Graphical Objects Research Articles

CUBot: Computer Vision on the Eye–Hand Coordination with a Computer-Using Robot and its Implementation

Eye–hand coordination (EHC) is of great importance in the research areas of human visual perception, computer vision and robotic vision. A computer-using robot (CUBot) is designed for investigating the EHC mechanism and its implementation is presented in this paper. The CUBot possesses the ability of operating a computer with a mouse like a human being. Based on the three phases of people using computer with a mouse, i.e. watching the screen, recognizing the graphical objects on the screen as well as controlling the mouse to let the cursor approach to the target, our CUBot can also perceive information merely through its vision and control the mouse by its robotic hand without any physical data communication connected to the operated computer. The CUBot is mainly composed of “Mouse-Hand” for operating the mouse, “mind” for realizing the object perception, cursor tracking, and EHC. Two experiments used for testing the ability of our EHC algorithm and the perception of CUBot confirm the feasibility of the proposed approach.

RoboSim: a simulation environment for programming virtual robots

In this paper, the design of RoboSim, a simulation environment for programming virtual Linkbot and Lego Mindstorms NXT/EV3 robots, is described in detail. RoboSim integrates into the Ch programming environment, a C/C++ interpreter that provides the ability to remotely control robots through interpreted C/C++ code. The same Ch code can control either hardware or virtual robots without any modification. Open source software projects Open Dynamics Engine, OpenSceneGraph, and Qt are employed to produce the virtual environment and user interface which provide the capability of running on all major software platforms. The design of the software includes multiple modules each specific to a particular task; therefore, the simulation library and graphical user interface (GUI) utilize the common pieces. The GUI provides an interactive view of RoboSim to add robots, obstacles, and graphical objects to preview the environment before executing code for the robots. Execution of Ch code designed for the robots generates a new RoboSim window which has the identical scene from the GUI with dynamic simulation capabilities. The interpreted code controlling the simulation can be paused and resumed as necessary to fully understand how the robots are moving.

3D Modeling as Method for Construction and Analysis of Graphic Objects

The use of 3D modeling when constructing and analyzing perspective projections and shadows is considered. The creation of photorealistic image is shown. The perspective of the construction project and characterization of its image are given as an example. The authors consider the construction of a dynamic block as a means of graphical information storage and automation of geometric constructions. The example of the dynamic block construction at creating a truss node is demonstrated. The constructions are considered as applied to the Auto-CAD software. The paper is aimed at improving the graphic methods of architectural design and improving the educational process when training the Bachelor’s degree students majoring in construction.

Automatic modeling of the surfaces of the equal slope in AutoCad system through language AutoLisp

Graphical computer modeling is a real possibility of solving problems on the formation of surfaces by a kinematic method. It is due to the presence of automated design systems, such as MathCad, Mathematika, AutoCad, etc. The advantage of the AutoCad system is the presence of the built-in language of functional AutoLisp. Having a wide range of mathematical functions and functions for drawing graphic objects, the AutoLisp language allows you to write a program for drawing shells of any complexity, in a particular case - shells of the same ramp on the elliptical plane, the surface of the involute helicoid, and then transferring the results to the AutoCAD environment. Playing objects in slow motion makes it possible to compose mini-films about the formation of surfaces. The image of graphical constructions in three-dimensional space using the AutoCAD color palette enhances the expressiveness of the image of surfaces and their elements. The aim of the study is the possibility of modeling the surface of the equal slope ramp on an elliptical plane, carried out by its gradual drawing in a slow dynamic mode with the creation of a mini-film that allows the surface to be displayed on the monitor screen

Steganalysis of 3D objects using statistics of local feature sets

3D steganalysis aims to identify subtle invisible changes produced in graphical objects through digital watermarking or steganography. Sets of statistical representations of 3D features, extracted from both cover and stego 3D mesh objects, are used as inputs into machine learning classifiers in order to decide whether any information was hidden in the given graphical object. The features proposed in this paper include those representing the local object curvature, vertex normals, the local geometry representation in the spherical coordinate system. The effectiveness of these features is tested in various combinations with other features used for 3D steganalysis. The relevance of each feature for 3D steganalysis is assessed using the Pearson correlation coefficient. Six different 3D watermarking and steganographic methods are used for creating the stego-objects used in the evaluation study.

On a graph calculus for modalities

We present a sound and complete graph calculus for modalities. This calculus is a general framework for expressing modal formulas and frame properties, with a rich repertoire of relations, and reasoning about them in a uniform manner. The calculus employs graphical interpretations of logical operators and builds graphical objects that represent conditions on Kripke structures.

MODEL VOLUMETRIC DOSING OF GROUND COFFEE ON THE BASIS OF SCADA-SYSTEM LABVIEW

About automation and mathematical model of volumetric dosing of ground coffee on the basis of SCADA - system and programming language LabView. The algorithms and functional diagram of the automation process of dispensing the ground coffee and described in the form of transfer functions of the process control parameters. This model differs from others in that it allows the use of dimensional algorithmic and computational description of data processing to produce the control signals to the drive system and the metering feeder at a presentation of the results as dynamic graphical objects by means of multi-window interface SCADA system. Product level speed drive dispenser weight in the package are controlled parameters of the system. Factors affecting as a disturbance on the accuracy of dosing with the physical and mechanical properties of the product are the degree of fullness of the hopper and the uneven flow of product to the dispensing mechanism. A more preferred method of research is the study of the process with the use of simulation techniques, than the construction of differential models. The developed control system allows you to monitor the dosing process, the level and doses of ground coffee in the migration of physical and mechanical properties and the motor controller rotary displacement metering is useful for analysis and further interpretation of the human operator in the formation of a decision on an operation of process equipment in the achievement of management objectives

“All Models Are Wrong”

Several years ago, the first thing i learned in my introductory statistics class was the following declaration, which the instructor had written in capital letters on the blackboard: “all models are wrong.” Models are statistical, graphic, or physical objects, and their primary quality is that they can be manipulated. Scientists and social scientists use them to think about the social or natural worlds and to represent those worlds in a simplified manner. Statistical models, which dominate the social sciences, particularly in economics, are typically equations with response and predictor variables. Specifically, a researcher seeks to understand some social phenomenon, such as the relation between students' scores on a math test and how many hours the students spent preparing for the exam. To predict or describe this relation, the researcher constructs a quantitative model with quantitative inputs (the number of hours each student spent studying) and outputs (each student's test score). The researcher hopes that the number of hours a student spent preparing for the exam will correlate with the student's score. If it does, this quantified relation can help describe the overall dynamics of test taking.

Service-Oriented Geographic Information Application of Petroleum Exploration and Development

The research objects of petroleum exploration and development (E&D) are basically related to the geographical location. Aiming at the multi-source of the spatial data, the heterogeneity between the spatial data and business data and the diversity of the application systems, a spatial data model is designed and the corresponding spatial database is established so that a unified management and maintenance for spatial data of E&D is achieved. Furthermore, the integrated geographic information services and data services are constructed that make the combination of graphical objects and business data possible. Finally, a universal geographic information integration service is constructed, so a new application need for geographic information functionalities can easily integrate the service.

ALET: Agents Learning their Environment through Text

AbstractFor intelligent virtual humans to interact in a rich environment, connections between the usable actions and objects must be defined. For scenarios consisting of hundreds of object types and many actions, having a simulation author create these connections by hand becomes and difficult. This limitation causes the simulation to have only a few object connections, whereas the rest of the objects are static and cannot be acted upon. Automated methods to connect objects to actions are promising but incomplete as they still miss key interactions and are unable to determine important characteristics of each action such as the manner of the action. We present Agents Learning their Environment through Text (ALET) to connect graphical objects to actions and provide an understanding of the actions. Observing that text contains descriptions of actions and connections to objects, ALET leverages large text corpora, and knowledge bases to provide candidate connections and descriptions for the actions and objects available in a simulation. The candidate connections and descriptions populate a representation that describes the graphical models and animations. We test ALET against other semantic generation methods, and find it more accurately determines object roles in actions, as well as determines semantic information about the action.

Approximate answering of queries involving polyline–polyline topological relationships

In geographic information systems, pictorial query languages are visual languages which make easier the user to express queries by free-hand drawing. In this perspective, this article proposes an approach to provide approximate answers to pictorial queries that do not match with the content of the database, that is, the results are null. It addresses the polyline–polyline topological relationships and is based on an algorithm, called Approximate Answer Computation algorithm, which exploits the notions of Operator Conceptual Neighborhood graph and 16-intersection matrix. The operator conceptual neighborhood graph represents the conceptual topological neighborhood between Symbolic Graphical Objects and is used for relaxing constraints of queries. The nodes of the operator conceptual neighborhood graph are labeled with geo-operators whose semantics has been formalized. The 16-intersection matrix provides enriched query details with respect to the well-known Dimensionally Extended 9-Intersection Model proposed in the literature. A set of minimal 16-intersection matrices associated with each node of the operator conceptual neighborhood graph, upon the external space connectivity condition, is defined and the proof of its minimality is provided. The main idea behind each introduced notion is illustrated using a running example throughout this article.

A scheme of AR-based personalized interactive broadcasting service in terrestrial digital broadcasting system

This paper proposes a AR-based personalized interactive broadcasting system via broadcast and broadband networks in terrestrial digital broadcasting system (DTV) environment. Augmented reality (AR) technology is a kind of mixed reality which 2D/3D graphics are integrated into the real world in order to enhance user experience and enrich information. A goal of AR-based interactive broadcasting system is to enable broadcasting program using AR technology to blend augmented content (2D/3D graphic object) with broadcasting content in real-time on receiving terminals. The proposed service scheme enables viewer-selectable augmented broadcasting service being provided from two content providers with authorization by a broadcaster and we show the implemented results under DTV environment.

SIGUEME: Technology-based intervention for low-functioning autism to train skills to work with visual signifiers and concepts

BackgroundPeople with low-functioning ASD and other disabilities often find it difficult to understand the symbols traditionally used in educational materials during the learning process. Technology-based interventions are becoming increasingly common, helping children with cognitive disabilities to perform academic tasks and improve their abilities and knowledge. Such children often find it difficult to perform certain tasks contained in educational materials since they lack necessary skills such as abstract reasoning. In order to help these children, the authors designed and created SIGUEME to train attention and the perceptual and visual cognitive skills required to work with and understand graphic materials and objects. MethodsA pre-test/post-test design was implemented to test SIGUEME. Seventy-four children with low-functioning ASD (age=13.47, SD=8.74) were trained with SIGUEME over twenty-five sessions and compared with twenty-eight children (age=12.61, SD=2.85) who had not received any intervention. ResultsThere was a statistically significant improvement in the experimental group in Attention (W=−5.497, p<0.001). There was also a significant change in Association and Categorization (W=2.721, p=0.007) and Interaction (W=−3.287, p=0.001). ConclusionsSIGUEME is an effective tool for improving attention, categorization and interaction in low-functioning children with ASD. It is also a useful and powerful instrument for teachers, parents and educators by increasing the child's motivation and autonomy.

Rank Centrality: Ranking from Pairwise Comparisons

The question of aggregating pairwise comparisons to obtain a global ranking over a collection of objects has been of interest for a very long time: be it ranking of online gamers (e.g., MSR’s TrueSkill system) and chess players, aggregating social opinions, or deciding which product to sell based on transactions. In most settings, in addition to obtaining a ranking, finding ‘scores’ for each object (e.g., player’s rating) is of interest for understanding the intensity of the preferences. In this paper, we propose Rank Centrality, an iterative rank aggregation algorithm for discovering scores for objects (or items) from pairwise comparisons. The algorithm has a natural random walk interpretation over the graph of objects with an edge present between a pair of objects if they are compared; the score, which we call Rank Centrality, of an object turns out to be its stationary probability under this random walk. To study the efficacy of the algorithm, we consider the popular Bradley-Terry-Luce (BTL) model (equivalent to the Multinomial Logit (MNL) for pairwise comparisons) in which each object has an associated score that determines the probabilistic outcomes of pairwise comparisons between objects. In terms of the pairwise marginal probabilities, which is the main subject of this paper, the MNL model and the BTL model are identical. We bound the finite sample error rates between the scores assumed by the BTL model and those estimated by our algorithm. In particular, the number of samples required to learn the score well with high probability depends on the structure of the comparison graph. When the Laplacian of the comparison graph has a strictly positive spectral gap, e.g., each item is compared to a subset of randomly chosen items, this leads to dependence on the number of samples that is nearly order optimal. Experimental evaluations on synthetic data sets generated according to the BTL model show that our algorithm performs as well as the maximum likelihood estimator for that model and outperforms other popular ranking algorithms.

Calibration with confidence: a principled method for panel assessment.

Frequently, a set of objects has to be evaluated by a panel of assessors, but not every object is assessed by every assessor. A problem facing such panels is how to take into account different standards among panel members and varying levels of confidence in their scores. Here, a mathematically based algorithm is developed to calibrate the scores of such assessors, addressing both of these issues. The algorithm is based on the connectivity of the graph of assessors and objects evaluated, incorporating declared confidences as weights on its edges. If the graph is sufficiently well connected, relative standards can be inferred by comparing how assessors rate objects they assess in common, weighted by the levels of confidence of each assessment. By removing these biases, ‘true’ values are inferred for all the objects. Reliability estimates for the resulting values are obtained. The algorithm is tested in two case studies: one by computer simulation and another based on realistic evaluation data. The process is compared to the simple averaging procedure in widespread use, and to Fisher's additive incomplete block analysis. It is anticipated that the algorithm will prove useful in a wide variety of situations such as evaluation of the quality of research submitted to national assessment exercises; appraisal of grant proposals submitted to funding panels; ranking of job applicants; and judgement of performances on degree courses wherein candidates can choose from lists of options.

PCA based 3D City Model Generalization for Electricity Simulation

3D city models are widely used in many applications such as electricity simulation, urban planning, navigation, transportation, city management and so on. One of the key issues in the 3D city study fields is how to reduce the complexity of 3D city models. In this paper, we present a novel method to simply the 3D city object using PCA (Principal component analysis). Different from the ordinary 3D objects in computer graphics, polygons in 3D city objects are usually correlated e.g. parallel to each other or nearly located in the same plane. Therefore, PCA can reduce the data volume efficiently. According to the experimental results, the proposed method can compress the 3D city models by 95% while preserving the overall similarity between the simplified and original models.

Graphical Methods for Designing Bolted Joints in Engineering Drawings

This article analyzes graphical methods for designing bolted joints in engineering drawings, presents design system of a truss node's with bolted connections. The creation methods of automated design system of a truss node's bolted joints are discovered with Unified Modeling Language. Graphical system can design steel plain truss node's bolted joints, form information tables of objects. The bars bolted connections near node sheet are calculated using programming object's bolted joints properties and methods. Drawing's graphical objects have additional data from which exchange of data between graphical system and information table of objects is executed. Example of truss node's bolted joints project with information table is presented. Creation problems of automated design system are discussed and conclusions are made.

An exploration into the visual aspects of roadmaps: the views from a panel of experts

Roadmapping is an established and popular method for strategic planning. Its strength is often characterised in terms of the visual way in which it can embody future plans and present pathways to realising an organisation's vision. However, although a roadmap is a visual management tool, the visual aspects from a graphic design perspective have been largely overlooked. In order to explore this perspective, a panel of experts was brought together for a research workshop which consisted of a focus group activity and a visual critique. The focus group elicited the good vs. bad visual features of roadmap visualisations. This was followed by a critique exercise where a sample set of representative roadmaps were examined in terms of their structural layout, graphical objects and population with content. These roadmaps were also empirically assessed (scored and ranked) to give an indication of their 'visual design goodness'.

Approximation Algorithms for Polynomial-Expansion and Low-Density Graphs

We study the family of intersection graphs of low density objects in low dimensional Euclidean space. This family is quite general, and includes planar graphs. We prove that such graphs have small separators. Next, we present efficient $(1+\varepsilon)$-approximation algorithms for these graphs, for Independent Set, Set Cover, and Dominating Set problems, among others. We also prove corresponding hardness of approximation for some of these optimization problems, providing a characterization of their intractability in terms of density.

Optimized Deep Learning Framework for Water Distribution Data-Driven Modeling

Deep Learning (DL), unlike conventional Artificial Neural network (ANN), is capable of self-learning data features layer by layer in unsupervised manner and creating a data-driven model with the given dataset. DL has been widely applied to big data analytics, graphics object detection, classification, voice recognition and many other problems. This paper presents an integrated data-driven modelling framework that couples DL with the well-developed evolutionary optimization tool in a scalable and heterogeneous high performance computing paradigm. The integrated framework enables modellers to effectively and efficiently construct a model with a given dataset. It is demonstrated that the framework has wide applicability including but not limited to the simulation, optimization and operation decision of water distribution systems. The paper elaborates the development of the deep learning framework with potential applications of facilitating the data fusion, system simulation and predictive analysis, anomaly detection from the time series data (pressures, flows and consumptions etc.), water usage prediction, construction of a meta-model as a surrogate to the physics-based models (hydraulic and water quality) for water distribution management.