817 research outputs found
Robust scheduling practices in the U.S. airline industry: Costs, returns, and inefficiencies
Airlines use robust scheduling to mitigate the impact of unforeseeable disruptions on profits. We examine how effectively three common practices—flexibility to swap aircraft, flexibility to reassign gates, and scheduled aircraft downtime—accomplish this goal. We first estimate a multiple-input, multiple-outcome production frontier, which defines the attainable set of outcomes from given inputs. We then recover unobserved input costs and calculate how expenditure on inputs affects outcomes and revenues. We find that the per-dollar return from expenditure on gates, or more effective management of existing gate capacity, is three times larger than the per-dollar returns from other inputs. Next, we use the estimated trade-offs faced by carriers along the frontier to measure the value to carriers of reducing delays. Finally, we calculate the improvement in carriers’ outcomes and profits if their operational inefficiencies are eliminated. On average, we estimate that operational inefficiencies cost carriers about $1.7 billion in revenue annually
Online multiple hypothesis testing for reproducible research
Modern data analysis frequently involves large-scale hypothesis testing,
which naturally gives rise to the problem of maintaining control of a suitable
type I error rate, such as the false discovery rate (FDR). In many biomedical
and technological applications, an additional complexity is that hypotheses are
tested in an online manner, one-by-one over time. However, traditional
procedures that control the FDR, such as the Benjamini-Hochberg procedure,
assume that all p-values are available to be tested at a single time point. To
address these challenges, a new field of methodology has developed over the
past 15 years showing how to control error rates for online multiple hypothesis
testing. In this framework, hypotheses arrive in a stream, and at each time
point the analyst decides whether to reject the current hypothesis based both
on the evidence against it, and on the previous rejection decisions. In this
paper, we present a comprehensive exposition of the literature on online error
rate control, with a review of key theory as well as a focus on applied
examples. We also provide simulation results comparing different online testing
algorithms and an up-to-date overview of the many methodological extensions
that have been proposed.Comment: Updated in response to reviewer comment
Policies and User Perception based Data Security in the Cloud
In today’s world, most of the companies migrated from desktop devices to the cloud. Cloud is a platform for storing large amount of data. Among this it is very necessary to provide data security over the un-trusted cloud. We cannot trust the cloud provider when sensitive data is stored in the cloud so that, various security aspects are required to protect sensitive data which is stored on the cloud. The main problem is that, how to deal with such security issues to protect sensitive data. With the help of policy based security, it is possible to minimize data security issues and to improve data privacy. This paper proposes a user perception framework. According to this framework, owner of the organization is able to tell which user of that organization will follow which rights. A particular user should provide his/her privileges to the owner and he will protect user’s data by giving full rights to access data based on the identification of the users
Learning from Many: Partner Exposure and Team Familiarity in Fluid Teams
In services where teams come together for short collaborations, managers are often advised to strive for high team familiarity so as to improve coordination and consequently, performance. However, inducing high team familiarity by keeping team membership intact can limit workers’ opportunities to acquire useful knowledge and alternative practices from exposure to a broader set of partners. We introduce an empirical measure for prior partner exposure and estimate its impact (along with that of team familiarity) on operational performance using data from the London Ambulance Service. Our analysis focuses on ambulance transports involving new paramedic recruits, where exogenous changes in team membership enable identification of the performance effect. Specifically, we investigate the impact of prior partner exposure on time spent during patient pickup at the scene and patient handover at the hospital. We find that the effect varies with the process characteristics. For the patient pickup process, which is less standardized, greater partner exposure directly improves performance. For the more standardized patient handover process, this beneficial effect is triggered beyond a threshold of sufficient individual experience. In addition, we find some evidence that this beneficial performance impact of prior partner exposure is amplified during periods of high workload, particularly for the patient handover process. Finally, a counterfactual analysis based on our estimates shows that a team formation strategy emphasizing partner exposure outperforms one that emphasizes team familiarity by about 9.2% in our empirical context
Zeolites to peptides: Statistical mechanics methods for structure solution and property evaluation
Methods in statistical mechanics are used to study structure and properties of zeolites and peptides. A Monte Carlo method is applied to solve structure of a newly synthesized zeolite. Understanding the structure of a zeolite could lead to optimization of chemical processes it is involved in. Dielectric constant and elastic modulus are calculated using a molecular dynamics method for a pure silica zeolite with and without the structure directing agent used in its synthesis. These properties are of interest due to the potential use of this zeolite as low dielectric constant material in manufacturing integrated circuits. Results of four methods probing energy landscapes in peptides are compared for four cyclic peptides. Their ability to equilibrate structural properties and their relative speeds are important in their ability to simulate complex structures. A docking study is carried out to probe interactions between two proteins, Cripto and Snail, and E-cadherin promoter. The study supports experimental evidence that Cripto is involved in expression of E-cadherin through a promoter priming mechanism. Finally, the use of computational models in the design of better vaccines is illustrated through an example of Influenza
As Low As Reasonably Practicable (ALARP), a moral model for clinical risk management in the setting of technology dependence
Children dependent upon life-prolonging medical technology are often subject to a constant background risk
of sudden death or catastrophic complications. Such children can be cared for in hospital, in an intensive care
environment with highly trained nurses and doctors able to deliver specialised, life-saving care immediately.
However, remaining in hospital, when life expectancy is limited can considered to be a harm in of itself.
Discharge home offers the possibility for an improved quality of life for the child and her family but comes with
significant medical risks.
When making decisions for children, two ethical models predominate, the promotion of the child's best
interests or the avoidance of harm. However, in some circumstances, particularly for children with life-limiting
and / or life-threatening illness, all options may be associated with risk. There are no good options, only
potentially harmful choices.
In this paper we explore decisions made by one family in such circumstances. We describe a model adopted
from risk management programmes beyond medicine, that offers a potential framework for identifying risks to
the child that are morally permissible. Some risks and harms to a child, not ordinarily permitted, may be
acceptable when undertaken in the pursuit of a specified desired good, so long as they are As Low as
Reasonably Practicable
Patients could share virtual medical appointments for better access to telemedicine
Shared medical appointments, whereby patients with similar medical conditions consult their medical practitioner together, alleviate pressure on the health system and provide an instant support network for the patient. Why not make them virtual
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