346 research outputs found

    Exploring Perovskite Photodiodes:Device Physics and Applications

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    The 2023 wearable photoplethysmography roadmap

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    Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology

    Graphonomics and your Brain on Art, Creativity and Innovation : Proceedings of the 19th International Graphonomics Conference (IGS 2019 – Your Brain on Art)

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    [Italiano]: “Grafonomia e cervello su arte, creatività e innovazione”. Un forum internazionale per discutere sui recenti progressi nell'interazione tra arti creative, neuroscienze, ingegneria, comunicazione, tecnologia, industria, istruzione, design, applicazioni forensi e mediche. I contributi hanno esaminato lo stato dell'arte, identificando sfide e opportunità, e hanno delineato le possibili linee di sviluppo di questo settore di ricerca. I temi affrontati includono: strategie integrate per la comprensione dei sistemi neurali, affettivi e cognitivi in ambienti realistici e complessi; individualità e differenziazione dal punto di vista neurale e comportamentale; neuroaesthetics (uso delle neuroscienze per spiegare e comprendere le esperienze estetiche a livello neurologico); creatività e innovazione; neuro-ingegneria e arte ispirata dal cervello, creatività e uso di dispositivi di mobile brain-body imaging (MoBI) indossabili; terapia basata su arte creativa; apprendimento informale; formazione; applicazioni forensi. / [English]: “Graphonomics and your brain on art, creativity and innovation”. A single track, international forum for discussion on recent advances at the intersection of the creative arts, neuroscience, engineering, media, technology, industry, education, design, forensics, and medicine. The contributions reviewed the state of the art, identified challenges and opportunities and created a roadmap for the field of graphonomics and your brain on art. The topics addressed include: integrative strategies for understanding neural, affective and cognitive systems in realistic, complex environments; neural and behavioral individuality and variation; neuroaesthetics (the use of neuroscience to explain and understand the aesthetic experiences at the neurological level); creativity and innovation; neuroengineering and brain-inspired art, creative concepts and wearable mobile brain-body imaging (MoBI) designs; creative art therapy; informal learning; education; forensics

    Moving usable security research out of the lab: evaluating the use of VR studies for real-world authentication research

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    Empirical evaluations of real-world research artefacts that derive results from observations and experiments are a core aspect of usable security research. Expert interviews as part of this thesis revealed that the costs associated with developing and maintaining physical research artefacts often amplify human-centred usability and security research challenges. On top of that, ethical and legal barriers often make usability and security research in the field infeasible. Researchers have begun simulating real-life conditions in the lab to contribute to ecological validity. However, studies of this type are still restricted to what can be replicated in physical laboratory settings. Furthermore, historically, user study subjects were mainly recruited from local areas only when evaluating hardware prototypes. The human-centred research communities have recognised and partially addressed these challenges using online studies such as surveys that allow for the recruitment of large and diverse samples as well as learning about user behaviour. However, human-centred security research involving hardware prototypes is often concerned with human factors and their impact on the prototypes’ usability and security, which cannot be studied using traditional online surveys. To work towards addressing the current challenges and facilitating research in this space, this thesis explores if – and how – virtual reality (VR) studies can be used for real-world usability and security research. It first validates the feasibility and then demonstrates the use of VR studies for human-centred usability and security research through six empirical studies, including remote and lab VR studies as well as video prototypes as part of online surveys. It was found that VR-based usability and security evaluations of authentication prototypes, where users provide touch, mid-air, and eye-gaze input, greatly match the findings from the original real-world evaluations. This thesis further investigated the effectiveness of VR studies by exploring three core topics in the authentication domain: First, the challenges around in-the-wild shoulder surfing studies were addressed. Two novel VR shoulder surfing methods were implemented to contribute towards realistic shoulder surfing research and explore the use of VR studies for security evaluations. This was found to allow researchers to provide a bridge over the methodological gap between lab and field studies. Second, the ethical and legal barriers when conducting in situ usability research on authentication systems were addressed. It was found that VR studies can represent plausible authentication environments and that a prototype’s in situ usability evaluation results deviate from traditional lab evaluations. Finally, this thesis contributes a novel evaluation method to remotely study interactive VR replicas of real-world prototypes, allowing researchers to move experiments that involve hardware prototypes out of physical laboratories and potentially increase a sample’s diversity and size. The thesis concludes by discussing the implications of using VR studies for prototype usability and security evaluations. It lays the foundation for establishing VR studies as a powerful, well-evaluated research method and unfolds its methodological advantages and disadvantages

    Learning-Based Ubiquitous Sensing For Solving Real-World Problems

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    Recently, as the Internet of Things (IoT) technology has become smaller and cheaper, ubiquitous sensing ability within these devices has become increasingly accessible. Learning methods have also become more complex in the field of computer science ac- cordingly. However, there remains a gap between these learning approaches and many problems in other disciplinary fields. In this dissertation, I investigate four different learning-based studies via ubiquitous sensing for solving real-world problems, such as in IoT security, athletics, and healthcare. First, I designed an online intrusion detection system for IoT devices via power auditing. To realize the real-time system, I created a lightweight power auditing device. With this device, I developed a distributed Convolutional Neural Network (CNN) for online inference. I demonstrated that the distributed system design is secure, lightweight, accurate, real-time, and scalable. Furthermore, I characterized potential Information-stealer attacks via power auditing. To defend against this potential exfiltration attack, a prototype system was built on top of the botnet detection system. In a testbed environment, I defined and deployed an IoT Information-stealer attack. Then, I designed a detection classifier. Altogether, the proposed system is able to identify malicious behavior on endpoint IoT devices via power auditing. Next, I enhanced athletic performance via ubiquitous sensing and machine learning techniques. I first designed a metric called LAX-Score to quantify a collegiate lacrosse team’s athletic performance. To derive this metric, I utilized feature selection and weighted regression. Then, the proposed metric was statistically validated on over 700 games from the last three seasons of NCAA Division I women’s lacrosse. I also exam- ined the biometric sensing dataset obtained from a collegiate team’s athletes over the course of a season. I then identified the practice features that are most correlated with high-performance games. Experimental results indicate that LAX-Score provides insight into athletic performance quality beyond wins and losses. Finally, I studied the data of patients with Parkinson’s Disease. I secured the Inertial Measurement Unit (IMU) sensing data of 30 patients while they conducted pre-defined activities. Using this dataset, I measured tremor events during drawing activities for more convenient tremor screening. Our preliminary analysis demonstrates that IMU sensing data can identify potential tremor events in daily drawing or writing activities. For future work, deep learning-based techniques will be used to extract features of the tremor in real-time. Overall, I designed and applied learning-based methods across different fields to solve real-world problems. The results show that combining learning methods with domain knowledge enables the formation of solutions

    Exploring Perovskite Photodiodes:Device Physics and Applications

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    An Outlook into the Future of Egocentric Vision

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    What will the future be? We wonder! In this survey, we explore the gap between current research in egocentric vision and the ever-anticipated future, where wearable computing, with outward facing cameras and digital overlays, is expected to be integrated in our every day lives. To understand this gap, the article starts by envisaging the future through character-based stories, showcasing through examples the limitations of current technology. We then provide a mapping between this future and previously defined research tasks. For each task, we survey its seminal works, current state-of-the-art methodologies and available datasets, then reflect on shortcomings that limit its applicability to future research. Note that this survey focuses on software models for egocentric vision, independent of any specific hardware. The paper concludes with recommendations for areas of immediate explorations so as to unlock our path to the future always-on, personalised and life-enhancing egocentric vision.Comment: We invite comments, suggestions and corrections here: https://openreview.net/forum?id=V3974SUk1
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