NANA: Novel assessment of nutrition and ageing

Purpose NANA is a 3-year project using sensitively-designed technology to improve data collection and integrate information on nutrition, physical and cognitive function and mental health to identify individuals at risk of under-nourishment and improve targeting of interventions. This research will also improve our understanding of the interactions between these factors, in order to better medical treatment and social provision. The toolkit has potential for commercial development for additional segments of the population. Method This is a multi-disciplinary program involving psychology, nutrition, engineering and software engineering. The first phase is a user needs analysis and will involve consulting with a broad cross-section of older people, caregivers, and health professionals, to establish what technical approaches would be useful and acceptable. The second phase focuses on the development of an integrated measurement toolkit. There are three inter-related subsections: (i) an iterative program to develop the assessment technology, (ii) techniques for dietary assessment in older people, and (iii) a parallel investigation of measures of cognition and mental health in older people. It includes a full validation of the assessment toolkit and will comprise a comparison of the new, integrated assessment with traditional 'pen and paper' methods with volunteers having the equipment installed in their homes.

Educational inclusiveness through Ludic engagement and digital creativity

This paper describes an approach to teaching and learning that combines elements of ludic engagement, gamification and digital creativity in order to make the learning of a serious subject a fun, interactive and inclusive experience for students regardless of their gender, age, culture, experience or any disabilities that they may have. This approach has been successfully used to teach software engineering to first year students but could in principle be transferred to any subject or discipline.

Performing knowledge requirements analysis for public organisations in a Virtual Learning Environment: a social network analysis approach

This paper describes an application of Social Network Analysis methods for identification of knowledge demands in public organisations. Affiliation networks established in a postgraduate programme were analysed. The course was executed in a distance education mode and its students worked on public agencies. Relations established among course participants were mediated through a virtual learning environment using Moodle. Data available in Moodle may be extracted using knowledge discovery in databases techniques. Potential degrees of closeness existing among different organisations and among researched subjects were assessed. This suggests how organisations could cooperate for knowledge management and also how to identify their common interests. The study points out that closeness among organisations and research topics may be assessed through affiliation networks. This opens up opportunities for applying knowledge management between organisations and creating communities of practice. Concepts of knowledge management and social network analysis provide the theoretical and methodological basis.

Dual semiosis analysis model managing customer-focused service innovation

Customers will not continue to pay for a service if it is perceived to be of poor quality, and/or of no value. With a paradigm shift towards business dependence on service orientated IS solutions [1], it is critical that alignment exists between service definition, delivery, and customer expectation, businesses are to ensure customer satisfaction. Services, and micro-service development, offer businesses a flexible structure for solution innovation, however, constant changes in technology, business and societal expectations means an iterative analysis solution is required to i) determine whether provider services adequately meet customer segment needs and expectations, and ii) to help guide business service innovation and development. In this paper, by incorporating multiple models, we propose a series of steps to help identify and prioritise service gaps. Moreover, the authors propose the Dual Semiosis Analysis Model, i.e. a tool that highlights where within the symbiotic customer / provider semiosis process, requirements misinterpretation, and/or service provision deficiencies occur. This paper offers the reader a powerful customer-centric tool, designed to help business managers highlight both what services are critical to customer quality perception, and where future innovation

A Framework for Exploring Multidimensional Data with 3D Projections

Visualization of high-dimensional data requires a mapping to a visual space. Whenever the goal is to preserve similarity relations a frequent strategy is to use 2D projections, which afford intuitive interactive exploration, e. g., by users locating and selecting groups and gradually drilling down to individual objects. In this paper, we propose a framework for projecting high-dimensional data to 3D visual spaces, based on a generalization of the Least-Square Projection (LSP). We compare projections to 2D and 3D visual spaces both quantitatively and through a user study considering certain exploration tasks. The quantitative analysis confirms that 3D projections outperform 2D projections in terms of precision. The user study indicates that certain tasks can be more reliably and confidently answered with 3D projections. Nonetheless, as 3D projections are displayed on 2D screens, interaction is more difficult. Therefore, we incorporate suitable interaction functionalities into a framework that supports 3D transformations, predefined optimal 2D views, coordinated 2D and 3D views, and hierarchical 3D cluster definition and exploration. For visually encoding data clusters in a 3D setup, we employ color coding of projected data points as well as four types of surface renderings. A second user study evaluates the suitability of these visual encodings. Several examples illustrate the framework`s applicability for both visual exploration of multidimensional abstract (non-spatial) data as well as the feature space of multi-variate spatial data.

An incremental space to visualize dynamic data sets

In Information Visualization, adding and removing data elements can strongly impact the underlying visual space. We have developed an inherently incremental technique (incBoard) that maintains a coherent disposition of elements from a dynamic multidimensional data set on a 2D grid as the set changes. Here, we introduce a novel layout that uses pairwise similarity from grid neighbors, as defined in incBoard, to reposition elements on the visual space, free from constraints imposed by the grid. The board continues to be updated and can be displayed alongside the new space. As similar items are placed together, while dissimilar neighbors are moved apart, it supports users in the identification of clusters and subsets of related elements. Densely populated areas identified in the incSpace can be efficiently explored with the corresponding incBoard visualization, which is not susceptible to occlusion. The solution remains inherently incremental and maintains a coherent disposition of elements, even for fully renewed sets. The algorithm considers relative positions for the initial placement of elements, and raw dissimilarity to fine tune the visualization. It has low computational cost, with complexity depending only on the size of the currently viewed subset, V. Thus, a data set of size N can be sequentially displayed in O(N) time, reaching O(N (2)) only if the complete set is simultaneously displayed.

Taking advantage of contextualized interactions while users watch TV

While watching TV, viewers use the remote control to turn the TV set on and off, change channel and volume, to adjust the image and audio settings, etc. Worldwide, research institutes collect information about audience measurement, which can also be used to provide personalization and recommendation services, among others. The interactive digital TV offers viewers the opportunity to interact with interactive applications associated with the broadcast program. Interactive TV infrastructure supports the capture of the user-TV interaction at fine-grained levels. In this paper we propose the capture of all the user interaction with a TV remote control-including short term and instant interactions: we argue that the corresponding captured information can be used to create content pervasively and automatically, and that this content can be used by a wide variety of services, such as audience measurement, personalization and recommendation services. The capture of fine grained data about instant and interval-based interactions also allows the underlying infrastructure to offer services at the same scale, such as annotation services and adaptative applications. We present the main modules of an infrastructure for TV-based services, along with a detailed example of a document used to record the user-remote control interaction. Our approach is evaluated by means of a proof-of-concept prototype which uses the Brazilian Digital TV System, the Ginga-NCL middleware.

Visual analysis of image collections

Multidimensional Visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces PEx-Image-Projection Explorer for Images-a tool aimed at supporting analysis of image collections. The tool supports a methodology that employs interactive visualizations to aid user-driven feature detection and classification tasks, thus offering improved analysis and exploration capabilities. The visual mappings employ similarity-based multidimensional projections and point placement to layout the data on a plane for visual exploration. In addition to its application to image databases, we also illustrate how the proposed approach can be successfully employed in simultaneous analysis of different data types, such as text and images, offering a common visual representation for data expressed in different modalities.

On modeling and evaluating multicomputer transcoding architectures for live-video streams

The pervasive and ubiquitous computing has motivated researches on multimedia adaptation which aims at matching the video quality to the user needs and device restrictions. This technique has a high computational cost which needs to be studied and estimated when designing architectures and applications. This paper presents an analytical model to quantify these video transcoding costs in a hardware independent way. The model was used to analyze the impact of transcoding delays in end-to-end live-video transmissions over LANs, MANs and WANs. Experiments confirm that the proposed model helps to define the best transcoding architecture for different scenarios.

Seamlessly integrating similarity queries in SQL

Modern database applications are increasingly employing database management systems (DBMS) to store multimedia and other complex data. To adequately support the queries required to retrieve these kinds of data, the DBMS need to answer similarity queries. However, the standard structured query language (SQL) does not provide effective support for such queries. This paper proposes an extension to SQL that seamlessly integrates syntactical constructions to express similarity predicates to the existing SQL syntax and describes the implementation of a similarity retrieval engine that allows posing similarity queries using the language extension in a relational DBM. The engine allows the evaluation of every aspect of the proposed extension, including the data definition language and data manipulation language statements, and employs metric access methods to accelerate the queries. Copyright (c) 2008 John Wiley & Sons, Ltd.

Generating Segmented Quality Meshes from Images

Techniques devoted to generating triangular meshes from intensity images either take as input a segmented image or generate a mesh without distinguishing individual structures contained in the image. These facts may cause difficulties in using such techniques in some applications, such as numerical simulations. In this work we reformulate a previously developed technique for mesh generation from intensity images called Imesh. This reformulation makes Imesh more versatile due to an unified framework that allows an easy change of refinement metric, rendering it effective for constructing meshes for applications with varied requirements, such as numerical simulation and image modeling. Furthermore, a deeper study about the point insertion problem and the development of geometrical criterion for segmentation is also reported in this paper. Meshes with theoretical guarantee of quality can also be obtained for each individual image structure as a post-processing step, a characteristic not usually found in other methods. The tests demonstrate the flexibility and the effectiveness of the approach.