Parameter-driven Level of Detail Derivation Method for Semantic Building Facade Model

The relentless progress in the research of geographic spatial data models and their application scenarios is propelling an unprecedented rich Level of Detail(LoD)in realistic 3D representation and smart cities.This pursuit of rich details not only adds complexity to entity models but also poses significant computational challenges for model visualization and 3D GIS.This paper introduces a novel method for deriving multi-LOD models,which can enhance the efficiency of spatial computing in complex 3D building models.Firstly,we extract multiple facades from a 3D building model(LoD3)and convert them into individual semantic facade models.Through the utilization of the developed facade layout graph,each semantic facade model is then transformed into a parametric model.Furthermore,we explore the specification of geometric and semantic details in building facades and define three different LODs for facades,offering a unique expression.Finally,an innovative heuristic method is introduced to simplify the parameterized facade.Through rigorous experimentation and evaluation,the effectiveness of the proposed parameterization methodology in capturing complex geometric details,semantic richness,and topological relationships of 3D building models is demonstrated.

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.

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.

A method to calculate design tide levels on the basis of numerical model of tidal current and its application

In order to determine the design tide levels in the areas without measured tide level data, especially in the areas where it is difficult to measure tidal levels, a calculation method based on a numerical model of tidal current is proposed. The essentials of the method are described, and its application is illustrated with an example. The results of the application show that the design tide levels calculated by the method are close to those determined by long-time measured tide level data, and its calculation precision is high, so it is feasible to use the method to determine the design tide levels in the areas.

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.

Steric Sea Level Change in Twentieth Century Historical Climate Simulation and IPCC-RCP8.5 Scenario Projection: A Comparison of Two Versions of FGOALS Model

To reveal the steric sea level change in 20th century historical climate simulations and future climate change projections under the IPCC＇s Representative Concentration Pathway 8.5 （RCP8.5） scenario, the results of two versions of LASG/IAP＇s Flexible Global Ocean-Atmosphere-Land System model （FGOALS） are analyzed. Both models reasonably reproduce the mean dynamic sea level features, with a spatial pattern correlation coefficient of 0.97 with the observation. Characteristics of steric sea level changes in the 20th century historical climate simulations and RCPS.5 scenario projections are investigated. The results show that, in the 20th century, negative trends covered most parts of the global ocean. Under the RCPS.5 scenario, global-averaged steric sea level exhibits a pronounced rising trend throughout the 21st century and the general rising trend appears in most parts of the global ocean. The magnitude of the changes in the 21st century is much larger than that in the 20th century. By the year 2100, the global-averaged steric sea level anomaly is 18 cm and 10 cm relative to the year 1850 in the second spectral version of FGOALS （FGOALS-s2） and the second grid-point version of FGOALS （FGOALS-g2）, respectively. The separate contribution of the thermosteric and halosteric components from various ocean layers is further evaluated. In the 20th century, the steric sea level changes in FGOALS-s2 （FGOALS-g2） are largely attributed to the thermosteric （halosteric） component relative to the pre-industrial control run. In contrast, in the 21st century, the thermosteric component, mainly from the upper 1000 m, dominates the steric sea level change in both models under the RCPS.5 scenario. In addition, the steric sea level change in the marginal sea of China is attributed to the thermosteric component.

The Application of a Grey Markov Model to Forecasting Annual Maximum Water Levels at Hydrological Stations

Compared with traditional real-time forecasting,this paper proposes a Grey Markov Model(GMM) to forecast the maximum water levels at hydrological stations in the estuary area.The GMM combines the Grey System and Markov theory into a higher precision model.The GMM takes advantage of the Grey System to predict the trend values and uses the Markov theory to forecast fluctuation values,and thus gives forecast results involving two aspects of information.The procedure for forecasting annul maximum water levels with the GMM contains five main steps:1) establish the GM(1,1) model based on the data series;2) estimate the trend values;3) establish a Markov Model based on relative error series;4) modify the relative errors caused in step 2,and then obtain the relative errors of the second order estimation;5) compare the results with measured data and estimate the accuracy.The historical water level records(from 1960 to 1992) at Yuqiao Hydrological Station in the estuary area of the Haihe River near Tianjin,China are utilized to calibrate and verify the proposed model according to the above steps.Every 25 years' data are regarded as a hydro-sequence.Eight groups of simulated results show reasonable agreement between the predicted values and the measured data.The GMM is also applied to the 10 other hydrological stations in the same estuary.The forecast results for all of the hydrological stations are good or acceptable.The feasibility and effectiveness of this new forecasting model have been proved in this paper.

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.

Assessment of prediction performances of stochastic models:Monthly groundwater level prediction in Southern Italy

Stochastic modelling of hydrological time series with insufficient length and data gaps is a serious challenge since these problems significantly affect the reliability of statistical models predicting and forecasting skills.In this paper,we proposed a method for searching the seasonal autoregressive integrated moving average(SARIMA)model parameters to predict the behavior of groundwater time series affected by the issues mentioned.Based on the analysis of statistical indices,8 stations among 44 available within the Campania region(Italy)have been selected as the highest quality measurements.Different SARIMA models,with different autoregressive,moving average and differentiation orders had been used.By reviewing the criteria used to determine the consistency and goodness-of-fit of the model,it is revealed that the model with specific combination of parameters,SARIMA(0,1,3)(0,1,2)_(12),has a high R^(2) value,larger than 92%,for each of the 8 selected stations.The same model has also good performances for what concern the forecasting skills,with an average NSE of about 96%.Therefore,this study has the potential to provide a new horizon for the simulation and reconstruction of groundwater time series within the investigated area.

Spatio-temporal variation of depth to groundwater level and its driving factors in arid and semi-arid regions of India

Climate change and increasing anthropogenic activities,such as over-exploitation of groundwater,are exerting unavoidable stress on groundwater resources.This study investigated the spatio-temporal variation of depth to groundwater level(DGWL)and the impacts of climatic(precipitation,maximum temperature,and minimum temperature)and anthropogenic(gross district product(GDP),population,and net irrigated area(NIA))variables on DGWL during 1994-2020.The study considered DGWL in 113 observation wells and piezometers located in arid western plains(Barmer and Jodhpur districts)and semi-arid eastern plains(Jaipur,Ajmer,Dausa,and Tonk districts)of Rajasthan State,India.Statistical methods were employed to examine the annual and seasonal patterns of DGWL,and the generalized additive model(GAM)was used to determine the impacts of climatic and anthropogenic variables on DGWL.During 1994-2020,except for Barmer District,where the mean annual DGWL was almost constant(around 26.50 m),all other districts exhibited increase in DGWL,with Ajmer District experiencing the most increase.The results also revealed that 36 observation wells and piezometers showed a statistically significant annual increasing trend in DGWL and 34 observation wells and piezometers exhibited a statistically significant decreasing trend in DGWL.Similarly,32 observation wells and piezometers showed an statistically significant increasing trend and 37 observation wells and piezometers showed a statistically significant decreasing trend in winter;33 observation wells and piezometers indicated a statistically significant increasing trend and 34 had a statistically significant decreasing trend in post-monsoon;35 observation wells and piezometers exhibited a statistically significant increasing trend and 32 observation wells and piezometers showed a statistically significant decreasing trend in pre-monsoon;and 36 observation wells and piezometers reflected a statistically significant increasing trend and 30 observation wells and piezometers reflected a statistically significant decreasing trend in monsoon.Interestingly,most of the observation wells and piezometers with increasing trends of DGWL were located in Dausa and Jaipur districts.Furthermore,the GAM analysis revealed that climatic variables,such as precipitation,significantly affected DGWL in Barmer District,and DGWL in all other districts was influenced by anthropogenic variables,including GDP,NIA,and population.As a result,stringent regulations should be implemented to curb excessive groundwater extraction,manage agricultural water demand,initiate proactive aquifer recharge programs,and strengthen sustainable management in these water-scarce regions.

Modeling the Pressure Distribution and the Changes of Water Level around the Offshore Platforms Exposed to Waves, Using the Numerical Model of Flow 3D

The humans’ need to use the oceans for exploration and extraction of oil has led to the development of engineering science in the field of offshore structures. Since it’s important to examine the offshore structures from different aspects and perspectives, we would have to evaluate many different parameters about them. So categorizing these parameters can help to perform their related analysis with more accuracy and more details. Due to the efficient force it exerts on the structure, the pressure distribution around every marine or hydraulic structure has a significant importance, and it even accounts for one of the dominant issues in designing and building of such structures. In the present study, an oil platform located in Phase 15 of South Pars oil fields, located in the Persian Gulf waters, has been analyzed using the FLOW 3D software. The outputs indicate that the pressure of water is distributed almost hydrostatically with the depth, and its maximum reaches 0.6 MPa at the bottom.

Application of Exponential Distribution in Modeling of State Holding Time in HIV/AIDS Transition Dynamics

Markov modeling of HIV/AIDS progression was done under the assumption that the state holding time (waiting time) had a constant hazard. This paper discusses the properties of the hazard function of the Exponential distributions and its modifications namely;Parameter proportion hazard (PH) and Accelerated failure time models (AFT) and their effectiveness in modeling the state holding time in Markov modeling of HIV/AIDS progression with and without risk factors. Patients were categorized by gender and age with female gender being the baseline. Data simulated using R software was fitted to each model, and the model parameters were estimated. The estimated P and Z values were then used to test the null hypothesis that the state waiting time data followed an Exponential distribution. Model identification criteria;Akaike information criteria (AIC), Bayesian information criteria (BIC), log-likelihood (LL), and R2 were used to evaluate the performance of the models. For the Survival Regression model, P and Z values supported the non-rejection of the null hypothesis for mixed gender without interaction and supported the rejection of the same for mixed gender with interaction term and males aged 50 - 60 years. Both Parameters supported the non-rejection of the null hypothesis in the rest of the age groups. For Gender male with interaction both P and Z values supported rejection in all the age groups except the age group 20 - 30 years. For Cox Proportional hazard and AFT models, both P and Z values supported the non-rejection of the null hypothesis across all age groups. The P-values for the three models supported different decisions for and against the Null hypothesis with AFT and Cox values supporting similar decisions in most of the age groups. Among the models considered, the regression assumption provided a superior fit based on (AIC), (BIC), (LL), and R2 Model identification criteria. This was particularly evident in age and gender subgroups where the data exhibited non-proportional hazards and violated the assumptions required for the Cox Proportional Hazard model. Moreover, the simplicity of the regression model, along with its ability to capture essential state transitions without over fitting, made it a more appropriate choice.

The Research of the Equation Model on the System-level Fault Diagnosis

In this paper we propose an equation model of system-level fault diagnoses, and construct corresponding theory and algorithms. People can turn any PMC model on ex-test into an equivalent equation (or a system of equations), and find all consistent fault patterns based on the equation model. We can also find all fault patterns, in which the fault node numbers are less than or equal to t without supposing t-diagnosable. It is not impossible for all graphic models.

Occlusion Culling Algorithm Using Prefetching and Adaptive Level of Detail Technique

A novel approach that integrates occlusion culling within the view-dependent rendering framework is proposed. The algorithm uses the prioritized-layered projection（PLP） algorithm to occlude those obscured objects, and uses an approximate visibility technique to accurately and efficiently determine which objects will be visible in the coming future and prefetch those objects from disk before they are rendered, view-dependent rendering technique provides the ability to change level of detail over the surface seamlessly and smoothly in real-time according to cell solidity value.

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.

Prediction of Ground Water Level in Arid Environment Using a Non-Deterministic Model

Modeling and forecasting of the groundwater water table are a major component of effective planning and management of water resources. One way to predict the groundwater level is analysis using a non-deterministic model. This study assessed the performance of such models in predicting the groundwater level at Kashan aquifer. Data from 36 piezometer wells in Kashan aquifer for 1999 to 2010 were used. The desired statistical interval was divided into two parts and statistics for 1990 to 2004 were used for modeling and statistics from 2005 to 2010 were used for valediction of the model. The Akaike criterion and correlation coefficients were used to determine the accuracy of the prediction models. The results indicated that the AR(2) model more accurately predicted ground water level in the plains;using this model, the groundwater water table was predicted for up to 60 mo.

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.