1,739 research outputs found

    Cultures of Citizenship in the Twenty-First Century: Literary and Cultural Perspectives on a Legal Concept

    Get PDF
    In the early twenty-first century, the concept of citizenship is more contested than ever. As refugees set out to cross the Mediterranean, European nation-states refer to "cultural integrity" and "immigrant inassimilability," revealing citizenship to be much more than a legal concept. The contributors to this volume take an interdisciplinary approach to considering how cultures of citizenship are being envisioned and interrogated in literary and cultural (con)texts. Through this framework, they attend to the tension between the citizen and its spectral others - a tension determined by how a country defines difference at a given moment

    2007 GREAT Day Program

    Get PDF
    SUNY Geneseo’s First Annual G.R.E.A.T. Day.https://knightscholar.geneseo.edu/program-2007/1001/thumbnail.jp

    Autonomous Radar-based Gait Monitoring System

    Get PDF
    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

    Amplifying the Music Listening Experience through Song Comments on Music Streaming Platforms

    Full text link
    Music streaming services are increasingly popular among younger generations who seek social experiences through personal expression and sharing of subjective feelings in comments. However, such emotional aspects are often ignored by current platforms, which affects the listeners' ability to find music that triggers specific personal feelings. To address this gap, this study proposes a novel approach that leverages deep learning methods to capture contextual keywords, sentiments, and induced mechanisms from song comments. The study augments a current music app with two features, including the presentation of tags that best represent song comments and a novel map metaphor that reorganizes song comments based on chronological order, content, and sentiment. The effectiveness of the proposed approach is validated through a usage scenario and a user study that demonstrate its capability to improve the user experience of exploring songs and browsing comments of interest. This study contributes to the advancement of music streaming services by providing a more personalized and emotionally rich music experience for younger generations.Comment: In the Proceedings of ChinaVis 202

    Electron Thermal Runaway in Atmospheric Electrified Gases: a microscopic approach

    Get PDF
    Thesis elaborated from 2018 to 2023 at the Instituto de AstrofĂ­sica de AndalucĂ­a under the supervision of Alejandro Luque (Granada, Spain) and Nikolai Lehtinen (Bergen, Norway). This thesis presents a new database of atmospheric electron-molecule collision cross sections which was published separately under the DOI : With this new database and a new super-electron management algorithm which significantly enhances high-energy electron statistics at previously unresolved ratios, the thesis explores general facets of the electron thermal runaway process relevant to atmospheric discharges under various conditions of the temperature and gas composition as can be encountered in the wake and formation of discharge channels

    Proceedings of the 25th Bilateral Student Workshop CTU Prague and HTW Dresden - User Interfaces & Visualization

    Get PDF
    This technical report publishes the proceedings of the 25th Bilateral Student Workshop CTU Prague and HTW Dresden - User Interfaces & Visualization -, which was held on the 25th and 26th November 2021. The workshop offers a possibility for young scientists to present their current research work in the fields of computer graphics, human-computer-interaction, robotics and usability. The works is meant as a platform to bring together researchers from both the Czech Technical University in Prague (CTU) and the University of Applied Sciences Dresden (HTW). The German Academic Exchange Service offers its financial support to allow student participants the bilateral exchange between Prague and Dresden.:1) Multiprojection of Langweil´s model, p.4 2) Design of an assistant for persons interested in study at CTU FEE, p.8 3) Sonification of a juggling performance, p.12 4) Investigating the Role of Usability User Experience and Aesthetics for Industrial Human–Machine Interfaces, p.16 5) Using optically illusive architecture to navigate users in Virtual Reality, p.23 6) Speed and Required Precision of Grabbing Physical Spheres in VR, p.27 7) ReFlex - A Framework for Research on Elastic Displays, p.32 8) Digital Reading Stand (DRS), p.38 9) IDOVIR – Infrastructure for Documentation of Virtual Reconstructions, p.45 10) Tracking multiple VR users in a shared physical space, p.50 11) Towards Aesthetics of Subjectivity in InfoVis, p.53 12) VentConnect: live to life and the octopus in the hospital server room, p.60 13) Nice noise: background noise enhancement with generated musical content, p.66 14) Parametric Curve Labeling, p.7

    Norman M. Klein's "Bleeding Through: Layers of Los Angeles": An Updated Edition 20 Years Later

    Get PDF
    In 2003, Norman M. Klein's docufable "Bleeding Through" raised questions of urban aesthetics and memory as part of the multimedia documentary "Bleeding Through: Layers of Los Angeles, 1920-1986." Now, 20 years later, this important text is reissued along with several essays addressing its central themes, such as the aesthetics and politics of urban memory, the development of Los Angeles since the 20th century, the role of urban imaginaries in US politics, or media evolution in the 21st century. The volume also features a long interview with Klein and two docufables from Klein's celebrated study "The History of Forgetting: Los Angeles and the Erasure of Memory", one being the kernel of the novella, the other imagining Walter Benjamin in L.A. Finally, the book contains links to two films featuring much of the multimedia material contained in the first edition

    Undergraduate and Graduate Course Descriptions, 2023 Spring

    Get PDF
    Wright State University undergraduate and graduate course descriptions from Spring 2023

    Enabling the Integration of Sustainable Design Methodological Frameworks and Computational Life Cycle Assessment Tools into Product Development Practice

    Get PDF
    Environmental sustainability has gained critical importance in product development (PD) due to increased regulation, market competition, and consumer awareness, leading companies to set ambitious climate targets . To meet these goals, PD practitioners (engineers and designers) are often left to adapt their practices to reduce the impacts of the products they manufacture. Literature review and interviews with practitioners show that they highly valued using quantitative life cycle assessment (LCA) results to inform decision making. LCA is a technique to measure the environmental impacts across various stages of a product life cycle. Existing LCA software tools, however, are designed for dedicated experts to use at the end of PD using detailed product information. This creates the “ecodesign paradox”, a tension between opportunity for change in the early-stages of PD and availability of data in later stages to make reliable decisions. Further, my research identified that novice users of LCA face additional barriers including: cumbersome user interfaces, unfamiliar terminology, and complicated information visualization. To address these challenges, I developed a tool called EcoSketch for use during early-stage PD by novice users. Practitioners, however, also struggle with translating environmental impact information into actionable design decisions. Hence, I co-created methodological frameworks of sustainable design strategies with industry partners: Synapse Product Development Inc. and Stanley Black and Decker Inc. Despite contextual differences, a key commonality was that practitioners at both firms sought “structured” and “data-driven\u27\u27 processes for sustainable design. Through multiple, extended internships, I also identified important drivers and barriers to sustainable design integration. Overall, my research demonstrates that co-creation improves receptivity, long-term adoption, and produces tangible improvements to sustainable outcomes in practice. In summary, my research pursues two key pathways to enable sustainable design integration: Developing human-centered life cycle assessment (LCA) tools that are designed for decision-making during the early stages of PD. Creating methodological frameworks to support the application of appropriate sustainable design strategies in PD practice. This thesis elaborates on my proposed coupling of robust frameworks with human-centered LCA tools, which I argue together comprise a transformative solution for industry professionals to effectively integrate sustainability considerations in their product development practices
    • …
    corecore