Reliability-based design optimization with confidence level under input model uncertainty due to limited test data

For obtaining a correct reliability-based optimum design, the input statistical model, which includes marginal and joint distributions of input random variables, needs to be accurately estimated. However, in most engineering applications, only limited data on input variables are available due to expensive testing costs. The input statistical model estimated from the insufficient data will be inaccurate, which leads to an unreliable optimum design. In this paper, reliability-based design optimization (RBDO) with the confidence level for input normal random variables is proposed to offset the inaccurate estimation of the input statistical model by using adjusted standard deviation and correlation coefficient that include the effect of inaccurate estimation of mean, standard deviation, and correlation coefficient.     

A scalable and self-adapting notification framework for healthcare information systems

There has been a great interest in publish/subscribe systems in recent years. This interest, coupled with the pervasiveness of light-weight electronic devices, such as cellular phones and personal digital assistants, has opened a new arena in publish/subscribe networks. Currently, many broker overlay networks are static and rarely change in structure. Often, a network overlay structure is predefined or manually modified. This paper presents a dynamic broker network for disseminating critical lab and patient information in a Healthcare information system. The reported work builds upon previous network optimization research on ad hoc publish/subscribe networks. The underlying framework utilizes user-defined cost functions to satisfy quality of service constraints. In essence, the broker network optimization problem is reduced to an incremental search problem to generate low cost network configurations. Certain reliability issues are also addressed by providing a scheduling algorithm to selectively retransmit information and handle broker connectivity failures.     

On tracing reactive systems

We present a rich and highly dynamic technique for analyzing, visualizing, and exploring the execution traces of reactive systems. The two inputs are a designer’s inter-object scenario-based behavioral model, visually described using a UML2-compliant dialect of live sequence charts (LSC), and an execution trace of the system. Our method allows one to visualize, navigate through, and explore, the activation and progress of the scenarios as they “come to life” during execution. Thus, a concrete system’s runtime is recorded and viewed through abstractions provided by behavioral models used for its design, tying the visualization and exploration of system execution traces to model-driven engineering. We support both event-based and real-time-based tracing, and use details-on-demand mechanisms, multi-scaling grids, and gradient coloring methods. Novel model exploration techniques include semantics-based navigation, filtering, and trace comparison. The ideas are implemented and tested in a prototype tool called the Tracer.     

Capturing the response of players to a location-based game

Location-based games offer opportunities for us to learn more about people’s interactions and feelings towards the environment they are in as well as to understand more about the mental models and locations associated with known environments, e.g. a university campus with its associations of learning. In our study, we wanted to manipulate the activities in a game to take advantage of certain locations in the hope of producing certain emotional reactions. However, it is not enough to simply produce these reactions; one must also have a way of capturing any emotions produced whether these are the ones expected or not. The objective of this paper, therefore, was to trial a new methodology for location-based games that aims at capturing the players’ emotional reactions to the activities in a game whilst in certain locations. In order to test the methodology, we designed a location-based game that can be played on any Bluetooth-enabled mobile phone that has an accelerometer. The game has been designed to interweave with a persons’ normal activity. As a result, there is little distinction between gaming time and non-gaming time.     

Adaptive autonomous underwater vehicles for littoral surveillance

Autonomous underwater vehicles (AUVs) have gained more interest in recent years for military as well as civilian applications. One potential application of AUVs is for the purpose of undersea surveillance. As research into undersea surveillance using AUVs progresses, issues arise as to how an AUV acquires, acts on, and shares information about the undersea battle space. These issues naturally touch on aspects of vehicle autonomy and underwater communications, and need to be resolved through a spiral development process that includes at sea experimentation. This paper presents a recent AUV implementation for active anti-submarine warfare tested at sea in the summer of 2010. On-board signal processing capabilities and an adaptive behavior are discussed in both a simulation and experimental context. The implications for underwater surveillance using AUVs are discussed.     

Tissue dynamics spectroscopy for three-dimensional tissue-based drug screening

Tissue dynamics spectroscopy combines dynamic light scattering with short-coherence digital holography to capture intracellular motion inside multicellular tumor spheroid tissue models. The cellular mechanical activity becomes an endogenous imaging contrast agent for motility contrast imaging. Fluctuation spectroscopy is performed on dynamic speckle from the proliferating shell and hypoxic core to generate drug-response spectrograms that are frequency versus time representations of the changes in spectral content induced by an applied compound or an environmental perturbation. A combination of 28 reference compounds and conditions applied to rat osteogenic UMR-106 spheroids generated spectrograms that were crosscorrelated in a similarity matrix used for unsupervised hierarchical clustering of similar compound responses. This work establishes the feasibility of tissue dynamics spectroscopy for three-dimensional tissue-based phenotypic profiling of drug response as a fully endogenous probe of the response of tissue to reference compounds.     

The Design with Intent Method: A design tool for influencing user behaviour

Using product and system design to influence user behaviour offers potential for improving performance and reducing user error, yet little guidance is available at the concept generation stage for design teams briefed with influencing user behaviour. This article presents the Design with Intent Method, an innovation tool for designers working in this area, illustrated via application to an everyday human-technology interaction problem: reducing the likelihood of a customer leaving his or her card in an automatic teller machine. The example application results in a range of feasible design concepts which are comparable to existing developments in ATM design, demonstrating that the method has potential for development and application as part of a user-centred design process.     

Sleep in a live-in mining operation: The influence of start times and restricted non-work activities

The amount of sleep obtained between shifts is influenced by numerous factors including the length of work and rest periods, the timing of the rest period relative to the endogenous circadian cycle and personal choices about the use of non-work time. The current study utilised a real-world live-in mining environment to examine the amount of sleep obtained when access to normal domestic, family and social activities was restricted. Participants were 29 mining operators (26 male, average age 37.4 ± 6.8 years) who recorded sleep, work and fatigue information and wore an activity monitor for a cycle of seven day shifts and seven night shifts (both 12 h) followed by either seven or fourteen days off. During the two weeks of work participants lived on-site. Total sleep time was significantly less (p < 0.01) while on-site on both day (6.1 ± 1.0 h) and night shifts (5.7 ± 1.5 h) than days off (7.4 ± 1.4 h). Further, night shift sleep was significantly shorter than day-shift sleep (p < 0.01). Assessment of subjective fatigue ratings showed that the sleep associated with both days off and night shifts had a greater recovery value than sleep associated with day shifts (p < 0.01). While on-site, participants obtained only 6 h of sleep indicating that the absence of competing domestic, family and social activities did not convert to more sleep. Factors including shift start times and circadian influences appear to have been more important.