Modelling asymmetry in the peripheral auditory system of the lizard

The ears of lizards are highly directional. The directionality is generated by strong acoustical coupling of the eardrums. A simple lumped-parameter model of the ear followed by binaural comparisons has been shown to perform successful phonotaxis in robot implementations. However, such a model will produce localization errors in the form of response bias if the ears are asymmetrical. We have evaluated how large errors are generated by asymmetry using simulations of the ear model in Mathematica 5.2. The study shows that the effect of asymmetry is minimal around the most directional frequency of the ear, but that biases reduce the useful bandwidth of localization. This work was presented in part at the First European Workshop on Artificial Life and Robotics, Vienna, Austria, July 12–13, 2007     

A non-contact technique for determining the depth of zero-order gratings

Abstract

In this work we present a simple, non-contact method for characterizing the depth of deep zero-order diffraction gratings using standard visible optics. Form birefringence exhibited by zero-order structures alters the polarization state of light transmitted through them. The amount of change is dependent on several factors including the depth of the grating grooves. By recording the polarization changes of laser light transmitted through the sample we demonstrate how the depth of any grating with a known pitch may be determined. Results for many different gratings have been analysed and show good agreement with groove depths measured from scanning electron micrographs. From these results a universal relationship between the amount of polarization change and the depth of the grating grooves has been determined.     

Rice-like CuO nanostructures for sensitive electrochemical sensing of hydrazine

In this work, a low temperature aqueous chemical growth methodology was used for the fabrication of CuO nanostructures. The as-synthesised nanostructures were then elaborately characterised by number of analytical techniques such as scanning electron microscopy (SEM) and X-ray powder diffraction (XRD). The obtained nanostructures were observed to possess interlaced rice-shaped structural features with the length and width of individual rice determined to be in the range of 200–300 nm and 50–100 nm respectively. The unique nanostructures when utilised as electrode material exhibited excellent electro-catalytic potential towards oxidation of hydrazine in alkaline media. The excellent conductive of CuO added by the high surface area of obtained nanorice-like structures enabled development of highly sensitive (3087 µA mM⁻¹ cm⁻²), selective and stable electrochemical sensor for hydrazine. In addition, the successfully application of the developed sensor in spiked tap, bottled and industrial water samples for the detection of hydrazine suggested its feasibility for practical environmental application.

     

Defect passivation on cast-mono crystalline screen-printed cells

Cast-mono crystalline silicon wafers contain crystallographic defects, which can severely impact the electrical performance of solar cells. This paper demonstrates that applying hydrogenation processes at moderate temperatures to finished screen print cells can passivate dislocation clusters within the cast-mono crystalline silicon wafers far better than the hydrogenation received during standard commercial firing conditions. Efficiency enhancements of up to 2% absolute are demonstrated on wafers with high dislocation densities. The impact of illumination to manipulate the charge state of hydrogen during annealing is investigated and found to not be significant on the wafers used in this study. This finding is contrary to a previous study on similar wafers that concluded increased H^– or H⁰ from laser illumination was responsible for the further passivation of positively charged dangling bonds within the dislocation clusters.     

Emerging Cooperation With Minimal Effort: Rewarding Over Mimicking

This paper compares supervised and unsupervised learning mechanisms for the emergence of cooperative multiagent spatial coordination using a top-down approach. By observing the global performance of a group of homogeneous agents-supported by a nonglobal knowledge of their environment-we attempt to extract information about the minimum size of the agent neurocontroller and the type of learning mechanism that collectively generate high-performing and robust behaviors with minimal computational effort. Consequently, a methodology for obtaining controllers of minimal size is introduced and a comparative study between supervised and unsupervised learning mechanisms for the generation of successful collective behaviors is presented. We have developed a prototype simulated world for our studies. This case study is primarily a computer games inspired world but its main features are also biologically plausible. The two specific tasks that the agents are tested in are the competing strategies of obstacle-avoidance and target-achievement. We demonstrate that cooperative behavior among agents, which is supported only by limited communication, appears to be necessary for the problem's efficient solution and that learning by rewarding the behavior of agent groups constitutes a more efficient and computationally preferred generic approach than supervised learning approaches in such complex multiagent worlds     

Preference Learning for Cognitive Modeling: A Case Study on Entertainment Preferences

Learning from preferences, which provide means for expressing a subject's desires, constitutes an important topic in machine learning research. This paper presents a comparative study of four alternative instance preference learning algorithms (both linear and nonlinear). The case study investigated is to learn to predict the expressed entertainment preferences of children when playing physical games built on their personalized playing features ( entertainment modeling). Two of the approaches are derived from the literature-the large-margin algorithm (LMA) and preference learning with Gaussian processes-while the remaining two are custom-designed approaches for the problem under investigation: meta-LMA and neuroevolution. Preference learning techniques are combined with feature set selection methods permitting the construction of effective preference models, given suitable individual playing features. The underlying preference model that best reflects children preferences is obtained through neuroevolution: 82.22% of cross-validation accuracy in predicting reported entertainment in the main set of game survey experimentation. The model is able to correctly match expressed preferences in 66.66% of cases on previously unseen data (p -value = 0.0136) of a second physical activity control experiment. Results indicate the benefit of the use of neuroevolution and sequential forward selection for the investigated complex case study of cognitive modeling in physical games.     

Physical and temporal scaling considerations in a robot model of cricket calling song preference

The cerebellum has been implicated in higher cognitive functions including learning, memory, and attention as well as its well-known role in motor programming. Recent studies have suggested that the cerebellum plays a role in shifts of attention. We investigated the contribution of the cerebellum to visuospatial attentional ability in a trial-by-trial cueing task involving the covert orienting of spatial attention. We recorded event-related evoked potentials (ERPs) and reaction times (RTs) in patients with cerebellar degenerative disorders affecting mainly the lateral cerebellum and compared them to age-matched controls. The RT data demonstrated that both the cerebellar patients and control subjects responded to the valid cues faster than to the invalid cues for both the central and the peripheral cues. Consistent with the RT data, the ERP data showed a comparable generation of attention shift-related negativities during the cue-target interval for both the central and the peripheral cue experiments. The early negative component of the ERP to the target was also comparably modulated in both groups as a function of cue validity, suggesting efficient facilitation of sensory pathways by prior allocation of spatial attention to the cued place. Conversely, the late negative deflection preceding the imperative target stimulus and the late sustained positivity following target presentation, which reflect neural activities for response preparation and selection, were reduced in the cerebellar group. These findings suggest that the lateral cerebellum makes little contribution to visuospatial attention shift in either the voluntary or automatic modes and support a role of the lateral cerebellum in the neural system required for response preparation and selection.