A New Multidimensional Time Series Forecasting Method Based on the EOF Iteration Scheme

In this paper a new .mnultidimensional time series forecasting scheme based on the empirical orthogonal function (EOF) stepwise iteration process is introduced. The scheme is tested in a series of forecast experiments of Nino3 SST anomalies and Tahiti-Darwin SO index. The results show that the scheme is feasible and ENSO predictable.

Time-Based Dynamic Trust Model Using Ant Colony Algorithm

The trust in distributed environment is uncertain, which is variation for various factors. This paper introduces TDTM, a model for time-based dynamic trust. Every entity in the distribute environment is endowed with a trust-vector, which figures the trust intensity between this entity and the others. The trust intensity is dynamic due to the time and the inter-operation between two entities, a method is proposed to quantify this change based on the mind of ant colony algorithm and then an algorithm for the transfer of trust relation is also proposed. Furthermore, this paper analyses the influence to the trust intensity among all entities that is aroused by the change of trust intensity between the two entities, and presents an algorithm to resolve the problem. Finally, we show the process of the trusts＇ change that is aroused by the time＇s lapse and the inter-operation through an instance.

TSLV:Time-Slice-Based Location Verification for VANET

Position-spoofing-based attacks seriously threaten the security of Vehicular Ad Hoc Network(VANET).An effective solution to detect position spoofing is location verification.However,since vehicles move fast and the topology changes quickly in VANET,the static location verification method in Wireless Sensor Network(WSN) is not suitable for VANET.Taking into account the dynamic changing topology of VANET and collusion,we propose a Time-Slice-based Location Verification scheme,named TSLV,to resist position spoofing in VANET.Specifically,TSLV transforms the dynamic topology into static topology by time slice and each time slice corresponds to a verification process.The verifier can implement location verification for the corresponding prover.During the verification process,the verifier first filters out vehicles which provide unreasonably claimed locations,and then uses the Mean Square Error(MSE)-based cluster approach to separate the consistent vehicles by time slice,and uses the consistent set for its verification.In addition,security analysis and simulation show that TSLV can defend against the collusion attack effectively.

Quorum systems for intrusion-tolerance based on trusted timely computing base

Quorum systems have been used to solve the problem of data consistency in distributed fault-tolerance systems. But when intrusions occur, traditional quorum systems have some disadvantages. For example, synchronous quorum systems are subject to DOS attacks, while asynchronous quorum systems need a larger system size （at least 3f＋1 for generic data, and f fewer for self-verifying data）. In order to solve the problems above, an intrusion-tolerance quorum system （ITQS） of hybrid time model based on trust timely computing base is presented （TTCB）. The TTCB is a trust secure real-time component inside the server with a well defined interface and separated from the operation system. It is in the synchronous communication environment while the application layer in the server deals with read-write requests and executes update-copy protocols asynchronously. The architectural hybridization of synchrony and asynchrony can achieve the data consistency and availability correctly. We also build two kinds of ITQSes based on TTCB, i.e., the symmetrical and the asymmetrical TTCB quorum systems. In the performance evaluations, we show that TTCB quorum systems are of smaller size, lower load and higher availability.

Uncertainty quantification for stochastic dynamical systems using time-dependent stochastic bases

A novel method based on time-dependent stochastic orthogonal bases for stochastic response surface approximation is proposed to overcome the problem of significant errors in the utilization of the generalized polynomial chaos(GPC) method that approximates the stochastic response by orthogonal polynomials. The accuracy and effectiveness of the method are illustrated by different numerical examples including both linear and nonlinear problems. The results indicate that the proposed method modifies the stochastic bases adaptively, and has a better approximation for the probability density function in contrast to the GPC method.

Timed Petri Net Models of Shared-Memory Bus-Based Multiprocessors

In shared-memory bus-based multiprocessors, when the number of processors grows, the processors spend an increasing amount of time waiting for access to the bus (and shared memory). This contention reduces the performance of processors and imposes a limitation of the number of processors that can be used efficiently in bus-based systems. Since the multi-processor’s performance depends upon many parameters which affect the performance in different ways, timed Petri nets are used to model shared-memory bus-based multiprocessors at the instruction execution level, and the developed models are used to study how the performance of processors changes with the number of processors in the system. The results illustrate very well the restriction on the number of processors imposed by the shared bus. All performance characteristics presented in this paper are obtained by discrete-event simulation of Petri net models.

Splitting Based Scheme for Three-dimensional MHD with Dual Time Stepping

A new hybrid numerical scheme of combining an E-CUSP(Energy-Convective Upwind and Split Pressure) method for the fluid part and the Constrained Transport(CT) for the magnetic induction part is proposed.In order to avoid the occurrence of negative pressure in the reconstructed profiles and its updated value,a positivity preserving method is provided.Furthermore,the MHD equations are solved at each physical time step by advancing in pseudo time.The use of dual time stepping is beneficial in the computation since the use of dual time stepping allows the physical time step not to be limited by the corresponding values in the smallest cell and to be selected based on the numerical accuracy criterion.This newly established hybrid scheme combined with positivity preserving method and dual time technique has demonstrated the accurateness and robustness through numerical experiments of benchmark problems such as the 2D Orszag-Tang vortex problem and the3 D shock-cloud interaction problem.

Analytical Modeling of Base Transit Time of SiGe HBTS Including Concentration Dependent Bandgap Narrowing Effect

Heterojunction Bipolar Transistors with SiGe base and Si emitter and collector have increasingly become important in high speed applications in electronics due to better performance of these devices with a modest increase in complexity of fabrication process. Speed of these devices is mainly determined by transit time of minority carriers across the device. Base transit time is the most important component of the total transit time. An analytical model is developed here to predict the variation of base transit time with Ge content, base doping concentration, temperature, and other device parameters. Studies have been made for both uniform and exponential doping distributions with different Ge profiles in the base region. Band gap narrowing effect due to high doping concentration is also taken into account in the model.

Experimental validation of a signal-based approach for structural earthquake damage detection using fractal dimension of time frequency feature

This article extends a signal-based approach formerly proposed by the authors, which utilizes the fractal dimension of time frequency feature （FDTFF） of displacements, for earthquake damage detection of moment resist frame （MRF）, and validates the approach with shaking table tests. The time frequency feature （TFF） of the relative displacement at measured story is defined as the real part of the coefficients of the analytical wavelet transform. The fractal dimension （FD） is to quantify the TFF within the fundamental frequency band using box counting method. It is verified that the FDTFFs at all stories of the linear MRF are identical with the help of static condensation method and modal superposition principle, while the FDTFFs at the stories with localized nonlinearities due to damage will be different from those at the stories without nonlinearities using the reverse-path methodology. By comparing the FDTFFs of displacements at measured stories in a structure, the damage-induced nonlinearity of the structure under strong ground motion can be detected and localized. Finally shaking table experiments on a 1：8 scale sixteen-story three-bay steel MRF with added frictional dampers, which generate local nonlinearities, are conducted to validate the approach.

Characteristic-Based Time Domain Method for Cylindrically Conformal Microstrip Patch Antennas

The characteristics of a cylindrical conformal microstrip patch antenna are analyzed by using the characteristic-based time domain （CBTD） method. A governing equation in the cylindrical coordinate system is formulated directly to facilitate the analysis of cylindrically conformal microstrip patch antennas. The algorithm has second-order accuracy both in time and space domain and has the potential to eliminate the spurious wave reflection from the numerical boundaries of the computational domain, Numerical results demonstrate the important merits and accuracy of the proposed technique in computational electromagnetics,

Web-based GIS System for Real-time Field Data Collection Using Personal Mobile Phone

Recently, use of mobile communicational devices in field data collection is increasing such as smart phones and cellular phones due to emergence of embedded Global Position System GPS and Wi-Fi Internet access. Accurate timely and handy field data collection is required for disaster management and emergency quick responses. In this article, we introduce web-based GIS system to collect the field data by personal mobile phone through Post Office Protocol POP3 mail server. The main objective of this work is to demonstrate real-time field data collection method to the students using their mobile phone to collect field data by timely and handy manners, either individual or group survey in local or global scale research.

Contention-Based Beaconless Real-Time Routing Protocol for Wireless Sensor Networks

This paper presents a novel real-time routing protocol, called CBRR, with less energy consumption for wireless sensor networks (WSNs). End-to-End real-time requirements are fulfilled with speed or delay constraint at each hop through integrating the contention and neighbor table mechanisms. More precisely, CBRR maintains a neighbor table via the contention mechanism being dependent on wireless broadcast instead of beacons. Comprehensive simulations show that CBRR can not only achieve higher performance in static networks, but also work well for dynamic networks.

Clustering-Inverse: A Generalized Model for Pattern-Based Time Series Segmentation

Patterned-based time series segmentation (PTSS) is an important task for many time series data mining applications. In this paper, according to the characteristics of PTSS, a generalized model is proposed for PTSS. First, a new inter-pretation for PTSS is given by comparing this problem with the prototype-based clustering (PC). Then, a novel model, called clustering-inverse model (CI-model), is presented. Finally, two algorithms are presented to implement this model. Our experimental results on artificial and real-world time series demonstrate that the proposed algorithms are quite effective.

Market-based control strategy for long-span structures considering the multi-time delay issue

To solve the different time delays that exist in the control device installed on spatial structures, in this study, discrete analysis using a 2N precise algorithm was selected to solve the multi-time-delay issue for long-span structures based on the market-based control （MBC） method. The concept of interval mixed energy was introduced from computational structural mechanics and optimal control research areas, and it translates the design of the MBC multi-time-delay controller into a solution for the segment matrix. This approach transforms the serial algorithm in time to parallel computing in space, greatly improving the solving efficiency and numerical stability. The designed controller is able to consider the issue of time delay with a linear controlling force combination and is especially effective for large time-delay conditions. A numerical example of a long-span structure was selected to demonstrate the effectiveness of the presented controller, and the time delay was found to have a significant impact on the results.

Time-Expanded Sampling for Ensemble-Based Filters:Assimilation Experiments with Real Radar Observations

By sampling perturbed state vectors from each ensemble prediction run at properly selected time levels in the vicinity of the analysis time, the recently proposed time-expanded sampling approach can enlarge the ensemble size without increasing the number of prediction runs and, hence, can reduce the computational cost of an ensemble-based filter. In this study, this approach is tested for the first time with real radar data from a tornadic thunderstorm. In particular, four assimilation experiments were performed to test the time-expanded sampling method against the conventional ensemble sampling method used by ensemble- based filters. In these experiments, the ensemble square-root filter （EnSRF） was used with 45 ensemble members generated by the time-expanded sampling and conventional sampling from 15 and 45 prediction runs, respectively, and quality-controlled radar data were compressed into super-observations with properly reduced spatial resolutions to improve the EnSRF performances. The results show that the time-expanded sampling approach not only can reduce the computational cost but also can improve the accuracy of the analysis, especially when the ensemble size is severely limited due to computational constraints for real-radar data assimilation. These potential merits are consistent with those previously demonstrated by assimilation experiments with simulated data.

A Model-free Approach to Fault Detection of Continuous-time Systems Based on Time Domain Data

In this paper, a model-free approach is presented to design an observer-based fault detection system of linear continuoustime systems based on input and output data in the time domain. The core of the approach is to directly identify parameters of the observer-based residual generator based on a numerically reliable data equation obtained by filtering and sampling the input and output signals.

“Deep-time Digital Basin” Based on Big Data and Artificial Intelligence

1 Introduction Information technology has been playing an ever-increasing role in geoscience.Sphisicated database platforms are essential for geological data storage,analysis and exchange of Big Data(Feblowitz,2013;Zhang et al.,2016;Teng et al.,2016;Tian and Li,2018).The United States has built an information-sharing platform for state-owned scientific data as a national strategy.

Monitoring models for base flow effect and daily variation of dam seepage elements considering time lag effect

Affected by external environmental factors and evolution of dam performance, dam seepage behavior shows nonlinear time-varying characteristics. In this study, to predict and evaluate the long-term development trend and short-term fluctuation of the dam seepage behavior, two monitoring models were developed, one for the base flow effect and one for daily variation of dam seepage elements. In the first model, to avoid the influence of the time lag effect on the evaluation of seepage variation with the time effect component of seepage elements, the base values of the seepage element and the reservoir water level were extracted using the wavelet multi-resolution analysis method, and the time effect component was separated by the established base flow effect monitoring model. For the development of the daily variation monitoring model for dam seepage elements, all the previous factors, of which the measured time series prior to the dam seepage element monitoring time may have certain influence on the monitored results, were considered. Those factors that were positively correlated with the analyzed seepage element were initially considered to be the support vector machine(SVM) model input factors, and then the SVM kernel function-based sensitivity analysis was performed to optimize the input factor set and establish the optimized daily variation SVM model. The efficiency and rationality of the two models were verified by case studies of the water level of two piezometric tubes buried under the slope of a concrete gravity dam.Sensitivity analysis of the optimized SVM model shows that the influences of the daily variation of the upstream reservoir water level and rainfall on the daily variation of piezometric tube water level are processes subject to normal distribution.

Observer-based adaptive control of uncertain time-delay switched systems with stuck actuator faults

This paper concerns the observer-based adaptive control problem of uncertain time-delay switched systems with stuck actuator faults. Under the case where the original controller cannot stabilize the faulty system, multiple adaptive controllers are designed and a suitable switching logic is incorporated to ensure the closed-loop system stability and state tracking. New delay-independent sufficient conditions for asymptotic stability are obtained in terms of linear matrix inequalities based on piecewise Lyapunov stability theory. On the other hand, adaptive laws for on-line updating of some of the controller parameters are also designed to compensate the effect of stuck failures. Finally, simulation results for reference [1] model show that the design is feasible and efficient.

核酸序列依赖性扩增、Real-time PCR及GM试验诊断侵袭性曲霉菌感染的临床应用评价

目的核酸序列依赖性扩增（nucleic acid sequence-based amplification,NASBA）、Real-time PCR及GM试验在侵袭性曲霉菌感染中的诊断价值。方法收集2013年11月~2014年6月临床上曲霉菌感染高危病患的血液标本80例,并根据EORTC/MSG诊断标准分为确诊组8例,拟诊组26例,非感染组46例,分别利用NASBA、real-time PCR及GM试验进行检测,计算3种方法的诊断指标并分析评价。结果 NASBA、real-time PCR及GM试验3种方法的灵敏度分别为76.47%、67.65%、52.94%,特异度分别为80.43%、89.13%、80.43%。联合诊断结果显示,NASBA与real-time PCR串联方案有最好的特异度（100%）及阳性预测值（100%）;NASBA与real-time PCR并联方案则最为灵敏（94.12%）。结论 NASBA用于诊断IA最为敏感,而real-time PCR则最为特异,GM试验的表现差于前两者。联合应用的诊断策略,在特定情况下提高临床早期诊断IA的准确性。