Prediction error expansion
Efficient reversible hiding technique based on pairwise prediction error expansion
... extraction. Prediction-error expansion (PEE) is an important method in reversible ...between prediction-errors are not regarded and not use in conventional PEE based ...the ...
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An Invisible, Reversible, Robust and Efficient Image Watermarking Algorithm Based on Adaptive Prediction Method
... adaptive prediction-error expansion, is proposed, which can recover original image after extracting the hidden ...the prediction accuracy of the ...
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Watermarking of relational databases: Survey
... Mahmoud E. Farfoura ,Shi-Jinn Horng a, et.al [30] designed and utilize an authentication protocol based on an efficient time-stamp protocol, and we propose a blind reversing watermarking method that assure ownership ...
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A Secure and Efficient Method for Remote Sensing Imagery Distribution in Cloud Computing
... “Reversible data hiding in encrypted images with somewhat homomorphic encryption based on sorting block-level prediction-error expansion,” Journal of Information Security and Application[r] ...
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Reversible audio data hiding algorithm using noncausal prediction of alterable orders
... better prediction performance, Yan and Wang pro- posed a prediction-error expansion method using linear prediction [19] which used past eight samples for predic- tion and the ...
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Using electronic health records and Internet search information for accurate influenza forecasting
... the error of a given method to that of the naive method; the raw error num- ber of the naive method is given in the ...forecasting error by about ...raw error of each method in each ...
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On stochastic stability of regional ocean models with uncertainty in wind forcing
... the prediction error (PE) due to uncertainty in initial conditions has been deeply investigated in the theoret- ical and numerical ...model-related error (particularly finite-amplitude) on model ...
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LÉVY-BASED ERROR PREDICTION IN CIRCULAR SYSTEMATIC SAMPLING
... In Hobolth and Jensen (2002) and Jónsdóttir et al. (2006), the process X is assumed to be Gaussian. Motivated by the fact that powers of the radial function and the support function are used in practice, we will in this ...
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For Value or for Worth? Part 2: A Neuroeconomical Thought Action Mood Space Modulated by (Un )Certainty as Sign or Goal tracking
... Prediction of less Effort or of Reward The ubiquitous “reward prediction error” RPE in most current accounts but not in all experiments could probably be smoothly replaced by a RPE norma[r] ...
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Prediction error minimization as a framework for social cognition research
... reducing prediction errors: active inference and perceptual ...tion error in a social environment, which serves to disambiguate competing mod- els about other ...
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Design a High Speed Error Prediction AES Algorithm
... To notify the system the Razor flip-flop will set the error signal to 1 to re execute the operation if any errors occur and notify the AHL circuit that an error has occurred. To detect whether an operation ...
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Prediction error preprocessing for perceptual color image compression
... quantization error below the detection ...a prediction error preprocessor based on the JND is investigated for higher performance in the design of the color image compression ...the prediction ...
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Consistency of the semivariogram fitting error on ordinary kriging prediction
... Kriging is a construction method that is primarily built based on the structure of experimental semivariograms and the power of fitting. The two functions, i.e., classical and robust semivariograms, are used in the ...
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Multi-target Prediction Methods for Bioinformatics: Approaches for Protein Function Prediction and Candidate Discovery for Gene Regulatory Network Expansion
... the prediction for the terms close to the root (typically easier to predict), is forced to flow through the leaf-terms, which are by far more difficult to ...continuous prediction to guarantee hierarchical ...
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Custovic_unc_0153D_19192.pdf
... Adebambo et al. (2016) notes that the forecast horizon might be a useful determinant of the relative forecasting power because forecasts made closer to the announcement date should contain more information, and thus be ...
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On Bürmann’s Theorem and Its Application to Problems of Linear and Nonlinear Heat Transfer and Diffusion »
... Expansions of this type will be applied to functions defined by integrals. For linear and also for nonlinear processes of heat transfer, these series expansions will serve us to find valuable approximations. This is due ...
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<p>Retrospective analysis of an intraoperative aberrometry database: a study investigating absolute prediction in eyes implanted with low cylinder power toric intraocular lenses</p>
... SE error, the patient will likely be dissatis fi ed with the result and may require ...absolute prediction errors of IA compared with conventional biometry in patients receiving toric IOLs to treat low ...
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Defect Prediction for Object Oriented Software using Support Vector based Fuzzy Classification Model
... defect prediction models. These models can be used in defect prediction, risk analysis, effort estimation, software testability and maintainability, and reliability analysis during early phases of software ...
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Energy Efficient Data Transmission using PID based Data Prediction System
... network, prediction-based data transmission approach may be use for ...dual prediction flowchart and a low-complexity prediction algorithm that takes advantage of PID (Proportional Integral ...
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Plantain: It is not only the dietary content, but also how we graze it…
... 1999; Khelil-Arfa et al. 2012; Winchester & Morris 1956; Appuhamy et al. 2014). However, many models use UN as input data or only predict daily UN averages, ignoring the known variability of N concentration, volume ...
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