Objective evaluation of qualified viewing spaces for near‐to‐eye and autostereoscopic two‐view displays

Abstract— Virtual‐image (near‐to‐eye) and two‐view autostereoscopic (3‐D) displays share similar optical properties in the comfortable user position for viewing. In this paper, the definitions and criteria of qualified viewing space (QVS) and qualified stereoscopic viewing space (QSVS) are discussed. Due to the complex nature of these viewing spaces, the related presumptions and the required optical characteristics and their measurements are specified. The effects of different display and observer parameters, such as interpupillary distance, to the resulting viewing spaces are discussed. Finally, real measurement data of two autostereoscopic display devices are presented.     

On the human ability to discriminate audio ambiances from similar locations of an urban environment

When developing advanced location-based systems augmented with audio ambiances, it would be cost-effective to use a few representative samples from typical environments for describing a larger number of similar locations. The aim of this experiment was to study the human ability to discriminate audio ambiances recorded in similar locations of the same urban environment. A listening experiment consisting of material from three different environments and nine different locations was carried out with nineteen subjects to study the credibility of audio representations for certain environments which would diminish the need for collecting huge audio databases. The first goal was to study to what degree humans are able to recognize whether the recording has been made in an indicated location or in another similar location, when presented with the name of the place, location on a map, and the associated audio ambiance. The second goal was to study whether the ability to discriminate audio ambiances from different locations is affected by a visual cue, by presenting additional information in form of a photograph of the suggested location. The results indicate that audio ambiances from similar urban areas of the same city differ enough so that it is not acceptable to use a single recording as ambience to represent different yet similar locations. Including an image was found to increase the perceived credibility of all the audio samples in representing a certain location. The results suggest that developers of audio-augmented location-based systems should aim at using audio samples recorded on-site for each location in order to achieve a credible impression.     

An opinion on imaging challenges in phenotyping field crops

Almost all the world’s food is grown in open fields, where plant phenotypes can be very different from those observed in greenhouses. Geneticists and agronomists studying food crops routinely detect, measure, and classify a wide variety of phenotypes in fields that contain many visually distinct types of a single crop. Augmenting humans in these tasks by automatically interpreting images raises some important and nontrivial challenges for research in computer vision. Nonetheless, the rewards for overcoming these obstacles could be exceptionally high for today’s 7 billion people, let alone the 9.6 billion projected by 2050 (United Nations Department of Economic and Social Affairs, Population Division, World Population Prospects: The 2012 Revision). To stimulate dialog between researchers in computer vision and those in genetics and agronomy, we offer our views on three computational challenges that are central to many phenotyping tasks. These are disambiguating one plant from another; assigning an individual plant’s organs to it; and identifying field phenotypes from those shown in archival images. We illustrate these challenges with annotated photographs of maize highlighting the regions of interest. We also describe some of the experimental, logistical, and photographic constraints on image collection and processing. While collecting the data sets needed for algorithmic experiments requires sustained collaboration and funding, the images we show and have posted should allow one to consider the problems, think of possible approaches, and decide on the next steps.     

Stress calculation for plastic helical gears under a real transverse contact ratio

Calculation methods of plastic helical gears with a real transverse contact ratio have never been studied in depth. The methods used in some references assume a uniform load distribution along the line of contact or don’t take into consideration the effect of premature mesh between one or more pair of teeth during engagement, which is not in good agreement with numerical results. This paper is focused on analysis of plastic helical gears. The nonuniform load distribution obtained from the proposed mathematical model is based on the calculation of the real contact ratio representing the real number of pairs of teeth in contact. This model also leads to the distribution of the tooth bending stress and the contact stress along the area of contact.     

PECVDTM Coatings in Industrial Applications

The adoption of GPI's Linear PECVD^TM process has accelerated over the last year. Several R&D and production reactor modules were installed at major companies and a turnkey in‐line system was completed. Through these installations, customers are confirming the superior deposition rate, uniformity and stability of Linear PECVD^TM compared to reactive sputtering. Today Linear PECVD^TM is being used to deposit oxide and nitride films on a variety of substrates. The films include SiO₂, TiO₂, Al2₂O₃, SiN, ZnO, and SnO and the applications include multi‐layer AR coatings, single layer oxides and nitrides in combination with sputtered films, thin‐film solar coatings, barrier films, anti‐smudge coatings and TCO's. This progress demonstrates that GPI's Linear PECVD^TM technology may soon displace reactive sputtering of oxides and nitrides for large area substrates in architectural glass, flat panel display and flexible web applications.     

Retraining attitudes and stereotypes to affect motivation and cognitive capacity under stereotype threat.

In a series of experiments, a retraining paradigm was used to test the effects of attitudes and stereotypes on individuals' motivation and cognitive capacity in stereotype-threatening contexts. Women trained to have a more positive math attitude exhibited increased math motivation (Study 1). This effect was not observed for men but was magnified among women when negative stereotypes were either primed subtly (Study 2) or indirectly reinforced (Study 3). Although attitudes had no effect on working memory capacity, women retrained to associate their gender with being good at math exhibited increased working memory capacity (Studies 3 and 4), which in turn mediated increased math performance (Study 4) in a stereotype-threatening context. Results suggest that although positive attitudes can motivate stigmatized individuals to engage with threatening domains, stereotypes need to be retrained to give them the cognitive capacity critical for success. Implications for interventions to reduce stereotype threat are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The constructive role of diversity in the global response of coupled neuron systems

We study the effect that the heterogeneity present among the elements of an ensemble of coupled excitable neurons has on the collective response of the system to an external signal. We consider two different interaction scenarios, one in which the neurons are diffusively coupled and another in which the neurons interact via pulse-like signals. We find that the type of interaction between the neurons has a crucial role in determining the response of the system to the external modulation. We develop a mean-field theory based on an order parameter expansion that quantitatively reproduces the numerical results in the case of diffusive coupling.     

Fitting semi‐empirical drying models using a tool based on wavelet neural networks: Modeling a maize drying process

Maize drying is an important process, especially for storage and conservation. For this study, the experimental stage was carried out using a forced convection dryer with air heated at different temperature conditions (306.05–441.85 K) and flow (0.13–0.256 m³/hr), totalizing 15 drying curves. Then the performances of the classic drying kinetics methodology and the approach proposed in this paper, in which the increase in moisture content of the product with time was represented combining exponential models and neural networks based on wavelets, were compared. Good performance was obtained in predictions using the proposed approach. One of the main differentials of the methodology adopted was the obtainment of a model that has a global predictive capacity, within the range of tested operating conditions, which can be used in predicting drying curves for different operating conditions.

Practical applications

The drying process is also one of the most widely used methods for preserving food, and has the advantage of reducing the costs of storage and transport because of the low volume and weight of the end product. During the last years, this topic has attracted a broad industrial interest, resulting in many research studies investigating the drying process. Usually, with regard to the classic approach for modeling of the drying process, the kinetics of drying curves obtained in different operating conditions is affected separately, that is, the parameters are estimated independently, resulting in different regression problems. With the classical approach, in general, it is not possible to obtain a comprehensive prediction model with regards to operating conditions. We have proposed an alternative modeling method. Aiming to obtain a modeling tool with an overall predictive ability, an approach for drying kinetics prediction that combines exponential models and neural networks was proposed. The proposed modeling method was able to predict drying curves for different operating conditions.