533 research outputs found
Special issue on advances in data intelligence and modelling
No full textShakshuki, EM (corresponding author), Acadia Univ, Jodrey Sch Comp Sci, Wolfville, NS, Canada.
[email protected]; [email protected]
Applications of machine learning in pervasive systems
No full textShakshuki, EM (corresponding author), Acadia Univ, Jodrey Sch Comp Sci, Wolfville, NS, Canada.
[email protected]; [email protected]; [email protected]
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Provider and administrator-level perspectives on strategies to reduce fear and improve patient trust in the emergency department in times of heightened immigration enforcement
No full textStudy objectivesHeightened immigration enforcement may induce fear in undocumented patients when coming to the Emergency Department (ED) for care. Limited literature examining health system policies to reduce immigrant fear exists. In this multi-site qualitative study, we sought to assess provider and system-level policies on caring for undocumented patients in three California EDs.MethodsWe recruited 41 ED providers and administrators from three California EDs (in San Francisco, Oakland, and Sylmar) with large immigrant populations. Participants were recruited using a trusted gatekeeper and snowball sampling. We conducted semi-structured interviews and analyzed the transcripts using constructivist grounded theory.ResultsWe interviewed 10 physicians, 11 nurses, 9 social workers, and 11 administrators, and identified 7 themes. Providers described existing policies and recent policy changes that facilitate access to care for undocumented patients. Providers reported that current training and communication around policies is limited, there are variations between who asks about and documents status, and there remains uncertainty around policy details, laws, and jurisdiction of staff. Providers also stated they are taking an active role in building safety and trust and see their role as supporting undocumented patients.ConclusionsThis study introduces ED-level health system perspectives and recommendations for caring for undocumented patients. There is a need for active, multi-disciplinary ED policy training, clear policy details including the extent of providers' roles, protocols on the screening and documentation of status, and continual reassessment of our health systems to reduce fear and build safety and trust with our undocumented communities
Assessing the performance of a serological point-of-care test in measuring detectable antibodies against SARS-CoV-2
No full textThis study investigated the performance of a rapid point-of-care antibody test, the BioMedomics COVID-19 IgM/IgG Rapid Test, in comparison with a high-quality, validated, laboratory-based platform, the Roche Elecsys Anti-SARS-CoV-2 assay. Serological testing was conducted on 709 individuals. Concordance metrics were estimated. Logistic regression was used to assess associations with seropositivity. SARS-CoV-2 seroprevalence was 63.5% (450/709; 95% CI 59.8%-67.0%) using the BioMedomics assay and 71.9% (510/709; 95% CI 68.5%-75.2%) using the Elecsys assay. There were 60 discordant results between the two assays, all of which were seropositive in the Elecsys assay, but seronegative in the BioMedomics assay. Overall, positive, and negative percent agreements between the two assays were 91.5% (95% CI 89.2%-93.5%), 88.2% (95% CI 85.1%-90.9%), and 100% (95% CI 98.2%-100%), respectively, with a Cohen’s kappa of 0.81 (95% CI 0.78–0.84). Excluding specimens with lower (Elecsys) antibody titers, the agreement improved with overall, positive, and negative percent concordance of 94.4% (95% CI 92.3%-96.1%), 91.8% (95% CI 88.8%-94.3%), and 100% (95% CI 98.2%-100%), respectively, and a Cohen’s kappa of 0.88 (95% CI 0.85–0.90). Logistic regression confirmed better agreement with higher antibody titers. The BioMedomics COVID-19 IgM/IgG Rapid Test demonstrated good performance in measuring detectable antibodies against SARS-CoV-2, supporting the utility of such rapid point-of-care serological testing to guide the public health responses and vaccine prioritization
Cloud Acknowledgment Scheme for a Node Network
No full textRecently, wireless devices are rapidly added to existing networks. This growth is due to abrupt development in technology and change of lifestyle. Due to the distribution nature of these networks, it is essential to mention that there is a substantial increase in the number of attacks as the network is expanding. By virtue of such trend, we are interested in bringing back centralization of a network even in wireless networks to deal with such attacks. In this paper, we propose a scheme called Cloud ACKnowledgement Scheme (CACKS) to strengthen a wireless network by fetching cloud as a monitoring tool. To validate our proposed approach, we performed several experiments using OMNET++ 5.4.1. The outcome of these experiments shows that the proposed scheme strongly monitors and protects the network from attackers while supporting unrestricted mobility. (C) 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Conference Program Chairs.Kaja, S (corresponding author), Acadia Univ, Jodrey Sch Comp Sci, Wolfville, NS B4P 2R6, Canada.
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Queue based Vehicular Ad Hoc Network Prognostic Offloading Approach
No full textVehicular Ad hoc NETworking (VANET) enables a vehicle to connect with other vehicles and the surrounding devices such as Road Side Units (RSUs) and base-stations through a wireless network. There are challenging issues within VANET environment caused by the high demand of Internet access. These issues include an increase in the vehicle traffic and the necessity of dynamic topologies. Nowadays, the high usage of Internet in vehicles is also increasing the load on the cellular network base-stations. To alleviate the load from the base-stations, vehicles should be able to switch the communication between the cellular network and RSUs to offload the data. When a vehicle is not within the RSU signal range, it is still possible for the vehicle to exchange information using Vehicle-to-Vehicle (V2V) communication. The main aim of this paper is to predict the vehicles topology, identify multiple offloading paths and compute the costs of the identified paths. Towards this end, knowledge defined network is utilized. To deal with connection interruptions in V2V, we develop algorithms for predicting an efficient V2V offloading path using queues. These algorithms make it possible to reduce the response time, improve the resource management of the network and helps in efficient service connectivity. (C) 2020 The Authors. Published by Elsevier B.V.Guntuka, S (corresponding author), Acadia Univ, Jodrey Sch Comp Sci, Wolfville, NS B4P 2R6, Canada.
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Toward a bio-inspired adaptive spatial clustering approach for IoT applications
No full textBio-inspired algorithms have demonstrated effective capabilities to solve Wireless Sensor Network (WSN) challenges. As sensors represent a main component in the emergent domain of Internet of Things (IoT), these algorithms are expected to perform also well in this field while adapting to contextual changes and optimizing the use of the limited resources. In this paper, we propose a new firefly-based clustering approach for IoT applications. Our approach includes a micro clustering phase during which Real-World Things (RWTs) compete and self-organize into clusters. These clusters are then polished during a macro-clustering phase where they compete to integrate small neighboring clusters. We extend our approach to allow the IoT clusters to self-adapt by hiring and/or firing RWTs depending on ongoing events and their expected impact on the network and its current deployment area. Initial simulations are showing promising results where the number of clusters tends to stabilize independently from the density of the network and the various communication ranges of RWTs. (c) 2017 Elsevier B.V. All rights reserved.Jabeur, N (reprint author), German Univ Technol Oman Gutech, Comp Sci Dept, POB 1816, Muscat 130, Oman.
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Mortality, functional outcome and health-related quality of life in patients with necrotizing skin- and soft tissue infections in the ICU: Protocol of a multinational prospective cohort study (SKIN-ICU)
No full texthttp://dx.doi.org/10.13039/501100013347 European Society of Intensive Care Medicin
A world-wide study on delirium assessments and presence of protocols
No full textAcknowledgement of collaborative authors: The “WDAD Study Team” comprises of 158 non-author collaborators. They are listed in Appendix 1a in the Supplementary Data. The authors would like to gratefully acknowledge the many participating clinicians for supporting the 2023 WDAD Study Team and survey. They are named in Appendix 1b in the Supplementary Data.Peer reviewe
A Modeling and Verification Approach to the Design of Distributed IMA Architectures Using TTEthernet
No full textAbstractIntegrated Modular Avionics (IMA) architectures complemented with Time-Triggered Ethernet (TTEthernet) provides a strong platform to support the design and deployment of distributed avionic software systems. The complexity of the design and continuous integration of such systems can be managed using a model-based methodology. In this paper, we build on top of our extension of the AADL modeling language to model TTEthernet-based distributed systems and leverage model transformations to enable undertaking the verification of the system models produced with this methodology. In particular, we propose to transform the system models to a model suitable for a simulation with DEVS. We illustrate the proposed approach using an example of a navigation and guidance system and we use this example to show the verification of the contention-freedom property of TTEthernet schedule
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