Advancement in multimedia technology has resulted in protection against distortion,modification,and *** implementing such protection,we have an existing technique called watermarking but obtaining desired distortion l...
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Advancement in multimedia technology has resulted in protection against distortion,modification,and *** implementing such protection,we have an existing technique called watermarking but obtaining desired distortion level with sufficient robustness is a challenging task for watermarking in multimedia *** the paper,we proposed a smart technique for video watermarking associating meta-heuristic algorithms along with an embedding method to gain an optimized *** main aim of the optimization algorithm is to obtain solutions with maximum robustness,and which should not exceed the set threshold of *** represent the accuracy of the proposed scheme,we employ a popular video watermarking technique(DCT domain)having frame selection and embedding method for watermarking.A squirrel search algorithm is chosen as a meta-heuristic algorithm that utilizes the stated fitness *** results indicate that quality constraint is fulfilled,and the proposed technique gives improved robustness against different attacks with several quality *** proposed technique could be practically implemented in several multimedia applications such as the films industry,medical imagery,OOT platforms,etc.
Background: In this paper we deal with modeling serum proteolysis process from tandem mass spectrometry data. The parameters of peptide degradation process inferred from LC-MS/MS data correspond directly to the activi...
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Background: In this paper we deal with modeling serum proteolysis process from tandem mass spectrometry data. The parameters of peptide degradation process inferred from LC-MS/MS data correspond directly to the activity of specific enzymes present in the serum samples of patients and healthy donors. Our approach integrate the existing knowledge about peptidases' activity stored in MEROPS database with the efficient procedure for estimation the model parameters. Results: Taking into account the inherent stochasticity of the process, the proteolytic activity is modeled with the use of Chemical Master Equation (CME). Assuming the stationarity of the Markov process we calculate the expected values of digested peptides in the model. The parameters are fitted to minimize the discrepancy between those expected values and the peptide activities observed in the MS data. constrained optimizationproblem is solved by Levenberg-Marquadt algorithm. Conclusions: Our results demonstrates the feasibility and potential of high-level analysis for LC-MS proteomic data. The estimated enzyme activities give insights into the molecular pathology of colorectal cancer. Moreover the developed framework is general and can be applied to study proteolytic activity in different systems.
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