As the fundamental and key technique to ensure the safe and reliable operation of vital systems,prognostics with an emphasis on the remaining useful life(RUL)prediction has attracted great attention in the last decade...As the fundamental and key technique to ensure the safe and reliable operation of vital systems,prognostics with an emphasis on the remaining useful life(RUL)prediction has attracted great attention in the last decades.In this paper,we briefly discuss the general idea and advances of various prognostics and RUL prediction methods for machinery,mainly including data-driven methods,physics-based methods,hybrid methods,etc.Based on the observations fromthe state of the art,we provide comprehensive discussions on the possible opportunities and challenges of prognostics and RUL prediction of machinery so as to steer the future development.展开更多
The performance of a call center is sensitive to customer abandonment. In this survey paper, we focus on G/GI/n ＋ GI parallel-server queues that serve as a building block to model call center operations. Such a queue...The performance of a call center is sensitive to customer abandonment. In this survey paper, we focus on G/GI/n ＋ GI parallel-server queues that serve as a building block to model call center operations. Such a queue has a general arrival process （the G ）, independent and identically distributed （iid） service times with a general distribution （the first G1 ）, and iid patience times with a general distribution （the ＋GI）. Following the square-root safety staffing rule, this queue can be operated in the quality- and efficiency-driven （QED） regime, which is characterized by large customer volume, the waiting times being a fraction of the service times, only a small fraction of customers abandoning the system, and high server utilization. Operational efficiency is the central target in a system whose staffing costs dominate other expenses. If a moderate fraction of customer abandonment is allowed, such a system should be operated in an overloaded regime known as the efficiency-driven （ED） regime. We survey recent results on the many-server queues that are operated in the QED and ED regimes. These results include the performance insensitivity to patience time distributions and diffusion and fluid approximate models as practical tools for performance analysis.展开更多
Vehicle electrification has emerged as a global strategy to address climate change and emissions externalities from the transportation sector.Deployment of charging infrastructure is needed to accelerate technology ad...Vehicle electrification has emerged as a global strategy to address climate change and emissions externalities from the transportation sector.Deployment of charging infrastructure is needed to accelerate technology adoption;however,managers and policymakers have had limited evidence on the use of public charging stations due to poor data sharing and decentralized ownership across regions.In this article,we use machine learning based classifiers to reveal insights about consumer charging behavior in 72 detected languages including Chinese.We investigate 10 years of consumer reviews in East and Southeast Asia from 2011 to 2021 to enable infrastructure evaluation at a larger geographic scale than previously available.We find evidence that charging stations at government locations result in higher failure rates with consumers compared to charging stations at private points of interest.This evidence contrasts with predictions in the U.S.and European markets,where the performance is closer to parity.We also find that networked stations with communication protocols provide a relatively higher quality of charging services,which favors policy support for connectivity,particularly for underserved or remote areas.展开更多
In this paper, we consider two different formulations （one is smooth and the other one is nonsmooth） for solving linear matrix inequalities （LMIs）, an important class of semidefinite programming （SDP）, under a c...In this paper, we consider two different formulations （one is smooth and the other one is nonsmooth） for solving linear matrix inequalities （LMIs）, an important class of semidefinite programming （SDP）, under a certain Slater constraint qualification assumption. We then propose two first-order methods, one based on subgradient method and the other based on Nesterov＇s optimal method, and show that they converge linearly for solving these formulations. Moreover, we introduce an accelerated prox-level method which converges linearly uniformly for both smooth and non-smooth problems without requiring the input of any problem parameters. Finally, we consider a special case of LMIs, i.e., linear system of inequalities, and show that a linearly convergent algorithm can be obtained under a much weaker assumption.展开更多
The COVID-19 pandemic provides an opportunity to explore the impact of government mandates on movement restrictions and non-pharmaceutical interventions on a novel infection,and we investigate these strategies in earl...The COVID-19 pandemic provides an opportunity to explore the impact of government mandates on movement restrictions and non-pharmaceutical interventions on a novel infection,and we investigate these strategies in early-stage outbreak dynamics.The rate of disease spread in South Africa varied over time as individuals changed behavior in response to the ongoing pandemic and to changing government policies.Using a system of ordinary differential equations,we model the outbreak in the province of Gauteng,assuming that several parameters vary over time.Analyzing data from the time period before vaccination gives the approximate dates of parameter changes,and those dates are linked to government policies.Unknown parameters are then estimated from available case data and used to assess the impact of each policy.Looking forward in time,possible scenarios give projections involving the implementation of two different vaccines at varying times.Our results quantify the impact of different government policies and demonstrate how vaccinations can alter infection spread.展开更多
基金The work in Section III was supported by the National Science Foundation of China(NSFC)(Nos.52025056,52005387)the work in Section IV was supported by the National Science Foundation of China(NSFC)(Nos.62233017,62073336).
文摘As the fundamental and key technique to ensure the safe and reliable operation of vital systems,prognostics with an emphasis on the remaining useful life(RUL)prediction has attracted great attention in the last decades.In this paper,we briefly discuss the general idea and advances of various prognostics and RUL prediction methods for machinery,mainly including data-driven methods,physics-based methods,hybrid methods,etc.Based on the observations fromthe state of the art,we provide comprehensive discussions on the possible opportunities and challenges of prognostics and RUL prediction of machinery so as to steer the future development.
基金This work was partially supported by the Brook Byers Institute for Sustainable Systems, the Hightower Chair, Georgia Research Alliance, and grants （083604, 1441208） from the US National Science Foundation Program for Emerging Frontiers in Research and Innovation （EFRI）.
基金supported in part by NSF grants CMMI-0825840 and CMMI-1030589
文摘The performance of a call center is sensitive to customer abandonment. In this survey paper, we focus on G/GI/n ＋ GI parallel-server queues that serve as a building block to model call center operations. Such a queue has a general arrival process （the G ）, independent and identically distributed （iid） service times with a general distribution （the first G1 ）, and iid patience times with a general distribution （the ＋GI）. Following the square-root safety staffing rule, this queue can be operated in the quality- and efficiency-driven （QED） regime, which is characterized by large customer volume, the waiting times being a fraction of the service times, only a small fraction of customers abandoning the system, and high server utilization. Operational efficiency is the central target in a system whose staffing costs dominate other expenses. If a moderate fraction of customer abandonment is allowed, such a system should be operated in an overloaded regime known as the efficiency-driven （ED） regime. We survey recent results on the many-server queues that are operated in the QED and ED regimes. These results include the performance insensitivity to patience time distributions and diffusion and fluid approximate models as practical tools for performance analysis.
基金supported by funding from the National Science Foundation(Nos.1931980 and 1945332)Microsoft Azure for researchand the U.S.State Department Diplomacy Lab.
文摘Vehicle electrification has emerged as a global strategy to address climate change and emissions externalities from the transportation sector.Deployment of charging infrastructure is needed to accelerate technology adoption;however,managers and policymakers have had limited evidence on the use of public charging stations due to poor data sharing and decentralized ownership across regions.In this article,we use machine learning based classifiers to reveal insights about consumer charging behavior in 72 detected languages including Chinese.We investigate 10 years of consumer reviews in East and Southeast Asia from 2011 to 2021 to enable infrastructure evaluation at a larger geographic scale than previously available.We find evidence that charging stations at government locations result in higher failure rates with consumers compared to charging stations at private points of interest.This evidence contrasts with predictions in the U.S.and European markets,where the performance is closer to parity.We also find that networked stations with communication protocols provide a relatively higher quality of charging services,which favors policy support for connectivity,particularly for underserved or remote areas.
文摘In this paper, we consider two different formulations （one is smooth and the other one is nonsmooth） for solving linear matrix inequalities （LMIs）, an important class of semidefinite programming （SDP）, under a certain Slater constraint qualification assumption. We then propose two first-order methods, one based on subgradient method and the other based on Nesterov＇s optimal method, and show that they converge linearly for solving these formulations. Moreover, we introduce an accelerated prox-level method which converges linearly uniformly for both smooth and non-smooth problems without requiring the input of any problem parameters. Finally, we consider a special case of LMIs, i.e., linear system of inequalities, and show that a linearly convergent algorithm can be obtained under a much weaker assumption.
基金This research was funded in part by the National Science Foundation,grant number 134651,to the MASAMU Advanced Study Institute.FBAwas supported by the National Science Foundation under grant number DMS 2028297CJEwas supported by the AMS-Simons Travel Grants,which are administered by the American Mathematical Society with support from the Simons Foundation.FC was supported by the University of Johanneburg URC Grant。
文摘The COVID-19 pandemic provides an opportunity to explore the impact of government mandates on movement restrictions and non-pharmaceutical interventions on a novel infection,and we investigate these strategies in early-stage outbreak dynamics.The rate of disease spread in South Africa varied over time as individuals changed behavior in response to the ongoing pandemic and to changing government policies.Using a system of ordinary differential equations,we model the outbreak in the province of Gauteng,assuming that several parameters vary over time.Analyzing data from the time period before vaccination gives the approximate dates of parameter changes,and those dates are linked to government policies.Unknown parameters are then estimated from available case data and used to assess the impact of each policy.Looking forward in time,possible scenarios give projections involving the implementation of two different vaccines at varying times.Our results quantify the impact of different government policies and demonstrate how vaccinations can alter infection spread.
