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A nomadic multi-agent based privacy metrics for e-health care : a deep learning approach
No full textIn recent years, there has been a surge in the use of deep learning systems for e-healthcare applications. While these systems can provide significant benefits regarding improved diagnosis and treatment, they also pose substantial privacy risks to patients' sensitive data. Privacy is a crucial issue in e-healthcare, and it is essential to keep patient information secure. A new approach based on multi-agent-based privacy metrics for e-healthcare deep learning systems has been proposed to address this issue. This approach uses a combination of deep learning and multi-agent systems to provide a more robust and secure method for e-healthcare applications. The multi-agent system is designed to monitor and control the access to patients' data by different agents in the system. Each agent is assigned a specific role and has specific data access permissions. The system employs a set of privacy metrics to a substantial privacy level of the data accessed by each agent. These metrics include confidentiality, integrity, and availability, evaluated in real-time and used to identify potential privacy violations. In addition to the multi-agent system, the deep learning component is also integrated into the system to improve the accuracy of diagnoses and treatment plans. The deep learning model is trained on a large dataset of medical records and can accurately predict the diagnosis and treatment plan based on the patient's symptoms and medical history. The multi-agent-based privacy metrics for the e-healthcare deep learning system approach have several advantages. It provides a more secure system for e-healthcare applications by ensuring only authorized agents can access patients' data. Privacy metrics enable the system to identify potential privacy violations in real-time, thereby reducing the risk of data breaches. Finally, integrating deep learning improves the accuracy of diagnoses and treatment plans, leading to better patient outcomes. [Abstract copyright: © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
Historical consciousness and bounded imagination : how history inspires and constrains innovation in long-lived firms
No full textUnexpected observations from a study of ultra-centenary Japanese firms suggest that organizational longevity might affect how managers relate to past, present, and future, and how they approach change and innovation. To account for these observations, we borrow the notion of historical consciousness, originally developed at the intersection of philosophy and historiography to indicate the continued salience of history in the present. Our findings suggest how historical consciousness might induce an approach to change – which we refer to as bounded imagination – that is simultaneously conservative and creative. These revelatory insights contribute to our understanding of how history and tradition can be mobilized as resources for action. They invite us, more generally, to expand our conceptualization of history in organizations – not only as a set of objective conditions and events (as in theories of imprinting and path dependence) or a discursive representation of the past (as in rhetorical history) but as subjective experience and interpretive frame shaping action in the present
Using infinite server queues with partial information for occupancy prediction
Get PDFMotivated by demand prediction for the custodial prison population in England and Wales, this paper describes an approach to the study of service systems using in nite server queues, where the system has non-empty initial state and the elapsed time of individuals initially present is not known. By separating the population into initial content and new arrivals, we can apply several techniques either separately or jointly to those sub-populations, to enable both short-term queue length predictions and longer-term considerations such as managing congestion and analysing the impact of potential interventions. The focus in the paper is the transient behaviour of the Mt=G=1 queue with a non-homogeneous Poisson arrival process and our analysis considers various possible simpli cations, including approximation. We illustrate the approach in that domain using publicly available data in a Bayesian framework to perform model inference
Post-racial politics, pre-emption and in/security
Get PDFMilitarized policing strategies aiming to identify and nullify risks to national security in Western nations have become central to the biopolitical regulation of racialized populations. While the disproportionate impact of pre-emptive counter-terrorism policing on ‘Muslim’ populations has been highlighted, the post-racial techno-politics of predictive policing as a mode of securitization remain overlooked. This article argues that the ‘war on terror’ is governed by a state of crisis that conditions a pre-emptive biopolitics of containment against (unknown) future threats. We examine how predictive policing is progressively dependent on the computational production of risk to avert impending terror. As such, extant forms of counter-terrorism algorithmic profiling are shown to mobilize post-racial calculative logics that renew racial oppression while appearing race-neutral. These predictive systems and pre-emptive actions, while seeking to securitize the future by identifying and nullifying suspects, evasively remake race as risky, thus rendering security indistinguishable from insecurity. Hence, we assert that state securitization is haunted by a profound sense of racialized dread over terrorism, for it can only resort to containing, rather than resolving, the perceived threat of race
Fewer native and periprosthetic femoral fracture patients receive an orthogeriatric review and expedited surgery compared to hip fracture patients
Get PDFIntroduction:
Disproportionate emphasis has been attributed to hip fracture over other femoral fractures through implementation of Best Practice Tariff (BPT). This retrospective comparative observational cohort study aimed to evaluate the epidemiology of native and periprosthetic femoral fractures, and establish any disparities in their management relative to hip fractures.
Methods:
All patients ≥60 years admitted with a native or periprosthetic femoral fracture during July 2016-June 2018 were identified using our hospital database. Results were compared to National Hip Fracture Database data over the same period.
Results:
58 native femoral, 87 periprosthetic and 1,032 hip fractures were identified. (46/58) 79% and 76/87 (89%) of native and periprosthetic femoral fractures were managed operatively. Surgery was performed <36 hours for 34/46 (74%) of native femoral and 33/76 (43%) of periprosthetic fractures compared to 826/1032 (80%) for hips. Median time to surgery was longer in periprosthetic femoral than hip fracture patients (44.7 vs 21.6 hours; p<0.0001). Orthogeriatrician review occurred in 24/58 (41%) and 48/87 (55%) of native and periprosthetic fractures compared to 1,017/1032 (99%) for hips (p<0.0001). One year mortality was 35%, 20% and 26% for native femoral, periprosthetic and hip fracture patients. Cox proportional hazard ratio was higher for native femoral than hip fracture patients (1.75; 95%CI 1.12 – 2.73).
Conclusions:
This study demonstrates large disparities in management of other femoral and periprosthetic fractures compared to hip fractures, specifically time to surgery and orthogeriatrician review. This may have resulted in the comparatively higher mortality rate of native femoral fracture patients. Expansion of the BPT to include the whole femur is likely to improve outcomes
Stationary local random countable sets over the Wiener noise
Get PDFThe times of Brownian local minima, maxima and their union are three distinct examples of local, stationary, dense, random countable sets associated with classical Wiener noise. Being local means, roughly, determined by the local behavior of the sample paths of the Brownian motion, and stationary means invariant relative to the Lévy shifts of the sample paths. We answer to the affirmative Tsirelson's question, whether or not there are any others, and develop some general theory for such sets. An extra ingredient to their structure, that of an honest indexation, leads to a splitting result that is akin to the Wiener-Hopf factorization of the Brownian motion at the minimum (or maximum) and has the latter as a special case. Sets admitting an honest indexation are moreover shown to have the property that no stopping time belongs to them with positive probability. They are also minimal: they do not have any non-empty proper local stationary subsets. Random sets, of the kind studied in this paper, honestly indexed or otherwise, give rise to nonclassical one-dimensional noises, generalizing the noise of splitting. Some properties of these noises and the inter-relations between them are investigated. In particular, subsets are connected to subnoises