216,564 research outputs found
Delusional beliefs and reason giving
Delusions are often regarded as irrational beliefs, but their irrationality is not sufficient to explain what is pathological about them. In this paper we ask whether deluded subjects have the capacity to support the content of their delusions with reasons, that is, whether they can author their delusional states. The hypothesis that delusions are characterised by a failure of authorship, which is a dimension of self knowledge, deserves to be
empirically tested because (a) it has the potential to account for the distinction between endorsing a delusion and endorsing a framework belief; (b) it contributes to a
philosophical analysis of the relationship between rationality and self knowledge; and (c) it informs diagnosis and therapy in clinical psychiatry. However, authorship cannot provide a demarcation criterion between delusions and other irrational belief states
On Selfish Memes: culture as complex adaptive system
We present the formal definition of meme in the sense of the equivalence between memetics and the theory of cultural evolution. From the formal definition we find that
culture can be seen analytically and persuade that memetic gives important role in the exploration of sociological theory, especially in the cultural studies. We show that we are not allowed to assume meme as smallest information unit in cultural evolution in general, but it is the smallest information we use on explaining cultural evolution. We construct a computational model and do simulation in advance presenting the selfish meme powerlaw
distributed. The simulation result shows that the contagion of meme as well as cultural evolution is a complex adaptive system. Memetics is the system and art of
importing genetics to social sciences
What If? The Art of Scenario Thinking for Nonprofits
Gives an overview of scenario thinking customized for a nonprofit audience. Outlines the basic phases of scenario development, and provides examples and advice for putting the process into practice. Includes an annotated bibliography of select readings
MLCapsule: Guarded Offline Deployment of Machine Learning as a Service
With the widespread use of machine learning (ML) techniques, ML as a service
has become increasingly popular. In this setting, an ML model resides on a
server and users can query it with their data via an API. However, if the
user's input is sensitive, sending it to the server is undesirable and
sometimes even legally not possible. Equally, the service provider does not
want to share the model by sending it to the client for protecting its
intellectual property and pay-per-query business model.
In this paper, we propose MLCapsule, a guarded offline deployment of machine
learning as a service. MLCapsule executes the model locally on the user's side
and therefore the data never leaves the client. Meanwhile, MLCapsule offers the
service provider the same level of control and security of its model as the
commonly used server-side execution. In addition, MLCapsule is applicable to
offline applications that require local execution. Beyond protecting against
direct model access, we couple the secure offline deployment with defenses
against advanced attacks on machine learning models such as model stealing,
reverse engineering, and membership inference
Air Traffic Management Safety Challenges
The primary goal of the Air Traffic Management (ATM) system is to control accident risk. ATM
safety has improved over the decades for many reasons, from better equipment to additional
safety defences. But ATM safety targets, improving on current performance, are now extremely
demanding. Safety analysts and aviation decision-makers have to make safety assessments
based on statistically incomplete evidence. If future risks cannot be estimated with precision,
then how is safety to be assured with traffic growth and operational/technical changes? What
are the design implications for the USA’s ‘Next Generation Air Transportation System’
(NextGen) and Europe’s Single European Sky ATM Research Programme (SESAR)? ATM
accident precursors arise from (eg) pilot/controller workload, miscommunication, and lack of upto-
date information. Can these accident precursors confidently be ‘designed out’ by (eg) better
system knowledge across ATM participants, automatic safety checks, and machine rather than
voice communication? Future potentially hazardous situations could be as ‘messy’ in system
terms as the Überlingen mid-air collision. Are ATM safety regulation policies fit for purpose: is it
more and more difficult to innovate, to introduce new technologies and novel operational
concepts? Must regulators be more active, eg more inspections and monitoring of real
operational and organisational practices
Impact of public release of performance data on the behaviour of healthcare consumers and providers.
BACKGROUND: It is becoming increasingly common to publish information about the quality and performance of healthcare organisations and individual professionals. However, we do not know how this information is used, or the extent to which such reporting leads to quality improvement by changing the behaviour of healthcare consumers, providers, and purchasers.
OBJECTIVES: To estimate the effects of public release of performance data, from any source, on changing the healthcare utilisation behaviour of healthcare consumers, providers (professionals and organisations), and purchasers of care. In addition, we sought to estimate the effects on healthcare provider performance, patient outcomes, and staff morale.
SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, and two trials registers on 26 June 2017. We checked reference lists of all included studies to identify additional studies.
SELECTION CRITERIA: We searched for randomised or non-randomised trials, interrupted time series, and controlled before-after studies of the effects of publicly releasing data regarding any aspect of the performance of healthcare organisations or professionals. Each study had to report at least one main outcome related to selecting or changing care.
DATA COLLECTION AND ANALYSIS: Two review authors independently screened studies for eligibility and extracted data. For each study, we extracted data about the target groups (healthcare consumers, healthcare providers, and healthcare purchasers), performance data, main outcomes (choice of healthcare provider, and improvement by means of changes in care), and other outcomes (awareness, attitude, knowledge of performance data, and costs). Given the substantial degree of clinical and methodological heterogeneity between the studies, we presented the findings for each policy in a structured format, but did not undertake a meta-analysis.
MAIN RESULTS: We included 12 studies that analysed data from more than 7570 providers (e.g. professionals and organisations), and a further 3,333,386 clinical encounters (e.g. patient referrals, prescriptions). We included four cluster-randomised trials, one cluster-non-randomised trial, six interrupted time series studies, and one controlled before-after study. Eight studies were undertaken in the USA, and one each in Canada, Korea, China, and The Netherlands. Four studies examined the effect of public release of performance data on consumer healthcare choices, and four on improving quality.There was low-certainty evidence that public release of performance data may make little or no difference to long-term healthcare utilisation by healthcare consumers (3 studies; 18,294 insurance plan beneficiaries), or providers (4 studies; 3,000,000 births, and 67 healthcare providers), or to provider performance (1 study; 82 providers). However, there was also low-certainty evidence to suggest that public release of performance data may slightly improve some patient outcomes (5 studies, 315,092 hospitalisations, and 7502 providers). There was low-certainty evidence from a single study to suggest that public release of performance data may have differential effects on disadvantaged populations. There was no evidence about effects on healthcare utilisation decisions by purchasers, or adverse effects.
AUTHORS\u27 CONCLUSIONS: The existing evidence base is inadequate to directly inform policy and practice. Further studies should consider whether public release of performance data can improve patient outcomes, as well as healthcare processes
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