The Underwater Acoustic(UWA)channel is bandwidth-constrained and experiences doubly selective fading.It is challenging to acquire perfect channel knowledge for Orthogonal Frequency Division Multiplexing(OFDM)communica...The Underwater Acoustic(UWA)channel is bandwidth-constrained and experiences doubly selective fading.It is challenging to acquire perfect channel knowledge for Orthogonal Frequency Division Multiplexing(OFDM)communications using a finite number of pilots.On the other hand,Deep Learning(DL)approaches have been very successful in wireless OFDM communications.However,whether they will work underwater is still a mystery.For the first time,this paper compares two categories of DL-based UWA OFDM receivers:the DataDriven(DD)method,which performs as an end-to-end black box,and the Model-Driven(MD)method,also known as the model-based data-driven method,which combines DL and expert OFDM receiver knowledge.The encoder-decoder framework and Convolutional Neural Network(CNN)structure are employed to establish the DD receiver.On the other hand,an unfolding-based Minimum Mean Square Error(MMSE)structure is adopted for the MD receiver.We analyze the characteristics of different receivers by Monte Carlo simulations under diverse communications conditions and propose a strategy for selecting a proper receiver under different communication scenarios.Field trials in the pool and sea are also conducted to verify the feasibility and advantages of the DL receivers.It is observed that DL receivers perform better than conventional receivers in terms of bit error rate.展开更多
Deep learning offers a novel opportunity to achieve both high-quality and high-speed computer-generated holography(CGH).Current data-driven deep learning algorithms face the challenge that the labeled training dataset...Deep learning offers a novel opportunity to achieve both high-quality and high-speed computer-generated holography(CGH).Current data-driven deep learning algorithms face the challenge that the labeled training datasets limit the training performance and generalization.The model-driven deep learning introduces the diffraction model into the neural network.It eliminates the need for the labeled training dataset and has been extensively applied to hologram generation.However,the existing model-driven deep learning algorithms face the problem of insufficient constraints.In this study,we propose a model-driven neural network capable of high-fidelity 4K computer-generated hologram generation,called 4K Diffraction Model-driven Network(4K-DMDNet).The constraint of the reconstructed images in the frequency domain is strengthened.And a network structure that combines the residual method and sub-pixel convolution method is built,which effectively enhances the fitting ability of the network for inverse problems.The generalization of the 4K-DMDNet is demonstrated with binary,grayscale and 3D images.High-quality full-color optical reconstructions of the 4K holograms have been achieved at the wavelengths of 450 nm,520 nm,and 638 nm.展开更多
Model-Driven Engineering (MDE) by reframing software development as the transformation of high-level models, promises lots of gains to Software Engineering in terms of productivity, quality and reusability. Although a...Model-Driven Engineering (MDE) by reframing software development as the transformation of high-level models, promises lots of gains to Software Engineering in terms of productivity, quality and reusability. Although a number of empirical studies have established the reality of these gains, there are still lots of reluctances toward the adoption of MDE in practice. This resistance can be explained by several technological and social factors among which a natural scepticism toward novel approaches. In this paper we attempt to provide arguments to help alleviate this scepticism by conducting an assessment of a MDE approach. Our goal is to show that although this MDE is novel, it retains similarities with the conventional Software Engineering approach while automating aspects of it.展开更多
Although the Model-Driven paradigm is being accepted in the research environment as a very useful and powerful option for effective software development, its real application in the enterprise context is still a chall...Although the Model-Driven paradigm is being accepted in the research environment as a very useful and powerful option for effective software development, its real application in the enterprise context is still a challenge for software engineering. Several causes can be stacked out, but one of them can be the lack of tool support for the efficient application of this paradigm. This paper presents a set of tools, grouped in a suite named NDT-Suite, which under the Model-Driven paradigm offer a suitable solution for software development. These tools explore different options that this paradigm can improve such as, development, quality assurance or requirement treatment. Besides, this paper analyses how they are being successfully applied in the industry.展开更多
The IEC 61131-3 standard defines a model and a set of programming languages for the development of industrial automation software. It is widely accepted by industry and most of the commercial tool vendors advertise co...The IEC 61131-3 standard defines a model and a set of programming languages for the development of industrial automation software. It is widely accepted by industry and most of the commercial tool vendors advertise compliance with it. On the other side, Model Driven Development (MDD) has been proved as a quite successful paradigm in general-purpose computing. This was the motivation for exploiting the benefits of MDD in the industrial automation domain. With the emerging IEC 61131 specification that defines an object-oriented (OO) extension to the function block model, there will be a push to the industry to better exploit the benefits of MDD in automation systems development. This work discusses possible alternatives to integrate the current but also the emerging specification of IEC 61131 in the model driven development process of automation systems. IEC 61499, UML and SysML are considered as possible alternatives to allow the developer to work in higher layers of abstraction than the one supported by IEC 61131 and to more effectively move from requirement specifications into the implementation model of the system.展开更多
Web Service Composition provides an opportunity for enterprises to increase the ability to adapt themselves to frequent changes in users' requirements by integrating existing services. Our research has focused on ...Web Service Composition provides an opportunity for enterprises to increase the ability to adapt themselves to frequent changes in users' requirements by integrating existing services. Our research has focused on proposing a framework to support dynamic composition and to use both SOAP-based and RESTful Web services simultaneously in composite services. In this paper a framework called "Model-driven Dynamic Composition of Heterogeneous Service" (MDCHeS) is introduced. It is elaborated in three different ways;each represents a particular view of the framework: data view, which consists of a Meta model and composition elements as well their relationships;process view, which introduces composition phases and used models in each phase;and component view, which shows an abstract view of the components and their interactions. In order to increase the dynamicity of MDCHeS framework, Model Driven Architecture and proxy based ideas are used.展开更多
Low-resolution analog-to-digital converter(ADC)is a promising solution to reduce hardware cost and power consumption in generalized frequency division multiplexing(GFDM)systems.The severe nonlinear distortion of ADCs ...Low-resolution analog-to-digital converter(ADC)is a promising solution to reduce hardware cost and power consumption in generalized frequency division multiplexing(GFDM)systems.The severe nonlinear distortion of ADCs and the non-orthogonality of GFDM make receiver design a great challenge.In this paper,we propose a novel model-driven receiver architecture for GFDM with low-resolution ADCs.Orthogonal approximate message passing(OAMP)framework is combined with the classical linear estimator in this work to create a robust iterative receiver for GFDM systems with low-precision ADCs.The corresponding model-driven network is organized based on the proposed novel iterative algorithm according to the procedures of the receiver.The network of OAMP can reduce the gap between the approximate algorithm and the Bayesian optimal result due to the information loss of ADCs.The signal flow of the neural network is designed by unfolding the iterative algorithms for channel estimation and data detection.Numerical results are provided to show that the proposed OAMP-based receiver algorithm outperforms traditional receivers and the model-driven network can further improve the system performance on the basis of the corresponding novel algorithm.展开更多
Cyber-physical systems(CPSs)have emerged as a potential enabling technology to handle the challenges in social and economic sustainable development.Since it was proposed in 2006,intensive research has been conducted,s...Cyber-physical systems(CPSs)have emerged as a potential enabling technology to handle the challenges in social and economic sustainable development.Since it was proposed in 2006,intensive research has been conducted,showing that the construction of a CPS is a hard and complex engineering process due to the nature of integrating a large number of heterogeneous subsystems.Among other approaches to dealing with the complex design issues,model-driven design of CPSs has shown its advantages.In this review paper,we present a survey of research on model-driven development of CPSs.We are concerned mainly with the widely used methods,techniques,and tools,and discuss how these are applied to CPSs.We also present comparative analyses on the surveyed techniques and tools from various perspectives,including their modeling languages,functionalities,and the challenges which they address in CPS design.With our understanding of the surveyed methods,we believe that model-driven approaches are an inevitable choice in building CPSs and further research effort is needed in the development of model-driven theories,techniques,and tools.We also argue that a unified modeling platform is needed.Such a platform would benefit research in the academic community and practical development in industry,and improve the collaboration between these two communities.展开更多
Platelets,one of the most significant materials in treating leukemia,have a limited shelf life of approximately five days.Because platelets cannot be manufactured and can only be centrifuged from whole or donated bloo...Platelets,one of the most significant materials in treating leukemia,have a limited shelf life of approximately five days.Because platelets cannot be manufactured and can only be centrifuged from whole or donated blood directly,an accurate ordering policy is necessary for the efficient use of this limited blood resource.Given this motivation,the present study examines an ordering policy for platelets to minimize the expected shortage and overage.Rather than using the two-step model-driven method that first fits a demand distribution and then optimizes the order quantity,we solve the issue using an integrated datadriven method.Specifically,the data-driven method works directly with demand data and does not rely on the assumption of demand distribution.Consequently,we derive theoretical insights into the optimal solutions.Through a comparative analysis,we find that the data-driven method has a mean anchoring effect,and the amounts of shortage and overage reduced by this method are greater than those reduced by the model-driven method.Finally,we present an extended model with the service level requirement and conclude that the order decided by the data-driven method can precisely satisfy the service level requirement;however,the order decided by the model-driven method may be either higher or lower than the service level requirement and can lead to a higher cost.展开更多
Activity-oriented context-aware （AOCA） applications are representative in pervasive computing. These appli- cations recognize daily-life human activities, perceive the environment status related to the activities, a...Activity-oriented context-aware （AOCA） applications are representative in pervasive computing. These appli- cations recognize daily-life human activities, perceive the environment status related to the activities, and react to ensure the smooth performance of the activities. Existing research proposed a specific light-weight, incremental method to support the development of such applications; however it is not easy to learn and use. This paper aims to facilitate the development of such applications and improve the productivity of developers. We propose AocML, a textual domain-specific language which provides a high-level abstraction of AOCA applications. Specifically, we first show the software model of AOCA applications and the abstract syntax of AocML. Then, we introduce the concrete syntax of AocML. We also implement the tools for AocML, including the development environment as well as the generation of Java code and ontology specification. Moreover, we use a case study and evaluation to demonstrate the advantages of AocML.展开更多
Reasonable prediction of concrete creep is the basis of studying long-term deflection of concrete structures.In this paper,a hybrid model-driven and data-driven(HMD)method for predicting concrete creep is proposed by ...Reasonable prediction of concrete creep is the basis of studying long-term deflection of concrete structures.In this paper,a hybrid model-driven and data-driven(HMD)method for predicting concrete creep is proposed by using the sequence integration strategy.Then,a novel uncertainty prediction model(UPM)is developed considering uncertainty quantification.Finally,the effectiveness of the proposed method is validated by using the North-western University(NU)database of creep,and the effect of uncertainty on prediction results are also discussed.The analysis results show that the proposed HMD method outperforms the model-driven and three data-driven methods,including the genetic algorithm-back propagation neural network(GA-BPNN),particle swarm optimization-support vector regression(PSO-SVR)and convolutional neural network only method,in accuracy and time efficiency.The proposed UPM of concrete creep not only ensures relatively good prediction accuracy,but also quantifies the model and measurement uncertainties during the prediction process.Additionally,although incorporating measurement uncertainty into concrete creep prediction can improve the prediction performance of UPM,the prediction interval of the creep compliance is more sensitive to model uncertainty than to measurement uncertainty,and the mean contribution of variance attributed to the model uncertainty to the total variance is about 90%.展开更多
As a disruptive technology,the blockchain is continuously finding novel application contexts,bringing new opportunities and radical changes.In this paper,we use blockchain as a communication infrastructure to support ...As a disruptive technology,the blockchain is continuously finding novel application contexts,bringing new opportunities and radical changes.In this paper,we use blockchain as a communication infrastructure to support multi-party business processes.In particular,through smart contracts specifically generated by the mentioned business process,it is possible to derive a trustable infrastructure enabling the interaction among parties.Moreover,the emergence of different blockchain technologies,satisfying different characteristics,gives the possibility to support the same business process dealing with different non-functional needs.In this paper,we propose a novel engineering methodology supported by a practical framework called Multi-Chain.It permits to derive,using a model-driven strategy,a blockchain-based infrastructure,that can be deployed over a specific blockchain technology(e.g.,Ethereum or Hyperledger Fabric).The objective is to permit the single definition and multiple deployments of the business process,to deliver the same functionalities,but satisfying different nonfunctional needs.In such a way,organisations willing to cooperate can select the multi-party business process and the blockchain technology they would like to use to satisfy their needs.Using Multi-Chain,they will be able to automatically derive from a Business Process Modelling Notation(BPMN)choreography diagram a blockchain infrastructure ready to be used.This overcomes the need to get acquainted with many details of the specific technology.展开更多
基金funded in part by the National Natural Science Foundation of China under Grant 62401167 and 62192712in part by the Key Laboratory of Marine Environmental Survey Technology and Application,Ministry of Natural Resources,P.R.China under Grant MESTA-2023-B001in part by the Stable Supporting Fund of National Key Laboratory of Underwater Acoustic Technology under Grant JCKYS2022604SSJS007.
文摘The Underwater Acoustic(UWA)channel is bandwidth-constrained and experiences doubly selective fading.It is challenging to acquire perfect channel knowledge for Orthogonal Frequency Division Multiplexing(OFDM)communications using a finite number of pilots.On the other hand,Deep Learning(DL)approaches have been very successful in wireless OFDM communications.However,whether they will work underwater is still a mystery.For the first time,this paper compares two categories of DL-based UWA OFDM receivers:the DataDriven(DD)method,which performs as an end-to-end black box,and the Model-Driven(MD)method,also known as the model-based data-driven method,which combines DL and expert OFDM receiver knowledge.The encoder-decoder framework and Convolutional Neural Network(CNN)structure are employed to establish the DD receiver.On the other hand,an unfolding-based Minimum Mean Square Error(MMSE)structure is adopted for the MD receiver.We analyze the characteristics of different receivers by Monte Carlo simulations under diverse communications conditions and propose a strategy for selecting a proper receiver under different communication scenarios.Field trials in the pool and sea are also conducted to verify the feasibility and advantages of the DL receivers.It is observed that DL receivers perform better than conventional receivers in terms of bit error rate.
基金We are grateful for financial supports from National Natural Science Foundation of China(62035003,61775117)China Postdoctoral Science Foundation(BX2021140)Tsinghua University Initiative Scientific Research Program(20193080075).
文摘Deep learning offers a novel opportunity to achieve both high-quality and high-speed computer-generated holography(CGH).Current data-driven deep learning algorithms face the challenge that the labeled training datasets limit the training performance and generalization.The model-driven deep learning introduces the diffraction model into the neural network.It eliminates the need for the labeled training dataset and has been extensively applied to hologram generation.However,the existing model-driven deep learning algorithms face the problem of insufficient constraints.In this study,we propose a model-driven neural network capable of high-fidelity 4K computer-generated hologram generation,called 4K Diffraction Model-driven Network(4K-DMDNet).The constraint of the reconstructed images in the frequency domain is strengthened.And a network structure that combines the residual method and sub-pixel convolution method is built,which effectively enhances the fitting ability of the network for inverse problems.The generalization of the 4K-DMDNet is demonstrated with binary,grayscale and 3D images.High-quality full-color optical reconstructions of the 4K holograms have been achieved at the wavelengths of 450 nm,520 nm,and 638 nm.
文摘Model-Driven Engineering (MDE) by reframing software development as the transformation of high-level models, promises lots of gains to Software Engineering in terms of productivity, quality and reusability. Although a number of empirical studies have established the reality of these gains, there are still lots of reluctances toward the adoption of MDE in practice. This resistance can be explained by several technological and social factors among which a natural scepticism toward novel approaches. In this paper we attempt to provide arguments to help alleviate this scepticism by conducting an assessment of a MDE approach. Our goal is to show that although this MDE is novel, it retains similarities with the conventional Software Engineering approach while automating aspects of it.
文摘Although the Model-Driven paradigm is being accepted in the research environment as a very useful and powerful option for effective software development, its real application in the enterprise context is still a challenge for software engineering. Several causes can be stacked out, but one of them can be the lack of tool support for the efficient application of this paradigm. This paper presents a set of tools, grouped in a suite named NDT-Suite, which under the Model-Driven paradigm offer a suitable solution for software development. These tools explore different options that this paradigm can improve such as, development, quality assurance or requirement treatment. Besides, this paper analyses how they are being successfully applied in the industry.
文摘The IEC 61131-3 standard defines a model and a set of programming languages for the development of industrial automation software. It is widely accepted by industry and most of the commercial tool vendors advertise compliance with it. On the other side, Model Driven Development (MDD) has been proved as a quite successful paradigm in general-purpose computing. This was the motivation for exploiting the benefits of MDD in the industrial automation domain. With the emerging IEC 61131 specification that defines an object-oriented (OO) extension to the function block model, there will be a push to the industry to better exploit the benefits of MDD in automation systems development. This work discusses possible alternatives to integrate the current but also the emerging specification of IEC 61131 in the model driven development process of automation systems. IEC 61499, UML and SysML are considered as possible alternatives to allow the developer to work in higher layers of abstraction than the one supported by IEC 61131 and to more effectively move from requirement specifications into the implementation model of the system.
文摘Web Service Composition provides an opportunity for enterprises to increase the ability to adapt themselves to frequent changes in users' requirements by integrating existing services. Our research has focused on proposing a framework to support dynamic composition and to use both SOAP-based and RESTful Web services simultaneously in composite services. In this paper a framework called "Model-driven Dynamic Composition of Heterogeneous Service" (MDCHeS) is introduced. It is elaborated in three different ways;each represents a particular view of the framework: data view, which consists of a Meta model and composition elements as well their relationships;process view, which introduces composition phases and used models in each phase;and component view, which shows an abstract view of the components and their interactions. In order to increase the dynamicity of MDCHeS framework, Model Driven Architecture and proxy based ideas are used.
基金This work was supported in part by the National Key Research and Development Program(2018YFA0701602)the National Natural Science Foundation of China for Distinguished Young Scholars of China(Nos.61625106,61531011)+1 种基金The work of C.K.Wen was supported in part by the Ministry of Science and Technology of Taiwan(MOST 106-2221-E-110-019)the ITRI in Hsinchu,Taiwan,China。
文摘Low-resolution analog-to-digital converter(ADC)is a promising solution to reduce hardware cost and power consumption in generalized frequency division multiplexing(GFDM)systems.The severe nonlinear distortion of ADCs and the non-orthogonality of GFDM make receiver design a great challenge.In this paper,we propose a novel model-driven receiver architecture for GFDM with low-resolution ADCs.Orthogonal approximate message passing(OAMP)framework is combined with the classical linear estimator in this work to create a robust iterative receiver for GFDM systems with low-precision ADCs.The corresponding model-driven network is organized based on the proposed novel iterative algorithm according to the procedures of the receiver.The network of OAMP can reduce the gap between the approximate algorithm and the Bayesian optimal result due to the information loss of ADCs.The signal flow of the neural network is designed by unfolding the iterative algorithms for channel estimation and data detection.Numerical results are provided to show that the proposed OAMP-based receiver algorithm outperforms traditional receivers and the model-driven network can further improve the system performance on the basis of the corresponding novel algorithm.
基金the Special Foundation for Basic Science and Frontier Technology Research Program of Chongqing,China(No.cstc2017jcyjAX0295)the Capacity Development Foundation of Southwest University,China(No.SWU116007)the National Natural Science Foundation of China(Nos.62032019,61732019,61672435,and 61811530327)。
文摘Cyber-physical systems(CPSs)have emerged as a potential enabling technology to handle the challenges in social and economic sustainable development.Since it was proposed in 2006,intensive research has been conducted,showing that the construction of a CPS is a hard and complex engineering process due to the nature of integrating a large number of heterogeneous subsystems.Among other approaches to dealing with the complex design issues,model-driven design of CPSs has shown its advantages.In this review paper,we present a survey of research on model-driven development of CPSs.We are concerned mainly with the widely used methods,techniques,and tools,and discuss how these are applied to CPSs.We also present comparative analyses on the surveyed techniques and tools from various perspectives,including their modeling languages,functionalities,and the challenges which they address in CPS design.With our understanding of the surveyed methods,we believe that model-driven approaches are an inevitable choice in building CPSs and further research effort is needed in the development of model-driven theories,techniques,and tools.We also argue that a unified modeling platform is needed.Such a platform would benefit research in the academic community and practical development in industry,and improve the collaboration between these two communities.
文摘Platelets,one of the most significant materials in treating leukemia,have a limited shelf life of approximately five days.Because platelets cannot be manufactured and can only be centrifuged from whole or donated blood directly,an accurate ordering policy is necessary for the efficient use of this limited blood resource.Given this motivation,the present study examines an ordering policy for platelets to minimize the expected shortage and overage.Rather than using the two-step model-driven method that first fits a demand distribution and then optimizes the order quantity,we solve the issue using an integrated datadriven method.Specifically,the data-driven method works directly with demand data and does not rely on the assumption of demand distribution.Consequently,we derive theoretical insights into the optimal solutions.Through a comparative analysis,we find that the data-driven method has a mean anchoring effect,and the amounts of shortage and overage reduced by this method are greater than those reduced by the model-driven method.Finally,we present an extended model with the service level requirement and conclude that the order decided by the data-driven method can precisely satisfy the service level requirement;however,the order decided by the model-driven method may be either higher or lower than the service level requirement and can lead to a higher cost.
基金The work was supported by the National Key Research and Development Program of China under Grant No. 2017YFB1001801, the National Natural Science Foundation of China under Grant Nos. 61702263, 61761136003, and 61373011, the Natural Science Foundation of Jiangsu Province of China under Grant No. BK20171427, and the Fundamental Research Funds for the Central Universities of China under Grant No. 30917011322.
文摘Activity-oriented context-aware （AOCA） applications are representative in pervasive computing. These appli- cations recognize daily-life human activities, perceive the environment status related to the activities, and react to ensure the smooth performance of the activities. Existing research proposed a specific light-weight, incremental method to support the development of such applications; however it is not easy to learn and use. This paper aims to facilitate the development of such applications and improve the productivity of developers. We propose AocML, a textual domain-specific language which provides a high-level abstraction of AOCA applications. Specifically, we first show the software model of AOCA applications and the abstract syntax of AocML. Then, we introduce the concrete syntax of AocML. We also implement the tools for AocML, including the development environment as well as the generation of Java code and ontology specification. Moreover, we use a case study and evaluation to demonstrate the advantages of AocML.
基金supported by the National Natural Science Foundation of China(Grant Nos.52208166 and 52108135)the National Key Research and Development Program of China(No.2021YFB2600900)+1 种基金the Science and Technology Innovation Program of Hunan Province(No.2022RC1186)the Aid program for Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan Province.
文摘Reasonable prediction of concrete creep is the basis of studying long-term deflection of concrete structures.In this paper,a hybrid model-driven and data-driven(HMD)method for predicting concrete creep is proposed by using the sequence integration strategy.Then,a novel uncertainty prediction model(UPM)is developed considering uncertainty quantification.Finally,the effectiveness of the proposed method is validated by using the North-western University(NU)database of creep,and the effect of uncertainty on prediction results are also discussed.The analysis results show that the proposed HMD method outperforms the model-driven and three data-driven methods,including the genetic algorithm-back propagation neural network(GA-BPNN),particle swarm optimization-support vector regression(PSO-SVR)and convolutional neural network only method,in accuracy and time efficiency.The proposed UPM of concrete creep not only ensures relatively good prediction accuracy,but also quantifies the model and measurement uncertainties during the prediction process.Additionally,although incorporating measurement uncertainty into concrete creep prediction can improve the prediction performance of UPM,the prediction interval of the creep compliance is more sensitive to model uncertainty than to measurement uncertainty,and the mean contribution of variance attributed to the model uncertainty to the total variance is about 90%.
文摘As a disruptive technology,the blockchain is continuously finding novel application contexts,bringing new opportunities and radical changes.In this paper,we use blockchain as a communication infrastructure to support multi-party business processes.In particular,through smart contracts specifically generated by the mentioned business process,it is possible to derive a trustable infrastructure enabling the interaction among parties.Moreover,the emergence of different blockchain technologies,satisfying different characteristics,gives the possibility to support the same business process dealing with different non-functional needs.In this paper,we propose a novel engineering methodology supported by a practical framework called Multi-Chain.It permits to derive,using a model-driven strategy,a blockchain-based infrastructure,that can be deployed over a specific blockchain technology(e.g.,Ethereum or Hyperledger Fabric).The objective is to permit the single definition and multiple deployments of the business process,to deliver the same functionalities,but satisfying different nonfunctional needs.In such a way,organisations willing to cooperate can select the multi-party business process and the blockchain technology they would like to use to satisfy their needs.Using Multi-Chain,they will be able to automatically derive from a Business Process Modelling Notation(BPMN)choreography diagram a blockchain infrastructure ready to be used.This overcomes the need to get acquainted with many details of the specific technology.
