Multiple Simultaneous Threats Detection in Distributed Systems

This research examines a simultaneous threats detection system for distributed systems that uses a hybrid identification fusion model. This hybrid model is comprised of mathematical and statistical data fusion engines: Dempster-Shafer, Extended Dempster-Shafer, and Generalised Evidential Processing (GEP). The simultaneous threats detection system produced threat detection rates of 56% using Dempster-Shafer whilst Extended Dempster-Shafer and Generalised Evidential Processing (GEP) achieved 80% and 95% threat detection rate. Thus, the simultaneous threats detection system can improve threat detection rates by 39% (i.e. 95% - 56%) simply by adopting a more effective hybrid fusion model. In terms of efficiency and performance, the comparison of the three inference engines of the simultaneous threats detection system showed that Generalised Evidential Processing is a better data fusion model than Dempster-Shafer or Extended Dempster-Shafer. In addition, the set cover packing technique was used as a middle-tier data fusion tool to determine the reduced size groups of the threat data. Set cover provided significant improvement and reduced the threat population from 2,272 to 295. This helped to minimise the complexity of evidential processing, and therefore reduced the cost and time taken to determine the combined probability mass of the multiple simultaneous threats detection system. This technique is particularly relevant to online and internet-dependent applications, including portals

Advancing specificity in delirium: The delirium subtyping initiative

BACKGROUND: Delirium, a common syndrome with heterogeneous etiologies and clinical presentations, is associated with poor long-term outcomes. Recording and analyzing all delirium equally could be hindering the field's understanding of pathophysiology and identification of targeted treatments. Current delirium subtyping methods reflect clinically evident features but likely do not account for underlying biology. METHODS: The Delirium Subtyping Initiative (DSI) held three sessions with an international panel of 25 experts. RESULTS: Meeting participants suggest further characterization of delirium features to complement the existing Diagnostic and Statistical Manual of Mental Disorders Fifth Edition Text Revision diagnostic criteria. These should span the range of delirium-spectrum syndromes and be measured consistently across studies. Clinical features should be recorded in conjunction with biospecimen collection, where feasible, in a standardized way, to determine temporal associations of biology coincident with clinical fluctuations. DISCUSSION: The DSI made recommendations spanning the breadth of delirium research including clinical features, study planning, data collection, and data analysis for characterization of candidate delirium subtypes. HIGHLIGHTS: Delirium features must be clearly defined, standardized, and operationalized. Large datasets incorporating both clinical and biomarker variables should be analyzed together. Delirium screening should incorporate communication and reasoning

Fifteen years of the Australian imaging, biomarkers and lifestyle (AIBL) study: Progress and observations from 2,359 older adults spanning the spectrum from cognitive normality to Alzheimer\u27s disease

Background: The Australian Imaging, Biomarkers and Lifestyle (AIBL) Study commenced in 2006 as a prospective study of 1,112 individuals (768 cognitively normal (CN), 133 with mild cognitive impairment (MCI), and 211 with Alzheimer\u27s disease dementia (AD)) as an \u27Inception cohort\u27 who underwent detailed ssessments every 18 months. Over the past decade, an additional 1247 subjects have been added as an \u27Enrichment cohort\u27 (as of 10 April 2019). Objective: Here we provide an overview of these Inception and Enrichment cohorts of more than 8,500 person-years of investigation. Methods: Participants underwent reassessment every 18 months including comprehensive cognitive testing, neuroimaging (magnetic resonance imaging, MRI; positron emission tomography, PET), biofluid biomarkers and lifestyle evaluations. Results: AIBL has made major contributions to the understanding of the natural history of AD, with cognitive and biological definitions of its three major stages: preclinical, prodromal and clinical. Early deployment of Aβ-amyloid and tau molecular PET imaging and the development of more sensitive and specific blood tests have facilitated the assessment of genetic and environmental factors which affect age at onset and rates of progression. Conclusion: This fifteen-year study provides a large database of highly characterized individuals with longitudinal cognitive, imaging and lifestyle data and biofluid collections, to aid in the development of interventions to delay onset, prevent or treat AD. Harmonization with similar large longitudinal cohort studies is underway to further these aims

Object and Access Evolution in Jarrah

Abstract- Persistent object evolution is at least as important as evolution at the system level since an object may outlive a system in which it is used and may be used in many systems concurrently. The programming language Jarrah is a Java extension supporting secure persistent objects and fine-grained access control to these objects. In this paper we describe the persistence and access control constructs of Jarrah and demonstrate how these constructs, originally designed for security, also enable the containment of various forms of object evolution

Supporting Parameterised Roles with Object-Based Access Control

The per-method access control lists of standard internet technologies allow only simple forms of access control to be expressed and enforced. They also fail to enforce a strict need-to-know view of persistent data. Real applications require more flexible security constraints including parameter restrictions, logging of accesses and state-dependent access constraints. In particular, the concept of parameterised roles, central to a fine-grained specification of access rules and compliance with privacy laws, should be supported in a natural way. In this paper we demonstrate how an object-based approach using the mechanism of bracket capabilities can be used to enforce various kinds of access constraints including discretionary, mandatory and parameterised role-based access control. We give examples from a health information system incorporating secure patient access and secure access by appropriate medical and administrative personnel