Contribution of the MERISE-Type Conceptual Data Model to the Construction of Monitoring and Evaluation Indicators of the Effectiveness of Training in Relation to the Needs of the Labor Market in the Republic of Congo

This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for structuring and analyzing data is underlined, as it enables the measurement of the adequacy between training and the needs of the labor market. The innovation of the study lies in the adaptation of the MERISE model to the local context, the development of innovative indicators, and the integration of a participatory approach including all relevant stakeholders. Contextual adaptation and local innovation: The study suggests adapting MERISE to the specific context of the Republic of Congo, considering the local particularities of the labor market. Development of innovative indicators and new measurement tools: It proposes creating indicators to assess skills matching and employer satisfaction, which are crucial for evaluating the effectiveness of vocational training. Participatory approach and inclusion of stakeholders: The study emphasizes actively involving training centers, employers, and recruitment agencies in the evaluation process. This participatory approach ensures that the perspectives of all stakeholders are considered, leading to more relevant and practical outcomes. Using the MERISE model allows for: • Rigorous data structuring, organization, and standardization: Clearly defining entities and relationships facilitates data organization and standardization, crucial for effective data analysis. • Facilitation of monitoring, analysis, and relevant indicators: Developing both quantitative and qualitative indicators helps measure the effectiveness of training in relation to the labor market, allowing for a comprehensive evaluation. • Improved communication and common language: By providing a common language for different stakeholders, MERISE enhances communication and collaboration, ensuring that all parties have a shared understanding. The study’s approach and contribution to existing research lie in: • Structured theoretical and practical framework and holistic approach: The study offers a structured framework for data collection and analysis, covering both quantitative and qualitative aspects, thus providing a comprehensive view of the training system. • Reproducible methodology and international comparison: The proposed methodology can be replicated in other contexts, facilitating international comparison and the adoption of best practices. • Extension of knowledge and new perspective: By integrating a participatory approach and developing indicators adapted to local needs, the study extends existing research and offers new perspectives on vocational training evaluation.

OBJECT ORIENTED DATA MODELLING WITH APPLICATIONS TO CAD

An object oriented data modelling in computer aided design (CAD) databases is focused. Starting with the discussion of data modelling requirements for CAD applications, appropriate data modelling features are introduced herewith. A feasible approach to select the “best” data model for an application is to analyze the data which has to be stored in the database. A data model is appropriate for modelling a given task if the information of the application environment can be easily mapped to the data model. Thus, the involved data are analyzed and then object oriented data model appropriate for CAD applications are derived. Based on the reviewed object oriented techniques applied in CAD, object oriented data modelling in CAD is addressed in details. At last 3D geometrical data models and implementation of their data model using the object oriented method are presented.

GPS probe map matching algorithm based on spatial data model

To improve the performance of the traditional map matching algorithms in freeway traffic state monitoring systems using the low logging frequency GPS （global positioning system） probe data, a map matching algorithm based on the Oracle spatial data model is proposed. The algorithm uses the Oracle road network data model to analyze the spatial relationships between massive GPS positioning points and freeway networks, builds an N-shortest path algorithm to find reasonable candidate routes between GPS positioning points efficiently, and uses the fuzzy logic inference system to determine the final matched traveling route. According to the implementation with field data from Los Angeles, the computation speed of the algorithm is about 135 GPS positioning points per second and the accuracy is 98.9%. The results demonstrate the effectiveness and accuracy of the proposed algorithm for mapping massive GPS positioning data onto freeway networks with complex geometric characteristics.

STUDY AND IMPROVEMENT OF MLS RELATIONAL DATA MODEL

The conception of multilevel security (MLS) is commonly used in the study of data model for secure database. But there are some limitations in the basic MLS model, such as inference channels. The availability and data integrity of the system are seriously constrained by it′s 'No Read Up, No Write Down' property in the basic MLS model. In order to eliminate the covert channels, the polyinstantiation and the cover story are used in the new data model. The read and write rules have been redefined for improving the agility and usability of the system based on the MLS model. All the methods in the improved data model make the system more secure, agile and usable.

Research on Multidimensional Data Model in Data Warehouse

Data structure and semantics of the traditional data model cannot effectively represent the data warehouse, it is difficult to effectively support online analytical processing （referred to as OLAP）. This paper is propose a new multidimensional data model based on the partial ordering and mapping. The data model can fully express the complex data structure and semantics of data warehouse, and provide an OLAP operation as the core of the operation of algebra, support structure in levels of complex aggregation operation sequence, which can effectively support the application of OLAE The data model supports the concept of aggregation function constraint, and provides constraint mechanism of the hierarchy aggregation function.

A Trajectory-Oriented Carriageway-Based Road Network Data Model, Part 1: Background

This is the first of a three-part series of pape rs which introduces a general background of building trajectory-oriented road net work data models, including motivation, related works, and basic concepts. The p urpose of the series is to develop a trajectory-oriented road network data mode l, namely carriageway-based road network data model (CRNM). Part 1 deals with t he modeling background. Part 2 proposes the principle and architecture of the CR NM. Part 3 investigates the implementation of the CRNM in a case study. In the p resent paper, the challenges of managing trajectory data are discussed. Then, de veloping trajectory-oriented road network data models is proposed as a solution and existing road network data models are reviewed. Basic representation approa ches of a road network are introduced as well as its constitution.

A Trajectory-Oriented, Carriageway-Based Road Network Data Model,Part 2:Methodology

This is the second of a three-part series of papers which presents the principle and architecture of the CRNM, a trajectory-oriented, carriageway-based road network data model. The first part of the series has introduced a general background of building trajectory-oriented road network data models, including motivation, related works, and basic concepts. Based on it, this paper describs the CRNM in detail. At first, the notion of basic roadway entity is proposed and discussed. Secondly, carriageway is selected as the basic roadway entity after compared with other kinds of roadway, and approaches to representing other roadways with carriageways are introduced. At last, an overall architecture of the CRNM is proposed.

A Trajectory-Oriented Carriageway-Based Road Network Data Model, Part 3: Implementation

This is the final of a three-part series of papers which mainly discusses the implementation issues of the CRNM. The first two papers in the series have introduced the modeling background and methodology, respectively. An overall architecture of the CRNM has been proposed in the last paper. On the basis of the above discusses, a linear reference method (LRM) for providing spatial references for location points of a trajectory is developed. A case study is introduced to illustrate the application of the CRNM for modeling a road network in the real world is given. A comprehensive conclusion is given for the series of papers.

XML-based integration data model and schema mappingin multidatabase systems

Multidatabase systems are designed to achieve schema integration and data interoperation among distributed and heterogeneous database systems. But data model heterogeneity and schema heterogeneity make this a challenging task. A multidatabase common data model is firstly introduced based on XML, named XML-based Integration Data Model (XIDM), which is suitable for integrating different types of schemas. Then an approach of schema mappings based on XIDM in multidatabase systems has been presented. The mappings include global mappings, dealing with horizontal and vertical partitioning between global schemas and export schemas, and local mappings, processing the transformation between export schemas and local schemas. Finally, the illustration and implementation of schema mappings in a multidatabase prototype - Panorama system are also discussed. The implementation results demonstrate that the XIDM is an efficient model for managing multiple heterogeneous data sources and the approaches of schema mapping based on XIDM behave very well when integrating relational, object-oriented database systems and other file systems.

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.

Research and application on integration modeling of 3D bodies in coal mine with blended data model based on TIN and ARTP

Data modeling is the foundation of three-dimensional visualization technology. First the paper proposed the 3D integrated data model of stratum, laneway and drill on the basic of TIN and ARTP, and designed the relevant conceptual and logical model from the view of data model, and described the data structure of geometric elements of the model by adopting the object-oriented modeling idea. And then studied the key modeling technology of stratum, laneway and drill, introduced the ARTP modeling process of stratum, laneway and drill and studied the 3D geometric modeling process of different section laneways. At last, the paper realized the three-dimensional visualization system professionally coalmine-oriented, using SQL Server as background database, Visual C＋＋6.0 and OpenGL as foreground development tools.

Component-based Topological Data Model for Three-dimensional Geology Modeling

On the study of the basic characteristics of geological objects and the special requirement for computing 3D geological model, this paper gives an object-oriented 3D topologic data model. In this model, the geological objects are divided into four object classes: point, line, area and volume. The volume class is further divided into four subclasses: the composite volume, the complex volume, the simple volume and the component. Twelve kinds of topological relations and the related data structures are designed for the geological objects.

KING GEORGE ISLAND SPATIAL DATA MODEL

Distribution,interoperability,interactivity,component are four main features of distributed GIS.Based on the principle of hypermap,hypermedia and distributed database,the paper comes up with a kind of distributed spatial data model which is in accordance with those features of distributed GIS.The model takes catalog service as the outline of spatial information globalization,and defines data structure of hypermap node in different level.Based on the model,it is feasible to manage and process distributed spatial information,and integrate multi_source,heterogeneous spatial data into a framework.Traditionally,to retrieve and access spatial data via Internet is only by theme or map name.With the concept of the model,it is possible to retrieve,load,and link spatial data by vector_based graphics on the Internet.

DEVELOPMENT OF A GIS DATA MODEL WITH SPATIAL,TEMPORAL AND ATTRIBUTE COMPONENTS BASED ON OBJECT-ORIENTED APPROACH

This paper presents a conceptual data model, the STA-model, for handling spatial, temporal and attribute aspects of objects in GIS. The model is developed on the basis of object-oriented modeling approach. This model includes two major parts: (a) modeling the signal objects by STA-object elements, and (b) modeling relationships between STA-objects. As an example, the STA-model is applied for modeling land cover change data with spatial, temporal and attribute components.

QTPV Data Model and Algorithm and Its Application to Geological Exploration Engineering

3D spatial data model and simulating are the core of 3D GIS can be adopted indifferent domains. A data model based on Quasi Tri-Prism Volume (QTPV) has been proposed. QTPVdefinition and its special cases have been discussed. Using QTPV and its special cases, irregularnatural geological bodies and regular subsurface engineering can be described efficiently. Theproposed model is composed of five primitives and six objects. Data structures and topologicalrelationship of the fives primitives and three objects describing stratigraphy are designed indetail. Some schemes are designed for the QTPV modelling of stratigraphy and subsurface engineeringaccording to modelling data. The model manipulation method of QTPV cutting by an arbitrary plane isdiscussed. Using VC^(++)6. 0 programming language integrated with SQL database and OpenGL graphiclibrary under windows environment, a system prototype 3DGeoMV has been developed. The experimentresult shows that the QTPV model is feasible and efficient in modelling subsurface engineering.

Data Model Transformation in CAD System for Multi View Modeling

This paper describes multi view modeling and data model transformation for the modeling. We have proposed a reference model of CAD system generation, which can be applied to various domain specific languages. However, the current CAD system generation cannot integrate data of multiple domains. Generally each domain has its own view of products. For example, in the domain of architectural structure, designers extract the necessary data from the data in architecture design. Domain experts translate one view into another view beyond domains using their own brains.The multi view modeling is a way to integrate product data of multiple domains, and make it possible to translate views among various domains by computers.

Panel data models with cross-sectional dependence: a selective review

In this review, we highlight some recent methodological and theoretical develop- ments in estimation and testing of large panel data models with cross-sectional dependence. The paper begins with a discussion of issues of cross-sectional dependence, and introduces the concepts of weak and strong cross-sectional dependence. Then, the main attention is primarily paid to spatial and factor approaches for modeling cross-sectional dependence for both linear and nonlinear （nonparametric and semiparametric） panel data models. Finally, we conclude with some speculations on future research directions.

Longwall face roof disaster prediction algorithm based on data model driving

Hydraulic support is the primary equipment used for surrounding rock control at fully mechanized mining faces.The load,location,and attitude of the hydraulic support are important sets of basis data to predict roof disasters.This paper summarized and analyzed the status of coal mine safety accidents and the primary influencing factors of roof disasters.This work also proposed monitoring characteristic parameters of roof disasters based on support posture-load changes,such as the support location and support posture.The data feature decomposition method of the additive model was used with the monitoring load data of the hydraulic support in the Yanghuopan coal mine to effectively extract the trend,cycle period,and residuals,which provided the period weighting characteristics of the longwall face.The autoregressive,long-short term memory,and support vector regression algorithms were used to model and analyze the monitoring data to realize single-point predictions.The seasonal autoregressive integrated moving average(SARIMA)and autoregressive integrated moving average(ARIMA)models were adopted to predict the support cycle load of the hydraulic support.The SARIMA model is shown to be better than the ARIMA model for load predictions in one support cycle,but the prediction effect of these two algorithms over a fracture cycle is poor.Therefore,we proposed a hydraulic support load prediction method based on multiple data cutting and a hydraulic support load template library.The constructed technical framework of the roof disaster intelligent prediction platform is based on this method to perform predictions and early warnings of roof disasters based on the load and posture monitoring information from the hydraulic support.

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.

Sampled-data modeling and dynamical effect of output-capacitor time-constant for valley voltage-mode controlled buck-boost converter

By analyzing the output voltage ripple of a buck-boost converter with large equivalent series resistance（ESR） of output capacitor, one valley voltage-mode controller for buck-boost converter is proposed. Considering the fact that the increasing and decreasing slopes of the inductor current are assumed to be constant during each switching cycle, an especial sampleddata model of valley voltage-mode controlled buck-boost converter is established. Based on this model, the dynamical effect of an output-capacitor time-constant on the valley voltage-mode controlled buck-boost converter is revealed and analyzed via the bifurcation diagrams, the movements of eigenvalues, the Lyapunov exponent spectra, the boundary equations,and the operating-state regions. It is found that with gradual reduction of output-capacitor time-constant, the buck-boost converter in continuous conduction mode（CCM） shows the evolutive dynamic behavior from period-1 to period-2, period-4, period-8, chaos, and invalid state. The stability boundary and the invalidated boundary are derived theoretically by stability analysis, where the stable state of valley voltage-mode controlled buck-boost converter can enter into an unstable state, and the converter can shift from the operation region to a forbidden region. These results verified by time-domain waveforms and phase portraits of both simulation and experiment indicate that the sampled-data model is correct and the time constant of the output capacitor is a critical factor for valley voltage-mode controlled buck-boost converter, which has a significant effect on the dynamics as well as control stability.