Traditional requirements method has some problems when it is used for large distributed systems. Multiple viewpoints oriented requirements method (MVORM) is a new method for resolving these problems. This paper develo...Traditional requirements method has some problems when it is used for large distributed systems. Multiple viewpoints oriented requirements method (MVORM) is a new method for resolving these problems. This paper develops two generic formal frameworks of MVORM, framework based on refinement relation (FBRR) and framework based on implementation relation (FBIR). They are generic, because no assumptions are made about the development process or the formal description languages to be used. Three kinds of specification relations and three kinds of specification transformations are discussed over FBIR and FBRR. This paper also compares the equivalence between FBIR and FBRR. We point out that an equivalent FBIR can be found for any FBRR, but reverse transformation is not always possible. We think FBIR is better than FBRR on most cases.展开更多
Conventional gradient-based full waveform inversion (FWI) is a local optimization, which is highly dependent on the initial model and prone to trapping in local minima. Globally optimal FWI that can overcome this limi...Conventional gradient-based full waveform inversion (FWI) is a local optimization, which is highly dependent on the initial model and prone to trapping in local minima. Globally optimal FWI that can overcome this limitation is particularly attractive, but is currently limited by the huge amount of calculation. In this paper, we propose a globally optimal FWI framework based on GPU parallel computing, which greatly improves the efficiency, and is expected to make globally optimal FWI more widely used. In this framework, we simplify and recombine the model parameters, and optimize the model iteratively. Each iteration contains hundreds of individuals, each individual is independent of the other, and each individual contains forward modeling and cost function calculation. The framework is suitable for a variety of globally optimal algorithms, and we test the framework with particle swarm optimization algorithm for example. Both the synthetic and field examples achieve good results, indicating the effectiveness of the framework. .展开更多
近年来,通信技术的持续演进导致通信网络的能耗显著增加。随着人工智能(AI,artificial intelligence)技术与算法在通信网络中的广泛应用和深度部署,未来6G智能通信网络架构和技术演进将对通信网络的节能减排带来更为严峻的挑战。基于边...近年来,通信技术的持续演进导致通信网络的能耗显著增加。随着人工智能(AI,artificial intelligence)技术与算法在通信网络中的广泛应用和深度部署,未来6G智能通信网络架构和技术演进将对通信网络的节能减排带来更为严峻的挑战。基于边缘计算和分布式联邦学习的联邦边缘智能(FEI,federated edge intelligence)网络已被普遍认为是实现6G网络内生智能的关键路径之一。然而,如何评估和优化联邦边缘智能网络的综合碳排放量仍然是一大难题。为解决该问题,首先,提出了一种联邦边缘智能网络碳排放评估框架和方法。其次,基于该评估框架和方法提出3种联邦边缘智能网络碳排放优化方案,包括动态能量交易(DET,dynamic energy trading)、动态任务分配(DTA,dynamic task allocation)和动态能量交易与任务分配(DETA,dynamic energy trading and task allocation)。最后,通过自行搭建的真实硬件平台,并利用真实世界的碳强度数据集进行联邦边缘智能网络生命周期碳排放仿真。实验结果表明,3种优化方案均能在不同场景和约束条件下显著减少联邦边缘智能网络的碳排放,为下一代智能通信网络的可持续发展和实现绿色低碳6G网络提供了依据。展开更多
金属离子过量使用会造成环境污染,危及人类健康。因此,对相关金属离子进行检测显得尤为重要。发光金属有机框架(Luminescent metal-organic frameworks,LMOFs)因其具备高色纯度、超高孔隙率和可调结构等优势,被视为简单有效且有前途的...金属离子过量使用会造成环境污染,危及人类健康。因此,对相关金属离子进行检测显得尤为重要。发光金属有机框架(Luminescent metal-organic frameworks,LMOFs)因其具备高色纯度、超高孔隙率和可调结构等优势,被视为简单有效且有前途的荧光传感材料。本文以3,5-二(4-咪唑-1-基)吡啶(Bip)为主配体,1,4-萘二甲酸(1,4-ndc)为辅助配体,Ni^(2+)为中心离子,采取溶剂热法合成了一例二维金属有机框架[Ni_(2)(Bip)_(2)(1,4-ndc)_(2)(H_(2)O)_(6)](记为CUST-756,其中CUST是Changchun University of Science and Technology缩写),并通过合成后修饰法制备了Eu^(3+)@CUST-756复合发光材料。利用XRD、FT-IR和XPS对合成的CUST-756和Eu^(3+)@CUST-756复合材料进行了基础表征。并且采用荧光光谱对样品进行了发光特性、金属离子传感性能及其机理研究。实验结果表明,Eu^(3+)@CUST-756在甲醇溶液中具备优异的发光性能和良好的稳定性,Eu^(3+)的引入使得材料可用于金属阳离子Cr^(3+)、Fe^(3+)检测。Cr^(3+)离子的检出限(limit of detection,LOD)为5.44µmol·L^(-1);Fe^(3+)离子的LOD为7.51µmol·L^(-1),与大多数LMOFs性能相近。展开更多
基金Supported by Natural Science Foundation of Hubei Province (98J0 75 ) Ziqiang Technical Innovation Foundation ofWuhan Universi
文摘Traditional requirements method has some problems when it is used for large distributed systems. Multiple viewpoints oriented requirements method (MVORM) is a new method for resolving these problems. This paper develops two generic formal frameworks of MVORM, framework based on refinement relation (FBRR) and framework based on implementation relation (FBIR). They are generic, because no assumptions are made about the development process or the formal description languages to be used. Three kinds of specification relations and three kinds of specification transformations are discussed over FBIR and FBRR. This paper also compares the equivalence between FBIR and FBRR. We point out that an equivalent FBIR can be found for any FBRR, but reverse transformation is not always possible. We think FBIR is better than FBRR on most cases.
文摘Conventional gradient-based full waveform inversion (FWI) is a local optimization, which is highly dependent on the initial model and prone to trapping in local minima. Globally optimal FWI that can overcome this limitation is particularly attractive, but is currently limited by the huge amount of calculation. In this paper, we propose a globally optimal FWI framework based on GPU parallel computing, which greatly improves the efficiency, and is expected to make globally optimal FWI more widely used. In this framework, we simplify and recombine the model parameters, and optimize the model iteratively. Each iteration contains hundreds of individuals, each individual is independent of the other, and each individual contains forward modeling and cost function calculation. The framework is suitable for a variety of globally optimal algorithms, and we test the framework with particle swarm optimization algorithm for example. Both the synthetic and field examples achieve good results, indicating the effectiveness of the framework. .
文摘近年来,通信技术的持续演进导致通信网络的能耗显著增加。随着人工智能(AI,artificial intelligence)技术与算法在通信网络中的广泛应用和深度部署,未来6G智能通信网络架构和技术演进将对通信网络的节能减排带来更为严峻的挑战。基于边缘计算和分布式联邦学习的联邦边缘智能(FEI,federated edge intelligence)网络已被普遍认为是实现6G网络内生智能的关键路径之一。然而,如何评估和优化联邦边缘智能网络的综合碳排放量仍然是一大难题。为解决该问题,首先,提出了一种联邦边缘智能网络碳排放评估框架和方法。其次,基于该评估框架和方法提出3种联邦边缘智能网络碳排放优化方案,包括动态能量交易(DET,dynamic energy trading)、动态任务分配(DTA,dynamic task allocation)和动态能量交易与任务分配(DETA,dynamic energy trading and task allocation)。最后,通过自行搭建的真实硬件平台,并利用真实世界的碳强度数据集进行联邦边缘智能网络生命周期碳排放仿真。实验结果表明,3种优化方案均能在不同场景和约束条件下显著减少联邦边缘智能网络的碳排放,为下一代智能通信网络的可持续发展和实现绿色低碳6G网络提供了依据。
文摘金属离子过量使用会造成环境污染,危及人类健康。因此,对相关金属离子进行检测显得尤为重要。发光金属有机框架(Luminescent metal-organic frameworks,LMOFs)因其具备高色纯度、超高孔隙率和可调结构等优势,被视为简单有效且有前途的荧光传感材料。本文以3,5-二(4-咪唑-1-基)吡啶(Bip)为主配体,1,4-萘二甲酸(1,4-ndc)为辅助配体,Ni^(2+)为中心离子,采取溶剂热法合成了一例二维金属有机框架[Ni_(2)(Bip)_(2)(1,4-ndc)_(2)(H_(2)O)_(6)](记为CUST-756,其中CUST是Changchun University of Science and Technology缩写),并通过合成后修饰法制备了Eu^(3+)@CUST-756复合发光材料。利用XRD、FT-IR和XPS对合成的CUST-756和Eu^(3+)@CUST-756复合材料进行了基础表征。并且采用荧光光谱对样品进行了发光特性、金属离子传感性能及其机理研究。实验结果表明,Eu^(3+)@CUST-756在甲醇溶液中具备优异的发光性能和良好的稳定性,Eu^(3+)的引入使得材料可用于金属阳离子Cr^(3+)、Fe^(3+)检测。Cr^(3+)离子的检出限(limit of detection,LOD)为5.44µmol·L^(-1);Fe^(3+)离子的LOD为7.51µmol·L^(-1),与大多数LMOFs性能相近。
