The Experts below are selected from a list of 324966 Experts worldwide ranked by ideXlab platform
Prabir Bhattacharya - One of the best experts on this subject based on the ideXlab platform.
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a driver fatigue Recognition Model based on information fusion and dynamic bayesian network
Information Sciences, 2010Co-Authors: Guosheng Yang, Prabir BhattacharyaAbstract:We propose a driver fatigue Recognition Model based on the dynamic Bayesian network, information fusion and multiple contextual and physiological features. We include features such as the contact physiological features (e.g., ECG and EEG), and apply the first-order Hidden Markov Model to compute the dynamics of the Bayesian network at different time slices. The experimental validation shows the effectiveness of the proposed system; also it indicates that the contact physiological features (especially ECG and EEG) are significant factors for inferring the fatigue state of a driver.
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a driver fatigue Recognition Model using fusion of multiple features
Systems Man and Cybernetics, 2005Co-Authors: Guosheng Yang, Prabir BhattacharyaAbstract:By using the fusion of contextual, visual and non-visual features, a Model based on Dempster-Shafer (D-S) evidence theory is proposed to obtain a reliable driver's fatigue Recognition. Firstly, an overall Model structure is set up with respect to the selected features and key symptoms of driver's fatigue. Secondly, a set of heuristic knowledge rules are used to determine the basic probability assignment; and a modified evidence combination is adopted to combine multiple pieces of evidence including consistent and conflicting ones. Thirdly, decision policy based on the basic probability assignment is applied to fatigue Recognition. At last, an example is given to illustrate the proposed fatigue Recognition Model.
Irena Cosic - One of the best experts on this subject based on the ideXlab platform.
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environmental light and its relationship with electromagnetic resonances of biomolecular interactions as predicted by the resonant Recognition Model
International Journal of Environmental Research and Public Health, 2016Co-Authors: Irena Cosic, Drasko Cosic, Katarina LazarAbstract:The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM). The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1) the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2) the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3) the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4) the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health.
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cellular ageing telomere telomerase and progerin analysed using resonant Recognition Model
Medical review, 2014Co-Authors: Irena Cosic, Katarina Lazar, Drasko CosicAbstract:We have analysed cellular ageing through telomere shortening and/or elongation using the Resonant Recognition Model which proposes that macromolecular (protein, DNA and RNA) interactions are resonant in nature and are characterised by frequency specific for each interaction. The two distinct frequencies have been identified characterising telomere shortening and elongation processes. Having these characteristic frequencies identified it opens new possible directions to influence and modulate cellular ageing at molecular level.
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originalni lanci original articles cellular ageing telomere telomerase and progerin analysed using resonant Recognition Model elijsko starenje telomere telomeraze i progerin analizirani metodom rezonant nog prepoznavanja
2014Co-Authors: Irena Cosic, Katarina Lazar, Drasko Cosic, Irena Cosic EmeritusAbstract:We have analysed cellular ageing through telomere shortening and/or elongation using the Resonant Recognition Model which proposes that macromolecular (protein, DNA and RNA) interactions are resonant in nature and are characterised by frequency specific for each interaction. The two distinct frequencies have been identified characterising telomere shortening and elongation processes. Having these characteristic frequencies identified it opens new possible directions to influence and modulate cellular ageing at molecular level.
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bioactive peptide design using the resonant Recognition Model
Nonlinear Biomedical Physics, 2007Co-Authors: Irena Cosic, Elena PirogovaAbstract:With a large number of DNA and protein sequences already known, the crucial question is to find out how the biological function of these macromolecules is "written" in the sequence of nucleotides or amino acids. Biological processes in any living organism are based on selective interactions between particular bio-molecules, mostly proteins. The rules governing the coding of a protein's biological function, i.e. its ability to selectively interact with other molecules, are still not elucidated. In addition, with the rapid accumulation of databases of protein primary structures, there is an urgent need for theoretical approaches that are capable of analysing protein structure-function relationships. The Resonant Recognition Model (RRM) [1, 2] is one attempt to identify the selectivity of protein interactions within the amino acid sequence. The RRM [1, 2] is a physico-mathematical approach that interprets protein sequence linear information using digital signal processing methods. In the RRM the protein primary structure is represented as a numerical series by assigning to each amino acid in the sequence a physical parameter value relevant to the protein's biological activity. The RRM concept is based on the finding that there is a significant correlation between spectra of the numerical presentation of amino acids and their biological activity. Once the characteristic frequency for a particular protein function/interaction is identified, it is possible then to utilize the RRM approach to predict the amino acids in the protein sequence, which predominantly contribute to this frequency and thus, to the observed function, as well as to design de novo peptides having the desired periodicities. As was shown in our previous studies of fibroblast growth factor (FGF) peptidic antagonists [2, 3] and human immunodeficiency virus (HIV) envelope agonists [2, 4], such de novo designed peptides express desired biological function. This study utilises the RRM computational approach to the analysis of oncogene and proto-oncogene proteins. The results obtained have shown that the RRM is capable of identifying the differences between the oncogenic and proto-oncogenic proteins with the possibility of identifying the "cancer-causing" features within their protein primary structure. In addition, the rational design of bioactive peptide analogues displaying oncogenic or proto-oncogenic-like activity is presented here.
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computational analysis of interactions between tumor and tumor suppressor proteins
2007Co-Authors: Elena Pirogova, M. Akay, Irena CosicAbstract:This chapter contains sections titled: Introduction Methodology: Resonant Recognition Model Results and Discussions Conclusion References
Drasko Cosic - One of the best experts on this subject based on the ideXlab platform.
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environmental light and its relationship with electromagnetic resonances of biomolecular interactions as predicted by the resonant Recognition Model
International Journal of Environmental Research and Public Health, 2016Co-Authors: Irena Cosic, Drasko Cosic, Katarina LazarAbstract:The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM). The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1) the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2) the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3) the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4) the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health.
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cellular ageing telomere telomerase and progerin analysed using resonant Recognition Model
Medical review, 2014Co-Authors: Irena Cosic, Katarina Lazar, Drasko CosicAbstract:We have analysed cellular ageing through telomere shortening and/or elongation using the Resonant Recognition Model which proposes that macromolecular (protein, DNA and RNA) interactions are resonant in nature and are characterised by frequency specific for each interaction. The two distinct frequencies have been identified characterising telomere shortening and elongation processes. Having these characteristic frequencies identified it opens new possible directions to influence and modulate cellular ageing at molecular level.
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originalni lanci original articles cellular ageing telomere telomerase and progerin analysed using resonant Recognition Model elijsko starenje telomere telomeraze i progerin analizirani metodom rezonant nog prepoznavanja
2014Co-Authors: Irena Cosic, Katarina Lazar, Drasko Cosic, Irena Cosic EmeritusAbstract:We have analysed cellular ageing through telomere shortening and/or elongation using the Resonant Recognition Model which proposes that macromolecular (protein, DNA and RNA) interactions are resonant in nature and are characterised by frequency specific for each interaction. The two distinct frequencies have been identified characterising telomere shortening and elongation processes. Having these characteristic frequencies identified it opens new possible directions to influence and modulate cellular ageing at molecular level.
Guosheng Yang - One of the best experts on this subject based on the ideXlab platform.
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a driver fatigue Recognition Model based on information fusion and dynamic bayesian network
Information Sciences, 2010Co-Authors: Guosheng Yang, Prabir BhattacharyaAbstract:We propose a driver fatigue Recognition Model based on the dynamic Bayesian network, information fusion and multiple contextual and physiological features. We include features such as the contact physiological features (e.g., ECG and EEG), and apply the first-order Hidden Markov Model to compute the dynamics of the Bayesian network at different time slices. The experimental validation shows the effectiveness of the proposed system; also it indicates that the contact physiological features (especially ECG and EEG) are significant factors for inferring the fatigue state of a driver.
-
a driver fatigue Recognition Model using fusion of multiple features
Systems Man and Cybernetics, 2005Co-Authors: Guosheng Yang, Prabir BhattacharyaAbstract:By using the fusion of contextual, visual and non-visual features, a Model based on Dempster-Shafer (D-S) evidence theory is proposed to obtain a reliable driver's fatigue Recognition. Firstly, an overall Model structure is set up with respect to the selected features and key symptoms of driver's fatigue. Secondly, a set of heuristic knowledge rules are used to determine the basic probability assignment; and a modified evidence combination is adopted to combine multiple pieces of evidence including consistent and conflicting ones. Thirdly, decision policy based on the basic probability assignment is applied to fatigue Recognition. At last, an example is given to illustrate the proposed fatigue Recognition Model.
Katarina Lazar - One of the best experts on this subject based on the ideXlab platform.
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environmental light and its relationship with electromagnetic resonances of biomolecular interactions as predicted by the resonant Recognition Model
International Journal of Environmental Research and Public Health, 2016Co-Authors: Irena Cosic, Drasko Cosic, Katarina LazarAbstract:The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM). The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1) the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2) the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3) the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4) the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health.
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cellular ageing telomere telomerase and progerin analysed using resonant Recognition Model
Medical review, 2014Co-Authors: Irena Cosic, Katarina Lazar, Drasko CosicAbstract:We have analysed cellular ageing through telomere shortening and/or elongation using the Resonant Recognition Model which proposes that macromolecular (protein, DNA and RNA) interactions are resonant in nature and are characterised by frequency specific for each interaction. The two distinct frequencies have been identified characterising telomere shortening and elongation processes. Having these characteristic frequencies identified it opens new possible directions to influence and modulate cellular ageing at molecular level.
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originalni lanci original articles cellular ageing telomere telomerase and progerin analysed using resonant Recognition Model elijsko starenje telomere telomeraze i progerin analizirani metodom rezonant nog prepoznavanja
2014Co-Authors: Irena Cosic, Katarina Lazar, Drasko Cosic, Irena Cosic EmeritusAbstract:We have analysed cellular ageing through telomere shortening and/or elongation using the Resonant Recognition Model which proposes that macromolecular (protein, DNA and RNA) interactions are resonant in nature and are characterised by frequency specific for each interaction. The two distinct frequencies have been identified characterising telomere shortening and elongation processes. Having these characteristic frequencies identified it opens new possible directions to influence and modulate cellular ageing at molecular level.