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Sample records for online filtering based

  1. Neural Online Filtering Based on Preprocessed Calorimeter Data

    CERN Document Server

    Torres, R C; The ATLAS collaboration; Simas Filho, E F; De Seixas, J M

    2009-01-01

    Among LHC detectors, ATLAS aims at coping with such high event rate by designing a three-level online triggering system. The first level trigger output will be ~75 kHz. This level will mark the regions where relevant events were found. The second level will validate LVL1 decision by looking only at the approved data using full granularity. At the level two output, the event rate will be reduced to ~2 kHz. Finally, the third level will look at full event information and a rate of ~200 Hz events is expected to be approved, and stored in persistent media for further offline analysis. Many interesting events decay into electrons, which have to be identified from the huge background noise (jets). This work proposes a high-efficient LVL2 electron / jet discrimination system based on neural networks fed from preprocessed calorimeter information. The feature extraction part of the proposed system performs a ring structure of data description. A set of concentric rings centered at the highest energy cell is generated ...

  2. Online Internal Temperature Estimation for Lithium-Ion Batteries Based on Kalman Filter

    OpenAIRE

    Jinlei Sun; Guo Wei; Lei Pei; Rengui Lu; Kai Song; Chao Wu; Chunbo Zhu

    2015-01-01

    The battery internal temperature estimation is important for the thermal safety in applications, because the internal temperature is hard to measure directly. In this work, an online internal temperature estimation method based on a simplified thermal model using a Kalman filter is proposed. As an improvement, the influences of entropy change and overpotential on heat generation are analyzed quantitatively. The model parameters are identified through a current pulse test. The charge/discharg...

  3. Online variational Bayesian filtering-based mobile target tracking in wireless sensor networks.

    Science.gov (United States)

    Zhou, Bingpeng; Chen, Qingchun; Li, Tiffany Jing; Xiao, Pei

    2014-11-11

    The received signal strength (RSS)-based online tracking for a mobile node in wireless sensor networks (WSNs) is investigated in this paper. Firstly, a multi-layer dynamic Bayesian network (MDBN) is introduced to characterize the target mobility with either directional or undirected movement. In particular, it is proposed to employ the Wishart distribution to approximate the time-varying RSS measurement precision's randomness due to the target movement. It is shown that the proposed MDBN offers a more general analysis model via incorporating the underlying statistical information of both the target movement and observations, which can be utilized to improve the online tracking capability by exploiting the Bayesian statistics. Secondly, based on the MDBN model, a mean-field variational Bayesian filtering (VBF) algorithm is developed to realize the online tracking of a mobile target in the presence of nonlinear observations and time-varying RSS precision, wherein the traditional Bayesian filtering scheme cannot be directly employed. Thirdly, a joint optimization between the real-time velocity and its prior expectation is proposed to enable online velocity tracking in the proposed online tacking scheme. Finally, the associated Bayesian Cramer-Rao Lower Bound (BCRLB) analysis and numerical simulations are conducted. Our analysis unveils that, by exploiting the potential state information via the general MDBN model, the proposed VBF algorithm provides a promising solution to the online tracking of a mobile node in WSNs. In addition, it is shown that the final tracking accuracy linearly scales with its expectation when the RSS measurement precision is time-varying.

  4. Research on a Lamb Wave and Particle Filter-Based On-Line Crack Propagation Prognosis Method

    OpenAIRE

    Chen, Jian; Yuan, Shenfang; Qiu, Lei; Cai, Jian; Yang, Weibo

    2016-01-01

    Prognostics and health management techniques have drawn widespread attention due to their ability to facilitate maintenance activities based on need. On-line prognosis of fatigue crack propagation can offer information for optimizing operation and maintenance strategies in real-time. This paper proposes a Lamb wave-particle filter (LW-PF)-based method for on-line prognosis of fatigue crack propagation which takes advantages of the possibility of on-line monitoring to evaluate the actual crack...

  5. On-line filtering

    International Nuclear Information System (INIS)

    Verkerk, C.

    1978-01-01

    Present day electronic detectors used in high energy physics make it possible to obtain high event rates and it is likely that future experiments will face even higher data rates than at present. The complexity of the apparatus increases very rapidly with time and also the criteria for selecting desired events become more and more complex. So complex in fact that the fast trigger system cannot be designed to fully cope with it. The interesting events become thus contaminated with multitudes of uninteresting ones. To distinguish the 'good' events from the often overwhelming background of other events one has to resort to computing techniques. Normally this selection is made in the first part of the analysis of the events, analysis normally performed on a powerful scientific computer. This implies however that many uninteresting or background events have to be recorded during the experiment for subsequent analysis. A number of undesired consequences result; and these constitute a sufficient reason for trying to perform the selection at an earlier stage, in fact ideally before the events are recorded on magnetic tape. This early selection is called 'on-line filtering' and it is the topic of the present lectures. (Auth.)

  6. Online Internal Temperature Estimation for Lithium-Ion Batteries Based on Kalman Filter

    Directory of Open Access Journals (Sweden)

    Jinlei Sun

    2015-05-01

    Full Text Available The battery internal temperature estimation is important for the thermal safety in applications, because the internal temperature is hard to measure directly. In this work, an online internal temperature estimation method based on a simplified thermal model using a Kalman filter is proposed. As an improvement, the influences of entropy change and overpotential on heat generation are analyzed quantitatively. The model parameters are identified through a current pulse test. The charge/discharge experiments under different current rates are carried out on the same battery to verify the estimation results. The internal and surface temperatures are measured with thermocouples for result validation and model construction. The accuracy of the estimated result is validated with a maximum estimation error of around 1 K.

  7. Online Speech/Music Segmentation Based on the Variance Mean of Filter Bank Energy

    Directory of Open Access Journals (Sweden)

    Zdravko Kačič

    2009-01-01

    Full Text Available This paper presents a novel feature for online speech/music segmentation based on the variance mean of filter bank energy (VMFBE. The idea that encouraged the feature's construction is energy variation in a narrow frequency sub-band. The energy varies more rapidly, and to a greater extent for speech than for music. Therefore, an energy variance in such a sub-band is greater for speech than for music. The radio broadcast database and the BNSI broadcast news database were used for feature discrimination and segmentation ability evaluation. The calculation procedure of the VMFBE feature has 4 out of 6 steps in common with the MFCC feature calculation procedure. Therefore, it is a very convenient speech/music discriminator for use in real-time automatic speech recognition systems based on MFCC features, because valuable processing time can be saved, and computation load is only slightly increased. Analysis of the feature's speech/music discriminative ability shows an average error rate below 10% for radio broadcast material and it outperforms other features used for comparison, by more than 8%. The proposed feature as a stand-alone speech/music discriminator in a segmentation system achieves an overall accuracy of over 94% on radio broadcast material.

  8. Online Speech/Music Segmentation Based on the Variance Mean of Filter Bank Energy

    Science.gov (United States)

    Kos, Marko; Grašič, Matej; Kačič, Zdravko

    2009-12-01

    This paper presents a novel feature for online speech/music segmentation based on the variance mean of filter bank energy (VMFBE). The idea that encouraged the feature's construction is energy variation in a narrow frequency sub-band. The energy varies more rapidly, and to a greater extent for speech than for music. Therefore, an energy variance in such a sub-band is greater for speech than for music. The radio broadcast database and the BNSI broadcast news database were used for feature discrimination and segmentation ability evaluation. The calculation procedure of the VMFBE feature has 4 out of 6 steps in common with the MFCC feature calculation procedure. Therefore, it is a very convenient speech/music discriminator for use in real-time automatic speech recognition systems based on MFCC features, because valuable processing time can be saved, and computation load is only slightly increased. Analysis of the feature's speech/music discriminative ability shows an average error rate below 10% for radio broadcast material and it outperforms other features used for comparison, by more than 8%. The proposed feature as a stand-alone speech/music discriminator in a segmentation system achieves an overall accuracy of over 94% on radio broadcast material.

  9. Analysis of a Kalman filter based method for on-line estimation of atmospheric dispersion parameters using radiation monitoring data

    DEFF Research Database (Denmark)

    Drews, Martin; Lauritzen, Bent; Madsen, Henrik

    2005-01-01

    A Kalman filter method is discussed for on-line estimation of radioactive release and atmospheric dispersion from a time series of off-site radiation monitoring data. The method is based on a state space approach, where a stochastic system equation describes the dynamics of the plume model...... parameters, and the observables are linked to the state variables through a static measurement equation. The method is analysed for three simple state space models using experimental data obtained at a nuclear research reactor. Compared to direct measurements of the atmospheric dispersion, the Kalman filter...... estimates are found to agree well with the measured parameters, provided that the radiation measurements are spread out in the cross-wind direction. For less optimal detector placement it proves difficult to distinguish variations in the source term and plume height; yet the Kalman filter yields consistent...

  10. On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure

    Directory of Open Access Journals (Sweden)

    Yuanqiang Ren

    2017-05-01

    Full Text Available Structural health monitoring (SHM of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures.

  11. Convergent Filter Bases

    Directory of Open Access Journals (Sweden)

    Coghetto Roland

    2015-09-01

    Full Text Available We are inspired by the work of Henri Cartan [16], Bourbaki [10] (TG. I Filtres and Claude Wagschal [34]. We define the base of filter, image filter, convergent filter bases, limit filter and the filter base of tails (fr: filtre des sections.

  12. Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing

    Directory of Open Access Journals (Sweden)

    Denis Delisle-Rodriguez

    2017-11-01

    Full Text Available This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG signals, but preserving the useful information. Standard deviation and Concordance Correlation Coefficient (CCC between target electrodes and its correspondent neighbor electrodes are analyzed on sliding windows to select those neighbors that are highly correlated. Afterwards, a model based on CCC is applied to provide higher values of weight to those correlated electrodes with lower similarity to the target electrode. The approach was applied to brain computer-interfaces (BCIs based on Canonical Correlation Analysis (CCA to recognize 40 targets of steady-state visual evoked potential (SSVEP, providing an accuracy (ACC of 86.44 ± 2.81%. In addition, also using this approach, features of low frequency were selected in the pre-processing stage of another BCI to recognize gait planning. In this case, the recognition was significantly ( p < 0.01 improved for most of the subjects ( A C C ≥ 74.79 % , when compared with other BCIs based on Common Spatial Pattern, Filter Bank-Common Spatial Pattern, and Riemannian Geometry.

  13. On-line measurement of oil contaminants in water by filter-based infrared analyzers

    International Nuclear Information System (INIS)

    Niemelae, P.

    1994-01-01

    The properties of a dedicated infrared analyzer for on-line measurement of the oil content of water, the Oili analyzer, are evaluated theoretically and with laboratory measurements. The analyzer was originally developed for controlling the discharge of ballast and bilge water from oil tankers and more than 200 such instruments have now been supplied for that purpose, representing about 10 % of the total market. Some technical improvements are suggested, and the improved instrument is shown to be capable of measuring oil in water to an accuracy of +- 20 % down to a detection limit of +5-10 ppm in the presence of high concentrations of interfering components and under varying environmental conditions. This opens up new potential applications for the instrument, e.g. the monitoring of water discharges from oil and gas production platforms. The infrared analyzer responds only to the dispersed oil fraction, and if the dissolved fraction is of interest as well, the instrument must be equipped with a UV option, as suggested here

  14. Visual object tracking by correlation filters and online learning

    Science.gov (United States)

    Zhang, Xin; Xia, Gui-Song; Lu, Qikai; Shen, Weiming; Zhang, Liangpei

    2018-06-01

    Due to the complexity of background scenarios and the variation of target appearance, it is difficult to achieve high accuracy and fast speed for object tracking. Currently, correlation filters based trackers (CFTs) show promising performance in object tracking. The CFTs estimate the target's position by correlation filters with different kinds of features. However, most of CFTs can hardly re-detect the target in the case of long-term tracking drifts. In this paper, a feature integration object tracker named correlation filters and online learning (CFOL) is proposed. CFOL estimates the target's position and its corresponding correlation score using the same discriminative correlation filter with multi-features. To reduce tracking drifts, a new sampling and updating strategy for online learning is proposed. Experiments conducted on 51 image sequences demonstrate that the proposed algorithm is superior to the state-of-the-art approaches.

  15. A diagnostic imaging approach for online characterization of multi-impact in aircraft composite structures based on a scanning spatial-wavenumber filter of guided wave

    Science.gov (United States)

    Ren, Yuanqiang; Qiu, Lei; Yuan, Shenfang; Su, Zhongqing

    2017-06-01

    Monitoring of impact and multi-impact in particular in aircraft composite structures has been an intensive research topic in the field of guided-wave-based structural health monitoring (SHM). Compared with the majority of existing methods such as those using signal features in the time-, frequency- or joint time-frequency domain, the approach based on spatial-wavenumber filter of guided wave shows superb advantage in effectively distinguishing particular wave modes and identifying their propagation direction relative to the sensor array. However, there exist two major issues when conducting online characterization of multi-impact event. Firstly, the spatial-wavenumber filter should be realized in the situation that the wavenumber of high spatial resolution of the complicated multi-impact signal cannot be measured or modeled. Secondly, it's difficult to identify the multiple impacts and realize multi-impact localization due to the overlapping of wavenumbers. To address these issues, a scanning spatial-wavenumber filter based diagnostic imaging method for online characterization of multi-impact event is proposed to conduct multi-impact imaging and localization in this paper. The principle of the scanning filter for multi-impact is developed first to conduct spatial-wavenumber filtering and to achieve wavenumber-time imaging of the multiple impacts. Then, a feature identification method of multi-impact based on eigenvalue decomposition and wavenumber searching is presented to estimate the number of impacts and calculate the wavenumber of the multi-impact signal, and an image mapping method is proposed as well to convert the wavenumber-time image to an angle-distance image to distinguish and locate the multiple impacts. A series of multi-impact events are applied to a carbon fiber laminate plate to validate the proposed methods. The validation results show that the localization of the multiple impacts are well achieved.

  16. LHCb Online event processing and filtering

    Science.gov (United States)

    Alessio, F.; Barandela, C.; Brarda, L.; Frank, M.; Franek, B.; Galli, D.; Gaspar, C.; Herwijnen, E. v.; Jacobsson, R.; Jost, B.; Köstner, S.; Moine, G.; Neufeld, N.; Somogyi, P.; Stoica, R.; Suman, S.

    2008-07-01

    The first level trigger of LHCb accepts one million events per second. After preprocessing in custom FPGA-based boards these events are distributed to a large farm of PC-servers using a high-speed Gigabit Ethernet network. Synchronisation and event management is achieved by the Timing and Trigger system of LHCb. Due to the complex nature of the selection of B-events, which are the main interest of LHCb, a full event-readout is required. Event processing on the servers is parallelised on an event basis. The reduction factor is typically 1/500. The remaining events are forwarded to a formatting layer, where the raw data files are formed and temporarily stored. A small part of the events is also forwarded to a dedicated farm for calibration and monitoring. The files are subsequently shipped to the CERN Tier0 facility for permanent storage and from there to the various Tier1 sites for reconstruction. In parallel files are used by various monitoring and calibration processes running within the LHCb Online system. The entire data-flow is controlled and configured by means of a SCADA system and several databases. After an overview of the LHCb data acquisition and its design principles this paper will emphasize the LHCb event filter system, which is now implemented using the final hardware and will be ready for data-taking for the LHC startup. Control, configuration and security aspects will also be discussed.

  17. LHCb Online event processing and filtering

    International Nuclear Information System (INIS)

    Alessio, F; Barandela, C; Brarda, L; Frank, M; Gaspar, C; Herwijnen, E v; Jacobsson, R; Jost, B; Koestner, S; Moine, G; Neufeld, N; Somogyi, P; Stoica, R; Suman, S; Franek, B; Galli, D

    2008-01-01

    The first level trigger of LHCb accepts one million events per second. After preprocessing in custom FPGA-based boards these events are distributed to a large farm of PC-servers using a high-speed Gigabit Ethernet network. Synchronisation and event management is achieved by the Timing and Trigger system of LHCb. Due to the complex nature of the selection of B-events, which are the main interest of LHCb, a full event-readout is required. Event processing on the servers is parallelised on an event basis. The reduction factor is typically 1/500. The remaining events are forwarded to a formatting layer, where the raw data files are formed and temporarily stored. A small part of the events is also forwarded to a dedicated farm for calibration and monitoring. The files are subsequently shipped to the CERN Tier0 facility for permanent storage and from there to the various Tier1 sites for reconstruction. In parallel files are used by various monitoring and calibration processes running within the LHCb Online system. The entire data-flow is controlled and configured by means of a SCADA system and several databases. After an overview of the LHCb data acquisition and its design principles this paper will emphasize the LHCb event filter system, which is now implemented using the final hardware and will be ready for data-taking for the LHC startup. Control, configuration and security aspects will also be discussed

  18. Sequential Monte Carlo filter for state estimation of LiFePO4 batteries based on an online updated model

    Science.gov (United States)

    Li, Jiahao; Klee Barillas, Joaquin; Guenther, Clemens; Danzer, Michael A.

    2014-02-01

    Battery state monitoring is one of the key techniques in battery management systems e.g. in electric vehicles. An accurate estimation can help to improve the system performance and to prolong the battery remaining useful life. Main challenges for the state estimation for LiFePO4 batteries are the flat characteristic of open-circuit-voltage over battery state of charge (SOC) and the existence of hysteresis phenomena. Classical estimation approaches like Kalman filtering show limitations to handle nonlinear and non-Gaussian error distribution problems. In addition, uncertainties in the battery model parameters must be taken into account to describe the battery degradation. In this paper, a novel model-based method combining a Sequential Monte Carlo filter with adaptive control to determine the cell SOC and its electric impedance is presented. The applicability of this dual estimator is verified using measurement data acquired from a commercial LiFePO4 cell. Due to a better handling of the hysteresis problem, results show the benefits of the proposed method against the estimation with an Extended Kalman filter.

  19. GA103: A microprogrammable processor for online filtering

    International Nuclear Information System (INIS)

    Calzas, A.; Danon, G.; Bouquet, B.

    1981-01-01

    GA 103 is a 16 bit microprogrammable processor which emulates the PDP 11 instruction set. It is based on the Am 2900 slices. It allows user-implemented microinstructions and addition of hardwired processors. It will perform on-line filtering tasks in the NA 14 experiment at CERN, based on the reconstruction of transverse momentum of photons detected in a lead glass calorimeter. (orig.)

  20. Online Parameter Identification and State of Charge Estimation of Lithium-Ion Batteries Based on Forgetting Factor Recursive Least Squares and Nonlinear Kalman Filter

    Directory of Open Access Journals (Sweden)

    Bizhong Xia

    2017-12-01

    Full Text Available State of charge (SOC estimation is the core of any battery management system. Most closed-loop SOC estimation algorithms are based on the equivalent circuit model with fixed parameters. However, the parameters of the equivalent circuit model will change as temperature or SOC changes, resulting in reduced SOC estimation accuracy. In this paper, two SOC estimation algorithms with online parameter identification are proposed to solve this problem based on forgetting factor recursive least squares (FFRLS and nonlinear Kalman filter. The parameters of a Thevenin model are constantly updated by FFRLS. The nonlinear Kalman filter is used to perform the recursive operation to estimate SOC. Experiments in variable temperature environments verify the effectiveness of the proposed algorithms. A combination of four driving cycles is loaded on lithium-ion batteries to test the adaptability of the approaches to different working conditions. Under certain conditions, the average error of the SOC estimation dropped from 5.6% to 1.1% after adding the online parameters identification, showing that the estimation accuracy of proposed algorithms is greatly improved. Besides, simulated measurement noise is added to the test data to prove the robustness of the algorithms.

  1. Online Identification with Reliability Criterion and State of Charge Estimation Based on a Fuzzy Adaptive Extended Kalman Filter for Lithium-Ion Batteries

    Directory of Open Access Journals (Sweden)

    Zhongwei Deng

    2016-06-01

    Full Text Available In the field of state of charge (SOC estimation, the Kalman filter has been widely used for many years, although its performance strongly depends on the accuracy of the battery model as well as the noise covariance. The Kalman gain determines the confidence coefficient of the battery model by adjusting the weight of open circuit voltage (OCV correction, and has a strong correlation with the measurement noise covariance (R. In this paper, the online identification method is applied to acquire the real model parameters under different operation conditions. A criterion based on the OCV error is proposed to evaluate the reliability of online parameters. Besides, the equivalent circuit model produces an intrinsic model error which is dependent on the load current, and the property that a high battery current or a large current change induces a large model error can be observed. Based on the above prior knowledge, a fuzzy model is established to compensate the model error through updating R. Combining the positive strategy (i.e., online identification and negative strategy (i.e., fuzzy model, a more reliable and robust SOC estimation algorithm is proposed. The experiment results verify the proposed reliability criterion and SOC estimation method under various conditions for LiFePO4 batteries.

  2. On-Line Temperature Estimation for Noisy Thermal Sensors Using a Smoothing Filter-Based Kalman Predictor

    Directory of Open Access Journals (Sweden)

    Xin Li

    2018-02-01

    Full Text Available Dynamic thermal management (DTM mechanisms utilize embedded thermal sensors to collect fine-grained temperature information for monitoring the real-time thermal behavior of multi-core processors. However, embedded thermal sensors are very susceptible to a variety of sources of noise, including environmental uncertainty and process variation. This causes the discrepancies between actual temperatures and those observed by on-chip thermal sensors, which seriously affect the efficiency of DTM. In this paper, a smoothing filter-based Kalman prediction technique is proposed to accurately estimate the temperatures from noisy sensor readings. For the multi-sensor estimation scenario, the spatial correlations among different sensor locations are exploited. On this basis, a multi-sensor synergistic calibration algorithm (known as MSSCA is proposed to improve the simultaneous prediction accuracy of multiple sensors. Moreover, an infrared imaging-based temperature measurement technique is also proposed to capture the thermal traces of an advanced micro devices (AMD quad-core processor in real time. The acquired real temperature data are used to evaluate our prediction performance. Simulation shows that the proposed synergistic calibration scheme can reduce the root-mean-square error (RMSE by 1.2 ∘ C and increase the signal-to-noise ratio (SNR by 15.8 dB (with a very small average runtime overhead compared with assuming the thermal sensor readings to be ideal. Additionally, the average false alarm rate (FAR of the corrected sensor temperature readings can be reduced by 28.6%. These results clearly demonstrate that if our approach is used to perform temperature estimation, the response mechanisms of DTM can be triggered to adjust the voltages, frequencies, and cooling fan speeds at more appropriate times.

  3. On-Line Temperature Estimation for Noisy Thermal Sensors Using a Smoothing Filter-Based Kalman Predictor.

    Science.gov (United States)

    Li, Xin; Ou, Xingtao; Li, Zhi; Wei, Henglu; Zhou, Wei; Duan, Zhemin

    2018-02-02

    Dynamic thermal management (DTM) mechanisms utilize embedded thermal sensors to collect fine-grained temperature information for monitoring the real-time thermal behavior of multi-core processors. However, embedded thermal sensors are very susceptible to a variety of sources of noise, including environmental uncertainty and process variation. This causes the discrepancies between actual temperatures and those observed by on-chip thermal sensors, which seriously affect the efficiency of DTM. In this paper, a smoothing filter-based Kalman prediction technique is proposed to accurately estimate the temperatures from noisy sensor readings. For the multi-sensor estimation scenario, the spatial correlations among different sensor locations are exploited. On this basis, a multi-sensor synergistic calibration algorithm (known as MSSCA) is proposed to improve the simultaneous prediction accuracy of multiple sensors. Moreover, an infrared imaging-based temperature measurement technique is also proposed to capture the thermal traces of an advanced micro devices (AMD) quad-core processor in real time. The acquired real temperature data are used to evaluate our prediction performance. Simulation shows that the proposed synergistic calibration scheme can reduce the root-mean-square error (RMSE) by 1.2 ∘ C and increase the signal-to-noise ratio (SNR) by 15.8 dB (with a very small average runtime overhead) compared with assuming the thermal sensor readings to be ideal. Additionally, the average false alarm rate (FAR) of the corrected sensor temperature readings can be reduced by 28.6%. These results clearly demonstrate that if our approach is used to perform temperature estimation, the response mechanisms of DTM can be triggered to adjust the voltages, frequencies, and cooling fan speeds at more appropriate times.

  4. Internet Filtering Technology and Aversive Online Experiences in Adolescents.

    Science.gov (United States)

    Przybylski, Andrew K; Nash, Victoria

    2017-05-01

    To evaluate the effectiveness of Internet filtering tools designed to shield adolescents from aversive experiences online. A total of 1030 in-home interviews were conducted with early adolescents aged from 12 to 15 years (M = 13.50, SD = 1.18) and their caregivers. Caregivers were asked about their use of Internet filtering and adolescent participants were interviewed about their recent online experiences. Contrary to our hypotheses, policy, and industry advice regarding the assumed benefits of filtering we found convincing evidence that Internet filters were not effective at shielding early adolescents from aversive online experiences. Preregistered prospective and randomised controlled trials are needed to determine the extent to which Internet filtering technology supports vs thwarts young people online and if their widespread use justifies their financial and informational costs. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Perception-Based Filtering for MMOGs

    Directory of Open Access Journals (Sweden)

    Souad El Merhebi

    2008-01-01

    Full Text Available Online games have exploded in the last few years. These games face several problems linked to scalability and interactivity. In fact, online games should provide a quick feedback of users' interactions as well as a coherent view of the shared world. However, the search for enhanced scalability dramatically increases message exchange. Such an increase consumes processing power and bandwidth, and thus limits interactivity, consistency, and scalability. To reduce the rate of message exchange, distributed virtual environment systems use filtering techniques such as interest management that filters messages according to users' interests in the world. These interests are influenced by perceptual facts which we study in this paper in order to build upon them a perception-based filtering technique. This technique satisfies users' needs by precisely providing an exact filtering which is more efficient than other techniques.

  6. The online data filters for Explorer and Nautilus

    International Nuclear Information System (INIS)

    D'Antonio, S

    2002-01-01

    The basic problem for gravitational wave detectors is to detect very small signals in the presence of noise which is often not Gaussian and not stationary. We cope with this problem by applying data filters, matched to short bursts, based on power spectra obtained online. We describe the new procedure adopted by the Rome group, where the signal-to-noise ratios obtained with various algorithms are compared and the best one is selected. The selected algorithm depends on the noise characteristics at that particular time

  7. Sensor Fusion Based on an Integrated Neural Network and Probability Density Function (PDF) Dual Kalman Filter for On-Line Estimation of Vehicle Parameters and States.

    Science.gov (United States)

    Vargas-Melendez, Leandro; Boada, Beatriz L; Boada, Maria Jesus L; Gauchia, Antonio; Diaz, Vicente

    2017-04-29

    Vehicles with a high center of gravity (COG), such as light trucks and heavy vehicles, are prone to rollover. This kind of accident causes nearly 33 % of all deaths from passenger vehicle crashes. Nowadays, these vehicles are incorporating roll stability control (RSC) systems to improve their safety. Most of the RSC systems require the vehicle roll angle as a known input variable to predict the lateral load transfer. The vehicle roll angle can be directly measured by a dual antenna global positioning system (GPS), but it is expensive. For this reason, it is important to estimate the vehicle roll angle from sensors installed onboard in current vehicles. On the other hand, the knowledge of the vehicle's parameters values is essential to obtain an accurate vehicle response. Some of vehicle parameters cannot be easily obtained and they can vary over time. In this paper, an algorithm for the simultaneous on-line estimation of vehicle's roll angle and parameters is proposed. This algorithm uses a probability density function (PDF)-based truncation method in combination with a dual Kalman filter (DKF), to guarantee that both vehicle's states and parameters are within bounds that have a physical meaning, using the information obtained from sensors mounted on vehicles. Experimental results show the effectiveness of the proposed algorithm.

  8. Information filtering in evolving online networks

    Science.gov (United States)

    Chen, Bo-Lun; Li, Fen-Fen; Zhang, Yong-Jun; Ma, Jia-Lin

    2018-02-01

    Recommender systems use the records of users' activities and profiles of both users and products to predict users' preferences in the future. Considerable works towards recommendation algorithms have been published to solve the problems such as accuracy, diversity, congestion, cold-start, novelty, coverage and so on. However, most of these research did not consider the temporal effects of the information included in the users' historical data. For example, the segmentation of the training set and test set was completely random, which was entirely different from the real scenario in recommender systems. More seriously, all the objects are treated as the same, regardless of the new, the popular or obsoleted products, so do the users. These data processing methods always lose useful information and mislead the understanding of the system's state. In this paper, we detailed analyzed the difference of the network structure between the traditional random division method and the temporal division method on two benchmark data sets, Netflix and MovieLens. Then three classical recommendation algorithms, Global Ranking method, Collaborative Filtering and Mass Diffusion method, were employed. The results show that all these algorithms became worse in all four key indicators, ranking score, precision, popularity and diversity, in the temporal scenario. Finally, we design a new recommendation algorithm based on both users' and objects' first appearance time in the system. Experimental results showed that the new algorithm can greatly improve the accuracy and other metrics.

  9. LHCb Online event processing and filtering

    CERN Document Server

    Alessio, F; Brarda, L; Frank, M; Franek, B; Galli, D; Gaspar, C; Van Herwijnen, E; Jacobsson, R; Jost, B; Köstner, S; Moine, G; Neufeld, N; Somogyi, P; Stoica, R; Suman, S

    2008-01-01

    The first level trigger of LHCb accepts one million events per second. After preprocessing in custom FPGA-based boards these events are distributed to a large farm of PC-servers using a high-speed Gigabit Ethernet network. Synchronisation and event management is achieved by the Timing and Trigger system of LHCb. Due to the complex nature of the selection of B-events, which are the main interest of LHCb, a full event-readout is required. Event processing on the servers is parallelised on an event basis. The reduction factor is typically 1/500. The remaining events are forwarded to a formatting layer, where the raw data files are formed and temporarily stored. A small part of the events is also forwarded to a dedicated farm for calibration and monitoring. The files are subsequently shipped to the CERN Tier0 facility for permanent storage and from there to the various Tier1 sites for reconstruction. In parallel files are used by various monitoring and calibration processes running within the LHCb Online system. ...

  10. Cluster Based Vector Attribute Filtering

    NARCIS (Netherlands)

    Kiwanuka, Fred N.; Wilkinson, Michael H.F.

    2016-01-01

    Morphological attribute filters operate on images based on properties or attributes of connected components. Until recently, attribute filtering was based on a single global threshold on a scalar property to remove or retain objects. A single threshold struggles in case no single property or

  11. An on-line estimation of battery pack parameters and state-of-charge using dual filters based on pack model

    International Nuclear Information System (INIS)

    Zhang, Xu; Wang, Yujie; Yang, Duo; Chen, Zonghai

    2016-01-01

    Accurate estimation of battery pack state-of-charge plays a very important role for electric vehicles, which directly reflects the behavior of battery pack usage. However, the inconsistency of battery makes the estimation of battery pack state-of-charge different from single cell. In this paper, to estimate the battery pack state-of-charge on-line, the definition of battery pack is proposed, and the relationship between the total available capacity of battery pack and single cell is put forward to analyze the energy efficiency influenced by battery inconsistency, then a lumped parameter battery model is built up to describe the dynamic behavior of battery pack. Furthermore, the extend Kalman filter-unscented Kalman filter algorithm is developed to identify the parameters of battery pack and forecast state-of-charge concurrently. The extend Kalman filter is applied to update the battery pack parameters by real-time measured data, while the unscented Kalman filter is employed to estimate the battery pack state-of-charge. Finally, the proposed approach is verified by experiments operated on the lithium-ion battery under constant current condition and the dynamic stress test profiles. Experimental results indicate that the proposed method can estimate the battery pack state-of-charge with high accuracy. - Highlights: • A novel space state equation is built to describe the pack dynamic behavior. • The dual filters method is used to estimate the pack state-of-charge. • Battery inconsistency is considered to analyze the pack usage efficiency. • The accuracy of the proposed method is verified under different conditions.

  12. Online analysis of five organic ultraviolet filters in environmental water samples using magnetism-enhanced monolith-based in-tube solid phase microextraction coupled with high-performance liquid chromatography.

    Science.gov (United States)

    Mei, Meng; Huang, Xiaojia

    2017-11-24

    Due to the endocrine disrupting properties, organic UV filters have been a great risk for humans and other organisms. Therefore, development of accurate and effective analytical methods is needed for the determination of UV filters in environmental waters. In this work, a fast, sensitive and environmentally friendly method combining magnetism-enhanced monolith-based in-tube solid phase microextraction with high-performance liquid chromatography with diode array detection (DAD) (ME-MB-IT/SPME-HPLC-DAD) for the online analysis of five organic UV filters in environmental water samples was developed. To extract UV filters effectively, an ionic liquid-based monolithic capillary column doped with magnetic nanoparticles was prepared by in-situ polymerization and used as extraction medium of online ME-MB-IT/SPME-HPLC-DAD system. Several extraction conditions including the intensity of magnetic field, sampling and desorption flow rate, volume of sample and desorption solvent, pH value and ionic strength of sample matrix were optimized thoroughly. Under the optimized conditions, the extraction efficiencies for five organic UV filters were in the range of 44.0-100%. The limits of detection (S/N=3) and limits of quantification (S/N=10) were 0.04-0.26μg/L and 0.12-0.87μg/L, respectively. The precisions indicated by relative standard deviations (RSDs) were less than 10% for both intra- and inter-day variabilities. Finally, the developed method was successfully applied to the determination of UV filters in three environmental water samples and satisfactory results were obtained. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Decentralized Social Filtering based on Trust

    OpenAIRE

    Olsson, Tomas

    1998-01-01

    This paper describes a decentralised approach to social filtering based on trust between agents in a multiagent system. The social filtering in the proposed approach is built on the interactions between collaborative software agents performing content-based filtering. This means that it uses a mixture of content-based and social filtering and thereby, it takes advantage of both methods.

  14. Implementation of a nonlinear filter for online nuclear counting

    International Nuclear Information System (INIS)

    Coulon, R.; Dumazert, J.; Kondrasovs, V.; Normand, S.

    2016-01-01

    Nuclear counting is a challenging task for nuclear instrumentation because of the stochastic nature of radioactivity. Event counting has to be processed and filtered to determine a stable count rate value and perform variation monitoring of the measured event. An innovative approach for nuclear counting is presented in this study, improving response time and maintaining count rate stability. Some nonlinear filters providing a local maximum likelihood estimation of the signal have been recently developed, which have been tested and compared with conventional linear filters. A nonlinear filter thus developed shows significant performance in terms of response time and measurement precision. The filter also presents the specificity of easy embedment into digital signal processor (DSP) electronics based on field-programmable gate arrays (FPGA) or microcontrollers, compatible with real-time requirements. © 2001 Elsevier Science. All rights reserved. - Highlights: • An efficient approach based on nonlinear filtering has been implemented. • The hypothesis test provides a local maximum likelihood estimation of the count rate. • The filter ensures an optimal compromise between precision and response time.

  15. The Atlas Experiment On-Line Monitoring And Filtering As An Example Of Real-Time Application

    Directory of Open Access Journals (Sweden)

    K. Korcyl

    2008-01-01

    Full Text Available The ATLAS detector, recording LHC particles’ interactions, produces events with rate of40 MHz and size of 1.6 MB. The processes with new and interesting physics phenomena arevery rare, thus an efficient on-line filtering system (trigger is necessary. The asynchronouspart of that system relays on few thousands of computing nodes running the filtering software.Applying refined filtering criteria results in increase of processing times what may lead tolack of processing resources installed on CERN site. We propose extension to this part ofthe system based on submission of the real-time filtering tasks into the Grid.

  16. Gradient based filtering of digital elevation models

    DEFF Research Database (Denmark)

    Knudsen, Thomas; Andersen, Rune Carbuhn

    We present a filtering method for digital terrain models (DTMs). The method is based on mathematical morphological filtering within gradient (slope) defined domains. The intention with the filtering procedure is to improbé the cartographic quality of height contours generated from a DTM based...

  17. Information Filtering Based on Users' Negative Opinions

    Science.gov (United States)

    Guo, Qiang; Li, Yang; Liu, Jian-Guo

    2013-05-01

    The process of heat conduction (HC) has recently found application in the information filtering [Zhang et al., Phys. Rev. Lett.99, 154301 (2007)], which is of high diversity but low accuracy. The classical HC model predicts users' potential interested objects based on their interesting objects regardless to the negative opinions. In terms of the users' rating scores, we present an improved user-based HC (UHC) information model by taking into account users' positive and negative opinions. Firstly, the objects rated by users are divided into positive and negative categories, then the predicted interesting and dislike object lists are generated by the UHC model. Finally, the recommendation lists are constructed by filtering out the dislike objects from the interesting lists. By implementing the new model based on nine similarity measures, the experimental results for MovieLens and Netflix datasets show that the new model considering negative opinions could greatly enhance the accuracy, measured by the average ranking score, from 0.049 to 0.036 for Netflix and from 0.1025 to 0.0570 for Movielens dataset, reduced by 26.53% and 44.39%, respectively. Since users prefer to give positive ratings rather than negative ones, the negative opinions contain much more information than the positive ones, the negative opinions, therefore, are very important for understanding users' online collective behaviors and improving the performance of HC model.

  18. Bayesian target tracking based on particle filter

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.

  19. Digital notch filter based active damping for LCL filters

    DEFF Research Database (Denmark)

    Yao, Wenli; Yang, Yongheng; Zhang, Xiaobin

    2015-01-01

    . In contrast, the active damping does not require any dissipation elements, and thus has become of increasing interest. As a result, a vast of active damping solutions have been reported, among which multi-loop control systems and additional sensors are necessary, leading to increased cost and complexity....... In this paper, a notch filter based active damping without the requirement of additional sensors is proposed, where the inverter current is employed as the feedback variable. Firstly, a design method of the notch filter for active damping is presented. The entire system stability has then been investigated...... in the z-domain. Simulations and experiments are carried out to verify the proposed active damping method. Both results have confirmed that the notch filter based active damping can ensure the entire system stability in the case of resonances with a good system performance....

  20. Linear Regression Based Real-Time Filtering

    Directory of Open Access Journals (Sweden)

    Misel Batmend

    2013-01-01

    Full Text Available This paper introduces real time filtering method based on linear least squares fitted line. Method can be used in case that a filtered signal is linear. This constraint narrows a band of potential applications. Advantage over Kalman filter is that it is computationally less expensive. The paper further deals with application of introduced method on filtering data used to evaluate a position of engraved material with respect to engraving machine. The filter was implemented to the CNC engraving machine control system. Experiments showing its performance are included.

  1. Online Reduction of Artifacts in EEG of Simultaneous EEG-fMRI Using Reference Layer Adaptive Filtering (RLAF).

    Science.gov (United States)

    Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R

    2018-01-01

    Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) allow us to study the active human brain from two perspectives concurrently. Signal processing based artifact reduction techniques are mandatory for this, however, to obtain reasonable EEG quality in simultaneous EEG-fMRI. Current artifact reduction techniques like average artifact subtraction (AAS), typically become less effective when artifact reduction has to be performed on-the-fly. We thus present and evaluate a new technique to improve EEG quality online. This technique adds up with online AAS and combines a prototype EEG-cap for reference recordings of artifacts, with online adaptive filtering and is named reference layer adaptive filtering (RLAF). We found online AAS + RLAF to be highly effective in improving EEG quality. Online AAS + RLAF outperformed online AAS and did so in particular online in terms of the chosen performance metrics, these being specifically alpha rhythm amplitude ratio between closed and opened eyes (3-45% improvement), signal-to-noise-ratio of visual evoked potentials (VEP) (25-63% improvement), and VEPs variability (16-44% improvement). Further, we found that EEG quality after online AAS + RLAF is occasionally even comparable with the offline variant of AAS at a 3T MRI scanner. In conclusion RLAF is a very effective add-on tool to enable high quality EEG in simultaneous EEG-fMRI experiments, even when online artifact reduction is necessary.

  2. Problem Based Learning Online

    DEFF Research Database (Denmark)

    Kolbæk, Ditte

    2018-01-01

    “How do two online learning designs affect student engagement in the PBL online modules?” The empirical data were collected and analyzed using a netnographic approach. The study finds that concepts such as self-directed learning and active involvement may be perceived very differently from the students...

  3. Flat microwave photonic filter based on hybrid of two filters

    International Nuclear Information System (INIS)

    Qi, Chunhui; Pei, Li; Ning, Tigang; Li, Jing; Gao, Song

    2010-01-01

    A new microwave photonic filter (MPF) hybrid of two filters that can realize both multiple taps and a flat bandpass or bandstop response is presented. Based on the phase character of a Mach–Zehnder modulator (MZM), a two taps finite impulse response (FIR) filter is obtained as the first part. The second part is obtained by taking full advantage of the wavelength selectivity of the fiber Bragg grating (FBG) and the gain of a erbium-doped fiber (EDF). Combining the two filters, the flat bandpass or bandstop response is realized by changing the coupler's factor k, the reflectivity of FBG1 R 1 or the gain of the EDF g. Optimizing the system parameters, a flat bandpass response with amplitude depth of more than 45 dB is obtained at k = 0.5, R 1 = 0.33, g = 10, and a flat bandstop response is also obtained at k = 0.4, R 1 = 0.5, g = 2. In addition, the free-spectral range (FSR) can be controlled by changing the length of the EDF and the length difference between two MZMs. The method is proved feasible by some experiments. Such a method offers realistic solutions to support future radio-frequency (RF) optical communication systems

  4. Using Collaborative Filtering to Support College Students' Use of Online Forum for English Learning

    Science.gov (United States)

    Wang, Pei-Yu; Yang, Hui-Chun

    2012-01-01

    This study examined the impact of collaborative filtering (the so-called recommender) on college students' use of an online forum for English learning. The forum was created with an open-source software, Drupal, and its extended recommender module. This study was guided by three main questions: 1) Is there any difference in online behaviors…

  5. Information Filtering via Heterogeneous Diffusion in Online Bipartite Networks.

    Science.gov (United States)

    Zhang, Fu-Guo; Zeng, An

    2015-01-01

    The rapid expansion of Internet brings us overwhelming online information, which is impossible for an individual to go through all of it. Therefore, recommender systems were created to help people dig through this abundance of information. In networks composed by users and objects, recommender algorithms based on diffusion have been proven to be one of the best performing methods. Previous works considered the diffusion process from user to object, and from object to user to be equivalent. We show in this work that it is not the case and we improve the quality of the recommendation by taking into account the asymmetrical nature of this process. We apply this idea to modify the state-of-the-art recommendation methods. The simulation results show that the new methods can outperform these existing methods in both recommendation accuracy and diversity. Finally, this modification is checked to be able to improve the recommendation in a realistic case.

  6. Online event filtering in the JADE data acquisition system

    International Nuclear Information System (INIS)

    Mills, H.E.

    1986-01-01

    The data acquisition system developed for the JADE experiment at PETRA, DESY includes the facility to use software to filter out background events. The design, implementation, testing and experience gained are discussed. (orig.)

  7. On-Line QRS Complex Detection Using Wavelet Filtering

    National Research Council Canada - National Science Library

    Szilagyi, L

    2001-01-01

    ...: first a wavelet transform filtering is applied to the signal, then QRS complex localization is performed using a maximum detection and peak classification algorithm The algorithm has been tested...

  8. Adaptive Rate Sampling and Filtering Based on Level Crossing Sampling

    Directory of Open Access Journals (Sweden)

    Saeed Mian Qaisar

    2009-01-01

    Full Text Available The recent sophistications in areas of mobile systems and sensor networks demand more and more processing resources. In order to maintain the system autonomy, energy saving is becoming one of the most difficult industrial challenges, in mobile computing. Most of efforts to achieve this goal are focused on improving the embedded systems design and the battery technology, but very few studies target to exploit the input signal time-varying nature. This paper aims to achieve power efficiency by intelligently adapting the processing activity to the input signal local characteristics. It is done by completely rethinking the processing chain, by adopting a non conventional sampling scheme and adaptive rate filtering. The proposed approach, based on the LCSS (Level Crossing Sampling Scheme presents two filtering techniques, able to adapt their sampling rate and filter order by online analyzing the input signal variations. Indeed, the principle is to intelligently exploit the signal local characteristics—which is usually never considered—to filter only the relevant signal parts, by employing the relevant order filters. This idea leads towards a drastic gain in the computational efficiency and hence in the processing power when compared to the classical techniques.

  9. Evidence-Based Evaluation of Inferior Vena Cava Filter Complications Based on Filter Type

    Science.gov (United States)

    Deso, Steven E.; Idakoji, Ibrahim A.; Kuo, William T.

    2016-01-01

    Many inferior vena cava (IVC) filter types, along with their specific risks and complications, are not recognized. The purpose of this study was to evaluate the various FDA-approved IVC filter types to determine device-specific risks, as a way to help identify patients who may benefit from ongoing follow-up versus prompt filter retrieval. An evidence-based electronic search (FDA Premarket Notification, MEDLINE, FDA MAUDE) was performed to identify all IVC filter types and device-specific complications from 1980 to 2014. Twenty-three IVC filter types (14 retrievable, 9 permanent) were identified. The devices were categorized as follows: conical (n = 14), conical with umbrella (n = 1), conical with cylindrical element (n = 2), biconical with cylindrical element (n = 2), helical (n = 1), spiral (n = 1), and complex (n = 1). Purely conical filters were associated with the highest reported risks of penetration (90–100%). Filters with cylindrical or umbrella elements were associated with the highest reported risk of IVC thrombosis (30–50%). Conical Bard filters were associated with the highest reported risks of fracture (40%). The various FDA-approved IVC filter types were evaluated for device-specific complications based on best current evidence. This information can be used to guide and optimize clinical management in patients with indwelling IVC filters. PMID:27247477

  10. Feature-Based Nonlocal Polarimetric SAR Filtering

    Directory of Open Access Journals (Sweden)

    Xiaoli Xing

    2017-10-01

    Full Text Available Polarimetric synthetic aperture radar (PolSAR images are inherently contaminated by multiplicative speckle noise, which complicates the image interpretation and image analyses. To reduce the speckle effect, several adaptive speckle filters have been developed based on the weighted average of the similarity measures commonly depending on the model or probability distribution, which are often affected by the distribution parameters and modeling texture components. In this paper, a novel filtering method introduces the coefficient of variance ( CV and Pauli basis (PB to measure the similarity, and the two features are combined with the framework of the nonlocal mean filtering. The CV is used to describe the complexity of various scenes and distinguish the scene heterogeneity; moreover, the Pauli basis is able to express the polarimetric information in PolSAR image processing. This proposed filtering combines the CV and Pauli basis to improve the estimation accuracy of the similarity weights. Then, the similarity of the features is deduced according to the test statistic. Subsequently, the filtering is proceeded by using the nonlocal weighted estimation. The performance of the proposed filter is tested with the simulated images and real PolSAR images, which are acquired by AIRSAR system and ESAR system. The qualitative and quantitative experiments indicate the validity of the proposed method by comparing with the widely-used despeckling methods.

  11. Internet filters and entry pages do not protect children from online alcohol marketing.

    Science.gov (United States)

    Jones, Sandra C; Thom, Jeffrey A; Davoren, Sondra; Barrie, Lance

    2014-02-01

    We review programs and policies to prevent children from accessing alcohol marketing online. To update the literature, we present our recent studies that assess (i) in-built barriers to underage access to alcohol brand websites and (ii) commercial internet filters. Alcohol websites typically had poor filter systems for preventing entry of underage persons; only half of the sites required the user to provide a date of birth, and none had any means of preventing users from trying again. Even the most effective commercial internet filters allowed access to one-third of the sites we examined.

  12. Group recommendation strategies based on collaborative filtering

    OpenAIRE

    Ricardo de Melo Queiroz, Sérgio

    2003-01-01

    Ricardo de Melo Queiroz, Sérgio; de Assis Tenório Carvalho, Francisco. Group recommendation strategies based on collaborative filtering. 2003. Dissertação (Mestrado). Programa de Pós-Graduação em Ciência da Computação, Universidade Federal de Pernambuco, Recife, 2003.

  13. Low power adder based auditory filter architecture.

    Science.gov (United States)

    Rahiman, P F Khaleelur; Jayanthi, V S

    2014-01-01

    Cochlea devices are powered up with the help of batteries and they should possess long working life to avoid replacing of devices at regular interval of years. Hence the devices with low power consumptions are required. In cochlea devices there are numerous filters, each responsible for frequency variant signals, which helps in identifying speech signals of different audible range. In this paper, multiplierless lookup table (LUT) based auditory filter is implemented. Power aware adder architectures are utilized to add the output samples of the LUT, available at every clock cycle. The design is developed and modeled using Verilog HDL, simulated using Mentor Graphics Model-Sim Simulator, and synthesized using Synopsys Design Compiler tool. The design was mapped to TSMC 65 nm technological node. The standard ASIC design methodology has been adapted to carry out the power analysis. The proposed FIR filter architecture has reduced the leakage power by 15% and increased its performance by 2.76%.

  14. Low Power Adder Based Auditory Filter Architecture

    Directory of Open Access Journals (Sweden)

    P. F. Khaleelur Rahiman

    2014-01-01

    Full Text Available Cochlea devices are powered up with the help of batteries and they should possess long working life to avoid replacing of devices at regular interval of years. Hence the devices with low power consumptions are required. In cochlea devices there are numerous filters, each responsible for frequency variant signals, which helps in identifying speech signals of different audible range. In this paper, multiplierless lookup table (LUT based auditory filter is implemented. Power aware adder architectures are utilized to add the output samples of the LUT, available at every clock cycle. The design is developed and modeled using Verilog HDL, simulated using Mentor Graphics Model-Sim Simulator, and synthesized using Synopsys Design Compiler tool. The design was mapped to TSMC 65 nm technological node. The standard ASIC design methodology has been adapted to carry out the power analysis. The proposed FIR filter architecture has reduced the leakage power by 15% and increased its performance by 2.76%.

  15. Human tracking in thermal images using adaptive particle filters with online random forest learning

    Science.gov (United States)

    Ko, Byoung Chul; Kwak, Joon-Young; Nam, Jae-Yeal

    2013-11-01

    This paper presents a fast and robust human tracking method to use in a moving long-wave infrared thermal camera under poor illumination with the existence of shadows and cluttered backgrounds. To improve the human tracking performance while minimizing the computation time, this study proposes an online learning of classifiers based on particle filters and combination of a local intensity distribution (LID) with oriented center-symmetric local binary patterns (OCS-LBP). Specifically, we design a real-time random forest (RF), which is the ensemble of decision trees for confidence estimation, and confidences of the RF are converted into a likelihood function of the target state. First, the target model is selected by the user and particles are sampled. Then, RFs are generated using the positive and negative examples with LID and OCS-LBP features by online learning. The learned RF classifiers are used to detect the most likely target position in the subsequent frame in the next stage. Then, the RFs are learned again by means of fast retraining with the tracked object and background appearance in the new frame. The proposed algorithm is successfully applied to various thermal videos as tests and its tracking performance is better than those of other methods.

  16. Technical Note: A fast online adaptive replanning method for VMAT using flattening filter free beams

    Energy Technology Data Exchange (ETDEWEB)

    Ates, Ozgur; Ahunbay, Ergun E.; Li, X. Allen, E-mail: ali@mcw.edu [Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226 (United States); Moreau, Michel [Elekta, Inc., Maryland Heights, Missouri 63043 (United States)

    2016-06-15

    Purpose: To develop a fast replanning algorithm based on segment aperture morphing (SAM) for online replanning of volumetric modulated arc therapy (VMAT) with flattening filter free (FFF) beams. Methods: A software tool was developed to interface with a VMAT research planning system, which enables the input and output of beam and machine parameters of VMAT plans. The SAM algorithm was used to modify multileaf collimator positions for each segment aperture based on the changes of the target from the planning (CT/MR) to daily image [CT/CBCT/magnetic resonance imaging (MRI)]. The leaf travel distance was controlled for large shifts to prevent the increase of VMAT delivery time. The SAM algorithm was tested for 11 patient cases including prostate, pancreatic, and lung cancers. For each daily image set, three types of VMAT plans, image-guided radiation therapy (IGRT) repositioning, SAM adaptive, and full-scope reoptimization plans, were generated and compared. Results: The SAM adaptive plans were found to have improved the plan quality in target and/or critical organs when compared to the IGRT repositioning plans and were comparable to the reoptimization plans based on the data of planning target volume (PTV)-V100 (volume covered by 100% of prescription dose). For the cases studied, the average PTV-V100 was 98.85% ± 1.13%, 97.61% ± 1.45%, and 92.84% ± 1.61% with FFF beams for the reoptimization, SAM adaptive, and repositioning plans, respectively. The execution of the SAM algorithm takes less than 10 s using 16-CPU (2.6 GHz dual core) hardware. Conclusions: The SAM algorithm can generate adaptive VMAT plans using FFF beams with comparable plan qualities as those from the full-scope reoptimization plans based on daily CT/CBCT/MRI and can be used for online replanning to address interfractional variations.

  17. Kernel-based noise filtering of neutron detector signals

    International Nuclear Information System (INIS)

    Park, Moon Ghu; Shin, Ho Cheol; Lee, Eun Ki

    2007-01-01

    This paper describes recently developed techniques for effective filtering of neutron detector signal noise. In this paper, three kinds of noise filters are proposed and their performance is demonstrated for the estimation of reactivity. The tested filters are based on the unilateral kernel filter, unilateral kernel filter with adaptive bandwidth and bilateral filter to show their effectiveness in edge preservation. Filtering performance is compared with conventional low-pass and wavelet filters. The bilateral filter shows a remarkable improvement compared with unilateral kernel and wavelet filters. The effectiveness and simplicity of the unilateral kernel filter with adaptive bandwidth is also demonstrated by applying it to the reactivity measurement performed during reactor start-up physics tests

  18. A family of quantization based piecewise linear filter networks

    DEFF Research Database (Denmark)

    Sørensen, John Aasted

    1992-01-01

    A family of quantization-based piecewise linear filter networks is proposed. For stationary signals, a filter network from this family is a generalization of the classical Wiener filter with an input signal and a desired response. The construction of the filter network is based on quantization...... of the input signal x(n) into quantization classes. With each quantization class is associated a linear filter. The filtering at time n is carried out by the filter belonging to the actual quantization class of x(n ) and the filters belonging to the neighbor quantization classes of x(n) (regularization......). This construction leads to a three-layer filter network. The first layer consists of the quantization class filters for the input signal. The second layer carries out the regularization between neighbor quantization classes, and the third layer constitutes a decision of quantization class from where the resulting...

  19. Improved Kalman Filter-Based Speech Enhancement with Perceptual Post-Filtering

    Institute of Scientific and Technical Information of China (English)

    WEIJianqiang; DULimin; YANZhaoli; ZENGHui

    2004-01-01

    In this paper, a Kalman filter-based speech enhancement algorithm with some improvements of previous work is presented. A new technique based on spectral subtraction is used for separation speech and noise characteristics from noisy speech and for the computation of speech and noise Autoregressive (AR) parameters. In order to obtain a Kalman filter output with high audible quality, a perceptual post-filter is placed at the output of the Kalman filter to smooth the enhanced speech spectra.Extensive experiments indicate that this newly proposed method works well.

  20. Design, control, and implementation of LCL-filter-based shunt active power filters

    DEFF Research Database (Denmark)

    Tang, Yi; Loh, Poh Chiang; Wang, Peng

    2011-01-01

    This paper concentrates on the design, control and implementation of an LCL-filter-based shunt active power filter (SAPF), which can effectively compensate harmonic currents produced by nonlinear loads in a three-phase three-wire power system. The use of LCL-filter at the output end of SAPF offer......-loop control system, and active damping implemented with fewer current sensors are all addressed here. An analytical design example is finally presented, being supported with experimental results, to verify its effectiveness and practicality.......This paper concentrates on the design, control and implementation of an LCL-filter-based shunt active power filter (SAPF), which can effectively compensate harmonic currents produced by nonlinear loads in a three-phase three-wire power system. The use of LCL-filter at the output end of SAPF offers...

  1. Independent component analysis based filtering for penumbral imaging

    International Nuclear Information System (INIS)

    Chen Yenwei; Han Xianhua; Nozaki, Shinya

    2004-01-01

    We propose a filtering based on independent component analysis (ICA) for Poisson noise reduction. In the proposed filtering, the image is first transformed to ICA domain and then the noise components are removed by a soft thresholding (shrinkage). The proposed filter, which is used as a preprocessing of the reconstruction, has been successfully applied to penumbral imaging. Both simulation results and experimental results show that the reconstructed image is dramatically improved in comparison to that without the noise-removing filters

  2. Measurement-based local quantum filters and their ability to ...

    Indian Academy of Sciences (India)

    Debmalya Das

    Berhampur (Transit Campus), National Highway 59, Berhampur 760 010, India. ∗. Corresponding author. E-mail: arvind@iisermohali.ac.in. MS received 29 July 2016; revised 21 October 2016; accepted 16 December 2016; published online 30 May 2017. Abstract. We introduce local filters as a means to detect the ...

  3. An Ensemble of Neural Networks for Online Electron Filtering at the ATLAS Experiment.

    CERN Document Server

    Da Fonseca Pinto, Joao Victor; The ATLAS collaboration

    2018-01-01

    In 2017 the ATLAS experiment implemented an ensemble of neural networks (NeuralRinger algorithm) dedicated to improving the performance of filtering events containing electrons in the high-input rate online environment of the Large Hadron Collider at CERN, Geneva. The ensemble employs a concept of calorimetry rings. The training procedure and final structure of the ensemble are used to minimize fluctuations from detector response, according to the particle energy and position of incidence. A detailed study was carried out to assess profile distortions in crucial offline quantities through the usage of statistical tests and residual analysis. These details and the online performance of this algorithm during the 2017 data-taking will be presented.

  4. A Digital Image Denoising Algorithm Based on Gaussian Filtering and Bilateral Filtering

    Directory of Open Access Journals (Sweden)

    Piao Weiying

    2018-01-01

    Full Text Available Bilateral filtering has been applied in the area of digital image processing widely, but in the high gradient region of the image, bilateral filtering may generate staircase effect. Bilateral filtering can be regarded as one particular form of local mode filtering, according to above analysis, an mixed image de-noising algorithm is proposed based on Gaussian filter and bilateral filtering. First of all, it uses Gaussian filter to filtrate the noise image and get the reference image, then to take both the reference image and noise image as the input for range kernel function of bilateral filter. The reference image can provide the image’s low frequency information, and noise image can provide image’s high frequency information. Through the competitive experiment on both the method in this paper and traditional bilateral filtering, the experimental result showed that the mixed de-noising algorithm can effectively overcome staircase effect, and the filtrated image was more smooth, its textural features was also more close to the original image, and it can achieve higher PSNR value, but the amount of calculation of above two algorithms are basically the same.

  5. Ensemble-based Kalman Filters in Strongly Nonlinear Dynamics

    Institute of Scientific and Technical Information of China (English)

    Zhaoxia PU; Joshua HACKER

    2009-01-01

    This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that occurs when the model jumps from one basin of attraction to the other. Four configurations of the ensemble-based Kalman filtering data assimilation techniques, including the ensemble Kalman filter, ensemble adjustment Kalman filter, ensemble square root filter and ensemble transform Kalman filter, are evaluated with their ability in predicting the regime transition (also called phase transition) and also are compared in terms of their sensitivity to both observational and sampling errors. The sensitivity of each ensemble-based filter to the size of the ensemble is also examined.

  6. Kalman filter-based gap conductance modeling

    International Nuclear Information System (INIS)

    Tylee, J.L.

    1983-01-01

    Geometric and thermal property uncertainties contribute greatly to the problem of determining conductance within the fuel-clad gas gap of a nuclear fuel pin. Accurate conductance values are needed for power plant licensing transient analysis and for test analyses at research facilities. Recent work by Meek, Doerner, and Adams has shown that use of Kalman filters to estimate gap conductance is a promising approach. A Kalman filter is simply a mathematical algorithm that employs available system measurements and assumed dynamic models to generate optimal system state vector estimates. This summary addresses another Kalman filter approach to gap conductance estimation and subsequent identification of an empirical conductance model

  7. Optimization-based particle filter for state and parameter estimation

    Institute of Scientific and Technical Information of China (English)

    Li Fu; Qi Fei; Shi Guangming; Zhang Li

    2009-01-01

    In recent years, the theory of particle filter has been developed and widely used for state and parameter estimation in nonlinear/non-Gaussian systems. Choosing good importance density is a critical issue in particle filter design. In order to improve the approximation of posterior distribution, this paper provides an optimization-based algorithm (the steepest descent method) to generate the proposal distribution and then sample particles from the distribution. This algorithm is applied in 1-D case, and the simulation results show that the proposed particle filter performs better than the extended Kalman filter (EKF), the standard particle filter (PF), the extended Kalman particle filter (PF-EKF) and the unscented particle filter (UPF) both in efficiency and in estimation precision.

  8. Compact Spectrometers Based on Linear Variable Filters

    Data.gov (United States)

    National Aeronautics and Space Administration — Demonstrate a linear-variable spectrometer with an H2RG array. Linear Variable Filter (LVF) spectrometers provide attractive resource benefits – high optical...

  9. Gabor filter based fingerprint image enhancement

    Science.gov (United States)

    Wang, Jin-Xiang

    2013-03-01

    Fingerprint recognition technology has become the most reliable biometric technology due to its uniqueness and invariance, which has been most convenient and most reliable technique for personal authentication. The development of Automated Fingerprint Identification System is an urgent need for modern information security. Meanwhile, fingerprint preprocessing algorithm of fingerprint recognition technology has played an important part in Automatic Fingerprint Identification System. This article introduces the general steps in the fingerprint recognition technology, namely the image input, preprocessing, feature recognition, and fingerprint image enhancement. As the key to fingerprint identification technology, fingerprint image enhancement affects the accuracy of the system. It focuses on the characteristics of the fingerprint image, Gabor filters algorithm for fingerprint image enhancement, the theoretical basis of Gabor filters, and demonstration of the filter. The enhancement algorithm for fingerprint image is in the windows XP platform with matlab.65 as a development tool for the demonstration. The result shows that the Gabor filter is effective in fingerprint image enhancement technology.

  10. Efficient Online Learning Algorithms Based on LSTM Neural Networks.

    Science.gov (United States)

    Ergen, Tolga; Kozat, Suleyman Serdar

    2017-09-13

    We investigate online nonlinear regression and introduce novel regression structures based on the long short term memory (LSTM) networks. For the introduced structures, we also provide highly efficient and effective online training methods. To train these novel LSTM-based structures, we put the underlying architecture in a state space form and introduce highly efficient and effective particle filtering (PF)-based updates. We also provide stochastic gradient descent and extended Kalman filter-based updates. Our PF-based training method guarantees convergence to the optimal parameter estimation in the mean square error sense provided that we have a sufficient number of particles and satisfy certain technical conditions. More importantly, we achieve this performance with a computational complexity in the order of the first-order gradient-based methods by controlling the number of particles. Since our approach is generic, we also introduce a gated recurrent unit (GRU)-based approach by directly replacing the LSTM architecture with the GRU architecture, where we demonstrate the superiority of our LSTM-based approach in the sequential prediction task via different real life data sets. In addition, the experimental results illustrate significant performance improvements achieved by the introduced algorithms with respect to the conventional methods over several different benchmark real life data sets.

  11. Filtered backprojection algorithm in RPCs based PET

    International Nuclear Information System (INIS)

    Cruceru, Ilie; Manea Ioana; Nicorescu, Carmen; Constantin Florin

    2003-01-01

    The basis of PET consists in administration of a radioactive isotope attached to a tracer that permits to reveal its molecular pathways in the human body. A 3-D Whole-Body-Scan is necessary in order to minimize the radiation exposure of the patient and to increase significantly the axial field of view (FOV). A major candidate for gamma pair detection in 3-D Whole-Body-Scan appear to be the RPCs (Resistive Plate Counters). They consist in a longitudinal microstrip grid 15 mm thick, spaced at 1 mm; the grid is placed between a large electric resistive glass anode (ρ = 10 12 Ωcm) and an aluminium cathode; the gap of around 300 μm is filled with a special gas and is polarized at around 6 kV. Several detecting structures based on Resistive Plate Counters (RPCs) are evaluated for use in a positron emission 3-Dimensional Whole-Body-Scan tomograph. The coincidence matrix is built for the specific detecting structure by means of random gamma pair ray generation and then the filtered backprojection algorithm is used to reconstruct the original picture. The accuracy of image reconstruction is examined for the four different detecting structures. (authors)

  12. The effect of heterogeneous dynamics of online users on information filtering

    International Nuclear Information System (INIS)

    Chen, Bo-Lun; Zeng, An; Chen, Ling

    2015-01-01

    The rapid expansion of the Internet requires effective information filtering techniques to extract the most essential and relevant information for online users. Many recommendation algorithms have been proposed to predict the future items that a given user might be interested in. However, there is an important issue that has always been ignored so far in related works, namely the heterogeneous dynamics of online users. The interest of active users changes more often than that of less active users, which asks for different update frequency of their recommendation lists. In this paper, we develop a framework to study the effect of heterogeneous dynamics of users on the recommendation performance. We find that the personalized application of recommendation algorithms results in remarkable improvement in the recommendation accuracy and diversity. Our findings may help online retailers make better use of the existing recommendation methods. - Highlights: • We study the effect of heterogeneous dynamics of users on recommendation. • Due to the user heterogeneity, their amount of links in the probe set is different. • The personalized algorithm implementation improves the recommendation performance. • Our results suggest different update frequency for users – recommendation list.

  13. The effect of heterogeneous dynamics of online users on information filtering

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Bo-Lun [Department of Computer Science, Yangzhou University of China, Yangzhou 225127 (China); Department of Computer Science, Nanjing University of Aeronautics and Astronautics of China, Nanjing 210016 (China); Department of Physics, University of Fribourg, Chemin du Musee 3, CH-1700 Fribourg (Switzerland); Zeng, An, E-mail: anzeng@bnu.edu.cn [School of Systems Science, Beijing Normal University, Beijing 100875 (China); Chen, Ling [Department of Computer Science, Yangzhou University of China, Yangzhou 225127 (China); Department of Computer Science, Nanjing University of Aeronautics and Astronautics of China, Nanjing 210016 (China)

    2015-11-06

    The rapid expansion of the Internet requires effective information filtering techniques to extract the most essential and relevant information for online users. Many recommendation algorithms have been proposed to predict the future items that a given user might be interested in. However, there is an important issue that has always been ignored so far in related works, namely the heterogeneous dynamics of online users. The interest of active users changes more often than that of less active users, which asks for different update frequency of their recommendation lists. In this paper, we develop a framework to study the effect of heterogeneous dynamics of users on the recommendation performance. We find that the personalized application of recommendation algorithms results in remarkable improvement in the recommendation accuracy and diversity. Our findings may help online retailers make better use of the existing recommendation methods. - Highlights: • We study the effect of heterogeneous dynamics of users on recommendation. • Due to the user heterogeneity, their amount of links in the probe set is different. • The personalized algorithm implementation improves the recommendation performance. • Our results suggest different update frequency for users – recommendation list.

  14. Avoiding the Use of Exhausted Drinking Water Filters: A Filter-Clock Based on Rusting Iron

    Directory of Open Access Journals (Sweden)

    Arnaud Igor Ndé-Tchoupé

    2018-05-01

    Full Text Available Efficient but affordable water treatment technologies are currently sought to solve the prevalent shortage of safe drinking water. Adsorption-based technologies are in the front-line of these efforts. Upon proper design, universally applied materials (e.g., activated carbons, bone chars, metal oxides are able to quantitatively remove inorganic and organic pollutants as well as pathogens from water. Each water filter has a defined removal capacity and must be replaced when this capacity is exhausted. Operational experience has shown that it may be difficult to convince some low-skilled users to buy new filters after a predicted service life. This communication describes the quest to develop a filter-clock to encourage all users to change their filters after the designed service life. A brief discussion on such a filter-clock based on rusting of metallic iron (Fe0 is presented. Integrating such filter-clocks in the design of water filters is regarded as essential for safeguarding public health.

  15. SU-E-J-127: Implementation of An Online Replanning Tool for VMAT Using Flattening Filter-Free Beams

    Energy Technology Data Exchange (ETDEWEB)

    Ates, O; Ahunbay, E; Li, X [Medical College of Wisconsin, Milwaukee, WI (United States)

    2015-06-15

    Purpose: This is to report the implementation of an online replanning tool based on segment aperture morphing (SAM) for VMAT with flattening filter free (FFF) beams. Methods: Previously reported SAM algorithm modified to accommodate VMAT with FFF beams was implemented in a tool that was interfaced with a treatment planning system (Monaco, Elekta). The tool allows (1) to output the beam parameters of the original VMAT plan from Monaco, and (2) to input the apertures generated from the SAM algorithm into Monaco for the dose calculation on daily CT/CBCT/MRI in the following steps:(1) Quickly generating target contour based on the image of the day, using an auto-segmentation tool (ADMIRE, Elekta) with manual editing if necessary; (2) Morphing apertures based on the SAM in the original VMAT plan to account for the interfractional change of the target from the planning to the daily images; (3) Calculating dose distribution for new apertures with the same numbers of MU as in the original plan; (4) Transferring the new plan into a record & verify system (MOSAIQ, Elekta); (5) Performing a pre-delivery QA based on software; (6) Delivering the adaptive plan for the fraction.This workflow was implemented on a 16-CPU (2.6 GHz dual-core) hardware with GPU and was tested for sample cases of prostate, pancreas and lung tumors. Results: The online replanning process can be completed within 10 minutes. The adaptive plans generally have improved the plan quality when compared to the IGRT repositioning plans. The adaptive plans with FFF beams have better normal tissue sparing as compared with those of FF beams. Conclusion: The online replanning tool based on SAM can quickly generate adaptive VMAT plans using FFF beams with improved plan quality than those from the IGRT repositioning plans based on daily CT/CBCT/MRI and can be used clinically. This research was supported by Elekta Inc. (Crawley, UK)

  16. SU-E-J-127: Implementation of An Online Replanning Tool for VMAT Using Flattening Filter-Free Beams

    International Nuclear Information System (INIS)

    Ates, O; Ahunbay, E; Li, X

    2015-01-01

    Purpose: This is to report the implementation of an online replanning tool based on segment aperture morphing (SAM) for VMAT with flattening filter free (FFF) beams. Methods: Previously reported SAM algorithm modified to accommodate VMAT with FFF beams was implemented in a tool that was interfaced with a treatment planning system (Monaco, Elekta). The tool allows (1) to output the beam parameters of the original VMAT plan from Monaco, and (2) to input the apertures generated from the SAM algorithm into Monaco for the dose calculation on daily CT/CBCT/MRI in the following steps:(1) Quickly generating target contour based on the image of the day, using an auto-segmentation tool (ADMIRE, Elekta) with manual editing if necessary; (2) Morphing apertures based on the SAM in the original VMAT plan to account for the interfractional change of the target from the planning to the daily images; (3) Calculating dose distribution for new apertures with the same numbers of MU as in the original plan; (4) Transferring the new plan into a record & verify system (MOSAIQ, Elekta); (5) Performing a pre-delivery QA based on software; (6) Delivering the adaptive plan for the fraction.This workflow was implemented on a 16-CPU (2.6 GHz dual-core) hardware with GPU and was tested for sample cases of prostate, pancreas and lung tumors. Results: The online replanning process can be completed within 10 minutes. The adaptive plans generally have improved the plan quality when compared to the IGRT repositioning plans. The adaptive plans with FFF beams have better normal tissue sparing as compared with those of FF beams. Conclusion: The online replanning tool based on SAM can quickly generate adaptive VMAT plans using FFF beams with improved plan quality than those from the IGRT repositioning plans based on daily CT/CBCT/MRI and can be used clinically. This research was supported by Elekta Inc. (Crawley, UK)

  17. Low Power Systolic Array Based Digital Filter for DSP Applications

    Directory of Open Access Journals (Sweden)

    S. Karthick

    2015-01-01

    Full Text Available Main concepts in DSP include filtering, averaging, modulating, and correlating the signals in digital form to estimate characteristic parameter of a signal into a desirable form. This paper presents a brief concept of low power datapath impact for Digital Signal Processing (DSP based biomedical application. Systolic array based digital filter used in signal processing of electrocardiogram analysis is presented with datapath architectural innovations in low power consumption perspective. Implementation was done with ASIC design methodology using TSMC 65 nm technological library node. The proposed systolic array filter has reduced leakage power up to 8.5% than the existing filter architectures.

  18. Michelson interferometer based interleaver design using classic IIR filter decomposition.

    Science.gov (United States)

    Cheng, Chi-Hao; Tang, Shasha

    2013-12-16

    An elegant method to design a Michelson interferometer based interleaver using a classic infinite impulse response (IIR) filter such as Butterworth, Chebyshev, and elliptic filters as a starting point are presented. The proposed design method allows engineers to design a Michelson interferometer based interleaver from specifications seamlessly. Simulation results are presented to demonstrate the validity of the proposed design method.

  19. Vehicle Sideslip Angle Estimation Based on Hybrid Kalman Filter

    Directory of Open Access Journals (Sweden)

    Jing Li

    2016-01-01

    Full Text Available Vehicle sideslip angle is essential for active safety control systems. This paper presents a new hybrid Kalman filter to estimate vehicle sideslip angle based on the 3-DoF nonlinear vehicle dynamic model combined with Magic Formula tire model. The hybrid Kalman filter is realized by combining square-root cubature Kalman filter (SCKF, which has quick convergence and numerical stability, with square-root cubature based receding horizon Kalman FIR filter (SCRHKF, which has robustness against model uncertainty and temporary noise. Moreover, SCKF and SCRHKF work in parallel, and the estimation outputs of two filters are merged by interacting multiple model (IMM approach. Experimental results show the accuracy and robustness of the hybrid Kalman filter.

  20. Wiener discrete cosine transform-based image filtering

    Science.gov (United States)

    Pogrebnyak, Oleksiy; Lukin, Vladimir V.

    2012-10-01

    A classical problem of additive white (spatially uncorrelated) Gaussian noise suppression in grayscale images is considered. The main attention is paid to discrete cosine transform (DCT)-based denoising, in particular, to image processing in blocks of a limited size. The efficiency of DCT-based image filtering with hard thresholding is studied for different sizes of overlapped blocks. A multiscale approach that aggregates the outputs of DCT filters having different overlapped block sizes is proposed. Later, a two-stage denoising procedure that presumes the use of the multiscale DCT-based filtering with hard thresholding at the first stage and a multiscale Wiener DCT-based filtering at the second stage is proposed and tested. The efficiency of the proposed multiscale DCT-based filtering is compared to the state-of-the-art block-matching and three-dimensional filter. Next, the potentially reachable multiscale filtering efficiency in terms of output mean square error (MSE) is studied. The obtained results are of the same order as those obtained by Chatterjee's approach based on nonlocal patch processing. It is shown that the ideal Wiener DCT-based filter potential is usually higher when noise variance is high.

  1. Biogas Filter Based on Local Natural Zeolite Materials

    OpenAIRE

    Krido Wahono, Satriyo; Anggo Rizal, Wahyu

    2014-01-01

    UPT BPPTK LIPI has created a biogas filter tool to improve the purity of methane in the biogas. The device shaped cylindrical tube containing absorbent materials which based on local natural zeolite of Indonesia. The absorbent has been activated and modified with other materials. This absorbtion material has multi-adsorption capacity for almost impurities gas of biogas. The biogas  filter increase methane content of biogas for 5-20%. The biogas filter improve the biogas’s performance such as ...

  2. Reactor - and accelerator-based filtered beams

    International Nuclear Information System (INIS)

    Mill, A.J.; Harvey, J.R.

    1980-01-01

    The neutrons produced in high flux nuclear reactors and in accelerator, induced fission and spallation reactions, represent the most intense sources of neutrons available for research. However, the neutrons from these sources are not monoenergetic, covering the broad range extending from 10 -3 eV up to 10 7 eV or so. In order to make quantitative measurements of the effects of neutrons and their dependence on neutron energy it is desirable to have mono-energetic neutron sources. The paper describes briefly methods of obtaining mono-energetic neutrons and different methods of filtration. This is followed by more detailed discussion of neutron window filters and a summary of the filtered beam facilities using this technique. The review concludes with a discussion of the main applications of filtered beams and their present and future importance

  3. Laser-induced breakdown spectroscopy in gases using ungated detection in combination with polarization filtering and online background correction

    International Nuclear Information System (INIS)

    Kiefer, J; Tröger, J W; Seeger, T; Leipertz, A; Li, B; Li, Z S; Aldén, M

    2010-01-01

    Quantitative and fast analysis of gas mixtures is an important task in the field of chemical, security and environmental analysis. In this paper we present a diagnostic approach based on laser-induced breakdown spectroscopy (LIBS). A polarization filter in the signal collection system enables sufficient suppression of elastically scattered light which otherwise reduces the dynamic range of the measurement. Running the detector with a doubled repetition rate as compared to the laser online background correction is obtained. Quantitative measurements of molecular air components in synthetic, ambient and expiration air are performed and demonstrate the potential of the method. The detection limits for elemental oxygen and hydrogen are in the order of 15 ppm and 10 ppm, respectively

  4. Variable flexure-based fluid filter

    Science.gov (United States)

    Brown, Steve B.; Colston, Jr., Billy W.; Marshall, Graham; Wolcott, Duane

    2007-03-13

    An apparatus and method for filtering particles from a fluid comprises a fluid inlet, a fluid outlet, a variable size passage between the fluid inlet and the fluid outlet, and means for adjusting the size of the variable size passage for filtering the particles from the fluid. An inlet fluid flow stream is introduced to a fixture with a variable size passage. The size of the variable size passage is set so that the fluid passes through the variable size passage but the particles do not pass through the variable size passage.

  5. Graphene-based tunable terahertz filter with rectangular ring ...

    Indian Academy of Sciences (India)

    A plasmonic band-pass filter based on graphene rectangular ring resonator with double narrow gaps is proposed and numerically investigated by finite-difference time-domain (FDTD) simulations. For the filter with or without gaps, the resonant frequencies can be effectively adjusted by changing the width of the graphene ...

  6. 3D Wavelet-Based Filter and Method

    Science.gov (United States)

    Moss, William C.; Haase, Sebastian; Sedat, John W.

    2008-08-12

    A 3D wavelet-based filter for visualizing and locating structural features of a user-specified linear size in 2D or 3D image data. The only input parameter is a characteristic linear size of the feature of interest, and the filter output contains only those regions that are correlated with the characteristic size, thus denoising the image.

  7. Graphene-based tunable terahertz filter with rectangular ring ...

    Indian Academy of Sciences (India)

    WEI SU

    2017-08-16

    Aug 16, 2017 ... Abstract. A plasmonic band-pass filter based on graphene rectangular ring resonator with double narrow gaps is proposed and numerically investigated by finite-difference time-domain (FDTD) simulations. For the filter with or without gaps, the resonant frequencies can be effectively adjusted by changing ...

  8. Particle filter based MAP state estimation: A comparison

    NARCIS (Netherlands)

    Saha, S.; Boers, Y.; Driessen, J.N.; Mandal, Pranab K.; Bagchi, Arunabha

    2009-01-01

    MAP estimation is a good alternative to MMSE for certain applications involving nonlinear non Gaussian systems. Recently a new particle filter based MAP estimator has been derived. This new method extracts the MAP directly from the output of a running particle filter. In the recent past, a Viterbi

  9. Particle filtering based structural assessment with acoustic emission sensing

    Science.gov (United States)

    Yan, Wuzhao; Abdelrahman, Marwa; Zhang, Bin; Ziehl, Paul

    2017-02-01

    Nuclear structures are designed to withstand severe loading events under various stresses. Over time, aging of structural systems constructed with concrete and steel will occur. This deterioration may reduce service life of nuclear facilities and/or lead to unnecessary or untimely repairs. Therefore, online monitoring of structures in nuclear power plants and waste storage has drawn significant attention in recent years. Of many existing non-destructive evaluation and structural monitoring approaches, acoustic emission is promising for assessment of structural damage because it is non-intrusive and is sensitive to corrosion and crack growth in reinforced concrete elements. To provide a rapid, actionable, and graphical means for interpretation Intensity Analysis plots have been developed. This approach provides a means for classification of damage. Since the acoustic emission measurement is only an indirect indicator of structural damage, potentially corrupted by non-genuine data, it is more suitable to estimate the states of corrosion and cracking in a Bayesian estimation framework. In this paper, we will utilize the accelerated corrosion data from a specimen at the University of South Carolina to develop a particle filtering-based diagnosis and prognosis algorithm. Promising features of the proposed algorithm are described in terms of corrosion state estimation and prediction of degradation over time to a predefined threshold.

  10. Artificial neural network (ANN)-based prediction of depth filter loading capacity for filter sizing.

    Science.gov (United States)

    Agarwal, Harshit; Rathore, Anurag S; Hadpe, Sandeep Ramesh; Alva, Solomon J

    2016-11-01

    This article presents an application of artificial neural network (ANN) modelling towards prediction of depth filter loading capacity for clarification of a monoclonal antibody (mAb) product during commercial manufacturing. The effect of operating parameters on filter loading capacity was evaluated based on the analysis of change in the differential pressure (DP) as a function of time. The proposed ANN model uses inlet stream properties (feed turbidity, feed cell count, feed cell viability), flux, and time to predict the corresponding DP. The ANN contained a single output layer with ten neurons in hidden layer and employed a sigmoidal activation function. This network was trained with 174 training points, 37 validation points, and 37 test points. Further, a pressure cut-off of 1.1 bar was used for sizing the filter area required under each operating condition. The modelling results showed that there was excellent agreement between the predicted and experimental data with a regression coefficient (R 2 ) of 0.98. The developed ANN model was used for performing variable depth filter sizing for different clarification lots. Monte-Carlo simulation was performed to estimate the cost savings by using different filter areas for different clarification lots rather than using the same filter area. A 10% saving in cost of goods was obtained for this operation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1436-1443, 2016. © 2016 American Institute of Chemical Engineers.

  11. Variable Step Size Maximum Correntropy Criteria Based Adaptive Filtering Algorithm

    Directory of Open Access Journals (Sweden)

    S. Radhika

    2016-04-01

    Full Text Available Maximum correntropy criterion (MCC based adaptive filters are found to be robust against impulsive interference. This paper proposes a novel MCC based adaptive filter with variable step size in order to obtain improved performance in terms of both convergence rate and steady state error with robustness against impulsive interference. The optimal variable step size is obtained by minimizing the Mean Square Deviation (MSD error from one iteration to the other. Simulation results in the context of a highly impulsive system identification scenario show that the proposed algorithm has faster convergence and lesser steady state error than the conventional MCC based adaptive filters.

  12. Information filtering based on transferring similarity.

    Science.gov (United States)

    Sun, Duo; Zhou, Tao; Liu, Jian-Guo; Liu, Run-Ran; Jia, Chun-Xiao; Wang, Bing-Hong

    2009-07-01

    In this Brief Report, we propose an index of user similarity, namely, the transferring similarity, which involves all high-order similarities between users. Accordingly, we design a modified collaborative filtering algorithm, which provides remarkably higher accurate predictions than the standard collaborative filtering. More interestingly, we find that the algorithmic performance will approach its optimal value when the parameter, contained in the definition of transferring similarity, gets close to its critical value, before which the series expansion of transferring similarity is convergent and after which it is divergent. Our study is complementary to the one reported in [E. A. Leicht, P. Holme, and M. E. J. Newman, Phys. Rev. E 73, 026120 (2006)], and is relevant to the missing link prediction problem.

  13. Optimum filter-based discrimination of neutrons and gamma rays

    International Nuclear Information System (INIS)

    Amiri, Moslem; Prenosil, Vaclav; Cvachovec, Frantisek

    2015-01-01

    An optimum filter-based method for discrimination of neutrons and gamma-rays in a mixed radiation field is presented. The existing filter-based implementations of discriminators require sample pulse responses in advance of the experiment run to build the filter coefficients, which makes them less practical. Our novel technique creates the coefficients during the experiment and improves their quality gradually. Applied to several sets of mixed neutron and photon signals obtained through different digitizers using stilbene scintillator, this approach is analyzed and its discrimination quality is measured. (authors)

  14. Low-power adaptive filter based on RNS components

    DEFF Research Database (Denmark)

    Bernocchi, Gian Luca; Cardarilli, Gian Carlo; Del Re, Andrea

    2007-01-01

    In this paper a low-power implementation of an adaptive FIR filter is presented. The filter is designed to meet the constraints of channel equalization for fixed wireless communications that typically requires a large number of taps, but a serial updating of the filter coefficients, based...... on the least mean squares (LMS) algorithm, is allowed. Previous work showed that the use of the residue number system (RNS) for the variable FIR filter grants advantages both in area and power consumption. On the other hand, the use of a binary serial implementation of the adaptation algorithm eliminates...... the need for complex scaling circuits in RNS. The advantages in terms of area and speed of the presented filter, with respect to its two's complement counterpart, are evaluated for implementations in standard cells....

  15. Online cross-validation-based ensemble learning.

    Science.gov (United States)

    Benkeser, David; Ju, Cheng; Lendle, Sam; van der Laan, Mark

    2018-01-30

    Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinite-dimensional target parameter, such as a regression function, in the setting where data are generated sequentially by a common conditional data distribution given summary measures of the past. This setting encompasses a wide range of time-series models and, as special case, models for independent and identically distributed data. Our estimator considers a large library of candidate online estimators and uses online cross-validation to identify the algorithm with the best performance. We show that by basing estimates on the cross-validation-selected algorithm, we are asymptotically guaranteed to perform as well as the true, unknown best-performing algorithm. We provide extensions of this approach including online estimation of the optimal ensemble of candidate online estimators. We illustrate excellent performance of our methods using simulations and a real data example where we make streaming predictions of infectious disease incidence using data from a large database. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  16. On-line monitoring of methanol and methyl formate in the exhaust gas of an industrial formaldehyde production plant by a mid-IR gas sensor based on tunable Fabry-Pérot filter technology.

    Science.gov (United States)

    Genner, Andreas; Gasser, Christoph; Moser, Harald; Ofner, Johannes; Schreiber, Josef; Lendl, Bernhard

    2017-01-01

    On-line monitoring of key chemicals in an industrial production plant ensures economic operation, guarantees the desired product quality, and provides additional in-depth information on the involved chemical processes. For that purpose, rapid, rugged, and flexible measurement systems at reasonable cost are required. Here, we present the application of a flexible mid-IR filtometer for industrial gas sensing. The developed prototype consists of a modulated thermal infrared source, a temperature-controlled gas cell for absorption measurement and an integrated device consisting of a Fabry-Pérot interferometer and a pyroelectric mid-IR detector. The prototype was calibrated in the research laboratory at TU Wien for measuring methanol and methyl formate in the concentration ranges from 660 to 4390 and 747 to 4610 ppmV. Subsequently, the prototype was transferred and installed at the project partner Metadynea Austria GmbH and linked to their Process Control System via a dedicated micro-controller and used for on-line monitoring of the process off-gas. Up to five process streams were sequentially monitored in a fully automated manner. The obtained readings for methanol and methyl formate concentrations provided useful information on the efficiency and correct functioning of the process plant. Of special interest for industry is the now added capability to monitor the start-up phase and process irregularities with high time resolution (5 s).

  17. Efficient Scalable Median Filtering Using Histogram-Based Operations.

    Science.gov (United States)

    Green, Oded

    2018-05-01

    Median filtering is a smoothing technique for noise removal in images. While there are various implementations of median filtering for a single-core CPU, there are few implementations for accelerators and multi-core systems. Many parallel implementations of median filtering use a sorting algorithm for rearranging the values within a filtering window and taking the median of the sorted value. While using sorting algorithms allows for simple parallel implementations, the cost of the sorting becomes prohibitive as the filtering windows grow. This makes such algorithms, sequential and parallel alike, inefficient. In this work, we introduce the first software parallel median filtering that is non-sorting-based. The new algorithm uses efficient histogram-based operations. These reduce the computational requirements of the new algorithm while also accessing the image fewer times. We show an implementation of our algorithm for both the CPU and NVIDIA's CUDA supported graphics processing unit (GPU). The new algorithm is compared with several other leading CPU and GPU implementations. The CPU implementation has near perfect linear scaling with a speedup on a quad-core system. The GPU implementation is several orders of magnitude faster than the other GPU implementations for mid-size median filters. For small kernels, and , comparison-based approaches are preferable as fewer operations are required. Lastly, the new algorithm is open-source and can be found in the OpenCV library.

  18. OTRA-Based Multi-Function Inverse Filter Configuration

    Directory of Open Access Journals (Sweden)

    Abdhesh Kumar Singh

    2017-01-01

    Full Text Available A new OTRA-based multifunction Inverse filter configuration is presented which is capable of realizing low pass, high pass and band pass filters using only two OTRAs and five to six passive elements. To the best knowledge of the authors, any inverse filter configuration using OTRAs has not been reported in the literature earlier. The effect of the major parasitics of the OTRAs and their effect on the performance filter have been investigated and measured through simulation results and Monte-Carlo analysis. The workability of the proposed circuits has been confirmed by SPICE simulations using CMOS-based-OTRA realizable in 0.18 µm CMOS technology. The proposed circuits are the only ones which provide simultaneously the following features: use of reasonable number of active elements (only 2, realizability of all the three basic filter functions, employment of all virtually grounded resistors and capacitors and tunability of all filter parameters (except gain factor, H_0 for inverse high pass. The centre/cut-off frequency of the various filter circuits lying in the vicinity of 1 MHz have been found to be realizable, which has been verified through SPICE simulation results and have been found to be in good agreement with the theoretical results.

  19. Optimization of modal filters based on arrays of piezoelectric sensors

    International Nuclear Information System (INIS)

    Pagani, Carlos C Jr; Trindade, Marcelo A

    2009-01-01

    Modal filters may be obtained by a properly designed weighted sum of the output signals of an array of sensors distributed on the host structure. Although several research groups have been interested in techniques for designing and implementing modal filters based on a given array of sensors, the effect of the array topology on the effectiveness of the modal filter has received much less attention. In particular, it is known that some parameters, such as size, shape and location of a sensor, are very important in determining the observability of a vibration mode. Hence, this paper presents a methodology for the topological optimization of an array of sensors in order to maximize the effectiveness of a set of selected modal filters. This is done using a genetic algorithm optimization technique for the selection of 12 piezoceramic sensors from an array of 36 piezoceramic sensors regularly distributed on an aluminum plate, which maximize the filtering performance, over a given frequency range, of a set of modal filters, each one aiming to isolate one of the first vibration modes. The vectors of the weighting coefficients for each modal filter are evaluated using QR decomposition of the complex frequency response function matrix. Results show that the array topology is not very important for lower frequencies but it greatly affects the filter effectiveness for higher frequencies. Therefore, it is possible to improve the effectiveness and frequency range of a set of modal filters by optimizing the topology of an array of sensors. Indeed, using 12 properly located piezoceramic sensors bonded on an aluminum plate it is shown that the frequency range of a set of modal filters may be enlarged by 25–50%

  20. Biogas Filter Based on Local Natural Zeolite Materials

    Directory of Open Access Journals (Sweden)

    Satriyo Krido Wahono

    2014-02-01

    Full Text Available UPT BPPTK LIPI has created a biogas filter tool to improve the purity of methane in the biogas. The device shaped cylindrical tube containing absorbent materials which based on local natural zeolite of Indonesia. The absorbent has been activated and modified with other materials. This absorbtion material has multi-adsorption capacity for almost impurities gas of biogas. The biogas  filter increase methane content of biogas for 5-20%. The biogas filter improve the biogas’s performance such as increasing methane contents, increasing heating value, reduction of odors, reduction of corrosion potential, increasing the efficiency and stability of the generator.

  1. An operator model-based filtering scheme

    International Nuclear Information System (INIS)

    Sawhney, R.S.; Dodds, H.L.; Schryer, J.C.

    1990-01-01

    This paper presents a diagnostic model developed at Oak Ridge National Laboratory (ORNL) for off-normal nuclear power plant events. The diagnostic model is intended to serve as an embedded module of a cognitive model of the human operator, one application of which could be to assist control room operators in correctly responding to off-normal events by providing a rapid and accurate assessment of alarm patterns and parameter trends. The sequential filter model is comprised of two distinct subsystems --- an alarm analysis followed by an analysis of interpreted plant signals. During the alarm analysis phase, the alarm pattern is evaluated to generate hypotheses of possible initiating events in order of likelihood of occurrence. Each hypothesis is further evaluated through analysis of the current trends of state variables in order to validate/reject (in the form of increased/decreased certainty factor) the given hypothesis. 7 refs., 4 figs

  2. Voltage harmonic elimination with RLC based interface smoothing filter

    International Nuclear Information System (INIS)

    Chandrasekaran, K; Ramachandaramurthy, V K

    2015-01-01

    A method is proposed for designing a Dynamic Voltage Restorer (DVR) with RLC interface smoothing filter. The RLC filter connected between the IGBT based Voltage Source Inverter (VSI) is attempted to eliminate voltage harmonics in the busbar voltage and switching harmonics from VSI by producing a PWM controlled harmonic voltage. In this method, the DVR or series active filter produces PWM voltage that cancels the existing harmonic voltage due to any harmonic voltage source. The proposed method is valid for any distorted busbar voltage. The operating VSI handles no active power but only harmonic power. The DVR is able to suppress the lower order switching harmonics generated by the IGBT based VSI. Good dynamic and transient results obtained. The Total Harmonic Distortion (THD) is minimized to zero at the sensitive load end. Digital simulations are carried out using PSCAD/EMTDC to validate the performance of RLC filter. Simulated results are presented. (paper)

  3. Application of wavelet-based multi-model Kalman filters to real-time flood forecasting

    Science.gov (United States)

    Chou, Chien-Ming; Wang, Ru-Yih

    2004-04-01

    This paper presents the application of a multimodel method using a wavelet-based Kalman filter (WKF) bank to simultaneously estimate decomposed state variables and unknown parameters for real-time flood forecasting. Applying the Haar wavelet transform alters the state vector and input vector of the state space. In this way, an overall detail plus approximation describes each new state vector and input vector, which allows the WKF to simultaneously estimate and decompose state variables. The wavelet-based multimodel Kalman filter (WMKF) is a multimodel Kalman filter (MKF), in which the Kalman filter has been substituted for a WKF. The WMKF then obtains M estimated state vectors. Next, the M state-estimates, each of which is weighted by its possibility that is also determined on-line, are combined to form an optimal estimate. Validations conducted for the Wu-Tu watershed, a small watershed in Taiwan, have demonstrated that the method is effective because of the decomposition of wavelet transform, the adaptation of the time-varying Kalman filter and the characteristics of the multimodel method. Validation results also reveal that the resulting method enhances the accuracy of the runoff prediction of the rainfall-runoff process in the Wu-Tu watershed.

  4. Assessing a robust ensemble-based Kalman filter for efficient ecosystem data assimilation of the Cretan Sea

    KAUST Repository

    Triantafyllou, George N.; Hoteit, Ibrahim; Luo, Xiaodong; Tsiaras, Kostas P.; Petihakis, George

    2013-01-01

    An application of an ensemble-based robust filter for data assimilation into an ecosystem model of the Cretan Sea is presented and discussed. The ecosystem model comprises two on-line coupled sub-models: the Princeton Ocean Model (POM) and the European Regional Seas Ecosystem Model (ERSEM). The filtering scheme is based on the Singular Evolutive Interpolated Kalman (SEIK) filter which is implemented with a time-local H∞ filtering strategy to enhance robustness and performances during periods of strong ecosystem variability. Assimilation experiments in the Cretan Sea indicate that robustness can be achieved in the SEIK filter by introducing an adaptive inflation scheme of the modes of the filter error covariance matrix. Twin-experiments are performed to evaluate the performance of the assimilation system and to study the benefits of using robust filtering in an ensemble filtering framework. Pseudo-observations of surface chlorophyll, extracted from a model reference run, were assimilated every two days. Simulation results suggest that the adaptive inflation scheme significantly improves the behavior of the SEIK filter during periods of strong ecosystem variability. © 2012 Elsevier B.V.

  5. Assessing a robust ensemble-based Kalman filter for efficient ecosystem data assimilation of the Cretan Sea

    KAUST Repository

    Triantafyllou, George N.

    2013-09-01

    An application of an ensemble-based robust filter for data assimilation into an ecosystem model of the Cretan Sea is presented and discussed. The ecosystem model comprises two on-line coupled sub-models: the Princeton Ocean Model (POM) and the European Regional Seas Ecosystem Model (ERSEM). The filtering scheme is based on the Singular Evolutive Interpolated Kalman (SEIK) filter which is implemented with a time-local H∞ filtering strategy to enhance robustness and performances during periods of strong ecosystem variability. Assimilation experiments in the Cretan Sea indicate that robustness can be achieved in the SEIK filter by introducing an adaptive inflation scheme of the modes of the filter error covariance matrix. Twin-experiments are performed to evaluate the performance of the assimilation system and to study the benefits of using robust filtering in an ensemble filtering framework. Pseudo-observations of surface chlorophyll, extracted from a model reference run, were assimilated every two days. Simulation results suggest that the adaptive inflation scheme significantly improves the behavior of the SEIK filter during periods of strong ecosystem variability. © 2012 Elsevier B.V.

  6. Information filtering in sparse online systems: recommendation via semi-local diffusion.

    Science.gov (United States)

    Zeng, Wei; Zeng, An; Shang, Ming-Sheng; Zhang, Yi-Cheng

    2013-01-01

    With the rapid growth of the Internet and overwhelming amount of information and choices that people are confronted with, recommender systems have been developed to effectively support users' decision-making process in the online systems. However, many recommendation algorithms suffer from the data sparsity problem, i.e. the user-object bipartite networks are so sparse that algorithms cannot accurately recommend objects for users. This data sparsity problem makes many well-known recommendation algorithms perform poorly. To solve the problem, we propose a recommendation algorithm based on the semi-local diffusion process on the user-object bipartite network. The simulation results on two sparse datasets, Amazon and Bookcross, show that our method significantly outperforms the state-of-the-art methods especially for those small-degree users. Two personalized semi-local diffusion methods are proposed which further improve the recommendation accuracy. Finally, our work indicates that sparse online systems are essentially different from the dense online systems, so it is necessary to reexamine former algorithms and conclusions based on dense data in sparse systems.

  7. Learning based particle filtering object tracking for visible-light systems.

    Science.gov (United States)

    Sun, Wei

    2015-10-01

    We propose a novel object tracking framework based on online learning scheme that can work robustly in challenging scenarios. Firstly, a learning-based particle filter is proposed with color and edge-based features. We train a. support vector machine (SVM) classifier with object and background information and map the outputs into probabilities, then the weight of particles in a particle filter can be calculated by the probabilistic outputs to estimate the state of the object. Secondly, the tracking loop starts with Lucas-Kanade (LK) affine template matching and follows by learning-based particle filter tracking. Lucas-Kanade method estimates errors and updates object template in the positive samples dataset, and learning-based particle filter tracker will start if the LK tracker loses the object. Finally, SVM classifier evaluates every tracked appearance to update the training set or restart the tracking loop if necessary. Experimental results show that our method is robust to challenging light, scale and pose changing, and test on eButton image sequence also achieves satisfactory tracking performance.

  8. Synthesis of Cascadable DDCC-Based Universal Filter Using NAM

    Directory of Open Access Journals (Sweden)

    Huu-Duy Tran

    2015-08-01

    Full Text Available A novel systematic approach for synthesizing DDCC-based voltage-mode biquadratic universal filters is proposed. The DDCCs are described by infinity-variables’ models of nullor-mirror elements which can be used in the nodal admittance matrix expansion process. Applying the proposed method, the obtained 12 equivalent filters offer the following features: multi-input and two outputs, realization of all five standard filter functions, namely lowpass, bandpass, highpass, notch and allpass, high-input impedance, employing only grounded capacitors and resistors, orthogonal controllability between pole frequency and quality factor, and cascadable, low active and passive sensitivities. The workability of some synthesized filters is verified by HSPICE simulations to demonstrate the feasibility of the proposed method.

  9. Study of an on-line filtering system for the ATLAS detector

    International Nuclear Information System (INIS)

    Fede, E.

    2001-01-01

    The first chapter presents today's knowledge about particle physics and a description of the main decay channels and physical signatures associated to the Higgs boson is given. The second chapter is dedicated to the LHC accelerator with a focus on the ATLAS detector and its sub-detectors. The third chapter presents ATLAS triggering system and its data acquisition system. In the fourth chapter the functionalities required for an adequate event filtering system concerning physics issues and data managing are described. The design of a prototype based on a fleet of PC computers linked through an Ethernet network is presented in the fifth chapter

  10. An approach for fixed coefficient RNS-based FIR filter

    Science.gov (United States)

    Srinivasa Reddy, Kotha; Sahoo, Subhendu Kumar

    2017-08-01

    In this work, an efficient new modular multiplication method for {2k-1, 2k, 2k+1-1} moduli set is proposed to implement a residue number system (RNS)-based fixed coefficient finite impulse response filter. The new multiplication approach reduces the number of partial products by using pre-loaded product block. The reduction in partial products with the proposed modular multiplication improves the clock frequency and reduces the area and power as compared with the conventional modular multiplication. Further, the present approach eliminates a binary number to residue number converter circuit, which is usually needed at the front end of RNS-based system. In this work, two fixed coefficient filter architectures with the new modular multiplication approach are proposed. The filters are implemented using Verilog hardware description language. The United Microelectronics Corporation 90 nm technology library has been used for synthesis and the results area, power and delay are obtained with the help of Cadence register transfer level compiler. The power delay product (PDP) is also considered for performance comparison among the proposed filters. One of the proposed architecture is found to improve PDP gain by 60.83% as compared with the filter implemented with conventional modular multiplier. The filters functionality is validated with the help of Altera DSP Builder.

  11. Image defog algorithm based on open close filter and gradient domain recursive bilateral filter

    Science.gov (United States)

    Liu, Daqian; Liu, Wanjun; Zhao, Qingguo; Fei, Bowen

    2017-11-01

    To solve the problems of fuzzy details, color distortion, low brightness of the image obtained by the dark channel prior defog algorithm, an image defog algorithm based on open close filter and gradient domain recursive bilateral filter, referred to as OCRBF, was put forward. The algorithm named OCRBF firstly makes use of weighted quad tree to obtain more accurate the global atmospheric value, then exploits multiple-structure element morphological open and close filter towards the minimum channel map to obtain a rough scattering map by dark channel prior, makes use of variogram to correct the transmittance map,and uses gradient domain recursive bilateral filter for the smooth operation, finally gets recovery images by image degradation model, and makes contrast adjustment to get bright, clear and no fog image. A large number of experimental results show that the proposed defog method in this paper can be good to remove the fog , recover color and definition of the fog image containing close range image, image perspective, the image including the bright areas very well, compared with other image defog algorithms,obtain more clear and natural fog free images with details of higher visibility, what's more, the relationship between the time complexity of SIDA algorithm and the number of image pixels is a linear correlation.

  12. Detail-enhanced multimodality medical image fusion based on gradient minimization smoothing filter and shearing filter.

    Science.gov (United States)

    Liu, Xingbin; Mei, Wenbo; Du, Huiqian

    2018-02-13

    In this paper, a detail-enhanced multimodality medical image fusion algorithm is proposed by using proposed multi-scale joint decomposition framework (MJDF) and shearing filter (SF). The MJDF constructed with gradient minimization smoothing filter (GMSF) and Gaussian low-pass filter (GLF) is used to decompose source images into low-pass layers, edge layers, and detail layers at multiple scales. In order to highlight the detail information in the fused image, the edge layer and the detail layer in each scale are weighted combined into a detail-enhanced layer. As directional filter is effective in capturing salient information, so SF is applied to the detail-enhanced layer to extract geometrical features and obtain directional coefficients. Visual saliency map-based fusion rule is designed for fusing low-pass layers, and the sum of standard deviation is used as activity level measurement for directional coefficients fusion. The final fusion result is obtained by synthesizing the fused low-pass layers and directional coefficients. Experimental results show that the proposed method with shift-invariance, directional selectivity, and detail-enhanced property is efficient in preserving and enhancing detail information of multimodality medical images. Graphical abstract The detailed implementation of the proposed medical image fusion algorithm.

  13. PARTICLE FILTER BASED VEHICLE TRACKING APPROACH WITH IMPROVED RESAMPLING STAGE

    Directory of Open Access Journals (Sweden)

    Wei Leong Khong

    2014-02-01

    Full Text Available Optical sensors based vehicle tracking can be widely implemented in traffic surveillance and flow control. The vast development of video surveillance infrastructure in recent years has drawn the current research focus towards vehicle tracking using high-end and low cost optical sensors. However, tracking vehicles via such sensors could be challenging due to the high probability of changing vehicle appearance and illumination, besides the occlusion and overlapping incidents. Particle filter has been proven as an approach which can overcome nonlinear and non-Gaussian situations caused by cluttered background and occlusion incidents. Unfortunately, conventional particle filter approach encounters particle degeneracy especially during and after the occlusion. Particle filter with sampling important resampling (SIR is an important step to overcome the drawback of particle filter, but SIR faced the problem of sample impoverishment when heavy particles are statistically selected many times. In this work, genetic algorithm has been proposed to be implemented in the particle filter resampling stage, where the estimated position can converge faster to hit the real position of target vehicle under various occlusion incidents. The experimental results show that the improved particle filter with genetic algorithm resampling method manages to increase the tracking accuracy and meanwhile reduce the particle sample size in the resampling stage.

  14. New Statistics for Texture Classification Based on Gabor Filters

    Directory of Open Access Journals (Sweden)

    J. Pavlovicova

    2007-09-01

    Full Text Available The paper introduces a new method of texture segmentation efficiency evaluation. One of the well known texture segmentation methods is based on Gabor filters because of their orientation and spatial frequency character. Several statistics are used to extract more information from results obtained by Gabor filtering. Big amount of input parameters causes a wide set of results which need to be evaluated. The evaluation method is based on the normal distributions Gaussian curves intersection assessment and provides a new point of view to the segmentation method selection.

  15. Virus removal in ceramic depth filters based on diatomaceous earth.

    Science.gov (United States)

    Michen, Benjamin; Meder, Fabian; Rust, Annette; Fritsch, Johannes; Aneziris, Christos; Graule, Thomas

    2012-01-17

    Ceramic filter candles, based on the natural material diatomaceous earth, are widely used to purify water at the point-of-use. Although such depth filters are known to improve drinking water quality by removing human pathogenic protozoa and bacteria, their removal regarding viruses has rarely been investigated. These filters have relatively large pore diameters compared to the physical dimension of viruses. However, viruses may be retained by adsorption mechanisms due to intermolecular and surface forces. Here, we use three types of bacteriophages to investigate their removal during filtration and batch experiments conducted at different pH values and ionic strengths. Theoretical models based on DLVO-theory are applied in order to verify experimental results and assess surface forces involved in the adsorptive process. This was done by calculation of interaction energies between the filter surface and the viruses. For two small spherically shaped viruses (MS2 and PhiX174), these filters showed no significant removal. In the case of phage PhiX174, where attractive interactions were expected, due to electrostatic attraction of oppositely charged surfaces, only little adsorption was reported in the presence of divalent ions. Thus, we postulate the existence of an additional repulsive force between PhiX174 and the filter surface. It is hypothesized that such an additional energy barrier originates from either the phage's specific knobs that protrude from the viral capsid, enabling steric interactions, or hydration forces between the two hydrophilic interfaces of virus and filter. However, a larger-sized, tailed bacteriophage of the family Siphoviridae was removed by log 2 to 3, which is explained by postulating hydrophobic interactions.

  16. IMU-based online kinematic calibration of robot manipulator.

    Science.gov (United States)

    Du, Guanglong; Zhang, Ping

    2013-01-01

    Robot calibration is a useful diagnostic method for improving the positioning accuracy in robot production and maintenance. An online robot self-calibration method based on inertial measurement unit (IMU) is presented in this paper. The method requires that the IMU is rigidly attached to the robot manipulator, which makes it possible to obtain the orientation of the manipulator with the orientation of the IMU in real time. This paper proposed an efficient approach which incorporates Factored Quaternion Algorithm (FQA) and Kalman Filter (KF) to estimate the orientation of the IMU. Then, an Extended Kalman Filter (EKF) is used to estimate kinematic parameter errors. Using this proposed orientation estimation method will result in improved reliability and accuracy in determining the orientation of the manipulator. Compared with the existing vision-based self-calibration methods, the great advantage of this method is that it does not need the complex steps, such as camera calibration, images capture, and corner detection, which make the robot calibration procedure more autonomous in a dynamic manufacturing environment. Experimental studies on a GOOGOL GRB3016 robot show that this method has better accuracy, convenience, and effectiveness than vision-based methods.

  17. Intelligent Online Store: User Behavior Analysis based Recommender System

    Directory of Open Access Journals (Sweden)

    Mohamadreza Karimi Alavije

    2015-06-01

    Full Text Available Recommender systems provide personalised recommendations to users, helping them find their ideal items, also play a key role in encouraging users to make their purchases through websites thus leading to the success of online stores. The collaborative filtering method is one of the most successful techniques utilized in these systems facilitating the provision of recommendations close to that of the customer's taste and need. However the proliferation of both customers and products on offer, the technique faces some issues such as "cold start" and scalability. As such in this paper a new method has been introduced in which user-based collaborative filtering is used at a base method along with a weighted clustering of users based upon demographics in order to improve the results obtained from the system. The implementation of the results of the algorithms demonstrate that the presented approach has a lower RMSE, which means that the system offers improved performance and accuracy and that the resulting recommendations are closer to the taste and preferences of the users.

  18. IMU-Based Online Kinematic Calibration of Robot Manipulator

    Directory of Open Access Journals (Sweden)

    Guanglong Du

    2013-01-01

    Full Text Available Robot calibration is a useful diagnostic method for improving the positioning accuracy in robot production and maintenance. An online robot self-calibration method based on inertial measurement unit (IMU is presented in this paper. The method requires that the IMU is rigidly attached to the robot manipulator, which makes it possible to obtain the orientation of the manipulator with the orientation of the IMU in real time. This paper proposed an efficient approach which incorporates Factored Quaternion Algorithm (FQA and Kalman Filter (KF to estimate the orientation of the IMU. Then, an Extended Kalman Filter (EKF is used to estimate kinematic parameter errors. Using this proposed orientation estimation method will result in improved reliability and accuracy in determining the orientation of the manipulator. Compared with the existing vision-based self-calibration methods, the great advantage of this method is that it does not need the complex steps, such as camera calibration, images capture, and corner detection, which make the robot calibration procedure more autonomous in a dynamic manufacturing environment. Experimental studies on a GOOGOL GRB3016 robot show that this method has better accuracy, convenience, and effectiveness than vision-based methods.

  19. Improved OCV Model of a Li-Ion NMC Battery for Online SOC Estimation Using the Extended Kalman Filter

    Directory of Open Access Journals (Sweden)

    Ines Baccouche

    2017-05-01

    Full Text Available Accurate modeling of the nonlinear relationship between the open circuit voltage (OCV and the state of charge (SOC is required for adaptive SOC estimation during the lithium-ion (Li-ion battery operation. Online SOC estimation should meet several constraints, such as the computational cost, the number of parameters, as well as the accuracy of the model. In this paper, these challenges are considered by proposing an improved simplified and accurate OCV model of a nickel manganese cobalt (NMC Li-ion battery, based on an empirical analytical characterization approach. In fact, composed of double exponential and simple quadratic functions containing only five parameters, the proposed model accurately follows the experimental curve with a minor fitting error of 1 mV. The model is also valid at a wide temperature range and takes into account the voltage hysteresis of the OCV. Using this model in SOC estimation by the extended Kalman filter (EKF contributes to minimizing the execution time and to reducing the SOC estimation error to only 3% compared to other existing models where the estimation error is about 5%. Experiments are also performed to prove that the proposed OCV model incorporated in the EKF estimator exhibits good reliability and precision under various loading profiles and temperatures.

  20. Kalman Filter Based Tracking in an Video Surveillance System

    Directory of Open Access Journals (Sweden)

    SULIMAN, C.

    2010-05-01

    Full Text Available In this paper we have developed a Matlab/Simulink based model for monitoring a contact in a video surveillance sequence. For the segmentation process and corect identification of a contact in a surveillance video, we have used the Horn-Schunk optical flow algorithm. The position and the behavior of the correctly detected contact were monitored with the help of the traditional Kalman filter. After that we have compared the results obtained from the optical flow method with the ones obtained from the Kalman filter, and we show the correct functionality of the Kalman filter based tracking. The tests were performed using video data taken with the help of a fix camera. The tested algorithm has shown promising results.

  1. Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

    Science.gov (United States)

    Simon, Donald L.; Garg, Sanjay

    2010-01-01

    A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

  2. Online Project Based Learning in Innovation Management.

    Science.gov (United States)

    O'Sullivan, David

    2003-01-01

    An innovation management course has three strands with face-to-face and online components: (1) seminars with online course notes and slides; (2) assignments (group online case studies, tutorials, in-class presentations); and (3) assessment (online, oral, in-class, written). Students are able to benchmark their work online and teachers use the…

  3. Predicting online ratings based on the opinion spreading process

    Science.gov (United States)

    He, Xing-Sheng; Zhou, Ming-Yang; Zhuo, Zhao; Fu, Zhong-Qian; Liu, Jian-Guo

    2015-10-01

    Predicting users' online ratings is always a challenge issue and has drawn lots of attention. In this paper, we present a rating prediction method by combining the user opinion spreading process with the collaborative filtering algorithm, where user similarity is defined by measuring the amount of opinion a user transfers to another based on the primitive user-item rating matrix. The proposed method could produce a more precise rating prediction for each unrated user-item pair. In addition, we introduce a tunable parameter λ to regulate the preferential diffusion relevant to the degree of both opinion sender and receiver. The numerical results for Movielens and Netflix data sets show that this algorithm has a better accuracy than the standard user-based collaborative filtering algorithm using Cosine and Pearson correlation without increasing computational complexity. By tuning λ, our method could further boost the prediction accuracy when using Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) as measurements. In the optimal cases, on Movielens and Netflix data sets, the corresponding algorithmic accuracy (MAE and RMSE) are improved 11.26% and 8.84%, 13.49% and 10.52% compared to the item average method, respectively.

  4. Energy Based Clutter Filtering for Vector Flow Imaging

    DEFF Research Database (Denmark)

    Villagómez Hoyos, Carlos Armando; Jensen, Jonas; Ewertsen, Caroline

    2017-01-01

    for obtaining vector flow measurements, since the spectra overlaps at high beam-to-flow angles. In this work a distinct approach is proposed, where the energy of the velocity spectrum is used to differentiate among the two signals. The energy based method is applied by limiting the amplitude of the velocity...... spectrum function to a predetermined threshold. The effect of the clutter filtering is evaluated on a plane wave (PW) scan sequence in combination with transverse oscillation (TO) and directional beamforming (DB) for velocity estimation. The performance of the filter is assessed by comparison...

  5. Optical supervised filtering technique based on Hopfield neural network

    Science.gov (United States)

    Bal, Abdullah

    2004-11-01

    Hopfield neural network is commonly preferred for optimization problems. In image segmentation, conventional Hopfield neural networks (HNN) are formulated as a cost-function-minimization problem to perform gray level thresholding on the image histogram or the pixels' gray levels arranged in a one-dimensional array [R. Sammouda, N. Niki, H. Nishitani, Pattern Rec. 30 (1997) 921-927; K.S. Cheng, J.S. Lin, C.W. Mao, IEEE Trans. Med. Imag. 15 (1996) 560-567; C. Chang, P. Chung, Image and Vision comp. 19 (2001) 669-678]. In this paper, a new high speed supervised filtering technique is proposed for image feature extraction and enhancement problems by modifying the conventional HNN. The essential improvement in this technique is to use 2D convolution operation instead of weight-matrix multiplication. Thereby, neural network based a new filtering technique has been obtained that is required just 3 × 3 sized filter mask matrix instead of large size weight coefficient matrix. Optical implementation of the proposed filtering technique is executed easily using the joint transform correlator. The requirement of non-negative data for optical implementation is provided by bias technique to convert the bipolar data to non-negative data. Simulation results of the proposed optical supervised filtering technique are reported for various feature extraction problems such as edge detection, corner detection, horizontal and vertical line extraction, and fingerprint enhancement.

  6. Estimation of Sideslip Angle Based on Extended Kalman Filter

    Directory of Open Access Journals (Sweden)

    Yupeng Huang

    2017-01-01

    Full Text Available The sideslip angle plays an extremely important role in vehicle stability control, but the sideslip angle in production car cannot be obtained from sensor directly in consideration of the cost of the sensor; it is essential to estimate the sideslip angle indirectly by means of other vehicle motion parameters; therefore, an estimation algorithm with real-time performance and accuracy is critical. Traditional estimation method based on Kalman filter algorithm is correct in vehicle linear control area; however, on low adhesion road, vehicles have obvious nonlinear characteristics. In this paper, extended Kalman filtering algorithm had been put forward in consideration of the nonlinear characteristic of the tire and was verified by the Carsim and Simulink joint simulation, such as the simulation on the wet cement road and the ice and snow road with double lane change. To test and verify the effect of extended Kalman filtering estimation algorithm, the real vehicle test was carried out on the limit test field. The experimental results show that the accuracy of vehicle sideslip angle acquired by extended Kalman filtering algorithm is obviously higher than that acquired by Kalman filtering in the area of the nonlinearity.

  7. Gaussian particle filter based pose and motion estimation

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Determination of relative three-dimensional (3D) position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fields such as photogrammetry.A solution to pose and motion estimation problem that uses two-dimensional (2D) intensity images from a single camera is desirable for real-time applications. The difficulty in performing this measurement is that the process of projecting 3D object features to 2D images is a nonlinear transformation. In this paper, the 3D transformation is modeled as a nonlinear stochastic system with the state estimation providing six degrees-of-freedom motion and position values, using line features in image plane as measuring inputs and dual quaternion to represent both rotation and translation in a unified notation. A filtering method called the Gaussian particle filter (GPF) based on the particle filtering concept is presented for 3D pose and motion estimation of a moving target from monocular image sequences. The method has been implemented with simulated data, and simulation results are provided along with comparisons to the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) to show the relative advantages of the GPF. Simulation results showed that GPF is a superior alternative to EKF and UKF.

  8. Narrowband spectral filter based on biconical tapered fiber

    Science.gov (United States)

    Celaschi, Sergio; Malheiros-Silveira, Gilliard N.

    2018-02-01

    The ease of fabrication and compactness of devices based on tapered optical fibers contribute to its potential using in several applications ranging from telecommunication components to sensing devices. In this work, we proposed, fabricated, and characterized a spectral filter made of biconical taper from a coaxial optical fiber. This filter is defined by adiabatically tapering a depressed-cladding fiber. The adiabatic taper profile obtained during fabrication prevents the interference of other modes than HE11 and HE12 ones, which play the main role for the beating phenomenon and the filter response. The evolution of the fiber shapes during the pulling was modeled by two coupled partial differential equations, which relate the normalized cross-section area, and the axial velocity of the fiber elongation. These equations govern the mass and axial momentum conservation. The numerical results of the filter characteristics are in good accordance with the experimental ones. The filter was packaged in order to let it ready for using in optical communication bands. The characteristics are: free spectral range (FSR) of 6.19 nm, insertion loss bellow 0.5 dB, and isolation > 20 dB at C-band. Its transmission spectrum extends from 1200 to 1600 nm where the optical fiber core supports monomode transmission. Such characteristics may also be interesting to be applied in sensing applications. We show preliminary numerical results assuming a biconic taper embedded into a dielectric media, showing promising results for electro-optic sensing applications.

  9. POF based glucose sensor incorporating grating wavelength filters

    DEFF Research Database (Denmark)

    Hassan, Hafeez Ul; Aasmul, Søren; Bang, Ole

    2014-01-01

    AND RESEARCH IN POLYMER OPTICAL DEVICES; TRIPOD. Within the domain of TRIPOD, research is conducted on "Plastic Optical Fiber based Glucose Sensors Incorporating Grating Wavelength Filters". Research will be focused to optimized fiber tips for better coupling efficiency, reducing the response time of sensor...

  10. Research on Kalman-filter based multisensor data fusion

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Multisensor data fusion has played a significant role in diverse areas ranging from local robot guidance to global military theatre defense etc.Various multisensor data fusion methods have been extensively investigated by researchers,of which Klaman filtering is one of the most important.Kalman filtering is the best-known recursive least mean-square algorithm to optimally estimate the unknown.states of a dynamic system,which has found widespread application in many areas.The scope of the work is restricted to investigate the various data fusion and track fusion techniques based on the Kalman Filter methods.then a new method of state fusion is proposed.Finally the simulation results demonstrate the effectiveness of the introduced method.

  11. Fish tracking by combining motion based segmentation and particle filtering

    Science.gov (United States)

    Bichot, E.; Mascarilla, L.; Courtellemont, P.

    2006-01-01

    In this paper, we suggest a new importance sampling scheme to improve a particle filtering based tracking process. This scheme relies on exploitation of motion segmentation. More precisely, we propagate hypotheses from particle filtering to blobs of similar motion to target. Hence, search is driven toward regions of interest in the state space and prediction is more accurate. We also propose to exploit segmentation to update target model. Once the moving target has been identified, a representative model is learnt from its spatial support. We refer to this model in the correction step of the tracking process. The importance sampling scheme and the strategy to update target model improve the performance of particle filtering in complex situations of occlusions compared to a simple Bootstrap approach as shown by our experiments on real fish tank sequences.

  12. Acoustic wave filter based on periodically poled lithium niobate.

    Science.gov (United States)

    Courjon, Emilie; Bassignot, Florent; Ulliac, Gwenn; Benchabane, Sarah; Ballandras, Sylvain

    2012-09-01

    Solutions for the development of compact RF passive transducers as an alternative to standard surface or bulk acoustic wave devices are receiving increasing interest. This article presents results on the development of an acoustic band-pass filter based on periodically poled ferroelectric domains in lithium niobate. The fabrication of periodically poled transducers (PPTs) operating in the range of 20 to 650 MHz has been achieved on 3-in (76.2-mm) 500-μm-thick wafers. This kind of transducer is able to excite elliptical as well as longitudinal modes, yielding phase velocities of about 3800 and 6500 ms(-1), respectively. A new type of acoustic band-pass filter is proposed, based on the use of PPTs instead of the SAWs excited by classical interdigital transducers. The design and the fabrication of such a filter are presented, as well as experimental measurements of its electrical response and transfer function. The feasibility of such a PPT-based filter is thereby demonstrated and the limitations of this method are discussed.

  13. Nonlinear system identification based on Takagi-Sugeno fuzzy modeling and unscented Kalman filter.

    Science.gov (United States)

    Vafamand, Navid; Arefi, Mohammad Mehdi; Khayatian, Alireza

    2018-03-01

    This paper proposes two novel Kalman-based learning algorithms for an online Takagi-Sugeno (TS) fuzzy model identification. The proposed approaches are designed based on the unscented Kalman filter (UKF) and the concept of dual estimation. Contrary to the extended Kalman filter (EKF) which utilizes derivatives of nonlinear functions, the UKF employs the unscented transformation. Consequently, non-differentiable membership functions can be considered in the structure of the TS models. This makes the proposed algorithms to be applicable for the online parameter calculation of wider classes of TS models compared to the recently published papers concerning the same issue. Furthermore, because of the great capability of the UKF in handling severe nonlinear dynamics, the proposed approaches can effectively approximate the nonlinear systems. Finally, numerical and practical examples are provided to show the advantages of the proposed approaches. Simulation results reveal the effectiveness of the proposed methods and performance improvement based on the root mean square (RMS) of the estimation error compared to the existing results. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  14. Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

    Science.gov (United States)

    Kim, Deok-Hwan

    As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

  15. Scattering-angle based filtering of the waveform inversion gradients

    KAUST Repository

    Alkhalifah, Tariq Ali

    2014-01-01

    Full waveform inversion (FWI) requires a hierarchical approach to maneuver the complex non-linearity associated with the problem of velocity update. In anisotropic media, the non-linearity becomes far more complex with the potential trade-off between the multiparameter description of the model. A gradient filter helps us in accessing the parts of the gradient that are suitable to combat the potential non-linearity and parameter trade-off. The filter is based on representing the gradient in the time-lag normalized domain, in which the low scattering angle of the gradient update is initially muted out in the FWI implementation, in what we may refer to as a scattering angle continuation process. The result is a low wavelength update dominated by the transmission part of the update gradient. In this case, even 10 Hz data can produce vertically near-zero wavenumber updates suitable for a background correction of the model. Relaxing the filtering at a later stage in the FWI implementation allows for smaller scattering angles to contribute higher-resolution information to the model. The benefits of the extended domain based filtering of the gradient is not only it's ability in providing low wavenumber gradients guided by the scattering angle, but also in its potential to provide gradients free of unphysical energy that may correspond to unrealistic scattering angles.

  16. Scattering-angle based filtering of the waveform inversion gradients

    KAUST Repository

    Alkhalifah, Tariq Ali

    2014-11-22

    Full waveform inversion (FWI) requires a hierarchical approach to maneuver the complex non-linearity associated with the problem of velocity update. In anisotropic media, the non-linearity becomes far more complex with the potential trade-off between the multiparameter description of the model. A gradient filter helps us in accessing the parts of the gradient that are suitable to combat the potential non-linearity and parameter trade-off. The filter is based on representing the gradient in the time-lag normalized domain, in which the low scattering angle of the gradient update is initially muted out in the FWI implementation, in what we may refer to as a scattering angle continuation process. The result is a low wavelength update dominated by the transmission part of the update gradient. In this case, even 10 Hz data can produce vertically near-zero wavenumber updates suitable for a background correction of the model. Relaxing the filtering at a later stage in the FWI implementation allows for smaller scattering angles to contribute higher-resolution information to the model. The benefits of the extended domain based filtering of the gradient is not only it\\'s ability in providing low wavenumber gradients guided by the scattering angle, but also in its potential to provide gradients free of unphysical energy that may correspond to unrealistic scattering angles.

  17. Widely Tunable 4th Order Switched Gm -C Band-Pass Filter Based on N-Path Filters

    NARCIS (Netherlands)

    Darvishi, M.; van der Zee, Ronan A.R.; Klumperink, Eric A.M.; Nauta, Bram

    2012-01-01

    Abstract—A widely tunable 4th order BPF based on the subtraction of two 2nd order 4-path passive-mixer filters with slightly different center frequencies is proposed. The center frequency of each 4-path filter is slightly shifted relative to its clock frequency (one upward and the other one

  18. A Hybrid Approach using Collaborative filtering and Content based Filtering for Recommender System

    Science.gov (United States)

    Geetha, G.; Safa, M.; Fancy, C.; Saranya, D.

    2018-04-01

    In today’s digital world, it has become an irksome task to find the content of one's liking in an endless variety of content that are being consumed like books, videos, articles, movies, etc. On the other hand there has been an emerging growth among the digital content providers who want to engage as many users on their service as possible for the maximum time. This gave birth to the recommender system comes wherein the content providers recommend users the content according to the users’ taste and liking. In this paper we have proposed a movie recommendation system. A movie recommendation is important in our social life due to its features such as suggesting a set of movies to users based on their interest, or the popularities of the movies. In this paper we are proposing a movie recommendation system that has the ability to recommend movies to a new user as well as the other existing users. It mines movie databases to collect all the important information, such as, popularity and attractiveness, which are required for recommendation. We use content-based and collaborative filtering and also hybrid filtering, which is a combination of the results of these two techniques, to construct a system that provides more precise recommendations concerning movies.

  19. Modeling of memristor-based chaotic systems using nonlinear Wiener adaptive filters based on backslash operator

    International Nuclear Information System (INIS)

    Zhao, Yibo; Jiang, Yi; Feng, Jiuchao; Wu, Lifu

    2016-01-01

    Highlights: • A novel nonlinear Wiener adaptive filters based on the backslash operator are proposed. • The identification approach to the memristor-based chaotic systems using the proposed adaptive filters. • The weight update algorithm and convergence characteristics for the proposed adaptive filters are derived. - Abstract: Memristor-based chaotic systems have complex dynamical behaviors, which are characterized as nonlinear and hysteresis characteristics. Modeling and identification of their nonlinear model is an important premise for analyzing the dynamical behavior of the memristor-based chaotic systems. This paper presents a novel nonlinear Wiener adaptive filtering identification approach to the memristor-based chaotic systems. The linear part of Wiener model consists of the linear transversal adaptive filters, the nonlinear part consists of nonlinear adaptive filters based on the backslash operator for the hysteresis characteristics of the memristor. The weight update algorithms for the linear and nonlinear adaptive filters are derived. Final computer simulation results show the effectiveness as well as fast convergence characteristics. Comparing with the adaptive nonlinear polynomial filters, the proposed nonlinear adaptive filters have less identification error.

  20. Efficient Kernel-Based Ensemble Gaussian Mixture Filtering

    KAUST Repository

    Liu, Bo

    2015-11-11

    We consider the Bayesian filtering problem for data assimilation following the kernel-based ensemble Gaussian-mixture filtering (EnGMF) approach introduced by Anderson and Anderson (1999). In this approach, the posterior distribution of the system state is propagated with the model using the ensemble Monte Carlo method, providing a forecast ensemble that is then used to construct a prior Gaussian-mixture (GM) based on the kernel density estimator. This results in two update steps: a Kalman filter (KF)-like update of the ensemble members and a particle filter (PF)-like update of the weights, followed by a resampling step to start a new forecast cycle. After formulating EnGMF for any observational operator, we analyze the influence of the bandwidth parameter of the kernel function on the covariance of the posterior distribution. We then focus on two aspects: i) the efficient implementation of EnGMF with (relatively) small ensembles, where we propose a new deterministic resampling strategy preserving the first two moments of the posterior GM to limit the sampling error; and ii) the analysis of the effect of the bandwidth parameter on contributions of KF and PF updates and on the weights variance. Numerical results using the Lorenz-96 model are presented to assess the behavior of EnGMF with deterministic resampling, study its sensitivity to different parameters and settings, and evaluate its performance against ensemble KFs. The proposed EnGMF approach with deterministic resampling suggests improved estimates in all tested scenarios, and is shown to require less localization and to be less sensitive to the choice of filtering parameters.

  1. CMS OnlineWeb-Based Monitoring

    CERN Document Server

    Wan, Zongru; Chakaberia, Irakli; Lopez-Perez, Juan Antonio; Maeshima, Kaori; Maruyama, Sho; Soha, Aron; Sulmanas, Balys; Wan, Zongru

    2012-01-01

    For large international High Energy Physics experiments, modern web technologies make the online monitoring of detector status, data acquisition status, trigger rates, luminosity, etc., accessible for the collaborators anywhere and anytime. This helps the collaborating experts monitor the status of the experiment, identify the problems, and improve data-taking efficiency. We present the Web-Based Monitoring project of the CMS experiment at the LHC of CERN. The data sources are relational databases and various messaging systems. The project provides a vast amount of in-depth information including real time data, historical trend, and correlations, in a user friendly way.

  2. Collaborative filtering recommendation model based on fuzzy clustering algorithm

    Science.gov (United States)

    Yang, Ye; Zhang, Yunhua

    2018-05-01

    As one of the most widely used algorithms in recommender systems, collaborative filtering algorithm faces two serious problems, which are the sparsity of data and poor recommendation effect in big data environment. In traditional clustering analysis, the object is strictly divided into several classes and the boundary of this division is very clear. However, for most objects in real life, there is no strict definition of their forms and attributes of their class. Concerning the problems above, this paper proposes to improve the traditional collaborative filtering model through the hybrid optimization of implicit semantic algorithm and fuzzy clustering algorithm, meanwhile, cooperating with collaborative filtering algorithm. In this paper, the fuzzy clustering algorithm is introduced to fuzzy clustering the information of project attribute, which makes the project belong to different project categories with different membership degrees, and increases the density of data, effectively reduces the sparsity of data, and solves the problem of low accuracy which is resulted from the inaccuracy of similarity calculation. Finally, this paper carries out empirical analysis on the MovieLens dataset, and compares it with the traditional user-based collaborative filtering algorithm. The proposed algorithm has greatly improved the recommendation accuracy.

  3. An e-Learning Collaborative Filtering Approach to Suggest Problems to Solve in Programming Online Judges

    Science.gov (United States)

    Toledo, Raciel Yera; Mota, Yailé Caballero

    2014-01-01

    The paper proposes a recommender system approach to cover online judge's domains. Online judges are e-learning tools that support the automatic evaluation of programming tasks done by individual users, and for this reason they are usually used for training students in programming contest and for supporting basic programming teachings. The…

  4. Collaborative Filtering Fusing Label Features Based on SDAE

    DEFF Research Database (Denmark)

    Huo, Huan; Liu, Xiufeng; Zheng, Deyuan

    2017-01-01

    problem, auxiliary information such as labels are utilized. Another approach of recommendation system is content-based model which can’t be directly integrated with CF-based model due to its inherent characteristics. Considering that deep learning algorithms are capable of extracting deep latent features......, this paper applies Stack Denoising Auto Encoder (SDAE) to content-based model and proposes LCF(Deep Learning for Collaborative Filtering) algorithm by combing CF-based model which fuses label features. Experiments on real-world data sets show that DLCF can largely overcome the sparsity problem...... and significantly improves the state of art approaches....

  5. The singular value filter: a general filter design strategy for PCA-based signal separation in medical ultrasound imaging.

    Science.gov (United States)

    Mauldin, F William; Lin, Dan; Hossack, John A

    2011-11-01

    A general filtering method, called the singular value filter (SVF), is presented as a framework for principal component analysis (PCA) based filter design in medical ultrasound imaging. The SVF approach operates by projecting the original data onto a new set of bases determined from PCA using singular value decomposition (SVD). The shape of the SVF weighting function, which relates the singular value spectrum of the input data to the filtering coefficients assigned to each basis function, is designed in accordance with a signal model and statistical assumptions regarding the underlying source signals. In this paper, we applied SVF for the specific application of clutter artifact rejection in diagnostic ultrasound imaging. SVF was compared to a conventional PCA-based filtering technique, which we refer to as the blind source separation (BSS) method, as well as a simple frequency-based finite impulse response (FIR) filter used as a baseline for comparison. The performance of each filter was quantified in simulated lesion images as well as experimental cardiac ultrasound data. SVF was demonstrated in both simulation and experimental results, over a wide range of imaging conditions, to outperform the BSS and FIR filtering methods in terms of contrast-to-noise ratio (CNR) and motion tracking performance. In experimental mouse heart data, SVF provided excellent artifact suppression with an average CNR improvement of 1.8 dB with over 40% reduction in displacement tracking error. It was further demonstrated from simulation and experimental results that SVF provided superior clutter rejection, as reflected in larger CNR values, when filtering was achieved using complex pulse-echo received data and non-binary filter coefficients.

  6. On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features

    Directory of Open Access Journals (Sweden)

    Mark Frogley

    2013-01-01

    Full Text Available To reduce the maintenance cost, avoid catastrophic failure, and improve the wind transmission system reliability, online condition monitoring system is critical important. In the real applications, many rotating mechanical faults, such as bearing surface defect, gear tooth crack, chipped gear tooth and so on generate impulsive signals. When there are these types of faults developing inside rotating machinery, each time the rotating components pass over the damage point, an impact force could be generated. The impact force will cause a ringing of the support structure at the structural natural frequency. By effectively detecting those periodic impulse signals, one group of rotating machine faults could be detected and diagnosed. However, in real wind turbine operations, impulsive fault signals are usually relatively weak to the background noise and vibration signals generated from other healthy components, such as shaft, blades, gears and so on. Moreover, wind turbine transmission systems work under dynamic operating conditions. This will further increase the difficulties in fault detection and diagnostics. Therefore, developing advanced signal processing methods to enhance the impulsive signals is in great needs.In this paper, an adaptive filtering technique will be applied for enhancing the fault impulse signals-to-noise ratio in wind turbine gear transmission systems. Multiple statistical features designed to quantify the impulsive signals of the processed signal are extracted for bearing fault detection. The multiple dimensional features are then transformed into one dimensional feature. A minimum error rate classifier will be designed based on the compressed feature to identify the gear transmission system with defect. Real wind turbine vibration signals will be used to demonstrate the effectiveness of the presented methodology.

  7. Scattering angle base filtering of the inversion gradients

    KAUST Repository

    Alkhalifah, Tariq Ali

    2014-01-01

    Full waveform inversion (FWI) requires a hierarchical approach based on the availability of low frequencies to maneuver the complex nonlinearity associated with the problem of velocity inversion. I develop a model gradient filter to help us access the parts of the gradient more suitable to combat this potential nonlinearity. The filter is based on representing the gradient in the time-lag normalized domain, in which low scattering angles of the gradient update are initially muted. The result are long-wavelength updates controlled by the ray component of the wavefield. In this case, even 10 Hz data can produce near zero wavelength updates suitable for a background correction of the model. Allowing smaller scattering angle to contribute provides higher resolution information to the model.

  8. A new iterative speech enhancement scheme based on Kalman filtering

    DEFF Research Database (Denmark)

    Li, Chunjian; Andersen, Søren Vang

    2005-01-01

    for a high temporal resolution estimation of this variance. A Local Variance Estimator based on a Prediction Error Kalman Filter is designed for this high temporal resolution variance estimation. To achieve fast convergence and avoid local maxima of the likelihood function, a Weighted Power Spectral....... Performance comparison shows significant improvement over the baseline EM algorithm in terms of three objective measures. Listening test indicates an improvement in subjective quality due to a significant reduction of musical noise compared to the baseline EM algorithm....

  9. Description of an identification method of thermocouple time constant based on application of recursive numerical filtering to temperature fluctuation

    International Nuclear Information System (INIS)

    Bernardin, B.; Le Guillou, G.; Parcy, JP.

    1981-04-01

    Usual spectral methods, based on temperature fluctuation analysis, aiming at thermocouple time constant identification are using an equipment too much sophisticated for on-line application. It is shown that numerical filtering is optimal for this application, the equipment is simpler than for spectral methods and less samples of signals are needed for the same accuracy. The method is described and a parametric study was performed using a temperature noise simulator [fr

  10. Remaining useful life prediction based on noisy condition monitoring signals using constrained Kalman filter

    International Nuclear Information System (INIS)

    Son, Junbo; Zhou, Shiyu; Sankavaram, Chaitanya; Du, Xinyu; Zhang, Yilu

    2016-01-01

    In this paper, a statistical prognostic method to predict the remaining useful life (RUL) of individual units based on noisy condition monitoring signals is proposed. The prediction accuracy of existing data-driven prognostic methods depends on the capability of accurately modeling the evolution of condition monitoring (CM) signals. Therefore, it is inevitable that the RUL prediction accuracy depends on the amount of random noise in CM signals. When signals are contaminated by a large amount of random noise, RUL prediction even becomes infeasible in some cases. To mitigate this issue, a robust RUL prediction method based on constrained Kalman filter is proposed. The proposed method models the CM signals subject to a set of inequality constraints so that satisfactory prediction accuracy can be achieved regardless of the noise level of signal evolution. The advantageous features of the proposed RUL prediction method is demonstrated by both numerical study and case study with real world data from automotive lead-acid batteries. - Highlights: • A computationally efficient constrained Kalman filter is proposed. • Proposed filter is integrated into an online failure prognosis framework. • A set of proper constraints significantly improves the failure prediction accuracy. • Promising results are reported in the application of battery failure prognosis.

  11. Adaptive probabilistic collocation based Kalman filter for unsaturated flow problem

    Science.gov (United States)

    Man, J.; Li, W.; Zeng, L.; Wu, L.

    2015-12-01

    The ensemble Kalman filter (EnKF) has gained popularity in hydrological data assimilation problems. As a Monte Carlo based method, a relatively large ensemble size is usually required to guarantee the accuracy. As an alternative approach, the probabilistic collocation based Kalman filter (PCKF) employs the Polynomial Chaos to approximate the original system. In this way, the sampling error can be reduced. However, PCKF suffers from the so called "cure of dimensionality". When the system nonlinearity is strong and number of parameters is large, PCKF is even more computationally expensive than EnKF. Motivated by recent developments in uncertainty quantification, we propose a restart adaptive probabilistic collocation based Kalman filter (RAPCKF) for data assimilation in unsaturated flow problem. During the implementation of RAPCKF, the important parameters are identified and active PCE basis functions are adaptively selected. The "restart" technology is used to alleviate the inconsistency between model parameters and states. The performance of RAPCKF is tested by unsaturated flow numerical cases. It is shown that RAPCKF is more efficient than EnKF with the same computational cost. Compared with the traditional PCKF, the RAPCKF is more applicable in strongly nonlinear and high dimensional problems.

  12. Supervised Filter Learning for Representation Based Face Recognition.

    Directory of Open Access Journals (Sweden)

    Chao Bi

    Full Text Available Representation based classification methods, such as Sparse Representation Classification (SRC and Linear Regression Classification (LRC have been developed for face recognition problem successfully. However, most of these methods use the original face images without any preprocessing for recognition. Thus, their performances may be affected by some problematic factors (such as illumination and expression variances in the face images. In order to overcome this limitation, a novel supervised filter learning algorithm is proposed for representation based face recognition in this paper. The underlying idea of our algorithm is to learn a filter so that the within-class representation residuals of the faces' Local Binary Pattern (LBP features are minimized and the between-class representation residuals of the faces' LBP features are maximized. Therefore, the LBP features of filtered face images are more discriminative for representation based classifiers. Furthermore, we also extend our algorithm for heterogeneous face recognition problem. Extensive experiments are carried out on five databases and the experimental results verify the efficacy of the proposed algorithm.

  13. Web-based Factors Affecting Online Purchasing Behaviour

    Science.gov (United States)

    Ariff, Mohd Shoki Md; Sze Yan, Ng; Zakuan, Norhayati; Zaidi Bahari, Ahamad; Jusoh, Ahmad

    2013-06-01

    The growing use of internet and online purchasing among young consumers in Malaysia provides a huge prospect in e-commerce market, specifically for B2C segment. In this market, if E-marketers know the web-based factors affecting online buyers' behaviour, and the effect of these factors on behaviour of online consumers, then they can develop their marketing strategies to convert potential customers into active one, while retaining existing online customers. Review of previous studies related to the online purchasing behaviour in B2C market has point out that the conceptualization and empirical validation of the online purchasing behaviour of Information and Communication Technology (ICT) literate users, or ICT professional, in Malaysia has not been clearly addressed. This paper focuses on (i) web-based factors which online buyers (ICT professional) keep in mind while shopping online; and (ii) the effect of web-based factors on online purchasing behaviour. Based on the extensive literature review, a conceptual framework of 24 items of five factors was constructed to determine web-based factors affecting online purchasing behaviour of ICT professional. Analysis of data was performed based on the 310 questionnaires, which were collected using a stratified random sampling method, from ICT undergraduate students in a public university in Malaysia. The Exploratory factor analysis performed showed that five factors affecting online purchase behaviour are Information Quality, Fulfilment/Reliability/Customer Service, Website Design, Quick and Details, and Privacy/Security. The result of Multiple Regression Analysis indicated that Information Quality, Quick and Details, and Privacy/Security affect positively online purchase behaviour. The results provide a usable model for measuring web-based factors affecting buyers' online purchase behaviour in B2C market, as well as for online shopping companies to focus on the factors that will increase customers' online purchase.

  14. Web-based Factors Affecting Online Purchasing Behaviour

    International Nuclear Information System (INIS)

    Ariff, Mohd Shoki Md; Yan, Ng Sze; Zakuan, Norhayati; Bahari, Ahamad Zaidi; Jusoh, Ahmad

    2013-01-01

    The growing use of internet and online purchasing among young consumers in Malaysia provides a huge prospect in e-commerce market, specifically for B2C segment. In this market, if E-marketers know the web-based factors affecting online buyers' behaviour, and the effect of these factors on behaviour of online consumers, then they can develop their marketing strategies to convert potential customers into active one, while retaining existing online customers. Review of previous studies related to the online purchasing behaviour in B2C market has point out that the conceptualization and empirical validation of the online purchasing behaviour of Information and Communication Technology (ICT) literate users, or ICT professional, in Malaysia has not been clearly addressed. This paper focuses on (i) web-based factors which online buyers (ICT professional) keep in mind while shopping online; and (ii) the effect of web-based factors on online purchasing behaviour. Based on the extensive literature review, a conceptual framework of 24 items of five factors was constructed to determine web-based factors affecting online purchasing behaviour of ICT professional. Analysis of data was performed based on the 310 questionnaires, which were collected using a stratified random sampling method, from ICT undergraduate students in a public university in Malaysia. The Exploratory factor analysis performed showed that five factors affecting online purchase behaviour are Information Quality, Fulfilment/Reliability/Customer Service, Website Design, Quick and Details, and Privacy/Security. The result of Multiple Regression Analysis indicated that Information Quality, Quick and Details, and Privacy/Security affect positively online purchase behaviour. The results provide a usable model for measuring web-based factors affecting buyers' online purchase behaviour in B2C market, as well as for online shopping companies to focus on the factors that will increase customers' online purchase.

  15. An active damping method based on biquad digital filter for parallel grid-interfacing inverters with LCL filters

    DEFF Research Database (Denmark)

    Lu, Xiaonan; Sun, Kai; Huang, Lipei

    2014-01-01

    around the switching frequency and its multiples. Although the LCL-filters have several advantages compared to single inductance filter, its resonance problem should be noticed. Conventionally, the resonance analysis is mainly focused on the single inverter system, whereas in a renewable energy system...... to the conventional active damping approaches, the biquad filter based active damping method does not require additional sensors and control loops. Meanwhile, the multiple instable closed-loop poles of the parallel inverter system can be moved to the stable region simultaneously. Real-time simulations based on d...

  16. Integrated reconfigurable photonic filters based on interferometric fractional Hilbert transforms.

    Science.gov (United States)

    Sima, C; Cai, B; Liu, B; Gao, Y; Yu, Y; Gates, J C; Zervas, M N; Smith, P G R; Liu, D

    2017-10-01

    In this paper, we present integrated reconfigurable photonic filters using fractional Hilbert transformers (FrHTs) and optical phase tuning structure within the silica-on-silicon platform. The proposed structure, including grating-based FrHTs, an X-coupler, and a pair of thermal tuning filaments, is fabricated through the direct UV grating writing technique. The thermal tuning effect is realized by the controllable microheaters located on the two arms of the X-coupler. We investigate the 200 GHz maximum bandwidth photonic FrHTs based on apodized planar Bragg gratings, and analyze the reflection spectrum responses. Through device integration and thermal modulation, the device could operate as photonic notch filters with 5 GHz linewidth and controllable single sideband suppression filters with measured 12 dB suppression ratio. A 50 GHz instantaneous frequency measuring system using this device is also schematically proposed and analyzed with potential 3 dB measurement improvement. The device could be configured with these multiple functions according to need. The reconfigurable structure has great potential in ultrafast all-optical signal processing fields.

  17. TUNNEL POINT CLOUD FILTERING METHOD BASED ON ELLIPTIC CYLINDRICAL MODEL

    Directory of Open Access Journals (Sweden)

    N. Zhu

    2016-06-01

    Full Text Available The large number of bolts and screws that attached to the subway shield ring plates, along with the great amount of accessories of metal stents and electrical equipments mounted on the tunnel walls, make the laser point cloud data include lots of non-tunnel section points (hereinafter referred to as non-points, therefore affecting the accuracy for modeling and deformation monitoring. This paper proposed a filtering method for the point cloud based on the elliptic cylindrical model. The original laser point cloud data was firstly projected onto a horizontal plane, and a searching algorithm was given to extract the edging points of both sides, which were used further to fit the tunnel central axis. Along the axis the point cloud was segmented regionally, and then fitted as smooth elliptic cylindrical surface by means of iteration. This processing enabled the automatic filtering of those inner wall non-points. Experiments of two groups showed coincident results, that the elliptic cylindrical model based method could effectively filter out the non-points, and meet the accuracy requirements for subway deformation monitoring. The method provides a new mode for the periodic monitoring of tunnel sections all-around deformation in subways routine operation and maintenance.

  18. Acoustic frequency filter based on anisotropic topological phononic crystals

    KAUST Repository

    Chen, Zeguo

    2017-11-02

    We present a design of acoustic frequency filter based on a two-dimensional anisotropic phononic crystal. The anisotropic band structure exhibits either a directional or a combined (global + directional) bandgap at certain frequency regions, depending on the geometry. When the time-reversal symmetry is broken, it may introduce a topologically nontrivial bandgap. The induced nontrivial bandgap and the original directional bandgap result in various interesting wave propagation behaviors, such as frequency filter. We develop a tight-binding model to characterize the effective Hamiltonian of the system, from which the contribution of anisotropy is explicitly shown. Different from the isotropic cases, the Zeeman-type splitting is not linear and the anisotropic bandgap makes it possible to achieve anisotropic propagation characteristics along different directions and at different frequencies.

  19. Chaotic secure communication based on strong tracking filtering

    International Nuclear Information System (INIS)

    Li Xiongjie; Xu Zhengguo; Zhou Donghua

    2008-01-01

    A scheme for implementing secure communication based on chaotic maps and strong tracking filter (STF) is presented, and a modified STF algorithm with message estimation is developed for the special requirement of chaotic secure communication. At the emitter, the message symbol is modulated by chaotic mapping and is output through a nonlinear function. At the receiver, the driving signal is received and the message symbol is recovered dynamically by the STF with estimation of message symbol. Simulation results of Holmes map demonstrate that when message symbols are binary codes, STF can effectively recover the codes of the message from the noisy chaotic signals. Compared with the extended Kalman filter (EKF), STF has a lower bit error rate

  20. Acoustic frequency filter based on anisotropic topological phononic crystals

    KAUST Repository

    Chen, Zeguo; Zhao, Jiajun; Mei, Jun; Wu, Ying

    2017-01-01

    We present a design of acoustic frequency filter based on a two-dimensional anisotropic phononic crystal. The anisotropic band structure exhibits either a directional or a combined (global + directional) bandgap at certain frequency regions, depending on the geometry. When the time-reversal symmetry is broken, it may introduce a topologically nontrivial bandgap. The induced nontrivial bandgap and the original directional bandgap result in various interesting wave propagation behaviors, such as frequency filter. We develop a tight-binding model to characterize the effective Hamiltonian of the system, from which the contribution of anisotropy is explicitly shown. Different from the isotropic cases, the Zeeman-type splitting is not linear and the anisotropic bandgap makes it possible to achieve anisotropic propagation characteristics along different directions and at different frequencies.

  1. Microstrip Cross-coupled Interdigital SIR Based Bandpass Filter

    Directory of Open Access Journals (Sweden)

    R. K. Maharjan

    2012-09-01

    Full Text Available A simple and compact 4.9 GHz bandpass filter for C-band applications is proposed. This paper presents a novel microstrip cross-coupled interdigital half-wavelength stepped impedance resonator (SIR based bandpass filter (BPF.The designed structure is similar to that of a combination of two parallel interdigital capacitors. The scattering parameters of the structure are measured using vector network analyzer (VNA. The self generated capacitive and inductive reactances within the interdigital resonators exhibited in a resonance frequency of 4.9 GHz. The resonant frequency and bandwidth of the capacitive cross-coupled resonator is directly optimized from the physical arrangement of the resonators. The measured insertion loss (S21 and return loss (S11 were 0.3 dB and 28 dB, respectively, at resonance frequency which were almost close to the simulation results.

  2. Kalman filter-based EM-optical sensor fusion for needle deflection estimation.

    Science.gov (United States)

    Jiang, Baichuan; Gao, Wenpeng; Kacher, Daniel; Nevo, Erez; Fetics, Barry; Lee, Thomas C; Jayender, Jagadeesan

    2018-04-01

    In many clinical procedures such as cryoablation that involves needle insertion, accurate placement of the needle's tip at the desired target is the major issue for optimizing the treatment and minimizing damage to the neighboring anatomy. However, due to the interaction force between the needle and tissue, considerable error in intraoperative tracking of the needle tip can be observed as needle deflects. In this paper, measurements data from an optical sensor at the needle base and a magnetic resonance (MR) gradient field-driven electromagnetic (EM) sensor placed 10 cm from the needle tip are used within a model-integrated Kalman filter-based sensor fusion scheme. Bending model-based estimations and EM-based direct estimation are used as the measurement vectors in the Kalman filter, thus establishing an online estimation approach. Static tip bending experiments show that the fusion method can reduce the mean error of the tip position estimation from 29.23 mm of the optical sensor-based approach to 3.15 mm of the fusion-based approach and from 39.96 to 6.90 mm, at the MRI isocenter and the MRI entrance, respectively. This work established a novel sensor fusion scheme that incorporates model information, which enables real-time tracking of needle deflection with MRI compatibility, in a free-hand operating setup.

  3. Artificial Fish Swarm Algorithm-Based Particle Filter for Li-Ion Battery Life Prediction

    Directory of Open Access Journals (Sweden)

    Ye Tian

    2014-01-01

    Full Text Available An intelligent online prognostic approach is proposed for predicting the remaining useful life (RUL of lithium-ion (Li-ion batteries based on artificial fish swarm algorithm (AFSA and particle filter (PF, which is an integrated approach combining model-based method with data-driven method. The parameters, used in the empirical model which is based on the capacity fade trends of Li-ion batteries, are identified dependent on the tracking ability of PF. AFSA-PF aims to improve the performance of the basic PF. By driving the prior particles to the domain with high likelihood, AFSA-PF allows global optimization, prevents particle degeneracy, thereby improving particle distribution and increasing prediction accuracy and algorithm convergence. Data provided by NASA are used to verify this approach and compare it with basic PF and regularized PF. AFSA-PF is shown to be more accurate and precise.

  4. Coarse Alignment Technology on Moving base for SINS Based on the Improved Quaternion Filter Algorithm.

    Science.gov (United States)

    Zhang, Tao; Zhu, Yongyun; Zhou, Feng; Yan, Yaxiong; Tong, Jinwu

    2017-06-17

    Initial alignment of the strapdown inertial navigation system (SINS) is intended to determine the initial attitude matrix in a short time with certain accuracy. The alignment accuracy of the quaternion filter algorithm is remarkable, but the convergence rate is slow. To solve this problem, this paper proposes an improved quaternion filter algorithm for faster initial alignment based on the error model of the quaternion filter algorithm. The improved quaternion filter algorithm constructs the K matrix based on the principle of optimal quaternion algorithm, and rebuilds the measurement model by containing acceleration and velocity errors to make the convergence rate faster. A doppler velocity log (DVL) provides the reference velocity for the improved quaternion filter alignment algorithm. In order to demonstrate the performance of the improved quaternion filter algorithm in the field, a turntable experiment and a vehicle test are carried out. The results of the experiments show that the convergence rate of the proposed improved quaternion filter is faster than that of the tradition quaternion filter algorithm. In addition, the improved quaternion filter algorithm also demonstrates advantages in terms of correctness, effectiveness, and practicability.

  5. Performance-Based Technology Selection Filter description report

    International Nuclear Information System (INIS)

    O'Brien, M.C.; Morrison, J.L.; Morneau, R.A.; Rudin, M.J.; Richardson, J.G.

    1992-05-01

    A formal methodology has been developed for identifying technology gaps and assessing innovative or postulated technologies for inclusion in proposed Buried Waste Integrated Demonstration (BWID) remediation systems. Called the Performance-Based Technology Selection Filter, the methodology provides a formalized selection process where technologies and systems are rated and assessments made based on performance measures, and regulatory and technical requirements. The results are auditable, and can be validated with field data. This analysis methodology will be applied to the remedial action of transuranic contaminated waste pits and trenches buried at the Idaho National Engineering Laboratory (INEL)

  6. Information filtering based on corrected redundancy-eliminating mass diffusion.

    Science.gov (United States)

    Zhu, Xuzhen; Yang, Yujie; Chen, Guilin; Medo, Matus; Tian, Hui; Cai, Shi-Min

    2017-01-01

    Methods used in information filtering and recommendation often rely on quantifying the similarity between objects or users. The used similarity metrics often suffer from similarity redundancies arising from correlations between objects' attributes. Based on an unweighted undirected object-user bipartite network, we propose a Corrected Redundancy-Eliminating similarity index (CRE) which is based on a spreading process on the network. Extensive experiments on three benchmark data sets-Movilens, Netflix and Amazon-show that when used in recommendation, the CRE yields significant improvements in terms of recommendation accuracy and diversity. A detailed analysis is presented to unveil the origins of the observed differences between the CRE and mainstream similarity indices.

  7. Performance-Based Technology Selection Filter description report

    Energy Technology Data Exchange (ETDEWEB)

    O' Brien, M.C.; Morrison, J.L.; Morneau, R.A.; Rudin, M.J.; Richardson, J.G.

    1992-05-01

    A formal methodology has been developed for identifying technology gaps and assessing innovative or postulated technologies for inclusion in proposed Buried Waste Integrated Demonstration (BWID) remediation systems. Called the Performance-Based Technology Selection Filter, the methodology provides a formalized selection process where technologies and systems are rated and assessments made based on performance measures, and regulatory and technical requirements. The results are auditable, and can be validated with field data. This analysis methodology will be applied to the remedial action of transuranic contaminated waste pits and trenches buried at the Idaho National Engineering Laboratory (INEL).

  8. A comparative study of Kalman filter and Linear Matrix Inequality based H infinity filter for SPND delay compensation

    International Nuclear Information System (INIS)

    Tamboli, P.K.; Duttagupta, Siddhartha P.; Roy, Kallol

    2016-01-01

    Highlights: • Derivation for delay compensation algorithm using recursive Kalman filter. • Derivation for delay compensation algorithm using Linear Matrix Inequality based H infinity filter. • Process modeling suitable for delay compensation. • Dynamic tuning of the delay compensation algorithm for both Kalman and H infinity filter. • Simulations and trade-off curve for Kalman and H infinity filter. - Abstract: This paper deals with delay compensation of vanadium Self Powered Neutron Detectors (SPNDs) using Linear Matrix Inequality (LMI) based H-infinity filtering method and compares the results with Kalman filtering method. The entire study is established upon the framework of neutron flux estimation in large core Pressurized Heavy Water Reactor (PHWR) in which delayed SPNDs such as vanadium SPNDs are used as in-core flux monitoring detectors. The use of vanadium SPNDs are limited to 3-D flux mapping despite of providing better Signal to Noise Ratio as compared to other prompt SPNDs, due to their small prompt component in the signal. The use of an appropriate delay compensation technique has been always considered to be an effective strategy to build a prompt and accurate estimate of the neutron flux. We also indicate the noise-response trade-off curve for both the techniques. Since all the delay compensation algorithms always suffer from noise amplification, we propose an efficient adaptive parameter tuning technique for improving performance of the filtering algorithm against noise in the measurement.

  9. Parallel Kalman filter track fit based on vector classes

    Energy Technology Data Exchange (ETDEWEB)

    Kisel, Ivan [GSI Helmholtzzentrum fuer Schwerionenforschung GmbH (Germany); Kretz, Matthias [Kirchhoff-Institut fuer Physik, Ruprecht-Karls Universitaet, Heidelberg (Germany); Kulakov, Igor [Goethe-Universitaet, Frankfurt am Main (Germany); National Taras Shevchenko University, Kyiv (Ukraine)

    2010-07-01

    Modern high energy physics experiments have to process terabytes of input data produced in particle collisions. The core of the data reconstruction in high energy physics is the Kalman filter. Therefore, developing the fast Kalman filter algorithm, which uses maximum available power of modern processors, is important, in particular for initial selection of events interesting for the new physics. One of processors features, which can speed up the algorithm, is a SIMD instruction set, which allows to pack several data items in one register and operate on all of them in one go, thus achieving more operations per clock cycle. Therefore a flexible and useful interface, which uses the SIMD instruction set on different CPU and GPU processors architectures, has been realized as a vector classes library. The Kalman filter based track fitting algorithm has been implemented with use of the vector classes. Fitting quality tests show good results with the residuals equal to 49 {mu}m and 44 {mu}m for x and y track parameters and relative momentum resolution of 0.7%. The fitting time of 0.053 {mu}s per track has been achieved on Intel Xeon X5550 with 8 cores at 2.6 GHz by using in addition Intel Threading Building Blocks.

  10. Aggregated wind power generation probabilistic forecasting based on particle filter

    International Nuclear Information System (INIS)

    Li, Pai; Guan, Xiaohong; Wu, Jiang

    2015-01-01

    Highlights: • A new method for probabilistic forecasting of aggregated wind power generation. • A dynamic system is established based on a numerical weather prediction model. • The new method handles the non-Gaussian and time-varying wind power uncertainties. • Particle filter is applied to forecast predictive densities of wind generation. - Abstract: Probability distribution of aggregated wind power generation in a region is one of important issues for power system daily operation. This paper presents a novel method to forecast the predictive densities of the aggregated wind power generation from several geographically distributed wind farms, considering the non-Gaussian and non-stationary characteristics in wind power uncertainties. Based on a mesoscale numerical weather prediction model, a dynamic system is established to formulate the relationship between the atmospheric and near-surface wind fields of geographically distributed wind farms. A recursively backtracking framework based on the particle filter is applied to estimate the atmospheric state with the near-surface wind power generation measurements, and to forecast the possible samples of the aggregated wind power generation. The predictive densities of the aggregated wind power generation are then estimated based on these predicted samples by a kernel density estimator. In case studies, the new method presented is tested on a 9 wind farms system in Midwestern United States. The testing results that the new method can provide competitive interval forecasts for the aggregated wind power generation with conventional statistical based models, which validates the effectiveness of the new method

  11. Active RC filter based implementation analysis part of two channel hybrid filter bank

    Directory of Open Access Journals (Sweden)

    Stojanović Vidosav

    2014-01-01

    Full Text Available In the present paper, a new design method for continuous-time powersymmetric active RC filters for Hybrid Filter Bank (HFB is proposed. Some theoretical properties of continious-time power-symmetric filters bank in a more general perspective are studied. This includes the derivation of a new general analytical form, and a study of poles and zeros locations in s-plane. In the proposed design method the analytic solution of filter coefficients is solved in sdomain using only one nonlinear equation Finally, the proposed approximation is compared to standard approximations. It was shown that attenuation and group delay characteristic of the proposed filter lie between Butterworth and elliptic characteristics. [Projekat Ministarstva nauke Republike Srbije, br. 32009TR

  12. Detail Enhancement for Infrared Images Based on Propagated Image Filter

    Directory of Open Access Journals (Sweden)

    Yishu Peng

    2016-01-01

    Full Text Available For displaying high-dynamic-range images acquired by thermal camera systems, 14-bit raw infrared data should map into 8-bit gray values. This paper presents a new method for detail enhancement of infrared images to display the image with a relatively satisfied contrast and brightness, rich detail information, and no artifacts caused by the image processing. We first adopt a propagated image filter to smooth the input image and separate the image into the base layer and the detail layer. Then, we refine the base layer by using modified histogram projection for compressing. Meanwhile, the adaptive weights derived from the layer decomposition processing are used as the strict gain control for the detail layer. The final display result is obtained by recombining the two modified layers. Experimental results on both cooled and uncooled infrared data verify that the proposed method outperforms the method based on log-power histogram modification and bilateral filter-based detail enhancement in both detail enhancement and visual effect.

  13. Scattering angle-based filtering via extension in velocity

    KAUST Repository

    Kazei, Vladimir; Tessmer, Ekkehart; Alkhalifah, Tariq

    2016-01-01

    The scattering angle between the source and receiver wavefields can be utilized in full-waveform inversion (FWI) and in reverse-time migration (RTM) for regularization and quality control or to remove low frequency artifacts. The access to the scattering angle information is costly as the relation between local image features and scattering angles has non-stationary nature. For the purpose of a more efficient scattering angle information extraction, we develop techniques that utilize the simplicity of the scattering angle based filters for constantvelocity background models. We split the background velocity model into several domains with different velocity ranges, generating an

  14. Scattering angle-based filtering via extension in velocity

    KAUST Repository

    Kazei, Vladimir

    2016-09-06

    The scattering angle between the source and receiver wavefields can be utilized in full-waveform inversion (FWI) and in reverse-time migration (RTM) for regularization and quality control or to remove low frequency artifacts. The access to the scattering angle information is costly as the relation between local image features and scattering angles has non-stationary nature. For the purpose of a more efficient scattering angle information extraction, we develop techniques that utilize the simplicity of the scattering angle based filters for constantvelocity background models. We split the background velocity model into several domains with different velocity ranges, generating an

  15. Spatial filters on demand based on aperiodic Photonic Crystals

    Energy Technology Data Exchange (ETDEWEB)

    Gailevicius, Darius; Purlys, Vytautas; Peckus, Martynas; Gadonas, Roaldas [Laser Research Center, Department of Quantum Electronics, Vilnius University (Lithuania); Staliunas, Kestutis [DONLL, Departament de Fisica, Universitat Politecnica de Catalunya (UPC), Terrassa (Spain); Institucio Catalana de Recerca i Estudis Avancats (ICREA), Barcelona (Spain)

    2017-08-15

    Photonic Crystal spatial filters, apart from stand-alone spatial filtering function, can also suppress multi-transverse-mode operation in laser resonators. Here it is shown that such photonic crystals can be designed by solving the inverse problem: for a given spatial filtering profile. Optimized Photonic Crystal filters were fabricated in photosensitive glass. Experiments have shown that such filters provide a more pronounced filtering effect for total and partial transmissivity conditions. (copyright 2017 by WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  16. Identifying city PV roof resource based on Gabor filter

    Science.gov (United States)

    Ruhang, Xu; Zhilin, Liu; Yong, Huang; Xiaoyu, Zhang

    2017-06-01

    To identify a city’s PV roof resources, the area and ownership distribution of residential buildings in an urban district should be assessed. To achieve this assessment, remote sensing data analysing is a promising approach. Urban building roof area estimation is a major topic for remote sensing image information extraction. There are normally three ways to solve this problem. The first way is pixel-based analysis, which is based on mathematical morphology or statistical methods; the second way is object-based analysis, which is able to combine semantic information and expert knowledge; the third way is signal-processing view method. This paper presented a Gabor filter based method. This result shows that the method is fast and with proper accuracy.

  17. a Voxel-Based Filtering Algorithm for Mobile LIDAR Data

    Science.gov (United States)

    Qin, H.; Guan, G.; Yu, Y.; Zhong, L.

    2018-04-01

    This paper presents a stepwise voxel-based filtering algorithm for mobile LiDAR data. In the first step, to improve computational efficiency, mobile LiDAR points, in xy-plane, are first partitioned into a set of two-dimensional (2-D) blocks with a given block size, in each of which all laser points are further organized into an octree partition structure with a set of three-dimensional (3-D) voxels. Then, a voxel-based upward growing processing is performed to roughly separate terrain from non-terrain points with global and local terrain thresholds. In the second step, the extracted terrain points are refined by computing voxel curvatures. This voxel-based filtering algorithm is comprehensively discussed in the analyses of parameter sensitivity and overall performance. An experimental study performed on multiple point cloud samples, collected by different commercial mobile LiDAR systems, showed that the proposed algorithm provides a promising solution to terrain point extraction from mobile point clouds.

  18. Automated Dimension Determination for NMF-based Incremental Collaborative Filtering

    Directory of Open Access Journals (Sweden)

    Xiwei Wang

    2015-12-01

    Full Text Available The nonnegative matrix factorization (NMF based collaborative filtering t e chniques h a ve a c hieved great success in product recommendations. It is well known that in NMF, the dimensions of the factor matrices have to be determined in advance. Moreover, data is growing fast; thus in some cases, the dimensions need to be changed to reduce the approximation error. The recommender systems should be capable of updating new data in a timely manner without sacrificing the prediction accuracy. In this paper, we propose an NMF based data update approach with automated dimension determination for collaborative filtering purposes. The approach can determine the dimensions of the factor matrices and update them automatically. It exploits the nearest neighborhood based clustering algorithm to cluster users and items according to their auxiliary information, and uses the clusters as the constraints in NMF. The dimensions of the factor matrices are associated with the cluster quantities. When new data becomes available, the incremental clustering algorithm determines whether to increase the number of clusters or merge the existing clusters. Experiments on three different datasets (MovieLens, Sushi, and LibimSeTi were conducted to examine the proposed approach. The results show that our approach can update the data quickly and provide encouraging prediction accuracy.

  19. Filter Selection for Optimizing the Spectral Sensitivity of Broadband Multispectral Cameras Based on Maximum Linear Independence.

    Science.gov (United States)

    Li, Sui-Xian

    2018-05-07

    Previous research has shown that the effectiveness of selecting filter sets from among a large set of commercial broadband filters by a vector analysis method based on maximum linear independence (MLI). However, the traditional MLI approach is suboptimal due to the need to predefine the first filter of the selected filter set to be the maximum ℓ₂ norm among all available filters. An exhaustive imaging simulation with every single filter serving as the first filter is conducted to investigate the features of the most competent filter set. From the simulation, the characteristics of the most competent filter set are discovered. Besides minimization of the condition number, the geometric features of the best-performed filter set comprise a distinct transmittance peak along the wavelength axis of the first filter, a generally uniform distribution for the peaks of the filters and substantial overlaps of the transmittance curves of the adjacent filters. Therefore, the best-performed filter sets can be recognized intuitively by simple vector analysis and just a few experimental verifications. A practical two-step framework for selecting optimal filter set is recommended, which guarantees a significant enhancement of the performance of the systems. This work should be useful for optimizing the spectral sensitivity of broadband multispectral imaging sensors.

  20. Filter Selection for Optimizing the Spectral Sensitivity of Broadband Multispectral Cameras Based on Maximum Linear Independence

    Directory of Open Access Journals (Sweden)

    Sui-Xian Li

    2018-05-01

    Full Text Available Previous research has shown that the effectiveness of selecting filter sets from among a large set of commercial broadband filters by a vector analysis method based on maximum linear independence (MLI. However, the traditional MLI approach is suboptimal due to the need to predefine the first filter of the selected filter set to be the maximum ℓ2 norm among all available filters. An exhaustive imaging simulation with every single filter serving as the first filter is conducted to investigate the features of the most competent filter set. From the simulation, the characteristics of the most competent filter set are discovered. Besides minimization of the condition number, the geometric features of the best-performed filter set comprise a distinct transmittance peak along the wavelength axis of the first filter, a generally uniform distribution for the peaks of the filters and substantial overlaps of the transmittance curves of the adjacent filters. Therefore, the best-performed filter sets can be recognized intuitively by simple vector analysis and just a few experimental verifications. A practical two-step framework for selecting optimal filter set is recommended, which guarantees a significant enhancement of the performance of the systems. This work should be useful for optimizing the spectral sensitivity of broadband multispectral imaging sensors.

  1. Estimation of the Diesel Particulate Filter Soot Load Based on an Equivalent Circuit Model

    Directory of Open Access Journals (Sweden)

    Yanting Du

    2018-02-01

    Full Text Available In order to estimate the diesel particulate filter (DPF soot load and improve the accuracy of regeneration timing, a novel method based on an equivalent circuit model is proposed based on the electric-fluid analogy. This proposed method can reduce the impact of the engine transient operation on the soot load, accurately calculate the flow resistance, and improve the estimation accuracy of the soot load. Firstly, the least square method is used to identify the flow resistance based on the World Harmonized Transient Cycle (WHTC test data, and the relationship between flow resistance, exhaust temperature and soot load is established. Secondly, the online estimation of the soot load is achieved by using the dual extended Kalman filter (DEKF. The results show that this method has good convergence and robustness with the maximal absolute error of 0.2 g/L at regeneration timing, which can meet engineering requirements. Additionally, this method can estimate the soot load under engine transient operating conditions and avoids a large number of experimental tests, extensive calibration and the analysis of complex chemical reactions required in traditional methods.

  2. Self-collimation-based photonic crystal notch filters

    International Nuclear Information System (INIS)

    Lee, Sun-Goo; Kim, Seong-Han; Kee, Chul-Sik; Kim, Kap-Joong

    2017-01-01

    We introduce a design concept of an optical notch filter (NF) utilizing two perfectly reflecting mirrors and a beam splitter. Based on the new design concept, a photonic crystal (PC)-NF based on the self-collimation phenomenon in a two-dimensional PC is proposed and studied through finite-difference time-domain simulations and experimental measurements in a microwave region. The transmission properties of the self-collimation-based PC-NF were demonstrated to be controlled by adjusting the values of parameters such as the radius of rods in the line-defect beam splitter, distance between the two perfectly reflecting mirrors, and radius of rods on the outermost surface of the perfectly reflecting mirrors. Our results indicate that the proposed design concept could provide a new approach to manipulate light propagation, and the PC-NF could increase the applicability of the self-collimation phenomenon in a PC. (paper)

  3. On-Line Voltage Stability Assessment based on PMU Measurements

    DEFF Research Database (Denmark)

    Garcia-Valle, Rodrigo; P. Da Silva, Luiz C.; Nielsen, Arne Hejde

    2009-01-01

    This paper presents a method for on-line monitoring of risk voltage collapse based on synchronised phasor measurement. As there is no room for intensive computation and analysis in real-time, the method is based on the combination of off-line computation and on-line monitoring, which are correlat...

  4. RSSI based indoor tracking in sensor networks using Kalman filters

    DEFF Research Database (Denmark)

    Tøgersen, Frede Aakmann; Skjøth, Flemming; Munksgaard, Lene

    2010-01-01

    We propose an algorithm for estimating positions of devices in a sensor network using Kalman filtering techniques. The specific area of application is monitoring the movements of cows in a barn. The algorithm consists of two filters. The first filter enhances the signal-to-noise ratio...

  5. Scheme of adaptive polarization filtering based on Kalman model

    Institute of Scientific and Technical Information of China (English)

    Song Lizhong; Qi Haiming; Qiao Xiaolin; Meng Xiande

    2006-01-01

    A new kind of adaptive polarization filtering algorithm in order to suppress the angle cheating interference for the active guidance radar is presented. The polarization characteristic of the interference is dynamically tracked by using Kalman estimator under variable environments with time. The polarization filter parameters are designed according to the polarization characteristic of the interference, and the polarization filtering is finished in the target cell. The system scheme of adaptive polarization filter is studied and the tracking performance of polarization filter and improvement of angle measurement precision are simulated. The research results demonstrate this technology can effectively suppress the angle cheating interference in guidance radar and is feasible in engineering.

  6. Information filtering based on corrected redundancy-eliminating mass diffusion.

    Directory of Open Access Journals (Sweden)

    Xuzhen Zhu

    Full Text Available Methods used in information filtering and recommendation often rely on quantifying the similarity between objects or users. The used similarity metrics often suffer from similarity redundancies arising from correlations between objects' attributes. Based on an unweighted undirected object-user bipartite network, we propose a Corrected Redundancy-Eliminating similarity index (CRE which is based on a spreading process on the network. Extensive experiments on three benchmark data sets-Movilens, Netflix and Amazon-show that when used in recommendation, the CRE yields significant improvements in terms of recommendation accuracy and diversity. A detailed analysis is presented to unveil the origins of the observed differences between the CRE and mainstream similarity indices.

  7. Ontology-based topic clustering for online discussion data

    Science.gov (United States)

    Wang, Yongheng; Cao, Kening; Zhang, Xiaoming

    2013-03-01

    With the rapid development of online communities, mining and extracting quality knowledge from online discussions becomes very important for the industrial and marketing sector, as well as for e-commerce applications and government. Most of the existing techniques model a discussion as a social network of users represented by a user-based graph without considering the content of the discussion. In this paper we propose a new multilayered mode to analysis online discussions. The user-based and message-based representation is combined in this model. A novel frequent concept sets based clustering method is used to cluster the original online discussion network into topic space. Domain ontology is used to improve the clustering accuracy. Parallel methods are also used to make the algorithms scalable to very large data sets. Our experimental study shows that the model and algorithms are effective when analyzing large scale online discussion data.

  8. Design of digital trapezoidal shaping filter based on LabVIEW

    International Nuclear Information System (INIS)

    Liu Yujuan; Qin Guoxiu; Yang Zhihui; Zhang Xiaodong

    2013-01-01

    It describes the design of a digital trapezoidal shaping filter to nuclear signals based on LabVIEW. A method of optimizing the trapezoidal shaping filter's parameters was presented and tested, and the test results of the effect of shaping filter algorithm were studied. (authors)

  9. Machine learning of radial basis function neural network based on Kalman filter: Introduction

    Directory of Open Access Journals (Sweden)

    Vuković Najdan L.

    2014-01-01

    Full Text Available This paper analyzes machine learning of radial basis function neural network based on Kalman filtering. Three algorithms are derived: linearized Kalman filter, linearized information filter and unscented Kalman filter. We emphasize basic properties of these estimation algorithms, demonstrate how their advantages can be used for optimization of network parameters, derive mathematical models and show how they can be applied to model problems in engineering practice.

  10. Tunable double-channel filter based on two-dimensional ferroelectric photonic crystals

    International Nuclear Information System (INIS)

    Jiang, Ping; Ding, Chengyuan; Hu, Xiaoyong; Gong, Qihuang

    2007-01-01

    A tunable double-channel filter is presented, which is based on a two-dimensional nonlinear ferroelectric photonic crystal made of cerium doped barium titanate. The filtering properties of the photonic crystal filter can be tuned by adjusting the defect structure or by a pump light. The influences of the structure disorders caused by the perturbations in the radius or the position of air holes on the filtering properties are also analyzed

  11. Tunable double-channel filter based on two-dimensional ferroelectric photonic crystals

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Ping [State Key Laboratory for Mesoscopic Physics, Department of Physics, Peking University, Beijing 100871 (China); Ding, Chengyuan [State Key Laboratory for Mesoscopic Physics, Department of Physics, Peking University, Beijing 100871 (China); Hu, Xiaoyong [State Key Laboratory for Mesoscopic Physics, Department of Physics, Peking University, Beijing 100871 (China)]. E-mail: xiaoyonghu@pku.edu.cn; Gong, Qihuang [State Key Laboratory for Mesoscopic Physics, Department of Physics, Peking University, Beijing 100871 (China)]. E-mail: qhgong@pku.edu.cn

    2007-04-02

    A tunable double-channel filter is presented, which is based on a two-dimensional nonlinear ferroelectric photonic crystal made of cerium doped barium titanate. The filtering properties of the photonic crystal filter can be tuned by adjusting the defect structure or by a pump light. The influences of the structure disorders caused by the perturbations in the radius or the position of air holes on the filtering properties are also analyzed.

  12. Multirate Digital Filters Based on FPGA and Its Applications

    International Nuclear Information System (INIS)

    Sharaf El-Din, R.M.A.

    2013-01-01

    Digital Signal Processing (DSP) is one of the fastest growing techniques in the electronics industry. It is used in a wide range of application fields such as, telecommunications, data communications, image enhancement and processing, video signals, digital TV broadcasting, and voice synthesis and recognition. Field Programmable Gate Array (FPGA) offers good solution for addressing the needs of high performance DSP systems. The focus of this thesis is on one of the basic DSP functions, namely filtering signals to remove unwanted frequency bands. Multi rate Digital Filters (MDFs) are the main theme here. Theory and implementation of MDF, as a special class of digital filters, will be discussed. Multi rate digital filters represent a class of digital filters having a number of attractive features like, low requirements for the coefficient word lengths, significant saving in computation and storage requirements results in a significant reduction in its dynamic power consumption. This thesis introduces an efficient FPGA realization of a multi rate decimation filter with narrow pass-band and narrow transition band to reduce the frequency sample rate by factor of 64 for noise thermometer applications. The proposed multi rate decimation filter is composed of three stages; the first stage is a Cascaded Integrator Comb (CIC) decimation filter, the second stage is a two-coefficient Half-Band (HB) filter and the last stage is a sharper transition HB filter. The frequency responses of individual stages as well as the overall filter response have been demonstrated with full simulation using MATLAB. The design and implementation of the proposed MDF on FPGA (XILINX Virtex XCV800 BG432-4), using VHSIC Hardware Description Language (VHDL), has been introduced. The implementation areas of the proposed filter stages are compared. Using CIC-HB technique saves 18% of the design area, compared to using six stages HB decimation filters.

  13. Infrared image background modeling based on improved Susan filtering

    Science.gov (United States)

    Yuehua, Xia

    2018-02-01

    When SUSAN filter is used to model the infrared image, the Gaussian filter lacks the ability of direction filtering. After filtering, the edge information of the image cannot be preserved well, so that there are a lot of edge singular points in the difference graph, increase the difficulties of target detection. To solve the above problems, the anisotropy algorithm is introduced in this paper, and the anisotropic Gauss filter is used instead of the Gauss filter in the SUSAN filter operator. Firstly, using anisotropic gradient operator to calculate a point of image's horizontal and vertical gradient, to determine the long axis direction of the filter; Secondly, use the local area of the point and the neighborhood smoothness to calculate the filter length and short axis variance; And then calculate the first-order norm of the difference between the local area of the point's gray-scale and mean, to determine the threshold of the SUSAN filter; Finally, the built SUSAN filter is used to convolution the image to obtain the background image, at the same time, the difference between the background image and the original image is obtained. The experimental results show that the background modeling effect of infrared image is evaluated by Mean Squared Error (MSE), Structural Similarity (SSIM) and local Signal-to-noise Ratio Gain (GSNR). Compared with the traditional filtering algorithm, the improved SUSAN filter has achieved better background modeling effect, which can effectively preserve the edge information in the image, and the dim small target is effectively enhanced in the difference graph, which greatly reduces the false alarm rate of the image.

  14. Introducing passive acoustic filter in acoustic based condition monitoring: Motor bike piston-bore fault identification

    Science.gov (United States)

    Jena, D. P.; Panigrahi, S. N.

    2016-03-01

    Requirement of designing a sophisticated digital band-pass filter in acoustic based condition monitoring has been eliminated by introducing a passive acoustic filter in the present work. So far, no one has attempted to explore the possibility of implementing passive acoustic filters in acoustic based condition monitoring as a pre-conditioner. In order to enhance the acoustic based condition monitoring, a passive acoustic band-pass filter has been designed and deployed. Towards achieving an efficient band-pass acoustic filter, a generalized design methodology has been proposed to design and optimize the desired acoustic filter using multiple filter components in series. An appropriate objective function has been identified for genetic algorithm (GA) based optimization technique with multiple design constraints. In addition, the sturdiness of the proposed method has been demonstrated in designing a band-pass filter by using an n-branch Quincke tube, a high pass filter and multiple Helmholtz resonators. The performance of the designed acoustic band-pass filter has been shown by investigating the piston-bore defect of a motor-bike using engine noise signature. On the introducing a passive acoustic filter in acoustic based condition monitoring reveals the enhancement in machine learning based fault identification practice significantly. This is also a first attempt of its own kind.

  15. Performance reliability prediction for thermal aging based on kalman filtering

    International Nuclear Information System (INIS)

    Ren Shuhong; Wen Zhenhua; Xue Fei; Zhao Wensheng

    2015-01-01

    The performance reliability of the nuclear power plant main pipeline that failed due to thermal aging was studied by the performance degradation theory. Firstly, through the data obtained from the accelerated thermal aging experiments, the degradation process of the impact strength and fracture toughness of austenitic stainless steel material of the main pipeline was analyzed. The time-varying performance degradation model based on the state space method was built, and the performance trends were predicted by using Kalman filtering. Then, the multi-parameter and real-time performance reliability prediction model for the main pipeline thermal aging was developed by considering the correlation between the impact properties and fracture toughness, and by using the stochastic process theory. Thus, the thermal aging performance reliability and reliability life of the main pipeline with multi-parameter were obtained, which provides the scientific basis for the optimization management of the aging maintenance decision making for nuclear power plant main pipelines. (authors)

  16. Whitelists Based Multiple Filtering Techniques in SCADA Sensor Networks

    Directory of Open Access Journals (Sweden)

    DongHo Kang

    2014-01-01

    Full Text Available Internet of Things (IoT consists of several tiny devices connected together to form a collaborative computing environment. Recently IoT technologies begin to merge with supervisory control and data acquisition (SCADA sensor networks to more efficiently gather and analyze real-time data from sensors in industrial environments. But SCADA sensor networks are becoming more and more vulnerable to cyber-attacks due to increased connectivity. To safely adopt IoT technologies in the SCADA environments, it is important to improve the security of SCADA sensor networks. In this paper we propose a multiple filtering technique based on whitelists to detect illegitimate packets. Our proposed system detects the traffic of network and application protocol attacks with a set of whitelists collected from normal traffic.

  17. Ultra compact triplexing filters based on SOI nanowire AWGs

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Jiashun; An Junming; Zhao Lei; Song Shijiao; Wang Liangliang; Li Jianguang; Wang Hongjie; Wu Yuanda; Hu Xiongwei, E-mail: junming@red.semi.ac.cn [State Key Laboratory on Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083 (China)

    2011-04-15

    An ultra compact triplexing filter was designed based on a silicon on insulator (SOI) nanowire arrayed waveguide grating (AWG) for fiber-to-the-home FTTH. The simulation results revealed that the design performed well in the sense of having a good triplexing function. The designed SOI nanowire AWGs were fabricated using ultraviolet lithography and induced coupler plasma etching. The experimental results showed that the crosstalk was less than -15 dB, and the 3 dB-bandwidth was 11.04 nm. The peak wavelength output from ports a, c, and b were 1455, 1510 and 1300 nm, respectively, which deviated from our original expectations. The deviation of the wavelength is mainly caused by 45 nm width deviation of the arrayed waveguides during the course of the fabrication process and partly caused by material dispersion. (semiconductor devices)

  18. Ultra compact triplexing filters based on SOI nanowire AWGs

    International Nuclear Information System (INIS)

    Zhang Jiashun; An Junming; Zhao Lei; Song Shijiao; Wang Liangliang; Li Jianguang; Wang Hongjie; Wu Yuanda; Hu Xiongwei

    2011-01-01

    An ultra compact triplexing filter was designed based on a silicon on insulator (SOI) nanowire arrayed waveguide grating (AWG) for fiber-to-the-home FTTH. The simulation results revealed that the design performed well in the sense of having a good triplexing function. The designed SOI nanowire AWGs were fabricated using ultraviolet lithography and induced coupler plasma etching. The experimental results showed that the crosstalk was less than -15 dB, and the 3 dB-bandwidth was 11.04 nm. The peak wavelength output from ports a, c, and b were 1455, 1510 and 1300 nm, respectively, which deviated from our original expectations. The deviation of the wavelength is mainly caused by 45 nm width deviation of the arrayed waveguides during the course of the fabrication process and partly caused by material dispersion. (semiconductor devices)

  19. Ultra compact triplexing filters based on SOI nanowire AWGs

    Science.gov (United States)

    Jiashun, Zhang; Junming, An; Lei, Zhao; Shijiao, Song; Liangliang, Wang; Jianguang, Li; Hongjie, Wang; Yuanda, Wu; Xiongwei, Hu

    2011-04-01

    An ultra compact triplexing filter was designed based on a silicon on insulator (SOI) nanowire arrayed waveguide grating (AWG) for fiber-to-the-home FTTH. The simulation results revealed that the design performed well in the sense of having a good triplexing function. The designed SOI nanowire AWGs were fabricated using ultraviolet lithography and induced coupler plasma etching. The experimental results showed that the crosstalk was less than -15 dB, and the 3 dB-bandwidth was 11.04 nm. The peak wavelength output from ports a, c, and b were 1455, 1510 and 1300 nm, respectively, which deviated from our original expectations. The deviation of the wavelength is mainly caused by 45 nm width deviation of the arrayed waveguides during the course of the fabrication process and partly caused by material dispersion.

  20. Public-channel cryptography based on mutual chaos pass filters.

    Science.gov (United States)

    Klein, Einat; Gross, Noam; Kopelowitz, Evi; Rosenbluh, Michael; Khaykovich, Lev; Kinzel, Wolfgang; Kanter, Ido

    2006-10-01

    We study the mutual coupling of chaotic lasers and observe both experimentally and in numeric simulations that there exists a regime of parameters for which two mutually coupled chaotic lasers establish isochronal synchronization, while a third laser coupled unidirectionally to one of the pair does not synchronize. We then propose a cryptographic scheme, based on the advantage of mutual coupling over unidirectional coupling, where all the parameters of the system are public knowledge. We numerically demonstrate that in such a scheme the two communicating lasers can add a message signal (compressed binary message) to the transmitted coupling signal and recover the message in both directions with high fidelity by using a mutual chaos pass filter procedure. An attacker, however, fails to recover an errorless message even if he amplifies the coupling signal.

  1. An optical tunable filter array based on LCOS phase grating

    Science.gov (United States)

    Feng, Dong; Wan, Zhujun; Chen, Xu; Yan, Shijia; Luo, Zhixiang

    2018-01-01

    This paper reports an optical tunable filter array (TFA) based on a LCOS (liquid crystal on silicon) chip. The input broadband optical beam is first dispersed by a bulk grating and then incident on the LCOS chip. The LCOS chip is phase-only modulated and constructed as a dynamic reflective phase grating. The phase modulation is adjusted to meet the Littrow angle for a specified passband wavelength and thus the optical beam corresponding to this wavelength is steered to the output. The input/output optical beams are coupled to optical fibers with a dual-fiber collimator. Four dualfiber collimators are vertically aligned as the inputs/outputs and the pixels of the LCOS chip are vertically allocated as four independent zones. Thus the device can act as a 4-channel TFA, which is assembled and functionally demonstrated.

  2. Star-sensor-based predictive Kalman filter for satelliteattitude estimation

    Institute of Scientific and Technical Information of China (English)

    林玉荣; 邓正隆

    2002-01-01

    A real-time attitude estimation algorithm, namely the predictive Kalman filter, is presented. This algorithm can accurately estimate the three-axis attitude of a satellite using only star sensor measurements. The implementation of the filter includes two steps: first, predicting the torque modeling error, and then estimating the attitude. Simulation results indicate that the predictive Kalman filter provides robust performance in the presence of both significant errors in the assumed model and in the initial conditions.

  3. urCF: An Approach to Integrating User Reviews into Memory-Based Collaborative Filtering

    Science.gov (United States)

    Zhang, Zhenxue

    2013-01-01

    Blessed by the Internet age, many online retailers (e.g., Amazon.com) have deployed recommender systems to help their customers identify products that may be of their interest in order to improve cross-selling and enhance customer loyalty. Collaborative Filtering (CF) is the most successful technique among different approaches to generating…

  4. CDBA-Based Universal Biquad Filter and Quadrature Oscillator

    Directory of Open Access Journals (Sweden)

    Worapong Tangsrirat

    2008-01-01

    Full Text Available The voltage-mode universal biquadratic filter and sinusoidal quadrature oscillator based on the use of current differencing buffered amplifiers (CDBAs as active components have been proposed in this paper. All the proposed configurations employ only two CDBAs and six passive components. The first proposed CDBA-based biquad configuration can realize all the standard types of the biquadratic functions, that is, lowpass, bandpass, highpass, bandstop, and allpass, from the same topology, and can also provide orthogonal tuning of the natural angular frequency (ωo and the bandwidth (BW through separate virtually grounded passive components. By slight modification of the first proposed configuration, the new CDBA-based sinusoidal quadrature oscillator is easily obtained. The oscillation condition and the oscillation frequency are independently adjustable by different virtually grounded resistors. The sensitivity analysis of all proposed circuit configurations is shown to be low. PSPICE simulations and experimental results based upon commercially available AD844-type CFAs are included, which confirm the workability of the proposed circuits.

  5. A novel method for EMG decomposition based on matched filters

    Directory of Open Access Journals (Sweden)

    Ailton Luiz Dias Siqueira Júnior

    Full Text Available Introduction Decomposition of electromyography (EMG signals into the constituent motor unit action potentials (MUAPs can allow for deeper insights into the underlying processes associated with the neuromuscular system. The vast majority of the methods for EMG decomposition found in the literature depend on complex algorithms and specific instrumentation. As an attempt to contribute to solving these issues, we propose a method based on a bank of matched filters for the decomposition of EMG signals. Methods Four main units comprise our method: a bank of matched filters, a peak detector, a motor unit classifier and an overlapping resolution module. The system’s performance was evaluated with simulated and real EMG data. Classification accuracy was measured by comparing the responses of the system with known data from the simulator and with the annotations of a human expert. Results The results show that decomposition of non-overlapping MUAPs can be achieved with up to 99% accuracy for signals with up to 10 active motor units and a signal-to-noise ratio (SNR of 10 dB. For overlapping MUAPs with up to 10 motor units per signal and a SNR of 20 dB, the technique allows for correct classification of approximately 71% of the MUAPs. The method is capable of processing, decomposing and classifying a 50 ms window of data in less than 5 ms using a standard desktop computer. Conclusion This article contributes to the ongoing research on EMG decomposition by describing a novel technique capable of delivering high rates of success by means of a fast algorithm, suggesting its possible use in future real-time embedded applications, such as myoelectric prostheses control and biofeedback systems.

  6. Complete filter-based cerebral embolic protection with transcatheter aortic valve replacement.

    Science.gov (United States)

    Van Gils, Lennart; Kroon, Herbert; Daemen, Joost; Ren, Claire; Maugenest, Anne-Marie; Schipper, Marguerite; De Jaegere, Peter P; Van Mieghem, Nicolas M

    2018-03-01

    To evaluate the value of left vertebral artery filter protection in addition to the current filter-based embolic protection technology to achieve complete cerebral protection during TAVR. The occurrence of cerebrovascular events after transcatheter aortic valve replacement (TAVR) has fueled concern for its potential application in younger patients with longer life expectancy. Transcatheter cerebral embolic protection (TCEP) devices may limit periprocedural cerebrovascular events by preventing macro and micro-embolization to the brain. Conventional filter-based TCEP devices cover three extracranial contributories to the brain, yet leave the left vertebral artery unprotected. Patients underwent TAVR with complete TCEP. A dual-filter system was deployed in the brachiocephalic trunk and left common carotid artery with an additional single filter in the left vertebral artery. After TAVR all filters were retrieved and sent for histopathological evaluation by an experienced pathologist. Eleven patients received a dual-filter system and nine of them received an additional left vertebral filter. In the remaining two patients, the left vertebral filter could not be deployed. No periprocedural strokes occurred. We found debris in all filters, consisting of thrombus, tissue derived debris, and foreign body material. The left vertebral filter contained debris in an equal amount of patients as the Sentinel filters. The size of the captured particles was similar between all filters. The left vertebral artery is an important entry route for embolic material to the brain during TAVR. Selective filter protection of the left vertebral artery revealed embolic debris in all patients. The clinical value of complete filter-based TCEP during TAVR warrants further research. © 2017 Wiley Periodicals, Inc.

  7. An Automated Energy Detection Algorithm Based on Morphological Filter Processing with a Modified Watershed Transform

    Science.gov (United States)

    2018-01-01

    ARL-TR-8270 ● JAN 2018 US Army Research Laboratory An Automated Energy Detection Algorithm Based on Morphological Filter...Automated Energy Detection Algorithm Based on Morphological Filter Processing with a Modified Watershed Transform by Kwok F Tom Sensors and Electron...1 October 2016–30 September 2017 4. TITLE AND SUBTITLE An Automated Energy Detection Algorithm Based on Morphological Filter Processing with a

  8. Robotic fish tracking method based on suboptimal interval Kalman filter

    Science.gov (United States)

    Tong, Xiaohong; Tang, Chao

    2017-11-01

    Autonomous Underwater Vehicle (AUV) research focused on tracking and positioning, precise guidance and return to dock and other fields. The robotic fish of AUV has become a hot application in intelligent education, civil and military etc. In nonlinear tracking analysis of robotic fish, which was found that the interval Kalman filter algorithm contains all possible filter results, but the range is wide, relatively conservative, and the interval data vector is uncertain before implementation. This paper proposes a ptimization algorithm of suboptimal interval Kalman filter. Suboptimal interval Kalman filter scheme used the interval inverse matrix with its worst inverse instead, is more approximate nonlinear state equation and measurement equation than the standard interval Kalman filter, increases the accuracy of the nominal dynamic system model, improves the speed and precision of tracking system. Monte-Carlo simulation results show that the optimal trajectory of sub optimal interval Kalman filter algorithm is better than that of the interval Kalman filter method and the standard method of the filter.

  9. Deviation-based spam-filtering method via stochastic approach

    Science.gov (United States)

    Lee, Daekyung; Lee, Mi Jin; Kim, Beom Jun

    2018-03-01

    In the presence of a huge number of possible purchase choices, ranks or ratings of items by others often play very important roles for a buyer to make a final purchase decision. Perfectly objective rating is an impossible task to achieve, and we often use an average rating built on how previous buyers estimated the quality of the product. The problem of using a simple average rating is that it can easily be polluted by careless users whose evaluation of products cannot be trusted, and by malicious spammers who try to bias the rating result on purpose. In this letter we suggest how trustworthiness of individual users can be systematically and quantitatively reflected to build a more reliable rating system. We compute the suitably defined reliability of each user based on the user's rating pattern for all products she evaluated. We call our proposed method as the deviation-based ranking, since the statistical significance of each user's rating pattern with respect to the average rating pattern is the key ingredient. We find that our deviation-based ranking method outperforms existing methods in filtering out careless random evaluators as well as malicious spammers.

  10. Predicting the Currency Market in Online Gaming via Lexicon-Based Analysis on Its Online Forum

    Directory of Open Access Journals (Sweden)

    Young Bin Kim

    2017-01-01

    Full Text Available Transactions involving virtual currencies are becoming increasingly common, including those in online games. In response, predicting the market price of a virtual currency is an important task for all involved, but it has not yet attracted much attention from researchers. This paper presents user opinions from online forums in a massive multiplayer online game (MMOG setting widely used around the world. We propose a method for predicting the next-day rise and fall of the currency used in an MMOG environment. Based on analysis of online forum users’ opinions, we predict daily fluctuations in the price of a currency used in an MMOG setting. Focusing specifically on the World of Warcraft game, one of the most widely used MMOGs, we demonstrate the feasibility of predicting the fluctuation in value of virtual currencies used in this game community.

  11. Classification of Textures Using Filter Based Local Feature Extraction

    Directory of Open Access Journals (Sweden)

    Bocekci Veysel Gokhan

    2016-01-01

    Full Text Available In this work local features are used in feature extraction process in image processing for textures. The local binary pattern feature extraction method from textures are introduced. Filtering is also used during the feature extraction process for getting discriminative features. To show the effectiveness of the algorithm before the extraction process, three different noise are added to both train and test images. Wiener filter and median filter are used to remove the noise from images. We evaluate the performance of the method with Naïve Bayesian classifier. We conduct the comparative analysis on benchmark dataset with different filtering and size. Our experiments demonstrate that feature extraction process combine with filtering give promising results on noisy images.

  12. Laser Rate Equation Based Filtering for Carrier Recovery in Characterization and Communication

    DEFF Research Database (Denmark)

    Piels, Molly; Iglesias Olmedo, Miguel; Xue, Weiqi

    2015-01-01

    We formulate a semiconductor laser rate equationbased approach to carrier recovery in a Bayesian filtering framework. Filter stability and the effect of model inaccuracies (unknown or un-useable rate equation coefficients) are discussed. Two potential application areas are explored: laser...... characterization and carrier recovery in coherent communication. Two rate equation based Bayesian filters, the particle filter and extended Kalman filter, are used in conjunction with a coherent receiver to measure frequency noise spectrum of a photonic crystal cavity laser with less than 20 nW of fiber...

  13. Online cell SOC estimation of Li-ion battery packs using a dual time-scale Kalman filtering for EV applications

    International Nuclear Information System (INIS)

    Dai, Haifeng; Wei, Xuezhe; Sun, Zechang; Wang, Jiayuan; Gu, Weijun

    2012-01-01

    Highlights: ► We use an equivalent circuit model to describe the characteristics of battery. ► A dual time-scale estimator is used to calculate pack average SOC and cell SOC. ► The estimator is based on the dynamic descriptions and extended Kalman filter. ► Three different test cases are designed to validate the proposed method. ► Test results indicate a good performance of the method for EV applications. -- Abstract: For the vehicular operation, due to the voltage and power/energy requirements, the battery systems are usually composed of up to hundreds of cells connected in series or parallel. To accommodate the operation conditions, the battery management system (BMS) should estimate State of Charge (SOC) to facilitate safe and efficient utilization of the battery. The performance difference among the cells makes a pure pack SOC estimation hardly provide sufficient information, which at last affects the computation of available energy and power and the safety of the battery system. So for a reliable and accurate management, the BMS should “know” the SOC of each individual cell. Several possible solutions on this issue have been reported in the recent years. This paper studies a method to determine online all individual cell SOCs of a series-connected battery pack. This method, with an equivalent circuit based “averaged cell” model, estimates the battery pack’s average SOC first, and then incorporates the performance divergences between the “averaged cell” and each individual cell to generate the SOC estimations for all cells. This method is developed based on extended Kalman filter (EKF), and to reduce the computation cost, a dual time-scale implementation is designed. The method is validated using results obtained from the measurements of a Li-ion battery pack under three different tests, and analysis indicates the good performance of the algorithm.

  14. Transistor-based filter for inhibiting load noise from entering a power supply

    Science.gov (United States)

    Taubman, Matthew S

    2013-07-02

    A transistor-based filter for inhibiting load noise from entering a power supply is disclosed. The filter includes a first transistor having an emitter coupled to a power supply, a collector coupled to a load, and a base. The filter also includes a first capacitor coupled between the base of the first transistor and a ground terminal. The filter further includes an impedance coupled between the base and a node between the collector and the load, or a second transistor and second capacitor. The impedance can be a resistor or an inductor.

  15. Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide

    DEFF Research Database (Denmark)

    Xiao, Binggang; Li, Sheng-Hua; Xiao, Sanshui

    2016-01-01

    Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide is proposed. Owing to subwavelength confinement, such a filter has advantage in the structure size without sacrificing the performance. The spoof SPP based notch is introduced to suppress the WLAN and satel......Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide is proposed. Owing to subwavelength confinement, such a filter has advantage in the structure size without sacrificing the performance. The spoof SPP based notch is introduced to suppress the WLAN...

  16. An online replanning method using warm start optimization and aperture morphing for flattening-filter-free beams.

    Science.gov (United States)

    Ahunbay, Ergun E; Ates, O; Li, X A

    2016-08-01

    In a situation where a couch shift for patient positioning is not preferred or prohibited (e.g., MR-linac), segment aperture morphing (SAM) can address target dislocation and deformation. For IMRT/VMAT with flattening-filter-free (FFF) beams, however, SAM method would lead to an adverse translational dose effect due to the beam unflattening. Here the authors propose a new two-step process to address both the translational effect of FFF beams and the target deformation. The replanning method consists of an offline and an online step. The offline step is to create a series of preshifted-plans (PSPs) obtained by a so-called "warm start" optimization (starting optimization from the original plan, rather than from scratch) at a series of isocenter shifts. The PSPs all have the same number of segments with very similar shapes, since the warm start optimization only adjusts the MLC positions instead of regenerating them. In the online step, a new plan is obtained by picking the closest PSP or linearly interpolating the MLC positions and the monitor units of the closest PSPs for the shift determined from the image of the day. This two-step process is completely automated and almost instantaneous (no optimization or dose calculation needed). The previously developed SAM algorithm is then applied for daily deformation. The authors tested the method on sample prostate and pancreas cases. The two-step interpolation method can account for the adverse dose effects from FFF beams, while SAM corrects for the target deformation. Plan interpolation method is effective in diminishing the unflat beam effect and may allow reducing the required number of PSPs. The whole process takes the same time as the previously reported SAM process (5-10 min). The new two-step method plus SAM can address both the translation effects of FFF beams and target deformation, and can be executed in full automation except the delineation of target contour required by the SAM process.

  17. Single-Phase LLCL-Filter-based Grid-Tied Inverter with Low-Pass Filter Based Capacitor Current Feedback Active damper

    DEFF Research Database (Denmark)

    Liu, Yuan; Wu, Weimin; Li, Yun

    2016-01-01

    The capacitor-current-feedback active damping method is attractive for high-order-filter-based high power grid-tied inverter when the grid impedance varies within a wide range. In order to improve the system control bandwidth and attenuate the high order grid background harmonics by using the quasi....... In this paper, a low pass filter is proposed to be inserted in the capacitor current feedback loop op LLCL-filter based grid-tied inverter together with a digital proportional and differential compensator. The detailed theoretical analysis is given. For verification, simulations on a 2kW/220V/10kHz LLCL...

  18. [Restoration filtering based on projection power spectrum for single-photon emission computed tomography].

    Science.gov (United States)

    Kubo, N

    1995-04-01

    To improve the quality of single-photon emission computed tomographic (SPECT) images, a restoration filter has been developed. This filter was designed according to practical "least squares filter" theory. It is necessary to know the object power spectrum and the noise power spectrum. The power spectrum is estimated from the power spectrum of a projection, when the high-frequency power spectrum of a projection is adequately approximated as a polynomial exponential expression. A study of the restoration with the filter based on a projection power spectrum was conducted, and compared with that of the "Butterworth" filtering method (cut-off frequency of 0.15 cycles/pixel), and "Wiener" filtering (signal-to-noise power spectrum ratio was a constant). Normalized mean-squared errors (NMSE) of the phantom, two line sources located in a 99mTc filled cylinder, were used. NMSE of the "Butterworth" filter, "Wiener" filter, and filtering based on a power spectrum were 0.77, 0.83, and 0.76 respectively. Clinically, brain SPECT images utilizing this new restoration filter improved the contrast. Thus, this filter may be useful in diagnosis of SPECT images.

  19. Restoration filtering based on projection power spectrum for single-photon emission computed tomography

    International Nuclear Information System (INIS)

    Kubo, Naoki

    1995-01-01

    To improve the quality of single-photon emission computed tomographic (SPECT) images, a restoration filter has been developed. This filter was designed according to practical 'least squares filter' theory. It is necessary to know the object power spectrum and the noise power spectrum. The power spectrum is estimated from the power spectrum of a projection, when the high-frequency power spectrum of a projection is adequately approximated as a polynomial exponential expression. A study of the restoration with the filter based on a projection power spectrum was conducted, and compared with that of the 'Butterworth' filtering method (cut-off frequency of 0.15 cycles/pixel), and 'Wiener' filtering (signal-to-noise power spectrum ratio was a constant). Normalized mean-squared errors (NMSE) of the phantom, two line sources located in a 99m Tc filled cylinder, were used. NMSE of the 'Butterworth' filter, 'Wiener' filter, and filtering based on a power spectrum were 0.77, 0.83, and 0.76 respectively. Clinically, brain SPECT images utilizing this new restoration filter improved the contrast. Thus, this filter may be useful in diagnosis of SPECT images. (author)

  20. Adaptive skin detection based on online training

    Science.gov (United States)

    Zhang, Ming; Tang, Liang; Zhou, Jie; Rong, Gang

    2007-11-01

    Skin is a widely used cue for porn image classification. Most conventional methods are off-line training schemes. They usually use a fixed boundary to segment skin regions in the images and are effective only in restricted conditions: e.g. good lightness and unique human race. This paper presents an adaptive online training scheme for skin detection which can handle these tough cases. In our approach, skin detection is considered as a classification problem on Gaussian mixture model. For each image, human face is detected and the face color is used to establish a primary estimation of skin color distribution. Then an adaptive online training algorithm is used to find the real boundary between skin color and background color in current image. Experimental results on 450 images showed that the proposed method is more robust in general situations than the conventional ones.

  1. Online EM with weight-based forgetting

    OpenAIRE

    Celaya, Enric; Agostini, Alejandro

    2015-01-01

    In the on-line version of the EM algorithm introduced by Sato and Ishii (2000), a time-dependent discount factor is introduced for forgetting the effect of the old posterior values obtained with an earlier, inaccurate estimator. In their approach, forgetting is uniformly applied to the estimators of each mixture component depending exclusively on time, irrespective of the weight attributed to each unit for the observed sample. This causes an excessive forgetting in the less frequently sampled...

  2. DIGITAL FILTERS IMPLEMENTATION IN MICROPROCESSOR-BASED RELAY PROTECTION

    Directory of Open Access Journals (Sweden)

    Yu. V. Rumiantsev

    2016-01-01

    Full Text Available This article presents the implementation of digital filters used in digital relay protection current measuring elements. Mathematical descriptions of the considered digital filters as well as the computer programs for their coefficients calculation are described. It has been shown that in order to reliable estimate the digital filter performance its input signals waveforms must be close to the actual secondary current waveform of the current transformer to which the digital protection with the estimated digital filter is connected. For these purposes in MatLab–Simulink dynamic simulation environment the power system and the current measuring element models were developed. Performed calculations allowed to reveal that the exponentially decaying DC component which in some cases contains in primary fault current drives the current transformer core into saturation even when its nominal parameters are not exceeded. This results in distortion of the current transformer secondary current which in this case contains higher and inter-harmonics. Moreover, such harmonic content is not completely taking into account during coefficients calculation of the considered digital filters what results in signal magnitude estimation inaccuracy. Comparison of the digital filters response to the above-mentioned input signals allowed to find out such digital filter implementations which enable signal magnitude estimation with a minimum error. Ways of filtering quality improvement concerned with the window functions are proposed. Thus, the joint usage of digital filter and Hamming window allows to achieve the zero value of the signal magnitude gain factor in high-frequency range and substantially suppress all spectral components above 100 Hz. The increasing of the signal magnitude settling time in this case can be reduced by choosing the most optimal parameters of the all components of the current measuring element.

  3. A collaborative filtering-based approach to biomedical knowledge discovery.

    Science.gov (United States)

    Lever, Jake; Gakkhar, Sitanshu; Gottlieb, Michael; Rashnavadi, Tahereh; Lin, Santina; Siu, Celia; Smith, Maia; Jones, Martin R; Krzywinski, Martin; Jones, Steven J M; Wren, Jonathan

    2018-02-15

    The increase in publication rates makes it challenging for an individual researcher to stay abreast of all relevant research in order to find novel research hypotheses. Literature-based discovery methods make use of knowledge graphs built using text mining and can infer future associations between biomedical concepts that will likely occur in new publications. These predictions are a valuable resource for researchers to explore a research topic. Current methods for prediction are based on the local structure of the knowledge graph. A method that uses global knowledge from across the knowledge graph needs to be developed in order to make knowledge discovery a frequently used tool by researchers. We propose an approach based on the singular value decomposition (SVD) that is able to combine data from across the knowledge graph through a reduced representation. Using cooccurrence data extracted from published literature, we show that SVD performs better than the leading methods for scoring discoveries. We also show the diminishing predictive power of knowledge discovery as we compare our predictions with real associations that appear further into the future. Finally, we examine the strengths and weaknesses of the SVD approach against another well-performing system using several predicted associations. All code and results files for this analysis can be accessed at https://github.com/jakelever/knowledgediscovery. sjones@bcgsc.ca. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  4. Online Particle Detection by Neural Networks Based on Topologic Calorimetry Information

    CERN Document Server

    Ciodaro, T; The ATLAS collaboration; Damazio, D; de Seixas, JM

    2011-01-01

    This paper presents the last results from the Ringer algorithm, which is based on artificial neural networks for the electron identification at the online filtering system of the ATLAS particle detector, in the context of the LHC experiment at CERN. The algorithm performs topological feature extraction over the ATLAS calorimetry information (energy measurements). Later, the extracted information is presented to a neural network classifier. Studies showed that the Ringer algorithm achieves high detection efficiency, while keeping the false alarm rate low. Optimizations, guided by detailed analysis, reduced the algorithm execution time in 59%. Also, the payload necessary to store the Ringer algorithm information represents less than 6.2 percent of the total filtering system amount

  5. Fuzzy Logic-Based Filter for Removing Additive and Impulsive Noise from Color Images

    Science.gov (United States)

    Zhu, Yuhong; Li, Hongyang; Jiang, Huageng

    2017-12-01

    This paper presents an efficient filter method based on fuzzy logics for adaptively removing additive and impulsive noise from color images. The proposed filter comprises two parts including noise detection and noise removal filtering. In the detection part, the fuzzy peer group concept is applied to determine what type of noise is added to each pixel of the corrupted image. In the filter part, the impulse noise is deducted by the vector median filter in the CIELAB color space and an optimal fuzzy filter is introduced to reduce the Gaussian noise, while they can work together to remove the mixed Gaussian-impulse noise from color images. Experimental results on several color images proves the efficacy of the proposed fuzzy filter.

  6. Harmonic Active Filtering and Impedance-based Stability Analysis in Offshore Wind Power Plants

    DEFF Research Database (Denmark)

    Dhua, Debasish; Yang, Guangya; Zhang, Zhe

    2017-01-01

    installation and provides effectively similar functionality as passive filters. This work is focused on harmonic propagation studies in wind power plants, power quality evaluation at the point of connection and harmonic mitigation by active filtering. Finally, an impedance-based stability analysis......Nowadays, to eliminate harmonics injected by the wind turbines in offshore wind power plants there is a need to install passive filters. Moreover, the passive filters are not adaptive to harmonic profile changes due to topology changes, grid loading etc. Therefore, active filters in wind turbines...... are proposed as a flexible harmonic mitigation measure. The motivation of this study is to explore the possibility of embedding active filtering in wind turbine grid-side converters without having to change the system electrical infrastructure. The active filtering method can prevent additional equipment...

  7. On the Systematic Synthesis of OTA-Based KHN Filters

    Directory of Open Access Journals (Sweden)

    Y.A. Li

    2014-04-01

    Full Text Available According to the nullor-mirror descriptions of OTA, the NAM expansion method for three different types of KHN filters employing OTAs is considered. The type-A filters employing five OTAs have 32 different forms, the type-B filters employing four OTAs have 32 different forms, and the type-C filters employing three OTAs have eight different forms. At last a total of 72 circuits are received. Having used canonic number of components, the circuits are easy to be integrated and both pole frequency and Q-factor can be tuned electronically through tuning bias currents of the OTAs. The MULTISIM simulation results have been included to verify the workability of the derived circuit.

  8. Research based on matlab method of digital trapezoidal shaping filter

    International Nuclear Information System (INIS)

    Zhou Qinghua; Zhang Ruanyu; Li Taihua

    2008-01-01

    In order to develop digital shaping system fast and conveniently, the paper presents the method of optimizing the trapezoidal shaping filter's parameters by using MATLAB, and discusses the affections of the parameters to the shaping result by this method. (authors)

  9. Damage Detection for Continuous Bridge Based on Static-Dynamic Condensation and Extended Kalman Filtering

    Directory of Open Access Journals (Sweden)

    Haoxiang He

    2014-01-01

    Full Text Available As an effective and classical method about physical parameter identification, extended Kalman filtering (EKF algorithm is widely used in structural damage identification, but the equations and solutions for the structure with bending deformation are not established based on EKF. The degrees of freedom about rotation can be eliminated by the static condensation method, and the dynamic condensation method considering Rayleigh damping is proposed in order to establish the equivalent and simplified modal based on complex finite element model such as continuous girder bridge. According to the requirement of bridge inspection and health monitoring, the online and convenient damage detection method based on EKF is presented. The impact excitation can be generated only on one location by one hammer actuator, and the signal in free vibration is analyzed. The deficiency that the complex excitation information is needed based on the traditional method is overcome. As a numerical example, a three-span continuous girder bridge is simulated, and the corresponding stiffness, the damage location and degree, and the damping parameter are identified accurately. It is verified that the method is suitable for the dynamic signal with high noise-signal ratio; the convergence speed is fast and this method is feasible for application.

  10. State of Charge and State of Health Estimation of AGM VRLA Batteries by Employing a Dual Extended Kalman Filter and an ARX Model for Online Parameter Estimation

    Directory of Open Access Journals (Sweden)

    Ngoc-Tham Tran

    2017-01-01

    Full Text Available State of charge (SOC and state of health (SOH are key issues for the application of batteries, especially the absorbent glass mat valve regulated lead-acid (AGM VRLA type batteries used in the idle stop start systems (ISSs that are popularly integrated into conventional engine-based vehicles. This is due to the fact that SOC and SOH estimation accuracy is crucial for optimizing battery energy utilization, ensuring safety and extending battery life cycles. The dual extended Kalman filter (DEKF, which provides an elegant and powerful solution, is widely applied in SOC and SOH estimation based on a battery parameter model. However, the battery parameters are strongly dependent on operation conditions such as the SOC, current rate and temperature. In addition, battery parameters change significantly over the life cycle of a battery. As a result, many experimental pretests investigating the effects of the internal and external conditions of a battery on its parameters are required, since the accuracy of state estimation depends on the quality of the information regarding battery parameter changes. In this paper, a novel method for SOC and SOH estimation that combines a DEKF algorithm, which considers hysteresis and diffusion effects, and an auto regressive exogenous (ARX model for online parameters estimation is proposed. The DEKF provides precise information concerning the battery open circuit voltage (OCV to the ARX model. Meanwhile, the ARX model continues monitoring parameter variations and supplies information on them to the DEKF. In this way, the estimation accuracy can be maintained despite the changing parameters of a battery. Moreover, online parameter estimation from the ARX model can save the time and effort used for parameter pretests. The validation of the proposed algorithm is given by simulation and experimental results.

  11. New Collaborative Filtering Algorithms Based on SVD++ and Differential Privacy

    OpenAIRE

    Xian, Zhengzheng; Li, Qiliang; Li, Gai; Li, Lei

    2017-01-01

    Collaborative filtering technology has been widely used in the recommender system, and its implementation is supported by the large amount of real and reliable user data from the big-data era. However, with the increase of the users’ information-security awareness, these data are reduced or the quality of the data becomes worse. Singular Value Decomposition (SVD) is one of the common matrix factorization methods used in collaborative filtering, which introduces the bias information of users a...

  12. Improvement of the steel quality through zirconia base ceramic filter

    International Nuclear Information System (INIS)

    Santos, Benedito M.; Foschini, Cesar R.; Santos, Ieda M.G.; Pinheiro, Adriano S.; Paskocimas, Carlos A.; Leite, Edson R.; Longo, Elson

    1997-01-01

    At the end of production, the steel presents inclusions own to the making process. Ceramics filters, with controlled porosity, are being produced to eliminate the impurities, so as to increase the good quality steel production. This work studies the optimization of the zirconia filters composition and production for siderurgical processes application. The study was done through the granulometric control, using BET, XRD and Hg Porosimetry. (author)

  13. Stable and efficient cubature-based filtering in dynamical systems

    CERN Document Server

    Ballreich, Dominik

    2017-01-01

    The book addresses the problem of calculation of d-dimensional integrals (conditional expectations) in filter problems. It develops new methods of deterministic numerical integration, which can be used to speed up and stabilize filter algorithms. With the help of these methods, better estimates and predictions of latent variables are made possible in the fields of economics, engineering and physics. The resulting procedures are tested within four detailed simulation studies.

  14. Extended Kalman Filter Modifications Based on an Optimization View Point

    OpenAIRE

    Skoglund, Martin; Hendeby, Gustaf; Axehill, Daniel

    2015-01-01

    The extended Kalman filter (EKF) has been animportant tool for state estimation of nonlinear systems sinceits introduction. However, the EKF does not possess the same optimality properties as the Kalman filter, and may perform poorly. By viewing the EKF as an optimization problem it is possible to, in many cases, improve its performance and robustness. The paper derives three variations of the EKF by applying different optimisation algorithms to the EKF costfunction and relate these to the it...

  15. A model-based adaptive state of charge estimator for a lithium-ion battery using an improved adaptive particle filter

    International Nuclear Information System (INIS)

    Ye, Min; Guo, Hui; Cao, Binggang

    2017-01-01

    Highlights: • Propose an improved adaptive particle swarm filter method. • The SoC estimation method for the battery based on the adaptive particle swarm filter is presented. • The algorithm is validated by the case study of different aged extent batteries. • The effectiveness and applicability of the algorithm are validated by the LiPB batteries. - Abstract: Obtaining accurate parameters, state of charge (SoC) and capacity of a lithium-ion battery is crucial for a battery management system, and establishing a battery model online is complex. In addition, the errors and perturbations of the battery model dramatically increase throughout the battery lifetime, making it more challenging to model the battery online. To overcome these difficulties, this paper provides three contributions: (1) To improve the robustness of the adaptive particle filter algorithm, an error analysis method is added to the traditional adaptive particle swarm algorithm. (2) An online adaptive SoC estimator based on the improved adaptive particle filter is presented; this estimator can eliminate the estimation error due to battery degradation and initial SoC errors. (3) The effectiveness of the proposed method is verified using various initial states of lithium nickel manganese cobalt oxide (NMC) cells and lithium-ion polymer (LiPB) batteries. The experimental analysis shows that the maximum errors are less than 1% for both the voltage and SoC estimations and that the convergence time of the SoC estimation decreased to 120 s.

  16. Fast rail corrugation detection based on texture filtering

    Science.gov (United States)

    Xiao, Jie; Lu, Kaixia

    2018-02-01

    The condition detection of rails in high-speed railway is one of the important means to ensure the safety of railway transportation. In order to replace the traditional manual inspection, save manpower and material resources, and improve the detection speed and accuracy, it is of great significance to develop a machine vision system for locating and identifying defects on rails automatically. Rail defects exhibit different properties and are divided into various categories related to the type and position of flaws on the rail. Several kinds of interrelated factors cause rail defects such as type of rail, construction conditions, and speed and/or frequency of trains using the rail. Rail corrugation is a particular kind of defects that produce an undulatory deformation on the rail heads. In high speed train, the corrugation induces harmful vibrations on wheels and its components and reduces the lifetime of rails. This type of defects should be detected to avoid rail fractures. In this paper, a novel method for fast rail corrugation detection based on texture filtering was proposed.

  17. Integrated organic electronic based optochemical sensors using polarization filters

    International Nuclear Information System (INIS)

    Kraker, Elke; Haase, Anja; Lamprecht, Bernhard; Jakopic, Georg; Konrad, Christian; Koestler, Stefan

    2008-01-01

    A compact, integrated photoluminescence based oxygen and pH sensor, utilizing an organic light emitting device (OLED) as the light source and an organic photodiode (OPD) as the detection unit, is described. The main challenge in such an integrated sensor is the suppression of the excitation light at the detector, which is typically by many orders of magnitude higher in intensity than the emitted fluorescence. In our approach, we refrain from utilizing edge filters which require narrow band excitation sources and dyes with an adequate large Stokes shift. We rather developed an integrated sensor concept relying on two polarizers to separate the emission and excitation light. One polarizer is located right after the OLED, while the other one, oriented at 90 deg. to the first, is placed in front of the OPD. The main advantage of this solution is that any combination of excitation and emission light is acceptable, even if the two signals overlap spectrally. This is especially important for the use of OLEDs as the excitation sources, as these devices typically exhibit a broad spectral emission

  18. Fuzzy Logic Based Autonomous Parallel Parking System with Kalman Filtering

    Science.gov (United States)

    Panomruttanarug, Benjamas; Higuchi, Kohji

    This paper presents an emulation of fuzzy logic control schemes for an autonomous parallel parking system in a backward maneuver. There are four infrared sensors sending the distance data to a microcontroller for generating an obstacle-free parking path. Two of them mounted on the front and rear wheels on the parking side are used as the inputs to the fuzzy rules to calculate a proper steering angle while backing. The other two attached to the front and rear ends serve for avoiding collision with other cars along the parking space. At the end of parking processes, the vehicle will be in line with other parked cars and positioned in the middle of the free space. Fuzzy rules are designed based upon a wall following process. Performance of the infrared sensors is improved using Kalman filtering. The design method needs extra information from ultrasonic sensors. Starting from modeling the ultrasonic sensor in 1-D state space forms, one makes use of the infrared sensor as a measurement to update the predicted values. Experimental results demonstrate the effectiveness of sensor improvement.

  19. Emotion Recognition of Speech Signals Based on Filter Methods

    Directory of Open Access Journals (Sweden)

    Narjes Yazdanian

    2016-10-01

    Full Text Available Speech is the basic mean of communication among human beings.With the increase of transaction between human and machine, necessity of automatic dialogue and removing human factor has been considered. The aim of this study was to determine a set of affective features the speech signal is based on emotions. In this study system was designs that include three mains sections, features extraction, features selection and classification. After extraction of useful features such as, mel frequency cepstral coefficient (MFCC, linear prediction cepstral coefficients (LPC, perceptive linear prediction coefficients (PLP, ferment frequency, zero crossing rate, cepstral coefficients and pitch frequency, Mean, Jitter, Shimmer, Energy, Minimum, Maximum, Amplitude, Standard Deviation, at a later stage with filter methods such as Pearson Correlation Coefficient, t-test, relief and information gain, we came up with a method to rank and select effective features in emotion recognition. Then Result, are given to the classification system as a subset of input. In this classification stage, multi support vector machine are used to classify seven type of emotion. According to the results, that method of relief, together with multi support vector machine, has the most classification accuracy with emotion recognition rate of 93.94%.

  20. Online measurement of bead geometry in GMAW-based additive manufacturing using passive vision

    International Nuclear Information System (INIS)

    Xiong, Jun; Zhang, Guangjun

    2013-01-01

    Additive manufacturing based on gas metal arc welding is an advanced technique for depositing fully dense components with low cost. Despite this fact, techniques to achieve accurate control and automation of the process have not yet been perfectly developed. The online measurement of the deposited bead geometry is a key problem for reliable control. In this work a passive vision-sensing system, comprising two cameras and composite filtering techniques, was proposed for real-time detection of the bead height and width through deposition of thin walls. The nozzle to the top surface distance was monitored for eliminating accumulated height errors during the multi-layer deposition process. Various image processing algorithms were applied and discussed for extracting feature parameters. A calibration procedure was presented for the monitoring system. Validation experiments confirmed the effectiveness of the online measurement system for bead geometry in layered additive manufacturing. (paper)

  1. HIGH-PRECISION ATTITUDE ESTIMATION METHOD OF STAR SENSORS AND GYRO BASED ON COMPLEMENTARY FILTER AND UNSCENTED KALMAN FILTER

    Directory of Open Access Journals (Sweden)

    C. Guo

    2017-07-01

    Full Text Available Determining the attitude of satellite at the time of imaging then establishing the mathematical relationship between image points and ground points is essential in high-resolution remote sensing image mapping. Star tracker is insensitive to the high frequency attitude variation due to the measure noise and satellite jitter, but the low frequency attitude motion can be determined with high accuracy. Gyro, as a short-term reference to the satellite’s attitude, is sensitive to high frequency attitude change, but due to the existence of gyro drift and integral error, the attitude determination error increases with time. Based on the opposite noise frequency characteristics of two kinds of attitude sensors, this paper proposes an on-orbit attitude estimation method of star sensors and gyro based on Complementary Filter (CF and Unscented Kalman Filter (UKF. In this study, the principle and implementation of the proposed method are described. First, gyro attitude quaternions are acquired based on the attitude kinematics equation. An attitude information fusion method is then introduced, which applies high-pass filtering and low-pass filtering to the gyro and star tracker, respectively. Second, the attitude fusion data based on CF are introduced as the observed values of UKF system in the process of measurement updating. The accuracy and effectiveness of the method are validated based on the simulated sensors attitude data. The obtained results indicate that the proposed method can suppress the gyro drift and measure noise of attitude sensors, improving the accuracy of the attitude determination significantly, comparing with the simulated on-orbit attitude and the attitude estimation results of the UKF defined by the same simulation parameters.

  2. LC Filter Design for Wide Band Gap Device Based Adjustable Speed Drives

    DEFF Research Database (Denmark)

    Vadstrup, Casper; Wang, Xiongfei; Blaabjerg, Frede

    2014-01-01

    the LC filter with a higher cut off frequency and without damping resistors. The selection of inductance and capacitance is chosen based on capacitor voltage ripple and current ripple. The filter adds a base load to the inverter, which increases the inverter losses. It is shown how the modulation index...

  3. A Study of Scenic Spot Living Facility Recommendation Based on Collaborative Filtering

    Directory of Open Access Journals (Sweden)

    Luo Wenbiao

    2015-01-01

    Full Text Available For the collection of massive complex information, the collaborative filtering system can work as a highly efficient information screening tool. It can recommend reasonable information reserve with multi angles according to the living service facility information of the scenic spots. The collaborative filtering system can collect information and forecast rating results based on users’ preference. According to different recommendation goals, the collaborative filtering system can recommend results for user feedback and give feedback of the recommendation results in various forms.

  4. An online replanning method using warm start optimization and aperture morphing for flattening-filter-free beams

    International Nuclear Information System (INIS)

    Ahunbay, Ergun E.; Ates, O.; Li, X. A.

    2016-01-01

    Purpose: In a situation where a couch shift for patient positioning is not preferred or prohibited (e.g., MR-linac), segment aperture morphing (SAM) can address target dislocation and deformation. For IMRT/VMAT with flattening-filter-free (FFF) beams, however, SAM method would lead to an adverse translational dose effect due to the beam unflattening. Here the authors propose a new two-step process to address both the translational effect of FFF beams and the target deformation. Methods: The replanning method consists of an offline and an online step. The offline step is to create a series of preshifted-plans (PSPs) obtained by a so-called “warm start” optimization (starting optimization from the original plan, rather than from scratch) at a series of isocenter shifts. The PSPs all have the same number of segments with very similar shapes, since the warm start optimization only adjusts the MLC positions instead of regenerating them. In the online step, a new plan is obtained by picking the closest PSP or linearly interpolating the MLC positions and the monitor units of the closest PSPs for the shift determined from the image of the day. This two-step process is completely automated and almost instantaneous (no optimization or dose calculation needed). The previously developed SAM algorithm is then applied for daily deformation. The authors tested the method on sample prostate and pancreas cases. Results: The two-step interpolation method can account for the adverse dose effects from FFF beams, while SAM corrects for the target deformation. Plan interpolation method is effective in diminishing the unflat beam effect and may allow reducing the required number of PSPs. The whole process takes the same time as the previously reported SAM process (5–10 min). Conclusions: The new two-step method plus SAM can address both the translation effects of FFF beams and target deformation, and can be executed in full automation except the delineation of target contour

  5. An online replanning method using warm start optimization and aperture morphing for flattening-filter-free beams

    Energy Technology Data Exchange (ETDEWEB)

    Ahunbay, Ergun E., E-mail: eahunbay@mcw.edu; Ates, O.; Li, X. A. [Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin 53226 (United States)

    2016-08-15

    Purpose: In a situation where a couch shift for patient positioning is not preferred or prohibited (e.g., MR-linac), segment aperture morphing (SAM) can address target dislocation and deformation. For IMRT/VMAT with flattening-filter-free (FFF) beams, however, SAM method would lead to an adverse translational dose effect due to the beam unflattening. Here the authors propose a new two-step process to address both the translational effect of FFF beams and the target deformation. Methods: The replanning method consists of an offline and an online step. The offline step is to create a series of preshifted-plans (PSPs) obtained by a so-called “warm start” optimization (starting optimization from the original plan, rather than from scratch) at a series of isocenter shifts. The PSPs all have the same number of segments with very similar shapes, since the warm start optimization only adjusts the MLC positions instead of regenerating them. In the online step, a new plan is obtained by picking the closest PSP or linearly interpolating the MLC positions and the monitor units of the closest PSPs for the shift determined from the image of the day. This two-step process is completely automated and almost instantaneous (no optimization or dose calculation needed). The previously developed SAM algorithm is then applied for daily deformation. The authors tested the method on sample prostate and pancreas cases. Results: The two-step interpolation method can account for the adverse dose effects from FFF beams, while SAM corrects for the target deformation. Plan interpolation method is effective in diminishing the unflat beam effect and may allow reducing the required number of PSPs. The whole process takes the same time as the previously reported SAM process (5–10 min). Conclusions: The new two-step method plus SAM can address both the translation effects of FFF beams and target deformation, and can be executed in full automation except the delineation of target contour

  6. All-Pass Filter Based Linear Voltage Controlled Quadrature Oscillator

    Directory of Open Access Journals (Sweden)

    Koushick Mathur

    2017-01-01

    Full Text Available A linear voltage controlled quadrature oscillator implemented from a first-order electronically tunable all-pass filter (ETAF is presented. The active element is commercially available current feedback amplifier (AD844 in conjunction with the relatively new Multiplication Mode Current Conveyor (MMCC device. Electronic tunability is obtained by the control node voltage (V of the MMCC. Effects of the device nonidealities, namely, the parasitic capacitors and the roll-off poles of the port-transfer ratios of the device, are shown to be negligible, even though the usable high-frequency ranges are constrained by these imperfections. Subsequently the filter is looped with an electronically tunable integrator (ETI to implement the quadrature oscillator (QO. Experimental responses on the voltage tunable phase of the filter and the linear-tuning law of the quadrature oscillator up to 9.9 MHz at low THD are verified by simulation and hardware tests.

  7. Thermally controlled femtosecond pulse shaping using metasurface based optical filters

    Science.gov (United States)

    Rahimi, Eesa; Şendur, Kürşat

    2018-02-01

    Shaping of the temporal distribution of the ultrashort pulses, compensation of pulse deformations due to phase shift in transmission and amplification are of interest in various optical applications. To address these problems, in this study, we have demonstrated an ultra-thin reconfigurable localized surface plasmon (LSP) band-stop optical filter driven by insulator-metal phase transition of vanadium dioxide. A Joule heating mechanism is proposed to control the thermal phase transition of the material. The resulting permittivity variation of vanadium dioxide tailors spectral response of the transmitted pulse from the stack. Depending on how the pulse's spectrum is located with respect to the resonance of the band-stop filter, the thin film stack can dynamically compress/expand the output pulse span up to 20% or shift its phase up to 360°. Multi-stacked filters have shown the ability to dynamically compensate input carrier frequency shifts and pulse span variations besides their higher span expansion rates.

  8. Efficient OCT Image Enhancement Based on Collaborative Shock Filtering.

    Science.gov (United States)

    Liu, Guohua; Wang, Ziyu; Mu, Guoying; Li, Peijin

    2018-01-01

    Efficient enhancement of noisy optical coherence tomography (OCT) images is a key task for interpreting them correctly. In this paper, to better enhance details and layered structures of a human retina image, we propose a collaborative shock filtering for OCT image denoising and enhancement. Noisy OCT image is first denoised by a collaborative filtering method with new similarity measure, and then the denoised image is sharpened by a shock-type filtering for edge and detail enhancement. For dim OCT images, in order to improve image contrast for the detection of tiny lesions, a gamma transformation is first used to enhance the images within proper gray levels. The proposed method integrating image smoothing and sharpening simultaneously obtains better visual results in experiments.

  9. BPSK Receiver Based on Recursive Adaptive Filter with Remodulation

    Directory of Open Access Journals (Sweden)

    N. Milosevic

    2011-12-01

    Full Text Available This paper proposes a new binary phase shift keying (BPSK signal receiver intended for reception under conditions of significant carrier frequency offsets. The recursive adaptive filter with least mean squares (LMS adaptation is used. The proposed receiver has a constant, defining the balance between the recursive and the nonrecursive part of the filter, whose proper choice allows a simple construction of the receiver. The correct choice of this parameter could result in unitary length of the filter. The proposed receiver has performance very close to the performance of the BPSK receiver with perfect frequency synchronization, in a wide range of frequency offsets (plus/minus quarter of the signal bandwidth. The results obtained by the software simulation are confirmed by the experimental results measured on the receiver realized with the universal software radio peripheral (USRP, with the baseband signal processing at personal computer (PC.

  10. Interference suppression using a SAW-based adaptive filter

    Science.gov (United States)

    Saulnier, Gary J.; Grant, Calvin J.; Das, Pankaj K.

    The structure and performance of a transversal filter interference suppressor that has been constructed using a surface acoustic wave (SAW) delay line are described. The delay line operates at a center frequency of 300 MHz and has eight equally spaced taps with an intertap delay of 150 ns. In the programmable mode, the tap weights are externally controllable, and in the adaptive mode, the tap weights are adjusted using the Widrow-Hoff least-mean-squared algorithm. Experimental results are provided that illustrate the performance of the filter in both the adaptive and programmable modes. Filter responses obtained in the adaptive mode are shown, along with spectra demonstrating the corresponding interference suppression. Bit-error-rate performance results for a single-tone jammer interfering with a direct sequence spread spectrum signal are presented.

  11. Ballistic target tracking algorithm based on improved particle filtering

    Science.gov (United States)

    Ning, Xiao-lei; Chen, Zhan-qi; Li, Xiao-yang

    2015-10-01

    Tracking ballistic re-entry target is a typical nonlinear filtering problem. In order to track the ballistic re-entry target in the nonlinear and non-Gaussian complex environment, a novel chaos map particle filter (CMPF) is used to estimate the target state. CMPF has better performance in application to estimate the state and parameter of nonlinear and non-Gassuian system. The Monte Carlo simulation results show that, this method can effectively solve particle degeneracy and particle impoverishment problem by improving the efficiency of particle sampling to obtain the better particles to part in estimation. Meanwhile CMPF can improve the state estimation precision and convergence velocity compared with EKF, UKF and the ordinary particle filter.

  12. An Adjoint-Based Adaptive Ensemble Kalman Filter

    KAUST Repository

    Song, Hajoon

    2013-10-01

    A new hybrid ensemble Kalman filter/four-dimensional variational data assimilation (EnKF/4D-VAR) approach is introduced to mitigate background covariance limitations in the EnKF. The work is based on the adaptive EnKF (AEnKF) method, which bears a strong resemblance to the hybrid EnKF/three-dimensional variational data assimilation (3D-VAR) method. In the AEnKF, the representativeness of the EnKF ensemble is regularly enhanced with new members generated after back projection of the EnKF analysis residuals to state space using a 3D-VAR [or optimal interpolation (OI)] scheme with a preselected background covariance matrix. The idea here is to reformulate the transformation of the residuals as a 4D-VAR problem, constraining the new member with model dynamics and the previous observations. This should provide more information for the estimation of the new member and reduce dependence of the AEnKF on the assumed stationary background covariance matrix. This is done by integrating the analysis residuals backward in time with the adjoint model. Numerical experiments are performed with the Lorenz-96 model under different scenarios to test the new approach and to evaluate its performance with respect to the EnKF and the hybrid EnKF/3D-VAR. The new method leads to the least root-mean-square estimation errors as long as the linear assumption guaranteeing the stability of the adjoint model holds. It is also found to be less sensitive to choices of the assimilation system inputs and parameters.

  13. Fast generation of Fresnel holograms based on multirate filtering.

    Science.gov (United States)

    Tsang, Peter; Liu, Jung-Ping; Cheung, Wai-Keung; Poon, Ting-Chung

    2009-12-01

    One of the major problems in computer-generated holography is the high computation cost involved for the calculation of fringe patterns. Recently, the problem has been addressed by imposing a horizontal parallax only constraint whereby the process can be simplified to the computation of one-dimensional sublines, each representing a scan plane of the object scene. Subsequently the sublines can be expanded to a two-dimensional hologram through multiplication with a reference signal. Furthermore, economical hardware is available with which sublines can be generated in a computationally free manner with high throughput of approximately 100 M pixels/second. Apart from decreasing the computation loading, the sublines can be treated as intermediate data that can be compressed by simply downsampling the number of sublines. Despite these favorable features, the method is suitable only for the generation of white light (rainbow) holograms, and the resolution of the reconstructed image is inferior to the classical Fresnel hologram. We propose to generate holograms from one-dimensional sublines so that the above-mentioned problems can be alleviated. However, such an approach also leads to a substantial increase in computation loading. To overcome this problem we encapsulated the conversion of sublines to holograms as a multirate filtering process and implemented the latter by use of a fast Fourier transform. Evaluation reveals that, for holograms of moderate size, our method is capable of operating 40,000 times faster than the calculation of Fresnel holograms based on the precomputed table lookup method. Although there is no relative vertical parallax between object points at different distance planes, a global vertical parallax is preserved for the object scene as a whole and the reconstructed image can be observed easily.

  14. An Adjoint-Based Adaptive Ensemble Kalman Filter

    KAUST Repository

    Song, Hajoon; Hoteit, Ibrahim; Cornuelle, Bruce D.; Luo, Xiaodong; Subramanian, Aneesh C.

    2013-01-01

    A new hybrid ensemble Kalman filter/four-dimensional variational data assimilation (EnKF/4D-VAR) approach is introduced to mitigate background covariance limitations in the EnKF. The work is based on the adaptive EnKF (AEnKF) method, which bears a strong resemblance to the hybrid EnKF/three-dimensional variational data assimilation (3D-VAR) method. In the AEnKF, the representativeness of the EnKF ensemble is regularly enhanced with new members generated after back projection of the EnKF analysis residuals to state space using a 3D-VAR [or optimal interpolation (OI)] scheme with a preselected background covariance matrix. The idea here is to reformulate the transformation of the residuals as a 4D-VAR problem, constraining the new member with model dynamics and the previous observations. This should provide more information for the estimation of the new member and reduce dependence of the AEnKF on the assumed stationary background covariance matrix. This is done by integrating the analysis residuals backward in time with the adjoint model. Numerical experiments are performed with the Lorenz-96 model under different scenarios to test the new approach and to evaluate its performance with respect to the EnKF and the hybrid EnKF/3D-VAR. The new method leads to the least root-mean-square estimation errors as long as the linear assumption guaranteeing the stability of the adjoint model holds. It is also found to be less sensitive to choices of the assimilation system inputs and parameters.

  15. Development of active porous medium filters based on plasma textiles

    International Nuclear Information System (INIS)

    Kuznetsov, Ivan A.; Saveliev, Alexei V.; Rasipuram, Srinivasan; Kuznetsov, Andrey V.; Brown, Alan; Jasper, Warren

    2012-01-01

    Inexpensive, flexible, washable, and durable materials that serve as antimicrobial filters and self-decontaminating fabrics are needed to provide active protection to people in areas regularly exposed to various biohazards, such as hospitals and bio research labs working with pathogens. Airlines and cruise lines need such material to combat the spread of infections. In households these materials can be used in HVAC filters to fight indoor pollution, which is especially dangerous to people suffering from asthma. Efficient filtering materials are also required in areas contaminated by other types of hazardous dust particulates, such as nuclear dust. The primary idea that guided the undertaken study is that a microplasma-generating structure can be embedded in a textile fabric to generate a plasma sheath (''plasma shield'') that kills bacterial agents coming in contact with the fabric. The research resulted in the development of a plasma textile that can be used for producing new types of self-decontaminating garments, fabrics, and filter materials, capable of activating a plasma sheath that would filter, capture, and destroy any bacteriological agent deposited on its surface. This new material relies on the unique antimicrobial and catalytic properties of cold (room temperature) plasma that is benign to people and does not cause thermal damage to many polymer textiles, such as Nomex and polypropylene. The uniqueness of cold plasma as a disinfecting agent lies in the inability of bacteria to develop resistance to plasma exposure, as they can for antibiotics. Plasma textiles could thus be utilized for microbial destruction in active antimicrobial filters (for continuous decontamination and disinfection of large amounts of air) as well as in self-decontaminating surfaces and antibacterial barriers (for example, for creating local antiseptic or sterile environments around wounds and burns).

  16. Development of active porous medium filters based on plasma textiles

    Science.gov (United States)

    Kuznetsov, Ivan A.; Saveliev, Alexei V.; Rasipuram, Srinivasan; Kuznetsov, Andrey V.; Brown, Alan; Jasper, Warren

    2012-05-01

    Inexpensive, flexible, washable, and durable materials that serve as antimicrobial filters and self-decontaminating fabrics are needed to provide active protection to people in areas regularly exposed to various biohazards, such as hospitals and bio research labs working with pathogens. Airlines and cruise lines need such material to combat the spread of infections. In households these materials can be used in HVAC filters to fight indoor pollution, which is especially dangerous to people suffering from asthma. Efficient filtering materials are also required in areas contaminated by other types of hazardous dust particulates, such as nuclear dust. The primary idea that guided the undertaken study is that a microplasma-generating structure can be embedded in a textile fabric to generate a plasma sheath ("plasma shield") that kills bacterial agents coming in contact with the fabric. The research resulted in the development of a plasma textile that can be used for producing new types of self-decontaminating garments, fabrics, and filter materials, capable of activating a plasma sheath that would filter, capture, and destroy any bacteriological agent deposited on its surface. This new material relies on the unique antimicrobial and catalytic properties of cold (room temperature) plasma that is benign to people and does not cause thermal damage to many polymer textiles, such as Nomex and polypropylene. The uniqueness of cold plasma as a disinfecting agent lies in the inability of bacteria to develop resistance to plasma exposure, as they can for antibiotics. Plasma textiles could thus be utilized for microbial destruction in active antimicrobial filters (for continuous decontamination and disinfection of large amounts of air) as well as in self-decontaminating surfaces and antibacterial barriers (for example, for creating local antiseptic or sterile environments around wounds and burns).

  17. Development of active porous medium filters based on plasma textiles

    Energy Technology Data Exchange (ETDEWEB)

    Kuznetsov, Ivan A.; Saveliev, Alexei V.; Rasipuram, Srinivasan; Kuznetsov, Andrey V.; Brown, Alan; Jasper, Warren [Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695 (United States); Textile Engineering Chemistry and Science, North Carolina State University, Raleigh, NC 27695 (United States)

    2012-05-15

    Inexpensive, flexible, washable, and durable materials that serve as antimicrobial filters and self-decontaminating fabrics are needed to provide active protection to people in areas regularly exposed to various biohazards, such as hospitals and bio research labs working with pathogens. Airlines and cruise lines need such material to combat the spread of infections. In households these materials can be used in HVAC filters to fight indoor pollution, which is especially dangerous to people suffering from asthma. Efficient filtering materials are also required in areas contaminated by other types of hazardous dust particulates, such as nuclear dust. The primary idea that guided the undertaken study is that a microplasma-generating structure can be embedded in a textile fabric to generate a plasma sheath (''plasma shield'') that kills bacterial agents coming in contact with the fabric. The research resulted in the development of a plasma textile that can be used for producing new types of self-decontaminating garments, fabrics, and filter materials, capable of activating a plasma sheath that would filter, capture, and destroy any bacteriological agent deposited on its surface. This new material relies on the unique antimicrobial and catalytic properties of cold (room temperature) plasma that is benign to people and does not cause thermal damage to many polymer textiles, such as Nomex and polypropylene. The uniqueness of cold plasma as a disinfecting agent lies in the inability of bacteria to develop resistance to plasma exposure, as they can for antibiotics. Plasma textiles could thus be utilized for microbial destruction in active antimicrobial filters (for continuous decontamination and disinfection of large amounts of air) as well as in self-decontaminating surfaces and antibacterial barriers (for example, for creating local antiseptic or sterile environments around wounds and burns).

  18. Improving Web-Based Student Learning Through Online Video Demonstrations

    Science.gov (United States)

    Miller, Scott; Redman, S.

    2010-01-01

    Students in online courses continue to lag their peers in comparable face-to-face (F2F) courses (Ury 2004, Slater & Jones 2004). A meta-study of web-based vs. classroom instruction by Sitzmann et al (2006) discovered that the degree of learner control positively influences the effectiveness of instruction: students do better when they are in control of their own learning. In particular, web-based courses are more effective when they incorporate a larger variety of instructional methods. To address this need, we developed a series of online videos to demonstrate various astronomical concepts and provided them to students enrolled in an online introductory astronomy course at Penn State University. We found that the online students performed worse than the F2F students on questions unrelated to the videos (t = -2.84), but that the online students who watched the videos performed better than the F2F students on related examination questions (t = 2.11). We also found that the online students who watched the videos performed significantly better than those who did not (t = 3.43). While the videos in general proved helpful, some videos were more helpful than others. We will discuss our thoughts on why this might be, and future plans to improve upon this study. These videos are freely available on iTunesU, YouTube, and Google Video.

  19. Particle-filtering-based estimation of maximum available power state in Lithium-Ion batteries

    International Nuclear Information System (INIS)

    Burgos-Mellado, Claudio; Orchard, Marcos E.; Kazerani, Mehrdad; Cárdenas, Roberto; Sáez, Doris

    2016-01-01

    Highlights: • Approach to estimate the state of maximum power available in Lithium-Ion battery. • Optimisation problem is formulated on the basis of a non-linear dynamic model. • Solutions of the optimisation problem are functions of state of charge estimates. • State of charge estimates computed using particle filter algorithms. - Abstract: Battery Energy Storage Systems (BESS) are important for applications related to both microgrids and electric vehicles. If BESS are used as the main energy source, then it is required to include adequate procedures for the estimation of critical variables such as the State of Charge (SoC) and the State of Health (SoH) in the design of Battery Management Systems (BMS). Furthermore, in applications where batteries are exposed to high charge and discharge rates it is also desirable to estimate the State of Maximum Power Available (SoMPA). In this regard, this paper presents a novel approach to the estimation of SoMPA in Lithium-Ion batteries. This method formulates an optimisation problem for the battery power based on a non-linear dynamic model, where the resulting solutions are functions of the SoC. In the battery model, the polarisation resistance is modelled using fuzzy rules that are function of both SoC and the discharge (charge) current. Particle filtering algorithms are used as an online estimation technique, mainly because these algorithms allow approximating the probability density functions of the SoC and SoMPA even in the case of non-Gaussian sources of uncertainty. The proposed method for SoMPA estimation is validated using the experimental data obtained from an experimental setup designed for charging and discharging the Lithium-Ion batteries.

  20. UFIR Filtering for GPS-Based Tracking over WSNs with Delayed and Missing Data

    Directory of Open Access Journals (Sweden)

    Karen Uribe-Murcia

    2018-01-01

    Full Text Available In smart cities, vehicles tracking is organized to increase safety by localizing cars using the Global Positioning System (GPS. The GPS-based system provides accurate tracking but is also required to be reliable and robust. As a main estimator, we propose using the unbiased finite impulse response (UFIR filter, which meets these needs as being more robust than the Kalman filter (KF. The UFIR filter is developed for vehicle tracking in discrete-time state-space over wireless sensor networks (WSNs with time-stamped data discretely delayed on k-step-lags and missing data. The state-space model is represented in a way such that the UFIR filter, KF, and H∞ filter can be used universally. Applications are given for measurement data, which are cooperatively transferred from a vehicle to a central station through several nodes with k-step-lags. Better tracking performance of the UFIR filter is shown experimentally.

  1. Photonic crystal ring resonator based optical filters for photonic integrated circuits

    International Nuclear Information System (INIS)

    Robinson, S.

    2014-01-01

    In this paper, a two Dimensional (2D) Photonic Crystal Ring Resonator (PCRR) based optical Filters namely Add Drop Filter, Bandpass Filter, and Bandstop Filter are designed for Photonic Integrated Circuits (PICs). The normalized output response of the filters is obtained using 2D Finite Difference Time Domain (FDTD) method and the band diagram of periodic and non-periodic structure is attained by Plane Wave Expansion (PWE) method. The size of the device is minimized from a scale of few tens of millimeters to the order of micrometers. The overall size of the filters is around 11.4 μm × 11.4 μm which is highly suitable of photonic integrated circuits

  2. Design and control of an LCL-filter-based three-phase active rectifier

    DEFF Research Database (Denmark)

    Liserre, Marco; Blaabjerg, Frede; Hansen, Steffan

    2005-01-01

    This paper proposes a step-by-step procedure for designing the LCL filter of a front-end three-phase active rectifier. The primary goal is to reduce the switching frequency ripple at a reasonable cost, while at the same time achieving a high-performance front-end rectifier (as characterized...... by a rapid dynamic response and good stability margin). An example LCL filter design is reported and a filter has been built and tested using the values obtained from this design. The experimental results demonstrate the performance of the design procedure both for the LCL filter and for the rectifier...... a powerful tool to design an LCL-filter-based active rectifier while avoiding trial-and-error procedures that can result in having to build several filter prototypes....

  3. Modelling of the modified-LLCL-filter-based single-phase grid-tied Aalborg inverter

    DEFF Research Database (Denmark)

    Liu, Zifa; Wu, Huiyun; Liu, Yuan

    2017-01-01

    Owing to less conduction and switching power losses, the recently proposed Aalborg inverter has high efficiency within a wide range of input DC voltage for single-phase DC/AC power conversion. In theory, the conduction power losses can be further decreased, if an LLCL-filter is adopted instead...... of an LCL-filter for a voltage source inverter, mainly due to the reduced inductance. The Aalborg inverter shows the characteristic of a current source inverter, when working in the `boost' state. Whether the LLCL-filter can meet the control requirement of this type inverter needs to be further explored....... In this study, the small signal analysis for the modified-LLCL-filter-based Aalborg inverter is addressed. Through the modelling, it can be proven that compared with the LCL-filter, the modified-LLCL-filter causes no extra control challenge for the Aalborg inverter, and therefore more inductance in the power...

  4. Applications of Kalman filters based on non-linear functions to numerical weather predictions

    Directory of Open Access Journals (Sweden)

    G. Galanis

    2006-10-01

    Full Text Available This paper investigates the use of non-linear functions in classical Kalman filter algorithms on the improvement of regional weather forecasts. The main aim is the implementation of non linear polynomial mappings in a usual linear Kalman filter in order to simulate better non linear problems in numerical weather prediction. In addition, the optimal order of the polynomials applied for such a filter is identified. This work is based on observations and corresponding numerical weather predictions of two meteorological parameters characterized by essential differences in their evolution in time, namely, air temperature and wind speed. It is shown that in both cases, a polynomial of low order is adequate for eliminating any systematic error, while higher order functions lead to instabilities in the filtered results having, at the same time, trivial contribution to the sensitivity of the filter. It is further demonstrated that the filter is independent of the time period and the geographic location of application.

  5. Applications of Kalman filters based on non-linear functions to numerical weather predictions

    Directory of Open Access Journals (Sweden)

    G. Galanis

    2006-10-01

    Full Text Available This paper investigates the use of non-linear functions in classical Kalman filter algorithms on the improvement of regional weather forecasts. The main aim is the implementation of non linear polynomial mappings in a usual linear Kalman filter in order to simulate better non linear problems in numerical weather prediction. In addition, the optimal order of the polynomials applied for such a filter is identified. This work is based on observations and corresponding numerical weather predictions of two meteorological parameters characterized by essential differences in their evolution in time, namely, air temperature and wind speed. It is shown that in both cases, a polynomial of low order is adequate for eliminating any systematic error, while higher order functions lead to instabilities in the filtered results having, at the same time, trivial contribution to the sensitivity of the filter. It is further demonstrated that the filter is independent of the time period and the geographic location of application.

  6. Measurement-based local quantum filters and their ability to ...

    Indian Academy of Sciences (India)

    Debmalya Das

    2017-05-30

    May 30, 2017 ... Entanglement; local filters; quantum measurement. PACS No. 03.65 ... ties [4,5], it also plays a key role in quantum computing where it is ... Furthermore, we pro- vide an ..... Corresponding to each of these vectors, we can con-.

  7. Comparison of three filters in asteroid-based autonomous navigation

    International Nuclear Information System (INIS)

    Cui Wen; Zhu Kai-Jian

    2014-01-01

    At present, optical autonomous navigation has become a key technology in deep space exploration programs. Recent studies focus on the problem of orbit determination using autonomous navigation, and the choice of filter is one of the main issues. To prepare for a possible exploration mission to Mars, the primary emphasis of this paper is to evaluate the capability of three filters, the extended Kalman filter (EKF), unscented Kalman filter (UKF) and weighted least-squares (WLS) algorithm, which have different initial states during the cruise phase. One initial state is assumed to have high accuracy with the support of ground tracking when autonomous navigation is operating; for the other state, errors are set to be large without this support. In addition, the method of selecting asteroids that can be used for navigation from known lists of asteroids to form a sequence is also presented in this study. The simulation results show that WLS and UKF should be the first choice for optical autonomous navigation during the cruise phase to Mars

  8. Molecular filter-based diagnostics in high speed flows

    Science.gov (United States)

    Elliott, Gregory S.; Samimy, MO; Arnette, Stephen A.

    1993-01-01

    The use of iodine molecular filters in nonintrusive planar velocimetry methods is examined. Detailed absorption profiles are obtained to highlight the effects that determine the profile shape. It is shown that pressure broadening induced by the presence of a nonabsorbing vapor can be utilized to significantly change the slopes bounding the absorbing region while remaining in the optically-thick regime.

  9. Efficient Kernel-Based Ensemble Gaussian Mixture Filtering

    KAUST Repository

    Liu, Bo; Ait-El-Fquih, Boujemaa; Hoteit, Ibrahim

    2015-01-01

    (KF)-like update of the ensemble members and a particle filter (PF)-like update of the weights, followed by a resampling step to start a new forecast cycle. After formulating EnGMF for any observational operator, we analyze the influence

  10. DSP based adaptive hysteresis-band current controlled active filter ...

    African Journals Online (AJOL)

    The use of non-linear loads critically affects the quality of supply by drawing harmonic currents and reactive power from the electrical distribution system. Active power filters are the most viable solution for solving such power quality problems in compliance with the harmonic standards. This article presents a digital signal ...

  11. FOG Random Drift Signal Denoising Based on the Improved AR Model and Modified Sage-Husa Adaptive Kalman Filter.

    Science.gov (United States)

    Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao

    2016-07-12

    In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved.

  12. Gender-Based Analysis On-Line Dialogue. Final Report.

    Science.gov (United States)

    2001

    An online dialogue on gender-based analysis (GBA) was held from February 15 to March 7, 2001. Invitations and a background paper titled "Why Gender-Based Analysis?" were sent to 350 women's organizations and individuals throughout Canada. Efforts were made to ensure that aboriginal and Metis women, visible minority women, and women with…

  13. Ultrafast all-optical clock recovery based on phase-only linear optical filtering

    DEFF Research Database (Denmark)

    Maram, Reza; Kong, Deming; Galili, Michael

    2014-01-01

    We report on a novel technique for all-optical clock recovery from RZ OOK data based on phase-only filtering, significantly enhancing the recovered clock quality and energy-efficiency compared to the use of a Fabry-Perot filter....

  14. 640 Gbit/s RZ-to-NRZ format conversion based on optical phase filtering

    DEFF Research Database (Denmark)

    Maram, Reza; Kong, Deming; Galili, Michael

    2014-01-01

    We propose a novel approach for all optical RZ-to-NRZ conversion based on optical phase filtering. The proposed concept is experimentally validated through format conversion of a 640 Gbit/s coherent RZ signal to NRZ signal using a simple phase filter implemented by a commercial optical waveshaper....

  15. Proposing Wavelet-Based Low-Pass Filter and Input Filter to Improve Transient Response of Grid-Connected Photovoltaic Systems

    Directory of Open Access Journals (Sweden)

    Bijan Rahmani

    2016-08-01

    Full Text Available Available photovoltaic (PV systems show a prolonged transient response, when integrated into the power grid via active filters. On one hand, the conventional low-pass filter, employed within the integrated PV system, works with a large delay, particularly in the presence of system’s low-order harmonics. On the other hand, the switching of the DC (direct current–DC converters within PV units also prolongs the transient response of an integrated system, injecting harmonics and distortion through the PV-end current. This paper initially develops a wavelet-based low-pass filter to improve the transient response of the interconnected PV systems to grid lines. Further, a damped input filter is proposed within the PV system to address the raised converter’s switching issue. Finally, Matlab/Simulink simulations validate the effectiveness of the proposed wavelet-based low-pass filter and damped input filter within an integrated PV system.

  16. Pleasant/Unpleasant Filtering for Affective Image Retrieval Based on Cross-Correlation of EEG Features

    Directory of Open Access Journals (Sweden)

    Keranmu Xielifuguli

    2014-01-01

    Full Text Available People often make decisions based on sensitivity rather than rationality. In the field of biological information processing, methods are available for analyzing biological information directly based on electroencephalogram: EEG to determine the pleasant/unpleasant reactions of users. In this study, we propose a sensitivity filtering technique for discriminating preferences (pleasant/unpleasant for images using a sensitivity image filtering system based on EEG. Using a set of images retrieved by similarity retrieval, we perform the sensitivity-based pleasant/unpleasant classification of images based on the affective features extracted from images with the maximum entropy method: MEM. In the present study, the affective features comprised cross-correlation features obtained from EEGs produced when an individual observed an image. However, it is difficult to measure the EEG when a subject visualizes an unknown image. Thus, we propose a solution where a linear regression method based on canonical correlation is used to estimate the cross-correlation features from image features. Experiments were conducted to evaluate the validity of sensitivity filtering compared with image similarity retrieval methods based on image features. We found that sensitivity filtering using color correlograms was suitable for the classification of preferred images, while sensitivity filtering using local binary patterns was suitable for the classification of unpleasant images. Moreover, sensitivity filtering using local binary patterns for unpleasant images had a 90% success rate. Thus, we conclude that the proposed method is efficient for filtering unpleasant images.

  17. Accelerometer North Finding System Based on the Wavelet Packet De-noising Algorithm and Filtering Circuit

    Directory of Open Access Journals (Sweden)

    LU Yongle

    2014-07-01

    Full Text Available This paper demonstrates a method and system for north finding with a low-cost piezoelectricity accelerometer based on the Coriolis acceleration principle. The proposed setup is based on the choice of an accelerometer with residual noise of 35 ng•Hz-1/2. The plane of the north finding system is aligned parallel to the local level, which helps to eliminate the effect of plane error. The Coriolis acceleration caused by the earth’s rotation and the acceleration’s instantaneous velocity is much weaker than the g-sensitivity acceleration. To get a high accuracy and a shorter time for north finding system, in this paper, the Filtering Circuit and the wavelet packet de-nosing algorithm are used as the following. First, the hardware is designed as the alternating currents across by filtering circuit, so the DC will be isolated and the weak AC signal will be amplified. The DC is interfering signal generated by the earth's gravity. Then, we have used a wavelet packet to filter the signal which has been done through the filtering circuit. Finally, compare the north finding results measured by wavelet packet filtering with those measured by a low-pass filter. Wavelet filter de-noise data shows that wavelet packet filtering and wavelet filter measurement have high accuracy. Wavelet Packet filtering has stronger ability to remove burst noise and higher engineering environment adaptability than that of Wavelet filtering. Experimental results prove the effectiveness and project implementation of the accelerometer north finding method based on wavelet packet de-noising algorithm.

  18. Multi-tap complex-coefficient incoherent microwave photonic filters based on optical single-sideband modulation and narrow band optical filtering.

    Science.gov (United States)

    Sagues, Mikel; García Olcina, Raimundo; Loayssa, Alayn; Sales, Salvador; Capmany, José

    2008-01-07

    We propose a novel scheme to implement tunable multi-tap complex coefficient filters based on optical single sideband modulation and narrow band optical filtering. A four tap filter is experimentally demonstrated to highlight the enhanced tuning performance provided by complex coefficients. Optical processing is performed by the use of a cascade of four phase-shifted fiber Bragg gratings specifically fabricated for this purpose.

  19. Preparation of affordable and multifunctional clay-based ceramic filter matrix for treatment of drinking water.

    Science.gov (United States)

    Shivaraju, H Puttaiah; Egumbo, Henok; Madhusudan, P; Anil Kumar, K M; Midhun, G

    2018-02-01

    Affordable clay-based ceramic filters with multifunctional properties were prepared using low-cost and active ingredients. The characterization results clearly revealed well crystallinity, structural elucidation, extensive porosity, higher surface area, higher stability, and durability which apparently enhance the treatment efficiency. The filtration rates of ceramic filter were evaluated under gravity and the results obtained were compared with a typical gravity slow sand filter (GSSF). All ceramic filters showed significant filtration rates of about 50-180 m/h, which is comparatively higher than the typical GSSF. Further, purification efficiency of clay-based ceramic filters was evaluated by considering important drinking water parameters and contaminants. A significant removal potential was achieved by the clay-based ceramic filter with 25% and 30% activated carbon along with active agents. Desired drinking water quality parameters were achieved by potential removal of nitrite (98.5%), nitrate (80.5%), total dissolved solids (62%), total hardness (55%), total organic pollutants (89%), and pathogenic microorganisms (100%) using ceramic filters within a short duration. The remarkable purification and disinfection efficiencies were attributed to the extensive porosity (0.202 cm 3  g -1 ), surface area (124.61 m 2  g -1 ), stability, and presence of active nanoparticles such as Cu, TiO 2 , and Ag within the porous matrix of the ceramic filter.

  20. Gene regulatory network inference by point-based Gaussian approximation filters incorporating the prior information.

    Science.gov (United States)

    Jia, Bin; Wang, Xiaodong

    2013-12-17

    : The extended Kalman filter (EKF) has been applied to inferring gene regulatory networks. However, it is well known that the EKF becomes less accurate when the system exhibits high nonlinearity. In addition, certain prior information about the gene regulatory network exists in practice, and no systematic approach has been developed to incorporate such prior information into the Kalman-type filter for inferring the structure of the gene regulatory network. In this paper, an inference framework based on point-based Gaussian approximation filters that can exploit the prior information is developed to solve the gene regulatory network inference problem. Different point-based Gaussian approximation filters, including the unscented Kalman filter (UKF), the third-degree cubature Kalman filter (CKF3), and the fifth-degree cubature Kalman filter (CKF5) are employed. Several types of network prior information, including the existing network structure information, sparsity assumption, and the range constraint of parameters, are considered, and the corresponding filters incorporating the prior information are developed. Experiments on a synthetic network of eight genes and the yeast protein synthesis network of five genes are carried out to demonstrate the performance of the proposed framework. The results show that the proposed methods provide more accurate inference results than existing methods, such as the EKF and the traditional UKF.

  1. Thickness filters for gradient based multi-material and thickness optimization of laminated composite structures

    DEFF Research Database (Denmark)

    Sørensen, Rene; Lund, Erik

    2015-01-01

    This paper presents a new gradient based method for performing discrete material and thickness optimization of laminated composite structures. The novelty in the new method lies in the application of so-called casting constraints, or thickness filters in this context, to control the thickness...... variation throughout the laminate. The filters replace the layerwise density variables with a single continuous through-the-thickness design variable. Consequently, the filters eliminate the need for having explicit constraints for preventing intermediate void through the thickness of the laminate....... Therefore, the filters reduce both the number of constraints and design variables in the optimization problem. Based upon a continuous approximation of a unit step function, the thickness filters are capable of projecting discrete 0/1 values to the underlying layerwise or ”physical” density variables which...

  2. Active Damping Techniques for LCL-Filtered Inverters-Based Microgrids

    DEFF Research Database (Denmark)

    Lorzadeh, Iman; Firoozabadi, Mehdi Savaghebi; Askarian Abyaneh, Hossein

    2015-01-01

    LCL-type filters are widely used in gridconnected voltage source inverters, since it provides switching ripples reduction with lower cost and weight than the L-type counterpart. However, the inclusion of LCL-filters in voltage source inverters complicates the current control design regarding system...... the different active damping approaches for grid-connected inverters with LCL filters, which are based on high-order filters and additional feedbacks methods. These techniques are analyzed and discussed in detail....... stability issues; because an inherent resonance peak appears due to zero impedance at that resonance frequency. Moreover, in grid-interactive low-voltage microgrids, the interactions among the LCL-filtered-based parallel inverters may result in a more complex multiresonance issue which may compromise...

  3. Integrable microwave filter based on a photonic crystal delay line.

    Science.gov (United States)

    Sancho, Juan; Bourderionnet, Jerome; Lloret, Juan; Combrié, Sylvain; Gasulla, Ivana; Xavier, Stephane; Sales, Salvador; Colman, Pierre; Lehoucq, Gaelle; Dolfi, Daniel; Capmany, José; De Rossi, Alfredo

    2012-01-01

    The availability of a tunable delay line with a chip-size footprint is a crucial step towards the full implementation of integrated microwave photonic signal processors. Achieving a large and tunable group delay on a millimetre-sized chip is not trivial. Slow light concepts are an appropriate solution, if propagation losses are kept acceptable. Here we use a low-loss 1.5 mm-long photonic crystal waveguide to demonstrate both notch and band-pass microwave filters that can be tuned over the 0-50-GHz spectral band. The waveguide is capable of generating a controllable delay with limited signal attenuation (total insertion loss below 10 dB when the delay is below 70 ps) and degradation. Owing to the very small footprint of the delay line, a fully integrated device is feasible, also featuring more complex and elaborate filter functions.

  4. Fractional Resonance-Based RLβCα Filters

    Directory of Open Access Journals (Sweden)

    Todd J. Freeborn

    2013-01-01

    Full Text Available We propose the use of a fractional order capacitor and fractional order inductor with orders 0≤α,  β≤1, respectively, in a fractional RLβCα series circuit to realize fractional-step lowpass, highpass, bandpass, and bandreject filters. MATLAB simulations of lowpass and highpass responses having orders of (α+β=1.1, 1.5, and 1.9 and bandpass and bandreject responses having orders of 1.5 and 1.9 are given as examples. PSPICE simulations of 1.1, 1.5, and 1.9 order lowpass and 1.0 and 1.4 order bandreject filters using approximated fractional order capacitors and fractional order inductors verify the implementations.

  5. 32Still Image Compression Algorithm Based on Directional Filter Banks

    OpenAIRE

    Chunling Yang; Duanwu Cao; Li Ma

    2010-01-01

    Hybrid wavelet and directional filter banks (HWD) is an effective multi-scale geometrical analysis method. Compared to wavelet transform, it can better capture the directional information of images. But the ringing artifact, which is caused by the coefficient quantization in transform domain, is the biggest drawback of image compression algorithms in HWD domain. In this paper, by researching on the relationship between directional decomposition and ringing artifact, an improved decomposition ...

  6. Localization of Wheeled Mobile Robot Based on Extended Kalman Filtering

    Directory of Open Access Journals (Sweden)

    Li Guangxu

    2015-01-01

    Full Text Available A mobile robot localization method which combines relative positioning with absolute orientation is presented. The code salver and gyroscope are used for relative positioning, and the laser radar is used to detect absolute orientation. In this paper, we established environmental map, multi-sensor information fusion model, sensors and robot motion model. The Extended Kalman Filtering (EKF is adopted as multi-sensor data fusion technology to realize the precise localization of wheeled mobile robot.

  7. Improved hybrid information filtering based on limited time window

    Science.gov (United States)

    Song, Wen-Jun; Guo, Qiang; Liu, Jian-Guo

    2014-12-01

    Adopting the entire collecting information of users, the hybrid information filtering of heat conduction and mass diffusion (HHM) (Zhou et al., 2010) was successfully proposed to solve the apparent diversity-accuracy dilemma. Since the recent behaviors are more effective to capture the users' potential interests, we present an improved hybrid information filtering of adopting the partial recent information. We expand the time window to generate a series of training sets, each of which is treated as known information to predict the future links proven by the testing set. The experimental results on one benchmark dataset Netflix indicate that by only using approximately 31% recent rating records, the accuracy could be improved by an average of 4.22% and the diversity could be improved by 13.74%. In addition, the performance on the dataset MovieLens could be preserved by considering approximately 60% recent records. Furthermore, we find that the improved algorithm is effective to solve the cold-start problem. This work could improve the information filtering performance and shorten the computational time.

  8. Thermally controlled femtosecond pulse shaping using metasurface based optical filters

    Directory of Open Access Journals (Sweden)

    Rahimi Eesa

    2018-02-01

    Full Text Available Shaping of the temporal distribution of the ultrashort pulses, compensation of pulse deformations due to phase shift in transmission and amplification are of interest in various optical applications. To address these problems, in this study, we have demonstrated an ultra-thin reconfigurable localized surface plasmon (LSP band-stop optical filter driven by insulator-metal phase transition of vanadium dioxide. A Joule heating mechanism is proposed to control the thermal phase transition of the material. The resulting permittivity variation of vanadium dioxide tailors spectral response of the transmitted pulse from the stack. Depending on how the pulse’s spectrum is located with respect to the resonance of the band-stop filter, the thin film stack can dynamically compress/expand the output pulse span up to 20% or shift its phase up to 360°. Multi-stacked filters have shown the ability to dynamically compensate input carrier frequency shifts and pulse span variations besides their higher span expansion rates.

  9. Improvement of QR Code Recognition Based on Pillbox Filter Analysis

    Directory of Open Access Journals (Sweden)

    Jia-Shing Sheu

    2013-04-01

    Full Text Available The objective of this paper is to perform the innovation design for improving the recognition of a captured QR code image with blur through the Pillbox filter analysis. QR code images can be captured by digital video cameras. Many factors contribute to QR code decoding failure, such as the low quality of the image. Focus is an important factor that affects the quality of the image. This study discusses the out-of-focus QR code image and aims to improve the recognition of the contents in the QR code image. Many studies have used the pillbox filter (circular averaging filter method to simulate an out-of-focus image. This method is also used in this investigation to improve the recognition of a captured QR code image. A blurred QR code image is separated into nine levels. In the experiment, four different quantitative approaches are used to reconstruct and decode an out-of-focus QR code image. These nine reconstructed QR code images using methods are then compared. The final experimental results indicate improvements in identification.

  10. Ultranarrow-bandwidth filter based on a thermal EIT medium.

    Science.gov (United States)

    Wang, Gang; Wang, Yu-Sheng; Huang, Emily Kay; Hung, Weilun; Chao, Kai-Lin; Wu, Ping-Yeh; Chen, Yi-Hsin; Yu, Ite A

    2018-05-21

    We present high-contrast electromagnetically-induced-transparency (EIT) spectra in a heated vapor cell of single isotope 87 Rb atoms. The EIT spectrum has both high resonant transmission up to 67% and narrow linewidth of 1.1 MHz. We get rid of the possible amplification resulted from the effects of amplification without population inversion and four-wave mixing. Therefore, this high transmitted light is not artificial. The theoretical prediction of the probe transmission agrees well with the data and the experimental parameters can be derived reasonably from the model. Such narrow and high-contrast spectral profile can be employed as a high precision bandpass filter, which provides a significant advantage in terms of stability and tunability. The central frequency tuning range of the filter is larger than 100 MHz with out-of-band blocking ≥15 dB. This bandpass filter can effectively produce light fields with subnatural linewidth. Nonlinearity associating with the narrow-linewidth and high-contrast EIT profile can be very useful in the applications utilizing the EIT effect.

  11. Passive ranging using a filter-based non-imaging method based on oxygen absorption.

    Science.gov (United States)

    Yu, Hao; Liu, Bingqi; Yan, Zongqun; Zhang, Yu

    2017-10-01

    To solve the problem of poor real-time measurement caused by a hyperspectral imaging system and to simplify the design in passive ranging technology based on oxygen absorption spectrum, a filter-based non-imaging ranging method is proposed. In this method, three bandpass filters are used to obtain the source radiation intensities that are located in the oxygen absorption band near 762 nm and the band's left and right non-absorption shoulders, and a photomultiplier tube is used as the non-imaging sensor of the passive ranging system. Range is estimated by comparing the calculated values of band-average transmission due to oxygen absorption, τ O 2 , against the predicted curve of τ O 2 versus range. The method is tested under short-range conditions. Accuracy of 6.5% is achieved with the designed experimental ranging system at the range of 400 m.

  12. A New Method for State of Charge Estimation of Lithium-Ion Battery Based on Strong Tracking Cubature Kalman Filter

    Directory of Open Access Journals (Sweden)

    Bizhong Xia

    2015-11-01

    Full Text Available The estimation of state of charge (SOC is a crucial evaluation index in a battery management system (BMS. The value of SOC indicates the remaining capacity of a battery, which provides a good guarantee of safety and reliability of battery operation. It is difficult to get an accurate value of the SOC, being one of the inner states. In this paper, a strong tracking cubature Kalman filter (STCKF based on the cubature Kalman filter is presented to perform accurate and reliable SOC estimation. The STCKF algorithm can adjust gain matrix online by introducing fading factor to the state estimation covariance matrix. The typical second-order resistor-capacitor model is used as the battery’s equivalent circuit model to dynamically simulate characteristics of the battery. The exponential-function fitting method accomplishes the task of relevant parameters identification. Then, the developed STCKF algorithm has been introduced in detail and verified under different operation current profiles such as Dynamic Stress Test (DST and New European Driving Cycle (NEDC. Making a comparison with extended Kalman filter (EKF and CKF algorithm, the experimental results show the merits of the STCKF algorithm in SOC estimation accuracy and robustness.

  13. An Agent-Based Approach to Modeling Online Social Influence

    NARCIS (Netherlands)

    Maanen, P.P. van; Vecht, B. van der

    2013-01-01

    The aim of this study is to better understand social influence in online social media. Therefore, we propose a method in which we implement, validate and improve an individual behavior model. The behavior model is based on three fundamental behavioral principles of social influence from the

  14. Automatic Online Lecture Highlighting Based on Multimedia Analysis

    Science.gov (United States)

    Che, Xiaoyin; Yang, Haojin; Meinel, Christoph

    2018-01-01

    Textbook highlighting is widely considered to be beneficial for students. In this paper, we propose a comprehensive solution to highlight the online lecture videos in both sentence- and segment-level, just as is done with paper books. The solution is based on automatic analysis of multimedia lecture materials, such as speeches, transcripts, and…

  15. Enhancing reliable online transaction with intelligent rule-based ...

    African Journals Online (AJOL)

    Enhancing reliable online transaction with intelligent rule-based fraud detection technique. ... These are with a bid to reducing amongst other things the cost of production and also dissuade the poor handling of Nigeria currency. The CBN pronouncement has necessitated the upsurge in transactions completed with credit ...

  16. Sesotho Online : Establishing an internet-based language ...

    African Journals Online (AJOL)

    It is against this background that the status, presentation and representation of African languages are being investigated. This article reports on the contribution of the website Sesotho Online to the establishment of an internet-based language knowledge community for the Sesotho language. In its literature review the article ...

  17. Modeling online social networks based on preferential linking

    International Nuclear Information System (INIS)

    Hu Hai-Bo; Chen Jun; Guo Jin-Li

    2012-01-01

    We study the phenomena of preferential linking in a large-scale evolving online social network and find that the linear preference holds for preferential creation, preferential acceptance, and preferential attachment. Based on the linear preference, we propose an analyzable model, which illustrates the mechanism of network growth and reproduces the process of network evolution. Our simulations demonstrate that the degree distribution of the network produced by the model is in good agreement with that of the real network. This work provides a possible bridge between the micro-mechanisms of network growth and the macrostructures of online social networks

  18. Re-Investigation of Generalized Integrator Based Filters From a First-Order-System Perspective

    DEFF Research Database (Denmark)

    Xin, Zhen; Zhao, Rende; Mattavelli, Paolo

    2016-01-01

    The generalized integrator (GI)-based filters can be categorized into two types: one is related to quadrature signal generator (QSG), and the other is related to sequence filter (SF). The QSG is used for generating the in-quadrature sinusoidal signals and the SF works for extracting the symmetrical...... extended structures and thus restrict their applications. To overcome the drawback, this paper uses the first-order-system concept to re-investigate the GI-based filters, with which their working principles can be intuitively understood and their structure correlations can be easily discovered. Moreover...

  19. Adaptive oriented PDEs filtering methods based on new controlling speed function for discontinuous optical fringe patterns

    Science.gov (United States)

    Zhou, Qiuling; Tang, Chen; Li, Biyuan; Wang, Linlin; Lei, Zhenkun; Tang, Shuwei

    2018-01-01

    The filtering of discontinuous optical fringe patterns is a challenging problem faced in this area. This paper is concerned with oriented partial differential equations (OPDEs)-based image filtering methods for discontinuous optical fringe patterns. We redefine a new controlling speed function to depend on the orientation coherence. The orientation coherence can be used to distinguish the continuous regions and the discontinuous regions, and can be calculated by utilizing fringe orientation. We introduce the new controlling speed function to the previous OPDEs and propose adaptive OPDEs filtering models. According to our proposed adaptive OPDEs filtering models, the filtering in the continuous and discontinuous regions can be selectively carried out. We demonstrate the performance of the proposed adaptive OPDEs via application to the simulated and experimental fringe patterns, and compare our methods with the previous OPDEs.

  20. Slice image pretreatment for cone-beam computed tomography based on adaptive filter

    International Nuclear Information System (INIS)

    Huang Kuidong; Zhang Dinghua; Jin Yanfang

    2009-01-01

    According to the noise properties and the serial slice image characteristics in Cone-Beam Computed Tomography (CBCT) system, a slice image pretreatment for CBCT based on adaptive filter was proposed. The judging criterion for the noise is established firstly. All pixels are classified into two classes: adaptive center weighted modified trimmed mean (ACWMTM) filter is used for the pixels corrupted by Gauss noise and adaptive median (AM) filter is used for the pixels corrupted by impulse noise. In ACWMTM filtering algorithm, the estimated Gauss noise standard deviation in the current slice image with offset window is replaced by the estimated standard deviation in the adjacent slice image to the current with the corresponding window, so the filtering accuracy of the serial images is improved. The pretreatment experiment on CBCT slice images of wax model of hollow turbine blade shows that the method makes a good performance both on eliminating noises and on protecting details. (authors)

  1. UWB Bandpass Filter with Ultra-wide Stopband based on Ring Resonator

    Science.gov (United States)

    Kazemi, Maryam; Lotfi, Saeedeh; Siahkamari, Hesam; Mohammadpanah, Mahmood

    2018-04-01

    An ultra-wideband (UWB) bandpass filter with ultra-wide stopband based on a rectangular ring resonator is presented. The filter is designed for the operational frequency band from 4.10 GHz to 10.80 GHz with an ultra-wide stopband from 11.23 GHz to 40 GHz. The even and odd equivalent circuits are used to achieve a suitable analysis of the proposed filter performance. To verify the design and analysis, the proposed bandpass filter is simulated using full-wave EM simulator Advanced Design System and fabricated on a 20mil thick Rogers_RO4003 substrate with relative permittivity of 3.38 and a loss tangent of 0.0021. The proposed filter behavior is investigated and simulation results are in good agreement with measurement results.

  2. A User-Oriented Splog Filtering Based on a Machine Learning

    Science.gov (United States)

    Yoshinaka, Takayuki; Ishii, Soichi; Fukuhara, Tomohiro; Masuda, Hidetaka; Nakagawa, Hiroshi

    A method for filtering spam blogs (splogs) based on a machine learning technique, and its evaluation results are described. Today, spam blogs (splogs) became one of major issues on the Web. The problem of splogs is that values of blog sites are different by people. We propose a novel user-oriented splog filtering method that can adapt each user's preference for valuable blogs. We use the SVM(Support Vector Machine) for creating a personalized splog filter for each user. We had two experiments: (1) an experiment of individual splog judgement, and (2) an experiment for user oriented splog filtering. From the former experiment, we found existence of 'gray' blogs that are needed to treat by persons. From the latter experiment, we found that we can provide appropriate personalized filters by choosing the best feature set for each user. An overview of proposed method, and evaluation results are described.

  3. Image Jacobian Matrix Estimation Based on Online Support Vector Regression

    Directory of Open Access Journals (Sweden)

    Shangqin Mao

    2012-10-01

    Full Text Available Research into robotics visual servoing is an important area in the field of robotics. It has proven difficult to achieve successful results for machine vision and robotics in unstructured environments without using any a priori camera or kinematic models. In uncalibrated visual servoing, image Jacobian matrix estimation methods can be divided into two groups: the online method and the offline method. The offline method is not appropriate for most natural environments. The online method is robust but rough. Moreover, if the images feature configuration changes, it needs to restart the approximating procedure. A novel approach based on an online support vector regression (OL-SVR algorithm is proposed which overcomes the drawbacks and combines the virtues just mentioned.

  4. Cryptanalysis of a computer cryptography scheme based on a filter bank

    International Nuclear Information System (INIS)

    Arroyo, David; Li Chengqing; Li Shujun; Alvarez, Gonzalo

    2009-01-01

    This paper analyzes the security of a recently-proposed signal encryption scheme based on a filter bank. A very critical weakness of this new signal encryption procedure is exploited in order to successfully recover the associated secret key.

  5. Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide

    DEFF Research Database (Denmark)

    Xiao, Binggang; Li, Sheng-Hua; Xiao, Sanshui

    2016-01-01

    Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide is proposed. Owing to subwavelength confinement, such a filter has advantage in the structure size without sacrificing the performance. The spoof SPP based notch is introduced to suppress the WLAN and satel...... and satellite communication signals. Due to planar structures proposed here, it is easy to integrate in the microwave integrated systems, which can play an important role in the microwave communication circuit and system.......Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide is proposed. Owing to subwavelength confinement, such a filter has advantage in the structure size without sacrificing the performance. The spoof SPP based notch is introduced to suppress the WLAN...

  6. Metamaterial based embedded acoustic filters for structural applications

    Directory of Open Access Journals (Sweden)

    Hongfei Zhu

    2013-09-01

    Full Text Available We investigate the use of acoustic metamaterials to design structural materials with frequency selective characteristics. By exploiting the properties of acoustic metamaterials, we tailor the propagation characteristics of the host structure to effectively filter the constitutive harmonics of an incoming broadband excitation. The design approach exploits the characteristics of acoustic waveguides coupled by cavity modes. By properly designing the cavity we can tune the corresponding resonant mode and, therefore, coupling the waveguide at a prescribed frequency. This structural design can open new directions to develop broadband passive vibrations and noise control systems fully integrated in structural components.

  7. Vision-Based Position Estimation Utilizing an Extended Kalman Filter

    Science.gov (United States)

    2016-12-01

    establishing the calibration mapping. A version of Kalman Filter was developed to minimize the impact of inaccuracies in the angle measurement as well...project error covariance ahead Z = [Ang_In; Alt_In]; % Measurements % Update Jacobian h11 = -XY_est(3,1)/(XY_est(1,1)^2+XY_est(3,1)^2); h13 ...XY_est(1,1)/(XY_est(1,1)^2+XY_est(3,1)^2); H = [h11 0 h13 0; 0 0 1 0]; Z_proj(1) = atan2(XY_proj(3),XY_proj(1)); % theta - predicted Z_proj(2

  8. A valley-filtering switch based on strained graphene.

    Science.gov (United States)

    Zhai, Feng; Ma, Yanling; Zhang, Ying-Tao

    2011-09-28

    We investigate valley-dependent transport through a graphene sheet modulated by both the substrate strain and the fringe field of two parallel ferromagnetic metal (FM) stripes. When the magnetizations of the two FM stripes are switched from the parallel to the antiparallel alignment, the total conductance, valley polarization and valley conductance excess change greatly over a wide range of Fermi energy, which results from the dependence of the valley-related transmission suppression on the polarity configuration of inhomogeneous magnetic fields. Thus the proposed structure exhibits the significant features of a valley-filtering switch and a magnetoresistance device.

  9. A valley-filtering switch based on strained graphene

    International Nuclear Information System (INIS)

    Zhai Feng; Ma Yanling; Zhang Yingtao

    2011-01-01

    We investigate valley-dependent transport through a graphene sheet modulated by both the substrate strain and the fringe field of two parallel ferromagnetic metal (FM) stripes. When the magnetizations of the two FM stripes are switched from the parallel to the antiparallel alignment, the total conductance, valley polarization and valley conductance excess change greatly over a wide range of Fermi energy, which results from the dependence of the valley-related transmission suppression on the polarity configuration of inhomogeneous magnetic fields. Thus the proposed structure exhibits the significant features of a valley-filtering switch and a magnetoresistance device. (paper)

  10. Implementation of High Time Delay Accuracy of Ultrasonic Phased Array Based on Interpolation CIC Filter.

    Science.gov (United States)

    Liu, Peilu; Li, Xinghua; Li, Haopeng; Su, Zhikun; Zhang, Hongxu

    2017-10-12

    In order to improve the accuracy of ultrasonic phased array focusing time delay, analyzing the original interpolation Cascade-Integrator-Comb (CIC) filter, an 8× interpolation CIC filter parallel algorithm was proposed, so that interpolation and multichannel decomposition can simultaneously process. Moreover, we summarized the general formula of arbitrary multiple interpolation CIC filter parallel algorithm and established an ultrasonic phased array focusing time delay system based on 8× interpolation CIC filter parallel algorithm. Improving the algorithmic structure, 12.5% of addition and 29.2% of multiplication was reduced, meanwhile the speed of computation is still very fast. Considering the existing problems of the CIC filter, we compensated the CIC filter; the compensated CIC filter's pass band is flatter, the transition band becomes steep, and the stop band attenuation increases. Finally, we verified the feasibility of this algorithm on Field Programming Gate Array (FPGA). In the case of system clock is 125 MHz, after 8× interpolation filtering and decomposition, time delay accuracy of the defect echo becomes 1 ns. Simulation and experimental results both show that the algorithm we proposed has strong feasibility. Because of the fast calculation, small computational amount and high resolution, this algorithm is especially suitable for applications with high time delay accuracy and fast detection.

  11. Investigation of New Microstrip Bandpass Filter Based on Patch Resonator with Geometrical Fractal Slot.

    Directory of Open Access Journals (Sweden)

    Yaqeen S Mezaal

    Full Text Available A compact dual-mode microstrip bandpass filter using geometrical slot is presented in this paper. The adopted geometrical slot is based on first iteration of Cantor square fractal curve. This filter has the benefits of possessing narrower and sharper frequency responses as compared to microstrip filters that use single mode resonators and traditional dual-mode square patch resonators. The filter has been modeled and demonstrated by Microwave Office EM simulator designed at a resonant frequency of 2 GHz using a substrate of εr = 10.8 and thickness of h = 1.27 mm. The output simulated results of the proposed filter exhibit 22 dB return loss, 0.1678 dB insertion loss and 12 MHz bandwidth in the passband region. In addition to the narrow band gained, miniaturization properties as well as weakened spurious frequency responses and blocked second harmonic frequency in out of band regions have been acquired. Filter parameters including insertion loss, return loss, bandwidth, coupling coefficient and external quality factor have been compared with different values of perturbation dimension (d. Also, a full comparative study of this filter as compared with traditional square patch filter has been considered.

  12. Tunable bandpass filter based on photonic crystal fiber filled with multiple liquid crystals

    DEFF Research Database (Denmark)

    Scolari, Lara; Tartarini, G.; Borelli, E.

    2007-01-01

    A tunable bandpass filter based on a photonic crystal fiber filled with two different liquid crystals is demonstrated. 130 nm bandwidth tunability is achieved by tuning the temperature from 30degC to 90degC.......A tunable bandpass filter based on a photonic crystal fiber filled with two different liquid crystals is demonstrated. 130 nm bandwidth tunability is achieved by tuning the temperature from 30degC to 90degC....

  13. A Polarization Maintaining Filter based on a Liquid-Crystal-Photonic-Bandgap-Fiber

    DEFF Research Database (Denmark)

    Scolari, Lara; Olausson, Christina Bjarnal Thulin; Turchinovich, Dmitry

    2008-01-01

    A polarization maintaining filter based on a liquid-crystal-photonic-bandgap-fiber is demonstrated. Its polarization extinction ratio is 14 dB at 1550 nm. Its tunability is 150 nm.......A polarization maintaining filter based on a liquid-crystal-photonic-bandgap-fiber is demonstrated. Its polarization extinction ratio is 14 dB at 1550 nm. Its tunability is 150 nm....

  14. Semi-analytical model of filtering effects in microwave phase shifters based on semiconductor optical amplifiers

    DEFF Research Database (Denmark)

    Chen, Yaohui; Xue, Weiqi; Öhman, Filip

    2008-01-01

    We present a model to interpret enhanced microwave phase shifts based on filter assisted slow and fast light effects in semiconductor optical amplifiers. The model also demonstrates the spectral phase impact of input optical signals.......We present a model to interpret enhanced microwave phase shifts based on filter assisted slow and fast light effects in semiconductor optical amplifiers. The model also demonstrates the spectral phase impact of input optical signals....

  15. Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

    Science.gov (United States)

    Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

    2014-05-01

    In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

  16. Online constrained model-based reinforcement learning

    CSIR Research Space (South Africa)

    Van Niekerk, B

    2017-08-01

    Full Text Available Constrained Model-based Reinforcement Learning Benjamin van Niekerk School of Computer Science University of the Witwatersrand South Africa Andreas Damianou∗ Amazon.com Cambridge, UK Benjamin Rosman Council for Scientific and Industrial Research, and School... MULTIPLE SHOOTING Using direct multiple shooting (Bock and Plitt, 1984), problem (1) can be transformed into a structured non- linear program (NLP). First, the time horizon [t0, t0 + T ] is partitioned into N equal subintervals [tk, tk+1] for k = 0...

  17. Binaural noise reduction via cue-preserving MMSE filter and adaptive-blocking-based noise PSD estimation

    Science.gov (United States)

    Azarpour, Masoumeh; Enzner, Gerald

    2017-12-01

    Binaural noise reduction, with applications for instance in hearing aids, has been a very significant challenge. This task relates to the optimal utilization of the available microphone signals for the estimation of the ambient noise characteristics and for the optimal filtering algorithm to separate the desired speech from the noise. The additional requirements of low computational complexity and low latency further complicate the design. A particular challenge results from the desired reconstruction of binaural speech input with spatial cue preservation. The latter essentially diminishes the utility of multiple-input/single-output filter-and-sum techniques such as beamforming. In this paper, we propose a comprehensive and effective signal processing configuration with which most of the aforementioned criteria can be met suitably. This relates especially to the requirement of efficient online adaptive processing for noise estimation and optimal filtering while preserving the binaural cues. Regarding noise estimation, we consider three different architectures: interaural (ITF), cross-relation (CR), and principal-component (PCA) target blocking. An objective comparison with two other noise PSD estimation algorithms demonstrates the superiority of the blocking-based noise estimators, especially the CR-based and ITF-based blocking architectures. Moreover, we present a new noise reduction filter based on minimum mean-square error (MMSE), which belongs to the class of common gain filters, hence being rigorous in terms of spatial cue preservation but also efficient and competitive for the acoustic noise reduction task. A formal real-time subjective listening test procedure is also developed in this paper. The proposed listening test enables a real-time assessment of the proposed computationally efficient noise reduction algorithms in a realistic acoustic environment, e.g., considering time-varying room impulse responses and the Lombard effect. The listening test outcome

  18. Statistical-uncertainty-based adaptive filtering of lidar signals

    International Nuclear Information System (INIS)

    Fuehrer, P. L.; Friehe, C. A.; Hristov, T. S.; Cooper, D. I.; Eichinger, W. E.

    2000-01-01

    An adaptive filter signal processing technique is developed to overcome the problem of Raman lidar water-vapor mixing ratio (the ratio of the water-vapor density to the dry-air density) with a highly variable statistical uncertainty that increases with decreasing photomultiplier-tube signal strength and masks the true desired water-vapor structure. The technique, applied to horizontal scans, assumes only statistical horizontal homogeneity. The result is a variable spatial resolution water-vapor signal with a constant variance out to a range limit set by a specified signal-to-noise ratio. The technique was applied to Raman water-vapor lidar data obtained at a coastal pier site together with in situ instruments located 320 m from the lidar. The micrometerological humidity data were used to calibrate the ratio of the lidar gains of the H 2 O and the N 2 photomultiplier tubes and set the water-vapor mixing ratio variance for the adaptive filter. For the coastal experiment the effective limit of the lidar range was found to be approximately 200 m for a maximum noise-to-signal variance ratio of 0.1 with the implemented data-reduction procedure. The technique can be adapted to off-horizontal scans with a small reduction in the constraints and is also applicable to other remote-sensing devices that exhibit the same inherent range-dependent signal-to-noise ratio problem. (c) 2000 Optical Society of America

  19. New Collaborative Filtering Algorithms Based on SVD++ and Differential Privacy

    Directory of Open Access Journals (Sweden)

    Zhengzheng Xian

    2017-01-01

    Full Text Available Collaborative filtering technology has been widely used in the recommender system, and its implementation is supported by the large amount of real and reliable user data from the big-data era. However, with the increase of the users’ information-security awareness, these data are reduced or the quality of the data becomes worse. Singular Value Decomposition (SVD is one of the common matrix factorization methods used in collaborative filtering, which introduces the bias information of users and items and is realized by using algebraic feature extraction. The derivative model SVD++ of SVD achieves better predictive accuracy due to the addition of implicit feedback information. Differential privacy is defined very strictly and can be proved, which has become an effective measure to solve the problem of attackers indirectly deducing the personal privacy information by using background knowledge. In this paper, differential privacy is applied to the SVD++ model through three approaches: gradient perturbation, objective-function perturbation, and output perturbation. Through theoretical derivation and experimental verification, the new algorithms proposed can better protect the privacy of the original data on the basis of ensuring the predictive accuracy. In addition, an effective scheme is given that can measure the privacy protection strength and predictive accuracy, and a reasonable range for selection of the differential privacy parameter is provided.

  20. Tyre-road grip coefficient assessment - Part II: online estimation using instrumented vehicle, extended Kalman filter, and neural network

    Science.gov (United States)

    Luque, Pablo; Mántaras, Daniel A.; Fidalgo, Eloy; Álvarez, Javier; Riva, Paolo; Girón, Pablo; Compadre, Diego; Ferran, Jordi

    2013-12-01

    The main objective of this work is to determine the limit of safe driving conditions by identifying the maximal friction coefficient in a real vehicle. The study will focus on finding a method to determine this limit before reaching the skid, which is valuable information in the context of traffic safety. Since it is not possible to measure the friction coefficient directly, it will be estimated using the appropriate tools in order to get the most accurate information. A real vehicle is instrumented to collect information of general kinematics and steering tie-rod forces. A real-time algorithm is developed to estimate forces and aligning torque in the tyres using an extended Kalman filter and neural networks techniques. The methodology is based on determining the aligning torque; this variable allows evaluation of the behaviour of the tyre. It transmits interesting information from the tyre-road contact and can be used to predict the maximal tyre grip and safety margin. The maximal grip coefficient is estimated according to a knowledge base, extracted from computer simulation of a high detailed three-dimensional model, using Adams® software. The proposed methodology is validated and applied to real driving conditions, in which maximal grip and safety margin are properly estimated.

  1. Online transition matrix identification of the state evolution model for the extended Kalman filter in electrical impedance tomography

    International Nuclear Information System (INIS)

    Moura, Fernando S; Aya, Julio C C; Lima, Raul G; Fleury, Agenor T

    2008-01-01

    One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on contour electrical potential measurements caused by an imposed electrical current distribution into the boundary. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, it is observed poor tracking ability of the Extended Kalman Filter (EKF). An analytically developed evolution model is not feasible at this moment. The present work investigates the possibility of identifying the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model is identified using the history of resistivity distribution obtained by a sensitivity matrix based algorithm. To numerically identify the linear evolution model, it is used the Ibrahim Time Domain Method, normally used to identify the transition matrix on structural dynamics. The investigation was performed by numerical simulations of a time varying domain with the addition of noise. Numerical dificulties to compute the transition matrix were solved using a Tikhonov regularization. The EKF numerical simulations suggest that the tracking ability is significantly improved.

  2. Moving Average Filter-Based Phase-Locked Loops: Performance Analysis and Design Guidelines

    DEFF Research Database (Denmark)

    Golestan, Saeed; Ramezani, Malek; Guerrero, Josep M.

    2014-01-01

    this challenge, incorporating moving average filter(s) (MAF) into the PLL structure has been proposed in some recent literature. A MAF is a linear-phase finite impulse response filter which can act as an ideal low-pass filter, if certain conditions hold. The main aim of this paper is to present the control...... design guidelines for a typical MAF-based PLL. The paper starts with the general description of MAFs. The main challenge associated with using the MAFs is then explained, and its possible solutions are discussed. The paper then proceeds with a brief overview of the different MAF-based PLLs. In each case......, the PLL block diagram description is shown, the advantages and limitations are briefly discussed, and the tuning approach (if available) is evaluated. The paper then presents two systematic methods to design the control parameters of a typical MAF-based PLL: one for the case of using a proportional...

  3. Stability Analysis and Active Damping for LLCL-filter-Based Grid-Connected Inverters

    DEFF Research Database (Denmark)

    Huang, Min; Wang, Xiongfei; Loh, Poh Chiang

    2015-01-01

    to use either passive or active damping methods. This paper analyzes the stability of the LLCL-filter based grid-connected inverter and identifies a critical resonant frequency for the LLCL-filter when sampling and transport delays are considered. In a high resonant frequency region the active damping...... is not required but in a low resonant frequency region the active damping is necessary. The basic LLCL resonance damping properties of different feedback states based on a notch filter concept are also studied. Then an active damping method which is using the capacitor current feedback for LLCL......-filter is introduced. Based on this active damping method, a design procedure for the controller is given. Last, both simulation and experimental results are provided to validate the theoretical analysis of this paper....

  4. EVD Dualdating Based Online Subspace Learning

    Directory of Open Access Journals (Sweden)

    Bo Jin

    2014-01-01

    Full Text Available Conventional incremental PCA methods usually only discuss the situation of adding samples. In this paper, we consider two different cases: deleting samples and simultaneously adding and deleting samples. To avoid the NP-hard problem of downdating SVD without right singular vectors and specific position information, we choose to use EVD instead of SVD, which is used by most IPCA methods. First, we propose an EVD updating and downdating algorithm, called EVD dualdating, which permits simultaneous arbitrary adding and deleting operation, via transforming the EVD of the covariance matrix into a SVD updating problem plus an EVD of a small autocorrelation matrix. A comprehensive analysis is delivered to express the essence, expansibility, and computation complexity of EVD dualdating. A mathematical theorem proves that if the whole data matrix satisfies the low-rank-plus-shift structure, EVD dualdating is an optimal rank-k estimator under the sequential environment. A selection method based on eigenvalues is presented to determine the optimal rank k of the subspace. Then, we propose three incremental/decremental PCA methods: EVDD-IPCA, EVDD-DPCA, and EVDD-IDPCA, which are adaptive to the varying mean. Finally, plenty of comparative experiments demonstrate that EVDD-based methods outperform conventional incremental/decremental PCA methods in both efficiency and accuracy.

  5. Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain-computer interface

    Science.gov (United States)

    Chen, Xiaogang; Wang, Yijun; Gao, Shangkai; Jung, Tzyy-Ping; Gao, Xiaorong

    2015-08-01

    Objective. Recently, canonical correlation analysis (CCA) has been widely used in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) due to its high efficiency, robustness, and simple implementation. However, a method with which to make use of harmonic SSVEP components to enhance the CCA-based frequency detection has not been well established. Approach. This study proposed a filter bank canonical correlation analysis (FBCCA) method to incorporate fundamental and harmonic frequency components to improve the detection of SSVEPs. A 40-target BCI speller based on frequency coding (frequency range: 8-15.8 Hz, frequency interval: 0.2 Hz) was used for performance evaluation. To optimize the filter bank design, three methods (M1: sub-bands with equally spaced bandwidths; M2: sub-bands corresponding to individual harmonic frequency bands; M3: sub-bands covering multiple harmonic frequency bands) were proposed for comparison. Classification accuracy and information transfer rate (ITR) of the three FBCCA methods and the standard CCA method were estimated using an offline dataset from 12 subjects. Furthermore, an online BCI speller adopting the optimal FBCCA method was tested with a group of 10 subjects. Main results. The FBCCA methods significantly outperformed the standard CCA method. The method M3 achieved the highest classification performance. At a spelling rate of ˜33.3 characters/min, the online BCI speller obtained an average ITR of 151.18 ± 20.34 bits min-1. Significance. By incorporating the fundamental and harmonic SSVEP components in target identification, the proposed FBCCA method significantly improves the performance of the SSVEP-based BCI, and thereby facilitates its practical applications such as high-speed spelling.

  6. Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

    Science.gov (United States)

    Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank

    2012-01-01

    This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

  7. Time Series Based for Online Signature Verification

    Directory of Open Access Journals (Sweden)

    I Ketut Gede Darma Putra

    2013-11-01

    Full Text Available Signature verification system is to match the tested signature with a claimed signature. This paper proposes time series based for feature extraction method and dynamic time warping for match method. The system made by process of testing 900 signatures belong to 50 participants, 3 signatures for reference and 5 signatures from original user, simple imposters and trained imposters for signatures test. The final result system was tested with 50 participants with 3 references. This test obtained that system accuracy without imposters is 90,44897959% at threshold 44 with rejection errors (FNMR is 5,2% and acceptance errors (FMR is 4,35102%, when with imposters system accuracy is 80,1361% at threshold 27 with error rejection (FNMR is 15,6% and acceptance errors (average FMR is 4,263946%, with details as follows: acceptance errors is 0,391837%, acceptance errors simple imposters is 3,2% and acceptance errors trained imposters is 9,2%.

  8. On-board adaptive model for state of charge estimation of lithium-ion batteries based on Kalman filter with proportional integral-based error adjustment

    Science.gov (United States)

    Wei, Jingwen; Dong, Guangzhong; Chen, Zonghai

    2017-10-01

    With the rapid development of battery-powered electric vehicles, the lithium-ion battery plays a critical role in the reliability of vehicle system. In order to provide timely management and protection for battery systems, it is necessary to develop a reliable battery model and accurate battery parameters estimation to describe battery dynamic behaviors. Therefore, this paper focuses on an on-board adaptive model for state-of-charge (SOC) estimation of lithium-ion batteries. Firstly, a first-order equivalent circuit battery model is employed to describe battery dynamic characteristics. Then, the recursive least square algorithm and the off-line identification method are used to provide good initial values of model parameters to ensure filter stability and reduce the convergence time. Thirdly, an extended-Kalman-filter (EKF) is applied to on-line estimate battery SOC and model parameters. Considering that the EKF is essentially a first-order Taylor approximation of battery model, which contains inevitable model errors, thus, a proportional integral-based error adjustment technique is employed to improve the performance of EKF method and correct model parameters. Finally, the experimental results on lithium-ion batteries indicate that the proposed EKF with proportional integral-based error adjustment method can provide robust and accurate battery model and on-line parameter estimation.

  9. Improving indoor air quality by using the new generation of corrugated cardboard-based filters.

    Science.gov (United States)

    Candiani, Gabriele; Del Curto, Barbara; Cigada, Alberto

    2012-09-27

    Indoor Air Quality (IAQ) is strictly affected by the concentration of total suspended particulate matter (TSP). Air filtration is by far the most feasible suggestion to improve IAQ. Unfortunately, highly effective HEPA filters also have a few major weaknesses that have hindered their widespread use. There is therefore a renewed interest in developing novel, cost-effective filtration systems. We have recently reported the development of cardboard-based filters for bacterial removal that were further implemented and tested herein. A parallelepiped filter manufactured by aligning strips of corrugated cardboard and surrounded by a cardboard frame was specifically designed with an internal pocket holding a partially cut antistatic pleated fabric (HP). This filter, together with its parent version (CTRL) and a commercially sourced specimen (CAF), were assessed comparatively in a long-time test to assess their effectiveness on TSP removal. We found that the TSP abatement efficiency (E%) of the HP filter was relatively high and invariable over the 93 days of test and the pressure drop (PD%) decrease because of filter clogging was moderate. Most important, the HP filter was the most effective if assessed in terms of overall yield (Y%) and its performance was quite constant over the entire period considered. This work disclosed this novel class of corrugated cardboard-based filters as promising tools to ameliorate IAQ in light of their good TSP removal properties that endure over time. Moreover, cardboard is a lightweight, inexpensive, and eco-friendly material and corrugated cardboard-based air filters are very easy to shape and mount on and/or replace in existing ventilation systems.

  10. A hybrid filtering method based on a novel empirical mode decomposition for friction signals

    International Nuclear Information System (INIS)

    Li, Chengwei; Zhan, Liwei

    2015-01-01

    During a measurement, the measured signal usually contains noise. To remove the noise and preserve the important feature of the signal, we introduce a hybrid filtering method that uses a new intrinsic mode function (NIMF) and a modified Hausdorff distance. The NIMF is defined as the difference between the noisy signal and each intrinsic mode function (IMF), which is obtained by empirical mode decomposition (EMD), ensemble EMD, complementary ensemble EMD, or complete ensemble EMD with adaptive noise (CEEMDAN). The relevant mode selecting is based on the similarity between the first NIMF and the rest of the NIMFs. With this filtering method, the EMD and improved versions are used to filter the simulation and friction signals. The friction signal between an airplane tire and the runaway is recorded during a simulated airplane touchdown and features spikes of various amplitudes and noise. The filtering effectiveness of the four hybrid filtering methods are compared and discussed. The results show that the filtering method based on CEEMDAN outperforms other signal filtering methods. (paper)

  11. L70 life prediction for solid state lighting using Kalman Filter and Extended Kalman Filter based models

    Energy Technology Data Exchange (ETDEWEB)

    Lall, Pradeep; Wei, Junchao; Davis, Lynn

    2013-08-08

    Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying damage using physics-based models. Life

  12. Tracking the business cycle of the Euro area: A multivariate model-based band-pass filter

    NARCIS (Netherlands)

    Azevedo, J.M.; Koopman, S.J.; Rua, A.

    2006-01-01

    This article proposes a multivariate bandpass filter based on the trend plus cycle decomposition model. The underlying multivariate dynamic factor model relies on specific formulations for trend and cycle components and produces smooth business cycle indicators with bandpass filter properties.

  13. A multi-timescale estimator for battery state of charge and capacity dual estimation based on an online identified model

    International Nuclear Information System (INIS)

    Wei, Zhongbao; Zhao, Jiyun; Ji, Dongxu; Tseng, King Jet

    2017-01-01

    Highlights: •SOC and capacity are dually estimated with online adapted battery model. •Model identification and state dual estimate are fully decoupled. •Multiple timescales are used to improve estimation accuracy and stability. •The proposed method is verified with lab-scale experiments. •The proposed method is applicable to different battery chemistries. -- Abstract: Reliable online estimation of state of charge (SOC) and capacity is critically important for the battery management system (BMS). This paper presents a multi-timescale method for dual estimation of SOC and capacity with an online identified battery model. The model parameter estimator and the dual estimator are fully decoupled and executed with different timescales to improve the model accuracy and stability. Specifically, the model parameters are online adapted with the vector-type recursive least squares (VRLS) to address the different variation rates of them. Based on the online adapted battery model, the Kalman filter (KF)-based SOC estimator and RLS-based capacity estimator are formulated and integrated in the form of dual estimation. Experimental results suggest that the proposed method estimates the model parameters, SOC, and capacity in real time with fast convergence and high accuracy. Experiments on both lithium-ion battery and vanadium redox flow battery (VRB) verify the generality of the proposed method on multiple battery chemistries. The proposed method is also compared with other existing methods on the computational cost to reveal its superiority for practical application.

  14. Tunable orbital angular momentum mode filter based on optical geometric transformation.

    Science.gov (United States)

    Huang, Hao; Ren, Yongxiong; Xie, Guodong; Yan, Yan; Yue, Yang; Ahmed, Nisar; Lavery, Martin P J; Padgett, Miles J; Dolinar, Sam; Tur, Moshe; Willner, Alan E

    2014-03-15

    We present a tunable mode filter for spatially multiplexed laser beams carrying orbital angular momentum (OAM). The filter comprises an optical geometric transformation-based OAM mode sorter and a spatial light modulator (SLM). The programmable SLM can selectively control the passing/blocking of each input OAM beam. We experimentally demonstrate tunable filtering of one or multiple OAM modes from four multiplexed input OAM modes with vortex charge of ℓ=-9, -4, +4, and +9. The measured output power suppression ratio of the propagated modes to the blocked modes exceeds 14.5 dB.

  15. Commutative discrete filtering on unstructured grids based on least-squares techniques

    International Nuclear Information System (INIS)

    Haselbacher, Andreas; Vasilyev, Oleg V.

    2003-01-01

    The present work is concerned with the development of commutative discrete filters for unstructured grids and contains two main contributions. First, building on the work of Marsden et al. [J. Comp. Phys. 175 (2002) 584], a new commutative discrete filter based on least-squares techniques is constructed. Second, a new analysis of the discrete commutation error is carried out. The analysis indicates that the discrete commutation error is not only dependent on the number of vanishing moments of the filter weights, but also on the order of accuracy of the discrete gradient operator. The results of the analysis are confirmed by grid-refinement studies

  16. Passivity-Based Stability Analysis and Damping Injection for Multiparalleled VSCs with LCL Filters

    DEFF Research Database (Denmark)

    Wang, Xiongfei; Blaabjerg, Frede; Loh, Poh Chiang

    2017-01-01

    is decomposed into a passive filter output admittance in series with an active admittance which is dependent on the current controller and the time delay. The frequency-domain passivity theory is then applied to the active admittance for system stability analysis. It reveals that the stability region...... of the single-loop grid current control is not only dependent on the time delay, but affected also by the resonance frequency of the converter-side filter inductor and filter capacitor. Further on, the damping injection based on the discrete derivative controller is proposed to enhance the passivity...

  17. Performance Evaluation of Glottal Inverse Filtering Algorithms Using a Physiologically Based Articulatory Speech Synthesizer

    Science.gov (United States)

    2017-01-05

    vol. 74, pp. 279–295, 1999. [11] M. Fröhlich, D. Michaelis, and H. W. Strube, “SIM— simultaneous inverse filtering and matching of a glottal flow...1 Performance Evaluation of Glottal Inverse Filtering Algorithms Using a Physiologically Based Articulatory Speech Synthesizer Yu-Ren Chien, Daryush...D. Mehta, Member, IEEE, Jón Guðnason, Matías Zañartu, Member, IEEE, and Thomas F. Quatieri, Fellow, IEEE Abstract—Glottal inverse filtering aims to

  18. LLCL-Filter Based Single-Phase Grid-Tied Aalborg Inverter

    DEFF Research Database (Denmark)

    Wu, Weimin; Feng, Shuangshuang; Ji, Junhao

    2014-01-01

    The Aalborg Inverter is a new type of high efficient DC/AC grid-tied inverter, where the input DC voltage can vary in a wide range. Compared with the LCL-filter, the LLCL-filter can save the total inductance for the conventional voltage source inverter. In this paper, an LLCL-filter based Aalborg...... Inverter is proposed and its character is illustrated through the small signal analysis in both “Buck” and “Buck-Boost” mode. From the modeling, it can be seen that the resonant inductor in the capacitor loop has not brought extra control difficulties, whereas more inductance in the power loop can be saved...

  19. Adaptive Kalman filtering for histogram-based appearance learning in infrared imagery.

    Science.gov (United States)

    Venkataraman, Vijay; Fan, Guoliang; Havlicek, Joseph P; Fan, Xin; Zhai, Yan; Yeary, Mark B

    2012-11-01

    Targets of interest in video acquired from imaging infrared sensors often exhibit profound appearance variations due to a variety of factors, including complex target maneuvers, ego-motion of the sensor platform, background clutter, etc., making it difficult to maintain a reliable detection process and track lock over extended time periods. Two key issues in overcoming this problem are how to represent the target and how to learn its appearance online. In this paper, we adopt a recent appearance model that estimates the pixel intensity histograms as well as the distribution of local standard deviations in both the foreground and background regions for robust target representation. Appearance learning is then cast as an adaptive Kalman filtering problem where the process and measurement noise variances are both unknown. We formulate this problem using both covariance matching and, for the first time in a visual tracking application, the recent autocovariance least-squares (ALS) method. Although convergence of the ALS algorithm is guaranteed only for the case of globally wide sense stationary process and measurement noises, we demonstrate for the first time that the technique can often be applied with great effectiveness under the much weaker assumption of piecewise stationarity. The performance advantages of the ALS method relative to the classical covariance matching are illustrated by means of simulated stationary and nonstationary systems. Against real data, our results show that the ALS-based algorithm outperforms the covariance matching as well as the traditional histogram similarity-based methods, achieving sub-pixel tracking accuracy against the well-known AMCOM closure sequences and the recent SENSIAC automatic target recognition dataset.

  20. Online Voting System Based on Image Steganography and Visual Cryptography

    Directory of Open Access Journals (Sweden)

    Biju Issac

    2017-01-01

    Full Text Available This paper discusses the implementation of an online voting system based on image steganography and visual cryptography. The system was implemented in Java EE on a web-based interface, with MySQL database server and Glassfish application server as the backend. After considering the requirements of an online voting system, current technologies on electronic voting schemes in published literature were examined. Next, the cryptographic and steganography techniques best suited for the requirements of the voting system were chosen, and the software was implemented. We have incorporated in our system techniques like the password hashed based scheme, visual cryptography, F5 image steganography and threshold decryption cryptosystem. The analysis, design and implementation phase of the software development of the voting system is discussed in detail. We have also used a questionnaire survey and did the user acceptance testing of the system.

  1. Learning Vocabulary through Paper and Online-Based Glossary

    Directory of Open Access Journals (Sweden)

    Ratih Novita Sari

    2017-08-01

    Full Text Available This study examined the effect of teaching glossary and personality traits on vocabulary learning. Two groups of students who had different personality (extroverted and introverted were exposed to two types of glosses: paper and online-based glossary. The two groups underwent two-month treatment. Prior to and after the treatment, each group was given pre and posttest. In calculating the data, two-way ANOVA was used. The results of the study showed that extroverted students learned vocabulary better through paper-based glossary, while introverted students learned vocabulary better through online-based. Further research needs to be conducted to determine whether age influences the use of teaching glossary or not

  2. Prediction of Lumen Output and Chromaticity Shift in LEDs Using Kalman Filter and Extended Kalman Filter Based Models

    Energy Technology Data Exchange (ETDEWEB)

    Lall, Pradeep; Wei, Junchao; Davis, J Lynn

    2014-06-24

    Abstract— Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have

  3. Research on the method of information system risk state estimation based on clustering particle filter

    Science.gov (United States)

    Cui, Jia; Hong, Bei; Jiang, Xuepeng; Chen, Qinghua

    2017-05-01

    With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

  4. Research on the method of information system risk state estimation based on clustering particle filter

    Directory of Open Access Journals (Sweden)

    Cui Jia

    2017-05-01

    Full Text Available With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

  5. Mixed-integrator-based bi-quad cell for designing a continuous time filter

    International Nuclear Information System (INIS)

    Chen Yong; Zhou Yumei

    2010-01-01

    A new mixed-integrator-based bi-quad cell is proposed. An alternative synthesis mechanism of complex poles is proposed compared with source-follower-based bi-quad cells which is designed applying the positive feedback technique. Using the negative feedback technique to combine different integrators, the proposed bi-quad cell synthesizes complex poles for designing a continuous time filter. It exhibits various advantages including compact topology, high gain, no parasitic pole, no CMFB circuit, and high capability. The fourth-order Butterworth lowpass filter using the proposed cells has been fabricated in 0.18 μm CMOS technology. The active area occupied by the filter with test buffer is only 200 x 170 μm 2 . The proposed filter consumes a low power of 201 μW and achieves a 68.5 dB dynamic range. (semiconductor integrated circuits)

  6. Signal reconstruction in wireless sensor networks based on a cubature Kalman particle filter

    International Nuclear Information System (INIS)

    Huang Jin-Wang; Feng Jiu-Chao

    2014-01-01

    For solving the issues of the signal reconstruction of nonlinear non-Gaussian signals in wireless sensor networks (WSNs), a new signal reconstruction algorithm based on a cubature Kalman particle filter (CKPF) is proposed in this paper. We model the reconstruction signal first and then use the CKPF to estimate the signal. The CKPF uses a cubature Kalman filter (CKF) to generate the importance proposal distribution of the particle filter and integrates the latest observation, which can approximate the true posterior distribution better. It can improve the estimation accuracy. CKPF uses fewer cubature points than the unscented Kalman particle filter (UKPF) and has less computational overheads. Meanwhile, CKPF uses the square root of the error covariance for iterating and is more stable and accurate than the UKPF counterpart. Simulation results show that the algorithm can reconstruct the observed signals quickly and effectively, at the same time consuming less computational time and with more accuracy than the method based on UKPF. (general)

  7. Noise Reduction in Breath Sound Files Using Wavelet Transform Based Filter

    Science.gov (United States)

    Syahputra, M. F.; Situmeang, S. I. G.; Rahmat, R. F.; Budiarto, R.

    2017-04-01

    The development of science and technology in the field of healthcare increasingly provides convenience in diagnosing respiratory system problem. Recording the breath sounds is one example of these developments. Breath sounds are recorded using a digital stethoscope, and then stored in a file with sound format. This breath sounds will be analyzed by health practitioners to diagnose the symptoms of disease or illness. However, the breath sounds is not free from interference signals. Therefore, noise filter or signal interference reduction system is required so that breath sounds component which contains information signal can be clarified. In this study, we designed a filter called a wavelet transform based filter. The filter that is designed in this study is using Daubechies wavelet with four wavelet transform coefficients. Based on the testing of the ten types of breath sounds data, the data is obtained in the largest SNRdB bronchial for 74.3685 decibels.

  8. A Divergence Median-based Geometric Detector with A Weighted Averaging Filter

    Science.gov (United States)

    Hua, Xiaoqiang; Cheng, Yongqiang; Li, Yubo; Wang, Hongqiang; Qin, Yuliang

    2018-01-01

    To overcome the performance degradation of the classical fast Fourier transform (FFT)-based constant false alarm rate detector with the limited sample data, a divergence median-based geometric detector on the Riemannian manifold of Heimitian positive definite matrices is proposed in this paper. In particular, an autocorrelation matrix is used to model the correlation of sample data. This method of the modeling can avoid the poor Doppler resolution as well as the energy spread of the Doppler filter banks result from the FFT. Moreover, a weighted averaging filter, conceived from the philosophy of the bilateral filtering in image denoising, is proposed and combined within the geometric detection framework. As the weighted averaging filter acts as the clutter suppression, the performance of the geometric detector is improved. Numerical experiments are given to validate the effectiveness of our proposed method.

  9. Passive Target Tracking in Non-cooperative Radar System Based on Particle Filtering

    Institute of Scientific and Technical Information of China (English)

    LI Shuo; TAO Ran

    2006-01-01

    We propose a target tracking method based on particle filtering(PF) to solve the nonlinear non-Gaussian target-tracking problem in the bistatic radar systems using external radiation sources. Traditional nonlinear state estimation method is extended Kalman filtering (EKF), which is to do the first level Taylor series extension. It will cause an inaccuracy or even a scatter estimation result on condition that there is either a highly nonlinear target or a large noise square-error. Besides, Kalman filtering is the optimal resolution under a Gaussian noise assumption, and is not suitable to the non-Gaussian condition. PF is a sort of statistic filtering based on Monte Carlo simulation that is using some random samples (particles) to simulate the posterior probability density of system random variables. This method can be used in any nonlinear random system. It can be concluded through simulation that PF can achieve higher accuracy than the traditional EKF.

  10. Pressure-controlled terahertz filter based on 1D photonic crystal with a defective semiconductor

    Science.gov (United States)

    Qinwen, XUE; Xiaohua, WANG; Chenglin, LIU; Youwen, LIU

    2018-03-01

    The tunable terahertz (THz) filter has been designed and studied, which is composed of 1D photonic crystal (PC) containing a defect layer of semiconductor GaAs. The analytical solution of 1D defective PC (1DDPC) is deduced based on the transfer matrix method, and the electromagnetic plane wave numerical simulation of this 1DDPC is performed by using the finite element method. The calculated and simulated results have confirmed that the filtering transmittance of this 1DDPC in symmetric structure of air/(Si/SiO2) N /GaAs/(SiO2/Si) N /air is far higher than in asymmetric structure of air/(Si/SiO2) N /GaAs/(Si/SiO2) N /air, where the filtering frequency can be tuned by the external pressure. It can provide a feasible route to design the external pressure-controlled THz filter based on 1DPC with a defective semiconductor.

  11. A mobile and web application-based recommendation system using color quantization and collaborative filtering

    OpenAIRE

    KAYA, FİDAN; YILDIZ, GÜREL; KAVAK, ADNAN

    2015-01-01

    In this paper, a recommendation system based on a mobile and web application is proposed for indoor decoration. The main contribution of this work is to apply two-stage filtering using linear matching and collaborative filtering to make recommendations. In the mobile application part, the image of the medium captured by a mobile phone is analyzed using color quantization methods, and these color analysis results along with other user-defined parameters such as height, width, and type of the p...

  12. Multisensor Distributed Track Fusion AlgorithmBased on Strong Tracking Filter and Feedback Integration1)

    Institute of Scientific and Technical Information of China (English)

    YANGGuo-Sheng; WENCheng-Lin; TANMin

    2004-01-01

    A new multisensor distributed track fusion algorithm is put forward based on combiningthe feedback integration with the strong tracking Kalman filter. Firstly, an effective tracking gateis constructed by taking the intersection of the tracking gates formed before and after feedback.Secondly, on the basis of the constructed effective tracking gate, probabilistic data association andstrong tracking Kalman filter are combined to form the new multisensor distributed track fusionalgorithm. At last, simulation is performed on the original algorithm and the algorithm presented.

  13. Alternating current line-filter based on electrochemical capacitor utilizing template-patterned graphene

    OpenAIRE

    Zhenkun Wu; Liyi Li; Ziyin Lin; Bo Song; Zhuo Li; Kyoung-Sik Moon; Ching-Ping Wong; Shu-Lin Bai

    2015-01-01

    Aluminum electrolytic capacitors (AECs) are widely used for alternating current (ac) line-filtering. However, their bulky size is becoming more and more incompatible with the rapid development of portable electronics. Here we report a scalable process to fabricate miniaturized graphene-based ac line-filters on flexible substrates at room temperature. In this work, graphene oxide (GO) is reduced by patterned metal interdigits at room temperature and used directly as the electrode material. The...

  14. Microwave photonic filters with negative coefficients based on phase inversion in an electro-optic modulator.

    Science.gov (United States)

    Capmany, José; Pastor, Daniel; Martinez, Alfonso; Ortega, Beatriz; Sales, Salvador

    2003-08-15

    We report on a novel technical approach to the implementation of photonic rf filters that is based on the pi phase inversion that a rf modulating signal suffers in an electro-optic Mach-Zehnder modulator, which depends on whether the positive or the negative linear slope of the signal's modulation transfer function is employed. Experimental evidence is provided of the implementation of filters with negative coefficients that shows excellent agreement with results predicted by the theory.

  15. Separating yolk from white: A filter based on economic properties of trend and cycle

    OpenAIRE

    Zhou, Peng

    2017-01-01

    This paper proposes a new filter technique to separate trend and cycle based on stylised economic properties of trend and cycle, rather than relying on ad hoc statistical proper-ties such as frequency. Given the theoretical separation between economic growth and business cycle literature, it is necessary to make the measures of trend and cycle match what the respective theories intend to explain. The proposed filter is applied to the long macroeconomic data collected by the Bank of England (1...

  16. Reflective Pedagogy: Making Meaning in Experiential Based Online Courses

    Directory of Open Access Journals (Sweden)

    Kathy L. Guthrie

    2010-07-01

    Full Text Available The use of reflective pedagogies has long been considered critical to facilitating meaningful learning through experientially based curricula; however, the use of such methods has not been extensively explored as implemented in virtual environments. The study reviewed utilizes a combination of survey research and individual interviews to examine student perceptions of the meaningful learning which occurred as a result of their participation in two Web-based courses that utilized reflective pedagogies. One course focuses on topics related to service-learning and the second on placement-based internships. Both were instructed using online coursework based in reflective pedagogies to compliment on-site placements within local communities.

  17. Designing metallic iron based water filters: Light from methylene blue discoloration.

    Science.gov (United States)

    Btatkeu-K, B D; Tchatchueng, J B; Noubactep, C; Caré, S

    2016-01-15

    Available water filtration systems containing metallic iron (Fe(0) filters) are pragmatically designed. There is a lack of sound design criteria to exploit the full potential of Fe(0) filters. A science-based design relies on valuable information on processes within a Fe(0) filter, including chemical reactions, hydrodynamics and their relation to the performance of the filter. The aim of this study was to establish a simple method to evaluate the initial performance of Fe(0) filters. The differential adsorptive affinity of methylene blue (MB) onto sand and iron oxide is exploited to characterize the evolution of a Fe(0)/sand system using the pure sand system as operational reference. Five systems were investigated for more than 70 days: pure sand, pure Fe(0), Fe(0)/sand, Fe(0)/pumice and Fe(0)/sand/pumice. Individual systems were characterized by the extent of changes in pH value, iron breakthrough, MB breakthrough and hydraulic conductivity. Results showed that for MB discoloration (i) pure sand was the most efficient system, (ii) hybrid systems were more sustainable than the pure Fe(0) system, and (iii) the pores of used pumice are poorly interconnected. Characterizing the initial reactivity of Fe(0) filters using MB discoloration has introduced a powerful tool for the exploration of various aspects of filter design. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Implementation of High Time Delay Accuracy of Ultrasonic Phased Array Based on Interpolation CIC Filter

    Directory of Open Access Journals (Sweden)

    Peilu Liu

    2017-10-01

    Full Text Available In order to improve the accuracy of ultrasonic phased array focusing time delay, analyzing the original interpolation Cascade-Integrator-Comb (CIC filter, an 8× interpolation CIC filter parallel algorithm was proposed, so that interpolation and multichannel decomposition can simultaneously process. Moreover, we summarized the general formula of arbitrary multiple interpolation CIC filter parallel algorithm and established an ultrasonic phased array focusing time delay system based on 8× interpolation CIC filter parallel algorithm. Improving the algorithmic structure, 12.5% of addition and 29.2% of multiplication was reduced, meanwhile the speed of computation is still very fast. Considering the existing problems of the CIC filter, we compensated the CIC filter; the compensated CIC filter’s pass band is flatter, the transition band becomes steep, and the stop band attenuation increases. Finally, we verified the feasibility of this algorithm on Field Programming Gate Array (FPGA. In the case of system clock is 125 MHz, after 8× interpolation filtering and decomposition, time delay accuracy of the defect echo becomes 1 ns. Simulation and experimental results both show that the algorithm we proposed has strong feasibility. Because of the fast calculation, small computational amount and high resolution, this algorithm is especially suitable for applications with high time delay accuracy and fast detection.

  19. Multi-UAV Doppler Information Fusion for Target Tracking Based on Distributed High Degrees Information Filters

    Directory of Open Access Journals (Sweden)

    Hamza Benzerrouk

    2018-03-01

    Full Text Available Multi-Unmanned Aerial Vehicle (UAV Doppler-based target tracking has not been widely investigated, specifically when using modern nonlinear information filters. A high-degree Gauss–Hermite information filter, as well as a seventh-degree cubature information filter (CIF, is developed to improve the fifth-degree and third-degree CIFs proposed in the most recent related literature. These algorithms are applied to maneuvering target tracking based on Radar Doppler range/range rate signals. To achieve this purpose, different measurement models such as range-only, range rate, and bearing-only tracking are used in the simulations. In this paper, the mobile sensor target tracking problem is addressed and solved by a higher-degree class of quadrature information filters (HQIFs. A centralized fusion architecture based on distributed information filtering is proposed, and yielded excellent results. Three high dynamic UAVs are simulated with synchronized Doppler measurement broadcasted in parallel channels to the control center for global information fusion. Interesting results are obtained, with the superiority of certain classes of higher-degree quadrature information filters.

  20. An improved collaborative filtering approach for predicting cross-category purchases based on binary market basket data

    OpenAIRE

    Mild, Andreas; Reutterer, Thomas

    2002-01-01

    Retail managers have been interested in learning about cross-category purchase behavior of their customers for a fairly long time. More recently, the task of inferring cross-category relationship patterns among retail assortments is gaining attraction due to its promotional potential within recommender systems used in online environments. Collaborative filtering algorithms are frequently used in such settings for the prediction of choices, preferences and/or ratings of online users. This pape...

  1. Gas Path Health Monitoring for a Turbofan Engine Based on a Nonlinear Filtering Approach

    Directory of Open Access Journals (Sweden)

    Yiqiu Lv

    2013-01-01

    Full Text Available Different approaches for gas path performance estimation of dynamic systems are commonly used, the most common being the variants of the Kalman filter. The extended Kalman filter (EKF method is a popular approach for nonlinear systems which combines the traditional Kalman filtering and linearization techniques to effectively deal with weakly nonlinear and non-Gaussian problems. Its mathematical formulation is based on the assumption that the probability density function (PDF of the state vector can be approximated to be Gaussian. Recent investigations have focused on the particle filter (PF based on Monte Carlo sampling algorithms for tackling strong nonlinear and non-Gaussian models. Considering the aircraft engine is a complicated machine, operating under a harsh environment, and polluted by complex noises, the PF might be an available way to monitor gas path health for aircraft engines. Up to this point in time a number of Kalman filtering approaches have been used for aircraft turbofan engine gas path health estimation, but the particle filters have not been used for this purpose and a systematic comparison has not been published. This paper presents gas path health monitoring based on the PF and the constrained extend Kalman particle filter (cEKPF, and then compares the estimation accuracy and computational effort of these filters to the EKF for aircraft engine performance estimation under rapid faults and general deterioration. Finally, the effects of the constraint mechanism and particle number on the cEKPF are discussed. We show in this paper that the cEKPF outperforms the EKF, PF and EKPF, and conclude that the cEKPF is the best choice for turbofan engine health monitoring.

  2. UD-DKF-based Parameters on-line Identification Method and AEKF-Based SOC Estimation Strategy of Lithium-ion Battery

    Directory of Open Access Journals (Sweden)

    Xuanju Dang

    2014-09-01

    Full Text Available State of charge (SOC is a significant parameter for the Battery Management System (BMS. The accurate estimation of the SOC can not only guarantee the SOC remaining within a reasonable scope of work, but also prevent the battery from being over or deeply-charged to extend the lifespan of battery. In this paper, the third-order RC equivalent circuit model is adopted to describe cell characteristics and the dual Kalman filter (DKF is used online to identify model parameters for battery. In order to avoid the impacts of rounding error calculation leading to the estimation error matrix loss of non-negative qualitative which result in the filtering divergence phenomenon, the UD decomposition method is applied for filtering time and state updates simultaneously to enhance the stability of the algorithm, reduce the computational complexity and improve the high recognition accuracy. Based on the obtained model parameters, Adaptive Extended Kalman Filter (AEKF is introduced to online estimate the SOC of battery. The simulation and experimental results demonstrate that the established third-order RC equivalent circuit model is effective, and the SOC estimation has a higher precision.

  3. Discrete Kalman Filter based Sensor Fusion for Robust Accessibility Interfaces

    International Nuclear Information System (INIS)

    Ghersi, I; Miralles, M T; Mariño, M

    2016-01-01

    Human-machine interfaces have evolved, benefiting from the growing access to devices with superior, embedded signal-processing capabilities, as well as through new sensors that allow the estimation of movements and gestures, resulting in increasingly intuitive interfaces. In this context, sensor fusion for the estimation of the spatial orientation of body segments allows to achieve more robust solutions, overcoming specific disadvantages derived from the use of isolated sensors, such as the sensitivity of magnetic-field sensors to external influences, when used in uncontrolled environments. In this work, a method for the combination of image-processing data and angular-velocity registers from a 3D MEMS gyroscope, through a Discrete-time Kalman Filter, is proposed and deployed as an alternate user interface for mobile devices, in which an on-screen pointer is controlled with head movements. Results concerning general performance of the method are presented, as well as a comparative analysis, under a dedicated test application, with results from a previous version of this system, in which the relative-orientation information was acquired directly from MEMS sensors (3D magnetometer-accelerometer). These results show an improved response for this new version of the pointer, both in terms of precision and response time, while keeping many of the benefits that were highlighted for its predecessor, giving place to a complementary method for signal acquisition that can be used as an alternative-input device, as well as for accessibility solutions. (paper)

  4. Collaborating Filtering Community Image Recommendation System Based on Scene

    Directory of Open Access Journals (Sweden)

    He Tao

    2017-01-01

    Full Text Available With the advancement of smart city, the development of intelligent mobile terminal and wireless network, the traditional text information service no longer meet the needs of the community residents, community image service appeared as a new media service. “There are pictures of the truth” has become a community residents to understand and master the new dynamic community, image information service has become a new information service. However, there are two major problems in image information service. Firstly, the underlying eigenvalues extracted by current image feature extraction techniques are difficult for users to understand, and there is a semantic gap between the image content itself and the user’s understanding; secondly, in community life of the image data increasing quickly, it is difficult to find their own interested image data. Aiming at the two problems, this paper proposes a unified image semantic scene model to express the image content. On this basis, a collaborative filtering recommendation model of fusion scene semantics is proposed. In the recommendation model, a comprehensiveness and accuracy user interest model is proposed to improve the recommendation quality. The results of the present study have achieved good results in the pilot cities of Wenzhou and Yan'an, and it is applied normally.

  5. Robust and Adaptive Block Tracking Method Based on Particle Filter

    Directory of Open Access Journals (Sweden)

    Bin Sun

    2015-10-01

    Full Text Available In the field of video analysis and processing, object tracking is attracting more and more attention especially in traffic management, digital surveillance and so on. However problems such as objects’ abrupt motion, occlusion and complex target structures would bring difficulties to academic study and engineering application. In this paper, a fragmentsbased tracking method using the block relationship coefficient is proposed. In this method, we use particle filter algorithm and object region is divided into blocks initially. The contribution of this method is that object features are not extracted just from a single block, the relationship between current block and its neighbor blocks are extracted to describe the variation of the block. Each block is weighted according to the block relationship coefficient when the block is voted on the most matched region in next frame. This method can make full use of the relationship between blocks. The experimental results demonstrate that our method can provide good performance in condition of occlusion and abrupt posture variation.

  6. Automated microaneurysm detection method based on double ring filter in retinal fundus images

    Science.gov (United States)

    Mizutani, Atsushi; Muramatsu, Chisako; Hatanaka, Yuji; Suemori, Shinsuke; Hara, Takeshi; Fujita, Hiroshi

    2009-02-01

    The presence of microaneurysms in the eye is one of the early signs of diabetic retinopathy, which is one of the leading causes of vision loss. We have been investigating a computerized method for the detection of microaneurysms on retinal fundus images, which were obtained from the Retinopathy Online Challenge (ROC) database. The ROC provides 50 training cases, in which "gold standard" locations of microaneurysms are provided, and 50 test cases without the gold standard locations. In this study, the computerized scheme was developed by using the training cases. Although the results for the test cases are also included, this paper mainly discusses the results for the training cases because the "gold standard" for the test cases is not known. After image preprocessing, candidate regions for microaneurysms were detected using a double-ring filter. Any potential false positives located in the regions corresponding to blood vessels were removed by automatic extraction of blood vessels from the images. Twelve image features were determined, and the candidate lesions were classified into microaneurysms or false positives using the rule-based method and an artificial neural network. The true positive fraction of the proposed method was 0.45 at 27 false positives per image. Forty-two percent of microaneurysms in the 50 training cases were considered invisible by the consensus of two co-investigators. When the method was evaluated for visible microaneurysms, the sensitivity for detecting microaneurysms was 65% at 27 false positives per image. Our computerized detection scheme could be improved for helping ophthalmologists in the early diagnosis of diabetic retinopathy.

  7. WaVPeak: Picking NMR peaks through wavelet-based smoothing and volume-based filtering

    KAUST Repository

    Liu, Zhi

    2012-02-10

    Motivation: Nuclear magnetic resonance (NMR) has been widely used as a powerful tool to determine the 3D structures of proteins in vivo. However, the post-spectra processing stage of NMR structure determination usually involves a tremendous amount of time and expert knowledge, which includes peak picking, chemical shift assignment and structure calculation steps. Detecting accurate peaks from the NMR spectra is a prerequisite for all following steps, and thus remains a key problem in automatic NMR structure determination. Results: We introduce WaVPeak, a fully automatic peak detection method. WaVPeak first smoothes the given NMR spectrum by wavelets. The peaks are then identified as the local maxima. The false positive peaks are filtered out efficiently by considering the volume of the peaks. WaVPeak has two major advantages over the state-of-the-art peak-picking methods. First, through wavelet-based smoothing, WaVPeak does not eliminate any data point in the spectra. Therefore, WaVPeak is able to detect weak peaks that are embedded in the noise level. NMR spectroscopists need the most help isolating these weak peaks. Second, WaVPeak estimates the volume of the peaks to filter the false positives. This is more reliable than intensity-based filters that are widely used in existing methods. We evaluate the performance of WaVPeak on the benchmark set proposed by PICKY (Alipanahi et al., 2009), one of the most accurate methods in the literature. The dataset comprises 32 2D and 3D spectra from eight different proteins. Experimental results demonstrate that WaVPeak achieves an average of 96%, 91%, 88%, 76% and 85% recall on 15N-HSQC, HNCO, HNCA, HNCACB and CBCA(CO)NH, respectively. When the same number of peaks are considered, WaVPeak significantly outperforms PICKY. The Author(s) 2012. Published by Oxford University Press.

  8. An effective coded excitation scheme based on a predistorted FM signal and an optimized digital filter

    DEFF Research Database (Denmark)

    Misaridis, Thanasis; Jensen, Jørgen Arendt

    1999-01-01

    This paper presents a coded excitation imaging system based on a predistorted FM excitation and a digital compression filter designed for medical ultrasonic applications, in order to preserve both axial resolution and contrast. In radars, optimal Chebyshev windows efficiently weight a nearly...... as with pulse excitation (about 1.5 lambda), depending on the filter design criteria. The axial sidelobes are below -40 dB, which is the noise level of the measuring imaging system. The proposed excitation/compression scheme shows good overall performance and stability to the frequency shift due to attenuation...... be removed by weighting. We show that by using a predistorted chirp with amplitude or phase shaping for amplitude ripple reduction and a correlation filter that accounts for the transducer's natural frequency weighting, output sidelobe levels of -35 to -40 dB are directly obtained. When an optimized filter...

  9. Gas refractometry based on an all-fiber spatial optical filter.

    Science.gov (United States)

    Silva, Susana; Coelho, L; André, R M; Frazão, O

    2012-08-15

    A spatial optical filter based on splice misalignment between optical fibers with different diameters is proposed for gas refractometry. The sensing head is formed by a 2 mm long optical fiber with 50 μm diameter that is spliced with a strong misalignment between two single-mode fibers (SMF28) and interrogated in transmission. The misalignment causes a Fabry-Perot behavior along the reduced-size fiber and depending on the lead-out SMF28 position, it is possible to obtain different spectral responses, namely, bandpass or band-rejection filters. It is shown that the spatial filter device is highly sensitive to refractive index changes on a nitrogen environment by means of the gas pressure variation. A maximum sensitivity of -1390 nm/RIU for the bandpass filter was achieved. Both devices have shown similar temperature responses with an average sensitivity of 25.7 pm/°C.

  10. Multi-band transmission color filters for multi-color white LEDs based visible light communication

    Science.gov (United States)

    Wang, Qixia; Zhu, Zhendong; Gu, Huarong; Chen, Mengzhu; Tan, Qiaofeng

    2017-11-01

    Light-emitting diodes (LEDs) based visible light communication (VLC) can provide license-free bands, high data rates, and high security levels, which is a promising technique that will be extensively applied in future. Multi-band transmission color filters with enough peak transmittance and suitable bandwidth play a pivotal role for boosting signal-noise-ratio in VLC systems. In this paper, multi-band transmission color filters with bandwidth of dozens nanometers are designed by a simple analytical method. Experiment results of one-dimensional (1D) and two-dimensional (2D) tri-band color filters demonstrate the effectiveness of the multi-band transmission color filters and the corresponding analytical method.

  11. NONLINEAR FILTER METHOD OF GPS DYNAMIC POSITIONING BASED ON BANCROFT ALGORITHM

    Institute of Scientific and Technical Information of China (English)

    ZHANGQin; TAOBen-zao; ZHAOChao-ying; WANGLi

    2005-01-01

    Because of the ignored items after linearization, the extended Kalman filter (EKF) becomes a form of suboptimal gradient descent algorithm. The emanative tendency exists in GPS solution when the filter equations are ill-posed. The deviation in the estimation cannot be avoided. Furthermore, the true solution may be lost in pseudorange positioning because the linearized pseudorange equations are partial solutions. To solve the above problems in GPS dynamic positioning by using EKF, a closed-form Kalman filter method called the two-stage algorithm is presented for the nonlinear algebraic solution of GPS dynamic positioning based on the global nonlinear least squares closed algorithm--Bancroft numerical algorithm of American. The method separates the spatial parts from temporal parts during processing the GPS filter problems, and solves the nonlinear GPS dynamic positioning, thus getting stable and reliable dynamic positioning solutions.

  12. An approach of point cloud denoising based on improved bilateral filtering

    Science.gov (United States)

    Zheng, Zeling; Jia, Songmin; Zhang, Guoliang; Li, Xiuzhi; Zhang, Xiangyin

    2018-04-01

    An omnidirectional mobile platform is designed for building point cloud based on an improved filtering algorithm which is employed to handle the depth image. First, the mobile platform can move flexibly and the control interface is convenient to control. Then, because the traditional bilateral filtering algorithm is time-consuming and inefficient, a novel method is proposed which called local bilateral filtering (LBF). LBF is applied to process depth image obtained by the Kinect sensor. The results show that the effect of removing noise is improved comparing with the bilateral filtering. In the condition of off-line, the color images and processed images are used to build point clouds. Finally, experimental results demonstrate that our method improves the speed of processing time of depth image and the effect of point cloud which has been built.

  13. Iris image recognition wavelet filter-banks based iris feature extraction schemes

    CERN Document Server

    Rahulkar, Amol D

    2014-01-01

    This book provides the new results in wavelet filter banks based feature extraction, and the classifier in the field of iris image recognition. It provides the broad treatment on the design of separable, non-separable wavelets filter banks, and the classifier. The design techniques presented in the book are applied on iris image analysis for person authentication. This book also brings together the three strands of research (wavelets, iris image analysis, and classifier). It compares the performance of the presented techniques with state-of-the-art available schemes. This book contains the compilation of basic material on the design of wavelets that avoids reading many different books. Therefore, it provide an easier path for the new-comers, researchers to master the contents. In addition, the designed filter banks and classifier can also be effectively used than existing filter-banks in many signal processing applications like pattern classification, data-compression, watermarking, denoising etc.  that will...

  14. Stability analysis and active damping for LLCL-filter based grid-connected inverters

    DEFF Research Database (Denmark)

    Huang, Min; Blaabjerg, Frede; Loh, Poh Chiang

    2014-01-01

    A higher order passive power filter (LLCL-filter) for the grid-tied inverter is becoming attractive for the industrial applications due to the possibility to reduce the cost of the copper and the magnetic material. To avoid the well-known stability problems of the LLCL-filter it is requested to use...... either passive or active damping methods. This paper analyzes the stability when damping is required and when damping is not necessary considering sampling and transport delay. Basic LLCL resonance damping properties of different feedback states are also studied. Then an active damping method which...... is using the capacitor current feedback for LLCL-filter is introduced. Based on this method, a design procedure for the control method is given. Last, both simulation and experimental results are provided to validate the theoretical analysis of this paper....

  15. Fading Kalman filter-based real-time state of charge estimation in LiFePO_4 battery-powered electric vehicles

    International Nuclear Information System (INIS)

    Lim, KaiChin; Bastawrous, Hany Ayad; Duong, Van-Huan; See, Khay Wai; Zhang, Peng; Dou, Shi Xue

    2016-01-01

    Highlights: • Real-time battery model parameters and SoC estimation with novel method is proposed. • Cascading filtering stages are used for parameters identification and SoC estimation. • Optimized fading Kalman filter is implemented for SoC estimation. • Accurate SoC estimation is validated in UDDS load profile experiment. • This approach is suitable for BMS in EV applications due to its simplicity. - Abstract: A novel online estimation technique for estimating the state of charge (SoC) of a lithium iron phosphate (LiFePO_4) battery has been developed. Based on a simplified model, the open circuit voltage (OCV) of the battery is estimated through two cascaded linear filtering stages. A recursive least squares filter is employed in the first stage to dynamically estimate the battery model parameters in real-time, and then, a fading Kalman filter (FKF) is used to estimate the OCV from these parameters. FKF can avoid the possibility of large estimation errors, which may occur with a conventional Kalman filter, due to its capability to compensate any modeling error through a fading factor. By optimizing the value of the fading factor in the set of recursion equations of FKF with genetic algorithms, the errors in estimating the battery’s SoC in urban dynamometer driving schedules-based experiments and real vehicle driving cycle experiments were below 3% compared to more than 9% in the case of using an ordinary Kalman filter. The proposed method with its simplified model provides the simplicity and feasibility required for real-time application with highly accurate SoC estimation.

  16. A nowcasting technique based on application of the particle filter blending algorithm

    Science.gov (United States)

    Chen, Yuanzhao; Lan, Hongping; Chen, Xunlai; Zhang, Wenhai

    2017-10-01

    To improve the accuracy of nowcasting, a new extrapolation technique called particle filter blending was configured in this study and applied to experimental nowcasting. Radar echo extrapolation was performed by using the radar mosaic at an altitude of 2.5 km obtained from the radar images of 12 S-band radars in Guangdong Province, China. The first bilateral filter was applied in the quality control of the radar data; an optical flow method based on the Lucas-Kanade algorithm and the Harris corner detection algorithm were used to track radar echoes and retrieve the echo motion vectors; then, the motion vectors were blended with the particle filter blending algorithm to estimate the optimal motion vector of the true echo motions; finally, semi-Lagrangian extrapolation was used for radar echo extrapolation based on the obtained motion vector field. A comparative study of the extrapolated forecasts of four precipitation events in 2016 in Guangdong was conducted. The results indicate that the particle filter blending algorithm could realistically reproduce the spatial pattern, echo intensity, and echo location at 30- and 60-min forecast lead times. The forecasts agreed well with observations, and the results were of operational significance. Quantitative evaluation of the forecasts indicates that the particle filter blending algorithm performed better than the cross-correlation method and the optical flow method. Therefore, the particle filter blending method is proved to be superior to the traditional forecasting methods and it can be used to enhance the ability of nowcasting in operational weather forecasts.

  17. a Threshold-Free Filtering Algorithm for Airborne LIDAR Point Clouds Based on Expectation-Maximization

    Science.gov (United States)

    Hui, Z.; Cheng, P.; Ziggah, Y. Y.; Nie, Y.

    2018-04-01

    Filtering is a key step for most applications of airborne LiDAR point clouds. Although lots of filtering algorithms have been put forward in recent years, most of them suffer from parameters setting or thresholds adjusting, which will be time-consuming and reduce the degree of automation of the algorithm. To overcome this problem, this paper proposed a threshold-free filtering algorithm based on expectation-maximization. The proposed algorithm is developed based on an assumption that point clouds are seen as a mixture of Gaussian models. The separation of ground points and non-ground points from point clouds can be replaced as a separation of a mixed Gaussian model. Expectation-maximization (EM) is applied for realizing the separation. EM is used to calculate maximum likelihood estimates of the mixture parameters. Using the estimated parameters, the likelihoods of each point belonging to ground or object can be computed. After several iterations, point clouds can be labelled as the component with a larger likelihood. Furthermore, intensity information was also utilized to optimize the filtering results acquired using the EM method. The proposed algorithm was tested using two different datasets used in practice. Experimental results showed that the proposed method can filter non-ground points effectively. To quantitatively evaluate the proposed method, this paper adopted the dataset provided by the ISPRS for the test. The proposed algorithm can obtain a 4.48 % total error which is much lower than most of the eight classical filtering algorithms reported by the ISPRS.

  18. Game-based online antenatal breastfeeding education: A pilot.

    Science.gov (United States)

    Grassley, Jane S; Connor, Kelley C; Bond, Laura

    2017-02-01

    The aim of this study was to evaluate the effect of the Healthy Moms intervention on antenatal breastfeeding self-efficacy and intention and to determine the feasibility of using an online game-based learning platform to deliver antenatal breastfeeding education. The Internet has potential for improving breastfeeding rates through improving women's access to antenatal breastfeeding education. Twelve computer-based breastfeeding education modules were developed using an online learning platform. Changes in participants' breastfeeding self-efficacy and intention pre- and post-intervention were measured using descriptive statistics and a one-way ANOVA. Of the 25 women submitting the pretest, four completed zero quests; seven, orientation only; eight, one to six breastfeeding quests; and six, 10 to 12 breastfeeding quests. No significant differences in breastfeeding self-efficacy and intention were found among the groups. Online antenatal breastfeeding education is feasible; however, further research is warranted to determine if it can affect breastfeeding outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Catching the Drift : Using Feature-Free Case-Based Reasoning for Spam Filtering.

    OpenAIRE

    Delany, Sarah Jane; Bridge, Derek

    2007-01-01

    n this paper, we compare case-based spam filters, focusing on their resilience to concept drift. In particular, we evaluate how to track concept drift using a case-based spam filter that uses a feature-free distance measure based on text compression. In our experiments, we compare two ways to normalise such a distance measure, finding that the one proposed in [1] performs better. We show that a policy as simple as retaining misclassified examples has a hugely beneficial effect on handling con...

  20. A soft sensor for bioprocess control based on sequential filtering of metabolic heat signals.

    Science.gov (United States)

    Paulsson, Dan; Gustavsson, Robert; Mandenius, Carl-Fredrik

    2014-09-26

    Soft sensors are the combination of robust on-line sensor signals with mathematical models for deriving additional process information. Here, we apply this principle to a microbial recombinant protein production process in a bioreactor by exploiting bio-calorimetric methodology. Temperature sensor signals from the cooling system of the bioreactor were used for estimating the metabolic heat of the microbial culture and from that the specific growth rate and active biomass concentration were derived. By applying sequential digital signal filtering, the soft sensor was made more robust for industrial practice with cultures generating low metabolic heat in environments with high noise level. The estimated specific growth rate signal obtained from the three stage sequential filter allowed controlled feeding of substrate during the fed-batch phase of the production process. The biomass and growth rate estimates from the soft sensor were also compared with an alternative sensor probe and a capacitance on-line sensor, for the same variables. The comparison showed similar or better sensitivity and lower variability for the metabolic heat soft sensor suggesting that using permanent temperature sensors of a bioreactor is a realistic and inexpensive alternative for monitoring and control. However, both alternatives are easy to implement in a soft sensor, alone or in parallel.

  1. A Soft Sensor for Bioprocess Control Based on Sequential Filtering of Metabolic Heat Signals

    Directory of Open Access Journals (Sweden)

    Dan Paulsson

    2014-09-01

    Full Text Available Soft sensors are the combination of robust on-line sensor signals with mathematical models for deriving additional process information. Here, we apply this principle to a microbial recombinant protein production process in a bioreactor by exploiting bio-calorimetric methodology. Temperature sensor signals from the cooling system of the bioreactor were used for estimating the metabolic heat of the microbial culture and from that the specific growth rate and active biomass concentration were derived. By applying sequential digital signal filtering, the soft sensor was made more robust for industrial practice with cultures generating low metabolic heat in environments with high noise level. The estimated specific growth rate signal obtained from the three stage sequential filter allowed controlled feeding of substrate during the fed-batch phase of the production process. The biomass and growth rate estimates from the soft sensor were also compared with an alternative sensor probe and a capacitance on-line sensor, for the same variables. The comparison showed similar or better sensitivity and lower variability for the metabolic heat soft sensor suggesting that using permanent temperature sensors of a bioreactor is a realistic and inexpensive alternative for monitoring and control. However, both alternatives are easy to implement in a soft sensor, alone or in parallel.

  2. Elaborate analysis and design of filter-bank-based sensing for wideband cognitive radios

    Science.gov (United States)

    Maliatsos, Konstantinos; Adamis, Athanasios; Kanatas, Athanasios G.

    2014-12-01

    The successful operation of a cognitive radio system strongly depends on its ability to sense the radio environment. With the use of spectrum sensing algorithms, the cognitive radio is required to detect co-existing licensed primary transmissions and to protect them from interference. This paper focuses on filter-bank-based sensing and provides a solid theoretical background for the design of these detectors. Optimum detectors based on the Neyman-Pearson theorem are developed for uniform discrete Fourier transform (DFT) and modified DFT filter banks with root-Nyquist filters. The proposed sensing framework does not require frequency alignment between the filter bank of the sensor and the primary signal. Each wideband primary channel is spanned and monitored by several sensor subchannels that analyse it in narrowband signals. Filter-bank-based sensing is proved to be robust and efficient under coloured noise. Moreover, the performance of the weighted energy detector as a sensing technique is evaluated. Finally, based on the Locally Most Powerful and the Generalized Likelihood Ratio test, real-world sensing algorithms that do not require a priori knowledge are proposed and tested.

  3. Multiple Maneuvering Target Tracking by Improved Particle Filter Based on Multiscan JPDA

    Directory of Open Access Journals (Sweden)

    Jing Liu

    2012-01-01

    Full Text Available The multiple maneuvering target tracking algorithm based on a particle filter is addressed. The equivalent-noise approach is adopted, which uses a simple dynamic model consisting of target state and equivalent noise which accounts for the combined effects of the process noise and maneuvers. The equivalent-noise approach converts the problem of maneuvering target tracking to that of state estimation in the presence of nonstationary process noise with unknown statistics. A novel method for identifying the nonstationary process noise is proposed in the particle filter framework. Furthermore, a particle filter based multiscan Joint Probability Data Association (JPDA filter is proposed to deal with the data association problem in a multiple maneuvering target tracking. In the proposed multiscan JPDA algorithm, the distributions of interest are the marginal filtering distributions for each of the targets, and these distributions are approximated with particles. The multiscan JPDA algorithm examines the joint association events in a multiscan sliding window and calculates the marginal posterior probability based on the multiscan joint association events. The proposed algorithm is illustrated via an example involving the tracking of two highly maneuvering, at times closely spaced and crossed, targets, based on resolved measurements.

  4. VizieR Online Data Catalog: Flux conversion factors for the Swift/UVOT filters (Brown+, 2016)

    Science.gov (United States)

    Brown, P. J.; Breeveld, A.; Roming, P. W. A.; Siegel, M.

    2016-10-01

    The conversion of observed magnitudes (or the actual observed photon or electron count rates) to a flux density is one of the most fundamental calculations. The flux conversions factors for the six Swift/UVOT filters are tabulated in Table1. (1 data file).

  5. Research on signal processing of shock absorber test bench based on zero-phase filter

    Science.gov (United States)

    Wu, Yi; Ding, Guoqing

    2017-10-01

    The quality of force-displacement diagram is significant to help evaluate the performance of shock absorbers. Damping force sampling data is often interfered by Gauss white noise, 50Hz power interference and its harmonic wave during the process of testing; data de-noising has become the core problem of drawing true, accurate and real-time indicator diagram. The noise and interference can be filtered out through generic IIR or FIR low-pass filter, but addition phase lag of useful signal will be caused due to the inherent attribute of IIR and FIR filter. The paper uses FRR method to realize zero-phase digital filtering in a software way based on mutual cancellation of phase lag between the forward and reverse sequences after through the filter. High-frequency interference above 40Hz are filtered out completely and noise attenuation is more than -40dB, with no additional phase lag. The method is able to restore the true signal as far as possible. Theoretical simulation and practical test indicate high-frequency noises have been effectively inhibited in multiple typical speed cases, signal-to-noise ratio being greatly improved; the curve in indicator diagram has better smoothness and fidelity. The FRR algorithm has low computational complexity, fast running time, and can be easily transplanted in multiple platforms.

  6. Tunable M-channel filter based on Thue-Morse heterostructures containing meta materials

    Directory of Open Access Journals (Sweden)

    H Pashaei Adl

    2015-01-01

    Full Text Available In this paper the tunable M-channel filters based on Thue-Morse heterostructures consisting of single -negative materials has been studied. The results showed that the number of resonance modes inside the zero- gap increases as the number of heterogenous interface, M, increases. The number of resonance modes inside the zero- gap is equal to that of heterogenous interface M, and it can be used as M channels filter. This result provides a feasible method to adjust the channel number of multiple-channel filters. When losses are involved, the results showed that the electric fields of the resonance modes decay largely with the increase of the number of heterogenous interface and damping factors. Besides, the relationship between the quality factor of multiple-channel filters and the number of heterogenous interface M is linear, and the quality factor of multiple-channel filters decreases with the increase of the damping factor. These results provide feasible methods to adjust the quality factor of multiple-channel filters

  7. Design of quadrature mirror filter bank using Lagrange multiplier method based on fractional derivative constraints

    Directory of Open Access Journals (Sweden)

    B. Kuldeep

    2015-06-01

    Full Text Available Fractional calculus has recently been identified as a very important mathematical tool in the field of signal processing. Digital filters designed by fractional derivatives give more accurate frequency response in the prescribed frequency region. Digital filters are most important part of multi-rate filter bank systems. In this paper, an improved method based on fractional derivative constraints is presented for the design of two-channel quadrature mirror filter (QMF bank. The design problem is formulated as minimization of L2 error of filter bank transfer function in passband, stopband interval and at quadrature frequency, and then Lagrange multiplier method with fractional derivative constraints is applied to solve it. The proposed method is then successfully applied for the design of two-channel QMF bank with higher order filter taps. Performance of the QMF bank design is then examined through study of various parameters such as passband error, stopband error, transition band error, peak reconstruction error (PRE, stopband attenuation (As. It is found that, the good design can be obtained with the change of number and value of fractional derivative constraint coefficients.

  8. A composite passive damping method of the LLCL-filter based grid-tied inverter

    DEFF Research Database (Denmark)

    Wu, Weimin; Huang, Min; Sun, Yunjie

    2012-01-01

    This paper investigates the maximum and the minimum gain of the proportional resonant based grid current controller for a grid-tied inverter with a passive damped high-order power filter. It is found that the choice of the controller gain is limited to the local maximum amplitude determined by Q......-factor around the characteristic frequency of the filter and grid impedance. To obtain the Q-factor of a high-order system, an equivalent circuit analysis method is proposed and illustrated through several classical passive damped LCL- and LLCL-filters. It is shown that both the RC parallel damper...... that is in parallel with the capacitor of the LCL-filter or with the Lf-Cf resonant circuit of the LLCL-filter, and the RL series damper in series with the grid-side inductor have their own application limits. Thus, a composite passive damped LLCL-filter for the grid-tied inverter is proposed, which can effectively...

  9. A low loss superconducting filter with four states based on symmetrical interdigital-loaded structure

    International Nuclear Information System (INIS)

    Gao, Tianqi; Wei, Bin; Cao, Bisong; Wang, Dan; Guo, Xubo

    2016-01-01

    Highlights: • A novel symmetrical interdigital-loaded microstrip structure is presents. • A six-pole L-band HTS filter with four states has similar in-band responses. • The coupling coefficients between resonators keep unchanged during tuning. • The low loss HTS filter can be tuned from 1.382 GHz to 1.193 GHz. - Abstract: This paper presents a new symmetrical interdigital-loaded microstrip structure. The symmetrical structure can be applied to design a filter that can work at different frequencies. The filter has similar in-band response at each working frequency with low insertion loss. Based on the proposed structures, a low-loss six-pole high temperature superconducting (HTS) filter with four different working states is designed and fabricated. The center frequency of the filter can be tuned discretely from 1.382 GHz to 1.193 GHz. All four states have similar in-band characters, whereas the insertion losses are less than 0.3 dB. The measured results are consistent with the simulations.

  10. RSSI-Based Distance Estimation Framework Using a Kalman Filter for Sustainable Indoor Computing Environments

    Directory of Open Access Journals (Sweden)

    Yunsick Sung

    2016-11-01

    Full Text Available Given that location information is the key to providing a variety of services in sustainable indoor computing environments, it is required to obtain accurate locations. Locations can be estimated by three distances from three fixed points. Therefore, if the distance between two points can be measured or estimated accurately, the location in indoor environments can be estimated. To increase the accuracy of the measured distance, noise filtering, signal revision, and distance estimation processes are generally performed. This paper proposes a novel framework for estimating the distance between a beacon and an access point (AP in a sustainable indoor computing environment. Diverse types of received strength signal indications (RSSIs are used for WiFi, Bluetooth, and radio signals, and the proposed distance estimation framework is unique in that it is independent of the specific wireless signal involved, being based on the Bluetooth signal of the beacon. Generally, RSSI measurement, noise filtering, and revision are required for distance estimation using RSSIs. The employed RSSIs are first measured from an AP, with multiple APs sometimes used to increase the accuracy of the distance estimation. Owing to the inevitable presence of noise in the measured RSSIs, the application of noise filtering is essential, and further revision is used to address the inaccuracy and instability that characterizes RSSIs measured in an indoor environment. The revised RSSIs are then used to estimate the distance. The proposed distance estimation framework uses one AP to measure the RSSIs, a Kalman filter to eliminate noise, and a log-distance path loss model to revise the measured RSSIs. In the experimental implementation of the framework, both a RSSI filter and a Kalman filter were respectively used for noise elimination to comparatively evaluate the performance of the latter for the specific application. The Kalman filter was found to reduce the accumulated errors by 8

  11. Integration of GPS precise point positioning and MEMS-based INS using unscented particle filter.

    Science.gov (United States)

    Abd Rabbou, Mahmoud; El-Rabbany, Ahmed

    2015-03-25

    Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) integrated system involves nonlinear motion state and measurement models. However, the extended Kalman filter (EKF) is commonly used as the estimation filter, which might lead to solution divergence. This is usually encountered during GPS outages, when low-cost micro-electro-mechanical sensors (MEMS) inertial sensors are used. To enhance the navigation system performance, alternatives to the standard EKF should be considered. Particle filtering (PF) is commonly considered as a nonlinear estimation technique to accommodate severe MEMS inertial sensor biases and noise behavior. However, the computation burden of PF limits its use. In this study, an improved version of PF, the unscented particle filter (UPF), is utilized, which combines the unscented Kalman filter (UKF) and PF for the integration of GPS precise point positioning and MEMS-based inertial systems. The proposed filter is examined and compared with traditional estimation filters, namely EKF, UKF and PF. Tightly coupled mechanization is adopted, which is developed in the raw GPS and INS measurement domain. Un-differenced ionosphere-free linear combinations of pseudorange and carrier-phase measurements are used for PPP. The performance of the UPF is analyzed using a real test scenario in downtown Kingston, Ontario. It is shown that the use of UPF reduces the number of samples needed to produce an accurate solution, in comparison with the traditional PF, which in turn reduces the processing time. In addition, UPF enhances the positioning accuracy by up to 15% during GPS outages, in comparison with EKF. However, all filters produce comparable results when the GPS measurement updates are available.

  12. Kalman/Map Filtering-Aided Fast Normalized Cross Correlation-Based Wi-Fi Fingerprinting Location Sensing

    Directory of Open Access Journals (Sweden)

    Yongliang Sun

    2013-11-01

    Full Text Available A Kalman/map filtering (KMF-aided fast normalized cross correlation (FNCC-based Wi-Fi fingerprinting location sensing system is proposed in this paper. Compared with conventional neighbor selection algorithms that calculate localization results with received signal strength (RSS mean samples, the proposed FNCC algorithm makes use of all the on-line RSS samples and reference point RSS variations to achieve higher fingerprinting accuracy. The FNCC computes efficiently while maintaining the same accuracy as the basic normalized cross correlation. Additionally, a KMF is also proposed to process fingerprinting localization results. It employs a new map matching algorithm to nonlinearize the linear location prediction process of Kalman filtering (KF that takes advantage of spatial proximities of consecutive localization results. With a calibration model integrated into an indoor map, the map matching algorithm corrects unreasonable prediction locations of the KF according to the building interior structure. Thus, more accurate prediction locations are obtained. Using these locations, the KMF considerably improves fingerprinting algorithm performance. Experimental results demonstrate that the FNCC algorithm with reduced computational complexity outperforms other neighbor selection algorithms and the KMF effectively improves location sensing accuracy by using indoor map information and spatial proximities of consecutive localization results.

  13. Kalman/Map filtering-aided fast normalized cross correlation-based Wi-Fi fingerprinting location sensing.

    Science.gov (United States)

    Sun, Yongliang; Xu, Yubin; Li, Cheng; Ma, Lin

    2013-11-13

    A Kalman/map filtering (KMF)-aided fast normalized cross correlation (FNCC)-based Wi-Fi fingerprinting location sensing system is proposed in this paper. Compared with conventional neighbor selection algorithms that calculate localization results with received signal strength (RSS) mean samples, the proposed FNCC algorithm makes use of all the on-line RSS samples and reference point RSS variations to achieve higher fingerprinting accuracy. The FNCC computes efficiently while maintaining the same accuracy as the basic normalized cross correlation. Additionally, a KMF is also proposed to process fingerprinting localization results. It employs a new map matching algorithm to nonlinearize the linear location prediction process of Kalman filtering (KF) that takes advantage of spatial proximities of consecutive localization results. With a calibration model integrated into an indoor map, the map matching algorithm corrects unreasonable prediction locations of the KF according to the building interior structure. Thus, more accurate prediction locations are obtained. Using these locations, the KMF considerably improves fingerprinting algorithm performance. Experimental results demonstrate that the FNCC algorithm with reduced computational complexity outperforms other neighbor selection algorithms and the KMF effectively improves location sensing accuracy by using indoor map information and spatial proximities of consecutive localization results.

  14. Tunable and reconfigurable multi-tap microwave photonic filter based on dynamic Brillouin gratings in fibers.

    Science.gov (United States)

    Sancho, J; Primerov, N; Chin, S; Antman, Y; Zadok, A; Sales, S; Thévenaz, L

    2012-03-12

    We propose and experimentally demonstrate new architectures to realize multi-tap microwave photonic filters, based on the generation of a single or multiple dynamic Brillouin gratings in polarization maintaining fibers. The spectral range and selectivity of the proposed periodic filters is extensively tunable, simply by reconfiguring the positions and the number of dynamic gratings along the fiber respectively. In this paper, we present a complete analysis of three different configurations comprising a microwave photonic filter implementation: a simple notch-type Mach-Zehnder approach with a single movable dynamic grating, a multi-tap performance based on multiple dynamic gratings and finally a stationary grating configuration based on the phase modulation of two counter-propagating optical waves by a common pseudo-random bit sequence (PRBS).

  15. Fine-filter method for Raman lidar based on wavelength division multiplexing and fiber Bragg grating.

    Science.gov (United States)

    Wang, Jun; Zheng, Jiao; Lu, Hong; Yan, Qing; Wang, Li; Liu, Jingjing; Hua, Dengxin

    2017-11-01

    Atmospheric temperature is one of the important parameters for the description of the atmospheric state. Most of the detection approaches to atmospheric temperature monitoring are based on rotational Raman scattering for better understanding atmospheric dynamics, thermodynamics, atmospheric transmission, and radiation. In this paper, we present a fine-filter method based on wavelength division multiplexing, incorporating a fiber Bragg grating in the visible spectrum for the rotational Raman scattering spectrum. To achieve high-precision remote sensing, the strong background noise is filtered out by using the secondary cascaded light paths. Detection intensity and the signal-to-noise ratio are improved by increasing the utilization rate of return signal form atmosphere. Passive temperature compensation is employed to reduce the temperature sensitivity of fiber Bragg grating. In addition, the proposed method provides a feasible solution for the filter system with the merits of miniaturization, high anti-interference, and high stability in the space-based platform.

  16. Cooperative Localization for Multi-AUVs Based on GM-PHD Filters and Information Entropy Theory

    Directory of Open Access Journals (Sweden)

    Lichuan Zhang

    2017-10-01

    Full Text Available Cooperative localization (CL is considered a promising method for underwater localization with respect to multiple autonomous underwater vehicles (multi-AUVs. In this paper, we proposed a CL algorithm based on information entropy theory and the probability hypothesis density (PHD filter, aiming to enhance the global localization accuracy of the follower. In the proposed framework, the follower carries lower cost navigation systems, whereas the leaders carry better ones. Meanwhile, the leaders acquire the followers’ observations, including both measurements and clutter. Then, the PHD filters are utilized on the leaders and the results are communicated to the followers. The followers then perform weighted summation based on all received messages and obtain a final positioning result. Based on the information entropy theory and the PHD filter, the follower is able to acquire a precise knowledge of its position.

  17. Optical microwave filter based on spectral slicing by use of arrayed waveguide gratings.

    Science.gov (United States)

    Pastor, Daniel; Ortega, Beatriz; Capmany, José; Sales, Salvador; Martinez, Alfonso; Muñoz, Pascual

    2003-10-01

    We have experimentally demonstrated a new optical signal processor based on the use of arrayed waveguide gratings. The structure exploits the concept of spectral slicing combined with the use of an optical dispersive medium. The approach presents increased flexibility from previous slicing-based structures in terms of tunability, reconfiguration, and apodization of the samples or coefficients of the transversal optical filter.

  18. Supervision in the PC based prototype for the ATLAS event filter

    CERN Document Server

    Bee, C P; Etienne, F; Fede, E; Meessen, C; Nacasch, R; Qian, Z; Touchard, F

    1999-01-01

    A prototype of the ATLAS event filter based on commodity PCs linked by a Fast Ethernet switch has been developed in Marseille. The present contribution focus on the supervision aspects of the prototype based on Java and Java mobile agents technology. (5 refs).

  19. Designing an Inverter-based Operational Transconductance Amplifier-capacitor Filter with Low Power Consumption for Biomedical Applications.

    Science.gov (United States)

    Yousefinezhad, Sajad; Kermani, Saeed; Hosseinnia, Saeed

    2018-01-01

    The operational transconductance amplifier-capacitor (OTA-C) filter is one of the best structures for implementing continuous-time filters. It is particularly important to design a universal OTA-C filter capable of generating the desired filter response via a single structure, thus reducing the filter circuit power consumption as well as noise and the occupied space on the electronic chip. In this study, an inverter-based universal OTA-C filter with very low power consumption and acceptable noise was designed with applications in bioelectric and biomedical equipment for recording biomedical signals. The very low power consumption of the proposed filter was achieved through introducing bias in subthreshold MOSFET transistors. The proposed filter is also capable of simultaneously receiving favorable low-, band-, and high-pass filter responses. The performance of the proposed filter was simulated and analyzed via HSPICE software (level 49) and 180 nm complementary metal-oxide-semiconductor technology. The rate of power consumption and noise obtained from simulations are 7.1 nW and 10.18 nA, respectively, so this filter has reduced noise as well as power consumption. The proposed universal OTA-C filter was designed based on the minimum number of transconductance blocks and an inverter circuit by three transconductance blocks (OTA).

  20. Combined adaptive multiple subtraction based on optimized event tracing and extended wiener filtering

    Science.gov (United States)

    Tan, Jun; Song, Peng; Li, Jinshan; Wang, Lei; Zhong, Mengxuan; Zhang, Xiaobo

    2017-06-01

    The surface-related multiple elimination (SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the predicted multiples and those in the source seismic records, which may result in conventional adaptive multiple subtraction methods being barely able to effectively suppress multiples in actual production. This paper introduces a combined adaptive multiple attenuation method based on the optimized event tracing technique and extended Wiener filtering. The method firstly uses multiple records predicted by SRME to generate a multiple velocity spectrum, then separates the original record to an approximate primary record and an approximate multiple record by applying the optimized event tracing method and short-time window FK filtering method. After applying the extended Wiener filtering method, residual multiples in the approximate primary record can then be eliminated and the damaged primary can be restored from the approximate multiple record. This method combines the advantages of multiple elimination based on the optimized event tracing method and the extended Wiener filtering technique. It is an ideal method for suppressing typical hyperbolic and other types of multiples, with the advantage of minimizing damage of the primary. Synthetic and field data tests show that this method produces better multiple elimination results than the traditional multi-channel Wiener filter method and is more suitable for multiple elimination in complicated geological areas.

  1. Virus Database and Online Inquiry System Based on Natural Vectors.

    Science.gov (United States)

    Dong, Rui; Zheng, Hui; Tian, Kun; Yau, Shek-Chung; Mao, Weiguang; Yu, Wenping; Yin, Changchuan; Yu, Chenglong; He, Rong Lucy; Yang, Jie; Yau, Stephen St

    2017-01-01

    We construct a virus database called VirusDB (http://yaulab.math.tsinghua.edu.cn/VirusDB/) and an online inquiry system to serve people who are interested in viral classification and prediction. The database stores all viral genomes, their corresponding natural vectors, and the classification information of the single/multiple-segmented viral reference sequences downloaded from National Center for Biotechnology Information. The online inquiry system serves the purpose of computing natural vectors and their distances based on submitted genomes, providing an online interface for accessing and using the database for viral classification and prediction, and back-end processes for automatic and manual updating of database content to synchronize with GenBank. Submitted genomes data in FASTA format will be carried out and the prediction results with 5 closest neighbors and their classifications will be returned by email. Considering the one-to-one correspondence between sequence and natural vector, time efficiency, and high accuracy, natural vector is a significant advance compared with alignment methods, which makes VirusDB a useful database in further research.

  2. Do Online Comments Influence the Public's Attitudes Toward an Organization? Effects of Online Comments Based on Individuals' Prior Attitudes.

    Science.gov (United States)

    Sung, Kang Hoon; Lee, Moon J

    2015-01-01

    The authors investigated the effects of reading different types of online comments about a company on people's attitude change based on individual's prior attitude toward the company. Based on Social Judgment Theory, several hypotheses were tested. The results showed that the effects of online comments interact with individuals' prior attitudes toward a corporation. People with a strong negative attitude toward a corporation were less influenced by other's online comments than people with a neutral attitude in general. However, people with a prior negative attitude were more affected by refutational two-sided comments than one-sided comments. The results suggest that the effects of user generated content should be studied in a holistic manner, not only by investigating the effects of online content itself, but also by examining how others' responses to the content shape or change individuals' attitudes based on their prior attitudes.

  3. British surgeons' experiences of mandatory online workplace-based assessment.

    Science.gov (United States)

    Pereira, Erlick A C; Dean, Benjamin J F

    2009-07-01

    An online workplace-based assessment tool, the Intercollegiate Surgical Curriculum Programme (ISCP), has become mandatory for all British surgical trainees appointed since August 2007. A compulsory pound125 annual trainee fee has also been introduced to fund its running costs. The study sought to evaluate user satisfaction with the ISCP. A total of 539 users across all surgical specialties (including 122 surgeons acting as assessors) were surveyed in late 2008 by online questionnaire regarding their experiences with the ISCP. Sixty-seven percent had used the tool for at least one year. It was rated above average by only 6% for its registration process and only 11% for recording meetings and objectives. Forty-nine percent described its online assessments as poor or very poor, only 9% considering them good or very good. Seventy-nine percent rated the website's user friendliness as average or worse, as did 72% its peer-assessment tool and 61% its logbook of procedures. Seventy-six percent of respondents had carried out paper assessments due to difficulties using the website. Six percent stated that the ISCP had impacted negatively on their training opportunities, 41% reporting a negative impact overall upon their training; only 6% reported a positive impact. Ninety-four percent did not consider the trainee fee good value, only 2% believing it should be paid by the trainee. The performance of the ISCP leaves large numbers of British surgeons unsatisfied. Its assessments lack appropriate evidence of validity and its introduction has been problematic. With reducing training hours, the increased online bureaucratic burden exacerbates low morale of trainees and trainers, adversely impacting potentially upon both competency and productivity.

  4. Physical Modeling of the Polyfrequency Filter-Compensating Device Based on the Capacitor-Coil

    Science.gov (United States)

    Butyrin, P. A.; Gusev, G. G.; Mikheev, D. V.; Shakirzianov, F. N.

    2017-12-01

    The paper presents the results of physical modeling and experimental study of the frequency characteristics of the polyfrequency filter-compensating device (PFCD) based on a capacitor-coil. The amplitude- frequency and phase-frequency characteristics of the physical PFCD model were constructed and its equivalent parameters were identified. The feasibility of a PFCD in the form of a single technical device with high technical and economic characteristics was experimentally proven. In the paper, recommendations for practical applications of the capacitor-coil-based PFCD are made and the advantages of the device over known standard passive filter-compensating devices are evaluated.

  5. Towards Effective Trust-Based Packet Filtering in Collaborative Network Environments

    DEFF Research Database (Denmark)

    Meng, Weizhi; Li, Wenjuan; Kwok, Lam-For

    2017-01-01

    compromised by insider attacks. In this paper, we adopt the existing CIDN framework and aim to apply a collaborative trust-based approach to reduce unwanted packets. More specifically, we develop a collaborative trust-based packet filter, which can be deployed in collaborative networks and be robust against...... typical insider attacks (e.g., betrayal attacks). Experimental results in various simulated and practical environments demonstrate that our filter can perform effectively in reducing unwanted traffic and can defend against insider attacks through identifying malicious nodes in a quick manner, as compared...

  6. Online marketing improvement based on marketing psychology, case: Roomsevilla

    OpenAIRE

    Laakkonen, Roosa

    2013-01-01

    The purpose of this thesis was to study and find out the best cost-effective online marketing channels for a Spanish housing agency Roomsevilla in order to strengthen its online marketing. In addition, this thesis aims to find out how the case company can use marketing psychology in its online marketing. The theoretical part includes online marketing, marketing mix and marketing psycho- logy which were collected from various books, online journals and websites. Also Cialdini's 6 Principle...

  7. Model-based Prognostics with Fixed-lag Particle Filters

    Data.gov (United States)

    National Aeronautics and Space Administration — Model-based prognostics exploits domain knowl- edge of the system, its components, and how they fail by casting the underlying physical phenom- ena in a...

  8. pyAmpli: an amplicon-based variant filter pipeline for targeted resequencing data.

    Science.gov (United States)

    Beyens, Matthias; Boeckx, Nele; Van Camp, Guy; Op de Beeck, Ken; Vandeweyer, Geert

    2017-12-14

    Haloplex targeted resequencing is a popular method to analyze both germline and somatic variants in gene panels. However, involved wet-lab procedures may introduce false positives that need to be considered in subsequent data-analysis. No variant filtering rationale addressing amplicon enrichment related systematic errors, in the form of an all-in-one package, exists to our knowledge. We present pyAmpli, a platform independent parallelized Python package that implements an amplicon-based germline and somatic variant filtering strategy for Haloplex data. pyAmpli can filter variants for systematic errors by user pre-defined criteria. We show that pyAmpli significantly increases specificity, without reducing sensitivity, essential for reporting true positive clinical relevant mutations in gene panel data. pyAmpli is an easy-to-use software tool which increases the true positive variant call rate in targeted resequencing data. It specifically reduces errors related to PCR-based enrichment of targeted regions.

  9. Passivity-based design of robust passive damping for LCL-filtered voltage source converters

    DEFF Research Database (Denmark)

    Wang, Xiongfei; Blaabjerg, Frede; Loh, Poh Chiang

    2015-01-01

    Passive damping is proven as a robust stabilizing technique for LCL-filtered voltage source converters. However, conventional design methods of passive dampers are based on the passive components only, while the inherent damping effect of time delay in the digital control system is overlooked....... In this paper, a frequency-domain passivity-based design approach is proposed, where the passive dampers are designed to eliminate the negative real part of the converter output admittance with closed-loop current control, rather than shaping the LCL-filter itself. Thus, the influence of time delay...... in the current control is included, which allows a relaxed design of the passive damper with the reduced power loss and improved stability robustness against grid parameters variations. Design procedures of two commonly used passive dampers with LCL-filtered VSCs are illustrated. Experimental results validate...

  10. Adaptive Kalman Filter Applied to Vision Based Head Gesture Tracking for Playing Video Games

    Directory of Open Access Journals (Sweden)

    Mohammadreza Asghari Oskoei

    2017-11-01

    Full Text Available This paper proposes an adaptive Kalman filter (AKF to improve the performance of a vision-based human machine interface (HMI applied to a video game. The HMI identifies head gestures and decodes them into corresponding commands. Face detection and feature tracking algorithms are used to detect optical flow produced by head gestures. Such approaches often fail due to changes in head posture, occlusion and varying illumination. The adaptive Kalman filter is applied to estimate motion information and reduce the effect of missing frames in a real-time application. Failure in head gesture tracking eventually leads to malfunctioning game control, reducing the scores achieved, so the performance of the proposed vision-based HMI is examined using a game scoring mechanism. The experimental results show that the proposed interface has a good response time, and the adaptive Kalman filter improves the game scores by ten percent.

  11. Simulation and Hardware Implementation of Shunt Active Power Filter Based on Synchronous Reference Frame Theory

    Directory of Open Access Journals (Sweden)

    Karthikrjan Senthilnathan

    2018-02-01

    Full Text Available This paper describes about the Hybrid Shunt Active Power Filter (HSAPF for the elimination of the current harmonics in the line side of the three phase three wire systems. The Active Power Filter is based on the Voltage Source Converter (VSC topology. The control strategy for the converter is based on Synchronous Reference Frame (SRF theory. The compensation of harmonics is done by the APF which is connected in the shunt configuration to the system. The Shunt APF has the better compensation of current harmonics. The design and implementation of Shunt active power filter is done by MATLAB/Simulink. The real time implementation by using the ATMEGA 8 Microcontroller. The Simulation and Hardware results shows that the current harmonics are eliminated in the system

  12. Design and evaluation of a filter-based chairside amalgam separation system

    Energy Technology Data Exchange (ETDEWEB)

    Stone, Mark E. [Naval Institute for Dental and Biomedical Research, 310A B Street, Great Lakes, Illinois 60088 (United States)], E-mail: mark.stone@yahoo.com; Cohen, Mark E.; Berry, Denise L.; Ragain, James C. [Naval Institute for Dental and Biomedical Research, 310A B Street, Great Lakes, Illinois 60088 (United States)

    2008-06-15

    This study evaluated the ability of a chairside filtration system to remove particulate-based mercury (Hg) from dental-unit wastewater. Prototypes of the chairside filtration system were designed and fabricated using reusable filter chambers with disposable filter elements. The system was installed in five dental operatories utilizing filter elements with nominal pore sizes of 50{mu}m, 15{mu}m, 1{mu}m, 0.5{mu}m, or with no system installed (control). Daily chairside wastewater samples were collected on ten consecutive days from each room and brought to the laboratory for processing. After processing the wastewater samples, Hg concentrations were determined with cold vapor atomic absorption spectrometry (USEPA method 7470A). Filter systems were exchanged after ten samples were collected so that all five of the configurations were evaluated in each room (with assignment order balanced by a Latin Square). The numbers of surfaces of amalgam placed and removed per day were tracked in each room. In part two, new filter systems with the 0.5{mu}m filter elements were installed in the five dental operatories and vacuum levels at the high-velocity evacuation cannula tip were measured with a vacuum gauge. In part three of the study, the chairside filtration system utilizing 0.5{mu}m and 15{mu}m filter elements was evaluated utilizing the ISO 11143 testing protocol, a laboratory test of amalgam separator efficiency utilizing amalgam samples of known particle size distribution. Mean Hg per chair per day (no filter installed) was 1087.38mg (SD = 993.92mg). Mean Hg per chair per day for the 50{mu}m, 15{mu}m, 1{mu}m, 0.5{mu}m filter configurations was 79.13mg (SD = 71.40mg), 23.55mg (SD = 23.25mg), 17.68mg (SD = 17.35mg), and 4.25mg (SD = 6.35mg), respectively (n = 50 for all groups). Calculated removal efficiencies from the clinical samples were 92.7%, 97.8%, 98.4%, and 99.6%, respectively. ANCOVA on data from the four filter groups, with amalgam-surfaces-removed included as a

  13. Gravity Matching Aided Inertial Navigation Technique Based on Marginal Robust Unscented Kalman Filter

    Directory of Open Access Journals (Sweden)

    Ming Liu

    2015-01-01

    Full Text Available This paper is concerned with the topic of gravity matching aided inertial navigation technology using Kalman filter. The dynamic state space model for Kalman filter is constructed as follows: the error equation of the inertial navigation system is employed as the process equation while the local gravity model based on 9-point surface interpolation is employed as the observation equation. The unscented Kalman filter is employed to address the nonlinearity of the observation equation. The filter is refined in two ways as follows. The marginalization technique is employed to explore the conditionally linear substructure to reduce the computational load; specifically, the number of the needed sigma points is reduced from 15 to 5 after this technique is used. A robust technique based on Chi-square test is employed to make the filter insensitive to the uncertainties in the above constructed observation model. Numerical simulation is carried out, and the efficacy of the proposed method is validated by the simulation results.

  14. A SLAM based on auxiliary marginalised particle filter and differential evolution

    Science.gov (United States)

    Havangi, R.; Nekoui, M. A.; Teshnehlab, M.; Taghirad, H. D.

    2014-09-01

    FastSLAM is a framework for simultaneous localisation and mapping (SLAM) using a Rao-Blackwellised particle filter. In FastSLAM, particle filter is used for the robot pose (position and orientation) estimation, and parametric filter (i.e. EKF and UKF) is used for the feature location's estimation. However, in the long term, FastSLAM is an inconsistent algorithm. In this paper, a new approach to SLAM based on hybrid auxiliary marginalised particle filter and differential evolution (DE) is proposed. In the proposed algorithm, the robot pose is estimated based on auxiliary marginal particle filter that operates directly on the marginal distribution, and hence avoids performing importance sampling on a space of growing dimension. In addition, static map is considered as a set of parameters that are learned using DE. Compared to other algorithms, the proposed algorithm can improve consistency for longer time periods and also, improve the estimation accuracy. Simulations and experimental results indicate that the proposed algorithm is effective.

  15. RB Particle Filter Time Synchronization Algorithm Based on the DPM Model.

    Science.gov (United States)

    Guo, Chunsheng; Shen, Jia; Sun, Yao; Ying, Na

    2015-09-03

    Time synchronization is essential for node localization, target tracking, data fusion, and various other Wireless Sensor Network (WSN) applications. To improve the estimation accuracy of continuous clock offset and skew of mobile nodes in WSNs, we propose a novel time synchronization algorithm, the Rao-Blackwellised (RB) particle filter time synchronization algorithm based on the Dirichlet process mixture (DPM) model. In a state-space equation with a linear substructure, state variables are divided into linear and non-linear variables by the RB particle filter algorithm. These two variables can be estimated using Kalman filter and particle filter, respectively, which improves the computational efficiency more so than if only the particle filter was used. In addition, the DPM model is used to describe the distribution of non-deterministic delays and to automatically adjust the number of Gaussian mixture model components based on the observational data. This improves the estimation accuracy of clock offset and skew, which allows achieving the time synchronization. The time synchronization performance of this algorithm is also validated by computer simulations and experimental measurements. The results show that the proposed algorithm has a higher time synchronization precision than traditional time synchronization algorithms.

  16. A Simple Differential Mode EMI Suppressor for the LLCL-Filter-Based Single-Phase Grid-Tied Transformerless Inverter

    DEFF Research Database (Denmark)

    Ji, Junhao; Wu, Weimin; He, Yuanbin

    2015-01-01

    The single-phase power converter topologies evolving of photovoltaic applications are still including passive filters, like the LCLor LLCL-filter. Compared with the LCL-filter, the total inductance of the LLCL-filter can be reduced a lot. However, due to the resonant inductor in series...... with the bypass capacitor, the differential mode (DM) electromagnetic interference (EMI) noise attenuation of an LLCL-filter-based grid-tied inverter declines. Conventionally, a capacitor was inserted in parallel with the LC resonant circuit branch of the LLCL-filter to suppress the DM EMI noise. In order...... to achieve a small value of capacitor as well as to minimize the additional reactive power, a novel simple DM EMI suppressor for the LLCL-filter-based system is proposed. The characters of two kinds of DM EMI suppressor are analyzed and compared in detail. Simulations and experiments on a 0.5-kW 110-V/50-Hz...

  17. Real-time noise reduction for Mössbauer spectroscopy through online implementation of a modified Kalman filter

    Energy Technology Data Exchange (ETDEWEB)

    Abrecht, David G., E-mail: david.abrecht@pnnl.gov [National Security Directorate, Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352 (United States); Schwantes, Jon M. [National Security Directorate, Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352 (United States); Kukkadapu, Ravi K. [Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352 (United States); McDonald, Benjamin S.; Eiden, Gregory C.; Sweet, Lucas E. [National Security Directorate, Pacific Northwest National Laboratory, 902 Battelle Blvd., Richland, WA 99352 (United States)

    2015-02-11

    Spectrum-processing software that incorporates a Gaussian smoothing kernel within the statistics of first-order Kalman filtration has been developed to provide cross-channel spectral noise reduction for increased real-time signal-to-noise ratios for Mössbauer spectroscopy. The filter was optimized for the breadth of the Gaussian using the Mössbauer spectrum of natural iron foil, and comparisons among the peak broadening, signal-to-noise ratios, and shifts in the calculated hyperfine parameters are presented. The results of optimization give a maximum improvement in the signal-to-noise ratio of 51.1% over the unfiltered spectrum at a Gaussian breadth of 27 channels, or 2.5% of the total spectrum width. The full-width half-maximum of the spectrum peaks showed an increase of 19.6% at this optimum point, indicating a relatively weak increase in the peak broadening relative to the signal enhancement, leading to an overall increase in the observable signal. Calculations of the hyperfine parameters showed that no statistically significant deviations were introduced from the application of the filter, confirming the utility of this filter for spectroscopy applications.

  18. Architecture for knowledge-based and federated search of online clinical evidence.

    Science.gov (United States)

    Coiera, Enrico; Walther, Martin; Nguyen, Ken; Lovell, Nigel H

    2005-10-24

    It is increasingly difficult for clinicians to keep up-to-date with the rapidly growing biomedical literature. Online evidence retrieval methods are now seen as a core tool to support evidence-based health practice. However, standard search engine technology is not designed to manage the many different types of evidence sources that are available or to handle the very different information needs of various clinical groups, who often work in widely different settings. The objectives of this paper are (1) to describe the design considerations and system architecture of a wrapper-mediator approach to federate search system design, including the use of knowledge-based, meta-search filters, and (2) to analyze the implications of system design choices on performance measurements. A trial was performed to evaluate the technical performance of a federated evidence retrieval system, which provided access to eight distinct online resources, including e-journals, PubMed, and electronic guidelines. The Quick Clinical system architecture utilized a universal query language to reformulate queries internally and utilized meta-search filters to optimize search strategies across resources. We recruited 227 family physicians from across Australia who used the system to retrieve evidence in a routine clinical setting over a 4-week period. The total search time for a query was recorded, along with the duration of individual queries sent to different online resources. Clinicians performed 1662 searches over the trial. The average search duration was 4.9 +/- 3.2 s (N = 1662 searches). Mean search duration to the individual sources was between 0.05 s and 4.55 s. Average system time (ie, system overhead) was 0.12 s. The relatively small system overhead compared to the average time it takes to perform a search for an individual source shows that the system achieves a good trade-off between performance and reliability. Furthermore, despite the additional effort required to incorporate the

  19. Construction and Experimental Implementation of a Model-Based Inverse Filter to Attenuate Hysteresis in Ferroelectric Transducers

    National Research Council Canada - National Science Library

    Hatch, Andrew G; Smith, Ralph C; De, Tathagata; Salapaka, Murti V

    2005-01-01

    .... In this paper, we illustrate the construction of inverse filters, based on homogenized energy models, which can be used to approximately linearize the piezoceramic transducer behavior for linear...

  20. Twitter-Based Detection of Illegal Online Sale of Prescription Opioid.

    Science.gov (United States)

    Mackey, Tim K; Kalyanam, Janani; Katsuki, Takeo; Lanckriet, Gert

    2017-12-01

    To deploy a methodology accurately identifying tweets marketing the illegal online sale of controlled substances. We first collected tweets from the Twitter public application program interface stream filtered for prescription opioid keywords. We then used unsupervised machine learning (specifically, topic modeling) to identify topics associated with illegal online marketing and sales. Finally, we conducted Web forensic analyses to characterize different types of online vendors. We analyzed 619 937 tweets containing the keywords codeine, Percocet, fentanyl, Vicodin, Oxycontin, oxycodone, and hydrocodone over a 5-month period from June to November 2015. A total of 1778 tweets (marketing the sale of controlled substances online; 90% had imbedded hyperlinks, but only 46 were "live" at the time of the evaluation. Seven distinct URLs linked to Web sites marketing or illegally selling controlled substances online. Our methodology can identify illegal online sale of prescription opioids from large volumes of tweets. Our results indicate that controlled substances are trafficked online via different strategies and vendors. Public Health Implications. Our methodology can be used to identify illegal online sellers in criminal violation of the Ryan Haight Online Pharmacy Consumer Protection Act.

  1. A online credit evaluation method based on AHP and SPA

    Science.gov (United States)

    Xu, Yingtao; Zhang, Ying

    2009-07-01

    Online credit evaluation is the foundation for the establishment of trust and for the management of risk between buyers and sellers in e-commerce. In this paper, a new credit evaluation method based on the analytic hierarchy process (AHP) and the set pair analysis (SPA) is presented to determine the credibility of the electronic commerce participants. It solves some of the drawbacks found in classical credit evaluation methods and broadens the scope of current approaches. Both qualitative and quantitative indicators are considered in the proposed method, then a overall credit score is achieved from the optimal perspective. In the end, a case analysis of China Garment Network is provided for illustrative purposes.

  2. An Online Banking System Based on Quantum Cryptography Communication

    Science.gov (United States)

    Zhou, Ri-gui; Li, Wei; Huan, Tian-tian; Shen, Chen-yi; Li, Hai-sheng

    2014-07-01

    In this paper, an online banking system has been built. Based on quantum cryptography communication, this system is proved unconditional secure. Two sets of GHZ states are applied, which can ensure the safety of purchase and payment, respectively. In another word, three trading participants in each triplet state group form an interdependent and interactive relationship. In the meantime, trading authorization and blind signature is introduced by means of controllable quantum teleportation. Thus, an effective monitor is practiced on the premise that the privacy of trading partners is guaranteed. If there is a dispute or deceptive behavior, the system will find out the deceiver immediately according to the relationship mentioned above.

  3. Design and FPGA Implementation of Variable Cutoff Frequency Filter based on Continuously Variable Fractional Delay Structure and Interpolation Technique

    Directory of Open Access Journals (Sweden)

    Sumedh Dhabu

    2015-09-01

    Full Text Available This paper presents the design and FPGA implementation of interpolated continuously variable fractional delay structure based filter (ICVFD filter with fine control over the cutoff frequency. In the ICVFD filter, each unit delay of the prototype lowpass filter is replaced by a continuously variable fractional delay (CVFD element proposed in this paper. The CVFD element requires the same number of multiplications as that of the second-order fractional delay structure used in the existing fractional delay structure based variable filter (FDS based filter, however it provides fractional delays corresponding to the higher-order fractional delay structures. Hence, the proposed ICVFD filter provides wider cutoff frequency range compared to the FDS based filter. The ICVFD filter is also capable of providing variable bandpass and highpass responses. We use two-stage approach for the FPGA implementation of the ICVFD filter. First, we use pipelining stages to shorten the critical path and improve the operating frequency. Then, we make use of specific hardware resource, i.e. RAM-based Shift Register (SRL to further improve the operating frequency and resource usage.

  4. A neural network-based optimal spatial filter design method for motor imagery classification.

    Directory of Open Access Journals (Sweden)

    Ayhan Yuksel

    Full Text Available In this study, a novel spatial filter design method is introduced. Spatial filtering is an important processing step for feature extraction in motor imagery-based brain-computer interfaces. This paper introduces a new motor imagery signal classification method combined with spatial filter optimization. We simultaneously train the spatial filter and the classifier using a neural network approach. The proposed spatial filter network (SFN is composed of two layers: a spatial filtering layer and a classifier layer. These two layers are linked to each other with non-linear mapping functions. The proposed method addresses two shortcomings of the common spatial patterns (CSP algorithm. First, CSP aims to maximize the between-classes variance while ignoring the minimization of within-classes variances. Consequently, the features obtained using the CSP method may have large within-classes variances. Second, the maximizing optimization function of CSP increases the classification accuracy indirectly because an independent classifier is used after the CSP method. With SFN, we aimed to maximize the between-classes variance while minimizing within-classes variances and simultaneously optimizing the spatial filter and the classifier. To classify motor imagery EEG signals, we modified the well-known feed-forward structure and derived forward and backward equations that correspond to the proposed structure. We tested our algorithm on simple toy data. Then, we compared the SFN with conventional CSP and its multi-class version, called one-versus-rest CSP, on two data sets from BCI competition III. The evaluation results demonstrate that SFN is a good alternative for classifying motor imagery EEG signals with increased classification accuracy.

  5. Information filtering via a scaling-based function.

    Science.gov (United States)

    Qiu, Tian; Zhang, Zi-Ke; Chen, Guang

    2013-01-01

    Finding a universal description of the algorithm optimization is one of the key challenges in personalized recommendation. In this article, for the first time, we introduce a scaling-based algorithm (SCL) independent of recommendation list length based on a hybrid algorithm of heat conduction and mass diffusion, by finding out the scaling function for the tunable parameter and object average degree. The optimal value of the tunable parameter can be abstracted from the scaling function, which is heterogeneous for the individual object. Experimental results obtained from three real datasets, Netflix, MovieLens and RYM, show that the SCL is highly accurate in recommendation. More importantly, compared with a number of excellent algorithms, including the mass diffusion method, the original hybrid method, and even an improved version of the hybrid method, the SCL algorithm remarkably promotes the personalized recommendation in three other aspects: solving the accuracy-diversity dilemma, presenting a high novelty, and solving the key challenge of cold start problem.

  6. Information filtering via a scaling-based function.

    Directory of Open Access Journals (Sweden)

    Tian Qiu

    Full Text Available Finding a universal description of the algorithm optimization is one of the key challenges in personalized recommendation. In this article, for the first time, we introduce a scaling-based algorithm (SCL independent of recommendation list length based on a hybrid algorithm of heat conduction and mass diffusion, by finding out the scaling function for the tunable parameter and object average degree. The optimal value of the tunable parameter can be abstracted from the scaling function, which is heterogeneous for the individual object. Experimental results obtained from three real datasets, Netflix, MovieLens and RYM, show that the SCL is highly accurate in recommendation. More importantly, compared with a number of excellent algorithms, including the mass diffusion method, the original hybrid method, and even an improved version of the hybrid method, the SCL algorithm remarkably promotes the personalized recommendation in three other aspects: solving the accuracy-diversity dilemma, presenting a high novelty, and solving the key challenge of cold start problem.

  7. A Method for Microalgae Proteomics Analysis Based on Modified Filter-Aided Sample Preparation.

    Science.gov (United States)

    Li, Song; Cao, Xupeng; Wang, Yan; Zhu, Zhen; Zhang, Haowei; Xue, Song; Tian, Jing

    2017-11-01

    With the fast development of microalgal biofuel researches, the proteomics studies of microalgae increased quickly. A filter-aided sample preparation (FASP) method is widely used proteomics sample preparation method since 2009. Here, a method of microalgae proteomics analysis based on modified filter-aided sample preparation (mFASP) was described to meet the characteristics of microalgae cells and eliminate the error caused by over-alkylation. Using Chlamydomonas reinhardtii as the model, the prepared sample was tested by standard LC-MS/MS and compared with the previous reports. The results showed mFASP is suitable for most of occasions of microalgae proteomics studies.

  8. Cantilever-based micro-particle filter with simultaneous single particle detection

    DEFF Research Database (Denmark)

    Noeth, Nadine-Nicole; Keller, Stephan Sylvest; Boisen, Anja

    2011-01-01

    Currently, separation of whole blood samples on lab-on-a-chip systems is achieved via filters followed by analysis of the filtered matter such as counting of blood cells. Here, a micro-chip based on cantilever technology is developed, which enables simultaneous filtration and counting of micro-particles...... from a liquid. A hole-array is integrated into a micro-cantilever, which is inserted into a microfluidic channel perpendicular to the flow. A metal pad at the apex of the cantilever enables an optical read-out of the deflection of the cantilever. When a micro-particle is too large to pass a hole...

  9. A NEW METHOD OF CHANNEL FRICTION INVERSION BASED ON KALMAN FILTER WITH UNKNOWN PARAMETER VECTOR

    Institute of Scientific and Technical Information of China (English)

    CHENG Wei-ping; MAO Gen-hai; LIU Guo-hua

    2005-01-01

    Channel friction is an important parameter in hydraulic analysis.A channel friction parameter inversion method based on Kalman Filter with unknown parameter vector is proposed.Numerical simulations indicate that when the number of monitoring stations exceeds a critical value, the solution is hardly affected.In addition, Kalman Filter with unknown parameter vector is effective only at unsteady state.For the nonlinear equations, computations of sensitivity matrices are time-costly.Two simplified measures can reduce computing time, but not influence the results.One is to reduce sensitivity matrix analysis time, the other is to substitute for sensitivity matrix.

  10. Word2vec and dictionary based approach for uyghur text filtering

    Science.gov (United States)

    Tohti, Turdi; Zhao, Yunxing; Musajan, Winira

    2017-08-01

    With emerging of deep learning, the expression of words in computer has made major breakthroughs and the effect of text processing based on word vector has also been significantly improved. This paper maps all patterns into a more abstract vector space by Uyghur-Chinese dictionary and deep learning tool Word2vec, at first. Secondly, a similar pattern is found according the characteristics of the original pattern. Finally, texts are filtered using Wu-Manber algorithm. Experiments show that this method can get obvious filtering accuracy and recall of Uyghur text information improved.

  11. Filtering Airborne LIDAR Data by AN Improved Morphological Method Based on Multi-Gradient Analysis

    Science.gov (United States)

    Li, Y.

    2013-05-01

    The technology of airborne Light Detection And Ranging (LIDAR) is capable of acquiring dense and accurate 3D geospatial data. Although many related efforts have been made by a lot of researchers in the last few years, LIDAR data filtering is still a challenging task, especially for area with high relief or hybrid geographic features. In order to address the bare-ground extraction from LIDAR point clouds of complex landscapes, a novel morphological filtering algorithm is proposed based on multi-gradient analysis in terms of the characteristic of LIDAR data distribution in this paper. Firstly, point clouds are organized by an index mesh. Then, the multigradient of each point is calculated using the morphological method. And, objects are removed gradually by choosing some points to carry on an improved opening operation constrained by multi-gradient iteratively. 15 sample data provided by ISPRS Working Group III/3 are employed to test the filtering algorithm proposed. These sample data include those environments that may lead to filtering difficulty. Experimental results show that filtering algorithm proposed by this paper is of high adaptability to various scenes including urban and rural areas. Omission error, commission error and total error can be simultaneously controlled in a relatively small interval. This algorithm can efficiently remove object points while preserves ground points to a great degree.

  12. Wide Bandpass and Narrow Bandstop Microstrip Filters based on Hilbert fractal geometry: design and simulation results.

    Directory of Open Access Journals (Sweden)

    Yaqeen S Mezaal

    Full Text Available This paper presents new Wide Bandpass Filter (WBPF and Narrow Bandstop Filter (NBSF incorporating two microstrip resonators, each resonator is based on 2nd iteration of Hilbert fractal geometry. The type of filter as pass or reject band has been adjusted by coupling gap parameter (d between Hilbert resonators using a substrate with a dielectric constant of 10.8 and a thickness of 1.27 mm. Numerical simulation results as well as a parametric study of d parameter on filter type and frequency responses are presented and studied. WBPF has designed at resonant frequencies of 2 and 2.2 GHz with a bandwidth of 0.52 GHz, -28 dB return loss and -0.125 dB insertion loss while NBSF has designed for electrical specifications of 2.37 GHz center frequency, 20 MHz rejection bandwidth, -0.1873 dB return loss and 13.746 dB insertion loss. The proposed technique offers a new alternative to construct low-cost high-performance filter devices, suitable for a wide range of wireless communication systems.

  13. Area efficient decimation filter based on merged delay transformation for wireless applications

    International Nuclear Information System (INIS)

    Rashid, U.; Siddiq, F.; Muhammad, T.; Jamal, H.

    2013-01-01

    Expected by 2014 is the 4G standard for cellular wireless communications, which will improve bandwidth, connectivity and roaming for mobile and stationary devices, 4G and other wireless systems are currently hot topics of research and development in the communication field. In wireless technologies like Global System for Mobile (GSM), Digital Enhanced Cordless Telecommunications (DECT) and Wi-Fi, decimation filters are essential part of transceivers being used. This paper describes a decimation filter which is efficient in terms of both the power consumption and the area used. The architecture is based upon Merged Delay Transformation (MDT). The existing Merged Delay Transformed Infinite Impulse Response (IIR) architecture is power efficient but requires larger area. The proposed and existing filters were implemented on Field-Programmable Gate Array (FPGA). The computational cost of the proposed filter is reduced to (3N/2 + 1) and M-1 times reduction in the number of multipliers in comparison to the existing FIR filter is achieved. The power consumption and speed remain nearly the same. (author)

  14. Quantum neural network-based EEG filtering for a brain-computer interface.

    Science.gov (United States)

    Gandhi, Vaibhav; Prasad, Girijesh; Coyle, Damien; Behera, Laxmidhar; McGinnity, Thomas Martin

    2014-02-01

    A novel neural information processing architecture inspired by quantum mechanics and incorporating the well-known Schrodinger wave equation is proposed in this paper. The proposed architecture referred to as recurrent quantum neural network (RQNN) can characterize a nonstationary stochastic signal as time-varying wave packets. A robust unsupervised learning algorithm enables the RQNN to effectively capture the statistical behavior of the input signal and facilitates the estimation of signal embedded in noise with unknown characteristics. The results from a number of benchmark tests show that simple signals such as dc, staircase dc, and sinusoidal signals embedded within high noise can be accurately filtered and particle swarm optimization can be employed to select model parameters. The RQNN filtering procedure is applied in a two-class motor imagery-based brain-computer interface where the objective was to filter electroencephalogram (EEG) signals before feature extraction and classification to increase signal separability. A two-step inner-outer fivefold cross-validation approach is utilized to select the algorithm parameters subject-specifically for nine subjects. It is shown that the subject-specific RQNN EEG filtering significantly improves brain-computer interface performance compared to using only the raw EEG or Savitzky-Golay filtered EEG across multiple sessions.

  15. Model-Based Collaborative Filtering Analysis of Student Response Data: Machine-Learning Item Response Theory

    Science.gov (United States)

    Bergner, Yoav; Droschler, Stefan; Kortemeyer, Gerd; Rayyan, Saif; Seaton, Daniel; Pritchard, David E.

    2012-01-01

    We apply collaborative filtering (CF) to dichotomously scored student response data (right, wrong, or no interaction), finding optimal parameters for each student and item based on cross-validated prediction accuracy. The approach is naturally suited to comparing different models, both unidimensional and multidimensional in ability, including a…

  16. Development and evaluation of a plant-based air filter system for ...

    African Journals Online (AJOL)

    We investigated a novel plant-based air filter system for bacterial growth control. The volatile components released from the experimental plant (Cupressus macrocarpa) were used as the basis of the bacterial growth control and inhibition. We monitored the effect of light on the gas exhausted from the system, and we found ...

  17. Kalman filter for speech enhancement in cocktail party scenarios using a codebook-based approach

    DEFF Research Database (Denmark)

    Kavalekalam, Mathew Shaji; Christensen, Mads Græsbøll; Gran, Fredrik

    2016-01-01

    Enhancement of speech in non-stationary background noise is a challenging task, and conventional single channel speech enhancement algorithms have not been able to improve the speech intelligibility in such scenarios. The work proposed in this paper investigates a single channel Kalman filter based...... trained codebook over a generic speech codebook in relation to the performance of the speech enhancement system....

  18. The impact of sensor errors and building structures on particle filter-based inertial positioning

    DEFF Research Database (Denmark)

    Toftkjær, Thomas; Kjærgaard, Mikkel Baun

    2012-01-01

    Positioning systems that do not depend on in-building infrastructures are critical for enabling a range of applications within pervasive computing. Particle filter-based inertial positioning promises infrastructure-less positioning, but previous research has not provided an understanding of how t...

  19. Vapour HF release of airgap-based UV-visible optical filters

    NARCIS (Netherlands)

    Ghaderi, M.; Ayerden, N.P.; De Graaf, G.; Wolffenbuttel, R.F.

    2015-01-01

    The design and CMOS-compatible fabrication of airgap-based optical filters in a surface micromachining process with sacrificial release using thevapour phase is presented. An airgap-dielectric layer combination offers a higher refractive index contrast, as compared to the conventional

  20. Development and evaluation of a plant-based air filter system for ...

    African Journals Online (AJOL)

    Y. Choi

    2013-04-17

    Apr 17, 2013 ... plant based filter system on bacterial growth in aqueous media, the compressed air was fed to the system at a rate of 200 mL/min, and the exhaust gas from the system was supplied to a bacterial culture. In this experiment, we attempted to verify the inhibition activity of the gas on bacterial growth in aqueous ...

  1. Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

    Science.gov (United States)

    Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

    2018-02-06

    This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

  2. Low-cost domestic water filter: The case for a process-based ...

    African Journals Online (AJOL)

    Low-cost domestic water filter: The case for a process-based approach for the development of a rural technology product. ... Since the project aims at technology transfer to the rural poor for generating rural livelihoods, appropriate financial models and the general sustainability issues for such an activity are briefly discussed ...

  3. Analysis of the Passive Damping Losses in LCL-Filter-Based Grid Converters

    DEFF Research Database (Denmark)

    Alzola, Rafael Pena; Liserre, Marco; Blaabjerg, Frede

    2013-01-01

    Passive damping is the most adopted method to guarantee the stability of LCL-filter-based grid converters. The method is simple and, if the switching and sampling frequencies are sufficiently high, the damping losses are negligible. This letter proposes the tuning of different passive damping...

  4. Image denoising using new pixon representation based on fuzzy filtering and partial differential equations

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan; Nikpour, Mohsen

    2012-01-01

    In this paper, we have proposed two extensions to pixon-based image modeling. The first one is using bicubic interpolation instead of bilinear interpolation and the second one is using fuzzy filtering method, aiming to improve the quality of the pixonal image. Finally, partial differential...

  5. Tunable polarisation-maintaining filter based on liquid crystal photonic bandgap fibre

    DEFF Research Database (Denmark)

    Scolari, Lara; Olausson, Christina Bjarnal Thulin; Weirich, Johannes

    2008-01-01

    A tunable and polarisation-maintaining all-in-fibre filter based on a liquid crystal photonic bandgap fibre is demonstrated. Its polarisation extinction ratio reaches 14 dB at 1550 nm wavelength. Its spectral tunability range spans over 250 nm in the temperature range 30–70°C. The measured...

  6. Widely tunable microwave photonic notch filter based on slow and fast light effects

    DEFF Research Database (Denmark)

    Xue, Weiqi; Sales, Salvador; Mørk, Jesper

    2009-01-01

    A continuously tunable microwave photonic notch filter at around 30 GHz is experimentally demonstrated and 100% fractional tuning over 360 range is achieved without changing the shape of the spectral response. The tuning mechanism is based on the use of slow and fast light effects in semiconducto...

  7. Si(Li) x-ray spectrometer with signal processing system based on digital filtering

    International Nuclear Information System (INIS)

    Lakatos, Tamas

    1985-01-01

    A new signal processing system is under development at ATOMKI, Debrecen, Hungary, based on digital filtering by a microprocessor. The advantages of the new method are summarized. Dead time can be decreased and the speed of signal processing can be increased. Computer simulations verified the theoretical conclusions. (D.Gy.)

  8. Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods

    Directory of Open Access Journals (Sweden)

    Anthony Hoak

    2017-03-01

    Full Text Available We develop an interactive likelihood (ILH for sequential Monte Carlo (SMC methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL and TUD-Stadtmitte using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA and classification of events, activities and relationships for multi-object trackers (CLEAR MOT. In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

  9. Design of adaptive filter amplifier in UV communication based on DSP

    Science.gov (United States)

    Lv, Zhaoshun; Wu, Hanping; Li, Junyu

    2016-10-01

    According to the problem of the weak signal at receiving end in UV communication, we design a high gain, continuously adjustable adaptive filter amplifier. Based on proposing overall technical indicators and analyzing its working principle of the signal amplifier, we use chip LMH6629MF and two chips of AD797BN to achieve three-level cascade amplification. And apply hardware of DSP TMS320VC5509A to implement digital filtering. Design and verification by Multisim, Protel 99SE and CCS, the results show that: the amplifier can realize continuously adjustable amplification from 1000 to 10000 times without distortion. Magnification error is <=%4@1000 10000. And equivalent input noise voltage of amplification circuit is <=6 nV/ √Hz @30KHz 45KHz, and realizing function of adaptive filtering. The design provides theoretical reference and technical support for the UV weak signal processing.

  10. Identification of chaotic memristor systems based on piecewise adaptive Legendre filters

    International Nuclear Information System (INIS)

    Zhao, Yibo; Zhang, Xiuzai; Xu, Jin; Guo, Yecai

    2015-01-01

    Memristor is a nonlinear device, which plays an important role in the design and implementation of chaotic systems. In order to be able to understand in-depth the complex nonlinear dynamic behaviors in chaotic memristor systems, modeling or identification of its nonlinear model is very important premise. This paper presents a chaotic memristor system identification method based on piecewise adaptive Legendre filters. The threshold decomposition is carried out for the input vector, and also the input signal subintervals via decomposition satisfy the convergence condition of the adaptive Legendre filters. Then the adaptive Legendre filter structure and adaptive weight update algorithm are derived. Final computer simulation results show the effectiveness as well as fast convergence characteristics.

  11. State and force observers based on multibody models and the indirect Kalman filter

    Science.gov (United States)

    Sanjurjo, Emilio; Dopico, Daniel; Luaces, Alberto; Naya, Miguel Ángel

    2018-06-01

    The aim of this work is to present two new methods to provide state observers by combining multibody simulations with indirect extended Kalman filters. One of the methods presented provides also input force estimation. The observers have been applied to two mechanism with four different sensor configurations, and compared to other multibody-based observers found in the literature to evaluate their behavior, namely, the unscented Kalman filter (UKF), and the indirect extended Kalman filter with simplified Jacobians (errorEKF). The new methods have some more computational cost than the errorEKF, but still much less than the UKF. Regarding their accuracy, both are better than the errorEKF. The method with input force estimation outperforms also the UKF, while the method without force estimation achieves results almost identical to those of the UKF. All the methods have been implemented as a reusable MATLAB® toolkit which has been released as Open Source in https://github.com/MBDS/mbde-matlab.

  12. Solar-blind ultraviolet band-pass filter based on metal—dielectric multilayer structures

    International Nuclear Information System (INIS)

    Wang Tian-Jiao; Xu Wei-Zong; Lu Hai; Ren Fang-Fang; Chen Dun-Jun; Zhang Rong; Zheng You-Dou

    2014-01-01

    Solar-blind ultraviolet (UV) band-pass filter has significant value in many scientific, commercial, and military applications, in which the detection of weak UV signal against a strong background of solar radiation is required. In this work, a solar-blind filter is designed based on the concept of “transparent metal”. The filter consisting of Al/SiO 2 multilayers could exhibit a high transmission in the solar-blind wavelength region and a wide stopband extending from near-ultraviolet to infrared wavelength range. The central wavelength, bandwidth, Q factor, and rejection ratio of the passband are numerically studied as a function of individual layer thickness and multilayer period. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

  13. Extinction ratio enhancement of SOA-based delayed-interference signal converter using detuned filtering

    Science.gov (United States)

    Zhang, B.; Kumar, S.; Yan, L.-S.; Willner, A. E.

    2007-12-01

    We demonstrate experimentally >3 dB extinction ratio improvement at the output of SOA-based delayed-interference signal converter (DISC) using optical off-centered filtering. Through careful modeling of the carrier and the phase dynamics, we explain in detail the origin of sub-pulses in the wavelength converted output, with an emphasis on the time-resolved frequency chirping of the output signal. Through our simulations we conclude that the sub-pulses and the main-pulses are oppositely chirped, which is also verified experimentally by analyzing the output with a chirp form analyzer. We propose and demonstrate an optical off-center filtering technique which effectively suppresses these sub-pulses. The effects of filter detuning and phase bias adjustment in the delayed-interferometer are experimentally characterized and optimized, leading to a >3 dB extinction ratio enhancement of the output signal.

  14. Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods.

    Science.gov (United States)

    Hoak, Anthony; Medeiros, Henry; Povinelli, Richard J

    2017-03-03

    We develop an interactive likelihood (ILH) for sequential Monte Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL) and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA) and classification of events, activities and relationships for multi-object trackers (CLEAR MOT)). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

  15. Alternating current line-filter based on electrochemical capacitor utilizing template-patterned graphene.

    Science.gov (United States)

    Wu, Zhenkun; Li, Liyi; Lin, Ziyin; Song, Bo; Li, Zhuo; Moon, Kyoung-Sik; Wong, Ching-Ping; Bai, Shu-Lin

    2015-06-17

    Aluminum electrolytic capacitors (AECs) are widely used for alternating current (ac) line-filtering. However, their bulky size is becoming more and more incompatible with the rapid development of portable electronics. Here we report a scalable process to fabricate miniaturized graphene-based ac line-filters on flexible substrates at room temperature. In this work, graphene oxide (GO) is reduced by patterned metal interdigits at room temperature and used directly as the electrode material. The as-fabricated device shows a phase angle of -75.4° at 120 Hz with a specific capacitance of 316 µF/cm(2) and a RC time constant of 0.35 ms. In addition, it retains 97.2% of the initial capacitance after 10000 charge/discharge cycles. These outstanding performance characteristics of our device demonstrate its promising to replace the conventional AECs for ac line filtering.

  16. Properties of predictor based on relative neighborhood graph localized FIR filters

    DEFF Research Database (Denmark)

    Sørensen, John Aasted

    1995-01-01

    A time signal prediction algorithm based on relative neighborhood graph (RNG) localized FIR filters is defined. The RNG connects two nodes, of input space dimension D, if their lune does not contain any other node. The FIR filters associated with the nodes, are used for local approximation...... of the training vectors belonging to the lunes formed by the nodes. The predictor training is carried out by iteration through 3 stages: initialization of the RNG of the training signal by vector quantization, LS estimation of the FIR filters localized in the input space by RNG nodes and adaptation of the RNG...... nodes by equalizing the LS approximation error among the lunes formed by the nodes of the RNG. The training properties of the predictor is exemplified on a burst signal and characterized by the normalized mean square error (NMSE) and the mean valence of the RNG nodes through the adaptation...

  17. A narrowband filter based on 2D 8-fold photonic quasicrystal

    Science.gov (United States)

    Ren, Jie; Sun, XiaoHong; Wang, Shuai

    2018-04-01

    In this paper, a novel structure of narrowband filter based on 2D 8-fold photonic quasicrystal (PQC) is proposed and investigated. The structure size is 8 μm × 8 μm, which promises its applications in optical integrated circuits and communication devices. Finite Element Method (FEM) has been employed to investigate the band gap of the filter. The resonance wavelength, transmission coefficient and 3 dB bandwidth are analyzed by varying the parameters of the structure. By optimizing the parameters of the filter, two design formulas of resonance wavelength are obtained. Also, for its better linearity of the resonance, the structure with line-defect has also seen a large uptake in sensor design.

  18. Two-Dimensional IIR Filter Design Using Simulated Annealing Based Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Supriya Dhabal

    2014-01-01

    Full Text Available We present a novel hybrid algorithm based on particle swarm optimization (PSO and simulated annealing (SA for the design of two-dimensional recursive digital filters. The proposed method, known as SA-PSO, integrates the global search ability of PSO with the local search ability of SA and offsets the weakness of each other. The acceptance criterion of Metropolis is included in the basic algorithm of PSO to increase the swarm’s diversity by accepting sometimes weaker solutions also. The experimental results reveal that the performance of the optimal filter designed by the proposed SA-PSO method is improved. Further, the convergence behavior as well as optimization accuracy of proposed method has been improved significantly and computational time is also reduced. In addition, the proposed SA-PSO method also produces the best optimal solution with lower mean and variance which indicates that the algorithm can be used more efficiently in realizing two-dimensional digital filters.

  19. Fault diagnosis for wind turbine planetary ring gear via a meshing resonance based filtering algorithm.

    Science.gov (United States)

    Wang, Tianyang; Chu, Fulei; Han, Qinkai

    2017-03-01

    Identifying the differences between the spectra or envelope spectra of a faulty signal and a healthy baseline signal is an efficient planetary gearbox local fault detection strategy. However, causes other than local faults can also generate the characteristic frequency of a ring gear fault; this may further affect the detection of a local fault. To address this issue, a new filtering algorithm based on the meshing resonance phenomenon is proposed. In detail, the raw signal is first decomposed into different frequency bands and levels. Then, a new meshing index and an MRgram are constructed to determine which bands belong to the meshing resonance frequency band. Furthermore, an optimal filter band is selected from this MRgram. Finally, the ring gear fault can be detected according to the envelope spectrum of the band-pass filtering result. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Comprehensive Utilization of Filter Residue from the Preparation Process of Zeolite-Based Catalysts

    Directory of Open Access Journals (Sweden)

    Shu-Qin Zheng

    2016-05-01

    Full Text Available A novel utilization method of filter residue from the preparation process of zeolite-based catalysts was investigated. Y zeolite and a fluid catalytic cracking (FCC catalyst were synthesized from filter residue. Compared to the Y zeolite synthesized by the conventional method, the Y zeolite synthesized from filter residue exhibited better thermal stability. The catalyst possessed wide-pore distribution. In addition, the pore volume, specific surface area, attrition resistance were superior to those of the reference catalyst. The yields of gasoline and light oil increased by 1.93 and 1.48 %, respectively. At the same time, the coke yield decreased by 0.41 %. The catalyst exhibited better gasoline and coke selectivity. The quality of the cracked gasoline had been improved.

  1. A cognition-based method to ease the computational load for an extended Kalman filter.

    Science.gov (United States)

    Li, Yanpeng; Li, Xiang; Deng, Bin; Wang, Hongqiang; Qin, Yuliang

    2014-12-03

    The extended Kalman filter (EKF) is the nonlinear model of a Kalman filter (KF). It is a useful parameter estimation method when the observation model and/or the state transition model is not a linear function. However, the computational requirements in EKF are a difficulty for the system. With the help of cognition-based designation and the Taylor expansion method, a novel algorithm is proposed to ease the computational load for EKF in azimuth predicting and localizing under a nonlinear observation model. When there are nonlinear functions and inverse calculations for matrices, this method makes use of the major components (according to current performance and the performance requirements) in the Taylor expansion. As a result, the computational load is greatly lowered and the performance is ensured. Simulation results show that the proposed measure will deliver filtering output with a similar precision compared to the regular EKF. At the same time, the computational load is substantially lowered.

  2. More than a filter: Feature-based attention regulates the distribution of visual working memory resources.

    Science.gov (United States)

    Dube, Blaire; Emrich, Stephen M; Al-Aidroos, Naseem

    2017-10-01

    Across 2 experiments we revisited the filter account of how feature-based attention regulates visual working memory (VWM). Originally drawing from discrete-capacity ("slot") models, the filter account proposes that attention operates like the "bouncer in the brain," preventing distracting information from being encoded so that VWM resources are reserved for relevant information. Given recent challenges to the assumptions of discrete-capacity models, we investigated whether feature-based attention plays a broader role in regulating memory. Both experiments used partial report tasks in which participants memorized the colors of circle and square stimuli, and we provided a feature-based goal by manipulating the likelihood that 1 shape would be probed over the other across a range of probabilities. By decomposing participants' responses using mixture and variable-precision models, we estimated the contributions of guesses, nontarget responses, and imprecise memory representations to their errors. Consistent with the filter account, participants were less likely to guess when the probed memory item matched the feature-based goal. Interestingly, this effect varied with goal strength, even across high probabilities where goal-matching information should always be prioritized, demonstrating strategic control over filter strength. Beyond this effect of attention on which stimuli were encoded, we also observed effects on how they were encoded: Estimates of both memory precision and nontarget errors varied continuously with feature-based attention. The results offer support for an extension to the filter account, where feature-based attention dynamically regulates the distribution of resources within working memory so that the most relevant items are encoded with the greatest precision. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  3. Bi Input-extended Kalman filter based estimation technique for speed-sensorless control of induction motors

    International Nuclear Information System (INIS)

    Barut, Murat

    2010-01-01

    This study offers a novel extended Kalman filter (EKF) based estimation technique for the solution of the on-line estimation problem related to uncertainties in the stator and rotor resistances inherent to the speed-sensorless high efficiency control of induction motors (IMs) in the wide speed range as well as extending the limited number of states and parameter estimations possible with a conventional single EKF algorithm. For this aim, the introduced estimation technique in this work utilizes a single EKF algorithm with the consecutive execution of two inputs derived from the two individual extended IM models based on the stator resistance and rotor resistance estimation, differently from the other approaches in past studies, which require two separate EKF algorithms operating in a switching or braided manner; thus, it has superiority over the previous EKF schemes in this regard. The proposed EKF based estimation technique performing the on-line estimations of the stator currents, the rotor flux, the rotor angular velocity, and the load torque involving the viscous friction term together with the rotor and stator resistance is also used in the combination with the speed-sensorless direct vector control of IM and tested with simulations under the challenging 12 scenarios generated instantaneously via step and/or linear variations of the velocity reference, the load torque, the stator resistance, and the rotor resistance in the range of high and zero speed, assuming that the measured stator phase currents and voltages are available. Even under those variations, the performance of the speed-sensorless direct vector control system established on the novel EKF based estimation technique is observed to be quite good.

  4. Bi Input-extended Kalman filter based estimation technique for speed-sensorless control of induction motors

    Energy Technology Data Exchange (ETDEWEB)

    Barut, Murat, E-mail: muratbarut27@yahoo.co [Nigde University, Department of Electrical and Electronics Engineering, 51245 Nigde (Turkey)

    2010-10-15

    This study offers a novel extended Kalman filter (EKF) based estimation technique for the solution of the on-line estimation problem related to uncertainties in the stator and rotor resistances inherent to the speed-sensorless high efficiency control of induction motors (IMs) in the wide speed range as well as extending the limited number of states and parameter estimations possible with a conventional single EKF algorithm. For this aim, the introduced estimation technique in this work utilizes a single EKF algorithm with the consecutive execution of two inputs derived from the two individual extended IM models based on the stator resistance and rotor resistance estimation, differently from the other approaches in past studies, which require two separate EKF algorithms operating in a switching or braided manner; thus, it has superiority over the previous EKF schemes in this regard. The proposed EKF based estimation technique performing the on-line estimations of the stator currents, the rotor flux, the rotor angular velocity, and the load torque involving the viscous friction term together with the rotor and stator resistance is also used in the combination with the speed-sensorless direct vector control of IM and tested with simulations under the challenging 12 scenarios generated instantaneously via step and/or linear variations of the velocity reference, the load torque, the stator resistance, and the rotor resistance in the range of high and zero speed, assuming that the measured stator phase currents and voltages are available. Even under those variations, the performance of the speed-sensorless direct vector control system established on the novel EKF based estimation technique is observed to be quite good.

  5. IMPACT OF COMPUTER BASED ONLINE ENTREPRENEURSHIP DISTANCE EDUCATION IN INDIA

    Directory of Open Access Journals (Sweden)

    Bhagwan SHREE RAM

    2012-07-01

    Full Text Available The success of Indian enterprises and professionals in the computer and information technology (CIT domain during the twenty year has been spectacular. Entrepreneurs, bureaucrats and technocrats are now advancing views about how India can ride CIT bandwagon and leapfrog into a knowledge-based economy in the area of entrepreneurship distance education on-line. Isolated instances of remotely located villagers sending and receiving email messages, effective application of mobile communications and surfing the Internet are being promoted as examples of how the nation can achieve this transformation, while vanquishing socio-economic challenges such as illiteracy, high growth of population, poverty, and the digital divide along the way. Likewise, even while a small fraction of the urban population in India has access to computers and the Internet, e-governance is being projected as the way of the future. There is no dearth of fascinating stories about CIT enabled changes, yet there is little discussion about whether such changes are effective and sustainable in the absence of the basic infrastructure that is accessible to the citizens of more advanced economies. When used appropriately, different CITs are said to help expand access to entrepreneurship distance education, strengthen the relevance of education to the increasingly digital workplace, and raise technical and managerial educational quality by, among others, helping make teaching and learning into an engaging, active process connected to real life. This research paper investigates on the impact of computer based online entrepreneurship distance education in India.

  6. File-based data flow in the CMS Filter Farm

    Science.gov (United States)

    Andre, J.-M.; Andronidis, A.; Bawej, T.; Behrens, U.; Branson, J.; Chaze, O.; Cittolin, S.; Darlea, G.-L.; Deldicque, C.; Dobson, M.; Dupont, A.; Erhan, S.; Gigi, D.; Glege, F.; Gomez-Ceballos, G.; Hegeman, J.; Holzner, A.; Jimenez-Estupiñán, R.; Masetti, L.; Meijers, F.; Meschi, E.; Mommsen, R. K.; Morovic, S.; Nunez-Barranco-Fernandez, C.; O'Dell, V.; Orsini, L.; Paus, C.; Petrucci, A.; Pieri, M.; Racz, A.; Roberts, P.; Sakulin, H.; Schwick, C.; Stieger, B.; Sumorok, K.; Veverka, J.; Zaza, S.; Zejdl, P.

    2015-12-01

    During the LHC Long Shutdown 1, the CMS Data Acquisition system underwent a partial redesign to replace obsolete network equipment, use more homogeneous switching technologies, and prepare the ground for future upgrades of the detector front-ends. The software and hardware infrastructure to provide input, execute the High Level Trigger (HLT) algorithms and deal with output data transport and storage has also been redesigned to be completely file- based. This approach provides additional decoupling between the HLT algorithms and the input and output data flow. All the metadata needed for bookkeeping of the data flow and the HLT process lifetimes are also generated in the form of small “documents” using the JSON encoding, by either services in the flow of the HLT execution (for rates etc.) or watchdog processes. These “files” can remain memory-resident or be written to disk if they are to be used in another part of the system (e.g. for aggregation of output data). We discuss how this redesign improves the robustness and flexibility of the CMS DAQ and the performance of the system currently being commissioned for the LHC Run 2.

  7. File-Based Data Flow in the CMS Filter Farm

    Energy Technology Data Exchange (ETDEWEB)

    Andre, J.M.; et al.

    2015-12-23

    During the LHC Long Shutdown 1, the CMS Data Acquisition system underwent a partial redesign to replace obsolete network equipment, use more homogeneous switching technologies, and prepare the ground for future upgrades of the detector front-ends. The software and hardware infrastructure to provide input, execute the High Level Trigger (HLT) algorithms and deal with output data transport and storage has also been redesigned to be completely file- based. This approach provides additional decoupling between the HLT algorithms and the input and output data flow. All the metadata needed for bookkeeping of the data flow and the HLT process lifetimes are also generated in the form of small “documents” using the JSON encoding, by either services in the flow of the HLT execution (for rates etc.) or watchdog processes. These “files” can remain memory-resident or be written to disk if they are to be used in another part of the system (e.g. for aggregation of output data). We discuss how this redesign improves the robustness and flexibility of the CMS DAQ and the performance of the system currently being commissioned for the LHC Run 2.

  8. A hybrid damping method for LLCL-filter based grid-tied inverter with a digital filter and an RC parallel passive damper

    DEFF Research Database (Denmark)

    Wu, Weimin; Lin, Zhe; Sun, Yunjie

    2013-01-01

    Grid-tied inverters have been widely used to inject the renewable energies into the distributed power generation systems. However, a large variation of the grid impedance challenges the stability of the high-order power filter based grid-tied inverter. Many passive and active damping methods have...... been proposed to overcome this issue. Recently, a composite passive damping method for a high-order power filter based grid-tied inverter with an RC parallel damper and an RL series damper was presented to eliminate this problem, but at the cost of more material and power losses. In this paper...

  9. Applying Case-Based Method in Designing Self-Directed Online Instruction: A Formative Research Study

    Science.gov (United States)

    Luo, Heng; Koszalka, Tiffany A.; Arnone, Marilyn P.; Choi, Ikseon

    2018-01-01

    This study investigated the case-based method (CBM) instructional-design theory and its application in designing self-directed online instruction. The purpose of this study was to validate and refine the theory for a self-directed online instruction context. Guided by formative research methodology, this study first developed an online tutorial…

  10. A method of incident angle estimation for high resolution spectral recovery in filter-array-based spectrometers

    Science.gov (United States)

    Kim, Cheolsun; Lee, Woong-Bi; Ju, Gun Wu; Cho, Jeonghoon; Kim, Seongmin; Oh, Jinkyung; Lim, Dongsung; Lee, Yong Tak; Lee, Heung-No

    2017-02-01

    In recent years, there has been an increasing interest in miniature spectrometers for research and development. Especially, filter-array-based spectrometers have advantages of low cost and portability, and can be applied in various fields such as biology, chemistry and food industry. Miniaturization in optical filters causes degradation of spectral resolution due to limitations on spectral responses and the number of filters. Nowadays, many studies have been reported that the filter-array-based spectrometers have achieved resolution improvements by using digital signal processing (DSP) techniques. The performance of the DSP-based spectral recovery highly depends on the prior information of transmission functions (TFs) of the filters. The TFs vary with respect to an incident angle of light onto the filter-array. Conventionally, it is assumed that the incident angle of light on the filters is fixed and the TFs are known to the DSP. However, the incident angle is inconstant according to various environments and applications, and thus TFs also vary, which leads to performance degradation of spectral recovery. In this paper, we propose a method of incident angle estimation (IAE) for high resolution spectral recovery in the filter-array-based spectrometers. By exploiting sparse signal reconstruction of the L1- norm minimization, IAE estimates an incident angle among all possible incident angles which minimizes the error of the reconstructed signal. Based on IAE, DSP effectively provides a high resolution spectral recovery in the filter-array-based spectrometers.

  11. Automatic speech signal segmentation based on the innovation adaptive filter

    Directory of Open Access Journals (Sweden)

    Makowski Ryszard

    2014-06-01

    Full Text Available Speech segmentation is an essential stage in designing automatic speech recognition systems and one can find several algorithms proposed in the literature. It is a difficult problem, as speech is immensely variable. The aim of the authors’ studies was to design an algorithm that could be employed at the stage of automatic speech recognition. This would make it possible to avoid some problems related to speech signal parametrization. Posing the problem in such a way requires the algorithm to be capable of working in real time. The only such algorithm was proposed by Tyagi et al., (2006, and it is a modified version of Brandt’s algorithm. The article presents a new algorithm for unsupervised automatic speech signal segmentation. It performs segmentation without access to information about the phonetic content of the utterances, relying exclusively on second-order statistics of a speech signal. The starting point for the proposed method is time-varying Schur coefficients of an innovation adaptive filter. The Schur algorithm is known to be fast, precise, stable and capable of rapidly tracking changes in second order signal statistics. A transfer from one phoneme to another in the speech signal always indicates a change in signal statistics caused by vocal track changes. In order to allow for the properties of human hearing, detection of inter-phoneme boundaries is performed based on statistics defined on the mel spectrum determined from the reflection coefficients. The paper presents the structure of the algorithm, defines its properties, lists parameter values, describes detection efficiency results, and compares them with those for another algorithm. The obtained segmentation results, are satisfactory.

  12. Machine health prognostics using the Bayesian-inference-based probabilistic indication and high-order particle filtering framework

    Science.gov (United States)

    Yu, Jianbo

    2015-12-01

    Prognostics is much efficient to achieve zero-downtime performance, maximum productivity and proactive maintenance of machines. Prognostics intends to assess and predict the time evolution of machine health degradation so that machine failures can be predicted and prevented. A novel prognostics system is developed based on the data-model-fusion scheme using the Bayesian inference-based self-organizing map (SOM) and an integration of logistic regression (LR) and high-order particle filtering (HOPF). In this prognostics system, a baseline SOM is constructed to model the data distribution space of healthy machine under an assumption that predictable fault patterns are not available. Bayesian inference-based probability (BIP) derived from the baseline SOM is developed as a quantification indication of machine health degradation. BIP is capable of offering failure probability for the monitored machine, which has intuitionist explanation related to health degradation state. Based on those historic BIPs, the constructed LR and its modeling noise constitute a high-order Markov process (HOMP) to describe machine health propagation. HOPF is used to solve the HOMP estimation to predict the evolution of the machine health in the form of a probability density function (PDF). An on-line model update scheme is developed to adapt the Markov process changes to machine health dynamics quickly. The experimental results on a bearing test-bed illustrate the potential applications of the proposed system as an effective and simple tool for machine health prognostics.

  13. UltiMatch-NL: a Web service matchmaker based on multiple semantic filters.

    Science.gov (United States)

    Mohebbi, Keyvan; Ibrahim, Suhaimi; Zamani, Mazdak; Khezrian, Mojtaba

    2014-01-01

    In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters.

  14. UltiMatch-NL: A Web Service Matchmaker Based on Multiple Semantic Filters

    Science.gov (United States)

    Mohebbi, Keyvan; Ibrahim, Suhaimi; Zamani, Mazdak; Khezrian, Mojtaba

    2014-01-01

    In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters. PMID:25157872

  15. Instantaneous Attitude Determination Based on Original Multi-antenna Observations Using Adaptively Robust Kalman Filtering

    Directory of Open Access Journals (Sweden)

    GAN Yu

    2015-09-01

    Full Text Available Attitude determination directly by carrier phase observation makes optimal use of observation and attitude constraints. The phase models based on misalignment angle and multiplicative quaternion error are derived. The state models for attitude estimation with and without external angular rate sensors are both erected. The attitude errors are estimated by adaptively robust filtering, in which the adaptive factors of ambiguity and attitude error are decided respectively following the idea of multi adaptive factor filtering. The factor of attitude is determined by a three-section function containing Ratio. Adaptively robust filtering makes the best use of constraint and historical information, fusing them in the calculation of float solution. As the accuracy of float solution and the structure of covariance matrix are improved greatly, the fix solution can be searched efficiently using LAMBDA (least-squares ambiguity decorrelation adjustment method merely, perfectly fulfilling the real-time requirement. Field test of a ship-based three-antenna attitude system is used to validate the proposed method. It is showed that direct attitude determination based on adaptively robust filtering has obvious advantages in efficiency and reliability.

  16. Exploration of digital entrepreneurship – online home based businesses through empirical analysis

    OpenAIRE

    Anwar, Naveed

    2015-01-01

    Digital entrepreneurship is a broad domain and includes businesses predominantly operating online, such as online retailers, portals, community sites and also businesses providing services to enable other businesses to operate online, such as web designers, platform providers and operators. This research focused online home based businesses on any stage of business development, for example start-up or grown, and focus on any aspect, such as raising finance, establishing networks or developing...

  17. Online dynamic equalization adjustment of high-power lithium-ion battery packs based on the state of balance estimation

    International Nuclear Information System (INIS)

    Wang, Shunli; Shang, Liping; Li, Zhanfeng; Deng, Hu; Li, Jianchao

    2016-01-01

    Highlights: • A novel concept (SOB, State of Balance) is proposed for the LIB pack equalization. • Core parameter detection and filtering is analyzed to identify the LIB pack behavior. • The electrical UKF model is adopted for the online dynamic estimation. • The equalization target model is built based on the optimum preference. • Comprehensive imbalance state calculation is implemented for the adjustment. - Abstract: A novel concept named as state of balance (SOB) is proposed and its online dynamic estimation method is presented for the high-power lithium-ion battery (LIB) packs, based on which the online dynamic equalization adjustment is realized aiming to protect the operation safety of its power supply application. The core parameter detection method based on the specific moving average algorithm is studied because of their identical varying characteristics on the individual cells due to the manufacturing variability and other factors, affecting the performance of the high-power LIB pack. The SOB estimation method is realized with the detailed deduction, in which a dual filter consisting of the Unscented Kalman filter (UKF), equivalent circuit model (ECM) and open circuit voltage (OCV) is used in order to predict the SOB state. It is beneficial for the energy operation and the energy performance state can be evaluated online prior to the adjustment method based on the terminal voltage consistency. The energy equalization is realized that is based on the credibility reasoning together with the equalization model building process. The experiments including the core parameter detection, SOB estimation and equalization adjustment are done and the experimental results are analyzed. The experiment results show that the numerical Coulomb efficiency is bigger than 95%. The cell voltage measurement error is less than 5 mV and the terminal voltage measurement error of the LIB pack is less than 1% FS. The measurement error of the battery discharge and charge

  18. Fuzzy Modelling for Human Dynamics Based on Online Social Networks.

    Science.gov (United States)

    Cuenca-Jara, Jesus; Terroso-Saenz, Fernando; Valdes-Vela, Mercedes; Skarmeta, Antonio F

    2017-08-24

    Human mobility mining has attracted a lot of attention in the research community due to its multiple implications in the provisioning of innovative services for large metropolises. In this scope, Online Social Networks (OSN) have arisen as a promising source of location data to come up with new mobility models. However, the human nature of this data makes it rather noisy and inaccurate. In order to deal with such limitations, the present work introduces a framework for human mobility mining based on fuzzy logic. Firstly, a fuzzy clustering algorithm extracts the most active OSN areas at different time periods. Next, such clusters are the building blocks to compose mobility patterns. Furthermore, a location prediction service based on a fuzzy rule classifier has been developed on top of the framework. Finally, both the framework and the predictor has been tested with a Twitter and Flickr dataset in two large cities.

  19. Arduino-based noise robust online heart-rate detection.

    Science.gov (United States)

    Das, Sangita; Pal, Saurabh; Mitra, Madhuchhanda

    2017-04-01

    This paper introduces a noise robust real time heart rate detection system from electrocardiogram (ECG) data. An online data acquisition system is developed to collect ECG signals from human subjects. Heart rate is detected using window-based autocorrelation peak localisation technique. A low-cost Arduino UNO board is used to implement the complete automated process. The performance of the system is compared with PC-based heart rate detection technique. Accuracy of the system is validated through simulated noisy ECG data with various levels of signal to noise ratio (SNR). The mean percentage error of detected heart rate is found to be 0.72% for the noisy database with five different noise levels.

  20. Enhanced Pedestrian Navigation Based on Course Angle Error Estimation Using Cascaded Kalman Filters.

    Science.gov (United States)

    Song, Jin Woo; Park, Chan Gook

    2018-04-21

    An enhanced pedestrian dead reckoning (PDR) based navigation algorithm, which uses two cascaded Kalman filters (TCKF) for the estimation of course angle and navigation errors, is proposed. The proposed algorithm uses a foot-mounted inertial measurement unit (IMU), waist-mounted magnetic sensors, and a zero velocity update (ZUPT) based inertial navigation technique with TCKF. The first stage filter estimates the course angle error of a human, which is closely related to the heading error of the IMU. In order to obtain the course measurements, the filter uses magnetic sensors and a position-trace based course angle. For preventing magnetic disturbance from contaminating the estimation, the magnetic sensors are attached to the waistband. Because the course angle error is mainly due to the heading error of the IMU, and the characteristic error of the heading angle is highly dependent on that of the course angle, the estimated course angle error is used as a measurement for estimating the heading error in the second stage filter. At the second stage, an inertial navigation system-extended Kalman filter-ZUPT (INS-EKF-ZUPT) method is adopted. As the heading error is estimated directly by using course-angle error measurements, the estimation accuracy for the heading and yaw gyro bias can be enhanced, compared with the ZUPT-only case, which eventually enhances the position accuracy more efficiently. The performance enhancements are verified via experiments, and the way-point position error for the proposed method is compared with those for the ZUPT-only case and with other cases that use ZUPT and various types of magnetic heading measurements. The results show that the position errors are reduced by a maximum of 90% compared with the conventional ZUPT based PDR algorithms.

  1. Colorization-Based RGB-White Color Interpolation using Color Filter Array with Randomly Sampled Pattern.

    Science.gov (United States)

    Oh, Paul; Lee, Sukho; Kang, Moon Gi

    2017-06-28

    Recently, several RGB-White (RGBW) color filter arrays (CFAs) have been proposed, which have extra white (W) pixels in the filter array that are highly sensitive. Due to the high sensitivity, the W pixels have better SNR (Signal to Noise Ratio) characteristics than other color pixels in the filter array, especially, in low light conditions. However, most of the RGBW CFAs are designed so that the acquired RGBW pattern image can be converted into the conventional Bayer pattern image, which is then again converted into the final color image by using conventional demosaicing methods, i.e., color interpolation techniques. In this paper, we propose a new RGBW color filter array based on a totally different color interpolation technique, the colorization algorithm. The colorization algorithm was initially proposed for colorizing a gray image into a color image using a small number of color seeds. Here, we adopt this algorithm as a color interpolation technique, so that the RGBW color filter array can be designed with a very large number of W pixels to make the most of the highly sensitive characteristics of the W channel. The resulting RGBW color filter array has a pattern with a large proportion of W pixels, while the small-numbered RGB pixels are randomly distributed over the array. The colorization algorithm makes it possible to reconstruct the colors from such a small number of RGB values. Due to the large proportion of W pixels, the reconstructed color image has a high SNR value, especially higher than those of conventional CFAs in low light condition. Experimental results show that many important information which are not perceived in color images reconstructed with conventional CFAs are perceived in the images reconstructed with the proposed method.

  2. Robust sawtooth period control based on adaptive online optimization

    International Nuclear Information System (INIS)

    Bolder, J.J.; Witvoet, G.; De Baar, M.R.; Steinbuch, M.; Van de Wouw, N.; Haring, M.A.M.; Westerhof, E.; Doelman, N.J.

    2012-01-01

    The systematic design of a robust adaptive control strategy for the sawtooth period using electron cyclotron current drive (ECCD) is presented. Recent developments in extremum seeking control (ESC) are employed to derive an optimized controller structure and offer practical tuning guidelines for its parameters. In this technique a cost function in terms of the desired sawtooth period is optimized online by changing the ECCD deposition location based on online estimations of the gradient of the cost function. The controller design does not require a detailed model of the sawtooth instability. Therefore, the proposed ESC is widely applicable to any sawtoothing plasma or plasma simulation and is inherently robust against uncertainties or plasma variations. Moreover, it can handle a broad class of disturbances. This is demonstrated by time-domain simulations, which show successful tracking of time-varying sawtooth period references throughout the whole operating space, even in the presence of variations in plasma parameters, disturbances and slow launcher mirror dynamics. Due to its simplicity and robustness the proposed ESC is a valuable sawtooth control candidate for any experimental tokamak plasma, and may even be applicable to other fusion-related control problems. (paper)

  3. The Automated Threaded Fastening Based on On-line Identification

    Directory of Open Access Journals (Sweden)

    Nicolas Ivan Giannoccaro

    2008-11-01

    Full Text Available The principle of the thread fastenings have been known and used for decades with the purpose of joining one component to another. Threaded fastenings are popular because they permit easy disassembly for maintenance, repair, relocation and recycling. Screw insertions are typically carried out manually. It is a difficult problem to automat. As a result there is very little published research on automating threaded fastenings, and most research on automated assembly focus on the peg-in-hole assembly problem. This paper investigates the problem of automated monitoring of the screw insertion process. The monitoring problem deals with predicting integrity of a threaded insertion, based on the torque vs. insertion depth curve generated during the insertions. The authors have developed an analytical model to predict the torque signature signals during self-tapping screw insertions. However, the model requires parameters on the screw dimensions and plate material properties are difficult to measure. This paper presents a study on on-line identification during screw fastenings. An identification methodology for two unknown parameter estimation during a self-tapping screw insertion process is presented. It is shown that friction and screw properties required by the model can be reliably estimated on-line. Experimental results are presented to validate the identification procedure.

  4. Towards effective and robust list-based packet filter for signature-based network intrusion detection: an engineering approach

    DEFF Research Database (Denmark)

    Meng, Weizhi; Li, Wenjuan; Kwok, Lam For

    2017-01-01

    Network intrusion detection systems (NIDSs) which aim to identify various attacks, have become an essential part of current security infrastructure. In particular, signature-based NIDSs are being widely implemented in industry due to their low rate of false alarms. However, the signature matching...... this problem, packet filtration is a promising solution to reduce unwanted traffic. Motivated by this, in this work, a list-based packet filter was designed and an engineering method of combining both blacklist and whitelist techniques was introduced. To further secure such filters against IP spoofing attacks...... in traffic filtration as well as workload reduction, and is robust against IP spoofing attacks....

  5. Particle Filter-Based Target Tracking Algorithm for Magnetic Resonance-Guided Respiratory Compensation : Robustness and Accuracy Assessment

    NARCIS (Netherlands)

    Bourque, Alexandra E; Bedwani, Stéphane; Carrier, Jean-François; Ménard, Cynthia; Borman, Pim; Bos, Clemens; Raaymakers, Bas W; Mickevicius, Nikolai; Paulson, Eric; Tijssen, Rob H N

    PURPOSE: To assess overall robustness and accuracy of a modified particle filter-based tracking algorithm for magnetic resonance (MR)-guided radiation therapy treatments. METHODS AND MATERIALS: An improved particle filter-based tracking algorithm was implemented, which used a normalized

  6. Model-Based Engine Control Architecture with an Extended Kalman Filter

    Science.gov (United States)

    Csank, Jeffrey T.; Connolly, Joseph W.

    2016-01-01

    This paper discusses the design and implementation of an extended Kalman filter (EKF) for model-based engine control (MBEC). Previously proposed MBEC architectures feature an optimal tuner Kalman Filter (OTKF) to produce estimates of both unmeasured engine parameters and estimates for the health of the engine. The success of this approach relies on the accuracy of the linear model and the ability of the optimal tuner to update its tuner estimates based on only a few sensors. Advances in computer processing are making it possible to replace the piece-wise linear model, developed off-line, with an on-board nonlinear model running in real-time. This will reduce the estimation errors associated with the linearization process, and is typically referred to as an extended Kalman filter. The nonlinear extended Kalman filter approach is applied to the Commercial Modular Aero-Propulsion System Simulation 40,000 (C-MAPSS40k) and compared to the previously proposed MBEC architecture. The results show that the EKF reduces the estimation error, especially during transient operation.

  7. Extending Correlation Filter-Based Visual Tracking by Tree-Structured Ensemble and Spatial Windowing.

    Science.gov (United States)

    Gundogdu, Erhan; Ozkan, Huseyin; Alatan, A Aydin

    2017-11-01

    Correlation filters have been successfully used in visual tracking due to their modeling power and computational efficiency. However, the state-of-the-art correlation filter-based (CFB) tracking algorithms tend to quickly discard the previous poses of the target, since they consider only a single filter in their models. On the contrary, our approach is to register multiple CFB trackers for previous poses and exploit the registered knowledge when an appearance change occurs. To this end, we propose a novel tracking algorithm [of complexity O(D) ] based on a large ensemble of CFB trackers. The ensemble [of size O(2 D ) ] is organized over a binary tree (depth D ), and learns the target appearance subspaces such that each constituent tracker becomes an expert of a certain appearance. During tracking, the proposed algorithm combines only the appearance-aware relevant experts to produce boosted tracking decisions. Additionally, we propose a versatile spatial windowing technique to enhance the individual expert trackers. For this purpose, spatial windows are learned for target objects as well as the correlation filters and then the windowed regions are processed for more robust correlations. In our extensive experiments on benchmark datasets, we achieve a substantial performance increase by using the proposed tracking algorithm together with the spatial windowing.

  8. The recommender system for virtual items in MMORPGs based on a novel collaborative filtering approach

    Science.gov (United States)

    Li, S. G.; Shi, L.

    2014-10-01

    The recommendation system for virtual items in massive multiplayer online role-playing games (MMORPGs) has aroused the interest of researchers. Of the many approaches to construct a recommender system, collaborative filtering (CF) has been the most successful one. However, the traditional CFs just lure customers into the purchasing action and overlook customers' satisfaction, moreover, these techniques always suffer from low accuracy under cold-start conditions. Therefore, a novel collaborative filtering (NCF) method is proposed to identify like-minded customers according to the preference similarity coefficient (PSC), which implies correlation between the similarity of customers' characteristics and the similarity of customers' satisfaction level for the product. Furthermore, the analytic hierarchy process (AHP) is used to determine the relative importance of each characteristic of the customer and the improved ant colony optimisation (IACO) is adopted to generate the expression of the PSC. The IACO creates solutions using the Markov random walk model, which can accelerate the convergence of algorithm and prevent prematurity. For a target customer whose neighbours can be found, the NCF can predict his satisfaction level towards the suggested products and recommend the acceptable ones. Under cold-start conditions, the NCF will generate the recommendation list by excluding items that other customers prefer.

  9. Self-commissioning notch filter for active damping in three phase LCL-filter based grid converters

    DEFF Research Database (Denmark)

    Alzola, Rafael Pena; Liserre, Marco; Blaabjerg, Frede

    2013-01-01

    inductance variations it is proposed to estimate the resonance frequency by means of Fourier analysis. The Goertzel algorithm, instead of the FFT, is used to reduce the calculation and memory requirements. Thus, the proposed self-commissioning notch filter results robust and consumes little computational...

  10. Water risk assessment in China based on the improved Water Risk Filter

    Science.gov (United States)

    Hong, G.; Yaqin, Q.; Qiong, L.; Cunwen, N.; Na, W.; Jiajia, L.; Jongde, G.; Na, Z.; Xiangyi, D.

    2014-09-01

    Finding an effective way to deal with the water crisis and the relationship between water and development is a major issue for all levels of government and different economic sectors across the world. Scientific understanding of water risk is the basis for achieving a scientific relationship between water and development, and water risk assessment is currently an important research focus. To effectively deal with the global water crisis, the World Wide Fund for Nature and German Investment and Development Company Limited proposed the concept of water risk and released an online Water Risk Filter in March 2012, which has been applied to at least 85 countries. To comprehensively and accurately reflect the situation of water risk in China, this study adjusts the water risk assessment indicators in the Water Risk Filter, taking the actual situation in China and the difficulty of obtaining the information about the indicators into account, and proposes an index system for water risk evaluation for China which consists of physical risk, regulatory risk and reputational risk. The improved Water Risk Filter is further used to assess the sources and causes of the water risks in 10 first-class and seven second-class water resource areas (WRAs). The results indicate that the water risk for the whole country is generally medium and low, while those for different regions in the country vary greatly, and those for southern regions are generally lower than those for northern regions. Government regulatory and policy implementation as well as media supervision in northern regions should be strengthened to reduce the water risk. The research results may provide decision support and references for both governments and industrial enterprises in identifying water risks, formulating prevention and control policies, and improving water resources management in China.

  11. Water risk assessment in China based on the improved Water Risk Filter

    Directory of Open Access Journals (Sweden)

    G. Hong

    2014-09-01

    Full Text Available Finding an effective way to deal with the water crisis and the relationship between water and development is a major issue for all levels of government and different economic sectors across the world. Scientific understanding of water risk is the basis for achieving a scientific relationship between water and development, and water risk assessment is currently an important research focus. To effectively deal with the global water crisis, the World Wide Fund for Nature and German Investment and Development Company Limited proposed the concept of water risk and released an online Water Risk Filter in March 2012, which has been applied to at least 85 countries. To comprehensively and accurately reflect the situation of water risk in China, this study adjusts the water risk assessment indicators in the Water Risk Filter, taking the actual situation in China and the difficulty of obtaining the information about the indicators into account, and proposes an index system for water risk evaluation for China which consists of physical risk, regulatory risk and reputational risk. The improved Water Risk Filter is further used to assess the sources and causes of the water risks in 10 first-class and seven second-class water resource areas (WRAs. The results indicate that the water risk for the whole country is generally medium and low, while those for different regions in the country vary greatly, and those for southern regions are generally lower than those for northern regions. Government regulatory and policy implementation as well as media supervision in northern regions should be strengthened to reduce the water risk. The research results may provide decision support and references for both governments and industrial enterprises in identifying water risks, formulating prevention and control policies, and improving water resources management in China.

  12. Low-dimensional recurrent neural network-based Kalman filter for speech enhancement.

    Science.gov (United States)

    Xia, Youshen; Wang, Jun

    2015-07-01

    This paper proposes a new recurrent neural network-based Kalman filter for speech enhancement, based on a noise-constrained least squares estimate. The parameters of speech signal modeled as autoregressive process are first estimated by using the proposed recurrent neural network and the speech signal is then recovered from Kalman filtering. The proposed recurrent neural network is globally asymptomatically stable to the noise-constrained estimate. Because the noise-constrained estimate has a robust performance against non-Gaussian noise, the proposed recurrent neural network-based speech enhancement algorithm can minimize the estimation error of Kalman filter parameters in non-Gaussian noise. Furthermore, having a low-dimensional model feature, the proposed neural network-based speech enhancement algorithm has a much faster speed than two existing recurrent neural networks-based speech enhancement algorithms. Simulation results show that the proposed recurrent neural network-based speech enhancement algorithm can produce a good performance with fast computation and noise reduction. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. Prognostics 101: A tutorial for particle filter-based prognostics algorithm using Matlab

    International Nuclear Information System (INIS)

    An, Dawn; Choi, Joo-Ho; Kim, Nam Ho

    2013-01-01

    This paper presents a Matlab-based tutorial for model-based prognostics, which combines a physical model with observed data to identify model parameters, from which the remaining useful life (RUL) can be predicted. Among many model-based prognostics algorithms, the particle filter is used in this tutorial for parameter estimation of damage or a degradation model. The tutorial is presented using a Matlab script with 62 lines, including detailed explanations. As examples, a battery degradation model and a crack growth model are used to explain the updating process of model parameters, damage progression, and RUL prediction. In order to illustrate the results, the RUL at an arbitrary cycle are predicted in the form of distribution along with the median and 90% prediction interval. This tutorial will be helpful for the beginners in prognostics to understand and use the prognostics method, and we hope it provides a standard of particle filter based prognostics. -- Highlights: ► Matlab-based tutorial for model-based prognostics is presented. ► A battery degradation model and a crack growth model are used as examples. ► The RUL at an arbitrary cycle are predicted using the particle filter

  14. Optimization of recommendations for abdomen computerized tomography based on reconstruction filters, voltage and tube current

    International Nuclear Information System (INIS)

    Silveira, Vinicius da Costa

    2015-01-01

    The use of computed tomography has increased significantly over the past decades. In Brazil the use increased more than twofold from 2008 to 2014, in the meantime the abdomen procedures have tripled. The high frequency of this procedure combined by the increasing collective radiation dose in medical exposures, has resulted development tools to maximize the benefit in CT images. This work aimed to establish protocols optimized in abdominal CT through acquisitions parameters and reconstructions techniques based on filters kernels. A sample of patients undergoing abdominal CT in a diagnostic center of Rio de Janeiro was assessed. Had been collected patients information and acquisitions parameters. The phantoms CT image acquisitions were performed by using different voltage values by adjusting the tube current (mAs) to obtain the same value from CTDI vol patients with normal BMI. Afterwards, the CTDIvol values were reduced by 30%, 50% and 60%. All images were reconstructed with low-contrast filters (A) and standard filters (B). The CTDIvol values for patients with normal BMI were 7% higher than in patients with underweight BMI and 30%, 50% and 60% lower than the overweight, obese I and III patients, respectively. The evaluations of image quality showed that variation of the current (mA) and the reconstruction filters did not affect the Hounsfield values. When the contrast-to-noise ratio (CNR) was normalized to CTDIvol, the protocols acquired with 60% reduction of CTDIvol with 140 kV and 80 kV showed CNR 6% lower than the routine. Modifications of the acquisition parameters did not affect spatial resolution, but the post-processing with B filters reduced the spatial frequency by 16%. With reduced the dose of 30%, lesions in the spleen had the CNR higher than 10% routine protocols with 140 kV acquired and post-processed to filter A. The image post-processing with a filter A with a 80kV voltage provided CNR values equal to the routine for the liver lesions with a 30

  15. High-transmission excited-state Faraday anomalous dispersion optical filter edge filter based on a Halbach cylinder magnetic-field configuration.

    Science.gov (United States)

    Rudolf, Andreas; Walther, Thomas

    2012-11-01

    We report on the realization of an excited-state Faraday anomalous dispersion optical filter (ESFADOF) edge filter based on the 5P(3/2)→8D(5/2) transition in rubidium. A maximum transmission of 81% has been achieved. This high transmission is only possible by utilizing a special configuration of magnetic fields taken from accelerator physics to provide a strong homogeneous magnetic field of approximately 6000 G across the vapor cell. The two resulting steep transmission edges are separated by more than 13 GHz, enabling its application in remote sensing.

  16. Density-based Monte Carlo filter and its applications in nonlinear stochastic differential equation models.

    Science.gov (United States)

    Huang, Guanghui; Wan, Jianping; Chen, Hui

    2013-02-01

    Nonlinear stochastic differential equation models with unobservable state variables are now widely used in analysis of PK/PD data. Unobservable state variables are usually estimated with extended Kalman filter (EKF), and the unknown pharmacokinetic parameters are usually estimated by maximum likelihood estimator. However, EKF is inadequate for nonlinear PK/PD models, and MLE is known to be biased downwards. A density-based Monte Carlo filter (DMF) is proposed to estimate the unobservable state variables, and a simulation-based M estimator is proposed to estimate the unknown parameters in this paper, where a genetic algorithm is designed to search the optimal values of pharmacokinetic parameters. The performances of EKF and DMF are compared through simulations for discrete time and continuous time systems respectively, and it is found that the results based on DMF are more accurate than those given by EKF with respect to mean absolute error. Copyright © 2012 Elsevier Ltd. All rights reserved.

  17. Synchrophasor-Based Online Coherency Identification in Voltage Stability Assessment

    Directory of Open Access Journals (Sweden)

    ADEWOLE, A. C.

    2015-11-01

    Full Text Available This paper presents and investigates a new measurement-based approach in the identification of coherent groups in load buses and synchronous generators for voltage stability assessment application in large interconnected power systems. A hybrid Calinski-Harabasz criterion and k-means clustering algorithm is developed for the determination of the cluster groups in the system. The proposed method is successfully validated by using the New England 39-bus test system. Also, the performance of the voltage stability assessment algorithm using wide area synchrophasor measurements from the key synchronous generator in each respective cluster was tested online for the prediction of the system's margin to voltage collapse using a testbed comprising of a Programmable Logic Controller (PLC in a hardware-in-the-loop configuration with the Real-Time Digital Simulator (RTDS and Phasor Measurement Units (PMUs.

  18. A Novel Kalman Filter for Human Motion Tracking With an Inertial-Based Dynamic Inclinometer.

    Science.gov (United States)

    Ligorio, Gabriele; Sabatini, Angelo M

    2015-08-01

    Design and development of a linear Kalman filter to create an inertial-based inclinometer targeted to dynamic conditions of motion. The estimation of the body attitude (i.e., the inclination with respect to the vertical) was treated as a source separation problem to discriminate the gravity and the body acceleration from the specific force measured by a triaxial accelerometer. The sensor fusion between triaxial gyroscope and triaxial accelerometer data was performed using a linear Kalman filter. Wrist-worn inertial measurement unit data from ten participants were acquired while performing two dynamic tasks: 60-s sequence of seven manual activities and 90 s of walking at natural speed. Stereophotogrammetric data were used as a reference. A statistical analysis was performed to assess the significance of the accuracy improvement over state-of-the-art approaches. The proposed method achieved, on an average, a root mean square attitude error of 3.6° and 1.8° in manual activities and locomotion tasks (respectively). The statistical analysis showed that, when compared to few competing methods, the proposed method improved the attitude estimation accuracy. A novel Kalman filter for inertial-based attitude estimation was presented in this study. A significant accuracy improvement was achieved over state-of-the-art approaches, due to a filter design that better matched the basic optimality assumptions of Kalman filtering. Human motion tracking is the main application field of the proposed method. Accurately discriminating the two components present in the triaxial accelerometer signal is well suited for studying both the rotational and the linear body kinematics.

  19. Voxel-Based Spatial Filtering Method for Canopy Height Retrieval from Airborne Single-Photon Lidar

    Directory of Open Access Journals (Sweden)

    Hao Tang

    2016-09-01

    Full Text Available Airborne single-photon lidar (SPL is a new technology that holds considerable potential for forest structure and carbon monitoring at large spatial scales because it acquires 3D measurements of vegetation faster and more efficiently than conventional lidar instruments. However, SPL instruments use green wavelength (532 nm lasers, which are sensitive to background solar noise, and therefore SPL point clouds require more elaborate noise filtering than other lidar instruments to determine canopy heights, particularly in daytime acquisitions. Histogram-based aggregation is a commonly used approach for removing noise from photon counting lidar data, but it reduces the resolution of the dataset. Here we present an alternate voxel-based spatial filtering method that filters noise points efficiently while largely preserving the spatial integrity of SPL data. We develop and test our algorithms on an experimental SPL dataset acquired over Garrett County in Maryland, USA. We then compare canopy attributes retrieved using our new algorithm with those obtained from the conventional histogram binning approach. Our results show that canopy heights derived using the new algorithm have a strong agreement with field-measured heights (r2 = 0.69, bias = 0.42 m, RMSE = 4.85 m and discrete return lidar heights (r2 = 0.94, bias = 1.07 m, RMSE = 2.42 m. Results are consistently better than height accuracies from the histogram method (field data: r2 = 0.59, bias = 0.00 m, RMSE = 6.25 m; DRL: r2 = 0.78, bias = −0.06 m and RMSE = 4.88 m. Furthermore, we find that the spatial-filtering method retains fine-scale canopy structure detail and has lower errors over steep slopes. We therefore believe that automated spatial filtering algorithms such as the one presented here can support large-scale, canopy structure mapping from airborne SPL data.

  20. Fast filtering algorithm based on vibration systems and neural information exchange and its application to micro motion robot

    International Nuclear Information System (INIS)

    Gao Wa; Zha Fu-Sheng; Li Man-Tian; Song Bao-Yu

    2014-01-01

    This paper develops a fast filtering algorithm based on vibration systems theory and neural information exchange approach. The characters, including the derivation process and parameter analysis, are discussed and the feasibility and the effectiveness are testified by the filtering performance compared with various filtering methods, such as the fast wavelet transform algorithm, the particle filtering method and our previously developed single degree of freedom vibration system filtering algorithm, according to simulation and practical approaches. Meanwhile, the comparisons indicate that a significant advantage of the proposed fast filtering algorithm is its extremely fast filtering speed with good filtering performance. Further, the developed fast filtering algorithm is applied to the navigation and positioning system of the micro motion robot, which is a high real-time requirement for the signals preprocessing. Then, the preprocessing data is used to estimate the heading angle error and the attitude angle error of the micro motion robot. The estimation experiments illustrate the high practicality of the proposed fast filtering algorithm. (general)