19 research outputs found

    Novel applications and contexts for the cognitive packet network

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    Autonomic communication, which is the development of self-configuring, self-adapting, self-optimising and self-healing communication systems, has gained much attention in the network research community. This can be explained by the increasing demand for more sophisticated networking technologies with physical realities that possess computation capabilities and can operate successfully with minimum human intervention. Such systems are driving innovative applications and services that improve the quality of life of citizens both socially and economically. Furthermore, autonomic communication, because of its decentralised approach to communication, is also being explored by the research community as an alternative to centralised control infrastructures for efficient management of large networks. This thesis studies one of the successful contributions in the autonomic communication research, the Cognitive Packet Network (CPN). CPN is a highly scalable adaptive routing protocol that allows for decentralised control in communication. Consequently, CPN has achieved significant successes, and because of the direction of research, we expect it to continue to find relevance. To investigate this hypothesis, we research new applications and contexts for CPN. This thesis first studies Information-Centric Networking (ICN), a future Internet architecture proposal. ICN adopts a data-centric approach such that contents are directly addressable at the network level and in-network caching is easily supported. An optimal caching strategy for an information-centric network is first analysed, and approximate solutions are developed and evaluated. Furthermore, a CPN inspired forwarding strategy for directing requests in such a way that exploits the in-network caching capability of ICN is proposed. The proposed strategy is evaluated via discrete event simulations and shown to be more effective in its search for local cache hits compared to the conventional methods. Finally, CPN is proposed to implement the routing system of an Emergency Cyber-Physical System for guiding evacuees in confined spaces in emergency situations. By exploiting CPN’s QoS capabilities, different paths are assigned to evacuees based on their ongoing health conditions using well-defined path metrics. The proposed system is evaluated via discrete-event simulations and shown to improve survival chances compared to a static system that treats evacuees in the same way.Open Acces

    Physical activity and exercise in dementia : an umbrella review of intervention and observational studies

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    Background: Dementia is a common condition in older people. Among the potential risk factors, increasing attention has been focused on sedentary behaviour. However, synthesizing literature exploring whether physical activity/exercise can affect health outcomes in people with dementia or with mild cognitive impairment (MCI) is still limited. Therefore, the aim of this umbrella review, promoted by the European Geriatric Medicine Society (EuGMS), is to understand the importance of physical activity/exercise for improving cognitive and non-cognitive outcomes in people with dementia/MCI. Methods: Umbrella review of systematic reviews (SR) (with or without meta-analyses) of randomized controlled trials (RCTs) and observational (prospective and case-control in people with MCI) studies based on a systematic literature search in several databases. The certainty of evidence of statistically significant outcomes attributable to physical activity/exercise interventions was evaluated using Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Results: Among 1,160 articles initially evaluated, 27 systematic reviews (4 without meta-analysis) for a total of 28,205 participants with dementia/MCI were included. No observational study on physical activity/exercise in MCI for preventing dementia was included. In SRs with MAs, physical activity/exercise was effective in improving global cognition in Alzheimer’s disease and in all types of dementia (very low/low certainty of evidence). Moreover, physical activity/ exercise significantly improved global cognition, attention, executive function, and memory in MCI, with a certainty of evidence varying from low to moderate. Finally, physical activity/exercise improved non-cognitive outcomes in people with dementia including falls and neuropsychiatric symptoms. SRs, without meta-analysis, corroborated these results. Conclusions: Supported by very low to moderate certainty of evidence, physical activity/exercise has a positive effect on several cognitive and non-cognitive outcomes in people with dementia and MCI, but RCTs, with low risk of bias/confounding, are still needed to confirm these findings

    Deprescribing tool for STOPPFall (screening tool of older persons prescriptions in older adults with high fall risk) items

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    Background: Health care professionals are often reluctant to deprescribe fall-risk-increasing drugs (FRIDs). Lack of knowledge and skills form a significant barrier. To support clinicians in the management of FRIDs and to facilitate the deprescribing process, a deprescribing tool was developed by a European expert group for STOPPFall (Screening Tool of Older Persons Prescriptions in older adults with high fall risk) items. Methods: STOPPFall was created using an expert Delphi consensus process in 2019 and in 2020, 24 panellists from EuGMS SIG on Pharmacology and Task and Finish on FRIDs completed deprescribing tool questionnaire. To develop the questionnaire, a Medline literature search was performed. The panellists were asked to indicate for every medication class a possible need for stepwise withdrawal and strategy for withdrawal. They were asked in which situations withdrawal should be performed. Furthermore, panellists were requested to indicate those symptoms patients should be monitored for after deprescribing and a possible need for follow-ups. Results: Practical deprescribing guidance was developed for STOPPFall medication classes. For each medication class, a decision tree algorithm was developed including steps from medication review to symptom monitoring after medication withdrawal. Conclusion: STOPPFall was combined with a practical deprescribing tool designed to optimize medication review. This practical guide can help overcome current reluctance towards deprescribing in clinical practice by providing an up-to-date and straightforward source of expert knowledge

    Association between number of medications and mortality in geriatric inpatients : a Danish nationwide register-based cohort study

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    Purpose: To explore the association between the number of medications and mortality in geriatric inpatients taking activities of daily living and comorbidities into account. Methods: A nationwide population-based cohort study was performed including all patients aged C65 years admitted to geriatric departments in Denmark during 2005-2014. The outcome of interest was mortality. Activities of daily living using Barthel-Index (BI) were measured at admission. National health registers were used to link data on an individual level extracting data on medications, and hospital diseases. Patients were followed to the end of study (31.12.2015), death, or emigration, which ever occurred first. Kaplan-Meier survival curves were used to estimate crude survival proportions. Univariable and multivariable analyses were performed using Cox regression. The multivariable analysis adjusted for age, marital status, period of hospital admission, BMI, and BI (model 1), and further adding either number of diseases (model 2) or Charlson comorbidity index (model 3). Results: We included 74603 patients (62.8% women), with a median age of 83 (interquartile range [IQR] 77-88) years. Patients used a median of 6 (IQR 4-9) medications. Increasing number of medications was associated with increased overall, 30-days, and 1-year mortality in all 3 multivariable models for both men and women. For each extra medication the mortality increased by 3% in women and 4% in men in the fully adjusted model. Conclusion: Increasing number of medications was associated with mortality in this nationwide cohort of geriatric inpatients. Our findings highlight the importance of polypharmacy in older patients with comorbidities

    Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking

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    The emerging massive density of human-held and machine-type nodes implies larger traffic deviatiolns in the future than we are facing today. In the future, the network will be characterized by a high degree of flexibility, allowing it to adapt smoothly, autonomously, and efficiently to the quickly changing traffic demands both in time and space. This flexibility cannot be achieved when the network’s infrastructure remains static. To this end, the topic of UAVs (unmanned aerial vehicles) have enabled wireless communications, and networking has received increased attention. As mentioned above, the network must serve a massive density of nodes that can be either human-held (user devices) or machine-type nodes (sensors). If we wish to properly serve these nodes and optimize their data, a proper wireless connection is fundamental. This can be achieved by using UAV-enabled communication and networks. This Special Issue addresses the many existing issues that still exist to allow UAV-enabled wireless communications and networking to be properly rolled out

    Indoor Positioning and Navigation

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    In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot
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