Approximate Symmetry Detection in Partial 3D Meshes

Symmetry is a common characteristic in natural and man‐made objects. Its ubiquitous nature can be exploited to facilitate the analysis and processing of computational representations of real objects. In particular, in computer graphics, the detection of symmetries in 3D geometry has enabled a number of applications in modeling and reconstruction. However, the problem of symmetry detection in incomplete geometry remains a challenging task. In this paper, we propose a vote‐based approach to detect symmetry in 3D shapes, with special interest in models with large missing parts. Our algorithm generates a set of candidate symmetries by matching local maxima of a surface function based on the heat diffusion in local domains, which guarantee robustness to missing data. In order to deal with local perturbations, we propose a multi‐scale surface function that is useful to select a set of distinctive points over which the approximate symmetries are defined. In addition, we introduce a vote‐based scheme that is aware of the partiality, and therefore reduces the number of false positive votes for the candidate symmetries. We show the effectiveness of our method in a varied set of 3D shapes and different levels of partiality. Furthermore, we show the applicability of our algorithm in the repair and completion of challenging reassembled objects in the context of cultural heritage.     

The calculus of context relations

We present the theory of context relations. Context relations are a method for incremental semantic analysis in language-specific editors, which is able to handle incomplete program fragments. The algorithm is generated from the definition of a language's static semantics and is based on inference rules and order-sorted unification. The paper presents the underlying mathematical theory, optimal incremental analysis algorithms, handling of user-defined polymorphism and overloading, and implementation issues. It is intended as the concluding report on a by now mature concept, which has successfully been used to generate efficient incremental type inferencers for languages like ADA and Fortran 8x.     

Cognitive and learning difficulties and how they affect access to IT systems

In October 2005, the IBM Human Ability and Accessibility Center and T.J. Watson Research Center hosted a symposium on “cognitive and learning difficulties and how they affect access to IT systems”. The central premise of the symposium was the recognition that cognitive and learning difficulties have a profound impact on a person’s ability to interact with information technology (IT) systems, but that little support is currently being offered by those systems. By bringing together internationally renowned experts from a variety of different, but complementary, research fields, the symposium aimed to provide a complete overview of the issues related to this topic. This paper summarises the discussions and findings of the symposium.     

A comparative study of stochastic optimization methods in electric motor design

The efficiency of universal electric motors that are widely used in home appliances can be improved by optimizing the geometry of the rotor and the stator. Expert designers traditionally approach this task by iteratively evaluating candidate designs and improving them according to their experience. However, the existence of reliable numerical simulators and powerful stochastic optimization techniques make it possible to automate the design procedure. We present a comparative study of six stochastic optimization algorithms in designing optimal rotor and stator geometries of a universal electric motor where the primary objective is to minimize the motor power losses. We compare three methods from the domain of evolutionary computation, generational evolutionary algorithm, steady-state evolutionary algorithm and differential evolution, two particle-based methods, particle-swarm optimization and electromagnetism-like algorithm, and a recently proposed multilevel ant stigmergy algorithm. By comparing their performance, the most efficient method for solving the problem is identified and an explanation of its success is offered.     

Introduction to the special issue on design science

The rigorous application of design science in information and communications technology (ICT) research is growing rapidly and producing exciting results. The five papers published in this special issue reflect some of the most recent ideas and research projects in ICT design science research (DSR). This introduction begins with concise summaries of the published papers. We then reflect on three key design science issues, using the published papers to illustrate our views. The three issues are: (1) the nature of the artifacts/problems studied in DSR in ICT disciplines; (2) the research approaches that are used; and (3) the nature of the research contributions that are made. We explain why we believe that these issues are interdependent and why thinking about these three issues as a whole can support an improved understanding of the goals and processes of design science research.     

Conceptualization,measurement, and application of semantic transparency in visual notations

Numerous visual notations are present in technical and business domains. Notations have to be cognitively effective to ease the planning, documentation, and communication of the domains’ concepts. Semantic transparency (ST) is one of the elementary principles that influence notations’ cognitive effectiveness. However, the principle is criticized for not being well defined and challenges arise in the evaluations and applications of ST. Accordingly, this research’s objectives were to answer how the ST principle is defined, operationalized, and evaluated in present notations as well as applied in the design of new notations in ICT and related areas. To meet these objectives, a systematic literature review was conducted with 94 studies passing the selection process criteria. The results reject one of the three aspects, which define semantic transparency, namely “ST is achieved with the use of icons.” Besides, taxonomies of related concepts and research methods, evaluation metrics, and other findings from this study can help to conduct verifiable ST-related experiments and applications, consequently improving the visual vocabularies of notations and effectiveness of the resulting diagrams.

     

The process map as an instrument to standardize processes: design and application at a financial service provider

The standardization of processes and the identification of shared business services in a service-oriented architecture (SOA) are currently widely discussed. Above all in practice, however, there still is a lack of appropriate instruments to support these tasks. In this paper an approach for a process map is introduced which allows for a systematic presentation—as complete as possible—of the processes in an enterprise (division). After a consistent refinement of the process has taken place by means of aggregation/disaggregation respectively, generalization/specialization relations, it is possible to identify primarily functional similarities of the detailed sub-processes. The application of the process map at a financial service provider (FSP) highlights how these similarities can be taken as a basis to standardize processes and to identify shared services.     

Self-calibration based on invariant view recognition: Dynamic approach to navigation

We extend a dynamic approach of behavior generation to the representation of spatial information. Two levels of dynamics integrate dead-reckoning, dominant far from home bases, and piloting, dominant near home bases. When the view-based piloting system recognizes a home base, visual place information recalibrates the dead-reckoning system, inverting the hierarchical ordering of the two dynamic levels by time scale inversion. Reference views taken at discrete home bases are recognized invariantly under rotation of views. This process yields compass information. Continuous translational information is obtained as a neural place representation built from view correlations with a scattered set of local views. This self-calibrating cognitive map couples into a dynamics of heading direction integrating the behaviors of obstacle avoidance and target acquisition. Targets can be designated in terms of the cognitive map. We demonstrate the dynamical model in simulation.