Issue Of Error Propagation Research Articles

Performance-enhanced NOMA-VLC using subcarrier pairwise coding

To alleviate the error propagation issue of non-orthogonal multiple access (NOMA) based visible light communication (VLC) systems, we propose and experimentally demonstrate the subcarrier pairwise coding (PWC) based NOMA-VLC. Without extra coding overhead, the computation-efficient subcarrier PWC can significantly improve the overall system performance by pairing the subcarriers of high signal-to-noise ratios (SNRs) with those of low SNRs. Under different transmitted baud rate from 150 MSa/s to 225 MSa/s, the bit error rate (BER) performance with and without PWC is investigated in a NOMA-VLC system. Experimental results show that with the optimized power ratio between the NOMA users, up to 3.3-dB Q2-factor improvement can be achieved by the proposed scheme.

Quantitative gaseous temperature and mole concentration measurements in spray generated mixture by p-xylene-PLIF imaging

ABSTRACTThe current study originally presents a detailed approach to implement the p-xylene based two-color PLIF for measuring gaseous mixture temperature and mole concentration field simultaneously. An 80 * 0.8 mm2 laser sheet at 266 nm is employed to excite homogenous p-xylene/nitrogen steady mixture flow in a calibration cell, where the known p-xylene mole concentration and temperature are adjustable. Doing so, the full band/spectral (centered at 289 nm) fluorescence intensity are respectively captured by ICCD camera that allows establishments of temperature–fluorescence ratio database. Concomitantly, the full band fluorescence intensity correlation with temperature and mole concentration is rightly created as well. Utilizing the identical laser sheet and detection channel, the quantitative temperature and mole concentration field in a far-field developed-spray region could be inferred by terms of full band/spectral fluorescence imaging through previous calibration database. The error propagation issue of temperature and mole concentration measurement by this approach are discussed. As a result, it is found that the relative temperature and mole concentration uncertainties are in the range of 5.4 ~ 7.3% and 8 ~ 9.3% (or 12.3 ~ 18.7% by bottom-up approach), respectively, within studied temperature range of 423 ~ 573K. Therefore, the suitability and capability of p-xylene as the tracer for spatio-temporal temperature and mole concentration measurements are preliminarily validated, which offers an alternative tracer option for gasoline/its surrogate spray studies. It is noted that replacing the p-xylene by other suitable fluorescence tracer, i.e.,1-methylnaphthalene, this approach could be rightly performed for studies of Diesel engine, or even gas turbine.

An empirical convolutional neural network approach for semantic relation classification

In industry, relation classification plays a significant role in today׳s search engine. Up to now, the state-of-the-art systems have the problems of over-reliance on the quality of handcrafted features annotated by experts and linguistic knowledge derived from linguistic analysis modules, which is costly and leads to the issue of error propagation. Currently, with the data-driven approaches attracting wide attention, deep learning achieves impressive performance in semantic processing tasks without much effort on costly features. In this work, we deal with the relation classification task utilizing a convolutional neural network (CNN) approach to automatically control feature learning from raw sentences and minimize the application of external toolkits and resources. Our proposed method has several distinct features. First, we exploit a simple but rational way to specify which input tokens are the target nominals in the input sentence, instead of Position Feature that used in other neural network relation classification systems. Secondly, a most suitable dropout strategy is used to prevent units in the neural network from co-adapting too much, which significantly reduces over-fitting and improves the performance. Eventually, using only word embedding as input features is sufficient to achieve desirable performance. Our experiments on the SemEval-2010 Task-8 dataset show that our CNN architecture without using any additional extracted features significantly outperforms the state-of-the-art systems and achieves an F1-score of 84.8% only considering the context between the two target nominals.

Noncoherent Receiver for Decode-and-Forward Cooperative Systems with Multi-Antenna Equipped Destination

This paper studies a maximum energy selection receiver for an adaptive decode-and-forward (DF) cooperative wireless system with multiple-antenna equipped destination. In particular, the destination selects the maximum output from all the outputs of the square-law detectors to perform the detection of the transmitted information. A close-form expression for the bit-error-rate (BER) is analytically derived when the system is deployed with binary frequency-shift keying (BFSK) modulation. The thresholds used at the relays to address the issue of error propagation are optimized to minimize the BER. While finding the optimal thresholds requires information on the average signal-to-noise ratios (SNRs) of all the transmission links in the system, the approximate thresholds at each relay that require only information on the average SNR of the source-corresponding relay are investigated. It is also derived that the system achieves a full diversity order with the approximate thresholds. Finally, both analytical and simulation results are provided to verify our analysis.

Calibration of a detector array through beam profile reconstruction with error-locking.

An iterative method is proposed to calibrate radiation sensitivities of an arbitrary two‐dimensional (2D) array of detectors. The array is irradiated with a wide open‐field beam at the central position, as well as at laterally and longitudinal shifted positions; the 2D beam profile of the wide field is reconstructed iteratively from the ratios of shifted images to the central image. The propagation errors due to output variation and inaccurate array positioning are estimated and removed from the reconstructed beam profile by an error‐locking scheme with narrow open‐field irradiations. The beam profile is interpolated when necessary and then compared to raw detector responses to determine sensitivities. Two additional methods were implemented for comparison: 1) the commercial iterative calibration method for MapCHECK2 with translation and rotation operations; 2) a labor‐intensive noniterative method without the issue of error propagation. A MapCHECK2 2D detector array was used to validate the proposed method with the 6 MV photon beam from a Varian iX linear accelerator. All calibration methods were repeated three times. A total of 5, 9, and 29 irradiations were required to implement the commercial method, the proposed method and the noniterative method respectively. Moreover, a 5 mm positioning error was intentionally introduced into the calibration procedures of the commercial and the proposed method to test their robustness. Under the normal operation condition of the linear accelerator and with careful alignment of the MapCHECK2, the deviations of the calibrated sensitivities of the proposed method and commercial method with respect to the noniterative method were 0.30%±0.29% and 0.92%±0.63% respectively; when the 5 mm positioning error was presented, these two methods resulted in deviations of 0.40%±0.36% and 3.58%±1.94%, respectively. A patient study suggested that, due to this 5 mm positioning error, the mean DTA (dose to agreement) passing rate by the commercial method was 2.7% lower than that by the noniterative method, whereas the proposed method led to a comparable passing rate. It is evident from this study that the proposed iterative method leads to within 1% mean calibration results to established methods. It requires much fewer number of measurements than noniterative method and is more robust against the positioning error than the commercial iterative method. The method also eliminates the need of rotation operations and, therefore, is applicable to inline detector arrays without rotation function, such as electronic portal imager device (EPID).PACS number: 87.56.Fc

Protein Classification with Extended-Sequence Coding by Sliding Window

A large number of unclassified sequences is still found in public databases, which suggests that there is still need for new investigations in the area. In this contribution, we present a methodology based on Artificial Neural Networks for protein functional classification. A new protein coding scheme, called here Extended-Sequence Coding by Sliding Windows, is presented with the goal of overcoming some of the difficulties of the well method Sequence Coding by Sliding Window. The new protein coding scheme uses more than one sliding window length with a weight factor that is proportional to the window length, avoiding the ambiguity problem without ignoring the identity of small subsequences Accuracy for Sequence Coding by Sliding Windows ranged from 60.1 to 77.7 percent for the first bacterium protein set and from 61.9 to 76.7 percent for the second one, whereas the accuracy for the proposed Extended-Sequence Coding by Sliding Windows scheme ranged from 70.7 to 97.1 percent for the first bacterium protein set and from 61.1 to 93.3 percent for the second one. Additionally, protein sequences classified inconsistently by the Artificial Neural Networks were analyzed by CD-Search revealing that there are some disagreement in public repositories, calling the attention for the relevant issue of error propagation in annotated databases due the incorrect transferred annotations.

Robust Video Region-of-Interest Coding Based on Leaky Prediction

A video region-of-interest (ROI) scalable coding scheme can ensure the priority of ROI. Error protection schemes can be used to guarantee the correct receipt of the ROI stream when transporting ROI scalable video over an error-prone network. However, we find that the correct receipt of ROI bitstreams cannot ensure the correct decoding of ROI due to the unique issue of the cross error propagation between ROI and background in ROI scalable coding. In this letter, we propose an ROI scalable coding framework based on leaky prediction (LP) for robustly transporting video over an error-prone network. Although several LP approaches have been proposed to improve layered coding, they cannot be applied to ROI scalable coding straightforwardly due to the cross error propagation issue. We deploy a leaky factor to weigh the two predictions: one from the constrained motion estimation (ME) within the ROI layer of the reference frame, and the other from the unrestricted ME in the overall reference frame. Simulation results show that the proposed scheme enhances the robustness of ROI scalability while maintaining coding efficiency.

Tramontano , Anna : The Ten Most Wanted Solutions in Protein Bioinformatics.

Tramontano , Anna : The Ten Most Wanted Solutions in Protein Bioinformatics.

Sensor orientation via RPCs

The adoption of rational functions as a preferred sensor orientation model for narrow field of view line scanner imagery accompanied the introduction of commercial high-resolution satellite imagery (HRSI) at the turn of the millennium. This paper reviews the developments in ground point determination from HRSI via the model of terrain independent rational polynomial coefficients (RPCs). A brief mathematical background to rational functions is first presented, along with a review of the models for generating RPCs from a rigorous sensor orientation, and for geopositioning via either forward intersection or monoplotting. The concept of RPC block adjustment with compensation for exterior orientation biases is then discussed, as is the means to enhance the original RPCs through a bias correction procedure. The potential for RPC block adjustment to yield sub-pixel geopositioning accuracy from HRSI is illustrated using results from experimental testing with two Quickbird stereo image pairs and three multi-image IKONOS blocks. Finally, error propagation issues in RPC block adjustment of HRSI are considered.

Radial error propagation issues in self-servo track writing technology

Conventional servo track writing needs external devices to position heads in hard disk drives to write servo patterns. In self-servo track writing (SSTW), the position reference is regenerated from previous written tracks and a servo pattern is propagated to cover the disk in a progressive mode. Errors will propagate and compound in this process. In this paper, the radial error propagation is discussed and a containment scheme is established. Furthermore, experimental results of SSTW on a head-disk assembly with blank media and off-the-shelf electronics are analyzed to show the effectiveness of error containment in self-radial propagation.

The effect of mean centering on prediction in multivariate calibration

AbstractTraditionally, one form of preprocessing in multivariate calibration methods such as principal component regression and partial least squares is mean centering the independent variables (responses) and the dependent variables (concentrations). However, upon examination of the statistical issue of error propagation in multivariate calibration, it was found that mean centering is not advised for some data structures. In this paper it is shown that for response data which (i) vary linearly with concentration, (ii) have no baseline (when there is a component with a non‐zero response that does not change in concentration) and (iii) have no closure in the concentrations (for each sample the concentrations of all components add to a constant, e.g. 100%) it is better not to mean center the calibration data. That is, the prediction errors as evaluated by a root mean square error statistic will be smaller for a model made with the raw data than a model made with mean‐centered data. With simulated data relative improvements ranging from 1% to 13% were observed depending on the amount of error in the calibration concentrations and responses.