随着传感、信号处理和通信技术的快速发展,关于网络控制系统(Networked control systems,NCSs)的研究引起了极大的关注.本文拟回顾关于网络控制系统的最新研究进展.为揭示反馈通信网络对控制系统的影响,主要讨论了为满足不同控制目的所...随着传感、信号处理和通信技术的快速发展,关于网络控制系统(Networked control systems,NCSs)的研究引起了极大的关注.本文拟回顾关于网络控制系统的最新研究进展.为揭示反馈通信网络对控制系统的影响,主要讨论了为满足不同控制目的所需的各种网络条件,例如:在时变信道的环境下,保证线性系统可镇定性所需的最低编码率;在间断观测的环境下,保证卡尔曼滤波器稳定性的临界丢包条件;在时不变连接图的环境下,达到线性多自主体系统趋同性所需的网络拓扑结构;在通信资源有限的情况下,基于事件驱动的采样与控制方法等.展开更多
Nutritional concerns, linear growth deficiency, and delayed puberty are currently detected in up to 85% of patients with Crohn's disease(CD) diagnosed at childhood. To provide advice on how to assess and manage nu...Nutritional concerns, linear growth deficiency, and delayed puberty are currently detected in up to 85% of patients with Crohn's disease(CD) diagnosed at childhood. To provide advice on how to assess and manage nutritional concerns in these patients, a Medline search was conducted using "pediatric inflammatory bowel disease", "pediatric Crohn's disease", "linear growth","pubertal growth", "bone health", and "vitamin D" as key words. Clinical trials, systematic reviews, and metaanalyses published between 2008 and 2013 were selected to produce this narrative review. Studies referring to earlier periods were also considered if the data was relevant to our review. Although current treatment strategies for CD that include anti-tumor necrosis factor-αtherapy have been shown to improve patients' growth rate, linear growth deficiencies are still common. In pediatric CD patients, prolonged diagnostic delay, high initial activity index, and stricturing/penetrating typeof behavior may cause growth deficiencies(in weight and height) and delayed puberty, with several studies reporting that these patients may not reach an optimal bone mass. Glucocorticoids and inflammation inhibit bone formation, though their impact on skeletal modeling remains unclear. Long-term control of active inflammation and an adequate intake of nutrients are both fundamental in promoting normal puberty. Recent evidence suggests that recombinant growth factor therapy is effective in improving short-term linear growth in selected patients, but is of limited benefit for ameliorating mucosal disease and reducing clinical disease activity. The authors conclude that an intense initial treatment(taking a "top-down" approach, with the early introduction of immunomodulatory treatment) may be justified to induce and maintain remission so that the growth of children with CD can catch up, ideally before puberty. Exclusive enteral nutrition has a key role in inducing remission and improving patients' nutritional status.展开更多
Linear induction motors are superior to rotary induction motors in direct drive systems because they can generate direct forward thrust force independent of mechanical transmission.However,due to the large air gap and...Linear induction motors are superior to rotary induction motors in direct drive systems because they can generate direct forward thrust force independent of mechanical transmission.However,due to the large air gap and cut-open magnetic circuit,their efficiency and power factor are quite low,which limit their application in high power drive systems.To attempt this challenge,this work presents a system-level optimization method for a single-sided linear induction motor drive system.Not only the motor but also the control system is included in the analysis.A system-level optimization method is employed to gain optimal steady-state and dynamic performances.To validate the effectiveness of the proposed optimization method,experimental results on a linear induction motor drive are presented and discussed.展开更多
This paper deals with analysis and synthesis problems of spatially interconnected systems where communicated information may get lost between subsystems. Spatial shift operator and temporal forward shift operator are ...This paper deals with analysis and synthesis problems of spatially interconnected systems where communicated information may get lost between subsystems. Spatial shift operator and temporal forward shift operator are introduced to model the interconnected systems as discrete time-space multidimensional linear systems with Markovian jumping parameters which reflect the state of communication channels. To ensure the whole system＇s well-posedness and mean square stability for a given packet loss rate, a condition is derived through analysis. Then a procedure of designing distributed dynamic output feedback controllers is proposed. The controllers have the same structure as the plants and are solved within the linear matrix inequality （LMI） framework. Finally, we apply these results to study the effect of communication losses on the multiple vehicle platoon control system, which further illustrates the effectiveness of the proposed model and method.展开更多
As image manipulation technology advances rapidly,the malicious use of image tampering has alarmingly escalated,posing a significant threat to social stability.In the realm of image tampering localization,accurately l...As image manipulation technology advances rapidly,the malicious use of image tampering has alarmingly escalated,posing a significant threat to social stability.In the realm of image tampering localization,accurately localizing limited samples,multiple types,and various sizes of regions remains a multitude of challenges.These issues impede the model’s universality and generalization capability and detrimentally affect its performance.To tackle these issues,we propose FL-MobileViT-an improved MobileViT model devised for image tampering localization.Our proposed model utilizes a dual-stream architecture that independently processes the RGB and noise domain,and captures richer traces of tampering through dual-stream integration.Meanwhile,the model incorporating the Focused Linear Attention mechanism within the lightweight network(MobileViT).This substitution significantly diminishes computational complexity and resolves homogeneity problems associated with traditional Transformer attention mechanisms,enhancing feature extraction diversity and improving the model’s localization performance.To comprehensively fuse the generated results from both feature extractors,we introduce the ASPP architecture for multi-scale feature fusion.This facilitates a more precise localization of tampered regions of various sizes.Furthermore,to bolster the model’s generalization ability,we adopt a contrastive learning method and devise a joint optimization training strategy that leverages fused features and captures the disparities in feature distribution in tampered images.This strategy enables the learning of contrastive loss at various stages of the feature extractor and employs it as an additional constraint condition in conjunction with cross-entropy loss.As a result,overfitting issues are effectively alleviated,and the differentiation between tampered and untampered regions is enhanced.Experimental evaluations on five benchmark datasets(IMD-20,CASIA,NIST-16,Columbia and Coverage)validate the effectiveness of our proposed model.展开更多
In oil and gas exploration,elucidating the complex interdependencies among geological variables is paramount.Our study introduces the application of sophisticated regression analysis method at the forefront,aiming not...In oil and gas exploration,elucidating the complex interdependencies among geological variables is paramount.Our study introduces the application of sophisticated regression analysis method at the forefront,aiming not just at predicting geophysical logging curve values but also innovatively mitigate hydrocarbon depletion observed in geochemical logging.Through a rigorous assessment,we explore the efficacy of eight regression models,bifurcated into linear and nonlinear groups,to accommodate the multifaceted nature of geological datasets.Our linear model suite encompasses the Standard Equation,Ridge Regression,Least Absolute Shrinkage and Selection Operator,and Elastic Net,each presenting distinct advantages.The Standard Equation serves as a foundational benchmark,whereas Ridge Regression implements penalty terms to counteract overfitting,thus bolstering model robustness in the presence of multicollinearity.The Least Absolute Shrinkage and Selection Operator for variable selection functions to streamline models,enhancing their interpretability,while Elastic Net amalgamates the merits of Ridge Regression and Least Absolute Shrinkage and Selection Operator,offering a harmonized solution to model complexity and comprehensibility.On the nonlinear front,Gradient Descent,Kernel Ridge Regression,Support Vector Regression,and Piecewise Function-Fitting methods introduce innovative approaches.Gradient Descent assures computational efficiency in optimizing solutions,Kernel Ridge Regression leverages the kernel trick to navigate nonlinear patterns,and Support Vector Regression is proficient in forecasting extremities,pivotal for exploration risk assessment.The Piecewise Function-Fitting approach,tailored for geological data,facilitates adaptable modeling of variable interrelations,accommodating abrupt data trend shifts.Our analysis identifies Ridge Regression,particularly when augmented by Piecewise Function-Fitting,as superior in recouping hydrocarbon losses,and underscoring its utility in resource quantification refinement.展开更多
文摘随着传感、信号处理和通信技术的快速发展,关于网络控制系统(Networked control systems,NCSs)的研究引起了极大的关注.本文拟回顾关于网络控制系统的最新研究进展.为揭示反馈通信网络对控制系统的影响,主要讨论了为满足不同控制目的所需的各种网络条件,例如:在时变信道的环境下,保证线性系统可镇定性所需的最低编码率;在间断观测的环境下,保证卡尔曼滤波器稳定性的临界丢包条件;在时不变连接图的环境下,达到线性多自主体系统趋同性所需的网络拓扑结构;在通信资源有限的情况下,基于事件驱动的采样与控制方法等.
文摘Nutritional concerns, linear growth deficiency, and delayed puberty are currently detected in up to 85% of patients with Crohn's disease(CD) diagnosed at childhood. To provide advice on how to assess and manage nutritional concerns in these patients, a Medline search was conducted using "pediatric inflammatory bowel disease", "pediatric Crohn's disease", "linear growth","pubertal growth", "bone health", and "vitamin D" as key words. Clinical trials, systematic reviews, and metaanalyses published between 2008 and 2013 were selected to produce this narrative review. Studies referring to earlier periods were also considered if the data was relevant to our review. Although current treatment strategies for CD that include anti-tumor necrosis factor-αtherapy have been shown to improve patients' growth rate, linear growth deficiencies are still common. In pediatric CD patients, prolonged diagnostic delay, high initial activity index, and stricturing/penetrating typeof behavior may cause growth deficiencies(in weight and height) and delayed puberty, with several studies reporting that these patients may not reach an optimal bone mass. Glucocorticoids and inflammation inhibit bone formation, though their impact on skeletal modeling remains unclear. Long-term control of active inflammation and an adequate intake of nutrients are both fundamental in promoting normal puberty. Recent evidence suggests that recombinant growth factor therapy is effective in improving short-term linear growth in selected patients, but is of limited benefit for ameliorating mucosal disease and reducing clinical disease activity. The authors conclude that an intense initial treatment(taking a "top-down" approach, with the early introduction of immunomodulatory treatment) may be justified to induce and maintain remission so that the growth of children with CD can catch up, ideally before puberty. Exclusive enteral nutrition has a key role in inducing remission and improving patients' nutritional status.
文摘Linear induction motors are superior to rotary induction motors in direct drive systems because they can generate direct forward thrust force independent of mechanical transmission.However,due to the large air gap and cut-open magnetic circuit,their efficiency and power factor are quite low,which limit their application in high power drive systems.To attempt this challenge,this work presents a system-level optimization method for a single-sided linear induction motor drive system.Not only the motor but also the control system is included in the analysis.A system-level optimization method is employed to gain optimal steady-state and dynamic performances.To validate the effectiveness of the proposed optimization method,experimental results on a linear induction motor drive are presented and discussed.
文摘This paper deals with analysis and synthesis problems of spatially interconnected systems where communicated information may get lost between subsystems. Spatial shift operator and temporal forward shift operator are introduced to model the interconnected systems as discrete time-space multidimensional linear systems with Markovian jumping parameters which reflect the state of communication channels. To ensure the whole system＇s well-posedness and mean square stability for a given packet loss rate, a condition is derived through analysis. Then a procedure of designing distributed dynamic output feedback controllers is proposed. The controllers have the same structure as the plants and are solved within the linear matrix inequality （LMI） framework. Finally, we apply these results to study the effect of communication losses on the multiple vehicle platoon control system, which further illustrates the effectiveness of the proposed model and method.
基金This study was funded by the Science and Technology Project in Xi’an(No.22GXFW0123)this work was supported by the Special Fund Construction Project of Key Disciplines in Ordinary Colleges and Universities in Shaanxi Province,the authors would like to thank the anonymous reviewers for their helpful comments and suggestions.
文摘As image manipulation technology advances rapidly,the malicious use of image tampering has alarmingly escalated,posing a significant threat to social stability.In the realm of image tampering localization,accurately localizing limited samples,multiple types,and various sizes of regions remains a multitude of challenges.These issues impede the model’s universality and generalization capability and detrimentally affect its performance.To tackle these issues,we propose FL-MobileViT-an improved MobileViT model devised for image tampering localization.Our proposed model utilizes a dual-stream architecture that independently processes the RGB and noise domain,and captures richer traces of tampering through dual-stream integration.Meanwhile,the model incorporating the Focused Linear Attention mechanism within the lightweight network(MobileViT).This substitution significantly diminishes computational complexity and resolves homogeneity problems associated with traditional Transformer attention mechanisms,enhancing feature extraction diversity and improving the model’s localization performance.To comprehensively fuse the generated results from both feature extractors,we introduce the ASPP architecture for multi-scale feature fusion.This facilitates a more precise localization of tampered regions of various sizes.Furthermore,to bolster the model’s generalization ability,we adopt a contrastive learning method and devise a joint optimization training strategy that leverages fused features and captures the disparities in feature distribution in tampered images.This strategy enables the learning of contrastive loss at various stages of the feature extractor and employs it as an additional constraint condition in conjunction with cross-entropy loss.As a result,overfitting issues are effectively alleviated,and the differentiation between tampered and untampered regions is enhanced.Experimental evaluations on five benchmark datasets(IMD-20,CASIA,NIST-16,Columbia and Coverage)validate the effectiveness of our proposed model.
文摘In oil and gas exploration,elucidating the complex interdependencies among geological variables is paramount.Our study introduces the application of sophisticated regression analysis method at the forefront,aiming not just at predicting geophysical logging curve values but also innovatively mitigate hydrocarbon depletion observed in geochemical logging.Through a rigorous assessment,we explore the efficacy of eight regression models,bifurcated into linear and nonlinear groups,to accommodate the multifaceted nature of geological datasets.Our linear model suite encompasses the Standard Equation,Ridge Regression,Least Absolute Shrinkage and Selection Operator,and Elastic Net,each presenting distinct advantages.The Standard Equation serves as a foundational benchmark,whereas Ridge Regression implements penalty terms to counteract overfitting,thus bolstering model robustness in the presence of multicollinearity.The Least Absolute Shrinkage and Selection Operator for variable selection functions to streamline models,enhancing their interpretability,while Elastic Net amalgamates the merits of Ridge Regression and Least Absolute Shrinkage and Selection Operator,offering a harmonized solution to model complexity and comprehensibility.On the nonlinear front,Gradient Descent,Kernel Ridge Regression,Support Vector Regression,and Piecewise Function-Fitting methods introduce innovative approaches.Gradient Descent assures computational efficiency in optimizing solutions,Kernel Ridge Regression leverages the kernel trick to navigate nonlinear patterns,and Support Vector Regression is proficient in forecasting extremities,pivotal for exploration risk assessment.The Piecewise Function-Fitting approach,tailored for geological data,facilitates adaptable modeling of variable interrelations,accommodating abrupt data trend shifts.Our analysis identifies Ridge Regression,particularly when augmented by Piecewise Function-Fitting,as superior in recouping hydrocarbon losses,and underscoring its utility in resource quantification refinement.
