The design of optimal separation flow sheets for multi-component mixtures is still not a solved problem This is especially the case when non-ideal or azeotropic mixtures or hybrid separation processes are considered. ...The design of optimal separation flow sheets for multi-component mixtures is still not a solved problem This is especially the case when non-ideal or azeotropic mixtures or hybrid separation processes are considered. We review recent developments in this field and present a systematic framework for the design of separation flow sheets. This framework proposes a three-step approach. In the first step different flow sheets are generated. In the second step these alternative flow sheet structures are evaluated with shortcut methods. In the third step a rigorous mixed-integer nonlinear programming （MINLP） optimization of the entire flow sheet is executed to determine the best alternative. Since a number of alternative flow sheets have already been eliminated, only a few optimization runs are necessary in this final step. The whole framework thus allows the systematic generation and evaluation of separation processes and is illustrated with the case study of the separation of ethanol and water.展开更多
The present work presents a statistical method to translate human voices across age groups,based on commonalities in voices of blood relations.The age-translated voices have been naturalized extracting the blood relat...The present work presents a statistical method to translate human voices across age groups,based on commonalities in voices of blood relations.The age-translated voices have been naturalized extracting the blood relation features e.g.,pitch,duration,energy,using Mel Frequency Cepstrum Coefficients(MFCC),for social compatibility of the voice-impaired.The system has been demonstrated using standard English and an Indian language.The voice samples for resynthesis were derived from 12 families,with member ages ranging from 8–80 years.The voice-age translation,performed using the Pitch synchronous overlap and add(PSOLA)approach,by modulation of extracted voice features,was validated by perception test.The translated and resynthesized voices were correlated using Linde,Buzo,Gray(LBG),and Kekre’s Fast Codebook generation(KFCG)algorithms.For translated voice targets,a strong(θ>∼93%andθ>∼96%)correlation was found with blood relatives,whereas,a weak(θ<∼78%andθ<∼80%)correlation range was found between different families and different gender from same families.The study further subcategorized the sampling and synthesis of the voices into similar or dissimilar gender groups,using a support vector machine(SVM)choosing between available voice samples.Finally,∼96%,∼93%,and∼94%accuracies were obtained in the identification of the gender of the voice sample,the age group samples,and the correlation between the original and converted voice samples,respectively.The results obtained were close to the natural voice sample features and are envisaged to facilitate a near-natural voice for speech-impaired easily.展开更多
Intermediate filaments, in addition to microtubules and actin microfilaments, are one of the three major components of the cytoskeleton in eukaryotic cells. It was discovered during the recent decades that in most cel...Intermediate filaments, in addition to microtubules and actin microfilaments, are one of the three major components of the cytoskeleton in eukaryotic cells. It was discovered during the recent decades that in most cells, intermediate filament proteins play key roles to reinforce cells subjected to large-deformation, and that they participate in signal transduction, and it was proposed that their nanome- chanical properties are critical to perform those functions. However, it is still poorly understood how the nanoscopic structure, as well as the combination of chemical composition, molecular structure and interfacial properties of these protein molecules contribute to the biomechanical properties of filaments and filament networks. Here we review recent progress in computational and theoretical studies of the intermediate filaments network at various levels in the protein＇s structure. A multiple scale method is discussed, used to couple molecular modeling with atomistic detail to larger-scale material properties of the networked material. It is shown that a finer-trains-coarser method- ology as discussed here provides a useful tool in understanding the biomechanical property and disease mechanism of intermediate filaments, coupling experiment and simulation. It further allows us to improve the understanding of associated disease mechanisms and lays the foundation for engineering the mechanical properties of biomaterials.展开更多
The paper presents a new algorithm of elastic stress predictor in non linear stochastic finite element method using the Generalized Polynomial Chaos. The statistical moments of strains calculated based on the displace...The paper presents a new algorithm of elastic stress predictor in non linear stochastic finite element method using the Generalized Polynomial Chaos. The statistical moments of strains calculated based on the displacement Polynomial Chaos expansion. To descretise the stochastic process of material the Karhunen-Loeve Expansion was used and it is presented. Using the strains and the material Karhunen-Loeve Expansion the stress components are calculated. A numerical example of shallow foundation was carried out and the results of stress and strain of the new algorithm were compared with those raised from Monte Carlo method which is treated as the exact solution. A great accuracy was presented.展开更多
The world of natural materials and structures provides an abundance of applications in which mechanics is a critical issue for our understanding of functional material properties. In particular, the mechanical propert...The world of natural materials and structures provides an abundance of applications in which mechanics is a critical issue for our understanding of functional material properties. In particular, the mechanical properties of biological materials and structures play an important role in virtually all physiological processes and at all scales, from the molecular and nanoscale to the macroscale, linking research fields as diverse as genetics to structural mechanics in an approach referred to as materiomics. Example cases that illustrate the importance of mechanics in biology include mechanical support provided by materials like bone, the facilitation of locomotion capabilities by muscle and tendon, or the protection against environmental impact by materials as the skin or armors. In this article we review recent progress and case studies, relevant for a variety of applications that range from medicine to civil engineering. We demonstrate the importance of fundamental mechanistic insight at multiple time- and length-scales to arrive at a systematic understanding of materials and structures in biology, in the context of both physiological and disease states and for the development of de novo biomaterials. Three particularly intriguing issues that will be discussed here include： First, the capacity of biological systems to turn weakness to strength through the utilization of multiple structural levels within the universality-diversity paradigm. Second, material breakdown in extreme and disease conditions. And third, we review an example where the hierarchical design paradigm found in natural protein materials has been applied in the development of a novel hiomaterial based on amyloid protein.展开更多
Intermediate filaments are one of the key components of the cytoskeleton in eukaryotic cells, and their mechanical properties are found to be equally important for physiological function and disease. While the mechani...Intermediate filaments are one of the key components of the cytoskeleton in eukaryotic cells, and their mechanical properties are found to be equally important for physiological function and disease. While the mechanical properties of single full length filaments have been studied, how the mechanical properties of crosslinks affect the mechanical property of the intermediate filament network is not well understood. This paper applies a mesoscopic model of the intermediate network with varied crosslink strengths to investigate its failure mechanism under the extreme mechanical loading. It finds that relatively weaker crosslinks lead to a more flaw tolerant intermediate filament network that is also 23% stronger than the one with strong crosslinks. These findings suggest that the mechanical properties of interfacial components are critical for bioinspired designs which provide intriguing mechanical properties.展开更多
The present system experimentally demonstrates a synthesis of syllables and words from tongue manoeuvers in multiple languages,captured by four oral sensors only.For an experimental demonstration of the system used in...The present system experimentally demonstrates a synthesis of syllables and words from tongue manoeuvers in multiple languages,captured by four oral sensors only.For an experimental demonstration of the system used in the oral cavity,a prototype tooth model was used.Based on the principle developed in a previous publication by the author(s),the proposed system has been implemented using the oral cavity(tongue,teeth,and lips)features alone,without the glottis and the larynx.The positions of the sensors in the proposed system were optimized based on articulatory(oral cavity)gestures estimated by simulating the mechanism of human speech.The system has been tested for all English alphabets and several words with sensor-based input along with an experimental demonstration of the developed algorithm,with limit switches,potentiometer,and flex sensors emulating the tongue in an artificial oral cavity.The system produces the sounds of vowels,consonants,and words in English,along with the pronunciation of meanings of their translations in four major Indian languages,all from oral cavity mapping.The experimental setup also caters to gender mapping of voice.The sound produced from the hardware has been validated by a perceptual test to verify the gender and word of the speech sample by listeners,with∼98%and∼95%accuracy,respectively.Such a model may be useful to interpret speech for those who are speech-disabled because of accidents,neuron disorder,spinal cord injury,or larynx disorder.展开更多
The numerous volumes of data generated every day necessitate the deployment of new technologies capable of dealing with massive amounts of data efficiently.This is the case with Association Rules,a tool for unsupervis...The numerous volumes of data generated every day necessitate the deployment of new technologies capable of dealing with massive amounts of data efficiently.This is the case with Association Rules,a tool for unsupervised data mining that extracts information in the form of IF-THEN patterns.Although various approaches for extracting frequent itemset(prior step before mining association rules)in extremely large databases have been presented,the high computational cost and shortage of memory remain key issues to be addressed while processing enormous data.The objective of this research is to discover frequent itemset by using clustering for preprocessing and adopting the linear prefix tree algorithm for mining the maximal frequent itemset.The performance of the proposed CL-LP-MAX-tree was evaluated by comparing it with the existing FP-max algorithm.Experimentation was performed with the three different standard datasets to record evidence to prove that the proposed CL-LP-MAX-tree algorithm outperform the existing FP-max algorithm in terms of runtime and memory consumption.展开更多
Machine learned force fields typically require manual construction of training sets consisting of thousands of first principles calculations,which can result in low training efficiency and unpredictable errors when ap...Machine learned force fields typically require manual construction of training sets consisting of thousands of first principles calculations,which can result in low training efficiency and unpredictable errors when applied to structures not represented in the training set of the model.This severely limits the practical application of these models in systems with dynamics governed by important rare events,such as chemical reactions and diffusion.We present an adaptive Bayesian inference method for automating the training of interpretable,low-dimensional,and multi-element interatomic force fields using structures drawn on the fly from molecular dynamics simulations.Within an active learning framework,the internal uncertainty of a Gaussian process regression model is used to decide whether to accept the model prediction or to perform a first principles calculation to augment the training set of the model.The method is applied to a range of single-and multi-element systems and shown to achieve a favorable balance of accuracy and computational efficiency,while requiring a minimal amount of ab initio training data.We provide a fully opensource implementation of our method,as well as a procedure to map trained models to computationally efficient tabulated force fields.展开更多
We consider an Adaptive Edge Finite Element Method （AEFEM） for the 3D eddy currents equations with variable coefficients using a residual-type a posteriori error estimator. Both the components of the estimator and c...We consider an Adaptive Edge Finite Element Method （AEFEM） for the 3D eddy currents equations with variable coefficients using a residual-type a posteriori error estimator. Both the components of the estimator and certain oscillation terms, due to the occurrence of the variable coefficients, have to be controlled properly within the adaptive loop which is taken care of by appropriate bulk criteria. Convergence of the AEFEM in terms of reductions of the energy norm of the discretization error and of the oscillations is shown. Numerical results are given to illustrate the performance of the AEFEM.展开更多
In-vehicle communication has been optimized day to day to keep updated of the technologies.Control area network(CAN)is used as a standard communication method because of its efficient and reliable connection.However,C...In-vehicle communication has been optimized day to day to keep updated of the technologies.Control area network(CAN)is used as a standard communication method because of its efficient and reliable connection.However,CAN is prone to several network level attacks because of its lack in security mechanisms.Various methods have been introduced to incorporate this in CAN.We proposed an unsupervised method of intrusion detection for in-vehicle communication networks by combining the optimal feature extracting ability of autoencoders and more precise clustering using fuzzy C-means(FCM).The proposed method is light weight and requires less computation time.We performed an extensive experiment and achieved an accuracy of 75.51%with the ML35o in-vehicle intrusion dataset.By experimental result,the proposed method also works better for other intrusion detection problems like wireless intrusion detection datasets such as WNS-DS with accuracy of 84.05%and network intrusion detection datasets such as KDDCup with accuracy 60.63%,UNSW_NB15 with accuracy 73.62%and Information Security Center of Excellence(Iscx)with accuracy 74.83%.Overall,the proposed method outperforms the existing methods and avoids labeled datasets when training an in-vehicle intrusion detection model.The results of the experiment of our proposed method performed on various intru-sion detection datasets indicate that the proposed approach is generalized and robust in detecting intrusions and can be effectively deployed in real time to monitor CAN traffic in vehicles and proactively alert during attacks.展开更多
The present work is concerned with the derivation of numerical methods to approximate the radiation dose in external beam radiotherapy.To address this issue,we consider a moment approximation of radiative transfer,clo...The present work is concerned with the derivation of numerical methods to approximate the radiation dose in external beam radiotherapy.To address this issue,we consider a moment approximation of radiative transfer,closed by an entropy minimization principle.The model under consideration is governed by a system of hyperbolic equations in conservation form supplemented by source terms.The main difficulty coming from the numerical approximation of this system is an explicit space dependence in the flux function.Indeed,this dependence will be seen to be stiff and specific numerical strategiesmust be derived in order to obtain the needed accuracy.A first approach is developed considering the 1D case,where a judicious change of variables allows to eliminate the space dependence in the flux function.This is not possible in multi-D.We therefore reinterpret the 1D scheme as a scheme on two meshes,and generalize this to 2D by alternating transformations between separate meshes.We call this procedure projection method.Several numerical experiments,coming from medical physics,illustrate the potential applicability of the developed method.展开更多
Because of stability constraints,most numerical schemes applied to hyperbolic systems of equations turn out to be costly when the flux term is multiplied by some very large scalar.This problem emerges with the M_(1)sy...Because of stability constraints,most numerical schemes applied to hyperbolic systems of equations turn out to be costly when the flux term is multiplied by some very large scalar.This problem emerges with the M_(1)system of equations in the field of radiotherapy when considering heterogeneous media with very disparate densities.Additionally,the flux term of the M_(1)system is non-linear,and in order for the model to be well-posed the numerical solution needs to fulfill conditions called realizability.In this paper,we propose a numerical method that overcomes the stability constraint and preserves the realizability property.For this purpose,we relax the M_(1)system to obtain a linear flux term.Then we extend the stencil of the difference quotient to obtain stability.The scheme is applied to a radiotherapy dose calculation example.展开更多
基金the Deutsche Forschungsgemeinschaft (German Research Foundation),DAAD (German Academic Exchange Service) and FUNDAYACUCHO, and Bayer Technology Services
文摘The design of optimal separation flow sheets for multi-component mixtures is still not a solved problem This is especially the case when non-ideal or azeotropic mixtures or hybrid separation processes are considered. We review recent developments in this field and present a systematic framework for the design of separation flow sheets. This framework proposes a three-step approach. In the first step different flow sheets are generated. In the second step these alternative flow sheet structures are evaluated with shortcut methods. In the third step a rigorous mixed-integer nonlinear programming （MINLP） optimization of the entire flow sheet is executed to determine the best alternative. Since a number of alternative flow sheets have already been eliminated, only a few optimization runs are necessary in this final step. The whole framework thus allows the systematic generation and evaluation of separation processes and is illustrated with the case study of the separation of ethanol and water.
基金The authors would like to acknowledge the Ministry of Electronics and Information Technology(MeitY),Government of India for financial support through the scholarship for Palli Padmini,during research work through Visvesvaraya Ph.D.Scheme for Electronics and IT.
文摘The present work presents a statistical method to translate human voices across age groups,based on commonalities in voices of blood relations.The age-translated voices have been naturalized extracting the blood relation features e.g.,pitch,duration,energy,using Mel Frequency Cepstrum Coefficients(MFCC),for social compatibility of the voice-impaired.The system has been demonstrated using standard English and an Indian language.The voice samples for resynthesis were derived from 12 families,with member ages ranging from 8–80 years.The voice-age translation,performed using the Pitch synchronous overlap and add(PSOLA)approach,by modulation of extracted voice features,was validated by perception test.The translated and resynthesized voices were correlated using Linde,Buzo,Gray(LBG),and Kekre’s Fast Codebook generation(KFCG)algorithms.For translated voice targets,a strong(θ>∼93%andθ>∼96%)correlation was found with blood relatives,whereas,a weak(θ<∼78%andθ<∼80%)correlation range was found between different families and different gender from same families.The study further subcategorized the sampling and synthesis of the voices into similar or dissimilar gender groups,using a support vector machine(SVM)choosing between available voice samples.Finally,∼96%,∼93%,and∼94%accuracies were obtained in the identification of the gender of the voice sample,the age group samples,and the correlation between the original and converted voice samples,respectively.The results obtained were close to the natural voice sample features and are envisaged to facilitate a near-natural voice for speech-impaired easily.
文摘Intermediate filaments, in addition to microtubules and actin microfilaments, are one of the three major components of the cytoskeleton in eukaryotic cells. It was discovered during the recent decades that in most cells, intermediate filament proteins play key roles to reinforce cells subjected to large-deformation, and that they participate in signal transduction, and it was proposed that their nanome- chanical properties are critical to perform those functions. However, it is still poorly understood how the nanoscopic structure, as well as the combination of chemical composition, molecular structure and interfacial properties of these protein molecules contribute to the biomechanical properties of filaments and filament networks. Here we review recent progress in computational and theoretical studies of the intermediate filaments network at various levels in the protein＇s structure. A multiple scale method is discussed, used to couple molecular modeling with atomistic detail to larger-scale material properties of the networked material. It is shown that a finer-trains-coarser method- ology as discussed here provides a useful tool in understanding the biomechanical property and disease mechanism of intermediate filaments, coupling experiment and simulation. It further allows us to improve the understanding of associated disease mechanisms and lays the foundation for engineering the mechanical properties of biomaterials.
文摘The paper presents a new algorithm of elastic stress predictor in non linear stochastic finite element method using the Generalized Polynomial Chaos. The statistical moments of strains calculated based on the displacement Polynomial Chaos expansion. To descretise the stochastic process of material the Karhunen-Loeve Expansion was used and it is presented. Using the strains and the material Karhunen-Loeve Expansion the stress components are calculated. A numerical example of shallow foundation was carried out and the results of stress and strain of the new algorithm were compared with those raised from Monte Carlo method which is treated as the exact solution. A great accuracy was presented.
基金Project supported by NSF, ARO,AFOSR and ONR.Additional support from DARPA and the MITEI
文摘The world of natural materials and structures provides an abundance of applications in which mechanics is a critical issue for our understanding of functional material properties. In particular, the mechanical properties of biological materials and structures play an important role in virtually all physiological processes and at all scales, from the molecular and nanoscale to the macroscale, linking research fields as diverse as genetics to structural mechanics in an approach referred to as materiomics. Example cases that illustrate the importance of mechanics in biology include mechanical support provided by materials like bone, the facilitation of locomotion capabilities by muscle and tendon, or the protection against environmental impact by materials as the skin or armors. In this article we review recent progress and case studies, relevant for a variety of applications that range from medicine to civil engineering. We demonstrate the importance of fundamental mechanistic insight at multiple time- and length-scales to arrive at a systematic understanding of materials and structures in biology, in the context of both physiological and disease states and for the development of de novo biomaterials. Three particularly intriguing issues that will be discussed here include： First, the capacity of biological systems to turn weakness to strength through the utilization of multiple structural levels within the universality-diversity paradigm. Second, material breakdown in extreme and disease conditions. And third, we review an example where the hierarchical design paradigm found in natural protein materials has been applied in the development of a novel hiomaterial based on amyloid protein.
文摘Intermediate filaments are one of the key components of the cytoskeleton in eukaryotic cells, and their mechanical properties are found to be equally important for physiological function and disease. While the mechanical properties of single full length filaments have been studied, how the mechanical properties of crosslinks affect the mechanical property of the intermediate filament network is not well understood. This paper applies a mesoscopic model of the intermediate network with varied crosslink strengths to investigate its failure mechanism under the extreme mechanical loading. It finds that relatively weaker crosslinks lead to a more flaw tolerant intermediate filament network that is also 23% stronger than the one with strong crosslinks. These findings suggest that the mechanical properties of interfacial components are critical for bioinspired designs which provide intriguing mechanical properties.
基金The authors would like to acknowledge theMinistry of Electronics and Informa-tion Technology(MeitY)Government of India for financial support through the scholarship for Palli Padmini,during research work through Visvesvaraya Ph.D.Scheme for Electronics and IT.
文摘The present system experimentally demonstrates a synthesis of syllables and words from tongue manoeuvers in multiple languages,captured by four oral sensors only.For an experimental demonstration of the system used in the oral cavity,a prototype tooth model was used.Based on the principle developed in a previous publication by the author(s),the proposed system has been implemented using the oral cavity(tongue,teeth,and lips)features alone,without the glottis and the larynx.The positions of the sensors in the proposed system were optimized based on articulatory(oral cavity)gestures estimated by simulating the mechanism of human speech.The system has been tested for all English alphabets and several words with sensor-based input along with an experimental demonstration of the developed algorithm,with limit switches,potentiometer,and flex sensors emulating the tongue in an artificial oral cavity.The system produces the sounds of vowels,consonants,and words in English,along with the pronunciation of meanings of their translations in four major Indian languages,all from oral cavity mapping.The experimental setup also caters to gender mapping of voice.The sound produced from the hardware has been validated by a perceptual test to verify the gender and word of the speech sample by listeners,with∼98%and∼95%accuracy,respectively.Such a model may be useful to interpret speech for those who are speech-disabled because of accidents,neuron disorder,spinal cord injury,or larynx disorder.
文摘The numerous volumes of data generated every day necessitate the deployment of new technologies capable of dealing with massive amounts of data efficiently.This is the case with Association Rules,a tool for unsupervised data mining that extracts information in the form of IF-THEN patterns.Although various approaches for extracting frequent itemset(prior step before mining association rules)in extremely large databases have been presented,the high computational cost and shortage of memory remain key issues to be addressed while processing enormous data.The objective of this research is to discover frequent itemset by using clustering for preprocessing and adopting the linear prefix tree algorithm for mining the maximal frequent itemset.The performance of the proposed CL-LP-MAX-tree was evaluated by comparing it with the existing FP-max algorithm.Experimentation was performed with the three different standard datasets to record evidence to prove that the proposed CL-LP-MAX-tree algorithm outperform the existing FP-max algorithm in terms of runtime and memory consumption.
基金B.K.acknowledges generous gift funding support from Bosch Research and partial support from the National Science Foundation under Grant No.1808162L.S.was supported by the Integrated Mesoscale Architectures for Sustainable Catalysis(IMASC),an Energy Frontier Research Center funded by the U.S.Department of Energy,Office of Science,Basic Energy Sciences under Award#DE-SC0012573A.M.K.and S.B.acknowledge funding from the MIT-Skoltech Center for Electrochemical Energy Storage.S.B.T.is supported by the Department of Energy Computational Science Graduate Fellowship under grant DE-FG02-97ER25308.
文摘Machine learned force fields typically require manual construction of training sets consisting of thousands of first principles calculations,which can result in low training efficiency and unpredictable errors when applied to structures not represented in the training set of the model.This severely limits the practical application of these models in systems with dynamics governed by important rare events,such as chemical reactions and diffusion.We present an adaptive Bayesian inference method for automating the training of interpretable,low-dimensional,and multi-element interatomic force fields using structures drawn on the fly from molecular dynamics simulations.Within an active learning framework,the internal uncertainty of a Gaussian process regression model is used to decide whether to accept the model prediction or to perform a first principles calculation to augment the training set of the model.The method is applied to a range of single-and multi-element systems and shown to achieve a favorable balance of accuracy and computational efficiency,while requiring a minimal amount of ab initio training data.We provide a fully opensource implementation of our method,as well as a procedure to map trained models to computationally efficient tabulated force fields.
基金The work of the first author was supported by the NSF under Grant No.DMS-0411403 and Grant No.DMS-0511611The second author acknowledges the support from the Austrian Science Foundation(FWF)under Grant No.Start Y-192Both authors acknowledge support and the inspiring athmosphere at the Johann Radon Institute for Computational and Applied Mathematics(RICAM),Linz,Austria,during the special semester on computational mechanics
文摘We consider an Adaptive Edge Finite Element Method （AEFEM） for the 3D eddy currents equations with variable coefficients using a residual-type a posteriori error estimator. Both the components of the estimator and certain oscillation terms, due to the occurrence of the variable coefficients, have to be controlled properly within the adaptive loop which is taken care of by appropriate bulk criteria. Convergence of the AEFEM in terms of reductions of the energy norm of the discretization error and of the oscillations is shown. Numerical results are given to illustrate the performance of the AEFEM.
文摘In-vehicle communication has been optimized day to day to keep updated of the technologies.Control area network(CAN)is used as a standard communication method because of its efficient and reliable connection.However,CAN is prone to several network level attacks because of its lack in security mechanisms.Various methods have been introduced to incorporate this in CAN.We proposed an unsupervised method of intrusion detection for in-vehicle communication networks by combining the optimal feature extracting ability of autoencoders and more precise clustering using fuzzy C-means(FCM).The proposed method is light weight and requires less computation time.We performed an extensive experiment and achieved an accuracy of 75.51%with the ML35o in-vehicle intrusion dataset.By experimental result,the proposed method also works better for other intrusion detection problems like wireless intrusion detection datasets such as WNS-DS with accuracy of 84.05%and network intrusion detection datasets such as KDDCup with accuracy 60.63%,UNSW_NB15 with accuracy 73.62%and Information Security Center of Excellence(Iscx)with accuracy 74.83%.Overall,the proposed method outperforms the existing methods and avoids labeled datasets when training an in-vehicle intrusion detection model.The results of the experiment of our proposed method performed on various intru-sion detection datasets indicate that the proposed approach is generalized and robust in detecting intrusions and can be effectively deployed in real time to monitor CAN traffic in vehicles and proactively alert during attacks.
基金supported by the Federation de Recherche des Pays de Loire FR9962 of the Centre National de la Recherche Scientifique(CNRS)by the German Research Foundation DFG under grant KL 1105/14/2+1 种基金and by German Academic Exchange Service DAAD under grant D/0707534The third author would like to thank the Fraunhofer ITWM for its financial support.
文摘The present work is concerned with the derivation of numerical methods to approximate the radiation dose in external beam radiotherapy.To address this issue,we consider a moment approximation of radiative transfer,closed by an entropy minimization principle.The model under consideration is governed by a system of hyperbolic equations in conservation form supplemented by source terms.The main difficulty coming from the numerical approximation of this system is an explicit space dependence in the flux function.Indeed,this dependence will be seen to be stiff and specific numerical strategiesmust be derived in order to obtain the needed accuracy.A first approach is developed considering the 1D case,where a judicious change of variables allows to eliminate the space dependence in the flux function.This is not possible in multi-D.We therefore reinterpret the 1D scheme as a scheme on two meshes,and generalize this to 2D by alternating transformations between separate meshes.We call this procedure projection method.Several numerical experiments,coming from medical physics,illustrate the potential applicability of the developed method.
文摘Because of stability constraints,most numerical schemes applied to hyperbolic systems of equations turn out to be costly when the flux term is multiplied by some very large scalar.This problem emerges with the M_(1)system of equations in the field of radiotherapy when considering heterogeneous media with very disparate densities.Additionally,the flux term of the M_(1)system is non-linear,and in order for the model to be well-posed the numerical solution needs to fulfill conditions called realizability.In this paper,we propose a numerical method that overcomes the stability constraint and preserves the realizability property.For this purpose,we relax the M_(1)system to obtain a linear flux term.Then we extend the stencil of the difference quotient to obtain stability.The scheme is applied to a radiotherapy dose calculation example.
