In the era of Big Data,the attention economy has emerged as a core logic of capital accumulation,yet behavioral economic explanations fail to penetrate the unconscious drives and desire structures underlying attention...In the era of Big Data,the attention economy has emerged as a core logic of capital accumulation,yet behavioral economic explanations fail to penetrate the unconscious drives and desire structures underlying attention investment.This paper adopts Lacan’s topological framework of the three orders(the Real,the Symbolic,and the Imaginary)to conduct a psychoanalytic dissection of the attention economy.It argues that Big Data-driven attention mechanisms essentially manipulate desire across these three orders:algorithms,functioning as the“digital big Other,”exploit the Real’s traumatic surplus and the deferred structure of desire through infinite scroll and traumatic stimuli;regulate identity production in the Symbolic via visibility laws,social currency,and datafication;and construct narcissistic illusions in the Imaginary through filters,filter bubbles,and illusions of hyperconnection.Ultimately,the paper proposes an ethics of lucid attention,calling for critical algorithmic literacy,confrontation with the Real’s lack,dismantling of Imaginary illusions,and reclaiming sovereignty over attention-essential for preserving subjective dignity and human freedom in the digital age.展开更多
In the research of scientific field, it is often necessary to continuously observe different indicators of individuals at different times and analyze the observed results. Among them, variables are mainly of two types...In the research of scientific field, it is often necessary to continuously observe different indicators of individuals at different times and analyze the observed results. Among them, variables are mainly of two types: ordered variables and continuous variables. When analyzing data for different types of variables, it is necessary to consider the correlation between multiple indicators of an individual, and often perform joint analysis on variable observation data of multiple indicators of an individual at different times, in order to achieve more accurate and true analysis results. Joint analysis often yields more information than separate analysis of various variables. In this paper, the ordered variable and the continuous variable are numerically modeled. Based on the potential variable model, the multivariate longitudinal data containing the ordered variable and the continuous variable are jointly analyzed, and the approximate value of the edge likelihood can be obtained by using the method of numerical integration.展开更多
In recent times the fixed point results in partially ordered metric spaces has greatly developed. In this paper we prove common fixed point results for multivalued and singlevalued mappings in partially ordered metric...In recent times the fixed point results in partially ordered metric spaces has greatly developed. In this paper we prove common fixed point results for multivalued and singlevalued mappings in partially ordered metric space. Our theorems generalized the theorem in [1] and extends the many more recent results in such spaces.展开更多
The increasing popularity of e-commerce brings large volumes of sporadic orders from different customers,which have to be handled by freight trucks and distribution centers. To improve the level of service and reduce ...The increasing popularity of e-commerce brings large volumes of sporadic orders from different customers,which have to be handled by freight trucks and distribution centers. To improve the level of service and reduce the total shipping cost as well as traffic congestions in urban area, flexible methods and optimal vehicle routing strategies should be adopted to improve the efficiency of distribution effort. An optimization solution for vehicle routing and scheduling problem with time window for sporadic orders (VRPTW- S) was provided based on time-dependent travel time extracted from floating car data (FCD) with ArcGIS platform. A VRPTW-S model derived from the traditional vehicle routing problem was proposed, in which uncertainty of customer orders and travel time were considered. Based on this model, an advanced vehicle routing algorithm was designed to solve the problem. A case study of Shenzhen, Guangdong province, China, was conducted to demonstrate the vehicle operation flow,in which process of FCD and efficiency of delivery systems under different situations were discussed. The final results demonstrated a good performance of application of time-dependent travel time information using FCD in solving vehicle routing problems.展开更多
Parametric survival models are essential for analyzing time-to-event data in fields such as engineering and biomedicine.While the log-logistic distribution is popular for its simplicity and closed-form expressions,it ...Parametric survival models are essential for analyzing time-to-event data in fields such as engineering and biomedicine.While the log-logistic distribution is popular for its simplicity and closed-form expressions,it often lacks the flexibility needed to capture complex hazard patterns.In this article,we propose a novel extension of the classical log-logistic distribution,termed the new exponential log-logistic(NExLL)distribution,designed to provide enhanced flexibility in modeling time-to-event data with complex failure behaviors.The NExLL model incorporates a new exponential generator to expand the shape adaptability of the baseline log-logistic distribution,allowing it to capture a wide range of hazard rate shapes,including increasing,decreasing,J-shaped,reversed J-shaped,modified bathtub,and unimodal forms.A key feature of the NExLL distribution is its formulation as a mixture of log-logistic densities,offering both symmetric and asymmetric patterns suitable for diverse real-world reliability scenarios.We establish several theoretical properties of the model,including closed-form expressions for its probability density function,cumulative distribution function,moments,hazard rate function,and quantiles.Parameter estimation is performed using seven classical estimation techniques,with extensive Monte Carlo simulations used to evaluate and compare their performance under various conditions.The practical utility and flexibility of the proposed model are illustrated using two real-world datasets from reliability and engineering applications,where the NExLL model demonstrates superior fit and predictive performance compared to existing log-logistic-basedmodels.This contribution advances the toolbox of parametric survivalmodels,offering a robust alternative formodeling complex aging and failure patterns in reliability,engineering,and other applied domains.展开更多
高性能同轴电缆网络(High Performance Network Over Coax,HINOC)技术是一种光纤同轴混合接入技术,已发展至第3代。为了实现万兆以太网的接入速率,第3代HINOC引入了多信道绑定机制。但该机制在有效扩展HINOC网络信道带宽的同时易导致HIM...高性能同轴电缆网络(High Performance Network Over Coax,HINOC)技术是一种光纤同轴混合接入技术,已发展至第3代。为了实现万兆以太网的接入速率,第3代HINOC引入了多信道绑定机制。但该机制在有效扩展HINOC网络信道带宽的同时易导致HIMAC(HINOC Medium Access Control)拆帧端接收的数据流失序。针对该问题,文中提出了一种拆帧重排序方法。通过重排序队列缓存管理、入队逻辑地址计算、超时判断及清空以及出队判断等关键技术的设计和实现来解决多信道绑定机制引起的拆帧乱序问题,并对其关键功能点进行仿真验证和板级验证。实验结果表明,所提方法能够有效处理多信道绑定导致的乱序问题,并且能够确保系统在遇到错误情况时稳定运行,具有较强的鲁棒性,满足万兆同轴宽带接入HIMAC 3.0的功能和性能要求。展开更多
The classic data envelopment analysis（DEA） model is used to evaluate decision-making units＇（DMUs） efficiency under the assumption that all DMUs are evaluated with the same criteria setting. Recently, new research...The classic data envelopment analysis（DEA） model is used to evaluate decision-making units＇（DMUs） efficiency under the assumption that all DMUs are evaluated with the same criteria setting. Recently, new researches begin to focus on the efficiency analysis of non-homogeneous DMU arose by real practices such as the evaluation of departments in a university, where departments argue for the adoption of different criteria based on their disciplinary characteristics. A DEA procedure is proposed in this paper to address the efficiency analysis of two non-homogeneous DMU groups. Firstly, an analytical framework is established to compromise diversified input and output（IO） criteria from two nonhomogenous groups. Then, a criteria fusion operation is designed to obtain different DEA analysis strategies. Meanwhile, Friedman test is introduced to analyze the consistency of all efficiency results produced by different strategies. Next, ordered weighted averaging（OWA） operators are applied to integrate different information to reach final conclusions. Finally, a numerical example is used to illustrate the proposed method. The result indicates that the proposed method relaxes the restriction of the classical DEA model,and can provide more analytical flexibility to address different decision analysis scenarios arose from practical applications.展开更多
For the purpose of enhancing reliability of aileron of Airbus new-generation A350 XWB,an evaluation of aileron reliability on the basis of maintenance data is presented in this paper.Practical maintenance data contain...For the purpose of enhancing reliability of aileron of Airbus new-generation A350 XWB,an evaluation of aileron reliability on the basis of maintenance data is presented in this paper.Practical maintenance data contains large number of censoring samples, information uncertainty of which makes it hard to evaluate reliability of aileron actuator.Considering that true lifetime of censoring sample has identical distribution with complete sample, if censoring sample is transformed into complete sample, conversion frequency of censoring sample can be estimated according to frequency of complete sample.On the one hand, standard life table estimation and product limit method are improved on the basis of such conversion frequency, enabling accurate estimation of various censoring samples.On the other hand, by taking such frequency as one of the weight factors and integrating variance of order statistics under standard distribution, weighted least square estimation is formed for accurately estimating various censoring samples.Large amounts of experiments and simulations show that reliabilities of improved life table and improved product limit method are closer to the true value and more conservative; moreover, weighted least square estimate（WLSE）, with conversion frequency of censoring sample and variances of order statistics as the weights, can still estimate accurately with high proportion of censored data in samples.Algorithm in this paper has good effect and can accurately estimate the reliability of aileron actuator even with small sample and high censoring rate.This research has certain significance in theory and engineering practice.展开更多
Due to the simplicity and flexibility of the power law process,it is widely used to model the failures of repairable systems.Although statistical inference on the parameters of the power law process has been well deve...Due to the simplicity and flexibility of the power law process,it is widely used to model the failures of repairable systems.Although statistical inference on the parameters of the power law process has been well developed,numerous studies largely depend on complete failure data.A few methods on incomplete data are reported to process such data,but they are limited to their specific cases,especially to that where missing data occur at the early stage of the failures.No framework to handle generic scenarios is available.To overcome this problem,from the point of view of order statistics,the statistical inference of the power law process with incomplete data is established in this paper.The theoretical derivation is carried out and the case studies demonstrate and verify the proposed method.Order statistics offer an alternative to the statistical inference of the power law process with incomplete data as they can reformulate current studies on the left censored failure data and interval censored data in a unified framework.The results show that the proposed method has more flexibility and more applicability.展开更多
The industrial Internet of Things(IoT)is a trend of factory development and a basic condition of intelligent factory.It is very important to ensure the security of data transmission in industrial IoT.Applying a new ch...The industrial Internet of Things(IoT)is a trend of factory development and a basic condition of intelligent factory.It is very important to ensure the security of data transmission in industrial IoT.Applying a new chaotic secure communication scheme to address the security problem of data transmission is the main contribution of this paper.The scheme is proposed and studied based on the synchronization of different-structure fractional-order chaotic systems with different order.The Lyapunov stability theory is used to prove the synchronization between the fractional-order drive system and the response system.The encryption and decryption process of the main data signals is implemented by using the n-shift encryption principle.We calculate and analyze the key space of the scheme.Numerical simulations are introduced to show the effectiveness of theoretical approach we proposed.展开更多
This paper investigates the consensus tracking problems of second-order multi-agent systems with a virtual leader via event-triggered control. A novel distributed event-triggered transmission scheme is proposed, which...This paper investigates the consensus tracking problems of second-order multi-agent systems with a virtual leader via event-triggered control. A novel distributed event-triggered transmission scheme is proposed, which is intermittently examined at constant sampling instants. Only partial neighbor information and local measurements are required for event detection. Then the corresponding event-triggered consensus tracking protocol is presented to guarantee second-order multi-agent systems to achieve consensus tracking. Numerical simulations are given to illustrate the effectiveness of the proposed strategy.展开更多
Two methods of computer data processing, linear fitting and nonlinear fitting, are applied to compute the rate constant for hydrogen peroxide decomposition reaction. The results indicate that not only the new methods ...Two methods of computer data processing, linear fitting and nonlinear fitting, are applied to compute the rate constant for hydrogen peroxide decomposition reaction. The results indicate that not only the new methods work with no necessity to measure the final oxygen volume, but also the fitting errors decrease evidently.展开更多
文摘In the era of Big Data,the attention economy has emerged as a core logic of capital accumulation,yet behavioral economic explanations fail to penetrate the unconscious drives and desire structures underlying attention investment.This paper adopts Lacan’s topological framework of the three orders(the Real,the Symbolic,and the Imaginary)to conduct a psychoanalytic dissection of the attention economy.It argues that Big Data-driven attention mechanisms essentially manipulate desire across these three orders:algorithms,functioning as the“digital big Other,”exploit the Real’s traumatic surplus and the deferred structure of desire through infinite scroll and traumatic stimuli;regulate identity production in the Symbolic via visibility laws,social currency,and datafication;and construct narcissistic illusions in the Imaginary through filters,filter bubbles,and illusions of hyperconnection.Ultimately,the paper proposes an ethics of lucid attention,calling for critical algorithmic literacy,confrontation with the Real’s lack,dismantling of Imaginary illusions,and reclaiming sovereignty over attention-essential for preserving subjective dignity and human freedom in the digital age.
文摘In the research of scientific field, it is often necessary to continuously observe different indicators of individuals at different times and analyze the observed results. Among them, variables are mainly of two types: ordered variables and continuous variables. When analyzing data for different types of variables, it is necessary to consider the correlation between multiple indicators of an individual, and often perform joint analysis on variable observation data of multiple indicators of an individual at different times, in order to achieve more accurate and true analysis results. Joint analysis often yields more information than separate analysis of various variables. In this paper, the ordered variable and the continuous variable are numerically modeled. Based on the potential variable model, the multivariate longitudinal data containing the ordered variable and the continuous variable are jointly analyzed, and the approximate value of the edge likelihood can be obtained by using the method of numerical integration.
文摘In recent times the fixed point results in partially ordered metric spaces has greatly developed. In this paper we prove common fixed point results for multivalued and singlevalued mappings in partially ordered metric space. Our theorems generalized the theorem in [1] and extends the many more recent results in such spaces.
基金National Natural Science Foundation of China(No.71101109)Shanghai Pujiang Program,China(No.12PJ1404600)
文摘The increasing popularity of e-commerce brings large volumes of sporadic orders from different customers,which have to be handled by freight trucks and distribution centers. To improve the level of service and reduce the total shipping cost as well as traffic congestions in urban area, flexible methods and optimal vehicle routing strategies should be adopted to improve the efficiency of distribution effort. An optimization solution for vehicle routing and scheduling problem with time window for sporadic orders (VRPTW- S) was provided based on time-dependent travel time extracted from floating car data (FCD) with ArcGIS platform. A VRPTW-S model derived from the traditional vehicle routing problem was proposed, in which uncertainty of customer orders and travel time were considered. Based on this model, an advanced vehicle routing algorithm was designed to solve the problem. A case study of Shenzhen, Guangdong province, China, was conducted to demonstrate the vehicle operation flow,in which process of FCD and efficiency of delivery systems under different situations were discussed. The final results demonstrated a good performance of application of time-dependent travel time information using FCD in solving vehicle routing problems.
文摘Parametric survival models are essential for analyzing time-to-event data in fields such as engineering and biomedicine.While the log-logistic distribution is popular for its simplicity and closed-form expressions,it often lacks the flexibility needed to capture complex hazard patterns.In this article,we propose a novel extension of the classical log-logistic distribution,termed the new exponential log-logistic(NExLL)distribution,designed to provide enhanced flexibility in modeling time-to-event data with complex failure behaviors.The NExLL model incorporates a new exponential generator to expand the shape adaptability of the baseline log-logistic distribution,allowing it to capture a wide range of hazard rate shapes,including increasing,decreasing,J-shaped,reversed J-shaped,modified bathtub,and unimodal forms.A key feature of the NExLL distribution is its formulation as a mixture of log-logistic densities,offering both symmetric and asymmetric patterns suitable for diverse real-world reliability scenarios.We establish several theoretical properties of the model,including closed-form expressions for its probability density function,cumulative distribution function,moments,hazard rate function,and quantiles.Parameter estimation is performed using seven classical estimation techniques,with extensive Monte Carlo simulations used to evaluate and compare their performance under various conditions.The practical utility and flexibility of the proposed model are illustrated using two real-world datasets from reliability and engineering applications,where the NExLL model demonstrates superior fit and predictive performance compared to existing log-logistic-basedmodels.This contribution advances the toolbox of parametric survivalmodels,offering a robust alternative formodeling complex aging and failure patterns in reliability,engineering,and other applied domains.
文摘高性能同轴电缆网络(High Performance Network Over Coax,HINOC)技术是一种光纤同轴混合接入技术,已发展至第3代。为了实现万兆以太网的接入速率,第3代HINOC引入了多信道绑定机制。但该机制在有效扩展HINOC网络信道带宽的同时易导致HIMAC(HINOC Medium Access Control)拆帧端接收的数据流失序。针对该问题,文中提出了一种拆帧重排序方法。通过重排序队列缓存管理、入队逻辑地址计算、超时判断及清空以及出队判断等关键技术的设计和实现来解决多信道绑定机制引起的拆帧乱序问题,并对其关键功能点进行仿真验证和板级验证。实验结果表明,所提方法能够有效处理多信道绑定导致的乱序问题,并且能够确保系统在遇到错误情况时稳定运行,具有较强的鲁棒性,满足万兆同轴宽带接入HIMAC 3.0的功能和性能要求。
基金supported by the National Natural Science Foundation of China(71471087)
文摘The classic data envelopment analysis（DEA） model is used to evaluate decision-making units＇（DMUs） efficiency under the assumption that all DMUs are evaluated with the same criteria setting. Recently, new researches begin to focus on the efficiency analysis of non-homogeneous DMU arose by real practices such as the evaluation of departments in a university, where departments argue for the adoption of different criteria based on their disciplinary characteristics. A DEA procedure is proposed in this paper to address the efficiency analysis of two non-homogeneous DMU groups. Firstly, an analytical framework is established to compromise diversified input and output（IO） criteria from two nonhomogenous groups. Then, a criteria fusion operation is designed to obtain different DEA analysis strategies. Meanwhile, Friedman test is introduced to analyze the consistency of all efficiency results produced by different strategies. Next, ordered weighted averaging（OWA） operators are applied to integrate different information to reach final conclusions. Finally, a numerical example is used to illustrate the proposed method. The result indicates that the proposed method relaxes the restriction of the classical DEA model,and can provide more analytical flexibility to address different decision analysis scenarios arose from practical applications.
基金supported by the National Natural Science Foundation of China (Nos.61403198, 61079013 and 61079014)Youth Foundation of Jiangsu Province in China (No.BK20140827)+2 种基金Key Programs of Natural Science Foundation of Chinathe China Civil Aviation Joint Fund (No.60939003)Natural Science Foundation of Jiangsu Province in China (No.BK2011737)
文摘For the purpose of enhancing reliability of aileron of Airbus new-generation A350 XWB,an evaluation of aileron reliability on the basis of maintenance data is presented in this paper.Practical maintenance data contains large number of censoring samples, information uncertainty of which makes it hard to evaluate reliability of aileron actuator.Considering that true lifetime of censoring sample has identical distribution with complete sample, if censoring sample is transformed into complete sample, conversion frequency of censoring sample can be estimated according to frequency of complete sample.On the one hand, standard life table estimation and product limit method are improved on the basis of such conversion frequency, enabling accurate estimation of various censoring samples.On the other hand, by taking such frequency as one of the weight factors and integrating variance of order statistics under standard distribution, weighted least square estimation is formed for accurately estimating various censoring samples.Large amounts of experiments and simulations show that reliabilities of improved life table and improved product limit method are closer to the true value and more conservative; moreover, weighted least square estimate（WLSE）, with conversion frequency of censoring sample and variances of order statistics as the weights, can still estimate accurately with high proportion of censored data in samples.Algorithm in this paper has good effect and can accurately estimate the reliability of aileron actuator even with small sample and high censoring rate.This research has certain significance in theory and engineering practice.
基金supported by the National Natural Science Foundation of China(51775090)。
文摘Due to the simplicity and flexibility of the power law process,it is widely used to model the failures of repairable systems.Although statistical inference on the parameters of the power law process has been well developed,numerous studies largely depend on complete failure data.A few methods on incomplete data are reported to process such data,but they are limited to their specific cases,especially to that where missing data occur at the early stage of the failures.No framework to handle generic scenarios is available.To overcome this problem,from the point of view of order statistics,the statistical inference of the power law process with incomplete data is established in this paper.The theoretical derivation is carried out and the case studies demonstrate and verify the proposed method.Order statistics offer an alternative to the statistical inference of the power law process with incomplete data as they can reformulate current studies on the left censored failure data and interval censored data in a unified framework.The results show that the proposed method has more flexibility and more applicability.
基金supported in part by the National Science Foundation Project of China (61931001, 61873026)the National Key R&D Program of China (2017YFC0820700)
文摘The industrial Internet of Things(IoT)is a trend of factory development and a basic condition of intelligent factory.It is very important to ensure the security of data transmission in industrial IoT.Applying a new chaotic secure communication scheme to address the security problem of data transmission is the main contribution of this paper.The scheme is proposed and studied based on the synchronization of different-structure fractional-order chaotic systems with different order.The Lyapunov stability theory is used to prove the synchronization between the fractional-order drive system and the response system.The encryption and decryption process of the main data signals is implemented by using the n-shift encryption principle.We calculate and analyze the key space of the scheme.Numerical simulations are introduced to show the effectiveness of theoretical approach we proposed.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61203147,61374047,and 61403168)
文摘This paper investigates the consensus tracking problems of second-order multi-agent systems with a virtual leader via event-triggered control. A novel distributed event-triggered transmission scheme is proposed, which is intermittently examined at constant sampling instants. Only partial neighbor information and local measurements are required for event detection. Then the corresponding event-triggered consensus tracking protocol is presented to guarantee second-order multi-agent systems to achieve consensus tracking. Numerical simulations are given to illustrate the effectiveness of the proposed strategy.
文摘Two methods of computer data processing, linear fitting and nonlinear fitting, are applied to compute the rate constant for hydrogen peroxide decomposition reaction. The results indicate that not only the new methods work with no necessity to measure the final oxygen volume, but also the fitting errors decrease evidently.
