Search results for: aposteriori error estimate

Authors: Qiang Niu, Linzhang Lu

Abstract:

Restarted GMRES methods augmented with approximate eigenvectors are widely used for solving large sparse linear systems. Recently a new scheme of augmenting with error approximations is proposed. The main aim of this paper is to develop a restarted GMRES method augmented with the combination of harmonic Ritz vectors and error approximations. We demonstrate that the resulted combination method can gain the advantages of two approaches: (i) effectively deflate the small eigenvalues in magnitude that may hamper the convergence of the method and (ii) partially recover the global optimality lost due to restarting. The effectiveness and efficiency of the new method are demonstrated through various numerical examples.

Keywords: Arnoldi process, GMRES, Krylov subspace, systems of linear equations.

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Authors: Susmita Das, Kala Praveen Bagadi

Abstract:

SDMA (Space-Division Multiple Access) is a MIMO (Multiple-Input and Multiple-Output) based wireless communication network architecture which has the potential to significantly increase the spectral efficiency and the system performance. The maximum likelihood (ML) detection provides the optimal performance, but its complexity increases exponentially with the constellation size of modulation and number of users. The QR decomposition (QRD) MUD can be a substitute to ML detection due its low complexity and near optimal performance. The minimum mean-squared-error (MMSE) multiuser detection (MUD) minimises the mean square error (MSE), which may not give guarantee that the BER of the system is also minimum. But the minimum bit error rate (MBER) MUD performs better than the classic MMSE MUD in term of minimum probability of error by directly minimising the BER cost function. Also the MBER MUD is able to support more users than the number of receiving antennas, whereas the rest of MUDs fail in this scenario. In this paper the performance of various MUD techniques is verified for the correlated MIMO channel models based on IEEE 802.16n standard.

Keywords: Multiple input multiple output, multiuser detection, orthogonal frequency division multiplexing, space division multiple access, Bit error rate

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Authors: Chana Raksiri, Pornchai Chatchaikulsiri

Abstract:

The objective of this research is parameters optimized of the stair shape workpiece which is cut by CNC Wire-Cut EDM (WEDW). The experiment material is SKD-11 steel of stair-shaped with variable height workpiece 10, 20, 30 and 40 mm. with the same 10 mm. thickness are cut by Sodick's CNC Wire-Cut EDM model AD325L. The experiments are designed by 3k full factorial experimental design at 3 level 2 factors and 9 experiments with 2 replicate. The selected two factor are servo voltage (SV) and servo feed rate (SF) and the response is cutting thickness error. The experiment is divided in two experiments. The first experiment determines the significant effective factor at confidential interval 95%. The SV factor is the significant effective factor from first result. In order to result smallest cutting thickness error of workpieces is 17 micron with the SV value is 46 volt. Also show that the lower SV value, the smaller different thickness error of workpiece. Then the second experiment is done to reduce different cutting thickness error of workpiece as small as possible by lower SV. The second experiment result show the significant effective factor at confidential interval 95% is the SV factor and the smallest cutting thickness error of workpieces reduce to 11 micron with the experiment SV value is 36 volt.

Keywords: CNC Wire-Cut, Variable Thickness Workpiece, Design of Experiments, Full Factorial Design

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Authors: M. Pourahmadi

Abstract:

The performance of time-reversal MUSIC algorithm will be dramatically degrades in presence of strong noise and multiple scattering (i.e. when scatterers are close to each other). This is due to error in determining the number of scatterers. The present paper provides a new approach to alleviate such a problem using an information theoretic criterion referred as minimum description length (MDL). The merits of the novel approach are confirmed by the numerical examples. The results indicate the time-reversal MUSIC yields accurate estimate of the target locations with considerable noise and multiple scattering in the received signals.

Keywords: Microwave imaging, Time reversal, MUSIC algorithm, Minimum Description Length (MDL).

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Authors: V. T. S. Dao, T. G. Etoh, C. Vo Le, H. D. Nguyen, K. Takehara, T. Akino, K. Nishi

Abstract:

Since 2004, we have been developing an in-situ storage image sensor (ISIS) that captures more than 100 consecutive images at a frame rate of 10 Mfps with ultra-high sensitivity as well as the video camera for use with this ISIS. Currently, basic research is continuing in an attempt to increase the frame rate up to 100 Mfps and above. In order to suppress electro-magnetic noise at such high frequency, a digital-noiseless imaging transfer scheme has been developed utilizing solely sinusoidal driving voltages. This paper presents highly efficient-yet-accurate expressions to estimate attenuation as well as phase delay of driving voltages through RC networks of an ultra-high-speed image sensor. Elmore metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE data, we found a simple expression that significantly improves the accuracy of the approximation. Similarly, another simple closed-form model to estimate phase delay through fundamental RC networks is also obtained. Estimation error of both expressions is much less than previous works, only less 2% for most of the cases . The framework of this analysis can be extended to address similar issues of other VLSI structures.

Keywords: Dimensional Analysis, ISIS, Digital-noiseless, RC network, Attenuation, Phase Delay, Elmore model

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Authors: Paitoon Kraipornsak

Abstract:

The recent global financial problem urges government to play role in stimulating the economy due to the fact that private sector has little ability to purchase during the recession. A concerned question is whether the increased government spending crowds out private consumption and whether it helps stimulate the economy. If the government spending policy is effective; the private consumption is expected to increase and can compensate the recent extra government expense. In this study, the government spending is categorized into government consumption spending and government capital spending. The study firstly examines consumer consumption along the line with the demand function in microeconomic theory. Three categories of private consumption are used in the study. Those are food consumption, non food consumption, and services consumption. The dynamic Almost Ideal Demand System of the three categories of the private consumption is estimated using the Vector Error Correction Mechanism model. The estimated model indicates the substituting effects (negative impacts) of the government consumption spending on budget shares of private non food consumption and of the government capital spending on budget share of private food consumption, respectively. Nevertheless the result does not necessarily indicate whether the negative effects of changes in the budget shares of the non food and the food consumption means fallen total private consumption. Microeconomic consumer demand analysis clearly indicates changes in component structure of aggregate expenditure in the economy as a result of the government spending policy. The macroeconomic concept of aggregate demand comprising consumption, investment, government spending (the government consumption spending and the government capital spending), export, and import are used to estimate for their relationship using the Vector Error Correction Mechanism model. The macroeconomic study found no effect of the government capital spending on either the private consumption or the growth of GDP while the government consumption spending has negative effect on the growth of GDP. Therefore no crowding out effect of the government spending is found on the private consumption but it is ineffective and even inefficient expenditure as found reducing growth of the GDP in the context of Thailand.

Keywords: government consumption spending, governmentcapital spending, private consumption on food, non food, andservices, Vector Error Correction Mechanism, Almost Ideal DemandSystem, substitution effect, complementary effect, consumer demand, aggregate demand

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Authors: Chisato Murakami, Makoto Takahashi

Abstract:

Force sensor has been used as requisite for knowing information on the amount and the directions of forces on the skin surface. We have developed a four-degrees-of-freedom capacitive force sensor (approximately 20×20×5 mm³) that has a flexible structure and sixteen parallel plate capacitors. An iterative algorithm was developed for estimating four displacements from the sixteen capacitances using fourth-order polynomial approximation of characteristics between capacitance and displacement. The estimation results from measured capacitances had large error caused by deterioration of the characteristics. In this study, effective capacitors had major information were selected on the basis of the capacitance change range and the characteristic shape. Maximum errors in calibration and non-calibration points were 25%and 6.8%.However the maximum error was larger than desired value, the smallness of averaged value indicated the occurrence of a few large error points. On the other hand, error in non-calibration point was within desired value.

 

Keywords: Force sensors, capacitive sensors, estimation, iterative algorithms.

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Authors: Tung-Hui Hsu, Wen-Yuh Jywe

Abstract:

Five-axis computer numerical control (CNC) machine tools (three linear and two rotary axes) are ideally suited to the fabrication of complex work pieces, such as dies, turbo blades, and cams. The locations of the axis average line and centerline of the rotary axes strongly influence the performance of these machines; however, techniques to compensate for eccentric error in the rotary axes remain weak. This paper proposes optical (Non-Bar) techniques capable of calibrating five-axis CNC machine tools and compensating for eccentric error in the rotary axes. This approach employs the measurement path in ISO/CD 10791-6 to determine the eccentric error in two rotary axes, for which compensatory measures can be implemented. Experimental results demonstrate that the proposed techniques can improve the performance of various five-axis CNC machine tools by more than 90%. Finally, a result of the cutting test using a B-type five-axis CNC machine tool confirmed to the usefulness of this proposed compensation technique.

Keywords: Calibration, compensation, rotary axis, five-axis computer numerical control (CNC) machine tools, eccentric error, optical calibration system, ISO/CD 10791-6

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Authors: Ayad A. Abdulkafi, Shahir F. Nawaf, Mohammed K. Hussein, Ibrahim K. Sileh, Fouad A. Abdulkafi

Abstract:

Visible light communication (VLC) is a new approach of optical wireless communication proposed to support the congested radio frequency (RF) spectrum. VLC systems are combined with orthogonal frequency division multiplexing (OFDM) to achieve high rate transmission and high spectral efficiency. In this paper, we investigate the Pilot-Assisted Channel Estimation for DC biased Optical OFDM (PACE-DCO-OFDM) systems to reduce the effects of the distortion on the transmitted signal. Least-square (LS) and linear minimum mean-squared error (LMMSE) estimators are implemented in MATLAB/Simulink to enhance the bit-error-rate (BER) of PACE-DCO-OFDM. Results show that DCO-OFDM system based on PACE scheme has achieved better BER performance compared to conventional system without pilot assisted channel estimation. Simulation results show that the proposed PACE-DCO-OFDM based on LMMSE algorithm can more accurately estimate the channel and achieves better BER performance when compared to the LS based PACE-DCO-OFDM and the traditional system without PACE. For the same signal to noise ratio (SNR) of 25 dB, the achieved BER is about 5×10^-4 for LMMSE-PACE and 4.2×10^-3 with LS-PACE while it is about 2×10^-1 for system without PACE scheme.

Keywords: Channel estimation, OFDM, pilot-assist, VLC.

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Authors: V. Amosov, Yu. Kashchuk, A. Krasilnikov, A. Kostin, A. Khovanskiy, A. Leonov, N. Rodionov, R. Rodionov

Abstract:

In present work the problem of the ITER fusion plasma neutron source parameter reconstruction using only the Vertical Neutron Camera data was solved. The possibility of neutron source parameter reconstruction was estimated by the numerical simulations and the analysis of adequateness of mathematic model was performed. The neutron source was specified in a parametric form. The numerical analysis of solution stability with respect to data distortion was done. The influence of the data errors on the reconstructed parameters is shown: • is reconstructed with errors less than 4% at all examined values of δ (until 60%); • is determined with errors less than 10% when δ do not overcome 5%; • is reconstructed with relative error more than 10 %; • integral intensity of the neutron source is determined with error 10% while δ error is less than 15%; where -error of signal measurements, (R0,Z0), the plasma center position,- /parameter of neutron source profile.

Keywords: ITER, neutronsource, neutron source profile reconstruction, Vertical Neutron Camera.

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Authors: H. M. Behairy, M. S. Khorsheed

Abstract:

Among other factors that characterize satellite communication channels is their high bit error rate. We present a system for still image transmission over noisy satellite channels. The system couples image compression together with error control codes to improve the received image quality while maintaining its bandwidth requirements. The proposed system is tested using a high resolution satellite imagery simulated over the Rician fading channel. Evaluation results show improvement in overall system including image quality and bandwidth requirements compared to similar systems with different coding schemes.

Keywords: Image Transmission, Image Compression, Channel Coding, Error-Control Coding, DCT, Convolution Codes, Viterbi Algorithm, PCGC.

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Authors: Soo-young Ye, Gi-Ryon Kim, Dong-Keun Jung, Seong-wan Baik, Gye-rok Jeon

Abstract:

In this paper, algorithm estimating the blood pressure was proposed using the pulse transit time (PTT) as a more convenient method of measuring the blood pressure. After measuring ECG and pressure pulse, and photoplethysmography, the PTT was calculated from the acquired signals. Thereafter, the system to indirectly measure the systolic pressure and the diastolic pressure was composed using the statistic method. In comparison between the blood pressure indirectly measured by proposed algorithm estimating the blood pressure and real blood pressure measured by conventional sphygmomanometer, the systolic pressure indicates the mean error of ±3.24mmHg and the standard deviation of 2.53mmHg, while the diastolic pressure indicates the satisfactory result, that is, the mean error of ±1.80mmHg and the standard deviation of 1.39mmHg. These results are satisfied with the regulation of ANSI/AAMI for certification of sphygmomanometer that real measurement error value should be within the mean error of ±5mmHg and the standard deviation of 8mmHg. These results are suggest the possibility of applying to portable and long time blood pressure monitoring system hereafter.

Keywords: Blood pressure, Systolic, Diastolic, Pulse transit time.

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Authors: Ali Asadian, Behzad Moshiri, Ali Khaki Sedigh, Caro Lucas

Abstract:

Most integrated inertial navigation systems (INS) and global positioning systems (GPS) have been implemented using the Kalman filtering technique with its drawbacks related to the need for predefined INS error model and observability of at least four satellites. Most recently, a method using a hybrid-adaptive network based fuzzy inference system (ANFIS) has been proposed which is trained during the availability of GPS signal to map the error between the GPS and the INS. Then it will be used to predict the error of the INS position components during GPS signal blockage. This paper introduces a genetic optimization algorithm that is used to update the ANFIS parameters with respect to the INS/GPS error function used as the objective function to be minimized. The results demonstrate the advantages of the genetically optimized ANFIS for INS/GPS integration in comparison with conventional ANFIS specially in the cases of satellites- outages. Coping with this problem plays an important role in assessment of the fusion approach in land navigation.

Keywords: Adaptive Network based Fuzzy Inference System (ANFIS), Genetic optimization, Global Positioning System (GPS), Inertial Navigation System (INS).

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Authors: Hadj Bourdoucen, Amer Alhabsi

Abstract:

In this paper, a post processing scheme is suggested for improvement of Bit Error-Rate (BER) in optical fiber transmission receivers. The developed scheme has been tested on optical fiber systems operating with a non-return-to-zero (NRZ) format at transmission rates of up to 10Gbps. The transmission system considered is based on well known transmitters and receivers blocks operating at wavelengths in the region of 1550 nm using a standard single mode fiber. Performance of improved detected signals has been evaluated via the analysis of quality factor and computed bit error rates. Numerical simulations have shown a noticeable improvement of the system BER after implementation of the suggested post processing operation on the detected electrical signals.

Keywords: BER improvement, Optical fiber, transmissionperformance, NRZ.

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Authors: Kibaek Kim, Dongjin Jung, Jinik Jang, Jechang Jeong

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In this paper, we proposed a method to reduce quantization error. In order to reduce quantization error, low pass filtering is applied on neighboring samples of current block in H.264/AVC. However, it has a weak point that low pass filtering is performed regardless of prediction direction. Since it doesn-t consider prediction direction, it may not reduce quantization error effectively. Proposed method considers prediction direction for low pass filtering and uses a threshold condition for reducing flag bit. We compare our experimental result with conventional method in H.264/AVC and we can achieve the average bit-rate reduction of 1.534% by applying the proposed method. Bit-rate reduction between 0.580% and 3.567% are shown for experimental results.

Keywords: Coding efficiency, H.264/AVC, Intra prediction, Low pass filter

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Authors: Venus Marza, Amin Seyyedi, Luiz Fernando Capretz

Abstract:

Software estimation accuracy is among the greatest challenges for software developers. This study aimed at building and evaluating a neuro-fuzzy model to estimate software projects development time. The forty-one modules developed from ten programs were used as dataset. Our proposed approach is compared with fuzzy logic and neural network model and Results show that the value of MMRE (Mean of Magnitude of Relative Error) applying neuro-fuzzy was substantially lower than MMRE applying fuzzy logic and neural network.

Keywords: Artificial Neural Network, Fuzzy Logic, Neuro-Fuzzy, Software Estimation

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Authors: Sambit Prasad Kar, P.Palanisamy

Abstract:

In this paper a novel method for multiple one dimensional real valued sinusoidal signal frequency estimation in the presence of additive Gaussian noise is postulated. A computationally simple frequency estimation method with efficient statistical performance is attractive in many array signal processing applications. The prime focus of this paper is to combine the subspace-based technique and a simple peak search approach. This paper presents a variant of the Propagator Method (PM), where a collaborative approach of SUMWE and Propagator method is applied in order to estimate the multiple real valued sine wave frequencies. A new data model is proposed, which gives the dimension of the signal subspace is equal to the number of frequencies present in the observation. But, the signal subspace dimension is twice the number of frequencies in the conventional MUSIC method for estimating frequencies of real-valued sinusoidal signal. The statistical analysis of the proposed method is studied, and the explicit expression of asymptotic (large-sample) mean-squared-error (MSE) or variance of the estimation error is derived. The performance of the method is demonstrated, and the theoretical analysis is substantiated through numerical examples. The proposed method can achieve sustainable high estimation accuracy and frequency resolution at a lower SNR, which is verified by simulation by comparing with conventional MUSIC, ESPRIT and Propagator Method.

Keywords: Frequency estimation, peak search, subspace-based method without eigen decomposition, quadratic convex function.

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Authors: Isti Surjandari, Riara Novita

Abstract:

Maintenance is one of the most important activities in the shipyard industry. However, sometimes it is not supported by adequate services from the shipyard, where inaccuracy in estimating the duration of the ship maintenance is still common. This makes estimation of ship maintenance duration is crucial. This study uses Data Mining approach, i.e., CART (Classification and Regression Tree) to estimate the duration of ship maintenance that is limited to dock works or which is known as dry docking. By using the volume of dock works as an input to estimate the maintenance duration, 4 classes of dry docking duration were obtained with different linear model and job criteria for each class. These linear models can then be used to estimate the duration of dry docking based on job criteria.

Keywords: Classification and regression tree (CART), data mining, dry docking, maintenance duration.

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Authors: Sanja Seljan, Ivan Dunđer

Abstract:

The paper presents combined automatic speech recognition (ASR) of English and machine translation (MT) for English and Croatian and Croatian-English language pairs in the domain of business correspondence. The first part presents results of training the ASR commercial system on English data sets, enriched by error analysis. The second part presents results of machine translation performed by free online tool for English and Croatian and Croatian-English language pairs. Human evaluation in terms of usability is conducted and internal consistency calculated by Cronbach's alpha coefficient, enriched by error analysis. Automatic evaluation is performed by WER (Word Error Rate) and PER (Position-independent word Error Rate) metrics, followed by investigation of Pearson’s correlation with human evaluation.

Keywords: Automatic machine translation, integrated language technologies, quality evaluation, speech recognition.

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Authors: Nazif Çalış, Murat Erişoğlu, Hamza Erol, Tayfun Servi

Abstract:

In the recent works related with mixture discriminant analysis (MDA), expectation and maximization (EM) algorithm is used to estimate parameters of Gaussian mixtures. But, initial values of EM algorithm affect the final parameters- estimates. Also, when EM algorithm is applied two times, for the same data set, it can be give different results for the estimate of parameters and this affect the classification accuracy of MDA. Forthcoming this problem, we use Self Organizing Mixture Network (SOMN) algorithm to estimate parameters of Gaussians mixtures in MDA that SOMN is more robust when random the initial values of the parameters are used [5]. We show effectiveness of this method on popular simulated waveform datasets and real glass data set.

Keywords: Self Organizing Mixture Network, MixtureDiscriminant Analysis, Waveform Datasets, Glass Identification, Mixture of Multivariate Normal Distributions

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Authors: Oscar Javier Herrera, Manuel Ángel Camacho

Abstract:

This paper addresses a cutting edge method of business demand forecasting, based on an empirical probability function when the historical behavior of the data is random. Additionally, it presents error determination based on the numerical method technique ‘propagation of errors.’ The methodology was conducted characterization and process diagnostics demand planning as part of the production management, then new ways to predict its value through techniques of probability and to calculate their mistake investigated, it was tools used numerical methods. All this based on the behavior of the data. This analysis was determined considering the specific business circumstances of a company in the sector of communications, located in the city of Bogota, Colombia. In conclusion, using this application it was possible to obtain the adequate stock of the products required by the company to provide its services, helping the company reduce its service time, increase the client satisfaction rate, reduce stock which has not been in rotation for a long time, code its inventory, and plan reorder points for the replenishment of stock.

Keywords: Demand Forecasting, Empirical Distribution, Propagation of Error.

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Authors: Susmita Sahoo, Madhumanti Datta, Rajib Kar

Abstract:

Fast delay estimation methods, as opposed to simulation techniques, are needed for incremental performance driven layout synthesis. On-chip inductive effects are becoming predominant in deep submicron interconnects due to increasing clock speed and circuit complexity. Inductance causes noise in signal waveforms, which can adversely affect the performance of the circuit and signal integrity. Several approaches have been put forward which consider the inductance for on-chip interconnect modelling. But for even much higher frequency, of the order of few GHz, the shunt dielectric lossy component has become comparable to that of other electrical parameters for high speed VLSI design. In order to cope up with this effect, on-chip interconnect has to be modelled as distributed RLCG line. Elmore delay based methods, although efficient, cannot accurately estimate the delay for RLCG interconnect line. In this paper, an accurate analytical delay model has been derived, based on first and second moments of RLCG interconnection lines. The proposed model considers both the effect of inductance and conductance matrices. We have performed the simulation in 0.18μm technology node and an error of as low as less as 5% has been achieved with the proposed model when compared to SPICE. The importance of the conductance matrices in interconnect modelling has also been discussed and it is shown that if G is neglected for interconnect line modelling, then it will result an delay error of as high as 6% when compared to SPICE.

Keywords: Delay Modelling; On-Chip Interconnect; RLCGInterconnect; Ramp Input; Damping; VLSI

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Authors: Shrawan Kumar, D. K. Lobiyal

Abstract:

In this paper, we propose improved versions of DVHop algorithm as QDV-Hop algorithm and UDV-Hop algorithm for better localization without the need for additional range measurement hardware. The proposed algorithm focuses on third step of DV-Hop, first error terms from estimated distances between unknown node and anchor nodes is separated and then minimized. In the QDV-Hop algorithm, quadratic programming is used to minimize the error to obtain better localization. However, quadratic programming requires a special optimization tool box that increases computational complexity. On the other hand, UDV-Hop algorithm achieves localization accuracy similar to that of QDV-Hop by solving unconstrained optimization problem that results in solving a system of linear equations without much increase in computational complexity. Simulation results show that the performance of our proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop and DV-Hop based algorithms in all considered scenarios.

Keywords: Wireless sensor networks, Error term, DV-Hop algorithm, Localization.

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Authors: M. Sedighizadeh, A. Rezazadeh

Abstract:

A self tuning PID control strategy using reinforcement learning is proposed in this paper to deal with the control of wind energy conversion systems (WECS). Actor-Critic learning is used to tune PID parameters in an adaptive way by taking advantage of the model-free and on-line learning properties of reinforcement learning effectively. In order to reduce the demand of storage space and to improve the learning efficiency, a single RBF neural network is used to approximate the policy function of Actor and the value function of Critic simultaneously. The inputs of RBF network are the system error, as well as the first and the second-order differences of error. The Actor can realize the mapping from the system state to PID parameters, while the Critic evaluates the outputs of the Actor and produces TD error. Based on TD error performance index and gradient descent method, the updating rules of RBF kernel function and network weights were given. Simulation results show that the proposed controller is efficient for WECS and it is perfectly adaptable and strongly robust, which is better than that of a conventional PID controller.

Keywords: Wind energy conversion systems, reinforcementlearning; Actor-Critic learning; adaptive PID control; RBF network.

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Authors: Dimitrios J. Dimitriou

Abstract:

It is widely recognised that the assets portfolio development is helping to enhance economic growth, productivity and competitiveness. While numerous studies and reports certify the positive effect of investments in large infrastructure investments on the local economy, still, the methodology to estimate the contribution in economic development is a challenging issue for researchers and economists. The key question is how to estimate those economic impacts in each economic system. This paper provides a compact and applicable methodological framework providing quantitative results in terms of the overall jobs and income generated into the project life cycle. According to a deterministic mathematical approach, the key variables and the modelling framework are presented. The numerical case study highlights key results for a new motorway project in Greece, which is experienced economic stress for many years, providing the opportunity for comparisons with similar cases.

Keywords: Quantitative modelling, economic impact; large transport infrastructure; economic assessment.

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Authors: Orose Rugchati, Kanita Thanacharoenchanaphas

Abstract:

This research studied the simulation of increased ambient ozone to estimate nutrient content and genetic changes in two Thai soybean cultivars (Chiang Mai 60 and Srisumrong 1). Ozone stress conditions affected proteins and lipids. It was found that proteins decreased, but lipids increased. Srisumrong 1 cultivars were more sensitive to ozone stress than Chiang Mai 60 cultivars. The effect of ozone stress conditions on plant phenotype and genotype was analyzed using the AFLP technique for the 2 Thai soybean cultivars (Chiang Mai 60 and Srisumrong 1).

Keywords: simulation, ambient ozone estimate, nutrient content, genetic changes , Thai soybean

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Authors: Nedeljko Cvejic, Artur Łoza, David Bull, Nishan Canagarajah

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In this paper, we present a novel objective nonreference performance assessment algorithm for image fusion. It takes into account local measurements to estimate how well the important information in the source images is represented by the fused image. The metric is based on the Universal Image Quality Index and uses the similarity between blocks of pixels in the input images and the fused image as the weighting factors for the metrics. Experimental results confirm that the values of the proposed metrics correlate well with the subjective quality of the fused images, giving a significant improvement over standard measures based on mean squared error and mutual information.

Keywords: Fusion performance measures, image fusion, non-reference quality measures, objective quality measures.

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Authors: Ching-Tsan Chiang, Sheng-Jie Yang, Jing-Kai Huang

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The purpose of this research is to develop and apply the RSCMAC to enhance the dynamic accuracy of Global Positioning System (GPS). GPS devices provide services of accurate positioning, speed detection and highly precise time standard for over 98% area on the earth. The overall operation of Global Positioning System includes 24 GPS satellites in space; signal transmission that includes 2 frequency carrier waves (Link 1 and Link 2) and 2 sets random telegraphic codes (C/A code and P code), on-earth monitoring stations or client GPS receivers. Only 4 satellites utilization, the client position and its elevation can be detected rapidly. The more receivable satellites, the more accurate position can be decoded. Currently, the standard positioning accuracy of the simplified GPS receiver is greatly increased, but due to affected by the error of satellite clock, the troposphere delay and the ionosphere delay, current measurement accuracy is in the level of 5~15m. In increasing the dynamic GPS positioning accuracy, most researchers mainly use inertial navigation system (INS) and installation of other sensors or maps for the assistance. This research utilizes the RSCMAC advantages of fast learning, learning convergence assurance, solving capability of time-related dynamic system problems with the static positioning calibration structure to improve and increase the GPS dynamic accuracy. The increasing of GPS dynamic positioning accuracy can be achieved by using RSCMAC system with GPS receivers collecting dynamic error data for the error prediction and follows by using the predicted error to correct the GPS dynamic positioning data. The ultimate purpose of this research is to improve the dynamic positioning error of cheap GPS receivers and the economic benefits will be enhanced while the accuracy is increased.

Keywords: Dynamic Error, GPS, Prediction, RSCMAC.

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Authors: O. P. Sharma, V. Janyani, S. Sancheti

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Inter-symbol interference if not taken care off may cause severe error at the receiver and the detection of signal becomes difficult. An adaptive equalizer employing Recursive Least Squares algorithm can be a good compensation for the ISI problem. In this paper performance of communication link in presence of Least Mean Square and Recursive Least Squares equalizer algorithm is analyzed. A Model of communication system having Quadrature amplitude modulation and Rician fading channel is implemented using MATLAB communication block set. Bit error rate and number of errors is evaluated for RLS and LMS equalizer algorithm, due to change in Signal to Noise Ratio (SNR) and fading component gain in Rician fading Channel.

Keywords: Least mean square (LMS), Recursive least squares(RLS), Adaptive equalization, Bit error rate (BER), Rician fading channel, Quadrature Amplitude Modulation (QAM), Signal to noiseratio (SNR).

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Authors: M. Kalamani, S. Valarmathy, M. Krishnamoorthi

Abstract:

In this paper, Fuzzy C-Means clustering with Expectation Maximization-Gaussian Mixture Model based hybrid modeling algorithm is proposed for Continuous Tamil Speech Recognition. The speech sentences from various speakers are used for training and testing phase and objective measures are between the proposed and existing Continuous Speech Recognition algorithms. From the simulated results, it is observed that the proposed algorithm improves the recognition accuracy and F-measure up to 3% as compared to that of the existing algorithms for the speech signal from various speakers. In addition, it reduces the Word Error Rate, Error Rate and Error up to 4% as compared to that of the existing algorithms. In all aspects, the proposed hybrid modeling for Tamil speech recognition provides the significant improvements for speechto- text conversion in various applications.

Keywords: Speech Segmentation, Feature Extraction, Clustering, HMM, EM-GMM, CSR.

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