1,019 research outputs found

    Mobile heritage practices. Implications for scholarly research, user experience design, and evaluation methods using mobile apps.

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    Mobile heritage apps have become one of the most popular means for audience engagement and curation of museum collections and heritage contexts. This raises practical and ethical questions for both researchers and practitioners, such as: what kind of audience engagement can be built using mobile apps? what are the current approaches? how can audience engagement with these experience be evaluated? how can those experiences be made more resilient, and in turn sustainable? In this thesis I explore experience design scholarships together with personal professional insights to analyse digital heritage practices with a view to accelerating thinking about and critique of mobile apps in particular. As a result, the chapters that follow here look at the evolution of digital heritage practices, examining the cultural, societal, and technological contexts in which mobile heritage apps are developed by the creative media industry, the academic institutions, and how these forces are shaping the user experience design methods. Drawing from studies in digital (critical) heritage, Human-Computer Interaction (HCI), and design thinking, this thesis provides a critical analysis of the development and use of mobile practices for the heritage. Furthermore, through an empirical and embedded approach to research, the thesis also presents auto-ethnographic case studies in order to show evidence that mobile experiences conceptualised by more organic design approaches, can result in more resilient and sustainable heritage practices. By doing so, this thesis encourages a renewed understanding of the pivotal role of these practices in the broader sociocultural, political and environmental changes.AHRC REAC

    2017 GREAT Day Program

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    SUNY Geneseo’s Eleventh Annual GREAT Day.https://knightscholar.geneseo.edu/program-2007/1011/thumbnail.jp

    Autonomous Radar-based Gait Monitoring System

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    Features related to gait are fundamental metrics of human motion [1]. Human gait has been shown to be a valuable and feasible clinical marker to determine the risk of physical and mental functional decline [2], [3]. Technologies that detect changes in people’s gait patterns, especially older adults, could support the detection, evaluation, and monitoring of parameters related to changes in mobility, cognition, and frailty. Gait assessment has the potential to be leveraged as a clinical measurement as it is not limited to a specific health care discipline and is a consistent and sensitive test [4]. A wireless technology that uses electromagnetic waves (i.e., radar) to continually measure gait parameters at home or in a hospital without a clinician’s participation has been proposed as a suitable solution [3], [5]. This approach is based on the interaction between electromagnetic waves with humans and how their bodies impact the surrounding and scattered wireless signals. Since this approach uses wireless waves, people do not need to wear or carry a device on their bodies. Additionally, an electromagnetic wave wireless sensor has no privacy issues because there is no video-based camera. This thesis presents the design and testing of a radar-based contactless system that can monitor people’s gait patterns and recognize their activities in a range of indoor environments frequently and accurately. In this thesis, the use of commercially available radars for gait monitoring is investigated, which offers opportunities to implement unobtrusive and contactless gait monitoring and activity recognition. A novel fast and easy-to-implement gait extraction algorithm that enables an individual’s spatiotemporal gait parameter extraction at each gait cycle using a single FMCW (Frequency Modulated Continuous Wave) radar is proposed. The proposed system detects changes in gait that may be the signs of changes in mobility, cognition, and frailty, particularly for older adults in individual’s homes, retirement homes and long-term care facilities retirement homes. One of the straightforward applications for gait monitoring using radars is in corridors and hallways, which are commonly available in most residential homes, retirement, and long-term care homes. However, walls in the hallway have a strong “clutter” impact, creating multipath due to the wide beam of commercially available radar antennas. The multipath reflections could result in an inaccurate gait measurement because gait extraction algorithms employ the assumption that the maximum reflected signals come from the torso of the walking person (rather than indirect reflections or multipath) [6]. To address the challenges of hallway gait monitoring, two approaches were used: (1) a novel signal processing method and (2) modifying the radar antenna using a hyperbolic lens. For the first approach, a novel algorithm based on radar signal processing, unsupervised learning, and a subject detection, association and tracking method is proposed. This proposed algorithm could be paired with any type of multiple-input multiple-output (MIMO) or single-input multiple-output (SIMO) FMCW radar to capture human gait in a highly cluttered environment without needing radar antenna alteration. The algorithm functionality was validated by capturing spatiotemporal gait values (e.g., speed, step points, step time, step length, and step count) of people walking in a hallway. The preliminary results demonstrate the promising potential of the algorithm to accurately monitor gait in hallways, which increases opportunities for its applications in institutional and home environments. For the second approach, an in-package hyperbola-based lens antenna was designed that can be integrated with a radar module package empowered by the fast and easy-to-implement gait extraction method. The system functionality was successfully validated by capturing the spatiotemporal gait values of people walking in a hallway filled with metallic cabinets. The results achieved in this work pave the way to explore the use of stand-alone radar-based sensors in long hallways for day-to-day long-term monitoring of gait parameters of older adults or other populations. The possibility of the coexistence of multiple walking subjects is high, especially in long-term care facilities where other people, including older adults, might need assistance during walking. GaitRite and wearables are not able to assess multiple people’s gait at the same time using only one device [7], [8]. In this thesis, a novel radar-based algorithm is proposed that is capable of tracking multiple people or extracting walking speed of a participant with the coexistence of other people. To address the problem of tracking and monitoring multiple walking people in a cluttered environment, a novel iterative framework based on unsupervised learning and advanced signal processing was developed and tested to analyze the reflected radio signals and extract walking movements and trajectories in a hallway environment. Advanced algorithms were developed to remove multipath effects or ghosts created due to the interaction between walking subjects and stationary objects, to identify and separate reflected signals of two participants walking at a close distance, and to track multiple subjects over time. This method allows the extraction of walking speed in multiple closely-spaced subjects simultaneously, which is distinct from previous approaches where the speed of only one subject was obtained. The proposed multiple-people gait monitoring was assessed with 22 participants who participated in a bedrest (BR) study conducted at McGill University Health Centre (MUHC). The system functionality also was assessed for in-home applications. In this regard, a cloud-based system is proposed for non-contact, real-time recognition and monitoring of physical activities and walking periods within a domestic environment. The proposed system employs standalone Internet of Things (IoT)-based millimeter wave radar devices and deep learning models to enable autonomous, free-living activity recognition and gait analysis. Range-Doppler maps generated from a dataset of real-life in-home activities are used to train deep learning models. The performance of several deep learning models was evaluated based on accuracy and prediction time, with the gated recurrent network (GRU) model selected for real-time deployment due to its balance of speed and accuracy compared to 2D Convolutional Neural Network Long Short-Term Memory (2D-CNNLSTM) and Long Short-Term Memory (LSTM) models. In addition to recognizing and differentiating various activities and walking periods, the system also records the subject’s activity level over time, washroom use frequency, sleep/sedentary/active/out-of-home durations, current state, and gait parameters. Importantly, the system maintains privacy by not requiring the subject to wear or carry any additional devices

    The cultural significance of Shakespeare on screen in the Twenty-First Century

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    The thesis explores twenty-first-century adaptations and appropriations of Shakespeare on screen, spanning cinema, television and online productions. It considers how a range of screen productions, spanning different mediums, aesthetics, languages and intended audiences, create cultural artefacts of the times in which they were made. The opening three chapters explore representations of British national identity, and how adaptations of different Shakespeare plays have reflected, interrogated and unpicked ‘Britishness’ in the opening decades of the 2000s. These chapters consider in turn: the BBC series The Hollow Crown: The Wars of the Roses (dir. Cooke, 2016) and its existence within the cultural moment of Britain’s vote to leave the EU; the different approaches to adapting Coriolanus in Ralph Fiennes’s 2011 Hollywood-style action film and Ben Wheatley’s disorienting anti-Hollywood deconstruction of the play in Happy New Year, Colin Burstead (2018), set in post-Brexit Britain; and the ways in which British culture, heritage and nostalgia are woven into adaptations of Romeo and Juliet in Kelly Asbury’s 2011 computer-animated film Gnomeo & Juliet and Carlo Carlei’s 2013 film, scripted by Julian Fellowes. The closing three chapters analyse screen adaptations through the lens of metamodernism, a structure of feeling proposed as the twenty-first-century successor to late twentieth-century postmodernism, which oscillates between sensibilities characterised by postmodern irony and detachment and a return to sincerity and affective connection. These chapters consider in turn: adaptations of King Lear in The King is Alive (dir. Levring, 2000) and Lear’s Shadow (dir. Elerding, 2018), and how they reclaim the play from its position of bleakness and nihilism during the closing decades of the twentieth century; the intersections of documentary authenticity and cinematic artifice in two non-Anglophone films, Makibefo (dir. Abela, 2000) and Caesar Must Die (dirs. Taviani and Taviani, 2012), which adapt Macbeth and Julius Caesar respectively; and the ways in which A Midsummer Night’s Dream was adapted in four different online productions created in 2020 under lockdown restrictions during the COVID-19 pandemic, which blend postmodern pop culture referentiality with affective sincerity. Throughout all six chapters, the thesis analyses the ways in which screen adaptations of Shakespeare – within the related but distinct media of film, television and digital theatre – have responded to the cultural and historical moment surrounding their production. It also explores what Shakespeare is doing within these mediums, and the ways in which the adaptive potential and cultural capital of Shakespeare on screen has developed from its position at the end of the twentieth century

    Inclusive and Safe Mobility Needs of Senior Citizens: Implications for Age-Friendly Cities and Communities

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    Municipalities are concerned with addressing social issues such as mobility inclusion and safety by increasing access to transport facilities and services for all groups in society to create equitable and equal access for all citizens. Moreover, the public transportation systems provided in cities have to be inclusive and safe, driven by emerging technologies such as Artificial Intelligence (AI)-based services that provide personalized recommendation to improve mobility inclusion and safety for all citizens in society, especially vulnerable road users such as senior citizens or older people. But at the moment, there are few studies that have investigated how municipalities can provide inclusive and safe public transportation in general and for senior citizens, particularly those aged 65 and above. Therefore, this study aimed to examine how to provide inclusive and safe mobility for senior citizens to improve out-of-home mobility services for senior citizens towards age-friendly cities and communities. Accordingly, a systematic literature review grounded on secondary data was adopted to investigate inclusive and safe mobility needs for senior citizens. The data were collected from previous research and existing documents, and a descriptive data analysis was carried out to provide insights on urban transportation policies related to senior citizens. Furthermore, case studies were adopted to present polices and strategies employed in Norway, Canada, the United States of America, the United Kingdom, Sweden, and Northern Ireland to identify measures employed to address the public transportation needs of an aging society, focusing on the provision of inclusive and safe mobility to senior citizens. Further findings from this study included the possible use of emerging technologies such as AI-based machine learning for inclusive and safe mobility.publishedVersio

    interActive Environments: Designing interactions to support active behaviors in urban public space

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    Alumni Journal - Volume 94, Number 2

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    Editorials2 | From the Editor4 | From the President6 | From the Dean News8 | School of Medicine News10 | Alumni News12 | This & That13 | Students14 | AIMS Report: Impacting Lives16 | Department Report: Surgery Graduation 202321 | Graduation Feature Features38 | By the Graduates: Reflections and stories form graduates44 | Honoring Two Epochal Leaders46 | I Died Four Times50 | Alumni Association: A Power for Good54 | Alumni Spotlight: Get to know56 | Life After Medicine In Memoriam57 | Alumni Remembered: Featured obituaries - Robert D. Mitchell \u2747, Lloyd A. Dayes \u2759https://scholarsrepository.llu.edu/sm-alumni-journal/1039/thumbnail.jp
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