Modern dog and cat owners increasingly use internet resources to obtain information on pet health issues. While access to online information can improve owners' knowledge of patient care and inform conversations with their veterinarian during consultations, there is also a risk that owners will misinterpret online information or gain a false impression of current standards in veterinary medicine. This in turn can cause problems or tensions, for example if the owner delays consulting their veterinarian about necessary treatment, or questions the veterinarian's medical advice. Based on an online questionnaire aimed at dog and cat owners in Austria, Denmark and the United Kingdom ( = 2117) we investigated the use of internet resources to find veterinary medical information, the type of internet resources that were used, and whether owner beliefs explain how often they used the internet to find medical information about their pet. Approximately one in three owners reported that they never used internet resources prior to (31.7%) or after (37.0%) a consultation with their veterinarian. However, when owners do make use of the internet, our results show that they were more likely to use it before than after the consultation. The most common internet resources used by owners were practice websites (35.0%), veterinary association websites (24.0%), or 'other' websites providing veterinary information (55.2%). Owners who believe that the use of internet resources enables them to have a more informed discussion with their veterinarians more often use internet resources prior to a consultation, whereas owners who believed that internet resources help them to make the right decision for their animal more often use internet resources after a consultation. The results suggest that veterinarians should actively ask pet owners if they use internet resources, and what resources they use, in order to facilitate open discussion about information obtained from the internet. Given that more than a third of pet owners use practice websites, the findings also suggest that veterinarians should actively curate their own websites where they can post information that they consider accurate and trustworthy.
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http://dx.doi.org/10.3389/fvets.2024.1417927 | DOI Listing |
Comput Biol Med
January 2025
Department of Computer Science, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran. Electronic address:
Tiny machine learning (TinyML) and edge intelligence have emerged as pivotal paradigms for enabling machine learning on resource-constrained devices situated at the extreme edge of networks. In this paper, we explore the transformative potential of TinyML in facilitating pervasive, low-power cardiovascular monitoring and real-time analytics for patients with cardiac anomalies, leveraging wearable devices as the primary interface. To begin with, we provide an overview of TinyML software and hardware enablers, accompanied by an examination of networking solutions such as Low-power Wide area network (LPWAN) that facilitate the seamless deployment of TinyML frameworks.
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January 2025
College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China.
As the Internet of Things (IoT) expands globally, the challenge of signal transmission in remote regions without traditional communication infrastructure becomes prominent. An effective solution involves integrating aerial, terrestrial, and space components to form a Space-Air-Ground Integrated Network (SAGIN). This paper discusses an uplink signal scenario in which various types of data collection sensors as IoT devices use Unmanned Aerial Vehicles (UAVs) as relays to forward signals to low-Earth-orbit satellites.
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January 2025
Department of Computer Science and Systems Engineering, Faculty of Information and Communication Technology, Wrocław University of Science and Technology, 50-370 Wrocław, Poland.
The distributed nature of IoT systems and new trends focusing on fog computing enforce the need for reliable communication that ensures the required quality of service for various scenarios. Due to the direct interaction with the real world, failure to deliver the required QoS level can introduce system failures and lead to further negative consequences for users. This paper introduces a prediction-based resource allocation method for Multi-Access Edge Computing-capable networks, aimed at assurance of the required QoS and optimization of resource utilization for various types of IoT use cases featuring adaptability to changes in users' requests.
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January 2025
African Centre of Excellence for Internet of Things, University of Rwanda, Kigali P.O. Box 4285, Rwanda.
The Internet of Things (IoT) and Industrial Internet of Things (IIoT) have drastically transformed industries by enhancing efficiency and flexibility but have also introduced substantial cybersecurity risks. The rise of zero-day attacks, which exploit unknown vulnerabilities, poses significant threats to these interconnected systems. Traditional signature-based intrusion detection systems (IDSs) are insufficient for detecting such attacks due to their reliance on pre-defined attack signatures.
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January 2025
School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.
This research presents an intelligent beam-hopping-based grant-free random access (GFRA) architecture designed for secure Internet of Things (IoT) communications in Low Earth Orbit (LEO) satellite networks. In light of the difficulties associated with facilitating extensive device connectivity while ensuring low latency and high reliability, we present a beam-hopping GFRA (BH-GFRA) scheme that enhances access efficiency and reduces resource collisions. Three distinct resource-hopping schemes, random hopping, group hopping, and orthogonal group hopping, are examined and utilized within the framework.
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