Refinement modeling and verification of secure operating systems for communication in digital twins

In traditional digital twin communication system testing,we can apply test cases as completely as possible in order to ensure the correctness of the system implementation,and even then,there is no guarantee that the digital twin communication system implementation is completely correct.Formal verification is currently recognized as a method to ensure the correctness of software system for communication in digital twins because it uses rigorous mathematical methods to verify the correctness of systems for communication in digital twins and can effectively help system designers determine whether the system is designed and implemented correctly.In this paper,we use the interactive theorem proving tool Isabelle/HOL to construct the formal model of the X86 architecture,and to model the related assembly instructions.The verification result shows that the system states obtained after the operations of relevant assembly instructions is consistent with the expected states,indicating that the system meets the design expectations.

Synoptic Verification of Precipitation Forecast of Three NWP Models from May to August of 2008 in Liaoning Province

In order to evaluate the precipitation forecast performance of mesoscale numerical model in Northeast China,mesoscale model in Liaoning Province and T213 model,and improve the ability to use their forecast products for forecasters,the synoptic verifications of their 12 h accumulated precipitation forecasts of 3 numerical modes from May to August in 2008 were made on the basis of different systems impacting weather in Liaoning Province.The time limitations were 24,36,48 and 60 h.The verified contents included 6 aspects such as intensity and position of precipitation center,intensity,location,scope and moving velocity of precipitation main body.The results showed that the three models had good forecasting capability for precipitation in Liaoning Province,but the cupacity of each model was obviously different.

Dynamic business process modeling and verification for inter-organizational collaboration

To achieve an on-demand and dynamic composition model of inter-organizational business processes, a new approach for business process modeling and verification is introduced by using the pi-calculus theory. A new business process model which is multi-role, multi-dimensional, integrated and dynamic is proposed relying on inter-organizational collaboration. Compatible with the traditional linear sequence model, the new model is an M x N multi-dimensional mesh, and provides horizontal and vertical formal descriptions for the collaboration business process model. Finally, the pi-calculus theory is utilized to verify the deadlocks, livelocks and synchronization of the example models. The result shows that the proposed approach is efficient and applicable in inter-organizational business process modeling.

Dynamic grey model of verification cycle and lifecycle of measuring instrument and its application

Two dynamic grey models DGM (1, 1) for the verification cycle and the lifecycle of measuring instrument based on time sequence and frequency sequence were set up, according to the statistical feature of examination data and weighting method. By a specific case, i.e. vernier caliper, it is proved that the fit precision and forecast precision of the models are much higher, the cycles are obviously different under different working conditions, and the forecast result of the frequency sequence model is better than that of the time sequence model. Combining dynamic grey model and auto-manufacturing case the controlling and information subsystems of verification cycle and the lifecycle based on information integration, multi-sensor controlling and management controlling were given. The models can be used in production process to help enterprise reduce error, cost and flaw.

VERIFICATION OF TROPICAL CYCLONE RAINFALL PREDICTIONS FROM CMA AND JMA GLOBAL MODELS

The number of tropical cyclone (TC) genesis over the South China Sea and the Northwest Pacific Ocean in 2009 is significantly less than the average (27.4). However, the number of landfall TC over China's Mainland and its associated rainfall is more than the average. This paper focuses on the performance of numerical weather prediction (NWP) of landfall TC precipitation over China in 2009. The China Meteorological Administration (CMA) and Japan Meteorological Agency (JMA) models are compared. Although the schemes of physical processes, the data assimilation system and the dynamic frame are entirely different for the two models, the results of forecast verification are similar to each other for TC rainfall and track except for TC Goni. In this paper, a day with daily rainfall amount greater than 50 mm was selected as a storm rain day when there was a TC affecting the mainland. There are 32 storm rain days related to the landing of typhoons and tropical depressions. The rainfall forecast verification methods of National Meteorological Centre (NMC) of CMA are selected to verify the models' rainfall forecast. Observational precipitation analyses related to TCs in 2009 indicate a U-shape spatial distribution in China. It is found that the rain belt forecasted by the two models within 60 hours shows good agreement with observations, both in the location and the maximum rainfall center. Beyond 3 days, the forecasted rainfall belt shifts northward on average, and the rainfall amount of the model forecasts becomes under-predicted. The rainfall intensity of CMA model forecast is more reasonable than that of JMA model. For heavy rain, the JMA model made more missing forecasts. The TC rainfall is verified in Guangdong, Guangxi, Fujian and Hainan where rainfall amount related to TCs is relatively larger than in other regions. The results indicate that the model forecast for Guangdong and Guangxi is more skillful than that for Hainan. The rainfall forecast for Hainan remains difficult for the models because of insufficient observation data and special tropical ocean climate.

Verification of A Numerical Harbour Wave Model

A numerical model for wave propagation in a harbour is verified by use of physical models. The extended time-dependent mild slope equation is employed as the governing equation, and the model is solved by use of ADI method containing the relaxation factor. Firstly, the reflection coefficient of waves in front of rubble-mound breakwaters under oblique incident waves is determined through physical model tests, and it is regarded as the basis for simulating partial reflection boundaries of the numerical model. Then model tests on refraction, diffraction and reflection of waves in a harbour are performed to measure wave height distribution. Comparative results between physical and numerical model tests show that the present numerical model can satisfactorily simulate the propagation of regular and irregular waves in a harbour with complex topography and boundary conditions.

Dynamic Signature Verification Using Pattern Recognition

Dynamic signature is a biometric modality that recognizes an individual’s anatomic and behavioural characteristics when signing their name. The rampant case of signature falsification (Identity Theft) was the key motivating factor for embarking on this study. This study was necessitated by the damages and dangers posed by signature forgery coupled with the intractable nature of the problem. The aim and objectives of this study is to design a proactive and responsive system that could compare two signature samples and detect the correct signature against the forged one. Dynamic Signature verification is an important biometric technique that aims to detect whether a given signature is genuine or forged. In this research work, Convolutional Neural Networks (CNNsor ConvNet) which is a class of deep, feed forward artificial neural networks that has successfully been applied to analysing visual imagery was used to train the model. The signature images are stored in a file directory structure which the Keras Python library can work with. Then the CNN was implemented in python using the Keras with the TensorFlow backend to learn the patterns associated with the signature. The result showed that for the same CNNs-based network experimental result of average accuracy, the larger the training dataset, the higher the test accuracy. However, when the training dataset are insufficient, better results can be obtained. The paper concluded that by training datasets using CNNs network, 98% accuracy in the result was recorded, in the experimental part, the model achieved a high degree of accuracy in the classification of the biometric parameters used.

Formal Verification of TASM Models by Translating into UPPAAL

Timed abstract state machine(TASM) is a formal specification language used to specify and simulate the behavior of real-time systems. Formal verification of TASM model can be fulfilled through model checking activities by translating into UPPAAL. Firstly, the translational semantics from TASM to UPPAAL is presented through atlas transformation language(ATL). Secondly, the implementation of the proposed model transformation tool TASM2UPPAAL is provided. Finally, a case study is given to illustrate the automatic transformation from TASM model to UPPAAL model.

VERIFICATION OF TYPHOON FORECASTS BY THE GRAPES MODEL

Four landfalling typhoon cases in 2005 were selected for a numerical simulation study with the Global/Regional Assimilation and Prediction System(GRAPES) model.The preliminary assessment results of the performance of the model,including the predictions of typhoon track,landfall time,location and intensity,etc.,are presented and the sources of errors are analyzed.The 24-hour distance forecast error of the typhoon center by the model is shown to be about 131 km,while the 48-hour error is 252 km.The model was relatively more skilful at forecasts of landfall time and locations than those of intensity at landfall.On average,the 24-hour forecasts were slightly better than the 48-hour ones.An analysis of data impacts indicates that the assimilation of unconventional observation data is essential for the improvement of the model simulation.The model could also be improved by increasing model resolution to simulate the mesoscale and fine scale systems and by improving methods of terrain refinement processing.

An On-chip Interconnection QoS Verification Platform of Processor of Large Data for Architectural Modeling Analysis

This paper presents introduction for a QoS verification of on-chip interconnection based on the new progress of the industry, which combined with an AMD processor chip design for big data. Some verification experience in architectural modeling and simulation of on-chip interconnection is also introduced in this paper.

ESTABLISHMENT AND VERIFICATION OF MATHEMATICAL MODEL FOR CURRENT LEAKAGE IN BIPOLAR MULTI－COMPARTMENT CELL

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Long-term Prediction and Verification of Rainfall Based on the Seasonal Model

Using the seasonal cross-multiplication trend model, monthly precipitation of eight national basic weather stations of Shaanxi Province from 2005 to 2010 was predicted, and the forecast results were verified using the rainfall scoring rules of China Meteorological Administration. The verification results show that the average score of annual precipitation prediction in recent six years is higher than that made by a professional forecaster, so this model has a good prospect of application. Moreover, the level of making prediction is steady, and it can be widely used in long-term prediction of rainfall.

Application and Verification of Multi-Model Products in Medium Range Forecast

The verification analysis is applied to medium-range forecast products of T639, ECMWF, Japan model, NCEP ensemble forecast and NMC multi-model integration in late October 2012. The results show that ECMWF model has obvious advantage over other models in terms of height field and precipitation forecast;the westerly-wind index, geostrophic U wind and 850 hPa temperature prediction products can reflect the adjustment of atmospheric circulation and the activity of cold air, which have a good reference for the medium-range temperature forecast in the eastern China;the prediction of ECMWF height field and wind field can well grasp the main weather processes within 192 h, but beyond 192 h the model forecast ability decreases significantly;different models have large deviations in the medium-range forecast of typhoon track and the intensity and range of typhoon precipitation.

Automatic Verification of Biochemical Network Using Model Checking Method

This study focuses on automatic searching and verifying methods for the teachability, transition logics and hierarchical structure in all possible paths of biological processes using model checking. The automatic search and verification for alternative paths within complex and large networks in biological process can provide a considerable amount of solutions, which is difficult to handle manually. Model checking is an automatic method for verifying if a circuit or a condition, expressed as a concurrent transition system, satisfies a set of properties expressed in a temporal logic, such as computational tree logic （CTL）. This article represents that model checking is feasible in biochemical network verification and it shows certain advantages over simulation for querying and searching of special behavioral properties in biochemical processes.

An Intelligent Cluster Verification Model Using WSN to Avoid Close Proximity and Control Outbreak of Pandemic in a Massive Crowd

Assemblage at public places for religious or sports events has become an integral part of our lives.These gatherings pose a challenge at places where fast crowd verification with social distancing(SD)is required,especially during a pandemic.Presently,verification of crowds is carried out in the form of a queue that increases waiting time resulting in congestion,stampede,and the spread of diseases.This article proposes a cluster verification model(CVM)using a wireless sensor network(WSN),single cluster approach(SCA),and split cluster approach(SpCA)to solve the aforementioned problem for pandemic cases.We show that SD,cluster approaches,and verification by WSN can overcome the management issues by optimizing the cluster size and verification time.Hence,our proposed method minimizes the chances of spreading diseases and stampedes in large events such as a pilgrimage.We consider the assembly points in the annual pilgrimage to Makkah Al-Mukarmah and Umrah for verification using Contiki/Cooja tool.We compute results such as verified cluster members(CMs)to define cluster size,success rate to determine the best success rate,and verification time to determine the optimal verification time for various scenarios.We validate ourmodel by comparing the results of each approach with the existing model.Our results showthat the SpCAwith SD is the best approach with a 96% success rate and optimization of verification time as compared to SCA with SD and the existing model.

Modeling and Verification of Aircraft Takeoff Through Novel Quantum Nets

The formal modeling and verification of aircraft takeoff is a challenge because it is a complex safety-critical operation.The task of aircraft takeoff is distributed amongst various computer-based controllers,however,with the growing malicious threats a secure communication between aircraft and controllers becomes highly important.This research serves as a starting point for integration of BB84 quantum protocol with petri nets for secure modeling and verification of takeoff procedure.The integrated model combines the BB84 quantum cryptographic protocol with powerful verification tool support offered by petri nets.To model certain important properties of BB84,a new variant of petri nets coined as Quantum Nets are proposed by defining their mathematical foundations and overall system dynamics,furthermore,some important system properties are also abstractly defined.The proposed QuantumNets are then applied for modeling of aircraft takeoff process by defining three quantum nets:namely aircraft,runway controller and gate controller.For authentication between quantum nets,the use of external places and transitions is demonstrated to describe the encryptiondecryption process of qubits stream.Finally,the developed takeoff quantum network is verified through simulation offered by colored petri-net(CPN)Tools.Moreover,reachability tree(RT)analysis is also performed to have greater confidence in feasibility and correctness of the proposed aircraft takeoff model through the Quantum Nets.

ExperimentalVerificationofaDetailedVehicle┐TrackVerticalInteractionModel

A theoretical model has been developed to investigate vertical dynamic interactions between railway vehicles and tracks. Wheel rail forces and dynamic responses of vehicle and track components can be simulated with the model. The model has been applied to the study of high speed and heavy haul railway dynamic problems. In order to verify the model completely, a full scale field experiment was performed on the Chinese Datong Qinhuangdao railway. Accelerations of rail, sleeper and ballast were measured and compared with the simulated results both in time domain and in frequency domain.

An Effective Approach to Verify the Correctness of Workflow Process Models Based on Petri Net

Along with the extensive use of workflow, analysis methods to verify the correctness of the workflow are becoming more and more important. In the paper, we exploit the verification method based on Petri net for workflow process models which deals with the verification of workflow and finds the potential errors in the process design. Additionally, an efficient verification algorithm is given.

Characteristic Verification and Parameter Optimization of Airbags Cushion System for Airborne Vehicle

Abstract： The major methods to investigate the airbags cushion system are experimental method, thermodynamic method and finite element method （FEM）. Airbags cushion systems are very complicated and very difficult to be investigated thoroughly by such methods For experimental method, it is nearly impossible to completely analyze and optimize the cushion characteristics of airbags of airborne vehicle because of charge issue, safety concern and time constraint. Thermodynamic method fails to take the non-linear effects of large airbag deformation and varied contact conditions into consideration. For finite element method, the FE model is usually complicated and the calculation takes tens of hours of CPU time. As a result, the optimization of the design based on a nonlinear model is very difficult by traditional iterative approach method. In this paper, a model based on FEM and control volume method is proposed to simulate landing cushion process of airborne vehicle with airbags cushion system in order to analyze and optimize the parameters in airbags cushion system. At first, the performance of airbags cushion system model is verified experimentally. In airdrop test, accelerometers are fixed in 4 test points distributed over engine mount, top, bottom and side armor plate of hull to obtain acceleration curves with time. The simulation results are obtained under the same conditions of the airdrop test and the simulation results agree very well with the experimental results, which indicate the established model is valid for further optimization. To optimize the parameters of airbags, equivalent response model based on Latin Hypercube DOE and radial basis function is employed instead of the complex finite element model. Then the optimal results based on equivalent response model are obtained using simulated annealing algorithm. After optimization, the maximal acceleration of airborne vehicle landing reduces 19.83%, while the energy absorption by airbags increases 7.85%. The performance of the airbags cushion system thus is largely improved through optimization, which indicates the proposed method has the capability of solving the parameter optimization problem of airbags cushion system for airborne vehicle.