UML-based combat effectiveness simulation system modeling within MDE

To reduce complexity, the combat effectiveness simulation system(CESS) is often decomposed into static structure,physical behavior, and cognitive behavior, and model abstraction is layered onto domain invariant knowledge(DIK) and application variant knowledge(AVK) levels. This study concentrates on the specification of CESS’s physical behaviors at the DIK level of abstraction, and proposes a model driven framework for efficiently developing simulation models within model-driven engineering(MDE). Technically, this framework integrates the four-layer metamodeling architecture and a set of model transformation techniques with the objective of reducing model heterogeneity and enhancing model continuity. As a proof of concept, a torpedo example is illustrated to explain how physical models are developed following the proposed framework. Finally, a combat scenario is constructed to demonstrate the availability, and a further verification is shown by a reasonable agreement between simulation results and field observations.

Energy principle of ferroelectric ceramics and single domain mechanical model

Many physical experiments have shown that the domain switching in a ferroelectric material is a complicated evolution process of the domain wall with the variation of stress and electric field. According to this mechanism, the volume fraction of the domain switching is introduced in the constitutive law of ferroelectric ceramic and used to study the nonlinear constitutive behavior of ferroelectric body in this paper. The principle of stationary total energy is put forward in which the basic unknown quantities are the displacement ui, electric displacement Di and volume fraction pI of the domain switching for the variant I. Mechanical field equation and a new domain switching criterion are obtained from the principle of stationary total energy. The domain switching criterion proposed in this paper is an expansion and development of the energy criterion. On the basis of the domain switching criterion, a set of linear algebraic equations for the volume fraction PI of domain switching is obtained, in which the coefficients of the linear algebraic equations only contain the unknown strain and electric fields. Then a single domain mechanical model is proposed in this paper. The poled ferroelectric specimen is considered as a transversely isotropic single domain. By using the partial experimental results, the hardening relation between the driving force of domain switching and the volume fraction of domain switching can be calibrated. Then the electromechanical response can be calculated on the basis of the calibrated hardening relation. The results involve the electric butterfly shaped curves of axial strain versus axial electric field, the hysteresis loops of electric displacement versus electric filed and the evo- lution process of the domain switching in the ferroelectric specimens under uniaxial coupled stress and electric field loading. The present theoretic prediction agrees reasonably with the experimental results given by Lynch.

Model architecture-oriented combat system effectiveness simulation based on MDE

Combat system effectiveness simulation (CSES) is a special type of complex system simulation. Three non-functional requirements (NFRs), i.e. model composability, domain specific modeling, and model evolvability, are gaining higher priority from CSES users when evaluating different modeling methodologies for CSES. Traditional CSES modeling methodologies are either domain-neutral (lack of domain characteristics consideration and limited support for model composability) or domain-oriented (lack of openness and evolvability) and fall short of the three NFRs. Inspired by the concept of architecture in systems engineering and software engineering fields, we extend it into a concept of model architecture for complex simulation systems, and propose a model architecture-oriented modeling methodology in which the model architecture plays a central role in achieving the three NFRs. Various model-driven engineering (MDE) approaches and technologies, including simulation modeling platform (SMP), unified modeling language (UML), domain specific modeling (DSM), eclipse modeling framework (EMF), graphical modeling framework (GMF), and so forth, are applied where possible in representing the CSES model architecture and its components' behaviors from physical and cognitive domain aspects. A prototype CSES system, called weapon effectiveness simulation system (WESS), and a non-trivial air-combat simulation example are presented to demonstrate the methodology.

Review on the Work of Agriculture Ontology Research Group

This paper introduces efforts and achievements of Agriculture Ontology Service Research Group of Agricultural Information Institute of Chinese Academy of Agriculture Sciences in last 10 years. It summarizes the research on ontology construction methodology, ontology management system, ontology application and etc.

Elimination of the impact of vessels on ocean wave height inversion with X-band wave monitoring radar

Directional wave spectra and integrated wave parameters can be derived from X-band radar sea surface images.A vessel on the sea surface has a significant influence on wave parameter inversions that can be seen as intensive backscatter speckles in X-band wave monitoring radar sea surface images.A novel algorithm to eliminate the interference of vessels in ocean wave height inversions from X-band wave monitoring radar is proposed.This algorithm is based on the characteristics of the interference.The principal components(PCs) of a sea surface image sequence are extracted using empirical orthogonal function(EOF)analysis.The standard deviation of the PCs is then used to identify vessel interference within the image sequence.To mitigate the interference,a suppression method based on a frequency domain geometric model is applied.The algorithm framework has been applied to OSMAR-X,a wave monitoring system developed by Wuhan University,based on nautical X-band radar.Several sea surface images captured on vessels by OSMAR-X are processed using the method proposed in this paper.Inversion schemes are validated by comparisons with data from in situ wave buoys.The root-mean-square error between the significant wave heights(SWH) retrieved from original interference radar images and those measured by the buoy is reduced by 0.25 m.The determinations of surface gravity wave parameters,in particular SWH,confirm the applicability of the proposed method.

Fifth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (5th-CASAM-N): II. Paradigm Application to a Bernoulli Model Comprising Uncertain Parameters

This work presents the application of the recently developed “Fifth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems (5th-CASAM-N)” to a simplified Bernoulli model. The 5th-CASAM-N builds upon and incorporates all of the lower-order (i.e., the first-, second-, third-, and fourth-order) adjoint sensitivities analysis methodologies. The Bernoulli model comprises a nonlinear model response, uncertain model parameters, uncertain model domain boundaries and uncertain model boundary conditions, admitting closed-form explicit expressions for the response sensitivities of all orders. Illustrating the specific mechanisms and advantages of applying the 5th-CASAM-N for the computation of the response sensitivities with respect to the uncertain parameters and boundaries reveals that the 5th-CASAM-N provides a fundamental step towards overcoming the curse of dimensionality in sensitivity and uncertainty analysis.

ON THE STABILITY OF THE SOLUTION TO A GONORRHEA DISCRETE MATHEMATICAL MODEL

In this paper, the author studies the stability of the solution to a three-dimension-al gonorrhea discrete mathematical model by Liapunoy method. The parameter es-timator of the slability domain is obtained and the rationality of the model is ex-plained in a theoretic way.

Active suspension with optimal control based on a full vehicle model

The 7-DOF model of a full vehicle with an active suspension is developed in this paper.The model is written into the state equation style.Actuator forces are treated as inputs in the state equations.Based on the basic optimal control theory,the optimal gains for the control system are figured out.So an optimal controller is developed and implemented using Matlab/Simulink,where the Riccati equation with coupling terms is deduced using the Hamilton equation.The all state feedback is chosen for the controller.The gains for all vehicle variables are traded off so that majority of indexes were up to optimal.The active suspension with optimal control is simulated in frequency domain and time domain separately,and compared with a passive suspension.Throughout all the simulation results,the optimal controller developed in this paper works well in the majority of instances.In all,the comfort and ride performance of the vehicle are improved under the active suspension with optimal control.

Design and Simulation of the Thin Film Pulse Transformer

A new thin film pulse transformer for using in ISND and ADSL systems has been designed based on a domain wall pinning model, the parameters of nano-magnetic thin film such as permeability and coercivity can be calculated. The main properties of the thin film transformer including the size, parallel inductance, Q value and turn ratio have been simulated and optimized. Simulation results show that the thin film transformer can be fairly operated in a frequency range of 0.001~20 MHz.

Modeling of the resilient supply chain system from a perspective of production design changes

Building an effective resilient supply chain system (RSCS) is critical and necessary to reduce the risk of supply chain disruptions in unexpected scenarios such as COVID-19 pandemic and trade wars. To overcome the impact of insufficient raw material supply on the supply chain in mass disruption scenarios, this study proposes a novel RSCS considering product design changes (PDC). An RSCS domain model is first developed from the perspective of PDC based on a general conceptual framework, i.e., function-context-behavior-principle-state-structure (FCBPSS), which can portray complex systems under unpredictable situations. Specifically, the interaction among the structure, state and behavior of the infrastructure system and substance system is captured, and then a quantitative analysis of the change impact process is presented to evaluate the resilience of both the product and supply chain. Next, a case study is conducted to demonstrate the PDC strategy and to validate the feasibility and effectiveness of the RSCS domain model. The results show that the restructured RSCS based on the proposed strategy and model can remedy the huge losses caused by the unavailability of raw materials.

Identification method for helicopter flight dynamics modeling with rotor degrees of freedom

A comprehensive method based on system identification theory for helicopter flight dynamics modeling with rotor degrees of freedom is developed. A fully parameterized rotor flapping equation for identification purpose is derived without using any theoretical model, so the confidence of the identified model is increased, and then the 6 degrees of freedom rigid body model is extended to 9 degrees of freedom high-order model. Bode sensitivity function is derived to increase the accuracy of frequency spectra calculation which influences the accuracy of model parameter identification. Then a frequency domain identification algorithm is established. Acceleration technique is developed furthermore to increase calculation efficiency, and the total identification time is reduced by more than 50% using this technique. A comprehensive two-step method is established for helicopter high-order flight dynamics model identification which increases the numerical stability of model identification compared with single step algorithm. Application of the developed method to identify the flight dynamics model of BO 105 helicopter based on flight test data is implemented. A comparative study between the high-order model and rigid body model is performed at last. The results show that the developed method can be used for helicopter high-order flight dynamics model identification with high accuracy as well as efficiency, and the advantage of identified high-order model is very obvious compared with low-order model.

Method for Processing Graph Degeneracy in Dynamic Geometry Based on Domain Design

A dynamic geometry system,as an important application in the field of geometric constraint solving,is widely used in elementary mathematics education;moreover,the dynamic geometry system is also a fundamental environment for automated theorem proving in geometry.In a geometric constraint solving process,a situation involving a critical point is often encountered,and geometric element degeneracy may occur at this point.Usually,the degeneracy situation must be substantively focused on during the learning and exploration process.However,many degeneracy situations cannot be completely presented even by the well-known dynamic geometry software.In this paper,the mechanisms causing the degeneracy of a geometric element are analyzed,and relevant definitions and formalized descriptions for the problem are provided according to the relevant modern Euclidean geometry theories.To solve the problem,the data structure is optimized,and a domain model design for the geometric element and the constraint relationships thereof in the dynamic geometry system are formed;furthermore,an update algorithm for the element is proposed based on the novel domain model.In addition,instances show that the proposed domain model and the update algorithm can effectively cope with the geometric element degeneracy situations in the geometric constraint solving process,thereby achieving unification of the dynamic geometry drawing and the geometric intuition of the user.

Trusted domain hierarchical model based on noninterference theory

To ensure the integrity and security of cloud tenants＇ workload, and to prevent unexpected interference among tenants, cloud platform must make sure that system behaviors are trusted. By analyzing threats that exist in the cloud platform, a novel trusted domain hierarchical model（TDHM） based on noninterference theory was proposed in this paper to solve these problems. First of all, the abstraction modeling of tenants＇ computing environment and trusted domain（TD） were introduced for designing TDHM with formal methods. Secondly, corresponding constraints for trusted running were given to satisfy security requirements of tenants＇ TD, and security properties of TDHM ware analyzed. After that, trusted behavior of TD was defined based on these properties, and the decision theorem of that was proved. It illustrated that the design and implementation of TD in cloud followed the model with characteristics of trusted behavior. Finally, the implementation of prototype system was introduced based on our previous work, and evaluation results showed that the performance loss was in the acceptable range.

Scaling relation of domain competition on(2+1)-dimensional ballistic deposition model with surface diffusion

During heteroepitaxial overlayer growth multiple crystal domains nucleated on a substrate surface compete with each other in such a manner that a domain covered by neighboring ones stops growing.The number density of active domains ρ decreases as the height h increases.A simple scaling argument leads to a scaling law of ρ~ h^（-γ） with a coarsening exponent γ=d/z,where d is the dimension of the substrate surface and z the dynamic exponent of a growth front.This scaling relation is confirmed by performing kinetic Monte Carlo simulations of the ballistic deposition model on a two-dimensional（d=2） surface,even when an isolated deposited particle diffuses on a crystal surface.

Effect of Meteorological Data Assimilation on Regional Air Quality Forecasts over the Korean Peninsula

The Weather Research and Forecasting model coupled with Chemistry(WRF-Chem),a type of online coupled chemistry-meteorology model(CCMM),considers the interaction between air quality and meteorology to improve air quality forecasting.Meteorological data assimilation(DA)can be used to reduce uncertainty in meteorological field,which is one factor causing prediction uncertainty in the CCMM.In this study,WRF-Chem and three-dimensional variational DA were used to examine the impact of meteorological DA on air quality and meteorological forecasts over the Korean Peninsula.The nesting model domains were configured over East Asia(outer domain)and the Korean Peninsula(inner domain).Three experiments were conducted by using different DA domains to determine the optimal model domain for the meteorological DA.When the meteorological DA was performed in the outer domain or both the outer and inner domains,the root-mean-square error(RMSE),bias of the predicted particulate matter(PM)concentrations,and the RMSE of predicted meteorological variables against the observations were smaller than those in the experiment where the meteorological DA was performed only in the inner domain.This indicates that the improvement of the synoptic meteorological fields by DA in the outer domain enhanced the meteorological initial and boundary conditions for the inner domain,subsequently improving air quality and meteorological predictions.Compared to the experiment without meteorological DA,the RMSE and bias of the meteorological and PM variables were smaller in the experiments with DA.The effect of meteorological DA on the improvement of PM predictions lasted for approximately 58-66 h,depending on the case.Therefore,the uncertainty reduction in the meteorological initial condition by the meteorological DA contributed to a reduction of the forecast errors of both meteorology and air quality.

Landscape structure and suitable habitat analysis for effective restoration planning in semi-arid mountain forests

Background:Suitable habitat and landscape structure play a pivotal role in the success of forest restoration projects.This study aimed to model the habitat suitability of wild almond(Amygdalus scoparia Spach)using three individual species distribution models(SDMs),i.e.,backpropagation artificial neural network(BP-ANN),maximum entropy(MaxEnt),generalized linear model(GLM),as well as the ensemble technique along with measuring the landscape metrics and analyzing the relationship between the distribution of the suitable habitat of the species in different landform classes in Fars Province,southern Iran.Results:There was no clear difference in the prediction performance of the models.The BP-ANN had the highest accuracy(AUC=0.935 and k=0.757)in modeling habitat suitability of A.scoparia,followed by the ensemble technique,GLM,and MaxEnt models with the AUC values of 0.890,0.887,and 0.777,respectively.The highest discrimination capacity was associated to the BP-ANN model,and the highest reliability was related to the ensemble technique.Moreover,evaluation of variable importance showed that the occurrence of A.scoparia was strongly dependent on climatic variables,particularly isothermality(Bio 3),temperature seasonality(Bio 4),and precipitation of driest quarter(Bio 17).Analysis of the distribution of species habitat in different landform classes revealed that the canyon,mountain top,upland drainage,and hills in valley classes had the highest suitability for the species establishment.Conclusions:Considering the importance of landform in the establishment of plant habitats,the combination of the outputs of the SDMs,landform,and the use of landscape metrics could provide both a clear view of habitat conditions and the possibility of analyzing habitat patches and their relationships that can be very useful in managing the remaining forests in semi-arid regions.The canyon,mountain top,and upland drainage classes were found to be the most important landforms to provide the highest suitable environmental conditions for the establishment of A.scoparia.Therefore,such landforms should be given priority in restoration projects of forest in the study area.

Harmonic Damping Characteristics of Single-phase Full-bridge Rectifier Based Loads

With the rapid development of power electronic technology,many linear single-phase loads in low voltage systems are replaced by those equipped with a single-phase diode rectifier.Therefore,most of single-phase loads become harmonic producers due to their nonlinear characteristics.The nonlinear loads may have different damping characteristics at harmonic frequencies,which could cause potential power quality problems.This paper studies the harmonic damping characteristics of such nonlinear loads.The harmonic damping index is defined to quantify the damping effect of nonlinear loads of harmonic frequencies by analyzing the harmonic model.Then,the harmonic damping index of different harmonic frequencies is compared through simulations and experiments.The results show that the nonlinear load has a constant damping effect for the fundamental frequency,but a stronger damping for the harmonic frequencies.The harmonic damping of such nonlinear loads varies with the harmonic phase angle of supply voltage,and becomes stronger with the increase of the harmonic order.It implies that this type of nonlinear load may be beneficial to the suppression of harmonic resonance.

Bergman kernel and complex singularity exponent

We give a precise estimate of the Bergman kernel for the model domain defined by Ω F = “(z,w) ∈ ? n+1: Im w ? |F(z)|2 > 0”, where F = (f 1, ..., f m ) is a holomorphic map from ? n to ? m , in terms of the complex singularity exponent of F.

Preference transfer model in collaborative filtering for implicit data

Generally, predicting whether an item will be liked or disliked by active users, and how much an item will be liked, is a main task of collaborative filtering systems or recommender systems. Recently, predicting most likely bought items for a target user, which is a subproblem of the rank problem of collaborative filtering, became an important task in collaborative filtering. Traditionally, the prediction uses the user item co-occurrence data based on users' buying behaviors. However, it is challenging to achieve good prediction performance using traditional methods based on single domain information due to the extreme sparsity of the buying matrix. In this paper, we propose a novel method called the preference transfer model for effective cross-domain collaborative filtering. Based on the preference transfer model, a common basis item-factor matrix and different user-factor matrices are factorized.Each user-factor matrix can be viewed as user preference in terms of browsing behavior or buying behavior. Then,two factor-user matrices can be used to construct a so-called ‘preference dictionary' that can discover in advance the consistent preference of users, from their browsing behaviors to their buying behaviors. Experimental results demonstrate that the proposed preference transfer model outperforms the other methods on the Alibaba Tmall data set provided by the Alibaba Group.