High level architecture evolved modular federation object model

To improve the agility, dynamics, composability, reusability, and development efficiency restricted by monolithic federation object model （FOM）, a modular FOM is proposed by high level architecture （HLA） evolved product development group. This paper reviews the state-of-the-art of HLA evolved modular FOM. In particular, related concepts, the overall impact on HLA standards, extension principles, and merging processes are discussed. Also permitted and restricted combinations, and merging rules are provided, and the influence on HLA interface specification is given. The comparison between modular FOM and base object model （BOM） is performed to illustrate the importance of their combination. The applications of modular FOM are summarized. Finally, the significance to facilitate compoable simulation both in academia and practice is presented and future directions are pointed out.

Level crossing in a two-photon Jaynes-Cummings model

In this paper,the energy spectrum of the two-photon Jaynes-Cummings model（TPJCM） is calculated exactly in the non-rotating wave approximation（non-RWA）,and we study the level-crossing problem by means of fidelity.A narrow peak of the fidelity is observed at the level-crossing point,which does not appear at the avoided-crossing point.Therefore fidelity is perfectly suited for detecting the level-crossing point in the energy spectrum.

Methodology for local correction of the heights of global geoid models to improve the accuracy of GNSS leveling

At present,one of the methods used to determine the height of points on the Earth’s surface is Global Navigation Satellite System(GNSS)leveling.It is possible to determine the orthometric or normal height by this method only if there is a geoid or quasi-geoid height model available.This paper proposes the methodology for local correction of the heights of high-order global geoid models such as EGM08,EIGEN-6C4,GECO,and XGM2019e_2159.This methodology was tested in different areas of the research field,covering various relief forms.The dependence of the change in corrected height accuracy on the input data was analyzed,and the correction was also conducted for model heights in three tidal systems:"tide free","mean tide",and"zero tide".The results show that the heights of EIGEN-6C4 model can be corrected with an accuracy of up to 1 cm for flat and foothill terrains with the dimensionality of 1°×1°,2°×2°,and 3°×3°.The EGM08 model presents an almost identical result.The EIGEN-6C4 model is best suited for mountainous relief and provides an accuracy of 1.5 cm on the 1°×1°area.The height correction accuracy of GECO and XGM2019e_2159 models is slightly poor,which has fuzziness in terms of numerical fluctuation.

A hybrid CNN-LSTM model for diagnosing rice nutrient levels at the rice panicle initiation stage

Nitrogen(N)and potassium(K)are two key mineral nutrient elements involved in rice growth.Accurate diagnosis of N and K status is very important for the rational application of fertilizers at a specific rice growth stage.Therefore,we propose a hybrid model for diagnosing rice nutrient levels at the early panicle initiation stage(EPIS),which combines a convolutional neural network(CNN)with an attention mechanism and a long short-term memory network(LSTM).The model was validated on a large set of sequential images collected by an unmanned aerial vehicle(UAV)from rice canopies at different growth stages during a two-year experiment.Compared with VGG16,AlexNet,GoogleNet,DenseNet,and inceptionV3,ResNet101 combined with LSTM obtained the highest average accuracy of 83.81%on the dataset of Huanghuazhan(HHZ,an indica cultivar).When tested on the datasets of HHZ and Xiushui 134(XS134,a japonica rice variety)in 2021,the ResNet101-LSTM model enhanced with the squeeze-and-excitation(SE)block achieved the highest accuracies of 85.38 and 88.38%,respectively.Through the cross-dataset method,the average accuracies on the HHZ and XS134 datasets tested in 2022 were 81.25 and 82.50%,respectively,showing a good generalization.Our proposed model works with the dynamic information of different rice growth stages and can efficiently diagnose different rice nutrient status levels at EPIS,which are helpful for making practical decisions regarding rational fertilization treatments at the panicle initiation stage.

Inclusive Multiple Models(IMM)for predicting groundwater levels and treating heterogeneity

An explicit model management framework is introduced for predictive Groundwater Levels(GWL),particularly suitable to Observation Wells(OWs)with sparse and possibly heterogeneous data.The framework implements Multiple Models(MM)under the architecture of organising them at levels,as follows:(i)Level 0:treat heterogeneity in the data,e.g.Self-Organised Mapping(SOM)to classify the OWs;and decide on model structure,e.g.formulate a grey box model to predict GWLs.(ii)Level 1:construct MMs,e.g.two Fuzzy Logic(FL)and one Neurofuzzy(NF)models.(iii)Level 2:formulate strategies to combine the MM at Level 1,for which the paper uses Artificial Neural Networks(Strategy 1)and simple averaging(Strategy 2).Whilst the above model management strategy is novel,a critical view is presented,according to which modelling practices are:Inclusive Multiple Modelling(IMM)practices contrasted with existing practices,branded by the paper as Exclusionary Multiple Modelling(EMM).Scientific thinking over IMMs is captured as a framework with four dimensions:Model Reuse(MR),Hierarchical Recursion(HR),Elastic Learning Environment(ELE)and Goal Orientation(GO)and these together make the acronym of RHEO.Therefore,IMM-RHEO is piloted in the aquifer of Tabriz Plain with sparse and possibly heterogeneous data.The results provide some evidence that(i)IMM at two levels improves on the accuracy of individual models;and(ii)model combinations in IMM practices bring‘model-learning’into fashion for learning with the goal to explain baseline conditions and impacts of subsequent management changes.

Greenland Ice Sheet Contribution to Future Global Sea Level Rise based on CMIP5 Models

Sea level rise （SLR） is one of the major socioeconomic risks associated with global warming. Mass losses from the Greenland ice sheet （GrIS） will be partially responsible for future SLR, although there are large uncertainties in modeled climate and ice sheet behavior. We used the ice sheet model SICOPOLIS （Simulation COde for POLythermal Ice Sheets） driven by climate projections from 20 models in the fifth phase of the Coupled Model Intercomparison Project （CMIP5） to estimate the GrlS contribution to global SLR. Based on the outputs of the 20 models, it is estimated that the GrIS will contribute 0-16 （0-27） cm to global SLR by 2100 under the Representative Concentration Pathways （RCP） 4.5 （RCP 8.5） scenarios. The projected SLR increases further to 7-22 （7-33） cm with 2~basal sliding included. In response to the results of the multimodel ensemble mean, the ice sheet model projects a global SLR of 3 cm and 7 cm （10 cm and 13 cm with 2~basal sliding） under the RCP 4.5 and RCP 8.5 scenarios, respectively. In addition, our results suggest that the uncertainty in future sea level projection caused by the large spread in climate projections could be reduced with model-evaluation and the selective use of model outputs.

New partial cooperation model for bilevel programming problems

Partial cooperation models are studied for many years to solve the bilevel programming problems where the follower’s optimal reaction is not unique. However, in these existed models, the follower’s cooperation level does not depend on the leader’s decision. A new model is proposed to solve this deficiency. It is proved the feasibility of the new model when the reaction set of the lower level is lower semicontinuous. And the numerical results show that the new model has optimal solutions when the reaction set of the lower level is discrete, lower semi-continuous and non-lower semi-continuous.

Safety Assessment of Closed-Loop Level Crossing Control Systems by Means of STAMP(Systems-Theoretic Accident Model and Processes)

There have been a large number of accidents at level crossings of railways and this has been considered to be a significant issue to be solved for the realization of safe and stable railway transport.A conventional level crossing control system is characterized by the use of two types of electronic train detectors;one detects a train approaching to a level crossing section and the other then detects the train having left the level crossing.By contrast,closed-loop level crossing control systems in which level crossing control equipment and train-borne equipment communicate with each other have been advocated and are expected to serve as an effective solution to the abovementioned issue.This paper describes the following three types of closed-loop level crossing control systems:decentralized level crossing control system,fully-centralized comprehensive level crossing control system and fully-centralized individual level crossing control system.This paper then assesses the safety of these systems in comparison to the conventional level crossing control system.For the purpose of the assessment of their safety,a new accident analysis model called STAMP(systems theoretic accident model and processes)that is suitable for software intensive systems is used to clarify the advantage of the proposed three types of level crossing control systems in terms of safety.

Evaluation of the sustainable development level of countries along the Belt and Road and its impact factors:Empirical analysis based on the Super-efficiency slacks-based measure and Tobit measure models

Sustainable development is an important component of the Belt and Road Initiative(BRI)and is of great significance for evaluating the levels of sustainable development of countries along this route(henceforth,BRI countries).Therefore,this study aims to identify the factors that influence the levels of sustainable development of BRI countries in a reasonable and objective manner.Eventually,this study employs the super efficiency slacks-based measure(Super-SBM)model,which considers unexpected outputs to measure the level of sustainable development of BRI countries.The dynamic change and composition of the sustainable development level of these countries are calculated using the global Malmquist-Luenberger index.Furthermore,the Tobit model is used to identify the factors influencing the level of sustainable development of BRI countries in general and in various categories.The empirical results suggest the following points.(a)The overall level of sustainable development of BRI countries is low,whereas those of high-income and middle-and high-income countries are relatively high.(b)The overall sustainable development levels of BRI countries declined to a certain extent in 2008 owing to the effect of the financial crisis,.However,the sustainable development level of other countries,barring low-income countries,has gradually increased since 2011.(c)Since 2008,technological progress has replaced technical efficiency as the main driving force behind the improvement of the sustainable development level of BRI countries.(d)A U-shaped relationship is observed between the economic and sustainable development levels of these countries.(e)The level of science and technology and the proportion of renewable energy consumption can promote the sustainable development of these countries.Moreover,a negative correlation exists between the level of opening to the outside world and that of sustainable development of countries that mainly export resource-based products and are dominated by labor-intensive export industries.Barring low-income countries,the energy structure plays an effective role in improving the level of sustainable development.Finally,the study presents suggestions for China in the process of coping with the sustainable development of relevant countries during its promotion of the BRI.

Top-level modeling theory of multi-discipline virtual prototype

Multi-disciplinary virtual prototypes of complex products are increasingly and widely used in modern advanced manufactur- ing. How to effectively address the problems of unified modeling, composition and reuse based on the multi-disciplinary heteroge- neous models has brought great challenges to the modeling and simulation （M＆S） science and technology. This paper presents a top-level modeling theory based on the meta modeling framework （M2F） of the COllaborative SIMulation （COSlM） theory of virtual prototyping to solve the problems. Firstly the fundamental prin- ciples of the top-level modeling theory are decribed to expound the premise, assumptions, basic conventions and special require- ments in the description of complex heterogeneous systems. Next the formalized definitions for each factor in top level modeling are proposed and the hierarchical nature of them is illustrated. After demonstrating that they are self-closing, this paper divides the top- level modeling into two views, static structural graph and dynamic behavioral graph. Finally, a case study is discussed to demon- strate the feasibility of the theory.

Water level updating model for flow calculation of river networks

Complex water movement and insufficient observation stations are the unfavorable factors in improving the accuracy of flow calculation of river networks. A water level updating model for river networks was set up based on a three-step method at key nodes, and model correction values were collected from gauge stations. To improve the accuracy of water level and discharge forecasts for the entire network, the discrete coefficients of the Saint-Venant equations for river sections were regarded as the media carrying the correction values from observation locations to other cross-sections of the river network system. To examine the applicability, the updating model was applied to flow calculation of an ideal river network and the Chengtong section of the Yangtze River. Comparison of the forecast results with the observed data demonstrates that this updating model can improve the forecast accuracy in both ideal and real river networks.

Development and Theoretic Validation of Model of Drum Level Sloshing

In order to develop a feasible model of drum level sloshing, the mechanism of drum level sloshing was analyzed, and the model of drum level sloshing was developed on the Easy5 software flat. The thermodynamic property of the model was validated by using the reference model, which was set up by using the method of lump parameter. The results indicate that the model can precisely reflect the phenomena of thermodynamic property inside drum, and the numeric error is within 1%. And the hydraulic property of the model was validated by the analytical theory of liquid sloshing, and the results indicate that the hydraulic property inside drum can also be correctly reflected by the model, and the sloshing period error is within 5%. The important work was done for exploring modeling for drum level sloshing, research of drum level sloshing and precision controlling of drum level.

REVIEW OF HIGH LEVEL FAULT MODELING APPROACHES FOR MIXED-SIGNAL SYSTEMS

In the modern analogue design, Transistor Level Fault Simulation (TLFS) plays the im-portant part since every fault in the whole circuit has to be simulated at that level. Unfortunately, it is a very CPU intensive task even though it maintains the high accuracy. Therefore, High Level Fault Modeling (HLFM) and High Level Fault Simulation (HLFS) are required in order to alleviate the efforts of simulation. In this paper, different HLFM approaches are reviewed at the device level during last two decades. We clarify their domains of application and evaluate their strengths and current limitations. We also analyze causes of faults and introduce various test approaches.

Quantum Spin Liquid Phase in the Shastry–Sutherland Model Detected by an Improved Level Spectroscopic Method

We study the spin-1/2 two-dimensional Shastry–Sutherland spin model by exact diagonalization of clusters with periodic boundary conditions, developing an improved level spectroscopic technique using energy gaps between states with different quantum numbers. The crossing points of some of the relative(composite) gaps have much weaker finite-size drifts than the normally used gaps defined only with respect to the ground state, thus allowing precise determination of quantum critical points even with small clusters. Our results support the picture of a spin liquid phase intervening between the well-known plaquette-singlet and antiferromagnetic ground states, with phase boundaries in almost perfect agreement with a recent density matrix renormalization group study, where much larger cylindrical lattices were used [J. Yang et al., Phys. Rev. B 105, L060409(2022)]. The method of using composite low-energy gaps to reduce scaling corrections has potentially broad applications in numerical studies of quantum critical phenomena.

Dynamic simulation of hydrodynamic model of drum level wave action and sloshing

In order to build the model of the drum level wave action and sloshing, based on the method of modularization modeling, the hydrodynamic model of drum level wave action and sloshing was developed, and dynamic simulation researches were carried out based on the model. The results indicate that both drum level and drum length have functional relations with period of drum level wave action and sloshing. When the drum level decreases or drum length increases, the period of drum level wave action and sloshing increases, density of liquid and number of sub-module division have little influence on the period of drum level wave action and sloshing. The model was validated by the analytical solution theory of liquid’s wave action and sloshing in cuboid container, and the 3D graphics of drum level wave action and sloshing was also obtained. The model can dynamically reflect the rules of wave action and sloshing of water in the container exactly.

Sea level rise projection in the South China Sea from CMIP5 models

Future potential sea level change in the South China Sea （SCS） is estimated by using 24 CMIP5 models under different representative concentration pathway （RCP） scenarios. By the end of the 21st century （2081–2100 relative to 1986–2005）, the multimodel ensemble mean dynamic sea level （DSL） is projected to rise 0.9, 1.6, and 1.1 cm under RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, resulting in a total sea level rise （SLR） of 40.9, 48.6, and 64.1 cm in the SCS. It indicates that the SCS will experience a substantial SLR over the 21st century, and the rise is only marginal larger than the global mean SLR. During the same period, the steric sea level （SSL） rise is estimated to be 6.7, 10.0, and 15.3 cm under the three scenarios, respectively, which accounts only for 16%, 21% and 24% of the total SLR in this region. The changes of the SSL in the SCS are almost out of phase with those of the DSL for the three scenarios. The central deep basin has a slightly weak DSL rise, but a strong SSL rise during the 21st century, compared with the north and southwest shelves.

Model test of the influence of cyclic water level fluctuations on a landslide

Many landslides in reservoir areas continuously deform under cyclic water level fluctuations due to reservoir operations. In this paper,a landslide model, developed for a typical colluvial landslide in the Three Gorges Reservoir area, is used to study the effect of cyclic water level fluctuations on the landslide. Five cyclic water level fluctuations were implemented in the test, and the fluctuation rate in the last two fluctuations doubled over the first three fluctuations. The pore water pressure and lateral landslide profiles were obtained during the test. A measurement of the landslide soil loss was proposed to quantitatively evaluate the influence of water level fluctuations. The test results show that the first water level rising is most negative to the landslide among the five cycles. The fourth drawdown with a higher drawdown rate caused further large landslide deformation. An increase of the water level drawdown rate is much more unfavorable to the landslide than an increase of the water level rising rate. In addition, the landslide was found to have an adaptive ability to resist subsequent water level fluctuations after undergoing large deformation during a water level fluctuation. The landslide deformation and observations in the field were found to support the test results well.

Incorporation of GIS Based Program into Hydraulic Model for Water Level Modeling on River Basin

Water resources management usually requires that hydraulic, ecological, and hydrological models be linked. The Hy- drologic Engineering Center River Analysis System (HEC-RAS) hydraulic model and the Hydrologic Engineering Center Geospatial River Analysis System (HEC-GEORAS), imitates flow and water profiles in the Neka river basin’s downstream flood plain. Hydrograph phases studied during the flood seasons of 1986-1999 and from 2002-2004 were used to calibrate and verify the hydraulic model respectively. Simulations of peak flood stages and hydrographs’ evaluations are congruent with studies and observations, with the former showing mean square errors between 4.8 - 10 cm. HECRAS calculations and forecast flood water levels. Nash-Sutcliffe effectiveness (CR3) is more than 0.92 along with elevated levels of water which were created with some effectiveness (CR5) of 0.94 for the validation period. The coupled two models show good performance in the water level modeling.

Impacts of the Lowest Model Level Height on Tropical Cyclone Intensity and Structure

Variable thicknesses in the lowest half-ηmodel level （LML） are often used in atmospheric models to compute surface diagnostic fields such as surface latent and sensible heat fluxes.The effects of the LML on simulated tropical cyclone （TC）evolution were investigated in this study using the Weather Research and Forecasting （WRF） model.The results demonstrated notable influences of the LML on TC evolution when the LML was placed below 12 m.The TC intensification rate decreased progressively with a lowering of the LML,but its ultimate intensity change was relatively small.The maximum 10-m winds showed different behavior to minimum sea level pressure and azimuthally-averaged tangential winds,and thus the windpressure relationship was changed accordingly by varying the LML.The TC circulation was more contracted in association with a higher LML.Surface latent heat fluxes were enhanced greatly by elevating the LML,wherein the wind speed at the LML played a dominant role.The changes in the wind speed at the LML were dependent not only on their profile differences,but also the different heights they were taken from.Due to the enhanced surface heat fluxes,more intense latent heat release occurred in the eyewall,which boosted the storm＇s intensification.A higher LML tended to produce a stronger storm,and therefore the surface friction was reinforced,which in turn induced stronger boundary layer inflow together with increased diabatic heating.

Assimilating the along-track sea level anomaly into the regional ocean modeling system using the ensemble optimal interpolation

The ensemble optimal interpolation （EnOI） is applied to the regional ocean modeling system （ROMS） with the ability to assimilate the along-track sea level anomaly （TSLA）. This system is tested with an eddy-resolving system of the South China Sea （SCS）. Background errors are derived from a running seasonal ensemble to account for the seasonal variability within the SCS. A fifth-order localization function with a 250 km localization radius is chosen to reduce the negative effects of sampling errors. The data assimilation system is tested from January 2004 to December 2006. The results show that the root mean square deviation （RMSD） of the sea level anomaly decreased from 10.57 to 6.70 cm, which represents a 36.6% reduction of error. The data assimilation reduces error for temperature within the upper 800 m and for salinity within the upper 200 m, although error degrades slightly at deeper depths. Surface currents are in better agreement with trajectories of surface drifters after data assimilation. The variance of sea level improves significantly in terms of both the amplitude and position of the strong and weak variance regions after assimilating TSLA. Results with AGE error （AGE） perform better than no AGE error （NoAGE） when considering the improvements of the temperature and the salinity. Furthermore, reasons for the extremely strong variability in the northern SCS in high resolution models are investigated. The results demonstrate that the strong variability of sea level in the high resolution model is caused by an extremely strong Kuroshio intrusion. Therefore, it is demonstrated that it is necessary to assimilate the TSLA in order to better simulate the SCS with high resolution models.