We propose a new clustering algorithm that assists the researchers to quickly and accurately analyze data. We call this algorithm Combined Density-based and Constraint-based Algorithm (CDC). CDC consists of two phases...We propose a new clustering algorithm that assists the researchers to quickly and accurately analyze data. We call this algorithm Combined Density-based and Constraint-based Algorithm (CDC). CDC consists of two phases. In the first phase, CDC employs the idea of density-based clustering algorithm to split the original data into a number of fragmented clusters. At the same time, CDC cuts off the noises and outliers. In the second phase, CDC employs the concept of K-means clustering algorithm to select a greater cluster to be the center. Then, the greater cluster merges some smaller clusters which satisfy some constraint rules. Due to the merged clusters around the center cluster, the clustering results show high accuracy. Moreover, CDC reduces the calculations and speeds up the clustering process. In this paper, the accuracy of CDC is evaluated and compared with those of K-means, hierarchical clustering, and the genetic clustering algorithm (GCA) proposed in 2004. Experimental results show that CDC has better performance.展开更多
In order to resolve the safety problem of the existing crane runway gir-ders(CRGs)with defects,the constraint-based R6 criterion is proposed to assess their structural integrity.The ex isting steel CRGs with defects a...In order to resolve the safety problem of the existing crane runway gir-ders(CRGs)with defects,the constraint-based R6 criterion is proposed to assess their structural integrity.The ex isting steel CRGs with defects at the weld joint between the upper flange and web plate,are characterized to three-dimensional finite element models with a semi-ellipse surface crack.The R6 criterion has been modified by considering the constraint effect which is represented by T-stress.The analysis results ilustrate that working condition of the cracked CRGs leads to high constraint level along the crack front.The crack aspect ratio(a/c)and run-way eccentricity(e)have significant influence on the integrity of the cracked CRGs.The integrity assessment results based on modified constraint-based R6 failure criterion enable to more effectively protect the cracked CRGs from brittle fracture failure.展开更多
A novel framework for fuzzy modeling and model-based control design is described. Based on the theory of fuzzy constraint processing, the fuzzy model can be viewed as a generalized Takagi-Sugeno （TS） fuzzy model wit...A novel framework for fuzzy modeling and model-based control design is described. Based on the theory of fuzzy constraint processing, the fuzzy model can be viewed as a generalized Takagi-Sugeno （TS） fuzzy model with fuzzy functional consequences. It uses multivariate antecedent membership functions obtained by granular-prototype fuzzy clustering methods and consequent fuzzy equations obtained by fuzzy regression techniques. Constrained optimization is used to estimate the consequent parameters, where the constraints are based on control-relevant a priori knowledge about the modeled process. The fuzzy-constraint-based approach provides the following features. 1） The knowledge base of a constraint-based fuzzy model can incorporate information with various types of fuzzy predicates. Consequently, it is easy to provide a fusion of different types of knowledge. The knowledge can be from data-driven approaches and/or from controlrelevant physical models. 2） A corresponding inference mechanism for the proposed model can deal with heterogeneous information granules. 3） Both numerical and linguistic inputs can be accepted for predicting new outputs. The proposed techniques are demonstrated by means of two examples： a nonlinear function-fitting problem and the well-known Box-Jenkins gas furnace process. The first example shows that the proposed model uses fewer fuzzy predicates achieving similar results with the traditional rule-based approach, while the second shows the performance can be significantly improved when the control-relevant constraints are considered.展开更多
A synchronous grammar based on the formalism of context-free grammar was developed by generalizing the first component of production that models the source text. Unlike other synchronous grammars, the grammar allows m...A synchronous grammar based on the formalism of context-free grammar was developed by generalizing the first component of production that models the source text. Unlike other synchronous grammars, the grammar allows multiple target productions to be associated to a single production rule which can be used to guide a parser to infer different possible translational equivalences for a recognized input string according to the feature constraints of symbols in the pattern. An extended generalized LR algorithm was adapted to the parsing of the proposed formalism to analyze the syntactic structure of a language. The grammar was used as the basis for building a machine translation system for Portuguese to Chinese translation. The empirical results show that the grammar is more expressive when modeling the translational equivalences of parallel texts for machine translation and grammar rewriting applications.展开更多
A new coarse-grained differentiated least interference routing algorithm(CDLI) with DiffServ-Aware was presented.This algorithm is composed of off-line and on-line stages,taking into account both real-time traffic and...A new coarse-grained differentiated least interference routing algorithm(CDLI) with DiffServ-Aware was presented.This algorithm is composed of off-line and on-line stages,taking into account both real-time traffic and best-effort traffic.Off-line stage is to determine the shortest path set disjointed path(DP) database for real-time traffic,and to identify link critical value by traffic profile information of real-time traffic and DP database.On-line stage is at first to select route in the DP database for real-time traffic,if there is no path to meet the needs,the dynamic routing will be operated.On-line routing algorithm chooses the relatively short path for real-time traffic to meet their bandwidth requirements,and for best-effort traffic it chooses a lighter load path.The simulation results show that compared with the dynamic online routing algorithm(DORA) and constrained shortest path first(CSPF) algorithm,the new algorithm can significantly improve network throughput and reduce the average path length of real-time traffic.This guarantees quality of service(QoS) of real-time traffic while improving the utilization of network resources.展开更多
Edge-finding and energetic reasoning are well known filtering rules used in constraint based disjunctive and cumulative scheduling during the propagation of the resource constraint. In practice, however, edge-finding ...Edge-finding and energetic reasoning are well known filtering rules used in constraint based disjunctive and cumulative scheduling during the propagation of the resource constraint. In practice, however, edge-finding is most used (because it has a low running time complexity) than the energetic reasoning which needs O(n3) time-intervals to be considered (where n is the number of tasks). In order to reduce the number of time-intervals in the energetic reasoning, the maximum density and the minimum slack notions are used as criteria to select the time-intervals. The paper proposes a new filtering algorithm for cumulative resource constraint, and titled energetic extended edge finder of complexity O(n3). The new algorithm is a hybridization of extended edge-finding and energetic reasoning: more powerful than the extended edge-finding and faster than the energetic reasoning. It is proven that the new algorithm subsumes the extended edge-finding algorithm. Results on Resource Constrained Project Scheduling Problems (RCPSP) from BL set and PSPLib librairies are reported. These results show that in practice the new algorithm is a good trade-off between the filtering power and the running time on instances where the number of tasks is less than 30.展开更多
In this paper, we have simulated and evaluated the performance tradeoff with routing protocols: Constrained Flooding, the Real-Time Search and the Adaptive Tree on MICA and MICAz platform with different radio models u...In this paper, we have simulated and evaluated the performance tradeoff with routing protocols: Constrained Flooding, the Real-Time Search and the Adaptive Tree on MICA and MICAz platform with different radio models using PROWLER for wireless sensor networks. The simulation results establish that the MICAz motes give low latency, high throughput, high energy consumption, low efficiency but better lifetime while the MICA motes give high success rate and less loss rate. It has been, thus, concluded that in case of all the radio models the MICAz is preferably better than MICA in applications where energy is a constraint. Moreover, use of MICAz motes increases the network lifetime in comparison to MICA for the radio models. Further, the AT protocol can be applied to achieve better energy consumption, efficiency and lifetime in real time for wireless sensor networks.展开更多
Design changes for 2D & 3D geometry are the most important features in the process of product design.Constraint modeling for variationl geometry based on geometric reasoning is one of the best approaches for this ...Design changes for 2D & 3D geometry are the most important features in the process of product design.Constraint modeling for variationl geometry based on geometric reasoning is one of the best approaches for this goal.However,it is difficult for the proposed systems to maintain or handle the consistency and completeness of the constraint model of the design objects.To change this situation,a semantic model and its control approach are presented,aiming at the integration of the data,knowledge and method related to design objects.Aconstraint definition system for in- teractively defining the semantic model and a prototype modeler based on the semantic model are also implemented to examine the idea which is extended to 3D geometric design too.展开更多
“In silico organisms”are computational genome-scale metabolic models used in systems and synthetic biology developed by constraint-based metabolic simulations using multi-omics and phenotypic data.The quality of the...“In silico organisms”are computational genome-scale metabolic models used in systems and synthetic biology developed by constraint-based metabolic simulations using multi-omics and phenotypic data.The quality of these models is hidden because of the limited availability of genomic information and genome-scale metabolic reconstruction methods.In this review,237 manually curated genome-scale models for various organisms with industrial and clinical significance were comprehensively reviewed,and their modelling information was tabulated based on literature.This review provides a comprehensive summary of potential applications of systems biology in biotechnology and biomedical research.Their broad applicability has been explored in the process of model improvement and design of experiments in metabolic design and drug development.This review summarizes their recent advances,challenges,and practical applications in Gram-negative bacteria,Gram-positive bacteria,archaea,fungi,algae,plants,and animals.Genome-scale models of microbes have been reviewed to address their various applications in metabolic systems engineering,strain optimization,bioremediation,biomanufacturing,and personalized systems medicine.Several models have been explored to understand the molecular mechanisms underlying pathogenesis,virulence,host-microbe interactions,and metabolic crosstalk.This review provides an overview of the current knowledge on human metabolic reconstructions and their important roles in human,microbiota-related,and complex metabolic disorders.Genome-scale models of human and animal metals offer ethical alternatives to the traditional animal testing methods.Current progress in systems biology research will lead to the development of indispensable databases,computational tools,and analytical platforms.This will strengthen data-driven discovery and facilitate integration of biological information into living systems.展开更多
Over the last 15 years,genome-scale metabolic models(GEMs)have been reconstructed for human and model animals,such as mouse and rat,to systematically understand metabolism,simulate multicellular or multi-tissue interp...Over the last 15 years,genome-scale metabolic models(GEMs)have been reconstructed for human and model animals,such as mouse and rat,to systematically understand metabolism,simulate multicellular or multi-tissue interplay,understand human diseases,and guide cell factory design for biopharmaceutical protein production.Here,we describe how metabolic networks can be represented using stoichiometric matrices and well-defined constraints for flux simulation.Then,we review the history of GEM development for quantitative understanding of Homo sapiens and other relevant animals,together with their applications.We describe how model develops from H.sapiens to other animals and from generic purpose to precise context-specific simulation.The progress of GEMs for animals greatly expand our systematic understanding of metabolism in human and related animals.We discuss the difficulties and present perspectives on the GEM development and the quest to integrate more biological processes and omics data for future research and translation.We truly hope that this review can inspire new models developed for other mammalian organisms and generate new algorithms for integrating big data to conduct more in-depth analysis to further make progress on human health and biopharmaceutical engineering.展开更多
文摘We propose a new clustering algorithm that assists the researchers to quickly and accurately analyze data. We call this algorithm Combined Density-based and Constraint-based Algorithm (CDC). CDC consists of two phases. In the first phase, CDC employs the idea of density-based clustering algorithm to split the original data into a number of fragmented clusters. At the same time, CDC cuts off the noises and outliers. In the second phase, CDC employs the concept of K-means clustering algorithm to select a greater cluster to be the center. Then, the greater cluster merges some smaller clusters which satisfy some constraint rules. Due to the merged clusters around the center cluster, the clustering results show high accuracy. Moreover, CDC reduces the calculations and speeds up the clustering process. In this paper, the accuracy of CDC is evaluated and compared with those of K-means, hierarchical clustering, and the genetic clustering algorithm (GCA) proposed in 2004. Experimental results show that CDC has better performance.
基金The works described in this paper are financially supported by the National Program on Key Research Project(2016YFC0701301-02),to which the authors are most grateful.
文摘In order to resolve the safety problem of the existing crane runway gir-ders(CRGs)with defects,the constraint-based R6 criterion is proposed to assess their structural integrity.The ex isting steel CRGs with defects at the weld joint between the upper flange and web plate,are characterized to three-dimensional finite element models with a semi-ellipse surface crack.The R6 criterion has been modified by considering the constraint effect which is represented by T-stress.The analysis results ilustrate that working condition of the cracked CRGs leads to high constraint level along the crack front.The crack aspect ratio(a/c)and run-way eccentricity(e)have significant influence on the integrity of the cracked CRGs.The integrity assessment results based on modified constraint-based R6 failure criterion enable to more effectively protect the cracked CRGs from brittle fracture failure.
文摘A novel framework for fuzzy modeling and model-based control design is described. Based on the theory of fuzzy constraint processing, the fuzzy model can be viewed as a generalized Takagi-Sugeno （TS） fuzzy model with fuzzy functional consequences. It uses multivariate antecedent membership functions obtained by granular-prototype fuzzy clustering methods and consequent fuzzy equations obtained by fuzzy regression techniques. Constrained optimization is used to estimate the consequent parameters, where the constraints are based on control-relevant a priori knowledge about the modeled process. The fuzzy-constraint-based approach provides the following features. 1） The knowledge base of a constraint-based fuzzy model can incorporate information with various types of fuzzy predicates. Consequently, it is easy to provide a fusion of different types of knowledge. The knowledge can be from data-driven approaches and/or from controlrelevant physical models. 2） A corresponding inference mechanism for the proposed model can deal with heterogeneous information granules. 3） Both numerical and linguistic inputs can be accepted for predicting new outputs. The proposed techniques are demonstrated by means of two examples： a nonlinear function-fitting problem and the well-known Box-Jenkins gas furnace process. The first example shows that the proposed model uses fewer fuzzy predicates achieving similar results with the traditional rule-based approach, while the second shows the performance can be significantly improved when the control-relevant constraints are considered.
文摘A synchronous grammar based on the formalism of context-free grammar was developed by generalizing the first component of production that models the source text. Unlike other synchronous grammars, the grammar allows multiple target productions to be associated to a single production rule which can be used to guide a parser to infer different possible translational equivalences for a recognized input string according to the feature constraints of symbols in the pattern. An extended generalized LR algorithm was adapted to the parsing of the proposed formalism to analyze the syntactic structure of a language. The grammar was used as the basis for building a machine translation system for Portuguese to Chinese translation. The empirical results show that the grammar is more expressive when modeling the translational equivalences of parallel texts for machine translation and grammar rewriting applications.
基金Project(2003AA781011) supported by the National High-Tech Research and Development of Program of China Project(20072022) supported by Science and Technology Foundation of Liaoning Province,China
文摘A new coarse-grained differentiated least interference routing algorithm(CDLI) with DiffServ-Aware was presented.This algorithm is composed of off-line and on-line stages,taking into account both real-time traffic and best-effort traffic.Off-line stage is to determine the shortest path set disjointed path(DP) database for real-time traffic,and to identify link critical value by traffic profile information of real-time traffic and DP database.On-line stage is at first to select route in the DP database for real-time traffic,if there is no path to meet the needs,the dynamic routing will be operated.On-line routing algorithm chooses the relatively short path for real-time traffic to meet their bandwidth requirements,and for best-effort traffic it chooses a lighter load path.The simulation results show that compared with the dynamic online routing algorithm(DORA) and constrained shortest path first(CSPF) algorithm,the new algorithm can significantly improve network throughput and reduce the average path length of real-time traffic.This guarantees quality of service(QoS) of real-time traffic while improving the utilization of network resources.
文摘Edge-finding and energetic reasoning are well known filtering rules used in constraint based disjunctive and cumulative scheduling during the propagation of the resource constraint. In practice, however, edge-finding is most used (because it has a low running time complexity) than the energetic reasoning which needs O(n3) time-intervals to be considered (where n is the number of tasks). In order to reduce the number of time-intervals in the energetic reasoning, the maximum density and the minimum slack notions are used as criteria to select the time-intervals. The paper proposes a new filtering algorithm for cumulative resource constraint, and titled energetic extended edge finder of complexity O(n3). The new algorithm is a hybridization of extended edge-finding and energetic reasoning: more powerful than the extended edge-finding and faster than the energetic reasoning. It is proven that the new algorithm subsumes the extended edge-finding algorithm. Results on Resource Constrained Project Scheduling Problems (RCPSP) from BL set and PSPLib librairies are reported. These results show that in practice the new algorithm is a good trade-off between the filtering power and the running time on instances where the number of tasks is less than 30.
文摘In this paper, we have simulated and evaluated the performance tradeoff with routing protocols: Constrained Flooding, the Real-Time Search and the Adaptive Tree on MICA and MICAz platform with different radio models using PROWLER for wireless sensor networks. The simulation results establish that the MICAz motes give low latency, high throughput, high energy consumption, low efficiency but better lifetime while the MICA motes give high success rate and less loss rate. It has been, thus, concluded that in case of all the radio models the MICAz is preferably better than MICA in applications where energy is a constraint. Moreover, use of MICAz motes increases the network lifetime in comparison to MICA for the radio models. Further, the AT protocol can be applied to achieve better energy consumption, efficiency and lifetime in real time for wireless sensor networks.
文摘Design changes for 2D & 3D geometry are the most important features in the process of product design.Constraint modeling for variationl geometry based on geometric reasoning is one of the best approaches for this goal.However,it is difficult for the proposed systems to maintain or handle the consistency and completeness of the constraint model of the design objects.To change this situation,a semantic model and its control approach are presented,aiming at the integration of the data,knowledge and method related to design objects.Aconstraint definition system for in- teractively defining the semantic model and a prototype modeler based on the semantic model are also implemented to examine the idea which is extended to 3D geometric design too.
基金the Science and Engineering Research Board(EEQ/2020/000095),Government of India,for their financial assistance.
文摘“In silico organisms”are computational genome-scale metabolic models used in systems and synthetic biology developed by constraint-based metabolic simulations using multi-omics and phenotypic data.The quality of these models is hidden because of the limited availability of genomic information and genome-scale metabolic reconstruction methods.In this review,237 manually curated genome-scale models for various organisms with industrial and clinical significance were comprehensively reviewed,and their modelling information was tabulated based on literature.This review provides a comprehensive summary of potential applications of systems biology in biotechnology and biomedical research.Their broad applicability has been explored in the process of model improvement and design of experiments in metabolic design and drug development.This review summarizes their recent advances,challenges,and practical applications in Gram-negative bacteria,Gram-positive bacteria,archaea,fungi,algae,plants,and animals.Genome-scale models of microbes have been reviewed to address their various applications in metabolic systems engineering,strain optimization,bioremediation,biomanufacturing,and personalized systems medicine.Several models have been explored to understand the molecular mechanisms underlying pathogenesis,virulence,host-microbe interactions,and metabolic crosstalk.This review provides an overview of the current knowledge on human metabolic reconstructions and their important roles in human,microbiota-related,and complex metabolic disorders.Genome-scale models of human and animal metals offer ethical alternatives to the traditional animal testing methods.Current progress in systems biology research will lead to the development of indispensable databases,computational tools,and analytical platforms.This will strengthen data-driven discovery and facilitate integration of biological information into living systems.
基金Shenzhen Scienceand Technology Innovation Commission,Grant/Award Number:KCXFZ20201221173207022National Natural Science Foundation of China,key program,Next Generation Corynebacterium Glutamate Cell Factory System Creation Technology,Grant/Award Number:21938004Department of Chemical Engineering-i BHE special cooperation joint fund project,Grant/Award Number:DCE-iBHE-2023-1。
文摘Over the last 15 years,genome-scale metabolic models(GEMs)have been reconstructed for human and model animals,such as mouse and rat,to systematically understand metabolism,simulate multicellular or multi-tissue interplay,understand human diseases,and guide cell factory design for biopharmaceutical protein production.Here,we describe how metabolic networks can be represented using stoichiometric matrices and well-defined constraints for flux simulation.Then,we review the history of GEM development for quantitative understanding of Homo sapiens and other relevant animals,together with their applications.We describe how model develops from H.sapiens to other animals and from generic purpose to precise context-specific simulation.The progress of GEMs for animals greatly expand our systematic understanding of metabolism in human and related animals.We discuss the difficulties and present perspectives on the GEM development and the quest to integrate more biological processes and omics data for future research and translation.We truly hope that this review can inspire new models developed for other mammalian organisms and generate new algorithms for integrating big data to conduct more in-depth analysis to further make progress on human health and biopharmaceutical engineering.
