Behavioral Validation of the Smartphone for Remote Microphone Technology

As part of a National Institutes of Health–National Institute on Deafness and Other communication Disorders (NIH-NIDCD)–supported project to develop open-source research and smartphone-based apps for enhancing speech recognition in noise, an app called Smartphone Hearing Aid Research Project Version 2 (SHARP-2) was tested with persons with normal and impaired hearing when using three sets of hearing aids (HAs) with wireless connectivity to an iPhone. Participants were asked to type sentences presented from a speaker in front of them while hearing noise from behind in two conditions, HA alone and HA + SHARP-2 app running on the iPhone. The signal was presented at a constant level of 65 dBA and the signal-to-noise ratio varied from −10 to +10, so that the task was difficult when listening through the bilateral HAs alone. This was important to allow for improvement to be measured when the HAs were connected to the SHARP-2 app on the smartphone. Benefit was achieved for most listeners with all three manufacturer HAs with the greatest improvements recorded for persons with normal (33.56%) and impaired hearing (22.21%) when using the SHARP-2 app with one manufacturer's made-for-all phones HAs. These results support the continued development of smartphone-based apps as an economical solution for enhancing speech recognition in noise for both persons with normal and impaired hearing.

Validation of a Driving Simulator Study on Driver Behavior at Passive Rail Level Crossings

Objective: The behavioral validation of an advanced driving simulator for its use in evaluating passive level crossing countermeasures was performed for stopping compliance and speed profile. Background: Despite the fact that most research on emerging interventions for improving level crossing safety is conducted in a driving simulator, no study has validated the use of a simulator for this type of research. Method: We monitored driver behavior at a selected passive level crossing in the Brisbane region in Australia for 3 months ( N = 916). The level crossing was then replicated in an advanced driving simulator, and we familiarized participant drivers ( N = 54) with traversing this crossing, characterized by low road and rail traffic. Results: We established relative validity for the stopping compliance and the approach speed. Conclusion: This validation study suggests that driving simulators are an appropriate tool to study the effects of interventions at passive level crossing with low road and rail traffic, which are prone to reduced compliance due to familiarity. Application: This study also provides support for the findings of previous driving simulator studies conducted to evaluate compliance and approach speeds of passive level crossings.

Application of Agent Based Simulation to analyze the impact of tax policy on soybean supply chain

This work seeks to explore and demonstrate the use of Agent Based Simulations (ABS) in modelling and simulating supply chains. Such methodology was applied to develop a model to evaluate the impact of current tax policies in soy supply chain in Brazil. The model brought interesting insights on how the country’s current tax structure induces logistics and tributary trade-offs, therefore generating a suboptimal grain distribution. This is accomplished by going through the conception and implementation of an Agent Based Model. First there is the definition and delimitation of the main agents acting upon soy’s supply chain, such as producers, trader and consumers. Those agents then have their behaviors studied and translated into programable patterns. Finally, the model considers the environmental interactions with the mentioned players, including the effects of infrastructure capacities, transportation costs, storage costs and tax legislation. After quantitative and behavioral validation, the simulation is then able to mimic the actual allocation of corn, soy and soymeal productions in their respective supply chains. This would allow inferring how the system could work in different tax conditions, thus quantifying the tributary impact in terms of congestions, idle infrastructure and delays. The analysis of such results points out that a path dependant tax system may induce agents to opt for inefficient logistic solutions, if such alternatives are cheaper when taking taxes into account. From those simulations it is possible to conclude that there are opportunities for supply chain efficiency gains in the design of a new tax policy.

Assessment of an Aggregate-Level Hand Hygiene Monitoring Technology for Measuring Hand Hygiene Performance Among Healthcare Personnel

BACKGROUNDDespite significant advances in technological methods for hand hygiene surveillance, a lack of evidence prohibits comparison of systems to one another or against the current gold standard of direct observation.OBJECTIVETo validate a hand hygiene monitoring technology (HHMT) designed to capture hand hygiene behaviors aggregated at the hospital-unit level (GOJO Industries, Akron, OH).METHODSOur team followed a rigorous validation approach to assess the sensitivity and positive predictive value (PPV) of an HHMT. A planned path was first used to measure the accuracy of the system when purposefully activated by investigators. Next, behavioral validation was used to quantify accuracy of the system in capturing real-world behaviors.RESULTSDuring the planned path phase, investigators performed 4,872 unique events across 3 distinct hospital buildings varying in size and age since construction. Overall sensitivity across the medical center was 88.7% with a PPV of 99.2%. During the behavioral validation phase, trained direct observers recorded 5,539 unique events across 3 distinct hospital buildings. Overall sensitivity across the medical center was 92.7% and PPV was 84.4%.CONCLUSIONObjective measures of sensitivity and PPV indicate the promise of the benefit of this and other HHMTs to capture basic behaviors associated with hand hygiene.Infect Control Hosp Epidemiol 2017;38:348–352