219 research outputs found
Technologie en gedragsverandering bij ouderen
No full textTechnologie wordt steeds vaker ingezet, maar werkt het ook? Sumit Mehra legt uit hoe wetenschappelijke inzichten vertaald kunnen worden naar een blended aanpak om gedragsverandering te realiseren. Hij licht dit toe aan de hand van het VITAMINE project waarbij ouderen met behulp van een tablet en e-coaching worden ondersteund om thuis een functioneel oefenprogramma te volgen dat is toegesneden op de individuele situatie
Tailored interactive technology for a healthy lifestyle
No full textDuring the persuasive technology symposium, Marije Deutekom - Baart de la Faille and colleagues organised a symposium session with 4 presentations: • Presentation 1: A home based exercise program: are older adults able to use mHealth technology? (Sumit Mehra). • Presentation 2: Promoting healthy diet and physical activity in children through the use of games: bridging the gap between industry and science (Monique Simons). • Presentation 3: Increased motivation for exercise through exercise apps such as BAMBEA (Joey van der Bie & Nicky Nibbeling) • Presentation 4: Which factors are important for effectiveness of sport- and health-related apps? Results of focus groups with experts (Joan Dallinga)
Performance analysis of the WiNC2R platform:
No full textA Cognitive Radio (CR) is an intelligent transceiver device, able to support multiple technologies, dynamic re-configurability, ease of programming and collaboration with other CR devices to improve the communication efficiency. The two key requirements for an efficient CR implementation are flexibility in operation/programming and speed.
WiNC2R (Winlab Network Centric Cognitive Radio) achieves high speed of operation using its hardware platform and flexibility using its software-configurable architecture. The current WiNC2R architecture implements an 802.11a-like OFDM flow. We evaluate the WiNC2R hardware architecture to see the modularity in the architecture, separation of data and control flow and the performance in terms of latency and throughput. To test the system, the Xilinx Bus Functional Model environment, which is designed to test the IBM standard bus-architecture-based hardware systems, is used. We use a simple ALOHA protocol in the MAC layer to communicate between two WiNC2R nodes and evaluate the performance under the best-case scenario, where the performance is only hindered by the architecture itself rather than external conditions like channel state.
The results of our basic experiments showed that for a single OFDM 802.11a-like flow, the Unit Control Modules (UCM) were idle for almost 80% of the total processing time.
We then tested the WiNC2R system to study the effects of changing the frame size. It was seen that the latencies in the WiNC2R transmitter are frame-size dependent while those in the receiver mainly depend on the size of the data in the last chunk rather than the size of the whole frame. We suggest that chunk size should be 2 OFDM symbols, and chunking be moved to MAC layer for better performance. We give analytical estimates of resulting performance improvement. In the next experiment, we describe virtualization in the WiNC2R by adding more flows. We describe the steps to implement the additional flows and estimate maximum number of concurrent flows possible.
In the last analysis, we show the effect of operating clock frequency on the performance. We prove that at 250 MHz operating frequency and 2 OFDM symbols per chunk, the current WiNC2R implementation will be able to satisfy the SIFS criterion.M.S.Includes bibliographical references (p. 72-73)by Sumit Satarka
Development and evaluation of a blended home-based exercise intervention for older adults
No full textAging is associated with a decline in the ability to carry out daily tasks. Physical activity can delay or diminish the decline and increase the ability of older adults to live independently at home. Performing home-based exercises can help older adults achieve the recommended levels of physical activity. Technology allows exercise programs to be tailored to individual needs. This thesis describes a blended intervention that was developed and evaluated according to the Medical Research Council framework. The principal findings are that older adults are motivated to perform technology-supported home-based exercises if they help them maintain self-reliance and there is sufficient guidance, safety is taken into account, and adherence is stimulated. To meet those conditions, a blended intervention was developed that was based on functional exercises, behavior change theory and human guidance. A custom-made tablet application appears to be usable by the target audience. A process evaluation has shown that the tablet as well as the coach support older adults in the various phases of self-regulating their exercise behavior. The blended intervention stimulates intrinsic motivation by supporting the autonomy of participants, fostering competence and, for some, meeting the need for relatedness by offering emotional support. Data derived from the tablet demonstrate that older adults participating in the intervention exhibit exercise behavior that is in line with WHO guidelines and that engagement with the tablet was a contributing factor. Future work should include assessment of intervention fidelity and explore which aspects of coaching can and cannot be further automated
Harnessing the potential of persuasive technology: getting older adults to exercise more with a blended intervention
No full textHarnessing the potential of persuasive technology:: Getting Older Adults to Exercise at Home with a Blended Intervention
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Query optimization in mobile environments
No full textWe consider the issue of optimizing queries for distributed processing in mobile environment. An interesting characteristic of mobile machines is that they depend on battery as a source of energy which may not be substantial enough. Hence, the appropriate optimization criterion in a mobile environment considers both resource utilization and energy consum- ption at the mobile client.
In this scenario, the optimal plan for a query depends on the residual battery level of the mobile client and the load at the server. We approach this problem by compiling a query into a sequence of candidate plans, such that for any state of the client-server system, the optimal plan is one of the candidate plans.
A general solution is proposed by adapting the partial order dynamic programming search algorithm (p.o dp) such that the coverset of the query is the set of candidate plans. We propose two novel algorithms, namely, the linear combinations algorithm and the linearset algorithm (referred to as the linear algorithms) that compute the linearset of a query. The linear- set of a query is an approximation to the coverset returned by p.o. dp.
We show, by means of simulation, that (1) the linearset is an excellent approximation of the coverset, (2) query compilation using the linear algorithms outperform query compilation using p.o. dp by factors ranging from 2 to 9, (3) the time taken to compile queries using the linear algorithms for the general optimization criterion is at most twice the time taken by a System R* like standard query optimizer search algorithm, and (4) the run time overhead incurred by the linear algorithms technique is minimal.
The techniques presented in the paper are of general applicability to multi-criterion optimization problems in distributed databases, where each criterion is an additive metric.Technical report lcsr-tr-21
Interactive machine learning for complex graphics selection
No full textThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 89-91).Modern vector graphics editors support the creation of a wonderful variety of complex designs and artwork. Users produce highly realistic illustrations, stylized representational art, even nuanced data visualizations. In light of these complex graphics, selections, representations of sets of objects that users want to manipulate, become more complex as well. Direct manipulation tools that artists and designers find accessible and useful for editing graphics such as logos and icons do not have the same applicability in these more complex cases. Given that selection is the first step for nearly all editing in graphics, it is important to enable artists and designers to express these complex selections. This thesis explores the use of interactive machine learning techniques to improve direct selection interfaces. To investigate this approach, I created Insight, an interactive machine learning selection tool for making a relevant class of complex selections: visually similar objects. To make a selection, users iteratively provide examples of selection objects by clicking on them in the graphic. Insight infers a selection from the examples at each step, allowing users to quickly understand results of actions and reactively shape the complex selection. The interaction resembles the direct manipulation interactions artists and designers have found accessible, while helping express complex selections by inferring many parameter changes from simple actions. I evaluated Insight in a user study of digital designers and artists, finding that Insight enabled users to effectively and easily make complex selections not supported by state-of-the-art vector graphics editors. My results contribute to existing work by both indicating a useful approach for providing complex representation access to artists and designers, and showing a new application for interactive machine learning.by Sumit Gogia.M. Eng
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