The ability of typically developing 2–3 year olds to infer the control mechanism for eye-gaze technology and the impact of causal language instruction

Purpose: Little is known about how children learn to control eye-gaze technology, and clinicians lack information to guide decision-making. This paper examines whether typically developing 2–3 year olds can infer for themselves the causal mechanisms by which eye-gaze technology is controlled, whether a teaching intervention based on causal language improves performance and how their performance compares to the same task accessed via a touchscreen. Methods and materials: Typically developing children’s (n = 9, Mean Age 28.7 months) performance on a cause and effect game presented on eye-gaze and touchscreen devices was compared. The game was presented first with no specific instruction on how to control the devices. This was followed by a subsequent presentation with explicit instruction about how the access methods worked, using a causal language approach. A final presentation examined whether children had retained any learning. Results: Performance in the eye-gaze condition without instruction (42.5% successful trials) was significantly below performance in the corresponding touchscreen condition (75%). However, when causal language instruction was added, performance with both access methods rose to comparable levels (90.7% eye-gaze and 94.6% touchscreen success). Performance gains were not retained post-intervention. Conclusions: Although 2–3 years in the study could make use of eye-gaze technology with support, this study found no evidence that these children could infer the causal mechanisms of control independently or intuitively. The lack of spatial contiguity and the comparative lack of feedback from eye-gaze devices are discussed as possible contributory factors.</p

Opportunities and Challenges in Applying Light-weight National-scale Spatial Network Models

This paper explores the use of light-weight national-scale spatial network models in order to develop methods of understanding urban environments in developing contexts with limited data, budgets and time availability. The validity of national-scale analysis has been established in research focussed on the United Kingdom and United States of America, but not in other socioeconomic and spatial landscapes. In order to evalute the extent to which this methodology still holds, Uruguay and The Maldives are taken as case studies. Open-source road-centre line data is used to construct spatial network models, which are analysed using space syntax analysis. First, each spatial network model is correlated with open-source population data to explore potential relationships between spatial network density (node count) and population. The study finds a notable relationship between national-scale population distribution and citywide node count, where the citywide radii of analysis is taken as the average global radii of the cities in each country under evaluation. Second, a comparative analysis of cities within each country is undertaken, finding that capital cities are consistently above the linear trendline. Potential uses of this approach in future applications are highlighted, for instance, in practical evidence-based decision making, and in research across larger samples of countries and variables. It is argued that, despite data, time and budget constraints, it is possible to construct light-weight national-scale spatial network models that are insightful in-and-of themselves, and in conjuction with other globally-available open-source data. This presents significant opportunities to equalise access to evidence-based urban design and policy

Visible spatial contiguity of social information and reward affects social learning in brown capuchins (<i>Sapajus apella</i>) and children (<i>Homo sapiens</i>)

Animal social learning is typically studied experimentally by the presentation of artificial foraging tasks. Although productive, results are often variable even for the same species. We present and test the hypothesis that one cause of variation is that spatial distance between rewards and the means of reward release causes conflicts for participants’ attentional focus. We investigated whether spatial contiguity between a visible reward and the means of release would affect behavioral responses that evidence social learning, testing 21 brown capuchins (Sapajus apella), a much studied species with variant evidence for social learning, and 180 two- to four-year old human children (Homo sapiens), a benchmark species known for a strong social learning disposition. Participants were presented with a novel transparent apparatus where a reward was either proximal or distal to a demonstrated means of releasing it. A distal reward location decreased attention towards the location of the demonstration and impaired subsequent success in gaining rewards. Generally, the capuchins produced the alternative method to that demonstrated whereas children copied the method demonstrated, although a distal reward location reduced copying in younger children. We conclude that some design features in common social learning tasks may significantly degrade the evidence for social learning. We have demonstrated this for two different primates but suggest that it is a significant factor to control for in social learning research across all taxa

Identifying Rural Comparative Advantage: Ethanol Plant Location Determinants and Tennessee Value Chains

As rural areas struggle to adjust to the changing U.S. economy with increasing unemployment, falling wages, and constrained capital markets, economic developers look for strategies to promote economic expansion. Development strategies identifying and evaluating county comparative advantage may offer the promise of economic growth in rural areas. This thesis develops two models whereby county comparative advantage can be empirically identified and evaluated. The study first examines ethanol plant location determinants at the county level, in the contiguous forty-eight United States, the second identified industry clusters within Tennessee at the county level and estimated the extent to which these clusters contributed to growth in labor productivity. In the first study, the location of grain-based ethanol plants is determined by infrastructure, product and input markets, fiscal attributes of local communities, and state and federal incentives. Bivariate probit regression along with spatial clustering methods are used to analyze investment activity of ethanol plants at the county level for the contiguous 48 United States from 2000-2007. The ability of a county to supply feedstock, and the absence of previously established ethanol plants, dominated the site selection decision between 2000 and 2007. Other factors, such as access to railroads or navigable rivers, product markets, low worker wages, producer credit and excise tax incentives, and methyl tertiary-butyl ether bans gave some counties comparative advantage with respect to attracting grain-based ethanol plant investment. The second study identified industry clusters or economic linkages between purchasers and suppliers, at the county and regional level for 447 economic sectors in Tennessee. Information about value-added activities or innovative potential is possible by determining the sector composition of the value chains defining an industry cluster. The cluster analysis was extended to estimate the extent to which specific value chains contributed to economic growth between 2001 and 2006 across Tennessee’s 95 counties using an econometric model. County and regional comparative advantage was determined by testing whether the presence of a particular value chain in a given county increased labor productivity during this period

Spatial accessibility to health care services: identifying under - serviced neighbourhoods in Canadian urban areas

Background Urban environments can influence many aspects of health and well-being and access to health care is one of them. Access to primary health care (PHC) in urban settings is a pressing research and policy issue in Canada. Most research on access to healthcare is focused on national and provincial levels in Canada; there is a need to advance current understanding to local scales such as neighbourhoods. Methods This study examines spatial accessibility to family physicians using the Three-Step Floating Catchment Area (3SFCA) method to identify neighbourhoods with poor geographical access to PHC services and their spatial patterning across 14 Canadian urban settings. An index of spatial access to PHC services, representing an accessibility score (physicians-per-1000 population), was calculated for neighborhoods using a 3km road network distance. Information about primary health care providers (this definition does not include mobile services such as health buses or nurse practitioners or less distributed services such as emergency rooms) used in this research was gathered from publicly available and routinely updated sources (i.e. provincial colleges of physicians and surgeons). An integrated geocoding approach was used to establish PHC locations. Results The results found that the three methods, Simple Ratio, Neighbourhood Simple Ratio, and 3SFCA that produce City level access scores are positively correlated with each other. Comparative analyses were performed both within and across urban settings to examine disparities in distributions of PHC services. It is found that neighbourhoods with poor accessibility scores in the main urban settings across Canada have further disadvantages in relation to population high health care needs. Conclusions The results of this study show substantial variations in geographical accessibility to PHC services both within and among urban areas. This research enhances our understanding of spatial accessibility to health care services at the neighbourhood level. In particular, the results show that the low access neighbourhoods tend to be clustered in the neighbourhoods at the urban periphery and immediately surrounding the downtown area

Teaching and Learning Spatial Thinking with Young Students: the Use and Influence of External Representations

Previous research suggests spatial thinking is fundamental to mathematics learning (Bronowski, 1947; Clements & Sarama, 2007, 2011), and acts as a predictor for future mathematical achievement levels (Battista, 1990; Gunderson et al., 2012). However, research with regard to spatial thinking is almost non-existent in early years mathematics classrooms (Bruce, Moss, & Ross, 2012; Clements & Sarama, 2011; Newcombe & Frick, 2010; Sarama & Clements, 2009, 2011; Stipek, 2013), and how to teach it in these contexts has received little attention. Fewer studies again have focused on the use of virtual manipulatives in influencing young students’ spatial thinking (Highfield & Mulligan, 2007; Ng & Sinclair, 2015). Despite a recent surge in studies exploring the influence of virtual manipulatives in mathematics classrooms, little is known about how these manipulatives compare to physical manipulatives, especially in regard to the changes that occur in the social interactions between teacher and students during the learning process. To date, there has been no comparative study conducted that explores the influence of different external representations (e.g., physical manipulatives and virtual manipulatives) on both the teaching and the learning aspects within mathematics classrooms. The purpose of this research is to explore the use of external representations (i.e., physical manipulatives as compared to virtual manipulatives) in the mathematics classroom and how these representations support young, disadvantaged students’ spatial thinking. The use of manipulatives is a common starting point for the teaching and learning of spatial thinking. Previous research on manipulative use (both physical and virtual) in mathematics education has yielded positive results with regard to student learning (Clements, 1999; Heddens, 1997; Highfield & Mulligan, 2007; Riconscente, 2013; Siemon et al., 2011; Warren, 2006; Warren & Miller, 2013). Recent studies indicate that these newer digital technologies promote interactions between visual and kinaesthetic learning, which have been shown to support the teaching and learning of spatial thinking (Battista, 2008; Bruce, McPherson, Sabeti, & Flynn, 2011; Clements & Sarama, 2011; Highfield & Mulligan, 2007; Jorgensen & Lowrie, 2012; Sinclair, de Freitas, & Ferrara, 2013; Sinclair & Moss, 2012). However, results from comparative studies between physical manipulatives and virtual manipulatives have been varied (e.g., Brown, 2007; Olkum, 2003; Suh, 2005). It is proposed that different types of manipulatives influence the teaching and learning of spatial thinking in different ways. By viewing the learning of spatial thinking through a sociocultural perspective, aspects of the teaching and learning of spatial learning in mathematics classrooms can be scrutinised. A review of the literature generated two research questions that informed the research design of this study. These were: 1. What influence do different external representations (e.g., physical manipulatives and virtual manipulatives) have on young students’ learning of spatial thinking? 2. What changes occur in the teaching and learning of spatial thinking when using different external representations (e.g., physical manipulatives and virtual manipulatives)? Given that the study focused on exploring students’ spatial thinking as they construct their knowledge from the interactions they experience with external representations, an interpretive paradigm was an appropriate epistemological, ontological and methodological stance adopted for the research. Vygotsky’s (1978) sociocultural theory provided a lens to interpret the interaction between teacher and students. Practical application of this theory permitted a narrowing lens to pinpoint particular aspects of the teaching of spatial thinking and students’ learning of spatial thinking. Within this study, these practical applications included the use of Anghileri’s “hierarchy of scaffolding practices” (2006) and Sfard’s “commognitive approach” (2008). The methodology for the study included teaching experiments. Data collection methods incorporated the use of pre-test, post-test and post post-testing using spatial testing material and observations of lessons from a teaching experiment (n = 68) comprising six lessons (three based on spatial orientation concepts and three based on spatial visualisation concepts). Findings from this study provide further insights into the teaching and learning of spatial thinking. First, the use of manipulatives (either physical or virtual) appears to be important to students’ learning of spatial thinking. Furthermore, the use of virtual manipulatives increases the communicative functions used by students, thus benefiting their spatial thinking. Second, teachers need to be able to instantaneously access deep content and pedagogical knowledge in order to maintain their role as “more knowledgeable other” and continually contribute to the teaching and learning of spatial thinking. Finally, teaching and learning appears to be positively influenced when both the teacher and students are major contributors to the classroom discourse. This study contributes to the understanding of how different external representations influence the teaching and learning of spatial thinking. Theoretical contributions to new knowledge include a hypothesised theory on the interaction between teacher, student and manipulatives type. Implications for future classroom practice include placing importance on the use of manipulatives and communication in mathematics classrooms. Furthermore, teachers need to be aware that their ability to instantaneously access deep levels of content and pedagogical knowledge to further develop students’ spatial thinking is essential and that for optimum learning to occur, both the teacher and students need to be major contributors to the teaching and learning process

Comparative Performance Analysis Of Deep Learning-Based Image Steganography Using U-Net, V-Net, And U-Net++ Encoders

Digital Imaging steganography is the act of hiding information in a cover picture in a way that can't be found or recovered. Three main types of methods are used in digital image steganography: neural network methods, spatial methods, and transform methods. The pixel values of an image are changed by spatial methods to embed information. On the other hand, the frequency of the image is changed by transform methods to embed information that is hidden. There are methods that use neural networks to hide things, and this is what the suggested method is all about. Through digital image steganography, this study looks into how deep convolutional neural networks (CNNs) can be used. With the increasing concerns about data infringement during transmission and storage, image steganography techniques have gained attention for hiding secret information within cover images. Traditional methods suffer from limitations such as low embedding capacity and poor reconstruction quality. To address these challenges, deep learning-based approaches have been proposed in the literature. Among them, the Convolutional Neural Network (CNN) based U-Net encoder has been extensively studied. However, its comparative performance with other CNN-based encoders like V-Net and U-Net++ remains unexplored in the context of image steganography. In this paper, we implement V-Net and U-Net++ encoders for image steganography and conduct a comprehensive performance assessment alongside U-Net architecture. These architectures are utilized to conceal a secret image within a cover image, and a unified and robust decoder is designed to extract the hidden information. Through experimental evaluations, we compare the embedding capacity, stego quality, and reconstruction quality of the three architectures. The U-Net architecture outperforms V-Net and U-Net++ in terms of embedding capacity and the quality of stego and reconstructed secret images. This research provides valuable insights into the effectiveness of different deep learning-based encoders for image steganography applications, aiding in the selection of appropriate architectures for securing digital images against unauthorized access. &nbsp

Measuring fragmentation of open space in urbanised Flanders: an evaluation of four methods

The open space in Flanders, the northern part of Belgium, can hardly be seen as really open. From the Middle Ages onward this area has been known for its spread out development pattern, which has even strengthened in recent decades. Especially the residential ribbon development and the omnipresent infrastructure are widely recognised. These developments have led to an intense fragmentation of open space. In this paper we present two new methods to analyse and quantify this fragmentation of open space from a spatial planning perspective, and compare them with two existing methods. This comparative analysis evaluates the differentmethods and connects them to different definitions of fragmentation. The average patch size method is more appropriate to describe general fragmentation if the focus is on major line infrastructures, whereas the density of fragmenting structures method matches with the interpretation of fragmentation as spatial heterogeneity. The two described methods to detect enclosed open space fragments as signs of fragmentation give different results depending on the data and methods used. The ribbon method however is more appropriate to detect open space fragments under threat of privatisation, since it works with a stricter definition of continuous ribbon development. All four methods are relevant for Flemish spatial planning policy, as they indicate where actions are needed to safeguard open space from further urbanisation tendencies. Furthermore, they can support a differentiated spatial policy and add to the scientific basis of the debate on alternative interpretations of Flemish open space

Monitoring bioaerosol and odour emissions from composting facilities - WR1121

Government policy requires that valuable resources should be recovered and recycled from biodegradable waste. A successful and growing organics recycling industry delivers this policy with composting being one of the principal technologies deployed to process suitable feedstock such as garden and food waste. Composting inevitably generates bioaerosols – particulate matter comprising cells or cellular components that are released into the air as a result of disturbance of composting feedstock or the processing of final product. Exposure to bioaerosols has the potential to be harmful to human and animal health. The Environment Agency adopts a precautionary and risk-based approach to the regulation of composting facilities which was developed on the basis of research by Wheeler et al. (2001) and which has been updated as new evidence has become available. The Environment Agency also requires site operators to monitor bioaerosols around their facilities using methods specified in a standard protocol which relies upon classical microbiology methods which are tried and tested but which are labour-intensive, slow and offer only a snapshot view of a highly dynamic system. A recent IOM review commissioned by Defra (Searl, 2009) on exposure-response relationships for bioaerosol emissions from waste treatment processes identified significant gaps in knowledge of exposure to bioaerosols and recommended that more research was needed into alternatives to viable microbial monitoring such as priority biomarkers (notably endotoxin) and potential surrogates such as particulate matter. The IOM review also concluded that there is a lack of information to support the development of appropriate stand-off distances. The overall aim of this project was to provide evidence on bioaerosol production, dispersion and potential exposures from composting facilities in support of future developments in policy and regulation of biowaste facilities. The objectives were: (i) to undertake a comprehensive set of standard and novel bioaerosol measurements at representative composting sites to assess comparability between different methods and also to measure spatial and temporal variations; and (ii) to determine the odour emissions and then compare these with bioaerosol emissions to see if odour is a marker of significant bioaerosol exposure. Standard (AfOR, 2009) and novel (CEN filter method, endotoxin, glucan, qPCR, real-time particulates) bioaerosols measurements were taken on a minimum of three to a maximum of six occasions over a twelve month period at four different composting facilities in England. The composting facilities were selected to represent sites of varying sizes (tonnages) and to allow a comparison of bioaerosol concentrations at standard open windrow sites versus a fully-contained site. Additional supporting information was collected including meteorological data at the time of sampling, observation of site operations and measurements of odour at one of the sites. Supporting bioaerosol and odour dispersion modelling was conducted at the site where the odour measurements were made. The spatial trend of bioaerosol concentrations described by Wheeler et al., (1991) and upon which EA regulatory policy is based was broadly corroborated by this dataset. Excursions above the EA acceptable levels at or beyond 250m from source were rare. Bioaerosol concentrations at the enclosed site were generally lower than at the open windrow sites. There was no evidence of a seasonal pattern in bioaerosol concentrations at any of the sites whereas between-sampling day variations were apparent. The cause(s) of these variations were not identified. No consistent relationship was observed between the concentration of bioaerosols measured by the two AfOR standard methods. The two methods displayed certain strengths and weakness in different situations. The IOM sampling device proved to be better suited to situations where high bioaerosol concentrations were encountered (close to source); the Andersen proving to be more effective in the lower concentration range typically found upwind of a site or at distance downwind from source. The higher volume filtration device tested in this project (referred to as the CEN method) produced data that did not consistently match either of the AfOR standard methods. This device demonstrated greater sensitivity than the IOM filter method but suffered drawbacks associated with its weight and a lack of ease of use in the field. Endotoxin concentrations were normally below the level recommended by the Dutch Expert Committee on Occupational Safety but occasional exceedances of this standard were detected at the larger open windrow sites. The majority of glucan measurements were below a widely referred to 10ng/m3 threshold. Significantly elevated concentrations were detected at one of the larger open windrow sites. The dynamic range of the qPCR method is wider (4-5-log) than either of the AfOR and the CEN methods. It is also quicker to carry out and has the potential for automation. The results from the qPCR method are mainly higher than standard AfOR methods, as the method does not distinguish viable and non-viable spores. The spatial distribution of Aspergillus fumigatus spores (by qPCR) along sampling transects, gives similar results compared to AfOR (and CEN) methods. Real time particle detection showed that both TSP and PM10 are correlated to Aspergillus fumigatus spore concentration. No consistent relationship was observed between odour and bioaerosol concentrations (although this was a limited dataset). The envelope of modelled (back-extrapolated) bioaerosol emission rates straddles several orders of magnitude. Distinguishing the influences of meteorological conditions on this variability was not possible. It was not possible to predict bioaerosol or odour emission rates with confidence. This continues to hamper confidence in modelling of odours and bioaerosols from open windrow facilities. The findings of this research have implications for the current standard monitoring protocol which should be reviewed accordingly. The findings of this multi-site survey accord with existing regulatory policy and are supportive of the general trend towards enclosed facilities. Notwithstanding this, continuing research is needed to enhance the database on emission from bioaerosol and odour abatement technologies (e.g. biofilters); to determine the cause(s) of occasional bioaerosol peaks from open facilities; to improve exposure assessments through better modelling protocols; and to link enhanced exposure information to future health impact studies

Assessing mobile mixed reality affordances as a comparative visualization pedagogy for design communication

Spatial visualisation skills and interpretation are critical in the design professions but are difficult for novice designers. There is growing evidence that mixed reality visualisation improves learner outcomes, but often these studies are focused on a single media representation and not on a comparison between media and the underpinning learning outcomes. Results from recent studies highlight the use of comparative visualisation pedagogy in design through learner reflective blogs and pilot studies with experts, but these studies are limited by expense and designs familiar to the learner. With increasing interest in mobile pedagogy, more assessment is required in understanding learner interpretation of comparative mobile mixed reality pedagogy. The aim of this study is to do this by evaluating insights from a first-year architectural design classroom through studying the impact and use of a range of mobile comparative visualisation technologies. Using a design-based research methodology and a usability framework for accessing comparative visualisation, this paper will study the complexities of spatial design in the built environment. Outcomes from the study highlight the positives of the approach but also the improvements required in the delivery of the visualisations to improve on the visibility and visual errors caused by the lack of mobile processing