An adaptive learning approach for 3-D surface reconstruction from point clouds.

In this paper, we propose a multiresolution approach for surface reconstruction from clouds of unorganized points representing an object surface in 3-D space. The proposed method uses a set of mesh operators and simple rules for selective mesh refinement, with a strategy based on Kohonen's self-organizing map (SOM). Basically, a self-adaptive scheme is used for iteratively moving vertices of an initial simple mesh in the direction of the set of points, ideally the object boundary. Successive refinement and motion of vertices are applied leading to a more detailed surface, in a multiresolution, iterative scheme. Reconstruction was experimented on with several point sets, including different shapes and sizes. Results show generated meshes very close to object final shapes. We include measures of performance and discuss robustness.     

The effects of glossy screens on the acceptance of flat‐panel displays

Abstract— The TCO requirements provide well‐known and recognized quality labels for displays. For these requirements to remain useful, they must continuously be reviewed and updated when necessary. The study described here was performed in response to the market trend of designing flat‐panel displays and notebooks with glare panels. The purpose of this study was to investigate subjective responses to display screens of different gloss levels for office workers working on different tasks under normal office‐lighting conditions. The study consisted of three parts, one where the users should set an acceptable reflex level, one where the user should rate their disturbance on a category scale, and one where the visual acuity of the users were investigated whether they were affected by glare or not. The results show that increasing gloss and increasing luminance levels had negative effects on the acceptance and the disturbance of reflexes. There were statistically significant differences in the acceptance and the disturbance levels between screens with low gloss and screens with high gloss, which suggests that screens with the highest gloss levels should be avoided. The study did not show an effect on the performance based on acuity testing.     

Visualization of myocardial perfusion derived from coronary anatomy

Visually assessing the effect of the coronary artery anatomy on the perfusion of the heart muscle in patients with coronary artery disease remains a challenging task. We explore the feasibility of visualizing this effect on perfusion using a numerical approach. We perform a computational simulation of the way blood is perfused throughout the myocardium purely based on information from a three-dimensional anatomical tomographic scan. The results are subsequently visualized using both three-dimensional visualizations and bull's eye plots, partially inspired by approaches currently common in medical practice. Our approach results in a comprehensive visualization of the coronary anatomy that compares well to visualizations commonly used for other scanning technologies. We demonstrate techniques giving detailed insight in blood supply, coronary territories and feeding coronary arteries of a selected region. We demonstrate the advantages of our approach through visualizations that show information which commonly cannot be directly observed in scanning data, such as a separate visualization of the supply from each coronary artery. We thus show that the results of a computational simulation can be effectively visualized and facilitate visually correlating these results to for example perfusion data.     

The role of a “make” or internal human resource management system in Spanish manufacturing companies: Empirical evidence

The combined study of the literature about human resource management and the resource‐based view of the firm and organizational learning provides an analysis framework useful for understanding how strategic human resource management systems contribute to the creation and development of a sustained competitive advantage for the firm. This article has two major aims. First, it provides a conceptual framework linking simultaneously three theoretical blocks: (a) human resource management, (b) organizational learning and knowledge management, and (c) sustained competitive advantage. Second, the article builds a causal model and tests it with a sample of Spanish firms from the manufacturing industry using structural equation modeling (SEM). After the performance of a cluster analysis, a group of 72 learning firms is identified and used to test the model. Finally, major conclusions and implications for management are drawn and further avenues for research are suggested. © 2008 Wiley Periodicals, Inc.     

Virtual rights? Property in online game objects and characters

The new industry of Massively Multi-Player Online Role-Playing Games (MMORPGs) brings together two sets of fictions: the interactive stories of shared computer games and the legal devices of intellectual property. In these virtual worlds, scarcity need not exist, but players tend to prefer the competition it creates. This leads to the development of property rights within the game world and players trading real money for virtual objects, ‘land’ and characters. This new phenomenon brings with it familiar legal problems such as theft, fraud and ownership disputes. Game creators also challenge the right of the players to claim ownership outside the game world. The volume and value of the items traded make real money trading an important area of current interest for intellectual property lawyers. Something is being traded, but does it fit neatly into existing conceptions of property rights and who owns it? Analysing the novel problems that result from various theoretical perspectives (utilitarianism, labour-desert theory and personality theory) leads to the conclusion that with time, we will see the development of property rights for players in online games. This connects with a growing understanding that the traditional conception of copyright law dealing with creative work generated by the solitary author is becoming less appropriate in the new creative spaces that information and communications technology brings, where individuals are both consumer and producer. In virtual worlds, new forms of intellectual property, and perhaps even new rights, are taking shape.     

A dynamic bibliometric model for identifying online communities

Predictive modelling of online dynamic user-interaction recordings and community identification from such data becomes more and more important with the widespread use of online communication technologies. Despite of the time-dependent nature of the problem, existing approaches of community identification are based on static or fully observed network connections. Here we present a new, dynamic generative model for the inference of communities from a sequence of temporal events produced through online computer- mediated interactions. The distinctive feature of our approach is that it tries to model the process in a more realistic manner, including an account for possible random temporal delays between the intended connections. The inference of these delays from the data then forms an integral part of our state-clustering methodology, so that the most likely communities are found on the basis of the likely intended connections rather than just the observed ones. We derive a maximum likelihood estimation algorithm for the identification of our model, which turns out to be computationally efficient for the analysis of historical data and it scales linearly with the number of non-zero observed (L + 1)-grams, where L is the Markov memory length. In addition, we also derive an incremental version of the algorithm, which could be used for real-time analysis. Results obtained on both synthetic and real-world data sets demonstrate the approach is flexible and able to reveal novel and insightful structural aspects of online interactions. In particular, the analysis of a full day worth synchronous Internet relay chat participation sequence, reveals the formation of an extremely clear community structure.     

Impacts in multibody systems: modeling and experiments

This paper outlines a novel approach to the modeling and analysis of impact involving multibody systems. This approach is based on an analysis of energy absorption and restitution during impact, using a decomposition of the kinetic energy, which decouples the parts associated with the spaces of admissible and constrained motions of the underlying unilateral constraints. Such a decomposition turns out to be useful in the analysis of energy dissipation during impact, and leads to a generalized definition of the energetic coefficient of restitution, which targets particularly collisions in multibody systems. The applicability of the approach reported is investigated by conducting an experimental study on a robotic testbed. It is shown that impact between multibody systems is considerably affected not only by the local dynamics characteristics of the interacting bodies, but also the configuration of the whole multibody system. The results reported here show that our decomposition can offer a sound characterization of impact in several problems of multibody systems.     

Diagnosis of lung nodule using Moran’s index and Geary’s coefficient in computerized tomography images

This paper analyzes the application of Moran’s index and Geary’s coefficient to the characterization of lung nodules as malignant or benign in computerized tomography images. The characterization method is based on a process that verifies which combination of measures, from the proposed measures, has been best able to discriminate between the benign and malignant nodules using stepwise discriminant analysis. Then, a linear discriminant analysis procedure was performed using the selected features to evaluate the ability of these in predicting the classification for each nodule. In order to verify this application we also describe tests that were carried out using a sample of 36 nodules: 29 benign and 7 malignant. A leave-one-out procedure was used to provide a less biased estimate of the linear discriminator’s performance. The two analyzed functions and its combinations have provided above 90% of accuracy and a value area under receiver operation characteristic (ROC) curve above 0.85, that indicates a promising potential to be used as nodules signature measures. The preliminary results of this approach are very encouraging in characterizing nodules using the two functions presented.

Dissimilarity-based classification of chromatographic profiles

This paper proposes a non-parametric method for the classification of thin-layer chromatographic (TLC) images from patterns represented in a dissimilarity space. Each pattern corresponds to a mixture of Gaussian approximation of the intensity profile. The methodology comprises various phases, including image processing and analysis steps to extract the chromatographic profiles and a classification phase to discriminate among two groups, one corresponding to normal cases and the other to three pathological classes. We present an extensive study of several dissimilarity-based approaches analysing the influence of the dissimilarity measure and the prototype selection method on the classification performance. The main conclusions of this paper are that, Match and Profile-difference dissimilarity measures present better results, and a new prototype selection methodology achieves a performance similar or even better than conventional methods. Furthermore, we also concluded that simplest classifiers, such as k-NN and linear discriminant classifiers (LDCs), present good performance being the overall classification error less than 10% for the four-class problem.     

A Secure Grid Medical Data Manager Interfaced to the gLite Middleware

The medical community is producing and manipulating a tremendous volume of digital data for which computerized archiving, processing and analysis is needed. Grid infrastructures are promising for dealing with challenges arising in computerized medicine but the manipulation of medical data on such infrastructures faces both the problem of interconnecting medical information systems to Grid middlewares and of preserving patients’ privacy in a wide and distributed multi-user system. These constraints are often limiting the use of Grids for manipulating sensitive medical data. This paper describes our design of a medical data management system taking advantage of the advanced gLite data management services, developed in the context of the EGEE project, to fulfill the stringent needs of the medical community. It ensures medical data protection through strict data access control, anonymization and encryption. The multi-level access control provides the flexibility needed for implementing complex medical use-cases. Data anonymization prevents the exposure of most sensitive data to unauthorized users, and data encryption guarantees data protection even when it is stored at remote sites. Moreover, the developed prototype provides a Grid storage resource manager (SRM) interface to standard medical DICOM servers thereby enabling transparent access to medical data without interfering with medical practice.