Search results for: Spectral Noise and short channeleffect (SCE).
1538 FT-NIR Method to Determine Moisture in Gluten Free Rice Based Pasta during Drying
Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra
Abstract:
Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.
Keywords: FT-NIR, Pasta, moisture determination.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28111537 Design of Multiplier-free State-Space Digital Filters
Authors: Tamal Bose, Zhurun Zhang, Miloje Radenkovic, Ojas Chauhan
Abstract:
In this paper, a novel approach is presented for designing multiplier-free state-space digital filters. The multiplier-free design is obtained by finding power-of-2 coefficients and also quantizing the state variables to power-of-2 numbers. Expressions for the noise variance are derived for the quantized state vector and the output of the filter. A “structuretransformation matrix" is incorporated in these expressions. It is shown that quantization effects can be minimized by properly designing the structure-transformation matrix. Simulation results are very promising and illustrate the design algorithm.Keywords: Digital filters, minimum noise, multiplier-free, quantization, state-space.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15241536 Synchronization Technique for Random Switching Frequency Pulse-Width Modulation
Authors: Apinan Aurasopon, Worawat Sa-ngiavibool
Abstract:
This paper proposes a synchronized random switching frequency pulse width modulation (SRSFPWM). In this technique, the clock signal is used to control the random noise frequency which is produced by the feedback voltage of a hysteresis circuit. These make the triangular carrier frequency equaling to the random noise frequency in each switching period with the symmetrical positive and negative slopes of triangular carrier. Therefore, there is no error voltage in PWM signal. The PSpice simulated results shown the proposed technique improved the performance in case of low frequency harmonics of PWM signal comparing with conventional random switching frequency PWM.
Keywords: Random switching frequency pulse - width modulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27841535 An Estimation of the Performance of HRLS Algorithm
Authors: Shazia Javed, Noor Atinah Ahmad
Abstract:
The householder RLS (HRLS) algorithm is an O(N2) algorithm which recursively updates an arbitrary square-root of the input data correlation matrix and naturally provides the LS weight vector. A data dependent householder matrix is applied for such an update. In this paper a recursive estimate of the eigenvalue spread and misalignment of the algorithm is presented at a very low computational cost. Misalignment is found to be highly sensitive to the eigenvalue spread of input signals, output noise of the system and exponential window. Simulation results show noticeable degradation in the misalignment by increase in eigenvalue spread as well as system-s output noise, while exponential window was kept constant.Keywords: HRLS algorithm, eigenvalue spread, misalignment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15651534 The Design and Implementation of Classifying Bird Sounds
Authors: Haiyi Zhang, Jianli Guo, Daqian Yang
Abstract:
This Classifying Bird Sounds (chip notes) project-s purpose is to reduce the unwanted noise from recorded bird sound chip notes, design a scheme to detect differences and similarities between recorded chip notes, and classify bird sound chip notes. The technologies of determining the similarities of sound waves have been used in communication, sound engineering and wireless sound applications for many years. Our research is focused on the similarity of chip notes, which are the sounds from different birds. The program we use is generated by Microsoft Cµ.Keywords: Classify Bird Sounds, Noise Filter, High-pass, Lowpass, Band-pass, Band-stop Filter, FIR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12381533 Real Time Acquisition and Psychoacoustic Analysis of Brain Wave
Authors: Shweta Singh, Dipali Bansal, Rashima Mahajan
Abstract:
Psychoacoustics has become a potential area of research due to the growing interest of both laypersons and medical and mental health professionals. Non invasive brain computer interface like Electroencephalography (EEG) is widely being used in this field. An attempt has been made in this paper to examine the response of EEG signals to acoustic stimuli further analyzing the brain electrical activity. The real time EEG is acquired for 6 participants using a cost effective and portable EMOTIV EEG neuro headset. EEG data analysis is further done using EMOTIV test bench, EDF browser and EEGLAB (MATLAB Tool) application software platforms. Spectral analysis of acquired neural signals (AF3 channel) using these software platforms are clearly indicative of increased brain activity in various bands. The inferences drawn from such an analysis have significant correlation with subject’s subjective reporting of the experiences. The results suggest that the methodology adopted can further be used to assist patients with sleeping and depressive disorders.
Keywords: OM’ chant, Spectral analysis, EDF Browser, EEGLAB, EMOTIV, Real time Acquisition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35631532 A Robust and Adaptive Unscented Kalman Filter for the Air Fine Alignment of the Strapdown Inertial Navigation System/GPS
Authors: Jian Shi, Baoguo Yu, Haonan Jia, Meng Liu, Ping Huang
Abstract:
Adapting to the flexibility of war, a large number of guided weapons launch from aircraft. Therefore, the inertial navigation system loaded in the weapon needs to undergo an alignment process in the air. This article proposes the following methods to the problem of inaccurate modeling of the system under large misalignment angles, the accuracy reduction of filtering caused by outliers, and the noise changes in GPS signals: first, considering the large misalignment errors of Strapdown Inertial Navigation System (SINS)/GPS, a more accurate model is made rather than to make a small-angle approximation, and the Unscented Kalman Filter (UKF) algorithms are used to estimate the state; then, taking into account the impact of GPS noise changes on the fine alignment algorithm, the innovation adaptive filtering algorithm is introduced to estimate the GPS’s noise in real-time; at the same time, in order to improve the anti-interference ability of the air fine alignment algorithm, a robust filtering algorithm based on outlier detection is combined with the air fine alignment algorithm to improve the robustness of the algorithm. The algorithm can improve the alignment accuracy and robustness under interference conditions, which is verified by simulation.
Keywords: Air alignment, fine alignment, inertial navigation system, integrated navigation system, UKF.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5231531 A Finite Precision Block Floating Point Treatment to Direct Form, Cascaded and Parallel FIR Digital Filters
Authors: Abhijit Mitra
Abstract:
This paper proposes an efficient finite precision block floating point (BFP) treatment to the fixed coefficient finite impulse response (FIR) digital filter. The treatment includes effective implementation of all the three forms of the conventional FIR filters, namely, direct form, cascaded and par- allel, and a roundoff error analysis of them in the BFP format. An effective block formatting algorithm together with an adaptive scaling factor is pro- posed to make the realizations more simple from hardware view point. To this end, a generic relation between the tap weight vector length and the input block length is deduced. The implementation scheme also emphasises on a simple block exponent update technique to prevent overflow even during the block to block transition phase. The roundoff noise is also investigated along the analogous lines, taking into consideration these implementational issues. The simulation results show that the BFP roundoff errors depend on the sig- nal level almost in the same way as floating point roundoff noise, resulting in approximately constant signal to noise ratio over a relatively large dynamic range.
Keywords: Finite impulse response digital filters, Cascade structure, Parallel structure, Block floating point arithmetic, Roundoff error.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16371530 Statistical Evaluation of Nonlinear Distortion using the Multi-Canonical Monte Carlo Method and the Split Step Fourier Method
Authors: Ioannis Neokosmidis, Nikos Gkekas, Thomas Kamalakis, Thomas Sphicopoulos
Abstract:
In high powered dense wavelength division multiplexed (WDM) systems with low chromatic dispersion, four-wave mixing (FWM) can prove to be a major source of noise. The MultiCanonical Monte Carlo Method (MCMC) and the Split Step Fourier Method (SSFM) are combined to accurately evaluate the probability density function of the decision variable of a receiver, limited by FWM. The combination of the two methods leads to more accurate results, and offers the possibility of adding other optical noises such as the Amplified Spontaneous Emission (ASE) noise.Keywords: Monte Carlo, Nonlinear optics, optical crosstalk, Wavelength-division Multiplexing (WDM).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16811529 Performance Comparison and Evaluation of AdaBoost and SoftBoost Algorithms on Generic Object Recognition
Authors: Doaa Hegazy, Joachim Denzler
Abstract:
SoftBoost is a recently presented boosting algorithm, which trades off the size of achieved classification margin and generalization performance. This paper presents a performance evaluation of SoftBoost algorithm on the generic object recognition problem. An appearance-based generic object recognition model is used. The evaluation experiments are performed using a difficult object recognition benchmark. An assessment with respect to different degrees of label noise as well as a comparison to the well known AdaBoost algorithm is performed. The obtained results reveal that SoftBoost is encouraged to be used in cases when the training data is known to have a high degree of noise. Otherwise, using Adaboost can achieve better performance.Keywords: SoftBoost algorithm, AdaBoost algorithm, Generic object recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18191528 Dielectric Recovery Characteristics of High Voltage Gas Circuit Breakers Operating with CO2 Mixture
Authors: Peng Lu, Branimir Radisavljevic, Martin Seeger, Daniel Over, Torsten Votteler, Bernardo Galletti
Abstract:
CO₂-based gas mixtures exhibit huge potential as the interruption medium for replacing SF₆ in high voltage switchgears. In this paper, the recovery characteristics of dielectric strength of CO₂-O₂ mixture in the post arc phase after the current zero are presented. As representative examples, the dielectric recovery curves under conditions of different gas filling pressures and short-circuit current amplitudes are presented. A series of dielectric recovery measurements suggests that the dielectric recovery rate is proportional to the mass flux of the blowing gas, and the dielectric strength recovers faster in the case of lower short circuit currents.
Keywords: CO2 mixture, high voltage circuit breakers, dielectric recovery rate, short-circuit current, mass flux.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4371527 Ensemble Learning with Decision Tree for Remote Sensing Classification
Authors: Mahesh Pal
Abstract:
In recent years, a number of works proposing the combination of multiple classifiers to produce a single classification have been reported in remote sensing literature. The resulting classifier, referred to as an ensemble classifier, is generally found to be more accurate than any of the individual classifiers making up the ensemble. As accuracy is the primary concern, much of the research in the field of land cover classification is focused on improving classification accuracy. This study compares the performance of four ensemble approaches (boosting, bagging, DECORATE and random subspace) with a univariate decision tree as base classifier. Two training datasets, one without ant noise and other with 20 percent noise was used to judge the performance of different ensemble approaches. Results with noise free data set suggest an improvement of about 4% in classification accuracy with all ensemble approaches in comparison to the results provided by univariate decision tree classifier. Highest classification accuracy of 87.43% was achieved by boosted decision tree. A comparison of results with noisy data set suggests that bagging, DECORATE and random subspace approaches works well with this data whereas the performance of boosted decision tree degrades and a classification accuracy of 79.7% is achieved which is even lower than that is achieved (i.e. 80.02%) by using unboosted decision tree classifier.Keywords: Ensemble learning, decision tree, remote sensingclassification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25721526 Effects of Thermal Radiation on Mixed Convection in a MHD Nanofluid Flow over a Stretching Sheet Using a Spectral Relaxation Method
Authors: Nageeb A. H. Haroun, Sabyasachi Mondal, Precious Sibanda
Abstract:
The effects of thermal radiation, Soret and Dufour parameters on mixed convection and nanofluid flow over a stretching sheet in the presence of a magnetic field are investigated. The flow is subject to temperature dependent viscosity and a chemical reaction parameter. It is assumed that the nanoparticle volume fraction at the wall may be actively controlled. The physical problem is modelled using systems of nonlinear differential equations which have been solved numerically using a spectral relaxation method. In addition to the discussion on heat and mass transfer processes, the velocity, nanoparticles volume fraction profiles as well as the skin friction coefficient are determined for different important physical parameters. A comparison of current findings with previously published results for some special cases of the problem shows an excellent agreement.Keywords: Non-isothermal wedge, thermal radiation, nanofluid, magnetic field, Soret and Dufour effects.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12621525 Image Enhancement Algorithm of Photoacoustic Tomography Using Active Contour Filtering
Authors: Prasannakumar Palaniappan, Dong Ho Shin, Chul Gyu Song
Abstract:
The photoacoustic images are obtained from a custom developed linear array photoacoustic tomography system. The biological specimens are imitated by conducting phantom tests in order to retrieve a fully functional photoacoustic image. The acquired image undergoes the active region based contour filtering to remove the noise and accurately segment the object area for further processing. The universal back projection method is used as the image reconstruction algorithm. The active contour filtering is analyzed by evaluating the signal to noise ratio and comparing it with the other filtering methods.
Keywords: Contour filtering, linear array, photoacoustic tomography, universal back projection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18311524 Effect of Different BER Performance Comparison of MAP and ML Detection
Authors: Naveed Ur Rehman, Rehan Jamil, Irfan Jamil
Abstract:
In this paper, we regard as a coded transmission over a frequency-selective channel. We plan to study analytically the convergence of the turbo-detector using a maximum a posteriori (MAP) equalizer and a MAP decoder. We demonstrate that the densities of the maximum likelihood (ML) exchanged during the iterations are e-symmetric and output-symmetric. Under the Gaussian approximation, this property allows to execute a one-dimensional scrutiny of the turbo-detector. By deriving the analytical terminology of the ML distributions under the Gaussian approximation, we confirm that the bit error rate (BER) performance of the turbo-detector converges to the BER performance of the coded additive white Gaussian noise (AWGN) channel at high signal to noise ratio (SNR), for any frequency selective channel.
Keywords: MAP, ML, SNR, Decoder, BER, Coded transmission.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22471523 Investigations of Flow Field with Different Turbulence Models on NREL Phase VI Blade
Authors: T. Y. Liu, C. H Lin., Y. M Ferng
Abstract:
Wind energy is one of the clean renewable energy. However, the low frequency (20-200HZ) noise generated from the wind turbine blades, which bothers the residents, becomes the major problem to be developed. It is useful for predicting the aerodynamic noise by flow field and pressure distribution analysis on the wind turbine blades. Therefore, the main objective of this study is to use different turbulence models to analyze the flow field and pressure distributions of the wing blades.
Three-dimensional Computation Fluid Dynamics (CFD) simulation of the flow field was used to calculate the flow phenomena for the National Renewable Energy Laboratory (NREL) Phase VI horizontal axis wind turbine rotor. Two different flow cases with different wind speeds were investigated: 7m/s with 72rpm and 15m/s with 72rpm.
Four kinds of RANS-based turbulence models, Standard k-ε, Realizable k-ε, SST k-ω, and v2f, were used to predict and analyze the results in the present work. The results show that the predictions on pressure distributions with SST k-ω and v2f turbulence models have good agreements with experimental data.
Keywords: Horizontal Axis Wind Turbine, turbulence model, noise.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21541522 Tests for Gaussianity of a Stationary Time Series
Authors: Adnan Al-Smadi
Abstract:
One of the primary uses of higher order statistics in signal processing has been for detecting and estimation of non- Gaussian signals in Gaussian noise of unknown covariance. This is motivated by the ability of higher order statistics to suppress additive Gaussian noise. In this paper, several methods to test for non- Gaussianity of a given process are presented. These methods include histogram plot, kurtosis test, and hypothesis testing using cumulants and bispectrum of the available sequence. The hypothesis testing is performed by constructing a statistic to test whether the bispectrum of the given signal is non-zero. A zero bispectrum is not a proof of Gaussianity. Hence, other tests such as the kurtosis test should be employed. Examples are given to demonstrate the performance of the presented methods.Keywords: Non-Gaussian, bispectrum, kurtosis, hypothesistesting, histogram.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18971521 Throughput Analysis over Power Line Communication Channel in an Electric Noisy Scenario
Authors: Edward P. Guillen, Julián J. López, Cesar Y. Barahona
Abstract:
Powerline Communications –PLC– as an alternative method for broadband networking, has the advantage of transmitting over channels already used for electrical distribution or even transmission. But these channels have been not designed with usual wired channels requirements for broadband applications such as stable impedance or known attenuation, and the network have to reject noises caused by electrical appliances that share the same channel. Noise control standards are difficult to complain or simply do not exist on Latin-American environments. This paper analyzes PLC throughput for home connectivity by probing noisy channel scenarios in a PLC network and the statistical results are shown.Keywords: Power Line Communications, OFDM, Noise Analysis, Throughput Analysis, PLC, Home Network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22971520 Stochastic Resonance in Nonlinear Signal Detection
Authors: Youguo Wang, Lenan Wu
Abstract:
Stochastic resonance (SR) is a phenomenon whereby the signal transmission or signal processing through certain nonlinear systems can be improved by adding noise. This paper discusses SR in nonlinear signal detection by a simple test statistic, which can be computed from multiple noisy data in a binary decision problem based on a maximum a posteriori probability criterion. The performance of detection is assessed by the probability of detection error Per . When the input signal is subthreshold signal, we establish that benefit from noise can be gained for different noises and confirm further that the subthreshold SR exists in nonlinear signal detection. The efficacy of SR is significantly improved and the minimum of Per can dramatically approach to zero as the sample number increases. These results show the robustness of SR in signal detection and extend the applicability of SR in signal processing.Keywords: Probability of detection error, signal detection, stochastic resonance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15211519 A Reconfigurable Distributed Multiagent System Optimized for Scalability
Authors: Summiya Moheuddin, Afzel Noore, Muhammad Choudhry
Abstract:
This paper proposes a novel solution for optimizing the size and communication overhead of a distributed multiagent system without compromising the performance. The proposed approach addresses the challenges of scalability especially when the multiagent system is large. A modified spectral clustering technique is used to partition a large network into logically related clusters. Agents are assigned to monitor dedicated clusters rather than monitor each device or node. The proposed scalable multiagent system is implemented using JADE (Java Agent Development Environment) for a large power system. The performance of the proposed topologyindependent decentralized multiagent system and the scalable multiagent system is compared by comprehensively simulating different fault scenarios. The time taken for reconfiguration, the overall computational complexity, and the communication overhead incurred are computed. The results of these simulations show that the proposed scalable multiagent system uses fewer agents efficiently, makes faster decisions to reconfigure when a fault occurs, and incurs significantly less communication overhead.Keywords: Multiagent system, scalable design, spectral clustering, reconfiguration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13741518 Problems of Lifelong Education Course in Information and Communication Technology
Authors: Hisham Md Suhadi, Faaizah Shahbodin, Jamaluddin Hashim
Abstract:
The study is the way to identify the problems that occur in organizing short course’s lifelong learning in the information and communication technology (ICT) education which are faced by the lecturer and staff at the Mara Skill Institute and Industrial Training Institute in Pahang Malaysia. The important aspects of these issues are classified to five which are selecting the courses administrative. Fifty lecturers and staff were selected as a respondent. The sample is selected by using the non-random sampling method purpose sampling. The questionnaire is used as a research instrument and divided into five main parts. All the data that gain from the questionnaire are analyzed by using the SPSS in term of mean, standard deviation and percentage. The findings showed, there are the problems occur in organizing the short course for lifelong learning in ICT education.Keywords: Lifelong education, information and communication technology (ICT), short course, ICT education, courses administrative.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17961517 Continuous Feature Adaptation for Non-Native Speech Recognition
Authors: Y. Deng, X. Li, C. Kwan, B. Raj, R. Stern
Abstract:
The current speech interfaces in many military applications may be adequate for native speakers. However, the recognition rate drops quite a lot for non-native speakers (people with foreign accents). This is mainly because the nonnative speakers have large temporal and intra-phoneme variations when they pronounce the same words. This problem is also complicated by the presence of large environmental noise such as tank noise, helicopter noise, etc. In this paper, we proposed a novel continuous acoustic feature adaptation algorithm for on-line accent and environmental adaptation. Implemented by incremental singular value decomposition (SVD), the algorithm captures local acoustic variation and runs in real-time. This feature-based adaptation method is then integrated with conventional model-based maximum likelihood linear regression (MLLR) algorithm. Extensive experiments have been performed on the NATO non-native speech corpus with baseline acoustic model trained on native American English. The proposed feature-based adaptation algorithm improved the average recognition accuracy by 15%, while the MLLR model based adaptation achieved 11% improvement. The corresponding word error rate (WER) reduction was 25.8% and 2.73%, as compared to that without adaptation. The combined adaptation achieved overall recognition accuracy improvement of 29.5%, and WER reduction of 31.8%, as compared to that without adaptation. Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32051516 Characteristics of Maximum Gliding Endurance Path for High-Altitude Solar UAVs
Authors: Gao Xian-Zhong, Hou Zhong-xi, Guo Zheng, Liu Jian-xia
Abstract:
Gliding during night without electric power is an efficient method to enhance endurance performance of solar aircrafts. The properties of maximum gliding endurance path are studied in this paper. The problem is formulated as an optimization problem about maximum endurance can be sustained by certain potential energy storage with dynamic equations and aerodynamic parameter constrains. The optimal gliding path is generated based on gauss pseudo-spectral method. In order to analyse relationship between altitude, velocity of solar UAVs and its endurance performance, the lift coefficient in interval of [0.4, 1.2] and flight envelopes between 0~30km are investigated. Results show that broad range of lift coefficient can improve solar aircrafts- long endurance performance, and it is possible for a solar aircraft to achieve the aim of long endurance during whole night just by potential energy storage.
Keywords: Solar UAVs, Gliding Endurance, gauss pseudo-spectral method, optimization problem
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29161515 Steady State Rolling and Dynamic Response of a Tire at Low Frequency
Authors: Md Monir Hossain, Anne Staples, Kuya Takami, Tomonari Furukawa
Abstract:
Tire noise has a significant impact on ride quality and vehicle interior comfort, even at low frequency. Reduction of tire noise is especially important due to strict state and federal environmental regulations. The primary sources of tire noise are the low frequency structure-borne noise and the noise that originates from the release of trapped air between the tire tread and road surface during each revolution of the tire. The frequency response of the tire changes at low and high frequency. At low frequency, the tension and bending moment become dominant, while the internal structure and local deformation become dominant at higher frequencies. Here, we analyze tire response in terms of deformation and rolling velocity at low revolution frequency. An Abaqus FEA finite element model is used to calculate the static and dynamic response of a rolling tire under different rolling conditions. The natural frequencies and mode shapes of a deformed tire are calculated with the FEA package where the subspace-based steady state dynamic analysis calculates dynamic response of tire subjected to harmonic excitation. The analysis was conducted on the dynamic response at the road (contact point of tire and road surface) and side nodes of a static and rolling tire when the tire was excited with 200 N vertical load for a frequency ranging from 20 to 200 Hz. The results show that frequency has little effect on tire deformation up to 80 Hz. But between 80 and 200 Hz, the radial and lateral components of displacement of the road and side nodes exhibited significant oscillation. For the static analysis, the fluctuation was sharp and frequent and decreased with frequency. In contrast, the fluctuation was periodic in nature for the dynamic response of the rolling tire. In addition to the dynamic analysis, a steady state rolling analysis was also performed on the tire traveling at ground velocity with a constant angular motion. The purpose of the computation was to demonstrate the effect of rotating motion on deformation and rolling velocity with respect to a fixed Newtonian reference point. The analysis showed a significant variation in deformation and rolling velocity due to centrifugal and Coriolis acceleration with respect to a fixed Newtonian point on ground.Keywords: Natural frequency, rotational motion, steady state rolling, subspace-based steady state dynamic analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13101514 Analysis of FWM Penalties in DWDM Systems Based on G.652, G.653, and G.655 Optical Fibers
Authors: Paula B. Harboe, Edilson da Silva, José R. Souza
Abstract:
This paper presents an investigation of the power penalties imposed by four-wave mixing (FWM) on G.652 (Single- Mode Fiber - SMF), G.653 (Dispersion-Shifted Fiber - DSF), and G.655 (Non-Zero Dispersion-Shifted Fiber - NZDSF) compliant fibers, considering the DWDM grids suggested by the ITU-T Recommendations G.692, and G.694.1, with uniform channel spacing of 100, 50, 25, and 12.5 GHz. The mathematical/numerical model assumes undepleted pumping, and shows very clearly the deleterious effect of FWM on the performance of DWDM systems, measured by the signal-to-noise ratio (SNR). The results make it evident that non-uniform channel spacing is practically mandatory for WDM systems based on DSF fibers.Keywords: DWDM systems, Four-Wave Mixing (FWM), G.652, G.653, G.655 compliant fibers, Signal-to-noise ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30441513 Studies of Rule Induction by STRIM from the Decision Table with Contaminated Attribute Values from Missing Data and Noise — In the Case of Critical Dataset Size —
Authors: Tetsuro Saeki, Yuichi Kato, Shoutarou Mizuno
Abstract:
STRIM (Statistical Test Rule Induction Method) has been proposed as a method to effectively induct if-then rules from the decision table which is considered as a sample set obtained from the population of interest. Its usefulness has been confirmed by simulation experiments specifying rules in advance, and by comparison with conventional methods. However, scope for future development remains before STRIM can be applied to the analysis of real-world data sets. The first requirement is to determine the size of the dataset needed for inducting true rules, since finding statistically significant rules is the core of the method. The second is to examine the capacity of rule induction from datasets with contaminated attribute values created by missing data and noise, since real-world datasets usually contain such contaminated data. This paper examines the first problem theoretically, in connection with the rule length. The second problem is then examined in a simulation experiment, utilizing the critical size of dataset derived from the first step. The experimental results show that STRIM is highly robust in the analysis of datasets with contaminated attribute values, and hence is applicable to real-world data
Keywords: Rule induction, decision table, missing data, noise.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14531512 Restoration of Noisy Document Images with an Efficient Bi-Level Adaptive Thresholding
Authors: Abhijit Mitra
Abstract:
An effective approach for extracting document images from a noisy background is introduced. The entire scheme is divided into three sub- stechniques – the initial preprocessing operations for noise cluster tightening, introduction of a new thresholding method by maximizing the ratio of stan- dard deviations of the combined effect on the image to the sum of weighted classes and finally the image restoration phase by image binarization utiliz- ing the proposed optimum threshold level. The proposed method is found to be efficient compared to the existing schemes in terms of computational complexity as well as speed with better noise rejection.
Keywords: Document image extraction, Preprocessing, Ratio of stan-dard deviations, Bi-level adaptive thresholding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14471511 Design of an Efficient Retimed CIC Compensation Filter
Authors: Vishal Awasthi, Krishna Raj
Abstract:
Unwanted side effects because of spectral aliasing and spectral imaging during signal processing would be the major concern over the sampling rate alteration. Multirate-multistage implementation of digital filter could come about a large computational saving than single rate filter suitable for sample rate conversion. This implementation can further improve through high-level architectural transformation in circuit level. Reallocating registers and relocating flip-flops across logic gates through retiming certainly a prominent sequential transformation technology, that optimize hardware circuits to achieve faster clocking speed without affecting the functionality. In this paper, we proposed an efficient compensated cascade Integrator comb (CIC) decimation filter structure that analyze the consequence of filter order variation which has a retimed FIR filter being compensator while using the cutset retiming technique and achieved an improvement in the passband droop by 14% to 39%, in computation time by 38.04%, 25.78%, 12.21%, 6.69% and 4.44% and reduction in path delay by 62.27%, 72%, 86.63%, 91.56% and 94.42% of 3, 6, 8, 12 and 24 order filter respectively than the non-retimed CIC compensation filter.
Keywords: Multirate Filtering, CIC decimation filter, Compensation theory, Retiming, Retiming algorithm, Filter order, Synchronous dataflow graph.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36921510 Integration of Support Vector Machine and Bayesian Neural Network for Data Mining and Classification
Authors: Essam Al-Daoud
Abstract:
Several combinations of the preprocessing algorithms, feature selection techniques and classifiers can be applied to the data classification tasks. This study introduces a new accurate classifier, the proposed classifier consist from four components: Signal-to- Noise as a feature selection technique, support vector machine, Bayesian neural network and AdaBoost as an ensemble algorithm. To verify the effectiveness of the proposed classifier, seven well known classifiers are applied to four datasets. The experiments show that using the suggested classifier enhances the classification rates for all datasets.Keywords: AdaBoost, Bayesian neural network, Signal-to-Noise, support vector machine, MCMC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20101509 Single Input ANC for Suppression of Breath Sound
Authors: Yunjung Lee, Pil Un Kim, Gyhyoun Lee, Jin Ho Cho, Myoung Nam Kim
Abstract:
Various sounds generated in the chest are included in auscultation sound. Adaptive Noise Canceller (ANC) is one of the useful techniques for biomedical signal. But the ANC is not suitable for auscultation sound. Because the ANC needs two input channels as a primary signal and a reference signals, but a stethoscope can provide just one input sound. Therefore, in this paper, it was proposed the Single Input ANC (SIANC) for suppression of breath sound in a cardiac auscultation sound. For the SIANC, it was proposed that the reference generation system which included Heart Sound Detector, Control and Reference Generator. By experiment and comparison, it was confirmed that the proposed SIANC was efficient for heart sound enhancement and it was independent of variations of a heartbeat.Keywords: Adaptive noise canceller, Auscultation, Breath soundsuppression, Signal enhancement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1454