Spatio-temporal Data Model Based on Relational Database System

In this paper,the entity_relation data model for integrating spatio_temporal data is designed.In the design,spatio_temporal data can be effectively stored and spatiao_temporal analysis can be easily realized.

A cloud model target damage effectiveness assessment algorithm based on spatio-temporal sequence finite multilayer fragments dispersion

To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.

Large Language Model Based Semantic Parsing for Intelligent Database Query Engine

With the rapid development of artificial intelligence, large language models (LLMs) have demonstrated remarkable capabilities in natural language understanding and generation. These models have great potential to enhance database query systems, enabling more intuitive and semantic query mechanisms. Our model leverages LLM’s deep learning architecture to interpret and process natural language queries and translate them into accurate database queries. The system integrates an LLM-powered semantic parser that translates user input into structured queries that can be understood by the database management system. First, the user query is pre-processed, the text is normalized, and the ambiguity is removed. This is followed by semantic parsing, where the LLM interprets the pre-processed text and identifies key entities and relationships. This is followed by query generation, which converts the parsed information into a structured query format and tailors it to the target database schema. Finally, there is query execution and feedback, where the resulting query is executed on the database and the results are returned to the user. The system also provides feedback mechanisms to improve and optimize future query interpretations. By using advanced LLMs for model implementation and fine-tuning on diverse datasets, the experimental results show that the proposed method significantly improves the accuracy and usability of database queries, making data retrieval easy for users without specialized knowledge.

Traveling Wave Solutions of a SIR Epidemic Model with Spatio-Temporal Delay

In this paper, we studied the traveling wave solutions of a SIR epidemic model with spatial-temporal delay. We proved that this result is determined by the basic reproduction number R0and the minimum wave speed c*of the corresponding ordinary differential equations. The methods used in this paper are primarily the Schauder fixed point theorem and comparison principle. We have proved that when R0>1and c>c*, the model has a non-negative and non-trivial traveling wave solution. However, for R01and c≥0or R0>1and 0cc*, the model does not have a traveling wave solution.

Database-oriented storage based on LMDB and linear octree for massive block model

Data organization requires high efficiency for large amount of data applied in the digital mine system. A new method of storing massive data of block model is proposed to meet the characteristics of the database, including ACID-compliant, concurrency support, data sharing, and efficient access. Each block model is organized by linear octree, stored in LMDB（lightning memory-mapped database）. Geological attribute can be queried at any point of 3D space by comparison algorithm of location code and conversion algorithm from address code of geometry space to location code of storage. The performance and robustness of querying geological attribute at 3D spatial region are enhanced greatly by the transformation from 3D to 2D and the method of 2D grid scanning to screen the inner and outer points. Experimental results showed that this method can access the massive data of block model, meeting the database characteristics. The method with LMDB is at least 3 times faster than that with etree, especially when it is used to read. In addition, the larger the amount of data is processed, the more efficient the method would be.

DATA MODEL AND VISUALIZATION OF 3D CITY LANDSCAPE BASED ON INTEGRATED DATABASES

Data acquisition and modeling are the two important, difficult and costful aspects in a Cybercity project. 2D-GIS is mature and can manage a lot of spatial data. Thus 3D-GIS should make the best of data and technology of 2D-GIS. Construction of a useful synthetic environment requires integration of multiple types of information like DEM, texture images and 3D representation of objects such as buildings. In this paper, the method for 3D city landscape data model and visualization based on integrated databases is presented. Since the data volume of raster are very huge, special strategies(for example, pyramid gridded method) must be adopted in order to manage raster data efficiently. Three different methods of data acquisition, the proper data structure and a simple modeling method are presented as well. At last, a pilot project of Shanghai Cybercity is illustrated.

Thermodynamic modeling of the La-Mg-Y system and Mg-based alloys database

As an example of the La-Mg-Y system, the method how to set up the themaodynamic model of individual phases was introduced in the process of thermodynamic optimization. The solution phases （liquid, body-centered cubic, face-centered cubic, hexagonal close-packed and double hexagonal close-packed） were modeled with the Redlich-Kister equation. The compound energy model has been used to describe the thermodynamic functions of the intermetallic compounds in the La-Mg-Y systems. The compounds Mg2Y, Mg24Y5, Mg12La, Mg17La2, Mg41Las, Mg3La and Mg2La in the La-Mg-Y system were treated as the formulae （Mg,Y）2（La,Mg,Y）, Mg24（La,Mg,Y）4Y, Mg12（La, Y）, Mg17（La,Y）2, Mg41（La,Y）5, Mg3（La,Mg,Y） and Mg2（La, Y）, respectively. A model （La, Mg,Y）0.5（La,Mg,Y）0.5 was applied to describe the compound MgM formed by MgLa and MgY in order to cope with the order-disorder transition between body-centered cubic solution （A2） and MgM with CsCl-type structure （B2） in the La-Mg-Y system. The Gibbs energies of individual phases were optimized in the La-Mg, La-Y and La-Mg-Y systems by CALPHAD technique. The projection of the liquidus surfaces for the La-Mg-Y system was predicted. The Mg-based alloys database including 36 binary and 15 ternary systems formed by Mg, Al, Cu, Ni, Mn, Zn and rare earth elements was set up in SGTE standard.

Constructing a raster-based spatio-temporal hierarchical data model for marine fisheries application

Marine information has been increasing quickly. The traditional database technologies have disadvantages in manipulating large amounts of marine information which relates to the position in 3-D with the time. Recently, greater emphasis has been placed on GIS （geographical information system）to deal with the marine information. The GIS has shown great success for terrestrial applications in the last decades, but its use in marine fields has been far more restricted. One of the main reasons is that most of the GIS systems or their data models are designed for land applications. They cannot do well with the nature of the marine environment and for the marine information. And this becomes a fundamental challenge to the traditional GIS and its data structure. This work designed a data model, the raster-based spatio-temporal hierarchical data model （RSHDM）, for the marine information system, or for the knowledge discovery fi＇om spatio-temporal data, which bases itself on the nature of the marine data and overcomes the shortages of the current spatio-temporal models when they are used in the field. As an experiment, the marine fishery data warehouse （FDW） for marine fishery management was set up, which was based on the RSHDM. The experiment proved that the RSHDM can do well with the data and can extract easily the aggregations that the management needs at different levels.

A Spatio-temporal Data Model for Road Network in Data Center Based on Incremental Updating in Vehicle Navigation System

The technique of incremental updating,which can better guarantee the real-time situation of navigational map,is the developing orientation of navigational road network updating.The data center of vehicle navigation system is in charge of storing incremental data,and the spatio-temporal data model for storing incremental data does affect the efficiency of the response of the data center to the requirements of incremental data from the vehicle terminal.According to the analysis on the shortcomings of several typical spatio-temporal data models used in the data center and based on the base map with overlay model,the reverse map with overlay model (RMOM) was put forward for the data center to make rapid response to incremental data request.RMOM supports the data center to store not only the current complete road network data,but also the overlays of incremental data from the time when each road network changed to the current moment.Moreover,the storage mechanism and index structure of the incremental data were designed,and the implementation algorithm of RMOM was developed.Taking navigational road network in Guangzhou City as an example,the simulation test was conducted to validate the efficiency of RMOM.Results show that the navigation database in the data center can response to the requirements of incremental data by only one query with RMOM,and costs less time.Compared with the base map with overlay model,the data center does not need to temporarily overlay incremental data with RMOM,so time-consuming of response is significantly reduced.RMOM greatly improves the efficiency of response and provides strong support for the real-time situation of navigational road network.

A reference model for database security proxy

How to protect the database, the kernel resources of information warfare, is becoming more and more important since the rapid development of computer and communication technology. As an application-level firewall, database security proxy can successfully repulse attacks originated from outside the network, reduce to zerolevel damage from foreign DBMS products. We enhanced the capability of the COAST' s firewall reference model by adding a transmission unit modification function and an attribute value mapping function,describes the schematic and semantic layer reference model, and finally forms a reference model for DBMS security proxy which greatly helps in the design and implementation of database security proxies. This modeling process can clearly separate the system functionality into three layers, define the possible security functions for each layer, and estimate the computational cost for each layer.

Divide and recombine approach for warranty database: estimating the reliability of an automobile component

The continuously updated database of failures and censored data of numerous products has become large, and on some covariates, information regarding the failure times is missing in the database. As the dataset is large and has missing information, the analysis tasks become complicated and a long time is required to execute the programming codes. In such situations, the divide and recombine (D&R) approach, which has a practical computational performance for big data analysis, can be applied. In this study, the D&R approach was applied to analyze the real field data of an automobile component with incomplete information on covariates using the Weibull regression model. Model parameters were estimated using the expectation maximization algorithm. The results of the data analysis and simulation demonstrated that the D&R approach is applicable for analyzing such datasets. Further, the percentiles and reliability functions of the distribution under different covariate conditions were estimated to evaluate the component performance of these covariates. The findings of this study have managerial implications regarding design decisions, safety, and reliability of automobile components.

DATA MODEL FOR MULTIMEDIA DATABASE SYSTEM NHMDB BASED ON NF^2 DATA MODEL

An approach to implementing the multimedia database system NHMDB based on NF2(Non-First-Normal-Form) data model is presented. This approach is easily implemented because NF2 structure can efficiently store various media data such as formatted data, text,graphics, image and voice. The main idea is to expand conceptual schema to maintain the consistency of tbreelevel schema in system NHMDB. We developed, implemented and experimented the storage structure and the multimedia data representation by an object identifier.implementation techniques are also discussed.

Spatio-temporal Changes and Associated Uncertainties of CENTURYmodelled SOC for Chinese Upland Soils, 1980-2010

Detailed information on the spatio-temporal changes of cropland soil organic carbon(SOC) can significantly contribute to the improvement of soil fertility and mitigate climate change. Nonetheless, information and knowledge on the national scale spatio-temporal changes and the corresponding uncertainties of SOC in Chinese upland soils remain limited. The CENTURY model was used to estimate the SOC storages and their changes in Chinese uplands from 1980 to 2010. With the Monte Carlo method, the uncertainties of CENTURY-modelled SOC dynamics associated with the spatial heterogeneous model inputs were quantified. Results revealed that the SOC storage in Chinese uplands increased from 3.03(1.59 to 4.78) Pg C in 1980 to 3.40(2.39 to 4.62) Pg C in 2010. Increment of SOC storage during this period was 370 Tg C, with an uncertainty interval of –440 to 1110 Tg C. The regional disparities of SOC changes reached a significant level, with considerable SOC accumulation in the Huang-Huai-Hai Plain of China and SOC loss in the northeastern China. The SOC lost from Meadow soils, Black soils and Chernozems was most severe, whilst SOC accumulation in Fluvo-aquic soils, Cinnamon soils and Purplish soils was most significant. In modelling large-scale SOC dynamics, the initial soil properties were major sources of uncertainty. Hence, more detailed information concerning the soil properties must be collected. The SOC stock of Chinese uplands in 2010 was still relatively low, manifesting that recommended agricultural management practices in conjunction with effectively economic and policy incentives to farmers for soil fertility improvement were indispensable for future carbon sequestration in these regions.

Spatio-temporal model for soil characteristic of reclamation land

The development of spatio-temporal data model is introduced. According to the soil characteristic of reclamation land, we adopt the base state with amendments model of multi-layer raster to organize the spatio-temporal data, using the combined data structure on linear quadtree and linear octree to code. The advantage of this model is that it can easily obtain the information of certain layer and integratedly analyze the data with other methods. Then, the methods of obtain and analyses are introduced. The method can provide a tool for the research of the soil characteristic change and spatial distribution in reclamation land.

Design of Conceptual Model in Digital Map Database

The components of map information are analyzed theoretically in this paper,and the map information includes mainly the spatial information,attributive information and temporal characteristics information.Then the digital map entity is defined according to construction characteristics of the map information.Finally,on the basis of the analyses of the construction characteristics of digital map entity and present conceptual model of digital map database,an abstracted conceptual model of digital map database is presented.And the Normal Form theory of relational database is discussed particularly.

Spatio-Temporal Dynamics and Structure Preserving Algorithm for Computer Virus Model

The present work is related to the numerical investigation of the spatio-temporal susceptible-latent-breaking out-recovered(SLBR)epidemic model.It describes the computer virus dynamics with vertical transmission via the internet.In these types of dynamics models,the absolute values of the state variables are the fundamental requirement that must be fulfilled by the numerical design.By taking into account this key property,the positivity preserving algorithm is designed to solve the underlying SLBR system.Since,the state variables associated with the phenomenon,represent the computer nodes,so they must take in absolute.Moreover,the continuous system(SLBR)acquires two steady states i.e.,the virus-free state and the virus existence state.The stability of the numerical design,at the equilibrium points,portrays an exceptional aspect about the propagation of the virus.The designed discretization algorithm sustains the stability of both the steady states.The computer simulations also endorse that the proposed discretization algorithm retains all the traits of the continuous SLBR model with spatial content.The stability and consistency of the proposed algorithm are verified,mathematically.All the facts are also ascertained by numerical simulations.

OMT-G Modeling and Cloud Implementation of a Reference Database of Addressing in Morocco

A reference database of addressing is an important resource for urban applications. The efficiency of an addressing system depends on both data quality and technical architecture. Data must respect a standard model that is flexible to meet different cases in the field. The technical architecture should be service oriented to offer a shared resource for multiple users and applications. This paper is to develop an addressing model for Morocco that extends Davis’s and Fonseca’s model presented in their work on the certainty of locations produced by an address geocoding system. We discuss the addressing data dictionary and acquisition plan in Morocco, revealing a diversified data management environment, characterized by multiple sources and actors. As a novelty in the field of GIS, we establish our technical architecture around cloud computing, according Service Oriented Application (SOA) standards. Our approach is based on the three pillars of cloud computing which are Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a service (IaaS).

Grain Yield Prediction of Henan Province Based on Spatio-temporal Regression Model

By using correlation analysis method,regression analysis method and time sequence method,we combine time and space,to establish grain yield spatio-temporal regression prediction model of Henan Province and all prefecture-level cities.At first,we use the grain yield in prefecture-level cities of Henan in the year 2000 and 2005,to establish regression model,and then taking the grain yield in one year as independent variable,we predict the grain yield in the fifth year afterwards.Taking the dependent variable value as independent variable again,we predict the grain yield at an interval of the same years,and based on this,predict year by year forward until the year we need.The research shows that the grain yield of Henan Province in the year 2015 and 2020 is 59.849 6 and 67.929 3 million t respectively,consistent with the research results of other scholars to some extent.

Spatio-temporal epidemic type aftershock sequence model for Tangshan aftershock sequence

Shallow earthquakes usually show obvious spatio-temporal clustering patterns. In this study, several spatio-temporal point process models are applied to investigate the clustering characteristics of the well-known Tangshan sequence based on classical empirical laws and a few assumptions. The relative fit of competing models is compared by Akalke Information Criterion. The spatial clustering pattern is well characterized by the model which gives the best fit to the data. A simulated aftershock sequence is generated by thinning algorithm and compared with the real seismicity.

Power Information System Database Cache Model Based on Deep Machine Learning

At present,the database cache model of power information system has problems such as slow running speed and low database hit rate.To this end,this paper proposes a database cache model for power information systems based on deep machine learning.The caching model includes program caching,Structured Query Language(SQL)preprocessing,and core caching modules.Among them,the method to improve the efficiency of the statement is to adjust operations such as multi-table joins and replacement keywords in the SQL optimizer.Build predictive models using boosted regression trees in the core caching module.Generate a series of regression tree models using machine learning algorithms.Analyze the resource occupancy rate in the power information system to dynamically adjust the voting selection of the regression tree.At the same time,the voting threshold of the prediction model is dynamically adjusted.By analogy,the cache model is re-initialized.The experimental results show that the model has a good cache hit rate and cache efficiency,and can improve the data cache performance of the power information system.It has a high hit rate and short delay time,and always maintains a good hit rate even under different computer memory;at the same time,it only occupies less space and less CPU during actual operation,which is beneficial to power The information system operates efficiently and quickly.