BACKGROUND Hepatitis B(HB)and hepatitis C(HC)place the largest burden in China,and a goal of eliminating them as a major public health threat by 2030 has been set.Making more informed and accurate forecasts of their s...BACKGROUND Hepatitis B(HB)and hepatitis C(HC)place the largest burden in China,and a goal of eliminating them as a major public health threat by 2030 has been set.Making more informed and accurate forecasts of their spread is essential for developing effective strategies,heightening the requirement for early warning to deal with such a major public health threat.AIM To monitor HB and HC epidemics by the design of a paradigmatic seasonal autoregressive fractionally integrated moving average(SARFIMA)for projections into 2030,and to compare the effectiveness with the seasonal autoregressive integrated moving average(SARIMA).METHODS Monthly HB and HC incidence cases in China were obtained from January 2004 to June 2023.Descriptive analysis and the Hodrick-Prescott method were employed to identify trends and seasonality.Two periods(from January 2004 to June 2022 and from January 2004 to December 2015,respectively)were used as the training sets to develop both models,while the remaining periods served as the test sets to evaluate the forecasting accuracy.RESULTS There were incidents of 23400874 HB cases and 3590867 HC cases from January 2004 to June 2023.Overall,HB remained steady[average annual percentage change(AAPC)=0.44,95%confidence interval(95%CI):-0.94-1.84]while HC was increasing(AAPC=8.91,95%CI:6.98-10.88),and both had a peak in March and a trough in February.In the 12-step-ahead HB forecast,the mean absolute deviation(15211.94),root mean square error(18762.94),mean absolute percentage error(0.17),mean error rate(0.15),and root mean square percentage error(0.25)under the best SARFIMA(3,0,0)(0,0.449,2)12 were smaller than those under the best SARIMA(3,0,0)(0,1,2)12(16867.71,20775.12,0.19,0.17,and 0.27,respectively).Similar results were also observed for the 90-step-ahead HB,12-step-ahead HC,and 90-step-ahead HC forecasts.The predicted HB incidents totaled 9865400(95%CI:7508093-12222709)cases and HC totaled 1659485(95%CI:856681-2462290)cases during 2023-2030.CONCLUSION Under current interventions,China faces enormous challenges to eliminate HB and HC epidemics by 2030,and effective strategies must be reinforced.The integration of SARFIMA into public health for the management of HB and HC epidemics can potentially result in more informed and efficient interventions,surpassing the capabilities of SARIMA.展开更多
In this paper, the problems of stability for a class of switched positive descriptor systems(SPDSs)with average dwell time(ADT) switching are investigated. First, based on the equivalent switched system and the proper...In this paper, the problems of stability for a class of switched positive descriptor systems(SPDSs)with average dwell time(ADT) switching are investigated. First, based on the equivalent switched system and the properties of the projector matrix, sufficient stabilities are given for the underlying systems in both continuoustime and discrete-time contexts. Then, a sufficient stability condition for the SPDS with both stable and unstable subsystems is obtained. The stability results for the SPDSs are represented in terms of a set of linear programmings(LPs) by the multiple linear co-positive Lyapunov function(MLCLF) approach. Finally, three numerical examples are given to illustrate the effectiveness of the obtained theoretical results.展开更多
In this paper,we consider the average-consensus problem with communication time delays and noisy links.We analyze two different cases of coupling topologies：fixed and switching topologies.By utilizing the stability t...In this paper,we consider the average-consensus problem with communication time delays and noisy links.We analyze two different cases of coupling topologies：fixed and switching topologies.By utilizing the stability theory of the stochastic differential equations,we analytically show that the average consensus could be achieved almost surely with the perturbation of noise and the communication time delays even if the time delay is time-varying.The theoretical results show that multi-agent systems can tolerate relatively large time delays if the noise is weak,and they can tolerate relatively strong noise if the time delays are low.The simulation results show that systems with strong noise intensities yield slow convergence.展开更多
This paper studies the weighted average consensus problem for networks of agents with fixed directed asymmetric unbalance information exchange topology. We suppose that the classical distributed consensus protocol is ...This paper studies the weighted average consensus problem for networks of agents with fixed directed asymmetric unbalance information exchange topology. We suppose that the classical distributed consensus protocol is destroyed by diverse time-delays which include communication time-delay and self time-delay. Based on the generalized Nyquist stability criterion and the Gerschgorin disk theorem, some sufficient conditions for the consensus of multi-agent systems are obtained. And we give the expression of the weighted average consensus value for our consensus protocol. Finally, numerical examples are presented to illustrate the theoretical results.展开更多
This paper investigates the correlation between stochastic resonance （SR） and the average phase-synchronization time which is between the input signal and the output signal in a bistable system driven by colour-corr...This paper investigates the correlation between stochastic resonance （SR） and the average phase-synchronization time which is between the input signal and the output signal in a bistable system driven by colour-correlated noises. The results show that the output signal-to-noise ratio can reach a maximum with the increase of the average phase- synchronization time, which may be helpful for understanding the principle of SR from the point of synchronization; however, SR and the maximum of the average phase-synchronization time appear at different optimal noise level, moreover, the effects on them of additive and multiplicative noise are different.展开更多
The average consensus problem in a directed network of multi-agent systems with communication time delays was investigated. The directed networks were balanced and weakly connected with fixed or switching topology dig...The average consensus problem in a directed network of multi-agent systems with communication time delays was investigated. The directed networks were balanced and weakly connected with fixed or switching topology digraph. Based on frequency domain analysis method, a sufficient condition of asymptotic stability of multi-agent systems with time delays was obtained,where the analytic formula between the maximum time delay and the directed network structure was provided. The maximum time delay can be derived directly and easily by the eigenvalue of Laplacian L. Numerical examples confirm the effectiveness of the proposed technique.展开更多
This paper presents a new method of detecting multi-periodicities in a seasonal time series. Conventional methods such as the average power spectrum or the autocorrelation function plot have been used in detecting mul...This paper presents a new method of detecting multi-periodicities in a seasonal time series. Conventional methods such as the average power spectrum or the autocorrelation function plot have been used in detecting multiple periodicities. However, there are numerous cases where those methods either fail, or lead to incorrectly detected periods. This, in turn in applications, produces improper models and results in larger forecasting errors. There is a strong need for a new approach to detecting multi-periodicities. This paper tends to fill this gap by proposing a new method which relies on a mathematical instrument, called the Average Power Function of Noise (APFN) of a time series. APFN has a prominent property that it has a strict local minimum at each period of the time series. This characteristic helps one in detecting periods in time series. Unlike the power spectrum method where it is assumed that the time series is composed of sinusoidal functions of different frequencies, in APFN it is assumed that the time series is periodic, the unique and a much weaker assumption. Therefore, this new instrument is expected to be more powerful in multi-periodicity detection than both the autocorrelation function plot and the average power spectrum. Properties of APFN and applications of the new method in periodicity detection and in forecasting are presented.展开更多
The average consensus in undirected networks of multi-agent with both fixed and switching topology coupling multiple time-varying delays is studied. By using orthogonal transformation techniques, the original system c...The average consensus in undirected networks of multi-agent with both fixed and switching topology coupling multiple time-varying delays is studied. By using orthogonal transformation techniques, the original system can be turned into a reduced dimensional system and then LMI-based method can be applied conveniently. Convergence analysis is conducted by constructing Lyapunov-Krasovskii function. Sufficient conditions on average consensus problem with multiple time-varying delays in undirected networks are obtained via linear matrix inequality (LMI) techniques. In particular, the maximal admissible upper bound of time-varying delays can be easily obtained by solving several simple and feasible LMIs. Finally, simulation examples are given to demonstrate the effectiveness of the theoretical results.展开更多
Time domain averaging(TDA) is essentially a comb filter,it cannot extract the specified harmonics which may be caused by some faults,such as gear eccentric.Meanwhile,TDA always suffers from period cutting error(PCE) t...Time domain averaging(TDA) is essentially a comb filter,it cannot extract the specified harmonics which may be caused by some faults,such as gear eccentric.Meanwhile,TDA always suffers from period cutting error(PCE) to different extent.Several improved TDA methods have been proposed,however they cannot completely eliminate the waveform reconstruction error caused by PCE.In order to overcome the shortcomings of conventional methods,a flexible time domain averaging(FTDA) technique is established,which adapts to the analyzed signal through adjusting each harmonic of the comb filter.In this technique,the explicit form of FTDA is first constructed by frequency domain sampling.Subsequently,chirp Z-transform(CZT) is employed in the algorithm of FTDA,which can improve the calculating efficiency significantly.Since the signal is reconstructed in the continuous time domain,there is no PCE in the FTDA.To validate the effectiveness of FTDA in the signal de-noising,interpolation and harmonic reconstruction,a simulated multi-components periodic signal that corrupted by noise is processed by FTDA.The simulation results show that the FTDA is capable of recovering the periodic components from the background noise effectively.Moreover,it can improve the signal-to-noise ratio by 7.9 dB compared with conventional ones.Experiments are also carried out on gearbox test rigs with chipped tooth and eccentricity gear,respectively.It is shown that the FTDA can identify the direction and severity of the eccentricity gear,and further enhances the amplitudes of impulses by 35%.The proposed technique not only solves the problem of PCE,but also provides a useful tool for the fault symptom extraction of rotating machinery.展开更多
The primary objective of the paper is to forecast the beta values of companies listed on Sensex,Bombay Stock Exchange(BSE).The BSE Sensex constitutes 30 top most companies listed which are popularly known as blue-chip...The primary objective of the paper is to forecast the beta values of companies listed on Sensex,Bombay Stock Exchange(BSE).The BSE Sensex constitutes 30 top most companies listed which are popularly known as blue-chip companies.To reach out the predefined objectives of the research,Auto Regressive Integrated Moving Average method is used to forecast the future risk and returns for 10 years of historical data from April 2007 to March 2017.Validation accomplished by comparison of forecasted and actual beta values for the hold back period of 2 years.Root-Mean-Square-Error and Mean-Absolute-Error both are used for accuracy measurement.The results revealed that out of 30 listed companies in the BSE Sensex,10 companies’exhibits high beta values,12 companies are with moderate and 8 companies are with low beta values.Further,it is to note that Housing Development Finance Corporation(HDFC)exhibits more inconsistency in terms of beta values though the average beta value is lowest among the companies under the study.A mixed trend is found in forecasted beta values of the BSE Sensex.In this analysis,all the p-values are less than the F-stat values except the case of Tata Steel and Wipro.Therefore,the null hypotheses were rejected leaving Tata Steel and Wipro.The values of actual and forecasted values are showing the almost same results with low error percentage.Therefore,it is concluded from the study that the estimation ARIMA could be acceptable,and forecasted beta values are accurate.So far,there are many studies on ARIMA model to forecast the returns of the stocks based on their historical data.But,hardly there are very few studies which attempt to forecast the returns on the basis of their beta values.Certainly,the attempt so made is a novel approach which has linked risk directly with return.On the basis of the present study,authors try to through light on investment decisions by linking it with beta values of respective stocks.Further,the outcomes of the present study undoubtedly useful to academicians,researchers,and policy makers in their respective area of studies.展开更多
Periodic components are of great significance for fault diagnosis and health monitoring of rotating machinery.Time synchronous averaging is an effective and convenient technique for extracting those components.However...Periodic components are of great significance for fault diagnosis and health monitoring of rotating machinery.Time synchronous averaging is an effective and convenient technique for extracting those components.However,the performance of time synchronous averaging is seriously limited when the separate segments are poorly synchronized.This paper proposes a new averaging method capable of extracting periodic components without external reference and an accurate period to solve this problem.With this approach,phase detection and compensation eliminate all segments'phase differences,which enables the segments to be well synchronized.The effectiveness of the proposed method is validated by numerical and experimental signals.展开更多
In compartment fires (houses, buildings, underground, warehouse, etc.), smokes are a major dan- ger during firemen intervention. Most of the time, they are at high temperature (>800?C) and they flow everywhere thro...In compartment fires (houses, buildings, underground, warehouse, etc.), smokes are a major dan- ger during firemen intervention. Most of the time, they are at high temperature (>800?C) and they flow everywhere through many kinds of ducts, which leads to the propagation of the combustion by the creation other fires in places which may be far away from the initial fire. In this paper, we present a new approach of the problem, which allows to better follow the fire behavior and especially to detect the dangers that may appear and endanger firefighters. This approach consists in a mathematical analysis based on the comparison of moving averages centered in the past, calculated on the temperature recordings of the smokes. As a consequence, this method may allow to improve decision support in real time and therefore to improve the security and the efficiency of firefighters in their operations against that kind of fires.展开更多
We calculate the average speed of a projectile in the absence of air resistance, a quantity that is missing from the treatment of the problem in the literature. We then show that this quantity is equal to the time-ave...We calculate the average speed of a projectile in the absence of air resistance, a quantity that is missing from the treatment of the problem in the literature. We then show that this quantity is equal to the time-average instantaneous speed of the projectile, but different from its space-average instantaneous speed. It is then shown that this behavior is shared by general motion of all particles regardless of the dimensionality of motion and the nature of the forces involved. The equality of average speed and time-average instantaneous speed can be useful in situations where the calculation of one is more difficult than the other. Thus, making it more efficient to calculate one by calculating the other.展开更多
In the context of the Diagnosis Related Groups(DRGs)system,the orthopedic hospital implemented refined drug control to provide a pharmacological reference for promoting rational clinical drug use.A statistical analysi...In the context of the Diagnosis Related Groups(DRGs)system,the orthopedic hospital implemented refined drug control to provide a pharmacological reference for promoting rational clinical drug use.A statistical analysis was conducted on the hospital’s data from January to December 2021(prior to the implementation of control),focusing on the types of unreasonable prescriptions.A multi-dimensional analysis was also conducted to identify the underlying causes of inappropriate medication practices.Following this,refined drug control measures were introduced,and data from January to December 2022(post-control)were compared,examining factors such as the average drug cost,drug expenses for the IC29 diagnosis group,and the drug cost ratio.An interrupted time-series analysis was employed to evaluate the effects of these interventions.The results showed that after the implementation of refined drug control in the orthopedic department,significant reductions were observed in the average cost per patient,average drug cost per patient,drug cost ratio,cost consumption index,average length of hospital stay,and allocation ratio(P<0.05).In particular,the first month of control(January 2022)saw a marked decrease in average drug costs per patient by 1272.90 yuan(P<0.01),a reduction in the drug cost ratio by 0.98%,and a decline in drug costs for the IC29 diagnosis group by 616.79 yuan(P>0.05).Moreover,the rate of unreasonable inappropriate prescribing dropped dramatically from 40.48%in 2021 to 3.57%by December 2022.The refined control of drug use within the orthopedic hospital significantly improved the rationality of clinical prescribing practices,reduced the occurrence of adverse drug reactions,and enhanced patient adherence to prescribed treatments.These findings demonstrated considerable clinical value in promoting efficient and safe drug use.展开更多
Air pollution,specifically fine particulate matter(PM2.5),represents a critical environmental and public health concern due to its adverse effects on respiratory and cardiovascular systems.Accurate forecasting of PM2....Air pollution,specifically fine particulate matter(PM2.5),represents a critical environmental and public health concern due to its adverse effects on respiratory and cardiovascular systems.Accurate forecasting of PM2.5 concentrations is essential for mitigating health risks;however,the inherent nonlinearity and dynamic variability of air quality data present significant challenges.This study conducts a systematic evaluation of deep learning algorithms including Convolutional Neural Network(CNN),Long Short-Term Memory(LSTM),and the hybrid CNN-LSTM as well as statistical models,AutoRegressive Integrated Moving Average(ARIMA)and Maximum Likelihood Estimation(MLE)for hourly PM2.5 forecasting.Model performance is quantified using Root Mean Squared Error(RMSE),Mean Absolute Error(MAE),Mean Absolute Percentage Error(MAPE),and the Coefficient of Determination(R^(2))metrics.The comparative analysis identifies optimal predictive approaches for air quality modeling,emphasizing computational efficiency and accuracy.Additionally,CNN classification performance is evaluated using a confusion matrix,accuracy,precision,and F1-score.The results demonstrate that the Hybrid CNN-LSTM model outperforms standalone models,exhibiting lower error rates and higher R^(2) values,thereby highlighting the efficacy of deep learning-based hybrid architectures in achieving robust and precise PM2.5 forecasting.This study underscores the potential of advanced computational techniques in enhancing air quality prediction systems for environmental and public health applications.展开更多
With the current situation of insecurity in Nigeria and the worsening condition of Nigerian roads, there is increasing demand for air travel. This increasing demand for airline services amidst limited resources result...With the current situation of insecurity in Nigeria and the worsening condition of Nigerian roads, there is increasing demand for air travel. This increasing demand for airline services amidst limited resources results in passenger dissatisfaction and reduction of revenue for airports and airlines. The dynamics of service demand and resource supply result in check-in issues for all the stakeholders in the commercial aviation industry. Hence, this research simulated the developed model for travelers’ check-in process at the “D Wing” of the Departure Section of Murtala Muhammed International Airport (MMIA), Ikeja, using Arena Software Tool. The simulation of the developed model was carried out by varying five different configurations of the servers with respect to the baggage weighing machines and passenger profiling devices to obtain the minimum average check-in time (ACT) for the process, with each configuration undergoing 133 completions of simulation runs. The result of the experimentation revealed that the 3 × 3 × 4 configuration of servers produced the smallest ACT of 18.25 minutes. This translates to a difference of about 58 minutes from the 76.16 minutes ACT of the real system;representing about 76% improvement in the check-in time of passengers. This study contributed to knowledge by revealing that the main choke points in the MMIA check-in system occur at the baggage weighing and passenger profiling areas as against the check-in counter sub-section as advanced by previous works. Furthermore, the research added value to knowledge by creating a balance between customer satisfaction and cost of operations thereby accommodating the interests of the passenger and the operator who are the two main stakeholders in the commercial aviation industry.展开更多
The increasing demand for airline services amidst limited resources results in passenger dissatisfaction and dwindling revenue for airports and airlines. The dynamics of service demand and resource supply results in c...The increasing demand for airline services amidst limited resources results in passenger dissatisfaction and dwindling revenue for airports and airlines. The dynamics of service demand and resource supply results in check-in issues for the stakeholders in the commercial aviation industry. This has the effect of impacting negatively on service performance, cost of operations, customer satisfaction, and overall throughput. Hence, this paper modelled the travelers’ check-in process at the “D Wing” of the Departure Section of Murtala Muhammed International Airport (MMIA), Ikeja, using Arena Software Tool. The work was carried out by determining the parameters of the queues at designated service points in the check-in process. The primary data required to develop the model were acquired by direct observation of passenger flow and oral interview. Thus, the average check-in time was determined. Thereafter, a model of the international check-in system of the MMIA was developed using Arena software in combination with Microsoft Office tools. The data collected were therefore inputted into the model and simulated;the real result was compared with the simulation result of 133 completions and there was no significant difference. The result showed that the model is a representation of the real system under study. Further work will be tailored towards simulation (<em>i.e</em>. the model will be subjected to experimentation in order to have different scenario).展开更多
To improve the forecasting reliability of travel time, the time-varying confidence interval of travel time on arterials is forecasted using an autoregressive integrated moving average and generalized autoregressive co...To improve the forecasting reliability of travel time, the time-varying confidence interval of travel time on arterials is forecasted using an autoregressive integrated moving average and generalized autoregressive conditional heteroskedasticity （ARIMA-GARCH） model. In which, the ARIMA model is used as the mean equation of the GARCH model to model the travel time levels and the GARCH model is used to model the conditional variances of travel time. The proposed method is validated and evaluated using actual traffic flow data collected from the traffic monitoring system of Kunshan city. The evaluation results show that, compared with the conventional ARIMA model, the proposed model cannot significantly improve the forecasting performance of travel time levels but has advantage in travel time volatility forecasting. The proposed model can well capture the travel time heteroskedasticity and forecast the time-varying confidence intervals of travel time which can better reflect the volatility of observed travel times than the fixed confidence interval provided by the ARIMA model.展开更多
基金Supported by the Key Scientific Research Project of Universities in Henan Province,No.21A330004Natural Science Foundation in Henan Province,No.222300420265.
文摘BACKGROUND Hepatitis B(HB)and hepatitis C(HC)place the largest burden in China,and a goal of eliminating them as a major public health threat by 2030 has been set.Making more informed and accurate forecasts of their spread is essential for developing effective strategies,heightening the requirement for early warning to deal with such a major public health threat.AIM To monitor HB and HC epidemics by the design of a paradigmatic seasonal autoregressive fractionally integrated moving average(SARFIMA)for projections into 2030,and to compare the effectiveness with the seasonal autoregressive integrated moving average(SARIMA).METHODS Monthly HB and HC incidence cases in China were obtained from January 2004 to June 2023.Descriptive analysis and the Hodrick-Prescott method were employed to identify trends and seasonality.Two periods(from January 2004 to June 2022 and from January 2004 to December 2015,respectively)were used as the training sets to develop both models,while the remaining periods served as the test sets to evaluate the forecasting accuracy.RESULTS There were incidents of 23400874 HB cases and 3590867 HC cases from January 2004 to June 2023.Overall,HB remained steady[average annual percentage change(AAPC)=0.44,95%confidence interval(95%CI):-0.94-1.84]while HC was increasing(AAPC=8.91,95%CI:6.98-10.88),and both had a peak in March and a trough in February.In the 12-step-ahead HB forecast,the mean absolute deviation(15211.94),root mean square error(18762.94),mean absolute percentage error(0.17),mean error rate(0.15),and root mean square percentage error(0.25)under the best SARFIMA(3,0,0)(0,0.449,2)12 were smaller than those under the best SARIMA(3,0,0)(0,1,2)12(16867.71,20775.12,0.19,0.17,and 0.27,respectively).Similar results were also observed for the 90-step-ahead HB,12-step-ahead HC,and 90-step-ahead HC forecasts.The predicted HB incidents totaled 9865400(95%CI:7508093-12222709)cases and HC totaled 1659485(95%CI:856681-2462290)cases during 2023-2030.CONCLUSION Under current interventions,China faces enormous challenges to eliminate HB and HC epidemics by 2030,and effective strategies must be reinforced.The integration of SARFIMA into public health for the management of HB and HC epidemics can potentially result in more informed and efficient interventions,surpassing the capabilities of SARIMA.
基金the National Natural Science Foundation of China(Nos.61374070 and 61374154)the Fundamental Research Funds for the Central Universities of China(Nos.DUT14QY14 and DUT14QY31)
文摘In this paper, the problems of stability for a class of switched positive descriptor systems(SPDSs)with average dwell time(ADT) switching are investigated. First, based on the equivalent switched system and the properties of the projector matrix, sufficient stabilities are given for the underlying systems in both continuoustime and discrete-time contexts. Then, a sufficient stability condition for the SPDS with both stable and unstable subsystems is obtained. The stability results for the SPDSs are represented in terms of a set of linear programmings(LPs) by the multiple linear co-positive Lyapunov function(MLCLF) approach. Finally, three numerical examples are given to illustrate the effectiveness of the obtained theoretical results.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 61203304,61203055,and 11226150)the Fundamental Research Funds for the Central Universities,China (Grant Nos. 2011QNA26,2010LKSX04,and 2010LKSX09)
文摘In this paper,we consider the average-consensus problem with communication time delays and noisy links.We analyze two different cases of coupling topologies：fixed and switching topologies.By utilizing the stability theory of the stochastic differential equations,we analytically show that the average consensus could be achieved almost surely with the perturbation of noise and the communication time delays even if the time delay is time-varying.The theoretical results show that multi-agent systems can tolerate relatively large time delays if the noise is weak,and they can tolerate relatively strong noise if the time delays are low.The simulation results show that systems with strong noise intensities yield slow convergence.
基金Supported by National Natural Science Foundation of China （61074032, 61473182, 61104089）, National High Technology Research and Development Program of China （863 Program） （2011AA040103-7）, Project of Science and Technology Commission of Shanghai Municipality （10JC1405000, 11ZR1413100,14JC1402200）, and Shanghai Rising-Star Program （13QA1401600）
基金supported by the National Natural Science Foundation of China(6127312661363002+3 种基金61374104)the Natural Science Foundation of Guangdong Province(10251064101000008S2012010009675)the Fundamental Research Funds for the Central Universities(2012ZM0059)
文摘This paper studies the weighted average consensus problem for networks of agents with fixed directed asymmetric unbalance information exchange topology. We suppose that the classical distributed consensus protocol is destroyed by diverse time-delays which include communication time-delay and self time-delay. Based on the generalized Nyquist stability criterion and the Gerschgorin disk theorem, some sufficient conditions for the consensus of multi-agent systems are obtained. And we give the expression of the weighted average consensus value for our consensus protocol. Finally, numerical examples are presented to illustrate the theoretical results.
文摘This paper investigates the correlation between stochastic resonance （SR） and the average phase-synchronization time which is between the input signal and the output signal in a bistable system driven by colour-correlated noises. The results show that the output signal-to-noise ratio can reach a maximum with the increase of the average phase- synchronization time, which may be helpful for understanding the principle of SR from the point of synchronization; however, SR and the maximum of the average phase-synchronization time appear at different optimal noise level, moreover, the effects on them of additive and multiplicative noise are different.
基金Supported by National Natural Science Foundation of China （61079001, 61273006）, National High Technology Research and Development Program of China （863 Program） （2011AAl10301）, Specialized Research Fund for the Doctoral Program of Higher Education of China （20111103110017）, Hebei Province Science and Technology Research and Development Planning Project （10203548D）, Hebei Province Science and Technology Planning Project （13210807） Hebei Province Science and Technology Conditions Building Program （11963546D）
基金National Natural Science Foundation of China(No.61074032)National High Technology Research and Development Program of China(No.2011AA040103-7)+3 种基金National Science Foundation of China(No.61104089)Science and Technology Commission of Shanghai Municipality,China(No.11JC1404000)Shanghai Rising-Star Program,China(No.13QA1401600)Shandong Province Special Topic of Information Strategy,China(No.2013EI214)
文摘The average consensus problem in a directed network of multi-agent systems with communication time delays was investigated. The directed networks were balanced and weakly connected with fixed or switching topology digraph. Based on frequency domain analysis method, a sufficient condition of asymptotic stability of multi-agent systems with time delays was obtained,where the analytic formula between the maximum time delay and the directed network structure was provided. The maximum time delay can be derived directly and easily by the eigenvalue of Laplacian L. Numerical examples confirm the effectiveness of the proposed technique.
文摘This paper presents a new method of detecting multi-periodicities in a seasonal time series. Conventional methods such as the average power spectrum or the autocorrelation function plot have been used in detecting multiple periodicities. However, there are numerous cases where those methods either fail, or lead to incorrectly detected periods. This, in turn in applications, produces improper models and results in larger forecasting errors. There is a strong need for a new approach to detecting multi-periodicities. This paper tends to fill this gap by proposing a new method which relies on a mathematical instrument, called the Average Power Function of Noise (APFN) of a time series. APFN has a prominent property that it has a strict local minimum at each period of the time series. This characteristic helps one in detecting periods in time series. Unlike the power spectrum method where it is assumed that the time series is composed of sinusoidal functions of different frequencies, in APFN it is assumed that the time series is periodic, the unique and a much weaker assumption. Therefore, this new instrument is expected to be more powerful in multi-periodicity detection than both the autocorrelation function plot and the average power spectrum. Properties of APFN and applications of the new method in periodicity detection and in forecasting are presented.
文摘The average consensus in undirected networks of multi-agent with both fixed and switching topology coupling multiple time-varying delays is studied. By using orthogonal transformation techniques, the original system can be turned into a reduced dimensional system and then LMI-based method can be applied conveniently. Convergence analysis is conducted by constructing Lyapunov-Krasovskii function. Sufficient conditions on average consensus problem with multiple time-varying delays in undirected networks are obtained via linear matrix inequality (LMI) techniques. In particular, the maximal admissible upper bound of time-varying delays can be easily obtained by solving several simple and feasible LMIs. Finally, simulation examples are given to demonstrate the effectiveness of the theoretical results.
基金supported by National Natural Science Foundation of China(Grant Nos.5112502251005173)+1 种基金PhD Programs Foundation of Ministry of Education of China(Grant No.20110201110025)the Fundamental Research Funds for the Central Universities of China
文摘Time domain averaging(TDA) is essentially a comb filter,it cannot extract the specified harmonics which may be caused by some faults,such as gear eccentric.Meanwhile,TDA always suffers from period cutting error(PCE) to different extent.Several improved TDA methods have been proposed,however they cannot completely eliminate the waveform reconstruction error caused by PCE.In order to overcome the shortcomings of conventional methods,a flexible time domain averaging(FTDA) technique is established,which adapts to the analyzed signal through adjusting each harmonic of the comb filter.In this technique,the explicit form of FTDA is first constructed by frequency domain sampling.Subsequently,chirp Z-transform(CZT) is employed in the algorithm of FTDA,which can improve the calculating efficiency significantly.Since the signal is reconstructed in the continuous time domain,there is no PCE in the FTDA.To validate the effectiveness of FTDA in the signal de-noising,interpolation and harmonic reconstruction,a simulated multi-components periodic signal that corrupted by noise is processed by FTDA.The simulation results show that the FTDA is capable of recovering the periodic components from the background noise effectively.Moreover,it can improve the signal-to-noise ratio by 7.9 dB compared with conventional ones.Experiments are also carried out on gearbox test rigs with chipped tooth and eccentricity gear,respectively.It is shown that the FTDA can identify the direction and severity of the eccentricity gear,and further enhances the amplitudes of impulses by 35%.The proposed technique not only solves the problem of PCE,but also provides a useful tool for the fault symptom extraction of rotating machinery.
文摘The primary objective of the paper is to forecast the beta values of companies listed on Sensex,Bombay Stock Exchange(BSE).The BSE Sensex constitutes 30 top most companies listed which are popularly known as blue-chip companies.To reach out the predefined objectives of the research,Auto Regressive Integrated Moving Average method is used to forecast the future risk and returns for 10 years of historical data from April 2007 to March 2017.Validation accomplished by comparison of forecasted and actual beta values for the hold back period of 2 years.Root-Mean-Square-Error and Mean-Absolute-Error both are used for accuracy measurement.The results revealed that out of 30 listed companies in the BSE Sensex,10 companies’exhibits high beta values,12 companies are with moderate and 8 companies are with low beta values.Further,it is to note that Housing Development Finance Corporation(HDFC)exhibits more inconsistency in terms of beta values though the average beta value is lowest among the companies under the study.A mixed trend is found in forecasted beta values of the BSE Sensex.In this analysis,all the p-values are less than the F-stat values except the case of Tata Steel and Wipro.Therefore,the null hypotheses were rejected leaving Tata Steel and Wipro.The values of actual and forecasted values are showing the almost same results with low error percentage.Therefore,it is concluded from the study that the estimation ARIMA could be acceptable,and forecasted beta values are accurate.So far,there are many studies on ARIMA model to forecast the returns of the stocks based on their historical data.But,hardly there are very few studies which attempt to forecast the returns on the basis of their beta values.Certainly,the attempt so made is a novel approach which has linked risk directly with return.On the basis of the present study,authors try to through light on investment decisions by linking it with beta values of respective stocks.Further,the outcomes of the present study undoubtedly useful to academicians,researchers,and policy makers in their respective area of studies.
基金Supported by National Postdoctoral Program for Innovative Talent of China (Grant No.BX20180031)。
文摘Periodic components are of great significance for fault diagnosis and health monitoring of rotating machinery.Time synchronous averaging is an effective and convenient technique for extracting those components.However,the performance of time synchronous averaging is seriously limited when the separate segments are poorly synchronized.This paper proposes a new averaging method capable of extracting periodic components without external reference and an accurate period to solve this problem.With this approach,phase detection and compensation eliminate all segments'phase differences,which enables the segments to be well synchronized.The effectiveness of the proposed method is validated by numerical and experimental signals.
文摘In compartment fires (houses, buildings, underground, warehouse, etc.), smokes are a major dan- ger during firemen intervention. Most of the time, they are at high temperature (>800?C) and they flow everywhere through many kinds of ducts, which leads to the propagation of the combustion by the creation other fires in places which may be far away from the initial fire. In this paper, we present a new approach of the problem, which allows to better follow the fire behavior and especially to detect the dangers that may appear and endanger firefighters. This approach consists in a mathematical analysis based on the comparison of moving averages centered in the past, calculated on the temperature recordings of the smokes. As a consequence, this method may allow to improve decision support in real time and therefore to improve the security and the efficiency of firefighters in their operations against that kind of fires.
文摘We calculate the average speed of a projectile in the absence of air resistance, a quantity that is missing from the treatment of the problem in the literature. We then show that this quantity is equal to the time-average instantaneous speed of the projectile, but different from its space-average instantaneous speed. It is then shown that this behavior is shared by general motion of all particles regardless of the dimensionality of motion and the nature of the forces involved. The equality of average speed and time-average instantaneous speed can be useful in situations where the calculation of one is more difficult than the other. Thus, making it more efficient to calculate one by calculating the other.
基金Jiangxi Provincial Hospital Pharmacy Special Research Fund Project(Grant No.2024-ZXYJ02).
文摘In the context of the Diagnosis Related Groups(DRGs)system,the orthopedic hospital implemented refined drug control to provide a pharmacological reference for promoting rational clinical drug use.A statistical analysis was conducted on the hospital’s data from January to December 2021(prior to the implementation of control),focusing on the types of unreasonable prescriptions.A multi-dimensional analysis was also conducted to identify the underlying causes of inappropriate medication practices.Following this,refined drug control measures were introduced,and data from January to December 2022(post-control)were compared,examining factors such as the average drug cost,drug expenses for the IC29 diagnosis group,and the drug cost ratio.An interrupted time-series analysis was employed to evaluate the effects of these interventions.The results showed that after the implementation of refined drug control in the orthopedic department,significant reductions were observed in the average cost per patient,average drug cost per patient,drug cost ratio,cost consumption index,average length of hospital stay,and allocation ratio(P<0.05).In particular,the first month of control(January 2022)saw a marked decrease in average drug costs per patient by 1272.90 yuan(P<0.01),a reduction in the drug cost ratio by 0.98%,and a decline in drug costs for the IC29 diagnosis group by 616.79 yuan(P>0.05).Moreover,the rate of unreasonable inappropriate prescribing dropped dramatically from 40.48%in 2021 to 3.57%by December 2022.The refined control of drug use within the orthopedic hospital significantly improved the rationality of clinical prescribing practices,reduced the occurrence of adverse drug reactions,and enhanced patient adherence to prescribed treatments.These findings demonstrated considerable clinical value in promoting efficient and safe drug use.
文摘Air pollution,specifically fine particulate matter(PM2.5),represents a critical environmental and public health concern due to its adverse effects on respiratory and cardiovascular systems.Accurate forecasting of PM2.5 concentrations is essential for mitigating health risks;however,the inherent nonlinearity and dynamic variability of air quality data present significant challenges.This study conducts a systematic evaluation of deep learning algorithms including Convolutional Neural Network(CNN),Long Short-Term Memory(LSTM),and the hybrid CNN-LSTM as well as statistical models,AutoRegressive Integrated Moving Average(ARIMA)and Maximum Likelihood Estimation(MLE)for hourly PM2.5 forecasting.Model performance is quantified using Root Mean Squared Error(RMSE),Mean Absolute Error(MAE),Mean Absolute Percentage Error(MAPE),and the Coefficient of Determination(R^(2))metrics.The comparative analysis identifies optimal predictive approaches for air quality modeling,emphasizing computational efficiency and accuracy.Additionally,CNN classification performance is evaluated using a confusion matrix,accuracy,precision,and F1-score.The results demonstrate that the Hybrid CNN-LSTM model outperforms standalone models,exhibiting lower error rates and higher R^(2) values,thereby highlighting the efficacy of deep learning-based hybrid architectures in achieving robust and precise PM2.5 forecasting.This study underscores the potential of advanced computational techniques in enhancing air quality prediction systems for environmental and public health applications.
文摘With the current situation of insecurity in Nigeria and the worsening condition of Nigerian roads, there is increasing demand for air travel. This increasing demand for airline services amidst limited resources results in passenger dissatisfaction and reduction of revenue for airports and airlines. The dynamics of service demand and resource supply result in check-in issues for all the stakeholders in the commercial aviation industry. Hence, this research simulated the developed model for travelers’ check-in process at the “D Wing” of the Departure Section of Murtala Muhammed International Airport (MMIA), Ikeja, using Arena Software Tool. The simulation of the developed model was carried out by varying five different configurations of the servers with respect to the baggage weighing machines and passenger profiling devices to obtain the minimum average check-in time (ACT) for the process, with each configuration undergoing 133 completions of simulation runs. The result of the experimentation revealed that the 3 × 3 × 4 configuration of servers produced the smallest ACT of 18.25 minutes. This translates to a difference of about 58 minutes from the 76.16 minutes ACT of the real system;representing about 76% improvement in the check-in time of passengers. This study contributed to knowledge by revealing that the main choke points in the MMIA check-in system occur at the baggage weighing and passenger profiling areas as against the check-in counter sub-section as advanced by previous works. Furthermore, the research added value to knowledge by creating a balance between customer satisfaction and cost of operations thereby accommodating the interests of the passenger and the operator who are the two main stakeholders in the commercial aviation industry.
文摘The increasing demand for airline services amidst limited resources results in passenger dissatisfaction and dwindling revenue for airports and airlines. The dynamics of service demand and resource supply results in check-in issues for the stakeholders in the commercial aviation industry. This has the effect of impacting negatively on service performance, cost of operations, customer satisfaction, and overall throughput. Hence, this paper modelled the travelers’ check-in process at the “D Wing” of the Departure Section of Murtala Muhammed International Airport (MMIA), Ikeja, using Arena Software Tool. The work was carried out by determining the parameters of the queues at designated service points in the check-in process. The primary data required to develop the model were acquired by direct observation of passenger flow and oral interview. Thus, the average check-in time was determined. Thereafter, a model of the international check-in system of the MMIA was developed using Arena software in combination with Microsoft Office tools. The data collected were therefore inputted into the model and simulated;the real result was compared with the simulation result of 133 completions and there was no significant difference. The result showed that the model is a representation of the real system under study. Further work will be tailored towards simulation (<em>i.e</em>. the model will be subjected to experimentation in order to have different scenario).
基金The National Natural Science Foundation of China(No.51108079)
文摘To improve the forecasting reliability of travel time, the time-varying confidence interval of travel time on arterials is forecasted using an autoregressive integrated moving average and generalized autoregressive conditional heteroskedasticity （ARIMA-GARCH） model. In which, the ARIMA model is used as the mean equation of the GARCH model to model the travel time levels and the GARCH model is used to model the conditional variances of travel time. The proposed method is validated and evaluated using actual traffic flow data collected from the traffic monitoring system of Kunshan city. The evaluation results show that, compared with the conventional ARIMA model, the proposed model cannot significantly improve the forecasting performance of travel time levels but has advantage in travel time volatility forecasting. The proposed model can well capture the travel time heteroskedasticity and forecast the time-varying confidence intervals of travel time which can better reflect the volatility of observed travel times than the fixed confidence interval provided by the ARIMA model.
