The Experts below are selected from a list of 517137 Experts worldwide ranked by ideXlab platform
Stavros G Manios - One of the best experts on this subject based on the ideXlab platform.
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a generic model for spoilage of acidic emulsified foods combining physicochemical Data Diversity and levels of specific spoilage organisms
International Journal of Food Microbiology, 2014Co-Authors: Stavros G Manios, Ronald J. W. Lambert, Panagiotis N SkandamisAbstract:Abstract The spoilage pattern of three emulsified, vegetable-based spreads of low pH (3.90–4.15) adjusted with acetic acid was characterized by correlating the growth of spoilage flora with the organoleptic and physicochemical changes, as well as the changes in the species composition of the dominant microflora during storage under isothermal conditions. In a further step, a generic (hereafter called ‘unified’) model was developed to describe the maximum specific growth rate of the specific spoilage organisms (SSOs) in all acetic acid acidified products, including literature Data and additional in-house Data from similar products, as a function of the storage temperature, pH (3.61–4.25) and initial concentration of the undissociated acetic acid in each product. The predictions of the unified model were compared with those of product-specific models, with temperature as the sole predictor variable. Two independent batches of commercially prepared pepper- (PS), fava beans- (FS) and eggplant-based (ES) spreads were stored at 4, 7, 10, 12, 15, 18, 20 and 25 °C. The growth of lactic acid bacteria (SSOs; LAB) was correlated with changes in pH, titratable acidity and organic acids concentration, as well as sensory characteristics, in order to define the shelf-life of the products. Isolates from each spread and storage temperature were grouped with SDS-PAGE and were identified with 16S rRNA, determining the association between spoilage and species Diversity. Product-specific models were developed using the square root model, while a polynomial and the Ratkowsky model were used for the development of the unified model. Products with lower pH and/or higher acetic acid content showed higher microbial stability. Lactobacillus plantarum or Lactobacillus brevis dominated the LAB association in all three spreads, although their relative percentage at the beginning of storage varied significantly. These facultative or obligate hetero-fermentative bacteria increased lactic acid and, sporadically, acetic acid levels in the spreads. The developed models were validated under real chill chain conditions and showed very good agreement with the observed Data in PS and FS. The spoilage perception patterns of the different products were similar and thus, the proposed unified model may provide accurate predictions for the spoilage of a wide variety of acetic acid-acidified spreads, regardless of differences in the formulation (e.g., raw materials) and the manufacturing procedure.
Panagiotis N Skandamis - One of the best experts on this subject based on the ideXlab platform.
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a generic model for spoilage of acidic emulsified foods combining physicochemical Data Diversity and levels of specific spoilage organisms
International Journal of Food Microbiology, 2014Co-Authors: Stavros G Manios, Ronald J. W. Lambert, Panagiotis N SkandamisAbstract:Abstract The spoilage pattern of three emulsified, vegetable-based spreads of low pH (3.90–4.15) adjusted with acetic acid was characterized by correlating the growth of spoilage flora with the organoleptic and physicochemical changes, as well as the changes in the species composition of the dominant microflora during storage under isothermal conditions. In a further step, a generic (hereafter called ‘unified’) model was developed to describe the maximum specific growth rate of the specific spoilage organisms (SSOs) in all acetic acid acidified products, including literature Data and additional in-house Data from similar products, as a function of the storage temperature, pH (3.61–4.25) and initial concentration of the undissociated acetic acid in each product. The predictions of the unified model were compared with those of product-specific models, with temperature as the sole predictor variable. Two independent batches of commercially prepared pepper- (PS), fava beans- (FS) and eggplant-based (ES) spreads were stored at 4, 7, 10, 12, 15, 18, 20 and 25 °C. The growth of lactic acid bacteria (SSOs; LAB) was correlated with changes in pH, titratable acidity and organic acids concentration, as well as sensory characteristics, in order to define the shelf-life of the products. Isolates from each spread and storage temperature were grouped with SDS-PAGE and were identified with 16S rRNA, determining the association between spoilage and species Diversity. Product-specific models were developed using the square root model, while a polynomial and the Ratkowsky model were used for the development of the unified model. Products with lower pH and/or higher acetic acid content showed higher microbial stability. Lactobacillus plantarum or Lactobacillus brevis dominated the LAB association in all three spreads, although their relative percentage at the beginning of storage varied significantly. These facultative or obligate hetero-fermentative bacteria increased lactic acid and, sporadically, acetic acid levels in the spreads. The developed models were validated under real chill chain conditions and showed very good agreement with the observed Data in PS and FS. The spoilage perception patterns of the different products were similar and thus, the proposed unified model may provide accurate predictions for the spoilage of a wide variety of acetic acid-acidified spreads, regardless of differences in the formulation (e.g., raw materials) and the manufacturing procedure.
John C. Knight - One of the best experts on this subject based on the ideXlab platform.
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security through redundant Data Diversity
Dependable Systems and Networks, 2008Co-Authors: Anh Nguyentuong, John C. Knight, David Evans, B Cox, Jack W DavidsonAbstract:Unlike other Diversity-based approaches, N-variant systems thwart attacks without requiring secrets. Instead, they use redundancy (to require an attacker to simultaneously compromise multiple variants with the same input) and tailored Diversity (to make it impossible to compromise all the variants with the same input for given attack classes). In this work, we develop a method for using Data Diversity in N-variant systems to provide high-assurance arguments against a class of Data corruption attacks. Data is transformed in the variants so identical concrete Data values have different interpretations. In order to corrupt the Data without detection, an attacker would need to alter the corresponding Data in each variant in a different way while sending the same inputs to all variants. We demonstrate our approach with a case study using that thwarts attacks that corrupt UID values.
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DSN - Security through redundant Data Diversity
2008 IEEE International Conference on Dependable Systems and Networks With FTCS and DCC (DSN), 2008Co-Authors: Anh Nguyen-tuong, John C. Knight, David Evans, B Cox, Jack W DavidsonAbstract:Unlike other Diversity-based approaches, N-variant systems thwart attacks without requiring secrets. Instead, they use redundancy (to require an attacker to simultaneously compromise multiple variants with the same input) and tailored Diversity (to make it impossible to compromise all the variants with the same input for given attack classes). In this work, we develop a method for using Data Diversity in N-variant systems to provide high-assurance arguments against a class of Data corruption attacks. Data is transformed in the variants so identical concrete Data values have different interpretations. In order to corrupt the Data without detection, an attacker would need to alter the corresponding Data in each variant in a different way while sending the same inputs to all variants. We demonstrate our approach with a case study using that thwarts attacks that corrupt UID values.
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Software fault tolerance using Data Diversity
1991Co-Authors: John C. KnightAbstract:Research on Data Diversity is discussed. Data Diversity relies on a different form of redundancy from existing approaches to software fault tolerance and is substantially less expensive to implement. Data Diversity can also be applied to software testing and greatly facilitates the automation of testing. Up to now it has been explored both theoretically and in a pilot study, and has been shown to be a promising technique. The effectiveness of Data Diversity as an error detection mechanism and the application of Data Diversity to differential equation solvers are discussed.
Francisco Correoso - One of the best experts on this subject based on the ideXlab platform.
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letters accurate short term wind speed prediction by exploiting Diversity in input Data using banks of artificial neural networks
Neurocomputing, 2009Co-Authors: Sancho Salcedosanz, Angel M Perezbellido, Emilio G Ortizgarcia, A Portillafigueras, L Prieto, Francisco CorreosoAbstract:Wind speed prediction is a very important part of wind parks management. Currently, hybrid physical-statistical wind speed forecasting models are used to this end, some of them using neural networks as the final step to obtain accurate wind speed predictions. In this paper we propose a method to improve the performance of one of these hybrid systems, by exploiting Diversity in the input Data of the neural network part of the system. The Diversity in the Data is produced by the physical models of the system, applied with different parameterizations. Two structures of neural network banks are used to exploit the input Data Diversity. We will show that our method is able to improve the performance of the system, obtaining accurate wind speed predictions better than the one obtained by the system using single neural networks.
Ramesh Karri - One of the best experts on this subject based on the ideXlab platform.
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Algorithm level re-computing using implementation Diversity: a register transfer level concurrent error detection technique
IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2002Co-Authors: Ramesh KarriAbstract:Concurrent error detection (CED) based on time redundancy entails performing the normal computation and the re-computation at different times and then comparing their results. Time redundancy implemented can only detect transient faults. We present two algorithm-level time-redundancy-based CED schemes that exploit register transfer level (RTL) implementation Diversity to detect transient and permanent faults. At the RTL, implementation Diversity can be achieved either by changing the operation-to-operator allocation or by shifting the operands before re-computation. By exploiting allocation Diversity and Data Diversity, a stuck-at fault will affect the two results in two different ways. The proposed schemes yield good fault detection probability with very low area overhead. We used the Synopsys behavior complier (BC), to validate the schemes.
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ICCAD - Algorithm level re-computing: a register transfer level concurrent error detection technique
IEEE ACM International Conference on Computer Aided Design. ICCAD 2001. IEEE ACM Digest of Technical Papers (Cat. No.01CH37281), 1Co-Authors: Ramesh KarriAbstract:In this paper we propose two algorithm-level time redundancy based Concurrent Error Detection (CED) schemes that exploit Diversity in a Register Transfer (RT) level implementation. RT level Diversity can be achieved either by changing the operation-to-operator allocation (allocation Diversity) or by shifting the operands before re-computation (Data Diversity). By enabling a fault to affect the normal result and the re-computed result in two different ways, RT level Diversity yields good CED capability with low area overhead. We used Synopsys Behavior Compiler (BC) to implement the technique.
