Real-time embedded software testing method based on extended finite state machine

The reliability of real-time embedded software directly determines the reliability of the whole real-time embedded sys- tem, and the effective software testing is an important way to ensure software quality and reliability. Based on the analysis of the characteristics of real-time embedded software, the formal method is introduced into the real-time embedded software testing field and the real-time extended finite state machine （RT-EFSM） model is studied firstly. Then, the time zone division method of real-time embedded system is presented and the definition and description methods of time-constrained transition equivalence class （timeCTEC） are presented. Furthermore, the approaches of the testing sequence and test case generation are put forward. Finally, the proposed method is applied to a typical avionics real- time embedded software testing practice and the examples of the timeCTEC, testing sequences and test cases are given. With the analysis of the testing result, the application verification shows that the proposed method can effectively describe the real-time embedded software state transition characteristics and real-time requirements and play the advantages of the formal methods in accuracy, effectiveness and the automation supporting. Combined with the testing platform, the real-time, closed loop and automated simulation testing for real-time embedded software can be realized effectively.

A Real-time Updated Model Predictive Control Strategy for Batch Processes Based on State Estimation

Nonlinear model predictive control(NMPC) is an appealing control technique for improving the performance of batch processes, but its implementation in industry is not always possible due to its heavy on-line computation. To facilitate the implementation of NMPC in batch processes, we propose a real-time updated model predictive control method based on state estimation. The method includes two strategies: a multiple model building strategy and a real-time model updated strategy. The multiple model building strategy is to produce a series of sim-plified models to reduce the on-line computational complexity of NMPC. The real-time model updated strategy is to update the simplified models to keep the accuracy of the models describing dynamic process behavior. The me-thod is validated with a typical batch reactor. Simulation studies show that the new method is efficient and robust with respect to model mismatch and changes in process parameters.

Specifying Requirements of Real-Time System with Rules and Templates

This paper presents a model specifying requirements of real-time systems. Different from existing researches, this model mainly uses rules and templates to represent hierarchical FSMs (Finite State Machine). In this model, one rule corresponds to one state transition of FSM and one template corresponds to one FSM. Rules and information with respect to a FSM can be written in a template. So templates include not only state diagrams, but also information that can not be described by FSM, such as performance requirements. The specification using this model consists of a collection of templates and it is easy for users to understand and to review. After introduced the related researches and principles of the model, this paper specifies requirements of a real-time system with this model, and discusses characters of this model in the end.

Research on Optimal Configuration of Energy Storage in Wind-Solar Microgrid Considering Real-Time Electricity Price

Capacity allocation and energy management strategies for energy storage are critical to the safety and economical operation of microgrids.In this paper,an improved energymanagement strategy based on real-time electricity price combined with state of charge is proposed to optimize the economic operation of wind and solar microgrids,and the optimal allocation of energy storage capacity is carried out by using this strategy.Firstly,the structure and model of microgrid are analyzed,and the outputmodel of wind power,photovoltaic and energy storage is established.Then,considering the interactive power cost between the microgrid and the main grid and the charge-discharge penalty cost of energy storage,an optimization objective function is established,and an improved energy management strategy is proposed on this basis.Finally,a physicalmodel is built inMATLAB/Simulink for simulation verification,and the energy management strategy is compared and analyzed on sunny and rainy days.The initial configuration cost function of energy storage is added to optimize the allocation of energy storage capacity.The simulation results show that the improved energy management strategy can make the battery charge-discharge response to real-time electricity price and state of charge better than the traditional strategy on sunny or rainy days,reduce the interactive power cost between the microgrid system and the power grid.After analyzing the change of energy storage power with cost,we obtain the best energy storage capacity and energy storage power.

Real-time road traffic state prediction based on ARIMA and Kalman filter

The realization of road traffic prediction not only provides real-time and effective information for travelers, but also helps them select the optimal route to reduce travel time. Road traffic prediction offers traffic guidance for travelers and relieves traffic jams. In this paper, a real-time road traffic state prediction based on autoregressive integrated moving average （ARIMA） and the Kalman filter is proposed. First, an ARIMA model of road traffic data in a time series is built on the basis of historical road traffic data. Second, this ARIMA model is combined with the Kalman filter to construct a road traffic state prediction algorithm, which can acquire the state, measurement, and updating equations of the Kalman filter. Third, the optimal parameters of the algorithm are discussed on the basis of historical road traffic data. Finally, four road segments in Beijing are adopted for case studies. Experimental results show that the real-time road traffic state prediction based on ARIMA and the Kalman filter is feasible and can achieve high accuracy.

Distributed Real-time State Estimation for Combined Heat and Power Systems

This paper proposes a distributed real-time state estimation(RTSE)method for the combined heat and power systems(CHPSs).First,a difference-based model for the heat system is established considering the dynamics of heat systems.This heat system model is further used along with the power system steady-state model for holistic CHPS state estimation.A cubature Kalman filter(CKF)-based RTSE is developed to deal with the system nonlinearity while integrating both the historical and present measurement information.Finally,a multi-timescale asynchronous distributed computation scheme is designed to enhance the scalability of the proposed method for largescale systems.This distributed implementation requires only a small amount of information exchange and thus protects the privacy of different energy systems.Simulations carried out on two CHPSs show that the proposed method can significantly improve the estimation efficiency of CHPS without loss of accuracy compared with other existing models and methods.

Improved Multiple Feature-electrochemical Thermal Coupling Modeling of Lithium-ion Batteries at Low-temperature with Real-time Coefficient Correction

Monitoring various internal parameters plays a core role in ensuring the safety of lithium-ion batteries in power supply applications.It also influences the sustainability effect and online state of charge prediction.An improved multiple feature-electrochemical thermal coupling modeling method is proposed considering low-temperature performance degradation for the complete characteristic expression of multi-dimensional information.This is to obtain the parameter influence mechanism with a multi-variable coupling relationship.An optimized decoupled deviation strategy is constructed for accurate state of charge prediction with real-time correction of time-varying current and temperature effects.The innovative decoupling method is combined with the functional relationships of state of charge and open-circuit voltage to capture energy management ef-fectively.Then,an adaptive equivalent-prediction model is constructed using the state-space equation and iterative feedback correction,making the proposed model adaptive to fractional calculation.The maximum state of charge estimation errors of the proposed method are 4.57% and 0.223% under the Beijing bus dynamic stress test and dynamic stress test conditions,respectively.The improved multiple feature-electrochemical thermal coupling modeling realizes the effective correction of the current and temperature variations with noise influencing coefficient,and provides an efficient state of charge prediction method adaptive to complex conditions.

A Trusted Measurement Scheme Suitable for the Clients in the Trusted Network

The trusted network connection is a hot spot in trusted computing field and the trust measurement and access control technology are used to deal with network security threats in trusted network.But the trusted network connection lacks fine-grained states and real-time measurement support for the client and the authentication mechanism is difficult to apply in the trusted network connection,it is easy to cause the loss of identity privacy.In order to solve the abovedescribed problems,this paper presents a trust measurement scheme suitable for clients in the trusted network,the scheme integrates the following attributes such as authentication mechanism,state measurement,and real-time state measurement and so on,and based on the authentication mechanism and the initial state measurement,the scheme uses the realtime state measurement as the core method to complete the trust measurement for the client.This scheme presented in this paper supports both static and dynamic measurements.Overall,the characteristics of this scheme such as fine granularity,dynamic,real-time state measurement make it possible to make more fine-grained security policy and therefore it overcomes inadequacies existing in the current trusted network connection.

WiSH:WiFi-Based Real-Time Human Detection

Sensorless sensing using wireless signals has been rapidly conceptualized and developed recently. Among numerous applications of WiFi-based sensing, human presence detection acts as a primary and fundamental function to boost applications in practice. Many complicated approaches have been proposed to achieve high detection accuracy, but they frequently omit various practical constraints such as real-time capability, computation efficiency, sampling rates, deployment efforts, etc. A practical detection system that works in realworld applicati ons is lacki ng. In this paper, we design and implement WiSH, a real-time system for con tactless human detection that is applicable for whole-day usage. WiSH employs lightweight yet effective methods and thus enables detection under practical conditions even on resource-limited devices with low signal sampling rates. We deploy WiSH on commodity desktops and customized tiny no des in different everyday scenarios. The experimental results dem on strate the superior performance of WiSH, which has a detection accuracy of >98% using a sampling rate of 20 Hz with an average detection delay of merely 1.5 s. Thus, we believe WiSH is a promising system for real-world deployment.

Comprehensive assessment of real-time precise products from IGS analysis centers

Real-Time Precise Point Positioning(RT-PPP)has been one of the research hotspots in GNSS(Global Navigation Satellite System)community for decades.Real-time precise products of satellite orbits and clocks are the prerequisite for RT-PPP.Thus,it is of great importance to investigate the current multi-GNSS real-time precise products in State Space Representation(SSR)from diferent analysis centers.In this article,SSR products from 10 analysis centers are comprehensively evaluated by comparing them with the fnal products and performing the kinematic PPP.The results show that analysis centers CNES(Centre National D’Etudes Spatiales)and WHU(GNSS Research Center of Wuhan University)provide the most complete products with the best quality.Concerning the accuracy of real-time products for the GNSSs,the accuracies of orbit and clock products are better than 5 cm and 0.15 ns,respectively,for Global Positioning System(GPS),followed by Galileo navigation satellite system(Galileo),BeiDou-3 Navigation Satellite System(BDS-3),GLObal NAvigation Satellite System(GLONASS),and BeiDou-2 Navigation Satellite System(BDS-2).Meanwhile,the results of the RT-PPP with quad-system show that the positioning accuracies are 1.76,1.12 and 2.68 cm in east,north,and up directions,respectively,and the convergence time to 0.1,0.1,0.2 m for corresponding directions is 15.35 min.

Online Rail Fastener Detection Based on YOLO Network

Traveling by high-speed rail and railway transportation have become an important part of people’s life and social production.Track is the basic equipment of railway transportation,and its performance directly affects the service lifetime of railway lines and vehicles.The anomaly detection of rail fasteners is in a priority,while the traditional manual method is extremely inefficient and dangerous to workers.Therefore,this paper introduces efficient computer vision into the railway detection system not only to locate the normal fasteners,but also to recognize the fasteners states.To be more specific,this paper mainly studies the rail fastener detection based on improved You can Only Look Once version 5(YOLOv5)network,and completes the real-time classification of fastener states.The improved YOLOv5 network proposed contains five sections,which are Input,Backbone,Neck,Head Detector and a read-only Few-shot Example Learning module.The main purpose of this project is to improve the detection precision and shorten the detection time.Ultimately,the rail fastener detection system proposed in this paper is confirmed to be superior to other advanced algorithms.This model achieves on-line fastener detection by completing the“sampling-detection-recognition-warning”cycle of a single sample before the next image is sampled.Specifically,the mean average precision of model reaches 94.6%.And the model proposed reaches the speed of 12 ms per image in the deployment environment of NVIDIA GTX1080Ti GPU.

Switching,explosion,and chaos of multi-wavelength soliton states in ultrafast fiber lasers

Because of the complexity and difficulty of realizing a multi-wavelength soliton state,reports on its internal dynamic characteristics are scarce.In this study,the switching and periodic soliton explosion processes of the multi-wavelength soliton state in a negative dispersion passively mode-locked fiber laser are realized.The generation of the multi-wavelength soliton state undergoes the process of noise,oscillation,and stable mode-locking,and the splitting and annihilation of solitons with different group velocities directly impact the generation and disappearance of three wavelengths.Positive and negative dispersion lead to different group velocities of solitons.The presence and displacement of solitons with different group velocities cause soliton collisions,which lead to soliton explosions.A soliton experiences relative phase oscillation,chaos,and oscillation,as well as convergence and separation before and after an explosion.With an increase in parameters related to pump power,single-soliton oscillation,multi-wavelength solitons,and chaos are found in experiments and simulations,proving the relevance and reliability between simulation and experimental results.This work promotes the dynamical study of multi-soliton collisions in nonlinear science and the development of chaos theory in multi-comb lasers.

On the Quantum Entanglement Reinterpretation Using the Time as Real Instantaneous Signal Field

In relativistic mechanics the time-like vector characterize the motion in spacetime with speed faster than the speed of light in vacuum c in which the line element ds2=c2dt2-dx2-dx2-dz2 is less than zero (where is infinitesimal change in time, and are infinitesimal change in space), thus the time in relativistic mechanics can instantaneously flow [1], however in quantum mechanics although the time is treated as unobservable parameter (without any Hermitian observable operator have engine-value equivalent to time) any two physical quantity described by two non-commuting observable operatorsand fulfill , the knowledge of one immediately produce the knowledge of the other [2], thus in quantum mechanics if two particles interacted in finite temporal epoch and then separated in space the gaining of knowledge by the local measurement of physical quantity runs on one them (for example the measurement of spin direction of one particle using Stern-Gerlach experiment) immediately produce the knowledge of the complementary physical quantity of the other particle (for example the opposite spin direction of the other particle), this simply called quantum entanglement the concept that so much advanced after publication of the Jon Bell’s 1964 celebrated paper [3] in which he illustrated that we can add parameters to quantum mechanics to determine the results of individual measurements, without changing the statistical predictions, and then he conclude “there must be a mechanism whereby the setting of one measuring device can influence the reading of another instrument, however remote. Moreover, the signal involved must propagate instantaneously so that such a theory could not be Lorentz invariant”. The question now what these signals that can propagate instantaneously? The answer in this paper will be the time signals field which is defined for each constituent matter particle M and at each space point P as the measure of the total length of all occupation and leaving epochs of P by M which is representing a sequence function compactly supported only at the space point occupied by it and indexed by the number of occupation epochs of P by M, thus the flow of this time signal field from the far future to near future through the present to the near past to the far past inferable by the flow of matter particles constituting the system(such as sun, moon earth and clocks hands). Thus the present will represent in this paper a local absolute feature of time signals field defined at each space point as the set of all occupation epochs of it by matter particle, however the past and future will represent relativistic non-local features of the time signal field defined at each space point as a set of all leaving epochs between each two sequential occupation epochs, so the future after one occupation epoch is representing a past of the next one. Thus according to current representation of time, the two Mc-Taggard’s A and B series of time [4] will exist together as temporal set and then the time is real, the A-series in current theory is a set of all occupation and leaving epochs of space point by the matter particle that is consisting of the present, past and future epochs, and the B-series is the set of all leaving epochs of space points between each two sequential occupation epochs which are taking position before or after the discrete occupation epochs between them and then before or after each other.

Neuroimaging Strategies Addressing Challenges in Using fMRI for the Children with Cerebral Palsy

Aim: This study sought to develop a process and methodology that could be a useful clinical and research tool for successfully completing functional magnetic resonance imaging (fMRI) scanning in children with Cerebral Palsy. Method: Six children with CP (mean age of 8.83 years;five with spastic hemiplegia, one with spastic quadriplegia) and three children with typical development (mean age of 9.33 years) completed an fMRI scanning protocol that used real-time motion feedback as a means of minimizing head and trunk motion. Anatomical, resting-state, and motor-task scans were sequentially obtained from each subject. Precentral “hand-knob” regions were identified on the anatomical scan and served as seed regions to reveal the functional connectivity of each subject’s brain as associated with hand movement. Results: Real-time motion feedback aided children in successful completion of resting state scans. Functional connectivity and brain activity mapping were obtained based on anatomical landmarks, and laterality indices were developed based on the obtained functional-connectivity map to specify a dominant side of brain activity that was matched to a clinical profile, despite anatomical variations that occur with Cerebral Palsy. Interpretation: Real-time motion feedback and the development of laterality indices can improve the clinical and research utility of fMRI scanning. What this paper adds: 1) Presents a real-time imaging protocol for fMRI to help children complete scanning;2) Presents an fMRI methodology to obtain laterality indices in the presence of abnormal anatomy;3) Provides findings of LI that match clinical diagnosis.

A Regulating Capacity Determination Method for Pumped Storage Hydropower to Restrain PV Generation Fluctuations

The variable speed and constant frequency pumped storage hydropower(PSH)unit can strongly support the complementation and joint power supply of cascaded hydropower and photovoltaic(PV)plants.Its fast response capability has provided a feasible solution for the rapid power and voltage regulation caused by real-time fluctuations of PV systems.However,currently there is a lack of research on precise evaluation on regulation capability and regulating capacity configuration for PSH to restrain the real-time fluctuations.In this paper,a cascaded hydro-PV-PSH complementary joint power system(CHPP)is studied,and a“rule-based”method for regulating capacity determination is proposed.A combined statistical technique is introduced to analyze the initial estimated regulating capacity of PSH.A continuous cyclic revision method is adopted to renew the ideal PV curve by repeatedly using the main operating constraints until an optimal regulating capacity of PSH matching the PV generation scale is achieved.The results of the case study verified the feasibility and effectiveness of PSH for restraining the fast fluctuations of PV systems in real-time,and the configuration between PV and PSH regulating capacity is obtained with real-time application requirements.Finally,analyses including weather conditions,curtailed energy and electricity shortage,the sensitivity analysis,and state transition frequency are presented to demonstrate the robustness of this study.

SOUND SPEED IN SYMMETRIC NUCLEAR MATTER WITH SGII TYPE INTERACTIONS

The equation of state (EOS) for nuclear matter plays an important role in the experiments of heavy ions with medium and high energy. As pointed out by Osnes and Strottman, Su and Kuo, when effective nucleon-nucleon interactions (NN interactions) in nuclear theory are extended to the cases of high density and/or high temperature, EOS