Modeling behavior of Geographic Objects: An experience with the Object Modeling Technique

This study is to design a system of object-oriented model (OOM) reuse. This enhance the efficiency of software reuse through expressing object model utilizing cases, retrieving object model which is reused and developing object modeling procedure. We developed object model reuse system by case-based reasoning, called case-based object model reuse system (COMOR System). This system consists of four subsystems: the graphic user interface to interact with end-user, the object-oriented model management system to build a new object model, the case base to store the past object models, and the knowledge base to store object-oriented modeling and reusing knowledge.

Active object-oriented database systems (AOODBSs) are based on the object-oriented paradigm and provide an event driven behavior for implementing time critical reactions by integrating event-condition-action (ECA) rules to the database. We focus on the modeling aspects of AOODBSs. We propose an integrated approach, called A/OODBMT (Active Object-Oriented Database Modeling Technique), which integrates and extends the Object Modeling Technique (OMT) method for conceptually designing active object-oriented database applications. A/OODBMT models database applications by defining and integrating four new types of models, namely the nested object model (NOM), the behavior model (BM), the nested rule model (NRM), and the nested event model (NEM).

The Unification of OMT, SDL and IDL for Service Creation

In the paper is highlighted the industrial objects as cars, spacecraft, telescopes, plotters, lasers, elevators, etc., which are described by the mathematical model with double astatism. These models of control objects have a double pole in the origin of the coordinate axes. In order to tune the PID controller to the model of object with double astatism, it was elaborated the tuning algorithm based on the maximum stability degree method with iterations. It was done the computer simulation of the automatic control system with the respectively model of object and PID controller and it was done the analysis of the obtained performance. The advantages of the maximum stability degree method with iterations were highlighted by the reducing calculations and time, which lead to the procedure simplification of the PID controller tuning.

In the past few years, object–oriented (O–O) conceptual data modeling has emerged as an alternative to the traditional technique of entity–relationship modeling. O–O modeling is based on the premise that the resulting models are easier to use and understand. However, most claims of O–O modeling superiority are not empirically verified. Previous studies in this area have focused on a database modeler’s ability to create conceptual data models from a written description, but the concept of understanding a completed data model by a database designer has not been investigated. Thus, this study explores a database designer’s ability to understand an O–O conceptual data model – the Object Modeling Technique (OMT) – compared to an E–R model – the extended–entity– relationship model (EER). The OMT and EER conceptual data modeling techniques are compared using three modeling performance criteria: (1) model understanding; (2) time to understand; and (3) perceived ease–of–use. Results of this study indicate that the only difference between the two techniques is in the time to understand – OMT is significantly faster for both simple and complex problems.

To understand a large and complicated system, its specifier and user should be able to separate essential concerns from irrelevant details. To do that, specification of behavioral semantics-as opposed to just signatures (i.e., syntax)-is essential. Abstract and precise specifications are the corner stones of object modeling. However, object modeling has usually considered only behavior of isolated objects. Real-world enterprises do not consist only of isolated objects. It is the joint behavior of associated objects that defines the object model of the enterprise and therefore makes the business understandable. The paper show how semantics of an information model (the result of analyzing the system) can be specified in an abstract and precise manner, by reusing programming methodology concepts, and how this approach to specification is used in standardization activities. >

Level set methods were proposed mainly by mathematicians for constructing a model of a 3D object of arbitrary topology. However, those methods are computationally inefficient due to repeated distance transformations and increased dimensions. In the paper, we propose a new method of modeling fast objects of arbitrary topology by using a surface evolution approach based on mathematical morphology. Given sensor data covering the whole object surface, the method begins with an initial approximation of the object by evolving a closed surface into a model topologically equivalent to the real object. The refined approximation is then performed using energy minimization. The method has been applied in several experiments using range data, and the results are reported in the paper. © 2002 Wiley Periodicals, Inc. Syst Comp Jpn, 33(9): 58–67, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.1152

Combining Object-Oriented and Real-Time Programming from an OMT and SDL design

NTRODUCTIONThe debate on vector versus raster based models is nearly as old as the concept of a GIS (Dutton 1979). It wasrestated as a debate between GIS with an object concept (not to be confused with object-oriented as used insoftware engineering; (Worboys 1994) uses the term object based GIS, where objects have sharp boundariesdelimited by vectors and the GIS which model the continuous variation of attributes over space using a regulartessellation - e.g. a raster (Frank 1990). Efforts to merge the two representations were attempted (Peuquet 1983).It has been a very fruitful debate as it has forced us to consider and reconsider the epistemological bases of ourwork and has led to an extensive discussion of fundamental questions (Chrisman 1987), (Mark and Frank 1991),(Mark 1993). The debate has promoted the development of ever more powerful software, achieving a nearlycomplete integration of vector and raster data (Herring 1990).It has been pointed out repeatedly that only few objects in geographic space have natural boundaries whichare sharp and well determined (Couclelis 1992). Most geographic objects seem to be an abstraction of thingswhich have unclear, fuzzy boundaries, if they have boundaries at all. The list includes most natural phenomena,from biotope to mountain range; extensive research efforts center around soil type data (Burrough1993);(Burrough 1986) and often use the techniques of fuzzy logic (Zadeh 1974). Nevertheless, many practicallyused GIS model reality in terms of crisply delimited objects. Cadastral systems, GIS used for facilities’management and automated mapping (AM/FM) and communal information systems all are appropriately orientedtowards distinct objects with well defined boundaries. The same systems, with the same models are also used tomanage soil maps and land use data, where the fiction of sharp boundaries contrasts with our view of reality.Depending on the application area or profession, one or the other spatial concept is more appropriate andallows one to capture the aspects of interest more succinctly. Users are accustomed to see a process described ina particular spatial framework, a legal discussion is most often cast in the framework of spatial objects with crispand determined boundaries whereas a discussion of the application of fertilizer might consider soil types as havingindeterminate boundaries. (Burrough and Frank 1995) and (Couclelis 1995) classify applications or phenomenaaccording to an evolving taxonomy of object types and of boundary types. This leaves two questions open,namely- where do these models of well-defined objects come from and- why are object models with sharp boundaries very often used in applications of GIS despite all obviousproblems with delimiting geographic objects?This paper attempts to address these two questions, starting from the point of view of experiential realism(Lakoff 1987). Experiential realism argues that the natural categories of human cognition are based on theexperience we have of the world and that the way we perceive the world is influenced by our cognitive apparatus(Couclelis 1992) for a practical application to geography (Mark 1993). There are two different environments for ourexperience, namely small scale and large scale (geographic) space. Our daily experience with handling smallobjects in small scale space, e.g., apples, stones, leads to a concept of objects with well defined boundaries. Thiscontrasts with the direct experience of large scale space, which leads to a different conceptual structure of space,mostly without dividing large scale space into delimited objects. These are both fundamental experiences forhuman beings which are deeply embodied in our thinking and give rise to the 'object' and 'field' concept.Experiential realism also assumes that metaphorical mapping (Lakoff and Johnson 1980) can be used toconceive situations in terms of previous experiences in different circumstances. For example, the experience withsmall prototypical objects with well determined boundaries is metaphorically translated to conceive the large scale

Reducing ‘Greenhouse Gas’ emissions, particularly of CO2, is a global commitment which has gained predominance with the emergence of sources that generate renewable energy as an alternative to traditional energy produced through fossil fuels. Renewable or ‘soft’ forms of energy are all those which use the elements of nature - for example, the wind and the sun - to generate energy without damaging the environment. ‘Geographic Modelling’ is an essential tool to better determine regions that have economically feasible energy potential, based on natural alternative sources. Therefore, the objective of this study was to identify energy potential based on wind and solar renewable sources. To achieve such goal, conceptual models of spatial analysis were designed and developed, in accordance with the norms established by the 'Object Modelling Technique' and by the operational models provided by 'ModelBuilder'. A test was applied in the south-central region of 'Continental Portugal'. The results showed average potential to generate wind energy and high potential to produce solar energy in the region.

A process for reverse engineering of relational databases is proposed. Object-oriented models provide a natural language for facilitating the re-engineering process. An object-oriented model can describe the existing software, the reverse-engineered semantic intent, and the forward-engineered new system. The Object Modeling Technique (OMT) notation for modeling data is adopted. Graphical OMT models are intuitive and provide a rigorous basis for specifying software. A more robust process than advanced in the literature is proposed. Guidelines for coping with design optimizations and unfortunate implementation decisions are provided. The process emphasizes analysis of candidate keys rather than primary keys. Three sources for information are incorporated: schema, observed patterns of data, and the semantic understanding of application intent.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A comparison of the object model underpinning open systems interconnection (OSI) network management standards with that being developed for object-oriented software development systems indicates a close alignment between the models. But the OSI object-model goes further: it supports notions of asynchronously occurring events, concurrency, and optionality of implementation. These features are not found in the OMG object-model, but neither are they precluded. Consequently, the way is paved for network-management product suppliers to use OMG-conformant software-development systems. >

This article proposes a SLAM algorithm referred to as RGBD-Sphere SLAM. The key innovation of this work is the prototypical system that demonstrates how formal models of 3D geometric shape and appearance can be transformed into generative classification models that detect and recognize these shapes. Object models are specified as shape programs in PSML; a custom-built procedural language for 3D object modeling. Classifiers for each PSML shape are created by simulating how instances of each shape manifest in real-world sensor data, e.g., color images and range images. The proposed RGBD-Sphere SLAM algorithm demonstrates a prototypical example of the system. Here, the PSML program specifies spherical 3D objects having diffuse surface albedos and distinct color appearances. A recognizer uses PSML models of each object's geometry and appearance to detect instances of these objects within streaming RGBD sensor data. The detected model parameters are then integrated into an RGBD SLAM algorithm; hence the name RGBD-Sphere SLAM. This article describes the PSML programs, the spherical detection and recognition algorithms used, and describes the impact this approach has for improving the performance of RGBD SLAM approaches by incorporating detected objects as landmarks. This is the first example of a prototypical system that externalizes the geometric and appearance modeling to a programming language from which a recognizer is created, and marks an important step towards enabling users to “program” their problem space and allow computers to transform the formal object models, as expressed in PSML, into customized classifiers suited for specific sensor suites, e.g., color imagery and depth imagery.

Work objective is to develop a patentable design of locomotive traction drive mechanisms using the example of a suspension unit. Research methods: object modeling method, analytical methods for calculating dynamics of rolling stock. Research results and novelty: the design of the railway electric motor suspension unit, which will reduce costs in the course of maintenance and repair of a locomotive with a solid gear by increasing the reliability of the suspension unit parts, eliminating their wear, has been developed; a compensation coupling device has been devised. We will synthesize the object model of a technical system based on the identification of its typical structure by classifying technical systems. Conclusion: the application of the object modeling method together with the object model allows avoiding errors in the development of new designs of technical objects based on existing comparables and eliminates defects of the selected prototype. The use of the object modeling method makes it possible to synthesize patentable designs of the locomotive underframe mechanisms.

Among the multitude of probabilistic tracking techniques, the Continuously Adaptive Mean Shift (CAMSHIFT) algorithm has been one of the most popular. Though several modifications have been proposed to the original formulation of CAMSHIFT, limitations still exist. In particular the algorithm underperforms when tracking textured and patterned objects. In this paper we generalize CAMSHIFT for the purposes of tracking such objects in non-stationary backgrounds. Our extension introduces a novel object modeling technique, while retaining a probabilistic back projection stage similar to the original CAMSHIFT algorithm, but with considerably more discriminative power. The object modeling now evolves beyond a single probability distribution to a more generalized joint density function on localized color patterns. In our framework, multiple co-occurrence density functions are estimated using information from several color channel combinations and these distributions are combined using an intuitive Bayesian approach. We validate our approach on several aerial tracking scenarios and demonstrate its improved performance over the original CAMSHIFT algorithm and one of its most successful variants.