4,011 research outputs found

    Harbingers of A New Age: Irish and Scots Irish Indian Fighters on the Colonial American Frontier

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    Through the examination of various points of Irish and Scots Irish settlement in the New World, a previously underrepresented portion of American history emerges to tell the story of a hearty and industrious people who literally went out into the wilderness and settled their own communities. Through their hard work and enterprising nature, they were able to not only survive in the face of extreme adversity on the frontier, but they preserved their culture for generations and contributed to the cultural, political, military, religious, and environmental influences that shaped the New World and the American nation. Their martial prowess and military ingenuity enabled them to survive through frontier warfare, and to emerge as highly valued soldiers in North America. In doing so, they created an identity that has come to be known as uniquely American. Through an understanding of the history of the Irish history and the evolution of Irish Indian Fighters in the New World, a unique perspective of American history comes to light

    PRIVACY’S NEXT ACT

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    This Article identifies and describes three data privacy policy developments from recent legislative sessions that may seem unrelated, but which I contend together offer clues about privacy law’s future over the short-to-medium term. The first is the proliferation, worldwide and in U.S. states, of legislative proposals and statutes referred to as “age-appropriate design codes.” Originating in the United Kingdom, age-appropriate design codes typically apply to online services “directed to children” and subject such services to transparency, default settings, and other requirements. Chief among them is an implied obligation to conduct ongoing assessments of whether a service could be deemed “directed to children” such that it triggers application of the codes. The second development is a well-documented push for responsible artificial intelligence (“AI”) practices in the form of new transparency and accountability frameworks. The most comprehensive such framework is the European Union’s AI Act, although similar reforms in Canada, as well as nascent reforms here in the United States, address analogous topics. Among these are requirements for AI developers to assess, document, and, in some instances, report to regulators the existence of potential harms and plans to mitigate them prior to launching a new AI-driven product or service. The third development, certain reforms to competition policies, is least likely to be traditionally counted among “privacy” laws. However, I argue that two recent reforms in Europe—the Digital Services Act and the Digital Markets Act—implicate data privacy concerns and should be viewed as imposing privacy-related compliance obligations. For instance, these frameworks address the use of personal data, including sensitive personal information, for online advertising purposes. My argument is that common threads across these developments underscore the dynamism of privacy law at a critical moment in its development and highlight the increased public awareness of the benefits––and risks––of a data-driven economy and society. To that end, I identify three specific trends among these developments that I anticipate recurring in data privacy policy proposals over privacy’s “next act.” First, legislators and regulators alike appear increasingly focused on age verification technologies as a mechanism for distinguishing between internet users and determining to whom they must provide certain protections. Second, there is a growing appetite for shifting assessment obligations onto regulated entities, albeit with guidance, and requiring that the results of such assessments are affirmatively disclosed to regulators. Third, privacy obligations are no longer limited to data privacy laws. They are increasingly found in other types of policy proposals––and detecting them will require a broader view of what constitutes a “privacy” law than typical among privacy professionals

    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

    County-Level Trends and Potential Disparities in the Suicide Rates in Virginia, 2020 – 2022

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    Abstract Objectives This study aims to investigate the influence of social determinants of health (SDH) on suicide patterns in the state of Virginia. Methods A secondary statistical analysis was conducted using publicly accessible data from the County Health Rankings & Roadmaps database for Virginia. Data from 2020 to 2022 were analyzed, focusing on age-adjusted suicide rates and SDH factors, including % rural, mental health provider rate, median household income, high school completion, and unemployment rates. Multiple regression analysis and visualizations were employed for data interpretation. Results The analysis revealed that SDH factors significantly predicted suicide rates across the study period. Median household income consistently emerged as a strong predictor of suicide in 2021 and 2022, indicating a decrease in suicide risk with higher income levels. High-risk areas, especially in rural and suburban counties, were noticed, with Southern counties having a slightly higher burden of suicide rates. Conclusion This study shows that SDH impacts suicide rates in Virginia, and there is a need for tailored interventions for high-risk areas. Economic stability and location matter. Addressing SDH, enhancing mental health access, and promoting community well-being is vital in suicide prevention. Keywords: Suicide, social determinants of health, rural-urban divide, racial disparities, mental health, public health, risk factors, Virginia, United States, age-adjusted suicide rates, poverty, median household incom

    Robust and Flexible Persistent Scatterer Interferometry for Long-Term and Large-Scale Displacement Monitoring

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    Die Persistent Scatterer Interferometrie (PSI) ist eine Methode zur Überwachung von Verschiebungen der Erdoberfläche aus dem Weltraum. Sie basiert auf der Identifizierung und Analyse von stabilen Punktstreuern (sog. Persistent Scatterer, PS) durch die Anwendung von Ansätzen der Zeitreihenanalyse auf Stapel von SAR-Interferogrammen. PS Punkte dominieren die Rückstreuung der Auflösungszellen, in denen sie sich befinden, und werden durch geringfügige Dekorrelation charakterisiert. Verschiebungen solcher PS Punkte können mit einer potenziellen Submillimetergenauigkeit überwacht werden, wenn Störquellen effektiv minimiert werden. Im Laufe der Zeit hat sich die PSI in bestimmten Anwendungen zu einer operationellen Technologie entwickelt. Es gibt jedoch immer noch herausfordernde Anwendungen für die Methode. Physische Veränderungen der Landoberfläche und Änderungen in der Aufnahmegeometrie können dazu führen, dass PS Punkte im Laufe der Zeit erscheinen oder verschwinden. Die Anzahl der kontinuierlich kohärenten PS Punkte nimmt mit zunehmender Länge der Zeitreihen ab, während die Anzahl der TPS Punkte zunimmt, die nur während eines oder mehrerer getrennter Segmente der analysierten Zeitreihe kohärent sind. Daher ist es wünschenswert, die Analyse solcher TPS Punkte in die PSI zu integrieren, um ein flexibles PSI-System zu entwickeln, das in der Lage ist mit dynamischen Veränderungen der Landoberfläche umzugehen und somit ein kontinuierliches Verschiebungsmonitoring ermöglicht. Eine weitere Herausforderung der PSI besteht darin, großflächiges Monitoring in Regionen mit komplexen atmosphärischen Bedingungen durchzuführen. Letztere führen zu hoher Unsicherheit in den Verschiebungszeitreihen bei großen Abständen zur räumlichen Referenz. Diese Arbeit befasst sich mit Modifikationen und Erweiterungen, die auf der Grund lage eines bestehenden PSI-Algorithmus realisiert wurden, um einen robusten und flexiblen PSI-Ansatz zu entwickeln, der mit den oben genannten Herausforderungen umgehen kann. Als erster Hauptbeitrag wird eine Methode präsentiert, die TPS Punkte vollständig in die PSI integriert. In Evaluierungsstudien mit echten SAR Daten wird gezeigt, dass die Integration von TPS Punkten tatsächlich die Bewältigung dynamischer Veränderungen der Landoberfläche ermöglicht und mit zunehmender Zeitreihenlänge zunehmende Relevanz für PSI-basierte Beobachtungsnetzwerke hat. Der zweite Hauptbeitrag ist die Vorstellung einer Methode zur kovarianzbasierten Referenzintegration in großflächige PSI-Anwendungen zur Schätzung von räumlich korreliertem Rauschen. Die Methode basiert auf der Abtastung des Rauschens an Referenzpixeln mit bekannten Verschiebungszeitreihen und anschließender Interpolation auf die restlichen PS Pixel unter Berücksichtigung der räumlichen Statistik des Rauschens. Es wird in einer Simulationsstudie sowie einer Studie mit realen Daten gezeigt, dass die Methode überlegene Leistung im Vergleich zu alternativen Methoden zur Reduktion von räumlich korreliertem Rauschen in Interferogrammen mittels Referenzintegration zeigt. Die entwickelte PSI-Methode wird schließlich zur Untersuchung von Landsenkung im Vietnamesischen Teil des Mekong Deltas eingesetzt, das seit einigen Jahrzehnten von Landsenkung und verschiedenen anderen Umweltproblemen betroffen ist. Die geschätzten Landsenkungsraten zeigen eine hohe Variabilität auf kurzen sowie großen räumlichen Skalen. Die höchsten Senkungsraten von bis zu 6 cm pro Jahr treten hauptsächlich in städtischen Gebieten auf. Es kann gezeigt werden, dass der größte Teil der Landsenkung ihren Ursprung im oberflächennahen Untergrund hat. Die präsentierte Methode zur Reduzierung von räumlich korreliertem Rauschen verbessert die Ergebnisse signifikant, wenn eine angemessene räumliche Verteilung von Referenzgebieten verfügbar ist. In diesem Fall wird das Rauschen effektiv reduziert und unabhängige Ergebnisse von zwei Interferogrammstapeln, die aus unterschiedlichen Orbits aufgenommen wurden, zeigen große Übereinstimmung. Die Integration von TPS Punkten führt für die analysierte Zeitreihe von sechs Jahren zu einer deutlich größeren Anzahl an identifizierten TPS als PS Punkten im gesamten Untersuchungsgebiet und verbessert damit das Beobachtungsnetzwerk erheblich. Ein spezieller Anwendungsfall der TPS Integration wird vorgestellt, der auf der Clusterung von TPS Punkten basiert, die innerhalb der analysierten Zeitreihe erschienen, um neue Konstruktionen systematisch zu identifizieren und ihre anfängliche Bewegungszeitreihen zu analysieren

    Forecasting marine spill risk along the U.S. Pacific coasts

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    This study analyzes historical trends and forecasts of spill risks in coastal counties along the U.S. Pacific, including Alaska and Hawaii. The method calculates spill impact, which rises with size but diminishes with age and distance from the coast. Over the past two decades, spill risks in California and Washington have increased significantly. Coastal counties in Puget Sound and San Francisco Bay have seen the highest increases, surpassing 2000 levels by 79 % and 39 %, respectively. Alaska experienced a moderate rise, while Oregon and Hawaii had smaller but noteworthy increases. Ocean currents may reduce risk by 38 % on average. Most counties are expected to experience increasing spill risks, particularly in Southern California and Southwest Washington, which could see nearly a 50 % increase by 2033 compared to present levels. These findings can help coastal zone monitoring and inform policies for protecting coastal regions, regulating marine transportation and reducing spill vulnerability.The author would like to acknowledge research funding received from UPV/EHU Econometrics Research Group (Basque Government grant IT1508-22) and EU Interreg Atlantic Area (EAPA_224/2016 MOSES). This research was conducted while the author was a visiting scholar in the Center for the Blue Economy, Middlebury Institute of International Studies @ Monterey (CA) USA. He also thanks two anonymous reviewers for their comments on an earlier version

    Driver-centered pervasive application for heart rate measurement

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    People spend a significant amount of time daily in the driving seat and some health complexity is possible to happen like heart-related problems, and stroke. Driver’s health conditions may also be attributed to fatigue, drowsiness, or stress levels when driving on the road. Drivers’ health is important to make sure that they are vigilant when they are driving on the road. A driver-centered pervasive application is proposed to monitor a driver’s heart rate while driving. The input will be acquired from the interaction between the driver and embedded sensors at the steering wheel, which is tied to a Bluetooth link with an Android smartphone. The driver can view his historical data easily in tabular or graph form with selected filters using the application since the sensor data are transferred to a real-time database for storage and analysis. The application is coupled with the tool to demonstrate an opportunity as an aftermarket service for vehicles that are not equipped with this technology

    The politics of internet privacy regulation in a globalised world: an examination of regulatory agencies' autonomy, politicisation, and lobbying strategies

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    The rapid proliferation of new information technologies has not only made internet privacy one of the most pressing issues of the contemporary area, it has also triggered new regulatory challenges because of their cross-border character. This PhD thesis examines the politics of internet privacy regulation at the global level. Existing research has largely investigated the extent to which there is no international privacy regime, when and why data protection regulations in the European Union affect member state laws and trade relations, and how interest groups shape data protection regulations in the EU. Little scholarly attention, however, has been accorded to the decision-making processes and policies produced beyond the legislative arena. Non-legislative and technical modes of policy-making are yet becoming more prominent in global politics. This research focuses on global data protection and internet privacy rules determined by leading, but little-known, internet regulatory agencies, in particular: the Internet Corporation for Assigned Names and Numbers, World Wide Web Consortium, Internet Engineering Task Force, and Institute of Electrical and Electronics Engineers. It investigates three distinct but interconnected questions regarding regulatory agencies' autonomy, politicisation, and interest groups' lobbying strategies. Each of the three questions corresponds to one substantive chapter and makes distinct contributions, using separate theoretical frameworks, methods, and analyses. Taken together, the chapters provide important theoretical arguments and empirical evidence on the making of internet privacy regulation, with a special emphasis on the role of corporate interests

    Implementing precision methods in personalizing psychological therapies: barriers and possible ways forward

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    This is the final version. Available on open access from Elsevier via the DOI in this recordData availability: No data was used for the research described in the article.Highlights: • Personalizing psychological treatments means to customize treatment for individuals to enhance outcomes. • The application of precision methods to clinical psychology has led to data-driven psychological therapies. • Applying data-informed psychological therapies involves clinical, technical, statistical, and contextual aspects

    RF Energy Harvesting Techniques for Battery-less Wireless Sensing, Industry 4.0 and Internet of Things: A Review

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    As the Internet of Things (IoT) continues to expand, the demand for the use of energy-efficient circuits and battery-less devices has grown rapidly. Battery-less operation, zero maintenance and sustainability are the desired features of IoT devices in fifth generation (5G) networks and green Industry 4.0 wireless systems. The integration of energy harvesting systems, IoT devices and 5G networks has the potential impact to digitalize and revolutionize various industries such as Industry 4.0, agriculture, food, and healthcare, by enabling real-time data collection and analysis, mitigating maintenance costs, and improving efficiency. Energy harvesting plays a crucial role in envisioning a low-carbon Net Zero future and holds significant political importance. This survey aims at providing a comprehensive review on various energy harvesting techniques including radio frequency (RF), multi-source hybrid and energy harvesting using additive manufacturing technologies. However, special emphasis is given to RF-based energy harvesting methodologies tailored for battery-free wireless sensing, and powering autonomous low-power electronic circuits and IoT devices. The key design challenges and applications of energy harvesting techniques, as well as the future perspective of System on Chip (SoC) implementation, data digitization in Industry 4.0, next-generation IoT devices, and 5G communications are discussed
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