Telecommunications Power Plant Damage Assessment for Hurricane Katrina– Site Survey and Follow-Up Results

This paper extends knowledge of disaster impact on the telecommunications power infrastructure by discussing the effects of Hurricane Katrina based on an on-site survey conducted in October 2005 and on public sources. It includes observations about power infrastructure damage in wire-line and wireless networks. In general, the impact on centralized network elements was more severe than on the distributed portion of the grids. The main cause of outage was lack of power due to fuel supply disruptions, flooding and security issues. This work also describes the means used to restore telecommunications services and proposes ways to improve logistics, such as coordinating portable generator set deployment among different network operators and reducing genset fuel consumption by installing permanent photovoltaic systems at sites where long electric outages are likely. One long term solution is to use of distributed generation. It also discusses the consequences on telecom power technology and practices since the storm.     

Monitoring children’s developmental progress using augmented toys and activity recognition

Previous research has established the connection between the way in which children interact with objects and the potential early identification of children with autism. Those findings motivate our own work to develop "smart toys," objects embedded with wireless sensors that are safe and enjoyable for very small children, that allow detailed interaction data to be easily recorded. These sensor-enabled toys provide opportunities for autism research by reducing the effort required to collect and analyze a child’s interactions with objects. In the future, such toys may be a useful part of clinical and in-home assessment tools. In this paper, we discuss the design of a collection of smart toys that can be used to automatically characterize the way in which a child is playing. We use statistical models to provide objective, quantitative measures of object play interactions. We also developed a tool to view rich forms of annotated play data for later analysis. We report the results of recognition experiments on more than fifty play sessions conducted with adults and children as well as discuss the opportunities for using this approach to support video annotation and other applications.     

Manual patient transfers: factors that influence decisions and kinematic strategies employed by nursing aides

While extensive literature has characterised factors that influence the acceptable mass of ‘boxes’ during MMH tasks, less is known about these factors when moving ‘people’ in healthcare settings. This study examined factors that influence decisions/approaches employed during manual patient transfers. Sixteen nursing aides manually-transferred a standardised ‘patient’; patient mass was adjusted (using a weight vest) to determine a maximum acceptable patient mass for this task (mass_max). Grip strength was the only worker characteristic significantly associated with mass_max (r?=?0.48). Older worker age was associated with smaller peak trunk flexion (r?= ?0.58) and shoulder abduction (r?= ?0.59), and greater trunk axial twist (r?=?0.52). Workers emphasised that patient characteristics (e.g. physical/cognitive status) influenced their decisions when performing transfers. These findings extend previous literature by suggesting that grip strength is a useful predictor of perceived work capacity, older workers adapt protective postural strategies during patient transfers and worker-patient dynamics are crucial during this high-risk occupational task.

Practitioner Summary: This study examined manual patient transfers performed by nursing aides. Worker grip strength (but not age or size) was associated with perceptions of maximum acceptable patient mass. Kinematic changes suggested more conservative strategies used by older workers. Workers emphasised that patient characteristics substantially influenced their decisions when performing transfer tasks.     

Perceived risk for influenza in veterans with spinal cord injuries and disorders.

Objective: Guided by the extended parallel process model (EPPM), the objective was to assess control processes dominant in influenza behavior decisions. Design: Cross-sectional survey. Results: Response rate was 31% (n=968). Regarding influenza risk, 59% were in danger control. Those in fear control were more likely to report influenza infection (p=.000). In the nonvaccinated, those in fear control were more likely to indicate not knowing where to get the vaccine (p=.016) and that it was unavailable (p=.027), and those in danger control believed they did not need it (p=.023). Zero critical values were more likely to indicate that no health provider recommended the shot (p=.002). Conclusions: Most perceived efficacy to be stronger than threat related to influenza; according to the EPPM, they are aware of their risk but recognize their ability to avert it. For those in danger control, messages should focus on increasing perceptions of severity and susceptibility to positively affect behavior change. For those in fear control, messages should focus on efficacy only. With a critical value of zero, no threat is induced, and a high-threat/high-efficacy approach should be taken. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An analytical framework for local feedforward networks

Interference in neural networks occurs when learning in one area of the input space causes unlearning in another area. Networks that are less susceptible to interference are referred to as spatially local networks. To obtain a better understanding of these properties, a theoretical framework, consisting of a measure of interference and a measure of network localization, is developed. These measures incorporate not only the network weights and architecture but also the learning algorithm. Using this framework to analyze sigmoidal, multilayer perceptron (MLP) networks that employ the backpropagation learning algorithm on the quadratic cost function, we address a familiar misconception that single-hidden-layer sigmoidal networks are inherently nonlocal by demonstrating that given a sufficiently large number of adjustable weights, single-hidden-layer sigmoidal MLPs exist that are arbitrarily local and retain the ability to approximate any continuous function on a compact domain.     

Optimization of anisotropic composite panels with T-shaped stiffeners including transverse shear effects and out-of-plane loading

A two-step method to optimize anisotropic composite panels with T-shaped stiffeners, including a new formulation of the transverse shear properties and an approximation of the ply contiguity (blocking) constraints as functions of the lamination parameters is provided. At the first step, a representative element of the stiffened panel (superstiffener) is optimized using mathematical programming and lamination parameters subjected to combined loading (in-plane and out-of-plane) under strength (laminate or ply failure), buckling and practical design constraints. Ply blocking constraints are imposed at this step to improve convergence towards practical laminates. At the second step, the actual superstiffener’s laminates are obtained by using a genetic algorithm. Results, for the case considered, show that the inclusion of transverse shear effects has an associated 2.5% mass penalty and that neglecting its effects might invoke earlier buckling failure. In addition, the influence of designing for failure strength at laminate or ply level is assessed.     

Computational auditory models in predicting noise reduction performance for wideband telephony applications

The performance of several noise reduction algorithms intended for wideband telephony was evaluated both subjectively and objectively. The chosen algorithms were based on statistical modeling, spectral subtraction, Wiener filtering, or subspace modelling principles. A customized wideband noise reduction database containing speech samples corrupted by three types of background noises at three SNR levels, along with their enhanced versions was created. The overall quality of the speech samples in the database was subsequently rated by a group of listeners with normal hearing capabilities. Comprehensive statistical analyses were performed to assess the reliability of the subjective data, and to assess the performance of noise reduction algorithms across varied noisy conditions. The subjective quality ratings were then used to investigate the performance of several auditory model-based objective quality metrics. Key results from these investigations include: (a) there was a high degree of inter- and intra-subject reliability in the subjective ratings, (b) noise reduction algorithms enhance speech quality for only a subset of the noise conditions, and (c) auditory model-based metrics perform similarly in predicting speech quality ratings, when speech quality scores pertaining to a particular noise condition were averaged.     

A wearable computer-based American sign Language Recogniser

Modern wearable computer designs package workstation-level performance in systems small enough to be worn as clothing. These machines enable technology to be brought where it is needed most for the handicapped: everyday mobile environments. This paper describes a research effort to make a wearable computer that can recognise (with the possible goal of translating) sentence-level American Sign Language (ASL) using only a baseball cap mounted camera for input. Current accuracy exceeds 97% per word on a 40-word lexicon.