Dataset Information

Information Fusion of Conflicting Input Data.

ABSTRACT: Sensors, and also actuators or external sources such as databases, serve as data sources in order to realise condition monitoring of industrial applications or the acquisition of characteristic parameters like production speed or reject rate. Modern facilities create such a large amount of complex data that a machine operator is unable to comprehend and process the information contained in the data. Thus, information fusion mechanisms gain increasing importance. Besides the management of large amounts of data, further challenges towards the fusion algorithms arise from epistemic uncertainties (incomplete knowledge) in the input signals as well as conflicts between them. These aspects must be considered during information processing to obtain reliable results, which are in accordance with the real world. The analysis of the scientific state of the art shows that current solutions fulfil said requirements at most only partly. This article proposes the multilayered information fusion system MACRO (multilayer attribute-based conflict-reducing observation) employing the ?BalTLCS (fuzzified balanced two-layer conflict solving) fusion algorithm to reduce the impact of conflicts on the fusion result. The performance of the contribution is shown by its evaluation in the scope of a machine condition monitoring application under laboratory conditions. Here, the MACRO system yields the best results compared to state-of-the-art fusion mechanisms. The utilised data is published and freely accessible.

SUBMITTER: Monks U

PROVIDER: S-EPMC5134457 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Information Fusion of Conflicting Input Data.

Mönks Uwe U Dörksen Helene H Lohweg Volker V Hübner Michael M

Sensors (Basel, Switzerland) 20161029 11

Sensors, and also actuators or external sources such as databases, serve as data sources in order to realise condition monitoring of industrial applications or the acquisition of characteristic parameters like production speed or reject rate. Modern facilities create such a large amount of complex data that a machine operator is unable to comprehend and process the information contained in the data. Thus, information fusion mechanisms gain increasing importance. Besides the management of large a ...[more]

PMID: 27801874

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Project description:ObjectiveThe number of patients with chronic diseases and subsequent visits to various healthcare professionals has been rising over the past decades, exposing patients to potential risks of receiving conflicting medication information. This study aims to investigate the prevalence of conflicting information on medications perceived by chronic patients in Switzerland and to understand its impact on patients' medication self-management and navigation in the healthcare system.ParticipantsThis cross-sectional study included adult patients taking at least one prescribed medication for at least 6 months, who had visited at least two physicians in the past 3 months.Main outcome measuresData on patients' perceptions of conflicting information were collected in person through a 17-item questionnaire available on paper and electronically with four domains: (1) whether the patient had perceived any conflicting information, (2) categories of conflicting information, (3) impact and (4) sources involved in the conflicting information.ResultsOf the 405 included patients, 47% perceived conflicting information related to one or more medication topics including indication, schedule, dosage, risk, severity or duration of side effects. Patients who perceived conflicting information were prescribed more drugs than those perceiving no conflicting information (p<0.01). Consequently, 65% of the participants modified their navigation of the healthcare system and 34% reported medication non-adherence. General practitioners (82%), specialist physicians (74%) and pharmacists (49%) were the healthcare professionals most often involved in conflicting information. Experience with the medication, its package insert and significant others were more frequently involved in conflicting information than internet or social media.ConclusionNearly half the patients in our study perceived conflicting information in the outpatient healthcare system, which can decrease medication effectiveness and pose safety issues. This issue is widely overlooked and unaddressed. Consistency of information among healthcare providers in partnership with patients should be reinforced through guidelines and new models of interprofessional care.

Project description:The COVID-19 pandemic constitutes a novel threat and traditional and new media provide people with an abundance of information and misinformation on the topic. In the current study, we investigated who tends to trust what type of mis/information. The data were collected in Norway from a sample of 405 participants during the first wave of COVID-19 in April 2020. We focused on three kinds of belief: the belief that the threat is overrated (COVID-threat skepticism), the belief that the threat is underrated (COVID-threat belief) and belief in misinformation about COVID-19. We studied sociodemographic factors associated with these beliefs and the interplay between attitudes to COVID-19, media consumption and prevention behavior. All three types of belief were associated with distrust in information about COVID-19 provided by traditional media and distrust in the authorities' approach to the pandemic. COVID-threat skepticism was associated with male gender, reduced news consumption since the start of the pandemic and lower levels of precautionary measures. Belief that the COVID-19 threat is underrated was associated with younger age, left-wing political orientation, increased news consumption during the pandemic and increased precautionary behavior. Consistent with the assumptions of the theory of planned behavior, individual beliefs about the seriousness of the COVID-19 threat predicted the extent to which individual participants adopted precautionary health measures. Both COVID-threat skepticism and COVID-threat belief were associated with endorsement of misinformation on COVID-19. Participants who endorsed misinformation tended to: have lower levels of education; be male; show decreased news consumption; have high Internet use and high trust in information provided by social media. Additionally, they tended to endorse multiple misinformation stories simultaneously, even when they were mutually contradictory. The strongest predictor for low compliance with precautionary measures was endorsement of a belief that the COVID-19 threat is overrated which at the time of the data collection was held also by some experts and featured in traditional media. The findings stress the importance of consistency of communication in situations of a public health threat.

Dataset Information

Information Fusion of Conflicting Input Data.

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Information Fusion of Conflicting Input Data.

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