Physical activity monitoring with wearable technology has the potential to support stroke rehabilitation. Little is known about how physical therapists use and value the use of wearable activity monitors. This cross-sectional study explores the use, perspectives, and barriers to wearable activity monitoring in day-to-day stroke care routines amongst physical therapists. Over 300 physical therapists in primary and geriatric care and rehabilitation centers in the Netherlands were invited to fill in an online survey that was developed based on previous studies and interviews with experts. In total, 103 complete surveys were analyzed. Out of the 103 surveys, 27% of the respondents were already using activity monitoring. Of the suggested treatment purposes of activity monitoring, 86% were perceived as useful by more than 55% of the therapists. The most recognized barriers to clinical implementation were lack of skills and knowledge of patients (65%) and not knowing what brand and type of monitor to choose (54%). Of the non-users, 79% were willing to use it in the future. In conclusion, although the concept of remote activity monitoring was perceived as useful, it was not widely adopted by physical therapists involved in stroke care. To date, skills, beliefs, and attitudes of individual therapists determine the current use of wearable technology.
ABSTRACT Purpose: This short paper describes the dashboard design process for online hate speech monitoring for multiple languages and platforms. Methodology/approach: A case study approach was adopted in which the authors followed a research & development project for a multilingual and multiplatform online dashboard monitoring online hate speech. The case under study is the project for the European Observatory of Online Hate (EOOH). Results: We outline the process taken for design and prototype development for which a design thinking approach was followed, including multiple potential user groups of the dashboard. The paper presents this process's outcome and the dashboard's initial use. The identified issues, such as obfuscation of the context or identity of user accounts of social media posts limiting the dashboard's usability while providing a trade-off in privacy protection, may contribute to the discourse on privacy and data protection in (big data) social media analysis for practitioners. Research limitations/implications: The results are from a single case study. Still, they may be relevant for other online hate speech detection and monitoring projects involving big data analysis and human annotation. Practical implications: The study emphasises the need to involve diverse user groups and a multidisciplinary team in developing a dashboard for online hate speech. The context in which potential online hate is disseminated and the network of accounts distributing or interacting with that hate speech seems relevant for analysis by a part of the user groups of the dashboard. International Information Management Association
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This article examines the impact of the COVID-19 pandemic on the sign language interpreting profession drawing on data from a fourth and final survey conducted in June 2021 as part of a series of online “living surveys” during the pandemic. The survey, featuring 331 respondents, highlights significant changes in the occupational conditions and practices of sign language interpreters due to the sudden shift towards remote video-mediated interpreting. The findings reveal a range of challenges faced by interpreters, including the complexities of audience design, lack of backchanneling from deaf consumers, the need for heightened self-monitoring, nuanced conversation management, and team work. Moreover, the study highlights the physical and mental health concerns that have emerged among interpreters as a result of the shift in working conditions, and a need for interpreters to acquire new skills such as coping with the multimodal nature of online interpreting. While the blend of remote, hybrid, and on-site work has introduced certain advantages, it also poses new challenges encompassing workload management, online etiquette, and occupational health concerns. The survey’s findings underscore the resilience and adaptability of SLIs in navigating the shift to remote interpreting, suggesting a lasting transformation in the profession with implications for future practice, training, and research in the post-pandemic era.
The integration of renewable energy resources, controllable devices and energy storage into electricity distribution grids requires Decentralized Energy Management to ensure a stable distribution process. This demands the full integration of information and communication technology into the control of distribution grids. Supervisory Control and Data Acquisition (SCADA) is used to communicate measurements and commands between individual components and the control server. In the future this control is especially needed at medium voltage and probably also at the low voltage. This leads to an increased connectivity and thereby makes the system more vulnerable to cyber-attacks. According to the research agenda NCSRA III, the energy domain is becoming a prime target for cyber-attacks, e.g., abusing control protocol vulnerabilities. Detection of such attacks in SCADA networks is challenging when only relying on existing network Intrusion Detection Systems (IDSs). Although these systems were designed specifically for SCADA, they do not necessarily detect malicious control commands sent in legitimate format. However, analyzing each command in the context of the physical system has the potential to reveal certain inconsistencies. We propose to use dedicated intrusion detection mechanisms, which are fundamentally different from existing techniques used in the Internet. Up to now distribution grids are monitored and controlled centrally, whereby measurements are taken at field stations and send to the control room, which then issues commands back to actuators. In future smart grids, communication with and remote control of field stations is required. Attackers, who gain access to the corresponding communication links to substations can intercept and even exchange commands, which would not be detected by central security mechanisms. We argue that centralized SCADA systems should be enhanced by a distributed intrusion-detection approach to meet the new security challenges. Recently, as a first step a process-aware monitoring approach has been proposed as an additional layer that can be applied directly at Remote Terminal Units (RTUs). However, this allows purely local consistency checks. Instead, we propose a distributed and integrated approach for process-aware monitoring, which includes knowledge about the grid topology and measurements from neighboring RTUs to detect malicious incoming commands. The proposed approach requires a near real-time model of the relevant physical process, direct and secure communication between adjacent RTUs, and synchronized sensor measurements in trustable real-time, labeled with accurate global time-stamps. We investigate, to which extend the grid topology can be integrated into the IDS, while maintaining near real-time performance. Based on topology information and efficient solving of power flow equation we aim to detect e.g. non-consistent voltage drops or the occurrence of over/under-voltage and -current. By this, centrally requested switching commands and transformer tap change commands can be checked on consistency and safety based on the current state of the physical system. The developed concepts are not only relevant to increase the security of the distribution grids but are also crucial to deal with future developments like e.g. the safe integration of microgrids in the distribution networks or the operation of decentralized heat or biogas networks.
Grid congestion has caused significant issues for many businesses and consumers, leading to pressing questions about potential expansion, the configuration of electrical infrastructure, opportunities to reduce energy usage, and the impacts of installing photovoltaic (PV) systems. This project is dedicated to developing a digital twin energy management system within an energy hub to enhance efficiency and sustainability. By integrating state-of-the-art digital twin technology with various energy systems, the project, led technically by HAN University of Applied Sciences and with security managed by Impact Iot Solutions, aims to optimize the management of diverse energy sources like solar panels, heat pumps, and storage systems. Central to our approach is ensuring that all data collected during the project, which includes system performance metrics but excludes any personal user information, is used responsibly and stored securely. Local storage at the energy hub allows real-time monitoring and data analysis, with secure remote access for project partners to facilitate collaboration. At the project's conclusion, non-sensitive data will be made publicly available on an open platform, promoting transparency and enabling further research and development by the broader community. This initiative not only seeks to improve energy management practices but also aims to serve as a model for future digital twin implementations in energy hubs worldwide. By focusing on innovation, privacy, and community engagement, the project represents a significant step forward in the integration of digital technologies into sustainable energy solutions.
