A Bayesian approach for pervasive estimation of breaststroke velocity using a wearable IMU

A ubiquitous assessment of swimming velocity (main metric of the performance) is essential for the coach to provide a tailored feedback to the trainee. We present a probabilistic framework for the data-driven estimation of the swimming velocity at every cycle using a low-cost wearable inertial measurement unit (IMU). The statistical validation of the method on 15 swimmers shows that an average relative error of 0.1 ± 9.6% and high correlation with the tethered reference system (rX,Y=0.91 ) is achievable. Besides, a simple tool to analyze the influence of sacrum kinematics on the performance is provided.

Fusion of Multi-Atlas Segmentations with Spatial Distribution Modeling

In recent years, multi-atlas fusion methods have gainedsignificant attention in medical image segmentation. Inthis paper, we propose a general Markov Random Field(MRF) based framework that can perform edge-preservingsmoothing of the labels at the time of fusing the labelsitself. More specifically, we formulate the label fusionproblem with MRF-based neighborhood priors, as an energyminimization problem containing a unary data term and apairwise smoothness term. We present how the existingfusion methods like majority voting, global weightedvoting and local weighted voting methods can be reframedto profit from the proposed framework, for generatingmore accurate segmentations as well as more contiguoussegmentations by getting rid of holes and islands. Theproposed framework is evaluated for segmenting lymphnodes in 3D head and neck CT images. A comparison ofvarious fusion algorithms is also presented.

Multi-Atlas based Segmentation of Head and Neck CT Images using Active Contour

This paper presents the segmentation of bilateral parotid glands in the Head and Neck (H&N) CT images using an active contour based atlas registration. We compare segmentation results from three atlas selection strategies: (i) selection of "single-most-similar" atlas for each image to be segmented, (ii) fusion of segmentation results from multiple atlases using STAPLE, and (iii) fusion of segmentation results using majority voting. Among these three approaches, fusion using majority voting provided the best results. Finally, we present a detailed evaluation on a dataset of eight images (provided as a part of H&N auto segmentation challenge conducted in conjunction with MICCAI-2010 conference) using majority voting strategy.

Identity [R]Evolution: Multi-Disciplinary Perpectives

The identity [r]evolution is happening. Who are you, who am I in the information society? In recent years, the convergence of several factors - technological, political, economic - has accelerated a fundamental change in our networked world. On a technological level, information becomes easier to gather, to store, to exchange and to process. The belief that more information brings more security has been a strong political driver to promote information gathering since September 11. Profiling intends to transform information into knowledge in order to anticipate one's behaviour, or needs, or preferences. It can lead to categorizations according to some specific risk criteria, for example, or to direct and personalized marketing. As a consequence, new forms of identities appear. They are not necessarily related to our names anymore. They are based on information, on traces that we leave when we act or interact, when we go somewhere or just stay in one place, or even sometimes when we make a choice. They are related to the SIM cards of our mobile phones, to our credit card numbers, to the pseudonyms that we use on the Internet, to our email addresses, to the IP addresses of our computers, to our profiles... Like traditional identities, these new forms of identities can allow us to distinguish an individual within a group of people, or describe this person as belonging to a community or a category. How far have we moved through this process? The identity [r]evolution is already becoming part of our daily lives. People are eager to share information with their "friends" in social networks like Facebook, in chat rooms, or in Second Life. Customers take advantage of the numerous bonus cards that are made available. Video surveillance is becoming the rule. In several countries, traditional ID documents are being replaced by biometric passports with RFID technologies. This raises several privacy issues and might actually even result in changing the perception of the concept of privacy itself, in particular by the younger generation. In the information society, our (partial) identities become the illusory masks that we choose -or that we are assigned- to interplay and communicate with each other. Rights, obligations, responsibilities, even reputation are increasingly associated with these masks. On the one hand, these masks become the key to access restricted information and to use services. On the other hand, in case of a fraud or negative reputation, the owner of such a mask can be penalized: doors remain closed, access to services is denied. Hence the current preoccupying growth of impersonation, identity-theft and other identity-related crimes. Where is the path of the identity [r]evolution leading us? The booklet is giving a glance on possible scenarios in the field of identity.

ConnectomeViewer - Multi-Modal Multi-Level Network Visualization and Analysis.

Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.

A design science approach to support the assessment of disruptive technology : the Swiss mobile payment case

Abstract In this thesis we present the design of a systematic integrated computer-based approach for detecting potential disruptions from an industry perspective. Following the design science paradigm, we iteratively develop several multi-actor multi-criteria artifacts dedicated to environment scanning. The contributions of this thesis are both theoretical and practical. We demonstrate the successful use of multi-criteria decision-making methods for technology foresight. Furthermore, we illustrate the design of our artifacts using build and-evaluate loops supported with a field study of the Swiss mobile payment industry. To increase the relevance of this study, we systematically interview key Swiss experts for each design iteration. As a result, our research provides a realistic picture of the current situation in the Swiss mobile payment market and reveals previously undiscovered weak signals for future trends. Finally, we suggest a generic design process for environment scanning.

Multi-slice three-dimensional myocardial strain tensor quantification using zHARP.

In this article we propose a novel method for calculating cardiac 3-D strain. The method requires the acquisition of myocardial short-axis (SA) slices only and produces the 3-D strain tensor at every point within every pair of slices. Three-dimensional displacement is calculated from SA slices using zHARP which is then used for calculating the local displacement gradient and thus the local strain tensor. There are three main advantages of this method. First, the 3-D strain tensor is calculated for every pixel without interpolation; this is unprecedented in cardiac MR imaging. Second, this method is fast, in part because there is no need to acquire long-axis (LA) slices. Third, the method is accurate because the 3-D displacement components are acquired simultaneously and therefore reduces motion artifacts without the need for registration. This article presents the theory of computing 3-D strain from two slices using zHARP, the imaging protocol, and both phantom and in-vivo validation.

Privacy-friendly Business Models for Location-Based Mobile Services

This paper presents a theoretical model to analyze the privacy issues around location based mobile business models. We report the results of an exploratory field experiment in Switzerland that assessed the factors driving user payoff in mobile business. We found that (1) the personal data disclosed has a negative effect on user payoff; (2) the amount of personalization available has a direct and positive effect, as well as a moderating effect on user payoff; (3) the amount of control over user's personal data has a direct and positive effect, as well as a moderating effect on user payoff. The results suggest that privacy protection could be the main value proposition in the B2C mobile market. From our theoretical model we derive a set of guidelines to design a privacy-friendly business model pattern for third-party services. We discuss four examples to show the mobile platform can play a key role in the implementation of these new business models.

Prototype of a web-based participative decision support platform in natural hazards and risk management

This paper presents the current state and development of a prototype web-GIS (Geographic Information System) decision support platform intended for application in natural hazards and risk management, mainly for floods and landslides. This web platform uses open-source geospatial software and technologies, particularly the Boundless (formerly OpenGeo) framework and its client side software development kit (SDK). The main purpose of the platform is to assist the experts and stakeholders in the decision-making process for evaluation and selection of different risk management strategies through an interactive participation approach, integrating web-GIS interface with decision support tool based on a compromise programming approach. The access rights and functionality of the platform are varied depending on the roles and responsibilities of stakeholders in managing the risk. The application of the prototype platform is demonstrated based on an example case study site: Malborghetto Valbruna municipality of North-Eastern Italy where flash floods and landslides are frequent with major events having occurred in 2003. The preliminary feedback collected from the stakeholders in the region is discussed to understand the perspectives of stakeholders on the proposed prototype platform.

Landslide detection and monitoring capability of boat-based mobile laser scanning along Dieppe coastal cliffs, Normandy

Integrated in a wide research assessing destabilizing and triggering factors to model cliff dynamic along the Dieppe's shoreline in High Normandy, this study aims at testing boat-based mobile LiDAR capabilities by scanning 3D point clouds of the unstable coastal cliffs. Two acquisition campaigns were performed in September 2012 and September 2013, scanning (1) a 30-km-long shoreline and (2) the same test cliffs in different environmental conditions and device settings. The potentials of collected data for 3D modelling, change detection and landslide monitoring were afterward assessed. By scanning during favourable meteorological and marine conditions and close to the coast, mobile LiDAR devices are able to quickly scan a long shoreline with median point spacing up to 10cm. The acquired data are then sufficiently detailed to map geomorphological features smaller than 0.5m2. Furthermore, our capability to detect rockfalls and erosion deposits (>m3) is confirmed, since using the classical approach of computing differences between sequential acquisitions reveals many cliff collapses between Pourville and Quiberville and only sparse changes between Dieppe and Belleville-sur-Mer. These different change rates result from different rockfall susceptibilities. Finally, we also confirmed the capability of the boat-based mobile LiDAR technique to monitor single large changes, characterizing the Dieppe landslide geometry with two main active scarps, retrogression up to 40m and about 100,000m3 of eroded materials.