A case study towards validation of global illumination algorithms: progressive hierarchical radiosity with clustering

In this paper, we present an efficient global illumination technique, and then we discuss the results of its extensive experimental validation. The technique is a hybrid of cluster-based hierarchical and progressive radiosity techniques, which does not require storing links between interacting surfaces and clusters. We tested our technique by applying a multistage validation procedure, which we designed specifically for global illumination solutions. First, we experimentally validate the algorithm against analytically derived and measured real-world data to check how calculation speed is traded for lighting simulation accuracy for various clustering and meshing scenarios. Then we test the algorithm performance and rendering quality by directly comparing the virtual and real-world images of a complex environment.     

Verification of the randomized consensus algorithm of Aspnes and Herlihy: a case study

Summary. The Probabilistic I/O Automaton model of [31] is used as the basis for a formal presentation and proof of the randomized consensus algorithm of Aspnes and Herlihy. The algorithm guarantees termination within expected polynomial time. The Aspnes-Herlihy algorithm is a rather complex algorithm. Processes move through a succession of asynchronous rounds, attempting to agree at each round. At each round, the agreement attempt involves a distributed random walk. The algorithm is hard to analyze because of its use of nontrivial results of probability theory (specifically, random walk theory which is based on infinitely many coin flips rather than on finitely many coin flips), because of its complex setting, including asynchrony and both nondeterministic and probabilistic choice, and because of the interplay among several different sub-protocols. We formalize the Aspnes-Herlihy algorithm using probabilistic I/O automata. In doing so, we decompose it formally into three subprotocols: one to carry out the agreement attempts, one to conduct the random walks, and one to implement a shared counter needed by the random walks. Properties of all three subprotocols are proved separately, and combined using general results about automaton composition. It turns out that most of the work involves proving non-probabilistic properties (invariants, simulation mappings, non-probabilistic progress properties, etc.). The probabilistic reasoning is isolated to a few small sections of the proof. The task of carrying out this proof has led us to develop several general proof techniques for probabilistic I/O automata. These include ways to combine expectations for different complexity measures, to compose expected complexity properties, to convert probabilistic claims to deterministic claims, to use abstraction mappings to prove probabilistic properties, and to apply random walk theory in a distributed computational setting. We apply all of these techniques to analyze the expected complexity of the algorithm. Received: February 1999 / Accepted: March 2000     

Role of a Common Frame of Reference in Cognitive Cooperation: Sharing Tasks between Agents in Air Traffic Control

This study deals with cognitive cooperation in the context of the design of cooperative computer support for sharing aircraft conflict detection and resolution tasks between human and machine in air traffic control. In order to specify some necessary cooperative capabilities of such a system, we have observed an artificial situation on a simulator where two radar controllers (RCs) had to cooperate for the management of a heavy traffic within a single sector. This paper reports the analysis of the verbal communications between the two RCs recorded during the simulation. The results enabled us to describe the elements of a common frame of reference (COFOR), elaborated and updated by the two RCs, as a crucial cooperative activity in this kind of situation. They also show the role of this COFOR in the implicit detection and resolution of interference between the RCs’ individual activities. Their contribution to design, associated with other investigations and the state of the art, is discussed.     

The normalform of a space curve and its application to surface design

x )=0 with ∥▿h∥=1. The normalform function h is (unlike the latter cases) not differentiable at curve points. Despite of this disadvantage the normalform is a suitable tool for designing surfaces which can be treated as common implicit surfaces. Many examples (bisector surfaces, constant distance sum/product surfaces, metamorphoses, blending surfaces, smooth approximation surfaces) demonstrate applications of the normalform to surface design. Published online: 25 July 2001     

Adaptive image-smoothing using a coplanar matrix and its application to document image binarization

Abstract. For document images corrupted by various kinds of noise, direct binarization images may be severely blurred and degraded. A common treatment for this problem is to pre-smooth input images using noise-suppressing filters. This article proposes an image-smoothing method used for prefiltering the document image binarization. Conceptually, we propose that the influence range of each pixel affecting its neighbors should depend on local image statistics. Technically, we suggest using coplanar matrices to capture the structural and textural distribution of similar pixels at each site. This property adapts the smoothing process to the contrast, orientation, and spatial size of local image structures. Experimental results demonstrate the effectiveness of the proposed method, which compares favorably with existing methods in reducing noise and preserving image features. In addition, due to the adaptive nature of the similar pixel definition, the proposed filter output is more robust regarding different noise levels than existing methods. Received: October 31, 2001 / October 09, 2002 Correspondence to:L. Fan (e-mail: fanlixin@ieee.org)     

Tracking a person with pre-recorded image database and a pan, tilt, and zoom camera

Abstract. This paper proposes a novel tracking strategy that can robustly track a person or other object within a fixed environment using a pan, tilt, and zoom camera with the help of a pre-recorded image database. We define a set of camera states which is sufficient to survey the environment for the target. Background images for these camera states are stored as an image database. During tracking, camera movements are restricted to these states. Tracking and segmentation are simplified, as each tracking image can be compared with the corresponding pre-recorded background image. Received: 26 August 1999 / Accepted: 22 February 2000     

Rule-based document structure understanding with a fuzzy combination of layout and textual features

Document image processing is a crucial process in office automation and begins at the ‘OCR’ phase with difficulties in document ‘analysis’ and ‘understanding’. This paper presents a hybrid and comprehensive approach to document structure analysis. Hybrid in the sense that it makes use of layout (geometrical) as well as textual features of a given document. These features are the base for potential conditions which in turn are used to express fuzzy matched rules of an underlying rule base. Rules can be formulated based on features which might be observed within one specific layout object. However, rules can also express dependencies between different layout objects. In addition to its rule driven analysis, which allows an easy adaptation to specific domains with their specific logical objects, the system contains domain-independent markup algorithms for common objects (e.g., lists). Received June 19, 2000 / Revised November 8, 2000     

Model reduction for multidisciplinary optimization - application to a 2D wing

Multidisciplinary optimization (MDO) is a growing field in engineering, with various applications in aerospace, aeronautics, car industry, etc. However, the presence of multiple disciplines leads to specific issues, which prevent MDO to be fully integrated in industrial design methodology. In practice, the key issues in MDO lie in the management of the interconnections between disciplines, along with the high number of simulations required to find a feasible multidisciplinary (optimal) solution. Therefore, in this paper, a novel approach is proposed, combining proper orthogonal decomposition to decrease the amount of data exchanged between disciplines, with surrogate models based on moving least squares to reduce disciplines. This method is applied to an original 2D wing demonstrator involving two disciplines (fluid and structure). The numerical results obtained for an optimization task show its benefits in diminishing both the interfaces between disciplines and the overall computational time.     

A hybrid reality environment and its application to the study of earthquake engineering

Visualization can provide the much needed computer-assisted design and analysis environment to foster problem-based learning, while Virtual Reality (VR) can provide the environment for hands-on manipulation, stimulating interactive learning in engineering and the sciences. In this paper, an interactive 2D and 3D (hybrid) environment is described, which facilitates collaborative learning and research and utilizes techniques in visualization and VR, therefore enhancing the interpretation of physical problems within these fields. The environment described, termed VizClass, incorporates a specially designed lecture room and laboratory integrating both 2-D and 3-D spatial activities by coupling a series of interactive projection display boards (touch-sensitive whiteboards) and a semi-immersive 3D wall display. The environment is particularly appealing for studying critical, complex engineering problems, for example, where time-varying feature modifications and coupling between multiple modes of movement are occurring. This paper describes the hardware architecture designed for this new hybrid environment as well as an initial application within the environment to the study of a real case history building subjected to a variety of earthquakes. The example simulation uses field measured seismic data sources, and illustrations of simple visual paradigms to provide an enhanced understanding of the physical model, the damage accumulated by the model, and the association between the measured and observed data. A detailed evaluation survey was also conducted to determine the merits of the presented environment and the techniques implemented. Results substantiate the plausibility of using these techniques for more general, everyday users. Over 70% of the survey participants believed that the techniques implemented were valuable for engineers.

An intelligent moving object optimization algorithm for design problems with mixed variables, mixed constraints and multiple objectives

This paper presents an optimization algorithm for engineering design problems having a mix of continuous, discrete and integer variables; a mix of linear, non-linear, differentiable, non-differential, equality, inequality and even discontinuous design constraints; and conflicting multiple design objectives. The intelligent movement of objects (vertices and compounds) is simulated in the algorithm based on a Nelder–Mead simplex with added features to handle variable types, bound and design constraints, local optima, search initiation from an infeasible region and numerical instability, which are the common requirements for large-scale, complex optimization problems in various engineering and business disciplines. The algorithm is called an INTElligent Moving Object algorithm and tested for a wide range of benchmark problems. Validation results for several examples, which are manageable within the scope of this paper, are presented herein. Satisfactory results have been obtained for all the test problems, hence, highlighting the benefits of the proposed method.     

Design, development and implementation of a global information warehouse: a case study at IBM

The characteristics of a global information warehouse (GIW) can be understood with reference to the three dimensions implied by the three words in its name. These dimensions are boundary of the system, semiotic level of the objects in the system, and organization of objects in the system, corresponding to the terms 'global', 'information' and 'warehouse', respectively. This paper defines these three dimensions and describes the system characteristics that flow from the definitions. These characteristics also highlight the issues involved in the design, development and implementation of GIWs. The case study following the discussion of the three dimensions illustrates these issues.     

Application of a Neural Fuzzy System with Rule Extraction to Fault Detection and Diagnosis

In this paper, the fuzzy min–max (FMM) neural network is integrated with a rule extraction algorithm, and the resulting network is applied to a real-world fault detection and diagnosis task in complex industrial processes. With the rule extraction capability, the FMM network is able to overcome the “black-box” phenomenon by justifying its predictions using fuzzy if–then rules that are comprehensible to domain users. To assess the effectiveness of the FMM network, real sensor measurements are collected and used for detecting and diagnosing the heat transfer and tube blockage conditions of a circulating water (CW) system in a power generation plant. The FMM network parameters are systematically varied and tested, with the results explained. Bootstrapping is employed to quantify stability of the network performance statistically. The extracted rules are found to be compatible with the domain information as well as the opinions of domain experts who are involved in the maintenance of the CW system. Implications of the FMM network with the rule extraction facility as an intelligent and useful fault detection and diagnosis tool are discussed.     

Relaxed fault detection and isolation: An application to a nonlinear case study

Given a number of possibly concurrent faults (and disturbances) that may affect a nonlinear dynamic system, it may not be possible to solve the standard fault detection and isolation (FDI) problem, i.e., to detect and isolate each single fault from all other, possibly concurrent faults and disturbances, due to the violation of the available necessary conditions of geometric nature. Motivated by a robotic application where this negative situation structurally occurs, we propose some relaxed formulations of the FDI problem and show how necessary and sufficient conditions for their solution can be derived from those available for standard FDI. The design of a hybrid residual generator follows directly from the fulfillment of the corresponding solvability conditions. In the considered nonlinear case study, a robotic system affected by possible actuator and/or force sensor faults, we detail the application of these results and present experimental tests for validation.     

Estimation and diagnosis using multi-models with application to a wastewater treatment plant

Process diagnosis is still considered a challenging engineering problem. Technological and also environmental systems have complex behaviors often involving nonlinear relationships. When confronted to such systems, there is a need to build systems that can operate over a wide range of operating conditions. For that it is very attractive to appeal to a decomposition of the system model into a number of simpler linear models. This paper mainly focuses on the use of multi-models for process diagnosis. It is shown how the traditional tools of the linear automatic can be wide and applied to multi-model structures. A proportional multi-integral observer is used for fault diagnosis using banks of observers to generate structured residuals. The performances of the proposed diagnosis method are highlighted through the application to a wastewater treatment plant model (WWTP), which is an uncertain nonlinear system affected by unknown inputs.     

Improved workflow modelling using role activity diagram-based modelling with application to a radiology service case study

The modelling of complex workflows is an important problem-solving technique within healthcare settings. However, currently most of the workflow models use a simplified flow chart of patient flow obtained using on-site observations, group-based debates and brainstorming sessions, together with historic patient data. This paper presents a systematic and semi-automatic methodology for knowledge acquisition with detailed process representation using sequential interviews of people in the key roles involved in the service delivery process. The proposed methodology allows the modelling of roles, interactions, actions, and decisions involved in the service delivery process. This approach is based on protocol generation and analysis techniques such as: (i) initial protocol generation based on qualitative interviews of radiology staff, (ii) extraction of key features of the service delivery process, (iii) discovering the relationships among the key features extracted, and, (iv) a graphical representation of the final structured model of the service delivery process. The methodology is demonstrated through a case study of a magnetic resonance (MR) scanning service-delivery process in the radiology department of a large hospital. A set of guidelines is also presented in this paper to visually analyze the resulting process model for identifying process vulnerabilities. A comparative analysis of different workflow models is also conducted.     

Multi-user mixed reality system ‘Gulliver’s World’: a case study on collaborative edutainment at the intersection of material and virtual worlds

This case study is about ‘Gulliver’s World’, a multi-user mixed reality environment that functions simultaneously as interactive edutainment platform and learning environment as well as flexible infrastructure for the expansion of mixed reality environments via innovations in technology and media art. As an exhibition project, the installation is characterized by a nonlinear exhibition concept that activates interaction between individual users and different modes of virtual reality as well as collaboration among the users themselves. At seven workstations, people of all age groups range along the Reality–Virtuality continuum while collaboratively creating 3D worlds. Results of these creation activities are interactive worlds at the nexus of theatre, digital film production and game environment. As a research project, ‘Gulliver’s World’ features multilevel infrastructure with exemplary content in which the latest insights and models to emerge from HCI research as well as concepts of mixed reality and virtual environments and their supporting technology are brought together and developed further.     

Complexity, signal detection, and the application of ergonomics: reflections on a healthcare case study

Complexity is a defining characteristic of healthcare, and ergonomic interventions in clinical practice need to take into account aspects vital for the success or failure of new technology. The introduction of new monitoring technology, for example, creates many ripple effects through clinical relationships and agents' cross-adaptations. This paper uses the signal detection paradigm to account for a case in which multiple clinical decision makers, across power hierarchies and gender gaps, manipulate each others' sensitivities to evidence and decision criteria. These are possible to analyze and predict with an applied ergonomics that is sensitive to the social complexities of the workplace, including power, gender, hierarchy and fuzzy system boundaries.