20,595 research outputs found
Curated routes: the project of developing experiential tracks in sub-urban landscape
The Curated Routes project reflects on the visiting routes’ ability to make apparent the internal characteristics of urban environments. The project’s name allude to the intellectual function of curation and the materiality of routes. Curate deals with the practice of arranging material –tangible or intangible- in a way that a new understanding of an area is revealed. The word routes refers to the linear associations that link places and guide movement. The Curated Routes aim to reinforce the development of bonding ties between people and urban environments by re-constructing the way we visit and explore a place.
The overall goal of the project is to outline the conceptual guidelines of a visitors’ guide that could later be used for the development of the informatics model. The project follows the methodology that the context-aware routes apply, though particular attention is paid to the second phase of the process where an innovative approach is applied. The introduction of the “chronotope” filters enables us to “knit” the terrestrial route to a range of informative storylines, and hence to develop different interpretations of an urban environment
User-centred design of flexible hypermedia for a mobile guide: Reflections on the hyperaudio experience
A user-centred design approach involves end-users from the very beginning. Considering users at the early stages compels designers to think in terms of utility and usability and helps develop the system on what is actually needed. This paper discusses the case of HyperAudio, a context-sensitive adaptive and mobile guide to museums developed in the late 90s. User requirements were collected via a survey to understand visitors’ profiles and visit styles in Natural Science museums. The knowledge acquired supported the specification of system requirements, helping defining user model, data structure and adaptive behaviour of the system. User requirements guided the design decisions on what could be implemented by using simple adaptable triggers and what instead needed more sophisticated adaptive techniques, a fundamental choice when all the computation must be done on a PDA. Graphical and interactive environments for developing and testing complex adaptive systems are discussed as a further
step towards an iterative design that considers the user interaction a central point. The paper discusses
how such an environment allows designers and developers to experiment with different system’s behaviours and to widely test it under realistic conditions by simulation of the actual context evolving over time. The understanding gained in HyperAudio is then considered in the perspective of the
developments that followed that first experience: our findings seem still valid despite the passed time
Using stratified medicine to understand, diagnose, and treat neuropathic pain
Neuropathic pain (NeuP) is defined as pain arising from a lesion or disease of the somatosensory nervous system. NeuP is common, affecting approximately 6-8% of the general population and currently treatment is inadequate due to both poor drug efficacy and tolerability. Many different types of injury can cause neuropathic pain including genetic (e.g. SCN9A gain of function variants), metabolic (e.g. diabetic polyneuropathy), infective (e.g. HIV associated neuropathy, hepatitis), traumatic and toxic (e.g. chemotherapy induced neuropathy) causes. Such injurious events can impact on anatomically distinct regions of the somatosensory nervous system ranging from the terminals of nociceptive afferents (in small fiber neuropathy) to the thalamus (in post-stroke pain). Classification of neuropathic pain using etiology and location remains an important aspect of routine clinical practice; however, pain medicine is coming to the realization that we need more precision in this classification. The hope is that improved classification will lead to better understanding of risk, prognosis and optimal treatment of NeuP
Towards a Practical Pedestrian Distraction Detection Framework using Wearables
Pedestrian safety continues to be a significant concern in urban communities
and pedestrian distraction is emerging as one of the main causes of grave and
fatal accidents involving pedestrians. The advent of sophisticated mobile and
wearable devices, equipped with high-precision on-board sensors capable of
measuring fine-grained user movements and context, provides a tremendous
opportunity for designing effective pedestrian safety systems and applications.
Accurate and efficient recognition of pedestrian distractions in real-time
given the memory, computation and communication limitations of these devices,
however, remains the key technical challenge in the design of such systems.
Earlier research efforts in pedestrian distraction detection using data
available from mobile and wearable devices have primarily focused only on
achieving high detection accuracy, resulting in designs that are either
resource intensive and unsuitable for implementation on mainstream mobile
devices, or computationally slow and not useful for real-time pedestrian safety
applications, or require specialized hardware and less likely to be adopted by
most users. In the quest for a pedestrian safety system that achieves a
favorable balance between computational efficiency, detection accuracy, and
energy consumption, this paper makes the following main contributions: (i)
design of a novel complex activity recognition framework which employs motion
data available from users' mobile and wearable devices and a lightweight
frequency matching approach to accurately and efficiently recognize complex
distraction related activities, and (ii) a comprehensive comparative evaluation
of the proposed framework with well-known complex activity recognition
techniques in the literature with the help of data collected from human subject
pedestrians and prototype implementations on commercially-available mobile and
wearable devices
Moregrasp: Restoration of Upper Limb Function in Individuals with High Spinal Cord Injury by Multimodal Neuroprostheses for Interaction in Daily Activities
The aim of the MoreGrasp project is to develop a noninvasive, multimodal user interface including a brain-computer interface (BCI) for intuitive control of a grasp neuroprosthesis to support individuals with high spinal cord injury (SCI) in everyday activities. We describe the current state of the project, including the EEG system, preliminary results of natural movements decoding in people with SCI, the new electrode concept for the grasp neuroprosthesis, the shared control architecture behind the system and the implementation of a user-centered design
Machine Learning of User Profiles: Representational Issues
As more information becomes available electronically, tools for finding
information of interest to users becomes increasingly important. The goal of
the research described here is to build a system for generating comprehensible
user profiles that accurately capture user interest with minimum user
interaction. The research described here focuses on the importance of a
suitable generalization hierarchy and representation for learning profiles
which are predictively accurate and comprehensible. In our experiments we
evaluated both traditional features based on weighted term vectors as well as
subject features corresponding to categories which could be drawn from a
thesaurus. Our experiments, conducted in the context of a content-based
profiling system for on-line newspapers on the World Wide Web (the IDD News
Browser), demonstrate the importance of a generalization hierarchy and the
promise of combining natural language processing techniques with machine
learning (ML) to address an information retrieval (IR) problem.Comment: 6 page
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