Specifying joint behavior of objects: formalization standardization

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.

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.

Behavior of geographic objects holds a critical role in spatial databases. This, along with objects' position and space-varying attributes form a minimal set of concepts sufficient to capture spatial peculiarities in terms of the object-oriented rationale. We present the semantics and the graphical notation of a prototypical object-oriented model for the conceptual design of spatial databases: by extending the Object Model of the Object Modeling Technique to the Geographic Object Model, we show how the above three concepts fit naturally into any objectoriented tool. We augment this model with the constructs of spatial aggregation and spatial grouping to express the critical aspects of space-varying attributes, object boundary fuzziness and uncertainty, spatial relationships, and attribute generalization. Our proposal integrates the field- and object-based geographic views in one model. The principal idea behind this effort is the incorporation of a set of concepts into any semantic or object-oriented model in order to make them communicate at the conceptual level (semantic interoperability).

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

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.

It is important to enable a robot to manipulate a target object that has no 3-D model information and is situated in an environment with other unknown objects nearby. This poses an open problem of how to combine perception and manipulation to enable the robot to build an appearance-based model of the target object on the spot to facilitate further manipulation of the object while avoiding the other unknown obstacles in the way. In this paper, we introduce an approach to enable a continuum manipulator, which is apt to maneuver through a crowded environment, to gradually build a 3-D surface model of the target object by moving an RGB-D sensor around the object while also detecting and avoiding surrounding unknown obstacles. Our approach interleaves perception and manipulation such that perception guides the manipulator movement, which in turn allows more perception of the target object for object model building and further manipulator motion. Our approach is characterized by a progressive strategy to register RGB-D images of the target object to build and extend a partial model of the object and the corresponding motion planning strategy for the continuum robot to carry out model building and avoid obstacles at the same time. To demonstrate the effectiveness of our approach, experiments on progressive model building of real objects from real RGB-D images are conducted, where a simulated continuum robot plans and executes its motion to carry the RGB-D camera around a target object for taking those images in an augmented reality setting.

This paper presents an approach to acquire textured 3D models of objects without the need for sophisticated hardware infrastructures. The approach is inexpensive, using a low-cost Microsoft Kinect RGB-D sensor and Augmented Reality (AR) markers printed on paper sheets. The AR-markers can be freely placed in the scene, allowing the modeling of objects of various sizes, and the sensor can be moved by the hand of an untrained person. To generate usable models with this very inexpensive and simple setup, the sequence of RGB-D scans is embedded in a graph-based optimizer for automatic post-refinement. The main novelty of this contribution is the development of an uncertainty model for an AR-marker. The AR-marker uncertainty models are used as constraints in an optimization problem to better estimate the object pose. The models are in the end further fine-tuned by a standard point-based registration algorithm. The results section presents realistic models of various objects generated using this system, e.g., parcels, sport balls, human dolls etc. Additionally, a quantitative analysis is presented using objects of known dimensions.

Creation of complex technical objects (CTO, such as science-intensive engineering objects, which are characterized by the number of elements and connections equal to 106 and more) – a process containing long subprocesses, complex objects, models, and based on available standards and information technology (IT). It is known from practice that CTO models are created with the help of information systems - components of CALS and PLM-solutions. This process have the following shortcomings: models at different stages of creation of CTO are not completely interconnected; CTO modeling takes place using different components of IT CALS and PLM-solutions, which creates constant difficulties in data conversion and leads to partial or complete loss of model data; there is no automated communication with other CTO models.
 A generalized model of complex technical objects is proposed, which based on using the theoretical-multiple approach allows to establish an information connection between the models of the process of creating complex technical objects. The information system of creation of the generalized model of difficult technical objects that allowed automating process of processing and construction of models is developed; to supplement the technology of parallel PLM design and components of information technologies CALS and PLM-solutions for the task of creating models of complex technical objects.

An integrated approach to CAD: modelling concepts in building design and construction

Object shape information is an important parameter in robot grasping tasks. However, it may be difficult to obtain accurate models of novel objects due to incomplete and noisy sensory measurements. In addition, object shape may change due to frequent interaction with the object (cereal boxes, etc). In this paper, we present a probabilistic approach for learning object models based on visual and tactile perception through physical interaction with an object. Our robot explores unknown objects by touching them strategically at parts that are uncertain in terms of shape. The robot starts by using only visual features to form an initial hypothesis about the object shape, then gradually adds tactile measurements to refine the object model. Our experiments involve ten objects of varying shapes and sizes in a real setup. The results show that our method is capable of choosing a small number of touches to construct object models similar to real object shapes and to determine similarities among acquired models.

Modern education is characterized by increased attention to the concept of model and methodology of modeling. She uses them in many fields of knowledge, but the study of computer science helps students to gather their knowledge of models into a common system and consciously apply them in their educational and practical activities. As the current task of learning is to update the content and obtain a new quality of result, the role of teaching computer modeling is becoming particularly important and has a priority ability to ensure the effectiveness of education in all its elements. The purpose of the article: is to identify the methodological features of teaching computer modeling in computer science lessons. Research methods: theoretical − analysis and generalization of scientific and methodological sources to substantiate the relevance, determining the place of the topic "Modeling" in the school course of computer science; generalizations to identify methodological features of teaching modeling in computer science lessons. An analysis of the high school computer science curriculum in the context of the topic revealed that the study of modeling in general and computer modeling, in particular, is included in the school computer science curriculum. An analysis of current computer science textbooks for high school students has shown that the topics of "Modeling" and "Computer Modeling" are presented quite concisely. There are three types of tasks in the teaching of computer modeling: to obtain the necessary information and formulate conclusions according to the given model of the object; develop a model of a real object based on data about it; perform the simulation process on a computer.

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).

Based on analysis and discussion of object representation, a hybrid model based tracking by detection algorithm is presented as yet a primary exploration. The whole system is made of a learning-detecting two phase loop. Object model is built on a general Haar-like feature space which is automatically generated and extracted by a special random projection. Our proposed algorithm involves two type of methods for object modeling, one is to learn a transformation matrix by Principal Component Analysis (PCA) as the multi-view appearance model of the target object, and the other is to learn a classifier by Fisher Linear Discriminant Analysis (FLD) as the classification between the foreground and the background. We extend the Fisher criterion to a multi-mode background situation, which is used to formulate features' discriminating power as feature weighting from the online captured positive/negative training data. In additionally, a two-stage detection is involved, in which all input samples firstly are tested by the learned FLD classifier to pick up candidates, then amongst candidates the maximum likelihood to the target template as the final detection result is searched for by PCA code matching. All generative model, discriminative model and target templates should online update due to appearance variation. A number of experiments illustrate that the proposed hybrid model based tracking algorithm does has advantages.