NOAA Radios and Neighbourhood Networks: Demographic Factors for Channel Preference for Hurricane Evacuation Information

This paper reviews literature on information channel type and disasters, and presents results on hurricane evacuation information gathering. Results show that respondents reported they would use television and radio most frequently for gathering information about hurricane evacuation. Minority respondents reported more preference of the use of community or local government as information sources than white respondents, females gathered information from multiple channels more than males, and younger residents gathered information from multiple channels more than older respondents. Implications include areas for future research in how channel utilization occurs during slow onset hazards in predominantly black communities, how age and gender relate to channel preference, and how channel preferences affect length of time to make decisions and engage in protective actions.     

Computer Vision Techniques Applied for Diagnostic Analysis of Retinal OCT Images: A Review

The retina is a tiny layer at the posterior pole of an eye and is made up of tissues sensitive to light, these tissues generate nerve signals that pass through the optic nerve to the brain. A retinal disorder occurs when the retina malfunctions; glaucoma, diabetic retinopathy and pathologic myopia are retinal disorders and principal causes of blindness worldwide. These retinal disorders are often diagnosed and treated by an ophthalmologist. However, to accurately assess a retinal disease, ophthalmologist would need qualitative and quantitative analysis of the disease, it’s early and current statistics, but acquisition of these measurements are not possible through manual techniques, there should be automated computer aided diagnosis (CAD) systems to assist ophthalmologists. In this comprehensive review, an analysis and evaluation has been performed of different computer vision and image processing approaches applied to OCT images for automatic diagnosis of retinal disorders. We also reported disease causes, symptoms and pathologies manifestations within OCT images, which can serve as baseline knowledge for development of an automated CAD system. Hence, this disease specific review offers a good understanding to analyze visual impairments from retinal OCT images which will help researcher to design enhanced therapeutic systems for retinal disorders.     

Seeing the woods for the trees: the problem of information inefficiency and information overload on operator performance

One of the recurring questions in designing dynamic control environments is whether providing more information leads to better operational decisions. The idea of having every piece of information is increasingly tempting (and in safety critical domains often mandatory) but has become a potential obstacle for designers and operators. The present research study examined this challenge of appropriate information design and usability within a railway control setting. A laboratory study was conducted to investigate the presentation of different levels of information (taken from data processing framework, Dadashi et al. in Ergonomics 57(3):387–402, 2014) and the association with, and potential prediction of, the performance of a human operator when completing a cognitively demanding problem-solving scenario within railways. Results indicated that presenting users only with information corresponding to their cognitive task, and in the absence of other, non task-relevant information, improves the performance of their problem-solving/alarm handling. Knowing the key features of interest to various agents (machine or human) and using the data processing framework to guide the optimal level of information required by each of these agents could potentially lead to safer and more usable designs.     

Emulation of complex open quantum systems using superconducting qubits

With quantum computers being out of reach for now, quantum simulators are alternative devices for efficient and accurate simulation of problems that are challenging to tackle using conventional computers. Quantum simulators are classified into analog and digital, with the possibility of constructing “hybrid” simulators by combining both techniques. Here we focus on analog quantum simulators of open quantum systems and address the limit that they can beat classical computers. In particular, as an example, we discuss simulation of the chlorosome light-harvesting antenna from green sulfur bacteria with over 250 phonon modes coupled to each electronic state. Furthermore, we propose physical setups that can be used to reproduce the quantum dynamics of a standard and multiple-mode Holstein model. The proposed scheme is based on currently available technology of superconducting circuits consist of flux qubits and quantum oscillators.     

The impact of map orientation and generalisation on congestion decisions: a comparison of schematic-egocentric and topographic-allocentric maps

Map information for drivers is usually presented in an allocentric-topographic form (as with printed maps) or in an egocentric-schematic form (as with road signs). The advent of new variable message boards on UK motorways raises the possibility of presenting road maps to reflect congestion ahead. Should these maps be allocentric-topographic or egocentric-schematic? This was assessed in an eye tracking study, with participants viewing maps of a motorway network in order to identify whether any congestion was relevant to their intended route. The schematic-egocentric maps were responded to most accurately with shorter fixation durations suggesting easier processing. In particular, the driver's entrance and intended exit from the map were attended to more in the allocentric maps. Individual differences in mental rotation ability also seem to contribute to poor performance on allocentric maps. The results favour schematic-egocentric maps for roadside congestion information, but also provide theoretical insights into map-rotation and individual differences. Statement of Relevance: This study informs designers and policy makers about optimum representations of traffic congestion on roadside variable message signs and, furthermore, demonstrates that individual differences contribute to problems with processing certain sign types. Schematic-egocentric representations of a motorway network produced the best results, as noted in behavioural and eye movement measures.     

Test-retest reliability of Purdue Pegboard performance in thermoneutral and cold ambient conditions

In the cold, Purdue Pegboard (PP) performance declines. The purpose of this study was to determine if this cold-induced impairment is consistent across days (i.e. test-retest reliability) in 5°C. In thermoneutral air (25°C), 14 men were familiarised to the dominant hand (PPa) and bimanual (PPb) PP tasks. They then experienced two 90-min cold exposures (Day 1, Day 2) while wearing ～1 clo. Bare hands were maintained throughout. Performance on both tasks showed high reliability from day to day (intraclass correlations >0.700) in both thermoneutral and cold conditions. However for both tasks, room temperature performance did not predict performance in the cold (intraclass correlations <0.450). When screening applicants for manual labour in the cold, one must consider that room temperature dexterity does not correlate with dexterity in the cold. It is recommended that a 60-min period of cold exposure be employed to assess manual dexterity in these workers. STATEMENT OF RELEVANCE: This study shows that PP performance in room temperature does not predict performance in the cold but performance in the cold is consistent from day to day. When screening applicants for manual labour in the cold, it is recommended that dexterity tests be conducted in the same ambient conditions.     

A forward-constrained regression algorithm for sparse kernel density estimation.

Using the classical Parzen window (PW) estimate as the target function, the sparse kernel density estimator is constructed in a forward-constrained regression (FCR) manner. The proposed algorithm selects significant kernels one at a time, while the leave-one-out (LOO) test score is minimized subject to a simple positivity constraint in each forward stage. The model parameter estimation in each forward stage is simply the solution of jackknife parameter estimator for a single parameter, subject to the same positivity constraint check. For each selected kernels, the associated kernel width is updated via the Gauss-Newton method with the model parameter estimate fixed. The proposed approach is simple to implement and the associated computational cost is very low. Numerical examples are employed to demonstrate the efficacy of the proposed approach.     

Development of a generic activities model of command and control

This paper reports on five different models of command and control. Four different models are reviewed: a process model, a contextual control model, a decision ladder model and a functional model. Further to this, command and control activities are analysed in three distinct domains: armed forces, emergency services and civilian services. From this analysis, taxonomies of command and control activities are developed that give rise to an activities model of command and control. This model will be used to guide further research into technological support of command and control activities.     

Icon identification in context: the changing role of icon characteristics with user experience

OBJECTIVE: This research examined the relative importance of icon characteristics in determining the speed and accuracy of icon identification. BACKGROUND: Studies to date have focused on the role of one or two icon characteristics when users first experience an icon set. This means that little is known about the relative importance of icon characteristics or how the role of icon characteristics might change as users gain experience with icons. METHODS: Thirty participants carried out an icon identification task over a long series of trials to simulate learning through experience. Icon characteristics investigated included semantic distance, concreteness, familiarity, and visual complexity. RESULTS: Icon characteristics were major determinants of performance, accounting for up to 69% of the variance observed in performance. However, the importance of icon characteristics changed with experience: Semantic distance is crucial initially while icon-function relationships are learned, but familiarity is important later because it has lasting effects on access to long-term memory representations. CONCLUSION: These findings suggest that icon concreteness may not be of primary importance when identifying icons and that semantic distance and familiarity may be more important. APPLICATION: Designers need to take into account icon characteristics other than concreteness when creating icons, particularly semantic distance and familiarity. The precise importance of the latter characteristics will vary depending on whether icons are rarely encountered or frequently used.