Geomaterials are known to be non-associated materials. Granular soils therefore exhibit a variety of failure modes, with diffuse or localized kinematical patterns. In fact, the notion of failure itself can be confusin...Geomaterials are known to be non-associated materials. Granular soils therefore exhibit a variety of failure modes, with diffuse or localized kinematical patterns. In fact, the notion of failure itself can be confusing with regard to granular soils, because it is not associated with an obvious phenomenology. In this study, we built a proper framework, using the second-order work theory, to describe some failure modes in geomaterials based on energy conservation. The occurrence of failure is defined by an abrupt increase in kinetic energy. The increase in kinetic energy from an equilibrium state, under incremental loading, is shown to be equal to the difference between the external second-order work,involving the external loading parameters, and the internal second-order work, involving the constitutive properties of the material. When a stress limit state is reached, a certain stress component passes through a maximum value and then may decrease. Under such a condition, if a certain additional external loading is applied, the system fails, sharply increasing the strain rate. The internal stress is no longer able to balance the external stress, leading to a dynamic response of the specimen. As an illustration, the theoretical framework was applied to the well-known undrained triaxial test for loose soils. The influence of the loading control mode was clearly highlighted. It is shown that the plastic limit theory appears to be a particular case of this more general second-order work theory. When the plastic limit condition is met, the internal second-order work is nil. A class of incremental external loadings causes the kinetic energy to increase dramatically, leading to the sudden collapse of the specimen, as observed in laboratory.展开更多
This paper studies synchronization of all nodes in a fractional-order complex dynamic network. An adaptive control strategy for synchronizing a dynamic network is proposed. Based on the Lyapunov stability theory, this...This paper studies synchronization of all nodes in a fractional-order complex dynamic network. An adaptive control strategy for synchronizing a dynamic network is proposed. Based on the Lyapunov stability theory, this paper shows that tracking errors of all nodes in a fractional-order complex network converge to zero. This simple yet prac- tical scheme can be used in many networks such as small-world networks and scale-free networks. Unlike the existing methods which assume the coupling configuration among the nodes of the network with diffusivity, symmetry, balance, or irreducibility, in this case, these assumptions are unnecessary, and the proposed adaptive strategy is more feasible. Two examples are presented to illustrate effectiveness of the proposed method.展开更多
台区电力工单记录反映了台区运行工况和用户需求,是制定台区用电安全管理制度和满足台区用户用电需求的重要依据。针对台区电力工单高复杂性和强专业性给台区工单分类带来的难题,提出一种融合标签平滑(LS)与预训练语言模型的台区电力工...台区电力工单记录反映了台区运行工况和用户需求,是制定台区用电安全管理制度和满足台区用户用电需求的重要依据。针对台区电力工单高复杂性和强专业性给台区工单分类带来的难题,提出一种融合标签平滑(LS)与预训练语言模型的台区电力工单分类模型(MiniRBT-LSTM-GAT)。首先,利用预训练模型计算电力工单文本中的字符级特征向量表示;其次,采用双向长短期记忆网络(BiLSTM)捕捉电力文本序列中的依赖关系;再次,通过图注意力网络(GAT)聚焦对文本分类贡献大的特征信息;最后,利用LS改进损失函数以提高模型的分类精度。所提模型与当前主流的文本分类算法在农网台区电力工单数据集(RSPWO)、浙江省95598电力工单数据集(ZJPWO)和THUCNews(TsingHua University Chinese News)数据集上的实验结果表明,与电力审计文本多粒度预训练语言模型(EPAT-BERT)相比,所提模型在RSPWO、ZJPWO上的查准率和F1值分别提升了2.76、2.02个百分点和1.77、1.40个百分点;与胶囊神经网络模型BRsyn-caps(capsule network based on BERT and dependency syntax)相比,所提模型在THUCNews数据集上的查准率和准确率分别提升了0.76和0.71个百分点。可见,所提模型有效提升了台区电力工单分类的性能,并在THUCNews数据集上表现良好,验证了模型的通用性。展开更多
智能工单系统是企业数字化转型的核心支撑平台。当前,智能工单系统面临多源异构数据的跨模态冗余及语义冲突问题,传统基于单模态处理架构的大语言模型(Large Language Model,LLM)存在关键信息漏检率高、数据清洗效果差的缺陷,严重制约...智能工单系统是企业数字化转型的核心支撑平台。当前,智能工单系统面临多源异构数据的跨模态冗余及语义冲突问题,传统基于单模态处理架构的大语言模型(Large Language Model,LLM)存在关键信息漏检率高、数据清洗效果差的缺陷,严重制约了工单系统智能化发展。针对该问题,混合专家模型(Mixture of Experts,MoE)可通过动态路由机制自适应分配多模态数据至特定专家网络,在提升跨模态特征融合精度的同时显著优化计算效率。基于此,提出一种基于混合专家模型的多模态工单数据智能处理方法。首先基于DeepSeekMoE架构设计了一种语义分析模型,以实现跨模态数据的特征解耦与关键内容提取。其次提出基于Thinker-Talker的多模态特征融合架构,有效提升冗余数据利用率与语义一致性。最后设计非结构化数据清洗与结构化表单生成算法,完成原始数据的降噪清洗与语义增强,输出符合规范的结构化工单。消融实验表明,该方法在私有化数据集上的信息提取精度达92.7%,较传统工单处理方式的标准符合度提升36.2%,为智能工单系统多模态数据处理提供了可扩展的技术范式。展开更多
目的:通过分析某三甲医院各临床科室接诉即办工单量的影响因素,探索降低工单量的关键指标,为优化管理流程提供依据。方法:本研究整理了2022年1月—2022年12月北京市某三甲医院42个临床科室的接诉即办工单量数据,采用广义线性模型(genera...目的:通过分析某三甲医院各临床科室接诉即办工单量的影响因素,探索降低工单量的关键指标,为优化管理流程提供依据。方法:本研究整理了2022年1月—2022年12月北京市某三甲医院42个临床科室的接诉即办工单量数据,采用广义线性模型(generalized linear model,GLM)建立回归方程,以最大似然估计算法求解接诉即办工单量的影响因素,并结合临床实践解释每个因素对工单量的影响程度。结果:经过统计学分析发现门诊人次数量(β=-19.738,P=0.050)、病房病死率(β=-7.688,P=0.050)、床位使用率(β=0.751,P=0.033)与工单总量密切相关。结论:医院应从合理规划床位资源,控制病床使用率;加强危重患者管理,降低病房病死率;加强门诊精细化管理等方面控制接诉即办工单总量;要针对不同的原因采取措施,提升医院的管理水平,以实现医院“接诉即办”工作常态化长效化。展开更多
基金the French Research Network Me Ge (Multiscale and Multiphysics Couplings in Geo-environmental Mechanics GDR CNRS 3176/2340, 2008e2015) for having supported this work
文摘Geomaterials are known to be non-associated materials. Granular soils therefore exhibit a variety of failure modes, with diffuse or localized kinematical patterns. In fact, the notion of failure itself can be confusing with regard to granular soils, because it is not associated with an obvious phenomenology. In this study, we built a proper framework, using the second-order work theory, to describe some failure modes in geomaterials based on energy conservation. The occurrence of failure is defined by an abrupt increase in kinetic energy. The increase in kinetic energy from an equilibrium state, under incremental loading, is shown to be equal to the difference between the external second-order work,involving the external loading parameters, and the internal second-order work, involving the constitutive properties of the material. When a stress limit state is reached, a certain stress component passes through a maximum value and then may decrease. Under such a condition, if a certain additional external loading is applied, the system fails, sharply increasing the strain rate. The internal stress is no longer able to balance the external stress, leading to a dynamic response of the specimen. As an illustration, the theoretical framework was applied to the well-known undrained triaxial test for loose soils. The influence of the loading control mode was clearly highlighted. It is shown that the plastic limit theory appears to be a particular case of this more general second-order work theory. When the plastic limit condition is met, the internal second-order work is nil. A class of incremental external loadings causes the kinetic energy to increase dramatically, leading to the sudden collapse of the specimen, as observed in laboratory.
基金Project supported by the National Natural Science Foundation of China(Nos.11672231 and11672233)the Natural Science Foundation of Shaanxi Province(No.2016JM1010)+1 种基金the Fundamental Research Funds for the Central Universities(No.3102017AX008)the Seed Foundation of Innovation and Creation for Graduate Students at the Northwestern Polytechnical University of China(No.Z2017187)
文摘This paper studies synchronization of all nodes in a fractional-order complex dynamic network. An adaptive control strategy for synchronizing a dynamic network is proposed. Based on the Lyapunov stability theory, this paper shows that tracking errors of all nodes in a fractional-order complex network converge to zero. This simple yet prac- tical scheme can be used in many networks such as small-world networks and scale-free networks. Unlike the existing methods which assume the coupling configuration among the nodes of the network with diffusivity, symmetry, balance, or irreducibility, in this case, these assumptions are unnecessary, and the proposed adaptive strategy is more feasible. Two examples are presented to illustrate effectiveness of the proposed method.
文摘台区电力工单记录反映了台区运行工况和用户需求,是制定台区用电安全管理制度和满足台区用户用电需求的重要依据。针对台区电力工单高复杂性和强专业性给台区工单分类带来的难题,提出一种融合标签平滑(LS)与预训练语言模型的台区电力工单分类模型(MiniRBT-LSTM-GAT)。首先,利用预训练模型计算电力工单文本中的字符级特征向量表示;其次,采用双向长短期记忆网络(BiLSTM)捕捉电力文本序列中的依赖关系;再次,通过图注意力网络(GAT)聚焦对文本分类贡献大的特征信息;最后,利用LS改进损失函数以提高模型的分类精度。所提模型与当前主流的文本分类算法在农网台区电力工单数据集(RSPWO)、浙江省95598电力工单数据集(ZJPWO)和THUCNews(TsingHua University Chinese News)数据集上的实验结果表明,与电力审计文本多粒度预训练语言模型(EPAT-BERT)相比,所提模型在RSPWO、ZJPWO上的查准率和F1值分别提升了2.76、2.02个百分点和1.77、1.40个百分点;与胶囊神经网络模型BRsyn-caps(capsule network based on BERT and dependency syntax)相比,所提模型在THUCNews数据集上的查准率和准确率分别提升了0.76和0.71个百分点。可见,所提模型有效提升了台区电力工单分类的性能,并在THUCNews数据集上表现良好,验证了模型的通用性。
文摘智能工单系统是企业数字化转型的核心支撑平台。当前,智能工单系统面临多源异构数据的跨模态冗余及语义冲突问题,传统基于单模态处理架构的大语言模型(Large Language Model,LLM)存在关键信息漏检率高、数据清洗效果差的缺陷,严重制约了工单系统智能化发展。针对该问题,混合专家模型(Mixture of Experts,MoE)可通过动态路由机制自适应分配多模态数据至特定专家网络,在提升跨模态特征融合精度的同时显著优化计算效率。基于此,提出一种基于混合专家模型的多模态工单数据智能处理方法。首先基于DeepSeekMoE架构设计了一种语义分析模型,以实现跨模态数据的特征解耦与关键内容提取。其次提出基于Thinker-Talker的多模态特征融合架构,有效提升冗余数据利用率与语义一致性。最后设计非结构化数据清洗与结构化表单生成算法,完成原始数据的降噪清洗与语义增强,输出符合规范的结构化工单。消融实验表明,该方法在私有化数据集上的信息提取精度达92.7%,较传统工单处理方式的标准符合度提升36.2%,为智能工单系统多模态数据处理提供了可扩展的技术范式。
文摘目的:通过分析某三甲医院各临床科室接诉即办工单量的影响因素,探索降低工单量的关键指标,为优化管理流程提供依据。方法:本研究整理了2022年1月—2022年12月北京市某三甲医院42个临床科室的接诉即办工单量数据,采用广义线性模型(generalized linear model,GLM)建立回归方程,以最大似然估计算法求解接诉即办工单量的影响因素,并结合临床实践解释每个因素对工单量的影响程度。结果:经过统计学分析发现门诊人次数量(β=-19.738,P=0.050)、病房病死率(β=-7.688,P=0.050)、床位使用率(β=0.751,P=0.033)与工单总量密切相关。结论:医院应从合理规划床位资源,控制病床使用率;加强危重患者管理,降低病房病死率;加强门诊精细化管理等方面控制接诉即办工单总量;要针对不同的原因采取措施,提升医院的管理水平,以实现医院“接诉即办”工作常态化长效化。
