A Survey of the Development of the Green River Community College and the Need for a Handbook in the Adult Evening School Program

It was the purpose of this study to trace the history of the Green River Community College and to show the need for the development of a handbook concerned with appropriate method for the adult student

A Physical Fitness Comparison Between Rural and Urban Children and Canadian Fitness Standards

The purpose of this study was to determine whether or not Manitoba school students of rural areas were better physically fit than students of urban areas. The investigator was also interested in finding out how these two areas (urban and rural) compared to the National Canadian Association for Health, Physical Education, and Recreation (CAHPER) standards. The comparisons were made by (1) comparing the mean of the rural and urban test results based on the findings of the Centennial Athletic Awards Programme: (2) by compar- ing the mean of rural and urban areas with the CAHPER mean. The null hypothesis was assumed for this study (.01 level) and the t technique for testing the significance of the difference between mean was used to compare the mean of urban and rural children, at each age level, for each event and for both sexes. The t technique was also used to compare the mean of urban and rural children to CAHPER fitness mean at each age level, for each event and for both sexes. Results indicated that no significant difference existed in the physical fitness of urban and rural students. There were, however, significant differences in favor of the Manitoba students (urban and rural) when compared to the national CAHPER fitness mean

Improving accuracy and efficiency of mutual information for multi-modal retinal image registration using adaptive probability density estimation

Mutual information (MI) is a popular similarity measure for performing image registration between different modalities. MI makes a statistical comparison between two images by computing the entropy from the probability distribution of the data. Therefore, to obtain an accurate registration it is important to have an accurate estimation of the true underlying probability distribution. Within the statistics literature, many methods have been proposed for finding the 'optimal' probability density, with the aim of improving the estimation by means of optimal histogram bin size selection. This provokes the common question of how many bins should actually be used when constructing a histogram. There is no definitive answer to this. This question itself has received little attention in the MI literature, and yet this issue is critical to the effectiveness of the algorithm. The purpose of this paper is to highlight this fundamental element of the MI algorithm. We present a comprehensive study that introduces methods from statistics literature and incorporates these for image registration. We demonstrate this work for registration of multi-modal retinal images: colour fundus photographs and scanning laser ophthalmoscope images. The registration of these modalities offers significant enhancement to early glaucoma detection, however traditional registration techniques fail to perform sufficiently well. We find that adaptive probability density estimation heavily impacts on registration accuracy and runtime, improving over traditional binning techniques. © 2013 Elsevier Ltd

Synchronization of coupled neural oscillators with heterogeneous delays

We investigate the effects of heterogeneous delays in the coupling of two excitable neural systems. Depending upon the coupling strengths and the time delays in the mutual and self-coupling, the compound system exhibits different types of synchronized oscillations of variable period. We analyze this synchronization based on the interplay of the different time delays and support the numerical results by analytical findings. In addition, we elaborate on bursting-like dynamics with two competing timescales on the basis of the autocorrelation function.Comment: 18 pages, 14 figure

The multi-modal nature of trustworthiness perception

Most past work on trustworthiness perception has focused on the structural features of the human face. The present study investigates the interplay of dynamic information from two channels – the face and the voice. By systematically varying the level of trustworthiness in each channel, 49 participants were presented with either facial or vocal information, or the combination of both, and made explicit judgements with respect to trustworthiness, dominance, and emotional valence. For most measures results revealed a primacy effect of facial over vocal cues. In examining the exact nature of the trustworthiness - emotion link we further found that emotional valence functioned as a significant mediator in impressions of trustworthiness. The findings extend previous correlational evidence and provide important knowledge of how trustworthiness in its dynamic and multi-modal form is decoded by the human perceiver. Index Terms: trustworthiness, face, voice, emotion, dynamic, multi-moda

Excitability in autonomous Boolean networks

We demonstrate theoretically and experimentally that excitable systems can be built with autonomous Boolean networks. Their experimental implementation is realized with asynchronous logic gates on a reconfigurabe chip. When these excitable systems are assembled into time-delay networks, their dynamics display nanosecond time-scale spike synchronization patterns that are controllable in period and phase.Comment: 6 pages, 5 figures, accepted in Europhysics Letters (epljournal.edpsciences.org

Between images and built form: Automating the recognition of standardised building components using deep learning

Building on the richness of recent contributions in the field, this paper presents a state-of-the-art CNN analysis method for automatingthe recognition of standardised building components in modern heritage buildings. At the turn of the twentieth century manufacturedbuilding components became widely advertised for specification by architects. Consequently, a form of standardisation across varioustypologies began to take place. During this era of rapid economic and industrialised growth, many forms of public building wereerected. This paper seeks to demonstrate a method for informing the recognition of such elements using deep learning to recognise'families' of elements across a range of buildings in order to retrieve and recognise their technical specifications from the contemporarytrade literature. The method is illustrated through the case of Carnegie Public Libraries in the UK, which provides a unique butubiquitous platform from which to explore the potential for the automated recognition of manufactured standard architecturalcomponents. The aim of enhancing this knowledge base is to use the degree to which these were standardised originally as a means toinform and so support their ongoing care but also that of many other contemporary buildings. Although these libraries are numerous,they are maintained at a local level and as such, their shared challenges for maintenance remain unknown to one another. Additionally,this paper presents a methodology to indirectly retrieve useful indicators and semantics, relating to emerging HBIM families, byapplying deep learning to a varied range of architectural imagery

Vocal and facial trustworthiness of talking heads

Trust is a key aspect to human communication due to its link to co-operation and survival. Recent research by [Ballew and Todorov 2007] has shown that humans can generate an initial trustworthiness judgement based on facial features within 100ms. However, in that work, perceived trustworthiness has been studied solely in the context of facial information. It has been suggested by [Surawski and Ossoff 2006] that trustworthiness cues are also prevalent in the auditory channel. There is however, no prior empirical evidence to suggest that visual cues are more important than audio cues and how people deal with inconsistent cues between the audio and visual channels