on a training set from one class and without any user parameterisation. Results on artificial and real data sets are presented, underpinning the usefulness of the approach.

Keywords: Support vector data description, anomaly detection, one-class classification, parameter tuning.

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Authors: Yisheng Rong, Jian Sun, Weiqiang Liu, Renjun Zhan

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A CFD study on heat flux reduction in hypersonic flow with opposing jet has been conducted. Flowfield parameters, reattachment point position, surface pressure distributions and heat flux distributions are obtained and validated with experiments. The physical mechanism of heat reduction has been analyzed. When the opposing jet blows, the freestream is blocked off, flows to the edges and not interacts with the surface to form aerodynamic heating. At the same time, the jet flows back to form cool recirculation region, which reduces the difference in temperature between the surface and the nearby gas, and then reduces the heat flux. As the pressure ratio increases, the interface between jet and freestream is gradually pushed away from the surface. Larger the total pressure ratio is, lower the heat flux is. To study the effect of the intensity of opposing jet more reasonably, a new parameter RPA has been introduced by combining the flux and the total pressure ratio. The study shows that the same shock wave position and total heat load can be obtained with the same RPA with different fluxes and the total pressures, which means the new parameter could stand for the intensity of opposing jet and could be used to analyze the influence of opposing jet on flow field and aerodynamic heating.

Keywords: opposing jet, aerodynamic heating, total pressure ratio, thermal protection system

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Authors: R. O’Reilly Meehan, D. B. Murray

Abstract:

In many practical situations, bubbles are dispersed in a liquid phase. Understanding these complex bubbly flows is therefore a key issue for applications such as shell and tube heat exchangers, mineral flotation and oxidation in water treatment. Although a large body of work exists for bubbles rising in an unbounded medium, that of bubbles rising in constricted geometries has received less attention. The particular case of a bubble sliding underneath an inclined surface is common to two-phase flow systems. The current study intends to expand this knowledge by performing experiments to quantify the streamwise flow structures associated with a single sliding air bubble under an inclined surface in quiescent water. This is achieved by means of two-dimensional, two-component particle image velocimetry (PIV), performed with a continuous wave laser and high-speed camera. PIV vorticity fields obtained in a plane perpendicular to the sliding surface show that there is significant bulk fluid motion away from the surface. The associated momentum of the bubble means that this wake motion persists for a significant time before viscous dissipation. The magnitude and direction of the flow structures in the streamwise measurement plane are found to depend on the point on its path through which the bubble enters the plane. This entry point, represented by a phase angle, affects the nature and strength of the vortical structures. This study reconstructs the vorticity field in the wake of the bubble, converting the field at different instances in time to slices of a large-scale wake structure. This is, in essence, Taylor’s ”frozen turbulence” hypothesis. Applying this to the vorticity fields provides a pseudo three-dimensional representation from 2-D data, allowing for a more intuitive understanding of the bubble wake. This study provides insights into the complex dynamics of a situation common to many engineering applications, particularly shell and tube heat exchangers in the nucleate boiling regime.

Keywords: Bubbly flow, particle image velocimetry, two-phase flow, wake structures.

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Authors: Dinesh Rao, M.G.M. Khan, Sabiha Khan

Abstract:

Calibration estimation is a method of adjusting the original design weights to improve the survey estimates by using auxiliary information such as the known population total (or mean) of the auxiliary variables. A calibration estimator uses calibrated weights that are determined to minimize a given distance measure to the original design weights while satisfying a set of constraints related to the auxiliary information. In this paper, we propose a new multivariate calibration estimator for the population mean in the stratified sampling design, which incorporates information available for more than one auxiliary variable. The problem of determining the optimum calibrated weights is formulated as a Mathematical Programming Problem (MPP) that is solved using the Lagrange multiplier technique.

Keywords: Calibration estimation, Stratified sampling, Multivariate auxiliary information, Mathematical programming problem, Lagrange multiplier technique.

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Authors: G. L. C. Yap

Abstract:

Modelling realized volatility with high-frequency returns is popular as it is an unbiased and efficient estimator of return volatility. A computationally simple model is fitting the logarithms of the realized volatilities with a fractionally integrated long-memory Gaussian process. The Gaussianity assumption simplifies the parameter estimation using the Whittle approximation. Nonetheless, this assumption may not be met in the finite samples and there may be a need to normalize the financial series. Based on the empirical indices S&P500 and DAX, this paper examines the performance of the linear volatility model pre-treated with normalization compared to its existing counterpart. The empirical results show that by including normalization as a pre-treatment procedure, the forecast performance outperforms the existing model in terms of statistical and economic evaluations.

Keywords: Long-memory, Gaussian process, Whittle estimator, normalization, volatility, value-at-risk.

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Authors: Hongbin Gu, Dongsu Wu, Hui Liu

Abstract:

A novel low-cost flight simulator with the development goals cost effectiveness and high performance has been realized for meeting the huge pilot training needs of airlines. The simulator consists of an aircraft dynamics model, a sophisticated designed low-profile electrical driven motion system with a subsided cabin, a mixed reality based semi-virtual cockpit system, a control loading system and some other subsystems. It shows its advantages over traditional flight simulator by its features achieved with open architecture, software solutions and low-cost hardware.

Keywords: Flight simulator, mixed reality, motion system, control loading system.

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Authors: Seyed Nima Tayarani Bathaie

Abstract:

In this paper, an image-receiving system was designed and implemented through optimization of object detection algorithms using Haar features. This optimized algorithm served as face and eye detection separately. Then, cascading them led to a clear image of the user. Utilization of this feature brought about higher security by preventing fraud. This attribute results from the fact that services will be given to the user on condition that a clear image of his face has already been captured which would exclude the inappropriate person. In order to expedite processing and eliminating unnecessary ones, the input image was compressed, a motion detection function was included in the program, and detection window size was confined.

Keywords: Face detection algorithm, Haar features, Security of ATM.

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Authors: Irwin Ma, Tony Wong, Thiagas Sankar

Abstract:

By systematically applying different engineering methods, difficult financial problems become approachable. Using a combination of theory and techniques such as wavelet transform, time series data mining, Markov chain based discrete stochastic optimization, and evolutionary algorithms, this work formulated a strategy to characterize and forecast non-linear time series. It attempted to extract typical features from the volatility data sets of S&P100 and S&P500 indices that include abrupt drops, jumps and other non-linearity. As a result, accuracy of forecasting has reached an average of over 75% surpassing any other publicly available results on the forecast of any financial index.

Keywords: Discrete stochastic optimization, genetic algorithms, genetic programming, volatility forecast

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Authors: Siddharth Ahuja, T. M. Muruganandam

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An analytical investigation is performed to study the unsteady response of a one-dimensional, non-linear dynamic shock system to external downstream pressure perturbations in a supersonic flow in a varying area duct. For a given pressure ratio across a wind tunnel, the normal shock's location can be computed as per one-dimensional steady gas dynamics. Similarly, for some other pressure ratio, the location of the normal shock will change accordingly, again computed using one-dimensional gas dynamics. This investigation focuses on the small-time interval between the first steady shock location and the new steady shock location (corresponding to different pressure ratios). In essence, this study aims to shed light on the motion of the shock from one steady location to another steady location. Further, this study aims to create the foundation of the Unsteady Gas Dynamics field enabling further insight in future research work. According to the new pressure ratio, a pressure pulse, generated at the exit of the tunnel which travels and perturbs the shock from its original position, setting it into motion. During such activity, other numerous physical phenomena also happen at the same time. However, three broad phenomena have been focused on, in this study - Traversal of a Wave, Fluid Element Interactions and Wave Interactions. The above mentioned three phenomena create, alter and kill numerous waves for different conditions. The waves which are created by the above-mentioned phenomena eventually interact with the shock and set it into motion. Numerous such interactions with the shock will slowly make it settle into its final position owing to the new pressure ratio across the duct, as estimated by one-dimensional gas dynamics. This analysis will be extremely helpful in the prediction of inlet 'unstart' of the flow in a supersonic engine intake and its prominence with the incoming flow Mach number, incoming flow pressure and the external perturbation pressure is also studied to help design more efficient supersonic intakes for engines like ramjets and scramjets.

Keywords: Analytical investigation, compression and expansion waves, fluid element interactions, shock trajectory, supersonic flow, unsteady gas dynamics, varying area duct, wave interactions.

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Authors: Ryosuke Ito, Goro Obinata, Chikara Nagai, Youngwoo Kim

Abstract:

This paper proposes a new parameter identification method based on Linear Fractional Transformation (LFT). It is assumed that the target linear system includes unknown parameters. The parameter deviations are separated from a nominal system via LFT, and identified by organizing I/O signals around the separated deviations of the real system. The purpose of this paper is to apply LFT to simultaneously identify the parameter deviations in systems with fewer outputs than unknown parameters. As a fundamental example, this method is implemented to one degree of freedom vibratory system. Via LFT, all physical parameters were simultaneously identified in this system. Then, numerical simulations were conducted for this system to verify the results. This study shows that all the physical parameters of a system with fewer outputs than unknown parameters can be effectively identified simultaneously using LFT.

Keywords: Identification, Linear Fractional Transformation, Right inverse system

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Authors: Chan Hee Park, Arim Lee, Jung Min Lee, Joo Hyun Moon

Abstract:

Accident in spent fuel pool (SFP) of Fukushima Daiichi Unit 4 showed the importance of continuous monitoring of the key environmental parameters such as water temperature, water level, and radiation level in the SFP at accident conditions. Because the SFP water temperature is one of the key parameters indicating SFP conditions, its behavior at accident conditions shall be understood to prepare appropriate measures. This study estimated temporal change in the SFP water temperature at Kori Unit 1 with 587 MWe for 1 hour after initiation of a loss-of-pool-cooling accident. For the estimation, ANSYS CFX 13.0 code was used. The estimation showed that the increasing rate of the water temperature was 3.90C per hour and the SFP water temperature could reach 1000C in 25.6 hours after the initiation of loss-of-pool-cooling accident.

Keywords: Spent fuel pool, water temperature, Kori Unit 1, a loss-of-pool-cooling accident.

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Authors: Bhumika Gupta, Jeayaram Subramanian, Hardik Vachhrajani, Avinash Shivdas

Abstract:

Indian food processing industry is one of the largest in the world in terms of production, consumption, exports and growth opportunities. SMEs play a crucial role within this. Large manufacturing firms largely dominate innovation studies in India. Innovation sources used by SMEs are often different from that of large firms. This paper focuses on exploring various sources of innovation adopted by food processing SMEs in Kerala, South India. Outcome suggests that SMEs use various sources like suppliers, competitors, employees, government/research institutions and customers to get new ideas.

Keywords: Food processing, innovation, SMEs, sources of innovation.

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Authors: Asma Alyahya

Abstract:

This study attempts to elicit the perceptions and attitudes of EFL learners of the Preparatory Year Program at KSU towards dialogue journal writing as an EFL learning strategy. The descriptive research design used incorporated both qualitative and quantitative instruments to accomplish the objectives of the study. A learners’ attitude questionnaire and follow-up interviewswith learners from a randomly selected representative sample of the participants were employed. The participants were 55 female Saudi university students in the Preparatory Year Program at King Saud University. The analysis of the results indicated that the PYP learners had highly positive attitudes towards dialogue journal writing in their EFL classes and positive perceptions of the benefits of the use of dialogue journal writing as an EFL learning strategy. The results also revealed that dialogue journals are considered an effective EFL learning strategy since they fulfill various needs for both learners and instructors. Interestingly, the analysis of the results also revealed that Saudi university level students tend to write about personal topics in their dialogue journals more than academic ones.

Keywords: Dialogue journals, EFL, learning strategy, writing.

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Authors: Yusuke Onoue, Seiji Fujino, Norimasa Nakashima

Abstract:

The IDR(s) method based on an extended IDR theorem was proposed by Sonneveld and van Gijzen. The original IDR(s) method has excellent property compared with the conventional iterative methods in terms of efficiency and small amount of memory. IDR(s) method, however, has unexpected property that relative residual 2-norm stagnates at the level of less than 10-12. In this paper, an effective strategy for stagnation detection, stagnation avoidance using adaptively information of parameter s and improvement of convergence rate itself of IDR(s) method are proposed in order to gain high accuracy of the approximated solution of IDR(s) method. Through numerical experiments, effectiveness of adaptive tuning IDR(s) method is verified and demonstrated.

Keywords: Krylov subspace methods, IDR(s), adaptive tuning, stagnation of relative residual.

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Authors: Shun-Chang Chang

Abstract:

In this paper, different nonlinear dynamics analysis techniques are employed to unveil the rich nonlinear phenomena of the electromagnetic system. In particular, bifurcation diagrams, time responses, phase portraits, Poincare maps, power spectrum analysis, and the construction of basins of attraction are all powerful and effective tools for nonlinear dynamics problems. We also employ the method of Lyapunov exponents to show the occurrence of chaotic motion and to verify those numerical simulation results. Finally, two cases of a chaotic electromagnetic system being effectively controlled by a reference signal or being synchronized to another nonlinear electromagnetic system are presented.

Keywords: bifurcation, Poincare map, Lyapunov exponent, chaotic motion.

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Authors: H. Sagha, S. Kasaei, E. Enayati, M. Dehghani

Abstract:

Although Face detection is not a recent activity in the field of image processing, it is still an open area for research. The greatest step in this field is the work reported by Viola and its recent analogous is Huang et al. Both of them use similar features and also similar training process. The former is just for detecting upright faces, but the latter can detect multi-view faces in still grayscale images using new features called 'sparse feature'. Finding these features is very time consuming and inefficient by proposed methods. Here, we propose a new approach for finding sparse features using a genetic algorithm system. This method requires less computational cost and gets more effective features in learning process for face detection that causes more accuracy.

Keywords: Face Detection, Genetic Algorithms, Sparse Feature.

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Authors: Kedit J.

Abstract:

This paper is the tomographic images reconstruction simulation for defects detection in specimen. The specimen is the thin cylindrical steel contained with low density materials. The defects in material are simulated in three shapes.The specimen image function will be transformed to projection data. Radon transform and its inverse provide the mathematical for reconstructing tomographic images from projection data. The result of the simulation show that the reconstruction images is complete for defect detection.

Keywords: Tomography, Tomography Reconstruction, Radon Transform

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Authors: H. Bakhshi, E. Khayyamian

Abstract:

Cognitive radios have been recognized as one of the most promising technologies dealing with the scarcity of the radio spectrum. In cognitive radio systems, secondary users are allowed to utilize the frequency bands of primary users when the bands are idle. Hence, how to accurately detect the idle frequency bands has attracted many researchers’ interest. Detection performance is sensitive toward noise power and gain fluctuation. Since signal to noise ratio (SNR) between primary user and secondary users are not the same and change over the time, SNR and noise power estimation is essential. In this paper, we present a cooperative spectrum sensing algorithm using SNR estimation to improve detection performance in the real situation.

Keywords: Cognitive radio, cooperative spectrum sensing, energy detection, SNR estimation, spectrum sensing, Rayleigh fading channel.

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Authors: A. Falsafain, S. M. Taheri, M. Mashinchi

Abstract:

Using a set of confidence intervals, we develop a common approach, to construct a fuzzy set as an estimator for unknown parameters in statistical models. We investigate a method to derive the explicit and unique membership function of such fuzzy estimators. The proposed method has been used to derive the fuzzy estimators of the parameters of a Normal distribution and some functions of parameters of two Normal distributions, as well as the parameters of the Exponential and Poisson distributions.

Keywords: Confidence interval. Fuzzy number. Fuzzy estimation.

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Authors: Yanan Yang, Zhigang Wang, Xiang Chen

Abstract:

This paper presents the use of Legendre pseudospectral method for the optimization of finite-thrust orbital transfer for spacecrafts. In order to get an accurate solution, the System-s dynamics equations were normalized through a dimensionless method. The Legendre pseudospectral method is based on interpolating functions on Legendre-Gauss-Lobatto (LGL) quadrature nodes. This is used to transform the optimal control problem into a constrained parameter optimization problem. The developed novel optimization algorithm can be used to solve similar optimization problems of spacecraft finite-thrust orbital transfer. The results of a numerical simulation verified the validity of the proposed optimization method. The simulation results reveal that pseudospectral optimization method is a promising method for real-time trajectory optimization and provides good accuracy and fast convergence.

Keywords: Finite-thrust, Orbital transfer, Legendre pseudospectral method

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Authors: Mojtaba Mahdavi, Mohamad Mahdavi, Maryam Yazdani

Abstract:

A heuristic conceptual model for to develop the Reliability Centered Maintenance (RCM), especially in preventive strategy, has been explored during this paper. In most real cases which complicity of system obligates high degree of reliability, this model proposes a more appropriate reliability function between life time distribution based and another which is based on relevant Extreme Value (EV) distribution. A statistical and mathematical approach is used to estimate and verify these two distribution functions. Then best one is chosen just among them, whichever is more reliable. A numeric Industrial case study will be reviewed to represent the concepts of this paper, more clearly.

Keywords: Lifetime distribution, Reliability, Estimation, Extreme value, Improving model, Series, Parallel.

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Authors: M.J. Park, K.H. Kim, O.M. Kwon

Abstract:

This paper proposes a delay-dependent leader-following consensus condition of multi-agent systems with both communication delay and probabilistic self-delay. The proposed methods employ a suitable piecewise Lyapunov-Krasovskii functional and the average dwell time approach. New consensus criterion for the systems are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Numerical example showed that the proposed method is effective.

Keywords: Multi-agent systems, probabilistic self-delay, consensus, Lyapunov method, LMI.

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Authors: Ketan Naik, P. H. Bhathawala

Abstract:

The purpose of this work is to develop a mathematical model of Human Cardiovascular System using lumped parameter method. The model is divided in three parts: Systemic Circulation, Pulmonary Circulation and the Heart. The established mathematical model has been simulated by MATLAB software. The innovation of this study is in describing the system based on the vessel diameters and simulating mathematical equations with active electrical elements. Terminology of human physical body and required physical data like vessel’s radius, thickness etc., which are required to calculate circuit parameters like resistance, inductance and capacitance, are proceeds from well-known medical books. The developed model is useful to understand the anatomic of human cardiovascular system and related syndromes. The model is deal with vessel’s pressure and blood flow at certain time.

Keywords: Cardiovascular system, lumped parameter method, mathematical modeling, simulation.

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Authors: V. Churkin, M. Lopatin

Abstract:

The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second – 95,3%.

Keywords: Bass model, generalized Bass model, replacement purchases, sales forecasting of innovations, statistics of sales of small wind turbines in the United States.

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