Collaborative cross-checking to enhance resilience

Resilience, the ability to adapt or absorb disturbance, disruption, and change, may be increased by team processes in a complex, socio-technical system. In particular, collaborative cross-checking is a strategy where at least two individuals or groups with different perspectives examine the others’ assumptions and/or actions to assess validity or accuracy. With this strategy, erroneous assessments or actions can be detected quickly enough to mitigate or eliminate negative consequences. In this paper, we seek to add to the understanding of the elements that are needed in effective cross-checking and the limitations of the strategy. We define collaborative cross-checking, describe in detail three healthcare incidents where collaborative cross-checks played a key role, and discuss the implications of emerging patterns.     

A web-based formative assessment tool for Masters students: A pilot study

The use of web-based learning and assessment tools is growing in tertiary institutions around the world. To date, very few papers have reported the development and evaluation of a web-based formative assessment tool for postgraduate students. The aim of the present paper was to report on the development and evaluation of an online formative assessment tool for this student group. The web-based formative assessment tool was evaluated by a sample of undergraduate students, postgraduate students and academic staff within a psychology department in order to determine the suitability and sensitivity of the tool. The results of this pilot test suggest that the development of such a tool is both appropriate and feasible for Masters students studying psychology.     

The Effects of Survey Administration on Disclosure Rates to Sensitive Items Among Men: A Comparison of an Internet Panel Sample with a RDD Telephone Sample

Research using Internet surveys is an emerging field, yet research on the legitimacy of using Internet studies, particularly those targeting sensitive topics, remains under-investigated. The current study builds on the existing literature by exploring the demographic differences between Internet panel and RDD telephone survey samples, as well as differences in responses with regard to experiences of intimate partner violence perpetration and victimization, alcohol and substance use/abuse, PTSD symptomatology, and social support. Analyses indicated that after controlling for demographic differences, there were few differences between the samples in their disclosure of sensitive information, and that the online sample was more socially isolated than the phone sample. Results are discussed in terms of their implications for using Internet samples in research on sensitive topics.     

Speech Recognition and In-Vehicle Telematics Devices: Potential Reductions in Driver Distraction

Speech Recognition is frequently cited as a potential remedy to distraction resulting from drivers' operation of in-vehicle devices. This position typically assumes that the introduction of speech recognition will result in reduced cognitive workload and improved driving performance. Past research neither fully supports nor fully discounts this assumption. However, it is difficult to compare many of these studies, due to differences in device operation tasks, the pacing of those tasks, speech recognition system performance, and system interface designs. In an effort to directly address the effect of voice recognition on driver distraction, the present authors developed a capability to manipulate the performance characteristics of a speech recognition system through a Wizard of Oz speech recognition system and installed this system in a simulated driving environment. The sensitivity of the simulated driving environment and speech recognition accuracy manipulation were evaluated in an initial study comparing driver cognitive workload and driving performance during self-paced simulated operation of a personal digital assistant (PDA) during no PDA use, manual control of the PDA, and speech control of the PDA. In the Speech PDA condition, speech recognition accuracy was varied between drivers. Analysis of drivers' emergency braking response times and rated cognitive workload revealed significantly lower cognitive demand and better performance in the No PDA condition when compared to the Manual PDA condition. The Speech PDA condition resulted in response times and rated cognitive workload levels that were between the No PDA and Manual PDA conditions, but not significantly different from either of these conditions. Further analysis of emergency braking performance revealed a non-significant trend towards better performance in conjunction with higher speech recognition accuracy levels. The potential for reducing driver distraction through the careful development and evaluation of speech recognition systems is discussed.     

No pain and gain!—experiences with Mentat on a biological application

Throughout much of the parallel processing community there is the sense that writing software for distributed-memory parallel processors Is subject to a ‘no pain—no gain’ rule: that In order to reap the benefits of parallel computation one must first suffer the pain of converting the application to run on a parallel machine. We believe this Is the result of Inadequate programming tools and not a problem Inherent to parallel processing. We will show that one can parallelize real scientific applications and obtain good performance with little effort If the right tools are used. Our vehicle for this demonstration is a 6000-line DNA and protein sequence comparison application that we have implemented in Mental, an object-oriented parallel processing system for both parallel and distributed architectures. We briefly describe the application and present performance information for both the Mentat version and a hand-coded parallel version of the application.     

Sharing the floodplain: Mediated modeling for environmental management

Complex ecosystems, such as the Upper Mississippi River (UMR), present major management challenges. Such systems often provide a range of ecosystem services that are differentially valued by stakeholders representing distinct interests (e.g., agriculture, conservation, navigation) or institutions (e.g., federal and state agencies). When no single entity has the knowledge or authority to resolve conflicts over shared resource use, stakeholders may struggle to jointly understand the scope of the problem and to reach reasonable compromises. This paper explores mediated modeling as a group consensus building process for understanding relationships between ecological, economic and cultural well-being in the UMR floodplain. We describe a workshop structure used to engage UMR stakeholders that may be extended to resource use conflicts in other complex ecosystems. We provide recommendations for improving on these participatory methods in structuring future efforts. In conclusion, we suggest that tools which facilitate collaborative learning, such as mediated modeling, need to be incorporated at an institutional level as a vital element of integrated ecosystem management.     

Preference-based topology optimization for vehicle concept design with concurrent static and crash load cases

In the simulation-based design process of automotive structures, an increasing amount of multi-disciplinary requirements have to be considered. Methods of topology optimization can be used to devise structural concepts early in the design process to obtain the best possible structural layout as starting point for further development steps. Especially relevant for the vehicle design process is the concurrent consideration of static load requirements representing normal operating conditions and energy absorption requirements targeting passive safety in crash events. When the disciplines are considered separately, the heuristic Hybrid Cellular Automaton topology optimization is a suitable method. However, in practical applications, both disciplines are usually addressed sequentially. This complicates the overall process and may reduce the quality of the final optimization result, since optimization objectives may be conflicting. We propose a preference-based Scaled Energy Weighting approach to address the topology optimization of both disciplines concurrently. The main idea is to decouple the user preference from the scaling of the different magnitudes of energies. This enables a multi-objective optimization and ultimately the selection of the desired trade-off solution. We first validate the capability of the method to provide structures optimized for stiffness and energy absorption objectives on beam examples. Finally, the method is applied to optimize a concept structure of an industrial vehicle body, demonstrating its practical feasibility.