62 research outputs found

    Challenging the gold standard: a methodological study of the quality and errors of web tracking data

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    Measuring what people consume and do online is crucial across the social sciences. In the last few years, web tracking data has gained popularity, being considered by most as the gold standard for measuring online behaviours. This thesis studies whether this prevailing notion holds true. Specifically, through a combination of traditional survey and computational methods, I assess the quality of web tracking data, its associated errors, and the consequences of these. The thesis is comprised of three distinct papers. In the first paper, inspired by the Total Survey Error, I present a Total Error framework for digital traces collected with Meters (TEM). The TEM framework describes the data generation and the analysis process for web tracking data and documents the sources of bias and variance that may arise in each step of this process. The framework suggests that metered data might indeed be affected by the error sources identified in our framework and, to some extent, biased. The second paper adopts an empirical approach to address a key error identified in the TEM framework: researchers’ failure to capture data from all the devices and browsers that individuals utilize to go online. The paper shows that tracking undercoverage is highly prevalent when using commercial panels. Additionally, through a simulation study, it demonstrates that web tracking estimates, both univariate and multivariate, are often substantially biased due to tracking undercoverage. The third paper explores the validity and reliability of web tracking data when used to measure media exposure. Merging traditional psychometric and computational techniques, I conduct a multiverse analysis to assess the predictive validity and true-score reliability of thousands of web tracking measures of media exposure. The findings show that web tracking measures have an overall low validity but remarkably high reliability. Additionally, results suggest that the design decisions made by researchers when designing web tracking measurements can have a substantial impact on their measurement properties. Collectively, this thesis challenges the prevailing belief in web tracking data as the gold standard to measure online behaviours. Methodologically, it illustrates how computational methods can be used to adapt survey methodology techniques to assess the quality of digital trace data

    National Conference on ‘Renewable Energy, Smart Grid and Telecommunication-2023

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    Theme of the Conference: “The challenges and opportunities of integrating renewable energy into the grid” The National Conference on Renewable Energy, Smart Grid, and Telecommunication - 2023 is a platform for industry experts, researchers, and policymakers to come together and explore the latest advancements and challenges in the fields of renewable energy, smart grids, and telecommunication. Conference Highlights: In-depth discussions on renewable energy technologies and innovations. Smart grid integration for a sustainable future. The role of telecommunication in advancing renewable energy solutions. Networking opportunities with industry leaders and experts. Presentation of cutting-edge research papers and case studies. Conference topics: Renewable Energy Technologies and Innovations Smart Grid Development and Implementation Telecommunication for Energy Systems Energy Storage and Grid Balancing Policy, Regulation, and Market Dynamics Environmental and Social Impacts of Renewable Energy Energy Transition and Future Outlook Integration of renewable energy into the grid Microgrids and decentralized energy systems Grid cybersecurity and data analytics IoT and sensor technologies for energy monitoring Data management and analytics in energy sector Battery storage technologies and applicationshttps://www.interscience.in/conf_proc_volumes/1087/thumbnail.jp

    Enhancing Geospatial Data: Collecting and Visualising User-Generated Content Through Custom Toolkits and Cloud Computing Workflows

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    Through this thesis we set the hypothesis that, via the creation of a set of custom toolkits, using cloud computing, online user-generated content, can be extracted from emerging large-scale data sets, allowing the collection, analysis and visualisation of geospatial data by social scientists. By the use of a custom-built suite of software, known as the ‘BigDataToolkit’, we examine the need and use of cloud computing and custom workflows to open up access to existing online data as well as setting up processes to enable the collection of new data. We examine the use of the toolkit to collect large amounts of data from various online sources, such as Social Media Application Programming Interfaces (APIs) and data stores, to visualise the data collected in real-time. Through the execution of these workflows, this thesis presents an implementation of a smart collector framework to automate the collection process to significantly increase the amount of data that can be obtained from the standard API endpoints. By the use of these interconnected methods and distributed collection workflows, the final system is able to collect and visualise a larger amount of data in real time than single system data collection processes used within traditional social media analysis. Aimed at allowing researchers without a core understanding of the intricacies of computer science, this thesis provides a methodology to open up new data sources to not only academics but also wider participants, allowing the collection of user-generated geographic and textual content, en masse. A series of case studies are provided, covering applications from the single researcher collecting data through to collection via the use of televised media. These are examined in terms of the tools created and the opportunities opened, allowing real-time analysis of data, collected via the use of the developed toolkit

    A Platform as a Service Framework for Ambient Assisted Living Services

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    The primary objective of Ambient Assisted Living (AAL) technology is to provide aid and assistance to individuals, particularly the elderly, in maintaining their independence and residing in their own homes and their known environment for an extended duration. AAL technology is becoming increasingly important due to the continuous decrease of birth-rate and increasing life expectancy, leading to a shrinking proportion of younger population in developed countries. This research proposes a cloud-based platform as a service (PaaS) for AAL that enables service providers to deliver services without the need for the user to invest in expensive technical equipment in advance, thus reducing high start-up costs. This hurdle, as identified by both peer groups and service solution vendors, stands as a pivotal challenge demanding resolution. The PaaS for AAL focuses on adaptation and personalization, as user acceptance of AAL services depends heavily on their situational needs. To provide customization, the PaaS for AAL can dynamically adapt its functionality and presentation of information based on the context of the environment or user, such as the medical state of the user and the condition at home. To store and retrieve information about the user, an ontology-backed database is implemented, and information about the environment is provided through interoperability with existing smart home appliances, directly attached sensors, and external web services. One of the key concerns of potential AAL users according to a field test during the research is privacy-related. A PaaS for AAL places regulatory demands on protecting the user’s privacy and personal information. Consequently, another part of this work focuses on the question of how general data sharing is possible based on the respective context of the user while protecting their privacy: By implementing monitoring, access control, and enforcement of privacy preserving data access, the platform for AAL is further enhanced. The extension of the introduced privacy policy language with context awareness is a significant step towards providing more robust privacy protection in AAL use cases. With a concluding evaluation survey, it can be shown that it allows for more granular control over data access and ensures that sensitive user data is only accessible when necessary and under appropriate conditions

    Paradoxes of Digital Disengagement : In Search of the Opt-Out Button

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    Life is increasingly governed by digital and smart technologies, platforms, big data and algorithms. Challenging our increasing dependence on the digital, this book raises provocative and urgent questions: in a world of compulsory digitality, is there an opt out button? Where, when, how, why and to whom is it available? Answering these questions has become even more relevant since the COVID-19 pandemic. In response, the book puts forward the concept of 'digital disengagement', explored across six key areas of digitisation: health; citizenship; education; consumer culture; labour; and the environment. As an interdisciplinary piece of work, the book will be useful to any scholar and activist in Digital, Internet and Social Media Studies; Digital Sociology and Social Policy; Digital Health; Media, Popular and Communication Studies; Consumer culture; and Environment Studies

    Participative Urban Health and Healthy Aging in the Age of AI

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    This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2022, held in Paris, France, in June 2022. The 15 full papers and 10 short papers presented in this volume were carefully reviewed and selected from 33 submissions. They cover topics such as design, development, deployment, and evaluation of AI for health, smart urban environments, assistive technologies, chronic disease management, and coaching and health telematics systems

    Development of web-based system for tracking students’ performance for early intervention: a case of darling wisdom academy

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    A Project Report Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in Embedded and Mobile Systems of The Nelson Mandela African Institution of Science and TechnologyStudent Information System (SIS) is critical for the effective operation of institutions of learning because it tracks student performance and allows for early intervention. The project's goal was to develop a functional, flexible, and convenient web-based SIS with user-friendly interface for enhancing students’ performance tracking for early intervention. During the requirements elicitation process, the project included benchmarking of other schools’ SIS. Benchmarking and user interviews were used to obtain requirements for the SIS. The system was developed through Rapid Application Development (RAD) and tested with unit, system, and integration testing. The survey showed that the system is 70% user-friendly, the system will provide easy interaction between students, parents, guardian, and school by 70%, 71% believe the technology will make student data management easier as 73% believe the system will help keep better records. The system provides a single login interface for school general secretary, students, and parents/guardians. The SIS allows students to monitor their academic progress, school management and designated staff manage student results, school general secretary deals with all aspects of system administration pertaining SIS. Secure Socket layer (SSL) certificate installed on the institutional domain where Information System (SI) is hosted. Object-orient Programming (OOP), prepared statements and password encryption were applied for IS security enhancement. SIS files and database were backup using JetBackup and log files were developed to enhance accountability. The efficiency and effectiveness of schools are dependent on the adoption of the SIS. The SIS provides timely student information to students, school management and parents. This system, however, will have to be integrated to other IS’s of DWA to achieve consistent data flow within the institution

    “Mobile phones as an ict resource in English teaching as a foreign language”

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    Mobile phones are ICT devices that allow operations such as calls, messages and Internet browsing. The main objective of this study was to describe the perspective of 14-15-year-old students on the use of mobile phones as an ICT resource in the learning of English as a foreign language at 11 de Noviembre Educative Unit. The research is focused on a quantitative-descriptive design, using a deductive method, based on the perspectives of the participants and the survey applied, which helped to collect real information from a general point of view. For data collection, 10 specific questions were designed and applied with their respective multiple-choice answers on the Likert scale. Once the Covid 19 cases were under control, the students returned to classrooms and with the help of the tutors of two parallels A and B, 21 students between the two grades were chosen. The results of the present research show that mobile phones are an important pedagogical resource for teaching and learning English. Mobile phones are also a resource that can be included in any class and not only in English class. At the same time, the issue of distraction was highlighted as the most common problem identified regarding the use of mobile phones in the classroom. In addition, students agreed that the mobile phone had been a useful teaching-learning resource during the quarantine caused by the pandemic disease Covid19 since it made it easier to access any information they need from the mobile phone. In conclusion, this study revealed that mobile phones played a fundamental role during the pandemic isolation, as it was the most used device in virtual classrooms. Therefore, it helped in training language skills, in other words it turned students’ mobile phones into useful educational tools. However, In the present day, with the return to the classrooms, mobile phones have become a distraction, therefore teachers must be trained in the use of these devices as a resource that allows them to carry out efficient teaching tactics in the classroom, using a variety of strategies and implementing some activities to get students to use their cell phones to learn.Los teléfonos móviles son dispositivos TIC que permiten realizar operaciones como llamadas, mensajes y navegación por Internet. El objetivo principal de este estudio fue describir la perspectiva de los estudiantes de 14 a 15 años sobre el uso del teléfono móvil como recurso TIC en el aprendizaje del inglés como lengua extranjera en la Unidad Educativa 11 de Noviembre. La investigación se centra en un diseño cuantitativo-descriptivo, se utilizó un método deductivo, basado en las perspectivas de los participantes y la encuesta aplicada, que ayudó a recoger información real desde un punto de vista general. Para la recolección de datos, se diseñaron y aplicaron 10 preguntas específicas con sus respectivas respuestas de opción múltiple en la escala de Likert. Una vez controlados los casos de Covid 19, los alumnos volvieron a las aulas y con la ayuda de los tutores de dos paralelos A y B, se eligieron 21 alumnos entre los dos grados. Los resultados de la presente investigación demuestran que los teléfonos móviles son un importante recurso pedagógico para la enseñanza y el aprendizaje del inglés. Los teléfonos móviles son también un recurso que puede incluirse en cualquier clase y no sólo en la de inglés. Al mismo tiempo, la cuestión de la distracción se destacó como el problema más común identificado en relación con el uso de los teléfonos móviles en el aula. Además, los estudiantes estuvieron de acuerdo en que el teléfono móvil había sido un recurso útil de enseñanza-aprendizaje durante la cuarentena causada por la enfermedad pandémica Covid19 ya que les facilitó el acceso a cualquier información que necesitaran desde el teléfono móvil. En conclusión, este estudio reveló que el teléfono móvil desempeñó un papel fundamental durante el aislamiento por la pandemia, ya que fue el dispositivo más utilizado en las aulas virtuales. Por lo tanto, ayudó en la formación de habilidades lingüísticas, es decir, convirtió los teléfonos móviles de los estudiantes en herramientas educativas útiles. Sin embargo, en la actualidad, con el regreso a las aulas, los teléfonos móviles se han convertido en una distracción, por lo que los profesores deben formarse en el uso de estos dispositivos como un recurso que les permita llevar a cabo tácticas de enseñanza eficientes en el aula, utilizando una variedad de estrategias e implementando algunas actividades para que los alumnos utilicen sus teléfonos móviles para aprender

    Emerging Technologies

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    This monograph investigates a multitude of emerging technologies including 3D printing, 5G, blockchain, and many more to assess their potential for use to further humanity’s shared goal of sustainable development. Through case studies detailing how these technologies are already being used at companies worldwide, author Sinan Küfeoğlu explores how emerging technologies can be used to enhance progress toward each of the seventeen United Nations Sustainable Development Goals and to guarantee economic growth even in the face of challenges such as climate change. To assemble this book, the author explored the business models of 650 companies in order to demonstrate how innovations can be converted into value to support sustainable development. To ensure practical application, only technologies currently on the market and in use actual companies were investigated. This volume will be of great use to academics, policymakers, innovators at the forefront of green business, and anyone else who is interested in novel and innovative business models and how they could help to achieve the Sustainable Development Goals. This is an open access book

    IoT security and privacy assessment using software-defined radios

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    The Internet of Things (IoT) has seen exceptional adoption in recent years, resulting in an unprecedented level of connectivity in personal and industrial domains. In parallel, software-defined radio (SDR) technology has become increasingly powerful, making it a compelling tool for wireless security research across multiple communication protocols. Specifically, SDRs are capable of manipulating the physical layer of protocols in software, which would otherwise be implemented statically in hardware. This flexibility enables research that goes beyond the boundaries of protocol specifications. This dissertation pursues four research directions that are either enabled by software-defined radio technology, or advance its utility for security research. First, we investigate the anti-tracking mechanisms defined by the Bluetooth Low Energy (BLE) wireless protocol. This protocol, present in virtually all wearable smart devices, implements address randomization in order to prevent unwanted tracking of its users. By analyzing raw advertising data from BLE devices using SDRs, we identify a vulnerability that allows an attacker to track a BLE device beyond the address randomization defined by the protocol. Second, we implement a compact, SDR-based testbed for physical layer benchmarking of wireless devices. The testbed is capable of emulating multiple data transmissions and produce intentional signal corruption in very precisely defined ways in order to investigate receiver robustness and undefined device behavior in the presence of malformed packets. We subject a range of Wi-Fi and Zigbee devices to specifically crafted packet collisions and "truncated packets" as a way to fingerprinting wireless device chipsets. Third, we introduce a middleware framework, coined "Snout", to improves accessibility and usability of SDRs. The architecture provides standardized data pipelines as well as an abstraction layer to GNU Radio flowgraphs which power SDR signal processing. This abstraction layer improves usability and maintainability by providing a declarative experiment configuration format instead of requiring constant manipulation of the signal processing code during experimentation. We show that Snout does not result in significant computational overhead, and maintains a predictable and modest memory footprint. Finally, we address the visibility problem arising from the growing number of IoT protocols across large bands of radio spectrum. We model an SDR-based IoT monitor which is capable of scanning multiple channels (including across multiple protocols), and employs channel switching policies to maximize freshness of information obtained by transmitting devices. We present multiple policies and compare their performance against an optimal Markov Decision Process (MDP) model, as well as through event-based simulation using real-world device traffic. The results of this work demonstrate the use of SDR technology in privacy and security research of IoT device communication, and open up opportunities for further low-layer protocol discoveries that require the use of software-defined radio as a research tool
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