Search results for: double robust estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4339

Search results for: double robust estimation

4219 Robust Stabilization of Rotational Motion of Underwater Robots against Parameter Uncertainties

Authors: Riku Hayashida, Tomoaki Hashimoto

Abstract:

This paper provides a robust stabilization method for rotational motion of underwater robots against parameter uncertainties. Underwater robots are expected to be used for various work assignments. The large variety of applications of underwater robots motivates researchers to develop control systems and technologies for underwater robots. Several control methods have been proposed so far for the stabilization of nominal system model of underwater robots with no parameter uncertainty. Parameter uncertainties are considered to be obstacles in implementation of the such nominal control methods for underwater robots. The objective of this study is to establish a robust stabilization method for rotational motion of underwater robots against parameter uncertainties. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: robust control, stabilization method, underwater robot, parameter uncertainty

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4218 Optimization Modeling of the Hybrid Antenna Array for the DoA Estimation

Authors: Somayeh Komeylian

Abstract:

The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

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4217 Hardware Implementation of Local Binary Pattern Based Two-Bit Transform Motion Estimation

Authors: Seda Yavuz, Anıl Çelebi, Aysun Taşyapı Çelebi, Oğuzhan Urhan

Abstract:

Nowadays, demand for using real-time video transmission capable devices is ever-increasing. So, high resolution videos have made efficient video compression techniques an essential component for capturing and transmitting video data. Motion estimation has a critical role in encoding raw video. Hence, various motion estimation methods are introduced to efficiently compress the video. Low bit‑depth representation based motion estimation methods facilitate computation of matching criteria and thus, provide small hardware footprint. In this paper, a hardware implementation of a two-bit transformation based low-complexity motion estimation method using local binary pattern approach is proposed. Image frames are represented in two-bit depth instead of full-depth by making use of the local binary pattern as a binarization approach and the binarization part of the hardware architecture is explained in detail. Experimental results demonstrate the difference between the proposed hardware architecture and the architectures of well-known low-complexity motion estimation methods in terms of important aspects such as resource utilization, energy and power consumption.

Keywords: binarization, hardware architecture, local binary pattern, motion estimation, two-bit transform

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4216 Monte Carlo Methods and Statistical Inference of Multitype Branching Processes

Authors: Ana Staneva, Vessela Stoimenova

Abstract:

A parametric estimation of the MBP with Power Series offspring distribution family is considered in this paper. The MLE for the parameters is obtained in the case when the observable data are incomplete and consist only with the generation sizes of the family tree of MBP. The parameter estimation is calculated by using the Monte Carlo EM algorithm. The estimation for the posterior distribution and for the offspring distribution parameters are calculated by using the Bayesian approach and the Gibbs sampler. The article proposes various examples with bivariate branching processes together with computational results, simulation and an implementation using R.

Keywords: Bayesian, branching processes, EM algorithm, Gibbs sampler, Monte Carlo methods, statistical estimation

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4215 Design and Test a Robust Bearing-Only Target Motion Analysis Algorithm Based on Modified Gain Extended Kalman Filter

Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

Abstract:

Passive sonar is a method for detecting acoustic signals in the ocean. It detects the acoustic signals emanating from external sources. With passive sonar, we can determine the bearing of the target only, no information about the range of the target. Target Motion Analysis (TMA) is a process to estimate the position and speed of a target using passive sonar information. Since bearing is the only available information, the TMA technique called Bearing-only TMA. Many TMA techniques have been developed. However, until now, there is not a very effective method that could be used to always track an unknown target and extract its moving trace. In this work, a design of effective Bearing-only TMA Algorithm is done. The measured bearing angles are very noisy. Moreover, for multi-beam sonar, the measurements is quantized due to the sonar beam width. To deal with this, modified gain extended Kalman filter algorithm is used. The algorithm is fine-tuned, and many modules are added to improve the performance. A special validation gate module is used to insure stability of the algorithm. Many indicators of the performance and confidence level measurement are designed and tested. A new method to detect if the target is maneuvering is proposed. Moreover, a reactive optimal observer maneuver based on bearing measurements is proposed, which insure converging to the right solution all of the times. To test the performance of the proposed TMA algorithm a simulation is done with a MATLAB program. The simulator program tries to model a discrete scenario for an observer and a target. The simulator takes into consideration all the practical aspects of the problem such as a smooth transition in the speed, a circular turn of the ship, noisy measurements, and a quantized bearing measurement come for multi-beam sonar. The tests are done for a lot of given test scenarios. For all the tests, full tracking is achieved within 10 minutes with very little error. The range estimation error was less than 5%, speed error less than 5% and heading error less than 2 degree. For the online performance estimator, it is mostly aligned with the real performance. The range estimation confidence level gives a value equal to 90% when the range error less than 10%. The experiments show that the proposed TMA algorithm is very robust and has low estimation error. However, the converging time of the algorithm is needed to be improved.

Keywords: target motion analysis, Kalman filter, passive sonar, bearing-only tracking

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4214 A Fault-Tolerant Full Adder in Double Pass CMOS Transistor

Authors: Abdelmonaem Ayachi, Belgacem Hamdi

Abstract:

This paper presents a fault-tolerant implementation for adder schemes using the dual duplication code. To prove the efficiency of the proposed method, the circuit is simulated in double pass transistor CMOS 32nm technology and some transient faults are voluntary injected in the Layout of the circuit. This fully differential implementation requires only 20 transistors which mean that the proposed design involves 28.57% saving in transistor count compared to standard CMOS technology.

Keywords: digital electronics, integrated circuits, full adder, 32nm CMOS tehnology, double pass transistor technology, fault toleance, self-checking

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4213 Double Burden of Hypertension-Hyperalbuminuria in the Pregnant Women: Cross-Sectional Study of Prevalence and Risk Factors in Foumban, West Region, Cameroon

Authors: Pierre Mintom, Ebai Patricia, Merlin Dasse, Marlyse Chantal Nyangon Ndongo, Aicha Aretouyap Kouotou, Felix Essiben, Christine Fernande Nyangono Biyegue

Abstract:

Background: The death of women during and after pregnancy remains a major concern in public health policy in Cameroon. Among the causes of this mortality is eclampsia which is a consequence of the Pre-eclampsia characterized by the double burden of pregnancy-induced hypertension and albuminuria in pregnant women. Objective: To determine the various factors associated with the pre-eclampsia in pregnant women of Foumban. Methodology: A cross-sectional and analytical study was carried out during the period from July to August 2020 and supplemented by another study carried out from August 05 to September 05, 2022, at the Foumban district hospital. A questionnaire was administered to pregnant women. It focused on socio-demographic parameters, the state nutritional, health status, and maternal parameters. Blood pressure was taken using an electronic blood pressure monitor, and urinary albumin was measuring using urine dipstick. Pre-eclampsia was defined by three types of double burden: double burden systolic hypertension–hyperalbuminuria (SHH), defined for SBP≥140 mmHg and hyperalbuminuria ≥1+ on urine dipstick, double burden diastolic hypertension–hyperalbuminuria (DHH), defined for PAD≥90 mmHg and hyperalbuminuria ≥1+ on the urine dipstick, and the double burden systolodiastolic arterial hypertension– hyperalbuminuria (SDHH), defined for SBP ≥ 140mmHg, PAD≥90 mmHg and hyperalbuminuria ≥1+ on urine dipstick. IBM SPSS Software was used for statistical analysis. Results: The results of this study show that the prevalence of pre-eclampsia was 17.3% for the double burden SHH, 19.9% for the double burden DHH and 14.1% for double burden SDHH. Associated factors with pre-eclampsia according to the three types of double burden were marital status (P<0.05), religion (P<0.05), history of hypertension before pregnancy (P<0.05). Associated factors for the double burden of DHH and SDHH were the nutritional status before the pregnancy (P<0.05) and the number of prenatal consultations (P<0.05). In terms of food groups, regular consumption of spices significantly increased the risk of pre-eclampsia by 5.318, 6.277 and 11.271 times respectively for the SHH, DHH and SDHH double burdens, while regular consumption of sweets regular consumption of sweets increased by 2.42 times and 2.053 times respectively the double DHH and SDHH burdens respectively. Conclusion: Our study made it possible to redefine pre-eclampsia by considering the subtypes of hypertension. Certain socio-demographic parameters and certain dietary habits influence the occurrence of pre-eclampsia characterized by the double burden Hypertension-hyperalbuminuria in pregnant women, which may later lead to the occurrence of eclampsia. Moreover, albuminemia could be a good predicitive factor of pre-eclampsia and could be explored.

Keywords: hypertension, hyperalbuminuria, pregnant women, foumban

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4212 A Novel Search Pattern for Motion Estimation in High Efficiency Video Coding

Authors: Phong Nguyen, Phap Nguyen, Thang Nguyen

Abstract:

High Efficiency Video Coding (HEVC) or H.265 Standard fulfills the demand of high resolution video storage and transmission since it achieves high compression ratio. However, it requires a huge amount of calculation. Since Motion Estimation (ME) block composes about 80 % of calculation load of HEVC, there are a lot of researches to reduce the computation cost. In this paper, we propose a new algorithm to lower the number of Motion Estimation’s searching points. The number of computing points in search pattern is down from 77 for Diamond Pattern and 81 for Square Pattern to only 31. Meanwhile, the Peak Signal to Noise Ratio (PSNR) and bit rate are almost equal to those of conventional patterns. The motion estimation time of new algorithm reduces by at 68.23%, 65.83%compared to the recommended search pattern of diamond pattern, square pattern, respectively.

Keywords: motion estimation, wide diamond, search pattern, H.265, test zone search, HM software

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4211 Using Derivative Free Method to Improve the Error Estimation of Numerical Quadrature

Authors: Chin-Yun Chen

Abstract:

Numerical integration is an essential tool for deriving different physical quantities in engineering and science. The effectiveness of a numerical integrator depends on different factors, where the crucial one is the error estimation. This work presents an error estimator that combines a derivative free method to improve the performance of verified numerical quadrature.

Keywords: numerical quadrature, error estimation, derivative free method, interval computation

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4210 Estimation of Slab Depth, Column Size and Rebar Location of Concrete Specimen Using Impact Echo Method

Authors: Y. T. Lee, J. H. Na, S. H. Kim, S. U. Hong

Abstract:

In this study, an experimental research for estimation of slab depth, column size and location of rebar of concrete specimen is conducted using the Impact Echo Method (IE) based on stress wave among non-destructive test methods. Estimation of slab depth had total length of 1800×300 and 6 different depths including 150 mm, 180 mm, 210 mm, 240 mm, 270 mm and 300 mm. The concrete column specimen was manufactured by differentiating the size into 300×300×300 mm, 400×400×400 mm and 500×500×500 mm. In case of the specimen for estimation of rebar, rebar of ∅22 mm was used in a specimen of 300×370×200 and arranged at 130 mm and 150 mm from the top to the rebar top. As a result of error rate of slab depth was overall mean of 3.1%. Error rate of column size was overall mean of 1.7%. Mean error rate of rebar location was 1.72% for top, 1.19% for bottom and 1.5% for overall mean showing relative accuracy.

Keywords: impact echo method, estimation, slab depth, column size, rebar location, concrete

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4209 An Application of Sinc Function to Approximate Quadrature Integrals in Generalized Linear Mixed Models

Authors: Altaf H. Khan, Frank Stenger, Mohammed A. Hussein, Reaz A. Chaudhuri, Sameera Asif

Abstract:

This paper discusses a novel approach to approximate quadrature integrals that arise in the estimation of likelihood parameters for the generalized linear mixed models (GLMM) as well as Bayesian methodology also requires computation of multidimensional integrals with respect to the posterior distributions in which computation are not only tedious and cumbersome rather in some situations impossible to find solutions because of singularities, irregular domains, etc. An attempt has been made in this work to apply Sinc function based quadrature rules to approximate intractable integrals, as there are several advantages of using Sinc based methods, for example: order of convergence is exponential, works very well in the neighborhood of singularities, in general quite stable and provide high accurate and double precisions estimates. The Sinc function based approach seems to be utilized first time in statistical domain to our knowledge, and it's viability and future scopes have been discussed to apply in the estimation of parameters for GLMM models as well as some other statistical areas.

Keywords: generalized linear mixed model, likelihood parameters, qudarature, Sinc function

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4208 Multi-Criteria Based Robust Markowitz Model under Box Uncertainty

Authors: Pulak Swain, A. K. Ojha

Abstract:

Portfolio optimization is based on dealing with the problems of efficient asset allocation. Risk and Expected return are two conflicting criteria in such problems, where the investor prefers the return to be high and the risk to be low. Using multi-objective approach we can solve those type of problems. However the information which we have for the input parameters are generally ambiguous and the input values can fluctuate around some nominal values. We can not ignore the uncertainty in input values, as they can affect the asset allocation drastically. So we use Robust Optimization approach to the problems where the input parameters comes under box uncertainty. In this paper, we solve the multi criteria robust problem with the help of  E- constraint method.

Keywords: portfolio optimization, multi-objective optimization, ϵ - constraint method, box uncertainty, robust optimization

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4207 Residual Life Estimation Based on Multi-Phase Nonlinear Wiener Process

Authors: Hao Chen, Bo Guo, Ping Jiang

Abstract:

Residual life (RL) estimation based on multi-phase nonlinear Wiener process was studied in this paper, which is significant for complicated products with small samples. Firstly, nonlinear Wiener model with random parameter was introduced and multi-phase nonlinear Wiener model was proposed to model degradation process of products that were nonlinear and separated into different phases. Then the multi-phase RL probability density function based on the presented model was derived approximately in a closed form and parameters estimation was achieved with the method of maximum likelihood estimation (MLE). Finally, the method was applied to estimate the RL of high voltage plus capacitor. Compared with the other three different models by log-likelihood function (Log-LF) and Akaike information criterion (AIC), the results show that the proposed degradation model can capture degradation process of high voltage plus capacitors in a better way and provide a more reliable result.

Keywords: multi-phase nonlinear wiener process, residual life estimation, maximum likelihood estimation, high voltage plus capacitor

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4206 The Acoustic Performance of Double-skin Wind Energy Facade

Authors: Sara Mota Carmo

Abstract:

Wind energy applied in architecture has been largely abandoned due to the uncomfortable noise it causes. This study aims to investigate the acoustical performance in the urban environment and indoor environment of a double-skin wind energy facade. Measurements for sound transmission were recorded by using a hand-held sound meter device on a reduced-scale prototype of a wind energy façade. The applied wind intensities ranged between 2m/s and 8m/s, and the increase sound produced were proportional to the wind intensity.The study validates the acoustic performance of wind energy façade using a double skin façade system, showing that noise reduction indoor by approximately 30 to 35 dB. However, the results found that above 6m/s win intensity, in urban environment, the wind energy system applied to the façade exceeds the maximum 50dB recommended by world health organization and needs some adjustments.

Keywords: double-skin wind energy facade, acoustic energy facade, wind energy in architecture, wind energy prototype

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4205 Identification of Author and Reviewer from Single and Double Blind Paper

Authors: Jatinderkumar R. Saini, Nikita. R. Sonthalia, Khushbu. A. Dodiya

Abstract:

Research leads to development of science and technology and hence to the betterment of humankind. Journals and conferences provide a platform to receive large number of research papers for publications and presentations before the expert and scientific community. In order to assure quality of such papers, they are also sent to reviewers for their comments. In order to maintain good ethical standards, the research papers are sent to reviewers in such a way that they do not know each other’s identity. This technique is called double-blind review process. It is called single-blind review process, if identity of any one party (generally authors) is disclosed to the other. This paper presents the techniques by which identity of author as well as reviewer could be made out even through double-blind review process. It is proposed that the characteristics and techniques presented here will help journals and conferences in assuring intentional or unintentional disclosure of identity revealing information by either party to the other.

Keywords: author, conference, double blind paper, journal, reviewer, single blind paper

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4204 Chemical Reaction Effects on Unsteady MHD Double-Diffusive Free Convective Flow over a Vertical Stretching Plate

Authors: Y. M. Aiyesimi, S. O. Abah, G. T. Okedayo

Abstract:

A general analysis has been developed to study the chemical reaction effects on unsteady MHD double-diffusive free convective flow over a vertical stretching plate. The governing nonlinear partial differential equations have been reduced to the coupled nonlinear ordinary differential equations by the similarity transformations. The resulting equations are solved numerically by using Runge-Kutta shooting technique. The effects of the chemical parameters are examined on the velocity, temperature and concentration profiles.

Keywords: chemical reaction, MHD, double-diffusive, stretching plate

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4203 Forecasting the Volatility of Geophysical Time Series with Stochastic Volatility Models

Authors: Maria C. Mariani, Md Al Masum Bhuiyan, Osei K. Tweneboah, Hector G. Huizar

Abstract:

This work is devoted to the study of modeling geophysical time series. A stochastic technique with time-varying parameters is used to forecast the volatility of data arising in geophysics. In this study, the volatility is defined as a logarithmic first-order autoregressive process. We observe that the inclusion of log-volatility into the time-varying parameter estimation significantly improves forecasting which is facilitated via maximum likelihood estimation. This allows us to conclude that the estimation algorithm for the corresponding one-step-ahead suggested volatility (with ±2 standard prediction errors) is very feasible since it possesses good convergence properties.

Keywords: Augmented Dickey Fuller Test, geophysical time series, maximum likelihood estimation, stochastic volatility model

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4202 Defects Estimation of Embedded Systems Components by a Bond Graph Approach

Authors: I. Gahlouz, A. Chellil

Abstract:

The paper concerns the estimation of system components faults by using an unknown inputs observer. To reach this goal, we used the Bond Graph approach to physical modelling. We showed that this graphical tool is allowing the representation of system components faults as unknown inputs within the state representation of the considered physical system. The study of the causal and structural features of the system (controllability, observability, finite structure, and infinite structure) based on the Bond Graph approach was hence fulfilled in order to design an unknown inputs observer which is used for the system component fault estimation.

Keywords: estimation, bond graph, controllability, observability

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4201 Design and Realization of Double-Delay Line Canceller (DDLC) Using Fpga

Authors: A. E. El-Henawey, A. A. El-Kouny, M. M. Abd –El-Halim

Abstract:

Moving target indication (MTI) which is an anti-clutter technique that limits the display of clutter echoes. It uses the radar received information primarily to display moving targets only. The purpose of MTI is to discriminate moving targets from a background of clutter or slowly-moving chaff particles as shown in this paper. Processing system in these radars is so massive and complex; since it is supposed to perform a great amount of processing in very short time, in most radar applications the response of a single canceler is not acceptable since it does not have a wide notch in the stop-band. A double-delay canceler is an MTI delay-line canceler employing the two-delay-line configuration to improve the performance by widening the clutter-rejection notches, as compared with single-delay cancelers. This canceler is also called a double canceler, dual-delay canceler, or three-pulse canceler. In this paper, a double delay line canceler is chosen for study due to its simplicity in both concept and implementation. Discussing the implementation of a simple digital moving target indicator (DMTI) using FPGA which has distinct advantages compared to other application specific integrated circuit (ASIC) for the purposes of this work. The FPGA provides flexibility and stability which are important factors in the radar application.

Keywords: FPGA, MTI, double delay line canceler, Doppler Shift

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4200 Estimating Lost Digital Video Frames Using Unidirectional and Bidirectional Estimation Based on Autoregressive Time Model

Authors: Navid Daryasafar, Nima Farshidfar

Abstract:

In this article, we make attempt to hide error in video with an emphasis on the time-wise use of autoregressive (AR) models. To resolve this problem, we assume that all information in one or more video frames is lost. Then, lost frames are estimated using analogous Pixels time information in successive frames. Accordingly, after presenting autoregressive models and how they are applied to estimate lost frames, two general methods are presented for using these models. The first method which is the same standard method of autoregressive models estimates lost frame in unidirectional form. Usually, in such condition, previous frames information is used for estimating lost frame. Yet, in the second method, information from the previous and next frames is used for estimating the lost frame. As a result, this method is known as bidirectional estimation. Then, carrying out a series of tests, performance of each method is assessed in different modes. And, results are compared.

Keywords: error steganography, unidirectional estimation, bidirectional estimation, AR linear estimation

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4199 Effect on Bandwidth of Using Double Substrates Based Metamaterial Planar Antenna

Authors: Smrity Dwivedi

Abstract:

The present paper has revealed the effect of double substrates over a bandwidth performance for planar antennas. The used material has its own importance to get minimum return loss and improved directivity. The author has taken double substrates to enhance the efficiency in terms of gain of antenna. Metamaterial based antenna has its own specific structure which increased the performance of antenna. Improved return loss is -20 dB, and the voltage standing wave ratio (VSWR) is 1.2, which is better than single substrate having return loss of -15 dB and VSWR of 1.4. Complete results are obtained using commercial software CST microwave studio.

Keywords: CST microwave studio, metamaterial, return loss, VSWR

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4198 Enhancing Athlete Training using Real Time Pose Estimation with Neural Networks

Authors: Jeh Patel, Chandrahas Paidi, Ahmed Hambaba

Abstract:

Traditional methods for analyzing athlete movement often lack the detail and immediacy required for optimal training. This project aims to address this limitation by developing a Real-time human pose estimation system specifically designed to enhance athlete training across various sports. This system leverages the power of convolutional neural networks (CNNs) to provide a comprehensive and immediate analysis of an athlete’s movement patterns during training sessions. The core architecture utilizes dilated convolutions to capture crucial long-range dependencies within video frames. Combining this with the robust encoder-decoder architecture to further refine pose estimation accuracy. This capability is essential for precise joint localization across the diverse range of athletic poses encountered in different sports. Furthermore, by quantifying movement efficiency, power output, and range of motion, the system provides data-driven insights that can be used to optimize training programs. Pose estimation data analysis can also be used to develop personalized training plans that target specific weaknesses identified in an athlete’s movement patterns. To overcome the limitations posed by outdoor environments, the project employs strategies such as multi-camera configurations or depth sensing techniques. These approaches can enhance pose estimation accuracy in challenging lighting and occlusion scenarios, where pose estimation accuracy in challenging lighting and occlusion scenarios. A dataset is collected From the labs of Martin Luther King at San Jose State University. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing different poses, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced pose detection model and lays the groundwork for future innovations in assistive enhancement technologies.

Keywords: computer vision, deep learning, human pose estimation, U-NET, CNN

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4197 Localization of Near Field Radio Controlled Unintended Emitting Sources

Authors: Nurbanu Guzey, S. Jagannathan

Abstract:

Locating radio controlled (RC) devices using their unintended emissions has a great interest considering security concerns. Weak nature of these emissions requires near field localization approach since it is hard to detect these signals in far field region of array. Instead of only angle estimation, near field localization also requires range estimation of the source which makes this method more complicated than far field models. Challenges of locating such devices in a near field region and real time environment are analyzed in this paper. An ESPRIT like near field localization scheme is utilized for both angle and range estimation. 1-D search with symmetric subarrays is provided. Two 7 element uniform linear antenna arrays (ULA) are employed for locating RC source. Experiment results of location estimation for one unintended emitting walkie-talkie for different positions are given.

Keywords: localization, angle of arrival (AoA), range estimation, array signal processing, ESPRIT, Uniform Linear Array (ULA)

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4196 An Enhanced Floor Estimation Algorithm for Indoor Wireless Localization Systems Using Confidence Interval Approach

Authors: Kriangkrai Maneerat, Chutima Prommak

Abstract:

Indoor wireless localization systems have played an important role to enhance context-aware services. Determining the position of mobile objects in complex indoor environments, such as those in multi-floor buildings, is very challenging problems. This paper presents an effective floor estimation algorithm, which can accurately determine the floor where mobile objects located. The proposed algorithm is based on the confidence interval of the summation of online Received Signal Strength (RSS) obtained from the IEEE 802.15.4 Wireless Sensor Networks (WSN). We compare the performance of the proposed algorithm with those of other floor estimation algorithms in literature by conducting a real implementation of WSN in our facility. The experimental results and analysis showed that the proposed floor estimation algorithm outperformed the other algorithms and provided highest percentage of floor accuracy up to 100% with 95-percent confidence interval.

Keywords: floor estimation algorithm, floor determination, multi-floor building, indoor wireless systems

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4195 Molecular Cloning and Identification of a Double WAP Domain–Containing Protein 3 Gene from Chinese Mitten Crab Eriocheir sinensis

Authors: Fengmei Li, Li Xu, Guoliang Xia

Abstract:

Whey acidic proteins (WAP) domain-containing proteins in crustacean are involved in innate immune response against microbial invasion. In the present study, a novel double WAP domain (DWD)-containing protein gene 3 was identified from Chinese mitten crab Eriocheir sinensis (designated EsDWD3) by expressed sequence tag (EST) analysis and PCR techniques. The full-length cDNA of EsDWD3 was of 1223 bp, consisting of a 5′-terminal untranslated region (UTR) of 74 bp, a 3′ UTR of 727 bp with a polyadenylation signal sequence AATAAA and a polyA tail, and an open reading frame (ORF) of 423 bp. The ORF encoded a polypeptide of 140 amino acids with a signal peptide of 22 amino acids. The deduced protein sequence EsDWD3 showed 96.4 % amino acid similar to other reported EsDWD1 from E. sinensis, and phylogenetic tree analysis revealed that EsDWD3 had closer relationships with the reported two double WAP domain-containing proteins of E. sinensis species.

Keywords: Chinese mitten crab, Eriocheir sinensis, cloning, double WAP domain-containing protein

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4194 Orthogonal Regression for Nonparametric Estimation of Errors-In-Variables Models

Authors: Anastasiia Yu. Timofeeva

Abstract:

Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect.

Keywords: grade point average, orthogonal regression, penalized regression spline, locally weighted regression

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4193 Robust Diagnosis of an Electro-Mechanical Actuators, Bond Graph LFT Approach

Authors: A. Boulanoir, B. Ould Bouamama, A. Debiane, N. Achour

Abstract:

The paper deals with robust Fault Detection and isolation with respect to parameter uncertainties based on linear fractional transformation form (LFT) Bond graph. The innovative interest of the proposed methodology is the use only one representation for systematic generation of robust analytical redundancy relations and adaptive residual thresholds for sensibility analysis. Furthermore, the parameter uncertainties are introduced graphically in the bond graph model. The methodology applied to the nonlinear industrial Electro-Mechanical Actuators (EMA) used in avionic systems, has determined first the structural monitorability analysis (which component can be monitored) with given instrumentation architecture with any need of complex calculation and secondly robust fault indicators for online supervision.

Keywords: bond graph (BG), electro mechanical actuators (EMA), fault detection and isolation (FDI), linear fractional transformation (LFT), mechatronic systems, parameter uncertainties, avionic system

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4192 Residual Lifetime Estimation for Weibull Distribution by Fusing Expert Judgements and Censored Data

Authors: Xiang Jia, Zhijun Cheng

Abstract:

The residual lifetime of a product is the operation time between the current time and the time point when the failure happens. The residual lifetime estimation is rather important in reliability analysis. To predict the residual lifetime, it is necessary to assume or verify a particular distribution that the lifetime of the product follows. And the two-parameter Weibull distribution is frequently adopted to describe the lifetime in reliability engineering. Due to the time constraint and cost reduction, a life testing experiment is usually terminated before all the units have failed. Then the censored data is usually collected. In addition, other information could also be obtained for reliability analysis. The expert judgements are considered as it is common that the experts could present some useful information concerning the reliability. Therefore, the residual lifetime is estimated for Weibull distribution by fusing the censored data and expert judgements in this paper. First, the closed-forms concerning the point estimate and confidence interval for the residual lifetime under the Weibull distribution are both presented. Next, the expert judgements are regarded as the prior information and how to determine the prior distribution of Weibull parameters is developed. For completeness, the cases that there is only one, and there are more than two expert judgements are both focused on. Further, the posterior distribution of Weibull parameters is derived. Considering that it is difficult to derive the posterior distribution of residual lifetime, a sample-based method is proposed to generate the posterior samples of Weibull parameters based on the Monte Carlo Markov Chain (MCMC) method. And these samples are used to obtain the Bayes estimation and credible interval for the residual lifetime. Finally, an illustrative example is discussed to show the application. It demonstrates that the proposed method is rather simple, satisfactory, and robust.

Keywords: expert judgements, information fusion, residual lifetime, Weibull distribution

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4191 A Novel Stator Resistance Estimation Method and Control Design of Speed-Sensorless Induction Motor Drives

Authors: N. Ben Si Ali, N. Benalia, N. Zarzouri

Abstract:

Speed sensorless systems are intensively studied during recent years; this is mainly due to their economical benefit and fragility of mechanical sensors and also the difficulty of installing this type of sensor in many applications. These systems suffer from instability problems and sensitivity to parameter mismatch at low speed operation. In this paper an analysis of adaptive observer stability with stator resistance estimation is given.

Keywords: motor drive, sensorless control, adaptive observer, stator resistance estimation

Procedia PDF Downloads 359
4190 Further Investigation of α+12C and α+16O Elastic Scattering

Authors: Sh. Hamada

Abstract:

The current work aims to study the rainbow like-structure observed in the elastic scattering of alpha particles on both 12C and 16O nuclei. We reanalyzed the experimental elastic scattering angular distributions data for α+12C and α+16O nuclear systems at different energies using both optical model and double folding potential of different interaction models such as: CDM3Y1, DDM3Y1, CDM3Y6 and BDM3Y1. Potential created by BDM3Y1 interaction model has the shallowest depth which reflects the necessity to use higher renormalization factor (Nr). Both optical model and double folding potential of different interaction models fairly reproduce the experimental data.

Keywords: density distribution, double folding, elastic scattering, nuclear rainbow, optical model

Procedia PDF Downloads 222