In this paper,a deadlock prevention policy for robotic manufacturing cells with uncontrollable and unobservable events is proposed based on a Petri net formalism.First,a Petri net for the deadlock control of such syst...In this paper,a deadlock prevention policy for robotic manufacturing cells with uncontrollable and unobservable events is proposed based on a Petri net formalism.First,a Petri net for the deadlock control of such systems is defined.Its admissible markings and first-met inadmissible markings(FIMs)are introduced.Next,place invariants are designed via an integer linear program(ILP)to survive all admissible markings and prohibit all FIMs,keeping the underlying system from reaching deadlocks,livelocks,bad markings,and the markings that may evolve into them by firing uncontrollable transitions.ILP also ensures that the obtained deadlock-free supervisor does not observe any unobservable transition.In addition,the supervisor is guaranteed to be admissible and structurally minimal in terms of both control places and added arcs.The condition under which the supervisor is maximally permissive in behavior is given.Finally,experimental results with the proposed method and existing ones are given to show its effectiveness.展开更多
This paper investigates the problem of cooperative localization(CL)for a multi-robot system(MRS)under dynamic measurement topology,which involves a group of robots collectively estimating their poses with respect to a...This paper investigates the problem of cooperative localization(CL)for a multi-robot system(MRS)under dynamic measurement topology,which involves a group of robots collectively estimating their poses with respect to a common reference frame using ego-motion measurements and robot-to-robot relative measurements.The authors provide a theoretical analysis of the time-varying unobservable subspace and propose a consistent cooperative localization algorithm.First,the authors introduce the relative measurement graph(RMG)to represent the relative pose measurements obtained by the MRS at each instant.Then,the authors derive the local observability matrix over a time interval.An equivalent relationship is established between the local observability matrix and the spectral matrices of the RMG.Moreover,the authors present a method for constructing the unobservable subspace based on the RMG under different topology conditions.Based on this analysis,the authors design a consistent cooperative localization algorithm that satisfies the constraints of the time-varying unobservable subspace.An analytical optimal solution is derived for the constrained optimization problem.Monte Carlo numerical simulations are conducted to demonstrate the consistency and accuracy of the proposed method.展开更多
Purpose-The border control becomes challenging when a protected region is large and there is a limited number of border patrols.This research paper proposes a novel heuristic-based patrol path planning scheme in order...Purpose-The border control becomes challenging when a protected region is large and there is a limited number of border patrols.This research paper proposes a novel heuristic-based patrol path planning scheme in order to efficiently patrol with resource scarcity.Design/methodology/approach-The trespasser influencing score,which is determined from the environmental characteristics and trespassing statistic of the region,is used as a heuristic for measuring a chance of approaching a trespasser.The patrol plan is occasionally updated with a new trespassing statistic during a border operation.The performance of the proposed patrol path planning scheme was evaluated and compared with other patrol path planning schemes by the empirical experiment under different scenarios.Findings-The result from the experiment indicates that the proposed patrol planning outperforms other patrol path planning schemes in terms of the trespasser detection rate,when more environment-aware trespassers are in the region.Research limitations/implications-The experiment was conducted through simulated agents in simulated environment,which were assumed to mimic real behavior and environment.Originality/value-This research paper contributes a heuristic-based patrol path planning scheme that applies the environmental characteristics and dynamic statistic of the region,as well as a border surveillance problem model that would be useful for mobile sensor planning in a border surveillance application.展开更多
Survival analysis is a fundamental tool in medical science for time-to-event data. However, its application to colony organisms like bees poses challenges due to their social nature. Traditional survival models may no...Survival analysis is a fundamental tool in medical science for time-to-event data. However, its application to colony organisms like bees poses challenges due to their social nature. Traditional survival models may not accurately capture the interdependence among individuals within a colony. Frailty models, accounting for shared risks within groups, offer a promising alternative. This study evaluates the performance of semi-parametric shared frailty models (gamma, inverse normal, and positive stable-in comparison to the traditional Cox model using bees’ survival data). We examined the effect of misspecification of the frailty distribution on regression and heterogeneity parameters using simulation and concluded that the heterogeneity parameter was more sensitive to misspecification of the frailty distribution and choice of initial parameters (cluster size and true heterogeneity parameter) compared to the regression parameter. From the data, parameter estimates for covariates were close for the four models but slightly higher for the Cox model. The shared gamma frailty model provided a better fit to the data in comparison with the other models. Therefore, when focusing on regression parameters, the gamma frailty model is recommended. This research underscores the importance of tailored survival methodologies for accurately analyzing time-to-event data in social organisms.展开更多
This paper deals with the synthesis of Petri net supervisor enforcing the more expressive constraints including marking terms, firing vector terms and Parikh vector terms. The method is developed to handle uncontrolla...This paper deals with the synthesis of Petri net supervisor enforcing the more expressive constraints including marking terms, firing vector terms and Parikh vector terms. The method is developed to handle uncontrollable and unobservable transitions existing in the constraints. The “greater-than or equal” general constraints can also be transformed into “less-than or equal” Parikh constraints. An example is analyzed to show how the problem is solved. General constraint is first transformed into Parikh vector constraints, and Matrix-Transformation is proposed to obtain the admissible constraints without uncontrollable and unobservable transitions. Then the supervisor can be constructed based on constraints only consisting of Parikh vector terms. The method is proved to be more concise and effective than the method presented by Iordache and Moody especially when applied to large scale systems.展开更多
The observability problem of switched linear singular（SLS） systems is studied in this paper. Based on the observability definition, the unobservable subspaces of given switching laws are investigated under the condi...The observability problem of switched linear singular（SLS） systems is studied in this paper. Based on the observability definition, the unobservable subspaces of given switching laws are investigated under the condition that all subsystems are regular. A necessary condition and a sufficient condition for observability of SLS systems are given. It is shown that the observability and controllability are dual for some special SLS systems with circulatory switching laws. The method developed here is applicable to the observability analysis of normal switched linear systems.展开更多
This paper analyzes the adoption dynamics of improved rainfed maize seeds disseminated in Senegal in 2013 by the West African Agricultural Productivity Program (WAAPP). We group maize producers into five groups (non-a...This paper analyzes the adoption dynamics of improved rainfed maize seeds disseminated in Senegal in 2013 by the West African Agricultural Productivity Program (WAAPP). We group maize producers into five groups (non-adopters, laggards/abandoners, late adopters, followers and pioneers/innovators) and take into account the heterogeneity of unobservable characteristics of the producers. In the pioneers/innovators group, the availability of labour, household size, shocks, and frequency of access to advice positively influence adoption, whereas financial constraints and high numbers of plots reduce the probability of adoption. Producers in the followers’ category tend to be older and more educated than those in the other categories. However, food insecurity and shocks such as diseases hamper adoption. For the group of late adopters, household size and available storage infrastructures explain adoption. However, the number of plots and shocks reduces their probability of adoption. Laggards tend to face shocks and food insecurity. The authors recommend to consider the dynamics of the adoption of technological innovations and heterogeneity of the characteristics of adopters groups in future research. They also recommend farmers to increase their adoption rate of the “Early Thai” and “Suwan 1” seed varieties thanks to their higher yields compared to traditional varieties. Also, a higher adoption rate would positively impact the food security of maize farmers in Eastern Senegal and High Casamance, especially in terms of availability. Other studies measuring the number of years needed for large-scale adoption of improved seed varieties should be conducted.展开更多
Despite increasing knowledge of barnyardgrass(Echinochloa crus-galli) interference with rice, relatively little is known how endophytes improve the ability of rice against barnyardgrass stress. Here, we provided a det...Despite increasing knowledge of barnyardgrass(Echinochloa crus-galli) interference with rice, relatively little is known how endophytes improve the ability of rice against barnyardgrass stress. Here, we provided a detailed temporal characterization of rice root-associated microbiomes during co-cultivation with barnyardgrass and a comparison with the microbiomes of weed-free rice plants. Alpha diversity analysis indicated that barnyardgrass had the opposite effects on endophytic bacteria and fungi in rice roots, in terms of the community diversity, richness and coverage at the rice seedling stage. Principal coordinate analysis showed that barnyardgrass had only a minor effect on the community composition of endophytes in rice roots at the rice seedling stage, but showed a significant and maximum interference at the heading stage. Rice recruited many endophytes to resist biotic stress from barnyardgrass, especially for fungi. PICRUSt(phylogenetic investigation of communities by reconstruction of unobserved states) predictive analysis indicated that 23 metabolic pathways of bacteria were overrepresented in rice. In addition, the main trophic mode of fungi was pathotroph according to FUNGuild analysis. A positive correlation between bacteria and fungi in rice roots was found via network analysis. Anaeromyxobacter, Azospira and Pseudolabrys were the vital bacteria, Phaeosphaeria and Funneliformis were the dominant fungi in maintaining the stability of the ecological network. These results provided data and a theoretical basis for the in-depth understanding of what role endophytes play in rice resistance to barnyardgrass stress and will have implications on improving the resistance of rice against biotic stress using root microbiota.展开更多
This paper mainly discusses the singular linear systems of distributional version. By using its matrices coefficients and some invariant subspaces, the distributionally weakly obseervability and the impulse observabil...This paper mainly discusses the singular linear systems of distributional version. By using its matrices coefficients and some invariant subspaces, the distributionally weakly obseervability and the impulse observability are analyzed.展开更多
This study investigates the degree of capital mobility in a panel of 16 Latin American and 4 Caribbean countries during 1960 to 2017 against the backdrop of the Feldstein-Horioka hypothesis by applying recent panel da...This study investigates the degree of capital mobility in a panel of 16 Latin American and 4 Caribbean countries during 1960 to 2017 against the backdrop of the Feldstein-Horioka hypothesis by applying recent panel data techniques.This is the first study on capital mobility in Latin American and Caribbean countries to employ the recently developed panel data procedure of the dynamic common correlated effects modeling technique of Chudik and Pesaran(J Econ 188:393–420,2015)and the error-correction testing of Gengenbach,Urbain,and Westerlund(Panel error correction testing with global stochastic trends,2008,J Appl Econ 31:982–1004,2016).These approaches address the serious panel data econometric issues of crosssection dependence,slope heterogeneity,nonstationarity,and endogeneity in a multifactor error-structure framework.The empirical findings of this study reveal a low average(mean)savings–retention coefficient for the panel as a whole and for most individual countries,as well as indicating a cointegration relationship between saving and investment ratios.The results indicate that there is a relatively high degree of capital mobility in the Latin American and Caribbean countries in the short run,while the long-run solvency condition is maintained,which is due to reduced frictions in goods and services markets causing increase competition.Increased capital mobility in these countries can promote economic growth and hasten the process of globalization by creating a conducive economic environment for FDI in these countries.展开更多
This paper presents an procedure for purifying training data sets （i.e., past occurrences of slope failures） for inverse estimation on unobserved trigger factors of ＂different types of simultaneous slope failures＂...This paper presents an procedure for purifying training data sets （i.e., past occurrences of slope failures） for inverse estimation on unobserved trigger factors of ＂different types of simultaneous slope failures＂. Due to difficulties in pixel-by-pixel observations of trigger factors, as one of the measures, the authors had proposed an inverse analysis algorithm on trigger factors based on SEM （structural equation modeling）. Through a measurement equation, the trigger factor is inversely estimated, and a TFI （trigger factor influence） map can be also produced. As a subsequence subject, a purification procedure of training data set should be constructed to improve the accuracy of TFI map which depends on the representativeness of given training data sets of different types of slope failures. The proposed procedure resamples the matched pixels between original groups of past slope failures （i.e., surface slope failures, deep-seated slope failures, landslides） and classified three groups by K-means clustering for all pixels corresponding to those slope failures. For all cases of three types of slope failures, the improvement of success rates with respect to resampled training data sets was confirmed. As a final outcome, the differences between TFI maps produced by using original and resampled training data sets, respectively, are delineated on a DIF map （difference map） which is useful for analyzing trigger factor influence in terms of ＂risky- and safe-side assessment＂ sub-areas with respect to ＂different types of simultaneous slope failures＂.展开更多
Drowsy driving has received comparatively less attention in traffic safety literature when compared to other safety issues,despite its devastating impact on society in terms of human life lost and associated economic ...Drowsy driving has received comparatively less attention in traffic safety literature when compared to other safety issues,despite its devastating impact on society in terms of human life lost and associated economic burdens.Therefore,this significant safety threat requires a thorough investigation.To address the temporal instability of factors contributing to crashes involving drowsy drivers,this paper divides the crash data into four time periods while capturing unobserved heterogeneity in the means and variances of random parameters.To explore the determinants affecting the severity of injuries sustained by drowsy drivers involved in single-vehicle crashes,injury outcomes are categorized into three groups:serious,moderate,and no injuries.Using four years of crash data from the state of Washington between 2013 and 2016,a wide range of factors were examined,including driver characteristics,roadway conditions,crash characteristics,vehicle conditions,lighting conditions,and temporal factors.The estimation results reveal that there is temporal instability in terms of the effect of determinants on injury severity across the years.However,some factors exhibit stable effects,such as female drivers,sober drivers,and non-hit-and-run crashes.Based on the findings of this study,decision-makers,traffic engineers,and traffic authorities can gain valuable knowledge and insights into the factors contributing to drowsy-related crashes,enabling them to make informed recommendations for safety countermeasures.展开更多
Bicycling has been actively promoted as a clean and efficient mode of commute.Besides,due to the personal and societal benefits it provides,it has been adopted by many city dwellers for short-distance trips.Despite th...Bicycling has been actively promoted as a clean and efficient mode of commute.Besides,due to the personal and societal benefits it provides,it has been adopted by many city dwellers for short-distance trips.Despite the integral role this active transport mode plays,it is unfortunately associated with a high risk of fatalities in the event of a traffic crash as they are not protected.Many studies have been conducted in several jurisdictions to examine the factors contributing to crashes involving these vulnerable road users.In the case of Louisiana which is currently experiencing increased cases of severe and fatal bicycleinvolved crashes,less attention has been paid to investigating the critical factors influencing bicyclist injury severity outcomes using more detailed data and advanced econometric modeling frameworks to help propose adequate policies to improve the safety of riders.Against this background,this study examined the key contributing factors influencing bicyclist injuries by using more detailed roadway crash data spanning 2010-2016 obtained from the state of Louisiana.The study then applies an advanced random parameter logit modeling with heterogeneity in means and variances to address the unobserved heterogeneity issue associated with traffic crash data.To overcome the imbalanced data issue,three major crash injury levels were used instead of the conventional five crash injury levels.Besides,the data groups classified under each injury level were compared for the final variable selection.The study found that distracted drivers,elderly bicyclists,careless operations,and riding in dark conditions increase the probability of having severe injuries in vehicle-bicyclist crashes.Moreover,the variables for straight-level roadways and city streets decrease the odds of severe injuries.The straight-level roadway may provide better sight distance for both drivers and bicyclists,and complex environments like city streets discourage crashes with severe injuries.展开更多
This research investigates the intricate relationship between the number of lanes on highways and injury severities sustained by commercial motor vehicle(CMV)drivers.Many studies have addressed crash determinants,but ...This research investigates the intricate relationship between the number of lanes on highways and injury severities sustained by commercial motor vehicle(CMV)drivers.Many studies have addressed crash determinants,but the safety implications of differing numbers of lanes remain insufficiently examined,especially during the highway planning stages.Our study fills this knowledge gap by analyzing injury severity crash factors for a varied number of lane scenarios.Employing a random parameter logit modeling framework,we differentiated injury levels for 2-4 lanes and 6-10 lanes.Key factors were identified for each number of lanes,with older,loss of vehicle control,non-collision crashes,and crashes,on locations where grade or hill existed,being more perilous and increasing the risk of sustaining severe injuries on 2-lane highways.For 4-lane highways,factors such as non-Oregonian drivers,older drivers,crashes that occurred during the spring season,and crashes that occurred beyond shoulders were associated with an elevated probability of being involved in severe injury crashes.Regarding highways with 6 lanes and higher,driving too fast for conditions and driver error(drowsy,fatigued,inattentive,or reckless)increases the odds of being involved in higher levels of injury crashes.To enhance truck driver safety,we recommend the implementation of electronic stability control in CMVs,with moderated speeds on graded sections,improved curve markers,and robust public safety campaigns.展开更多
This paper provides an integrated analytical framework to investigate the demographic and behavioural factors that significantly influence public support for pedestrianisation. Pedestrianisation is often introduced by...This paper provides an integrated analytical framework to investigate the demographic and behavioural factors that significantly influence public support for pedestrianisation. Pedestrianisation is often introduced by local authorities with the intention of improving air quality, the walkability of streets, road safety and opportunities for the local economy, however, issues remain regarding how accessible pedestrianised areas are for individuals who have conditions that limit their mobility. Using data from a survey, conducted during 2020 in Edinburgh (UK), public perceptions towards pedestrianisation were investigated through statistical testing and the development of random forest and ordered probit models. The random forest approach can help identify the relative importance of explanatory variables, whereas the ordered probit models can unveil the demographic and behavioural determinants of public support. To account for the potential effect of unobserved heterogeneity within respondents’ perceptions, random parameters were also considered in the ordered probit modelling framework. Initial results showed that residents are generally supportive of most issues surrounding pedestrianisation. Random parameters ordered probit modelling identified mode of travel and trip frequency as significant factors affecting key aspects of public support, such that active travellers were significantly more likely to support pedestrianisation, while those who rarely visit Edinburgh city centre were more likely to oppose pedestrianisation. Overall, a variety of independent analyses and modelling approaches suggest common influences on opinion, including behavioural patterns relating to transport modal choice and trip frequency, while disability was also found to have considerable effect on support as a fixed and random parameter. The statistical models are evaluated in terms of goodness-of-fit measures, before policy implications are discussed.展开更多
As the phasor measurement unit(PMU)placement problem involves a cost-benefit trade-off,more PMUs get placed on higher-voltage buses.However,this leads to the fact that many lower-voltage levels of the bulk power syste...As the phasor measurement unit(PMU)placement problem involves a cost-benefit trade-off,more PMUs get placed on higher-voltage buses.However,this leads to the fact that many lower-voltage levels of the bulk power system cannot be observed by PMUs.This lack of visibility then makes timesynchronized state estimation of the full system a challenging problem.In this paper,a deep neural network-based state estimator(DeNSE)is proposed to solve this problem.The DeNSE employs a Bayesian framework to indirectly combine the inferences drawn from slow-timescale but widespread supervisory control and data acquisition(SCADA)data with fast-timescale but selected PMU data,to attain sub-second situational awareness of the full system.The practical utility of the DeNSE is demonstrated by considering topology change,non-Gaussian measurement noise,and detection and correction of bad data.The results obtained using the IEEE 118-bus system demonstrate the superiority of the DeNSE over a pure SCADA state estimator and a PMU-only linear state estimator from a technoeconomic viability perspective.Lastly,the scalability of the DeNSE is proven by estimating the states of a large and realistic 2000-bus synthetic Texas system.展开更多
It is only the observable part of the real world that can be stored in data. For such incomplete and ill-structured data, data crystallizing aims at presenting the hidden structure among events including unobservable ...It is only the observable part of the real world that can be stored in data. For such incomplete and ill-structured data, data crystallizing aims at presenting the hidden structure among events including unobservable events. This is realized by data crystallization, where dummy items, corresponding to potential existence ofunobservable events, are inserted to the given data. These dummy items and their relations with observable events are visualized by applying KeyGraph to the data with dummy items, like the crystallization of snow where dusts are involved in the formation of crystallization of water molecules. For tuning the granularity level of structure to be visualized, the tool of data crystallization is integrated with human＇s process of understanding significant scenarios in the real world. This basic method is expected to be applicable for various real world domains where previous methods of chance-discovery lead human to successful decision making. In this paper, we apply the data crystallization with human-interactive annealing （DCHA） to the design of products in a real company. The results show its effect to industrial decision making.展开更多
This paper investigates an M/M/1 constant retrial queue with reserved time and vacations.A new arriving customer will take up the server and accept service immediately if the server is idle.Otherwise,if the server is ...This paper investigates an M/M/1 constant retrial queue with reserved time and vacations.A new arriving customer will take up the server and accept service immediately if the server is idle.Otherwise,if the server is busy or on vacation,customers have to join a retrial orbit and wait for retry.Once a service is completed,the server will reserve a random time to seek a customer from the orbit at a constant retrial rate.If there is no arrivals(from the orbit or outside)during the idle period,to save energy,the server will take a vacation.This paper studies the fully unobservable case.First,the steady-state condition of the system is analyzed by using the Foster’s criterion,and the customers’expected waiting time is obtained based on the generating function technique.And then,by introducing an appropriate revenue structure,the equilibrium strategies of customers and the socially optimal strategy are all derived.Furthermore,a comparison between them is made and the effect of some main system parameters is studied.展开更多
Estimation of treatment effects is one of the crucial mainstays in economics and sociology studies.The problem will become more serious and complicated if the treatment variable is endogenous for the presence of unobs...Estimation of treatment effects is one of the crucial mainstays in economics and sociology studies.The problem will become more serious and complicated if the treatment variable is endogenous for the presence of unobserved confounding.The estimation and conclusion are likely to be biased and misleading if the endogeny of treatment variable is ignored.In this article,we propose the pseudo maximum likelihood method to estimate treatment effects in nonlinear models.The proposed method allows the unobserved confounding and random error terms to exist in an arbitrary relationship(such as,add or multiply),and the unobserved confounding have different influence directions on treatment variables and outcome variables.The proposed estimator is consistent and asymptotically normally distributed.Simulation studies show that the proposed estimator performs better than the special regression estimator,and the proposed method is stable for various distribution of error terms.Finally,the proposed method is applied to the real data that studies the influence of individuals have health insurance on an individual’s decision to visit a doctor.展开更多
For the purpose of exploring the factors affecting injury severity of children and adolescents involved in traffic crashes in Greece,disaggregate crash data including 13,431 involving children and adolescents from all...For the purpose of exploring the factors affecting injury severity of children and adolescents involved in traffic crashes in Greece,disaggregate crash data including 13,431 involving children and adolescents from all regions of Greece for the period 2006–2015 were utilized.In order to identify factors affecting injury severity and account for potential unobserved heterogeneity,a series of mixed logit models were utilized.To explore and address potential temporal instability of crash-related risk factors,the likelihood ratio test was applied.Results indicated that night crashes,crashes outside urban areas as well as crashes involving bicycles or powered-two-wheelers are associated with higher injury severity of children and adolescents.Interestingly,crashes involving pedestrians are associated with lower injury severity than head-on collisions and run-off-road collisions with fixed objects.Side and sideswipe crashes also result in lower injury severities.The likelihood ratio test indicated that crash-related factors are instable when comparing the models utilizing data before and after 2010 respectively.This study contributes to the current knowledge in the field,as to the best of our knowledge this is the first study that addresses unobserved heterogeneity when analyzing child and adolescent injury severity.Overall,the findings of this study provide useful insights and could assist in unveiling crash risk factors and prioritize programs and measures to promote road safety of children and adolescents.展开更多
基金supported by the National Natural Science Foundation of China(61773206)the Natural Science Foundation of Jiangsu Province of China(BK20170131)+1 种基金Jiangsu Overseas Visiting Scholar Program for University Prominent Young&Middle-aged Teachers and Presidents(2019-19)the Deanship of Scientific Research(DSR)at King Abdulaziz University(RG-20-135-38)。
文摘In this paper,a deadlock prevention policy for robotic manufacturing cells with uncontrollable and unobservable events is proposed based on a Petri net formalism.First,a Petri net for the deadlock control of such systems is defined.Its admissible markings and first-met inadmissible markings(FIMs)are introduced.Next,place invariants are designed via an integer linear program(ILP)to survive all admissible markings and prohibit all FIMs,keeping the underlying system from reaching deadlocks,livelocks,bad markings,and the markings that may evolve into them by firing uncontrollable transitions.ILP also ensures that the obtained deadlock-free supervisor does not observe any unobservable transition.In addition,the supervisor is guaranteed to be admissible and structurally minimal in terms of both control places and added arcs.The condition under which the supervisor is maximally permissive in behavior is given.Finally,experimental results with the proposed method and existing ones are given to show its effectiveness.
文摘This paper investigates the problem of cooperative localization(CL)for a multi-robot system(MRS)under dynamic measurement topology,which involves a group of robots collectively estimating their poses with respect to a common reference frame using ego-motion measurements and robot-to-robot relative measurements.The authors provide a theoretical analysis of the time-varying unobservable subspace and propose a consistent cooperative localization algorithm.First,the authors introduce the relative measurement graph(RMG)to represent the relative pose measurements obtained by the MRS at each instant.Then,the authors derive the local observability matrix over a time interval.An equivalent relationship is established between the local observability matrix and the spectral matrices of the RMG.Moreover,the authors present a method for constructing the unobservable subspace based on the RMG under different topology conditions.Based on this analysis,the authors design a consistent cooperative localization algorithm that satisfies the constraints of the time-varying unobservable subspace.An analytical optimal solution is derived for the constrained optimization problem.Monte Carlo numerical simulations are conducted to demonstrate the consistency and accuracy of the proposed method.
文摘Purpose-The border control becomes challenging when a protected region is large and there is a limited number of border patrols.This research paper proposes a novel heuristic-based patrol path planning scheme in order to efficiently patrol with resource scarcity.Design/methodology/approach-The trespasser influencing score,which is determined from the environmental characteristics and trespassing statistic of the region,is used as a heuristic for measuring a chance of approaching a trespasser.The patrol plan is occasionally updated with a new trespassing statistic during a border operation.The performance of the proposed patrol path planning scheme was evaluated and compared with other patrol path planning schemes by the empirical experiment under different scenarios.Findings-The result from the experiment indicates that the proposed patrol planning outperforms other patrol path planning schemes in terms of the trespasser detection rate,when more environment-aware trespassers are in the region.Research limitations/implications-The experiment was conducted through simulated agents in simulated environment,which were assumed to mimic real behavior and environment.Originality/value-This research paper contributes a heuristic-based patrol path planning scheme that applies the environmental characteristics and dynamic statistic of the region,as well as a border surveillance problem model that would be useful for mobile sensor planning in a border surveillance application.
文摘Survival analysis is a fundamental tool in medical science for time-to-event data. However, its application to colony organisms like bees poses challenges due to their social nature. Traditional survival models may not accurately capture the interdependence among individuals within a colony. Frailty models, accounting for shared risks within groups, offer a promising alternative. This study evaluates the performance of semi-parametric shared frailty models (gamma, inverse normal, and positive stable-in comparison to the traditional Cox model using bees’ survival data). We examined the effect of misspecification of the frailty distribution on regression and heterogeneity parameters using simulation and concluded that the heterogeneity parameter was more sensitive to misspecification of the frailty distribution and choice of initial parameters (cluster size and true heterogeneity parameter) compared to the regression parameter. From the data, parameter estimates for covariates were close for the four models but slightly higher for the Cox model. The shared gamma frailty model provided a better fit to the data in comparison with the other models. Therefore, when focusing on regression parameters, the gamma frailty model is recommended. This research underscores the importance of tailored survival methodologies for accurately analyzing time-to-event data in social organisms.
基金Project supported by the National Natural Science Foundation of China (No. 60504024), Zhejiang Provincial Education Department(No. 20050905), and "151 Talent Project" of Zhejiang Province,China
文摘This paper deals with the synthesis of Petri net supervisor enforcing the more expressive constraints including marking terms, firing vector terms and Parikh vector terms. The method is developed to handle uncontrollable and unobservable transitions existing in the constraints. The “greater-than or equal” general constraints can also be transformed into “less-than or equal” Parikh constraints. An example is analyzed to show how the problem is solved. General constraint is first transformed into Parikh vector constraints, and Matrix-Transformation is proposed to obtain the admissible constraints without uncontrollable and unobservable transitions. Then the supervisor can be constructed based on constraints only consisting of Parikh vector terms. The method is proved to be more concise and effective than the method presented by Iordache and Moody especially when applied to large scale systems.
基金the National Natural Science Foundation of China (No. 90405017, 60274021, 60334040)China Postdoctoral Science Foundation (No.20060400415)the 973 Program of China (No. 2002CB312205)
文摘The observability problem of switched linear singular（SLS） systems is studied in this paper. Based on the observability definition, the unobservable subspaces of given switching laws are investigated under the condition that all subsystems are regular. A necessary condition and a sufficient condition for observability of SLS systems are given. It is shown that the observability and controllability are dual for some special SLS systems with circulatory switching laws. The method developed here is applicable to the observability analysis of normal switched linear systems.
文摘This paper analyzes the adoption dynamics of improved rainfed maize seeds disseminated in Senegal in 2013 by the West African Agricultural Productivity Program (WAAPP). We group maize producers into five groups (non-adopters, laggards/abandoners, late adopters, followers and pioneers/innovators) and take into account the heterogeneity of unobservable characteristics of the producers. In the pioneers/innovators group, the availability of labour, household size, shocks, and frequency of access to advice positively influence adoption, whereas financial constraints and high numbers of plots reduce the probability of adoption. Producers in the followers’ category tend to be older and more educated than those in the other categories. However, food insecurity and shocks such as diseases hamper adoption. For the group of late adopters, household size and available storage infrastructures explain adoption. However, the number of plots and shocks reduces their probability of adoption. Laggards tend to face shocks and food insecurity. The authors recommend to consider the dynamics of the adoption of technological innovations and heterogeneity of the characteristics of adopters groups in future research. They also recommend farmers to increase their adoption rate of the “Early Thai” and “Suwan 1” seed varieties thanks to their higher yields compared to traditional varieties. Also, a higher adoption rate would positively impact the food security of maize farmers in Eastern Senegal and High Casamance, especially in terms of availability. Other studies measuring the number of years needed for large-scale adoption of improved seed varieties should be conducted.
基金supported by the National Natural Science Foundation of China(Grant No.31701803)Changsha Natural Science Foundation,China(Grant No.kq2202336)the Special Project of Hunan Innovative Province Construction,China(Grant No.S2021ZCKPZT0004)。
文摘Despite increasing knowledge of barnyardgrass(Echinochloa crus-galli) interference with rice, relatively little is known how endophytes improve the ability of rice against barnyardgrass stress. Here, we provided a detailed temporal characterization of rice root-associated microbiomes during co-cultivation with barnyardgrass and a comparison with the microbiomes of weed-free rice plants. Alpha diversity analysis indicated that barnyardgrass had the opposite effects on endophytic bacteria and fungi in rice roots, in terms of the community diversity, richness and coverage at the rice seedling stage. Principal coordinate analysis showed that barnyardgrass had only a minor effect on the community composition of endophytes in rice roots at the rice seedling stage, but showed a significant and maximum interference at the heading stage. Rice recruited many endophytes to resist biotic stress from barnyardgrass, especially for fungi. PICRUSt(phylogenetic investigation of communities by reconstruction of unobserved states) predictive analysis indicated that 23 metabolic pathways of bacteria were overrepresented in rice. In addition, the main trophic mode of fungi was pathotroph according to FUNGuild analysis. A positive correlation between bacteria and fungi in rice roots was found via network analysis. Anaeromyxobacter, Azospira and Pseudolabrys were the vital bacteria, Phaeosphaeria and Funneliformis were the dominant fungi in maintaining the stability of the ecological network. These results provided data and a theoretical basis for the in-depth understanding of what role endophytes play in rice resistance to barnyardgrass stress and will have implications on improving the resistance of rice against biotic stress using root microbiota.
文摘This paper mainly discusses the singular linear systems of distributional version. By using its matrices coefficients and some invariant subspaces, the distributionally weakly obseervability and the impulse observability are analyzed.
文摘This study investigates the degree of capital mobility in a panel of 16 Latin American and 4 Caribbean countries during 1960 to 2017 against the backdrop of the Feldstein-Horioka hypothesis by applying recent panel data techniques.This is the first study on capital mobility in Latin American and Caribbean countries to employ the recently developed panel data procedure of the dynamic common correlated effects modeling technique of Chudik and Pesaran(J Econ 188:393–420,2015)and the error-correction testing of Gengenbach,Urbain,and Westerlund(Panel error correction testing with global stochastic trends,2008,J Appl Econ 31:982–1004,2016).These approaches address the serious panel data econometric issues of crosssection dependence,slope heterogeneity,nonstationarity,and endogeneity in a multifactor error-structure framework.The empirical findings of this study reveal a low average(mean)savings–retention coefficient for the panel as a whole and for most individual countries,as well as indicating a cointegration relationship between saving and investment ratios.The results indicate that there is a relatively high degree of capital mobility in the Latin American and Caribbean countries in the short run,while the long-run solvency condition is maintained,which is due to reduced frictions in goods and services markets causing increase competition.Increased capital mobility in these countries can promote economic growth and hasten the process of globalization by creating a conducive economic environment for FDI in these countries.
文摘This paper presents an procedure for purifying training data sets （i.e., past occurrences of slope failures） for inverse estimation on unobserved trigger factors of ＂different types of simultaneous slope failures＂. Due to difficulties in pixel-by-pixel observations of trigger factors, as one of the measures, the authors had proposed an inverse analysis algorithm on trigger factors based on SEM （structural equation modeling）. Through a measurement equation, the trigger factor is inversely estimated, and a TFI （trigger factor influence） map can be also produced. As a subsequence subject, a purification procedure of training data set should be constructed to improve the accuracy of TFI map which depends on the representativeness of given training data sets of different types of slope failures. The proposed procedure resamples the matched pixels between original groups of past slope failures （i.e., surface slope failures, deep-seated slope failures, landslides） and classified three groups by K-means clustering for all pixels corresponding to those slope failures. For all cases of three types of slope failures, the improvement of success rates with respect to resampled training data sets was confirmed. As a final outcome, the differences between TFI maps produced by using original and resampled training data sets, respectively, are delineated on a DIF map （difference map） which is useful for analyzing trigger factor influence in terms of ＂risky- and safe-side assessment＂ sub-areas with respect to ＂different types of simultaneous slope failures＂.
文摘Drowsy driving has received comparatively less attention in traffic safety literature when compared to other safety issues,despite its devastating impact on society in terms of human life lost and associated economic burdens.Therefore,this significant safety threat requires a thorough investigation.To address the temporal instability of factors contributing to crashes involving drowsy drivers,this paper divides the crash data into four time periods while capturing unobserved heterogeneity in the means and variances of random parameters.To explore the determinants affecting the severity of injuries sustained by drowsy drivers involved in single-vehicle crashes,injury outcomes are categorized into three groups:serious,moderate,and no injuries.Using four years of crash data from the state of Washington between 2013 and 2016,a wide range of factors were examined,including driver characteristics,roadway conditions,crash characteristics,vehicle conditions,lighting conditions,and temporal factors.The estimation results reveal that there is temporal instability in terms of the effect of determinants on injury severity across the years.However,some factors exhibit stable effects,such as female drivers,sober drivers,and non-hit-and-run crashes.Based on the findings of this study,decision-makers,traffic engineers,and traffic authorities can gain valuable knowledge and insights into the factors contributing to drowsy-related crashes,enabling them to make informed recommendations for safety countermeasures.
文摘Bicycling has been actively promoted as a clean and efficient mode of commute.Besides,due to the personal and societal benefits it provides,it has been adopted by many city dwellers for short-distance trips.Despite the integral role this active transport mode plays,it is unfortunately associated with a high risk of fatalities in the event of a traffic crash as they are not protected.Many studies have been conducted in several jurisdictions to examine the factors contributing to crashes involving these vulnerable road users.In the case of Louisiana which is currently experiencing increased cases of severe and fatal bicycleinvolved crashes,less attention has been paid to investigating the critical factors influencing bicyclist injury severity outcomes using more detailed data and advanced econometric modeling frameworks to help propose adequate policies to improve the safety of riders.Against this background,this study examined the key contributing factors influencing bicyclist injuries by using more detailed roadway crash data spanning 2010-2016 obtained from the state of Louisiana.The study then applies an advanced random parameter logit modeling with heterogeneity in means and variances to address the unobserved heterogeneity issue associated with traffic crash data.To overcome the imbalanced data issue,three major crash injury levels were used instead of the conventional five crash injury levels.Besides,the data groups classified under each injury level were compared for the final variable selection.The study found that distracted drivers,elderly bicyclists,careless operations,and riding in dark conditions increase the probability of having severe injuries in vehicle-bicyclist crashes.Moreover,the variables for straight-level roadways and city streets decrease the odds of severe injuries.The straight-level roadway may provide better sight distance for both drivers and bicyclists,and complex environments like city streets discourage crashes with severe injuries.
文摘This research investigates the intricate relationship between the number of lanes on highways and injury severities sustained by commercial motor vehicle(CMV)drivers.Many studies have addressed crash determinants,but the safety implications of differing numbers of lanes remain insufficiently examined,especially during the highway planning stages.Our study fills this knowledge gap by analyzing injury severity crash factors for a varied number of lane scenarios.Employing a random parameter logit modeling framework,we differentiated injury levels for 2-4 lanes and 6-10 lanes.Key factors were identified for each number of lanes,with older,loss of vehicle control,non-collision crashes,and crashes,on locations where grade or hill existed,being more perilous and increasing the risk of sustaining severe injuries on 2-lane highways.For 4-lane highways,factors such as non-Oregonian drivers,older drivers,crashes that occurred during the spring season,and crashes that occurred beyond shoulders were associated with an elevated probability of being involved in severe injury crashes.Regarding highways with 6 lanes and higher,driving too fast for conditions and driver error(drowsy,fatigued,inattentive,or reckless)increases the odds of being involved in higher levels of injury crashes.To enhance truck driver safety,we recommend the implementation of electronic stability control in CMVs,with moderated speeds on graded sections,improved curve markers,and robust public safety campaigns.
文摘This paper provides an integrated analytical framework to investigate the demographic and behavioural factors that significantly influence public support for pedestrianisation. Pedestrianisation is often introduced by local authorities with the intention of improving air quality, the walkability of streets, road safety and opportunities for the local economy, however, issues remain regarding how accessible pedestrianised areas are for individuals who have conditions that limit their mobility. Using data from a survey, conducted during 2020 in Edinburgh (UK), public perceptions towards pedestrianisation were investigated through statistical testing and the development of random forest and ordered probit models. The random forest approach can help identify the relative importance of explanatory variables, whereas the ordered probit models can unveil the demographic and behavioural determinants of public support. To account for the potential effect of unobserved heterogeneity within respondents’ perceptions, random parameters were also considered in the ordered probit modelling framework. Initial results showed that residents are generally supportive of most issues surrounding pedestrianisation. Random parameters ordered probit modelling identified mode of travel and trip frequency as significant factors affecting key aspects of public support, such that active travellers were significantly more likely to support pedestrianisation, while those who rarely visit Edinburgh city centre were more likely to oppose pedestrianisation. Overall, a variety of independent analyses and modelling approaches suggest common influences on opinion, including behavioural patterns relating to transport modal choice and trip frequency, while disability was also found to have considerable effect on support as a fixed and random parameter. The statistical models are evaluated in terms of goodness-of-fit measures, before policy implications are discussed.
基金This work was supported in part by the U.S.Department of Energy(No.DEEE0009355)the National Science Foundation(NSF)(No.ECCS-2145063)the Electric Power Research Institute(EPRI)(No.10013085)。
文摘As the phasor measurement unit(PMU)placement problem involves a cost-benefit trade-off,more PMUs get placed on higher-voltage buses.However,this leads to the fact that many lower-voltage levels of the bulk power system cannot be observed by PMUs.This lack of visibility then makes timesynchronized state estimation of the full system a challenging problem.In this paper,a deep neural network-based state estimator(DeNSE)is proposed to solve this problem.The DeNSE employs a Bayesian framework to indirectly combine the inferences drawn from slow-timescale but widespread supervisory control and data acquisition(SCADA)data with fast-timescale but selected PMU data,to attain sub-second situational awareness of the full system.The practical utility of the DeNSE is demonstrated by considering topology change,non-Gaussian measurement noise,and detection and correction of bad data.The results obtained using the IEEE 118-bus system demonstrate the superiority of the DeNSE over a pure SCADA state estimator and a PMU-only linear state estimator from a technoeconomic viability perspective.Lastly,the scalability of the DeNSE is proven by estimating the states of a large and realistic 2000-bus synthetic Texas system.
文摘It is only the observable part of the real world that can be stored in data. For such incomplete and ill-structured data, data crystallizing aims at presenting the hidden structure among events including unobservable events. This is realized by data crystallization, where dummy items, corresponding to potential existence ofunobservable events, are inserted to the given data. These dummy items and their relations with observable events are visualized by applying KeyGraph to the data with dummy items, like the crystallization of snow where dusts are involved in the formation of crystallization of water molecules. For tuning the granularity level of structure to be visualized, the tool of data crystallization is integrated with human＇s process of understanding significant scenarios in the real world. This basic method is expected to be applicable for various real world domains where previous methods of chance-discovery lead human to successful decision making. In this paper, we apply the data crystallization with human-interactive annealing （DCHA） to the design of products in a real company. The results show its effect to industrial decision making.
文摘This paper investigates an M/M/1 constant retrial queue with reserved time and vacations.A new arriving customer will take up the server and accept service immediately if the server is idle.Otherwise,if the server is busy or on vacation,customers have to join a retrial orbit and wait for retry.Once a service is completed,the server will reserve a random time to seek a customer from the orbit at a constant retrial rate.If there is no arrivals(from the orbit or outside)during the idle period,to save energy,the server will take a vacation.This paper studies the fully unobservable case.First,the steady-state condition of the system is analyzed by using the Foster’s criterion,and the customers’expected waiting time is obtained based on the generating function technique.And then,by introducing an appropriate revenue structure,the equilibrium strategies of customers and the socially optimal strategy are all derived.Furthermore,a comparison between them is made and the effect of some main system parameters is studied.
基金supported by the National Natural Science Foundation of China (Nos.12101545)by the natural science foundation of Inner Mongolia Autonomous Region (2022MS01007)。
文摘Estimation of treatment effects is one of the crucial mainstays in economics and sociology studies.The problem will become more serious and complicated if the treatment variable is endogenous for the presence of unobserved confounding.The estimation and conclusion are likely to be biased and misleading if the endogeny of treatment variable is ignored.In this article,we propose the pseudo maximum likelihood method to estimate treatment effects in nonlinear models.The proposed method allows the unobserved confounding and random error terms to exist in an arbitrary relationship(such as,add or multiply),and the unobserved confounding have different influence directions on treatment variables and outcome variables.The proposed estimator is consistent and asymptotically normally distributed.Simulation studies show that the proposed estimator performs better than the special regression estimator,and the proposed method is stable for various distribution of error terms.Finally,the proposed method is applied to the real data that studies the influence of individuals have health insurance on an individual’s decision to visit a doctor.
基金funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 754462
文摘For the purpose of exploring the factors affecting injury severity of children and adolescents involved in traffic crashes in Greece,disaggregate crash data including 13,431 involving children and adolescents from all regions of Greece for the period 2006–2015 were utilized.In order to identify factors affecting injury severity and account for potential unobserved heterogeneity,a series of mixed logit models were utilized.To explore and address potential temporal instability of crash-related risk factors,the likelihood ratio test was applied.Results indicated that night crashes,crashes outside urban areas as well as crashes involving bicycles or powered-two-wheelers are associated with higher injury severity of children and adolescents.Interestingly,crashes involving pedestrians are associated with lower injury severity than head-on collisions and run-off-road collisions with fixed objects.Side and sideswipe crashes also result in lower injury severities.The likelihood ratio test indicated that crash-related factors are instable when comparing the models utilizing data before and after 2010 respectively.This study contributes to the current knowledge in the field,as to the best of our knowledge this is the first study that addresses unobserved heterogeneity when analyzing child and adolescent injury severity.Overall,the findings of this study provide useful insights and could assist in unveiling crash risk factors and prioritize programs and measures to promote road safety of children and adolescents.
