The development of a semantic model for the interpretation of mathematics including the use of technology

The semantic model developed in this research was in response to the difficulty a group of mathematics learners had with conventional mathematical language and their interpretation of mathematical constructs. In order to develop the model ideas from linguistics, psycholinguistics, cognitive psychology, formal languages and natural language processing were investigated. This investigation led to the identification of four main processes: the parsing process, syntactic processing, semantic processing and conceptual processing. The model showed the complex interdependency between these four processes and provided a theoretical framework in which the behaviour of the mathematics learner could be analysed. The model was then extended to include the use of technological artefacts into the learning process. To facilitate this aspect of the research, the theory of instrumentation was incorporated into the semantic model. The conclusion of this research was that although the cognitive processes were interdependent, they could develop at different rates until mastery of a topic was achieved. It also found that the introduction of a technological artefact into the learning environment introduced another layer of complexity, both in terms of the learning process and the underlying relationship between the four cognitive processes.

Towards a model for exploring the relationship between managerial decision problems and decision support opportunities

The organisational decision making environment is complex, and decision makers must deal with uncertainty and ambiguity on a continuous basis. Managing and handling decision problems and implementing a solution, requires an understanding of the complexity of the decision domain to the point where the problem and its complexity, as well as the requirements for supporting decision makers, can be described. Research in the Decision Support Systems domain has been extensive over the last thirty years with an emphasis on the development of further technology and better applications on the one hand, and on the other hand, a social approach focusing on understanding what decision making is about and how developers and users should interact. This research project considers a combined approach that endeavours to understand the thinking behind managers’ decision making, as well as their informational and decisional guidance and decision support requirements. This research utilises a cognitive framework, developed in 1985 by Humphreys and Berkeley that juxtaposes the mental processes and ideas of decision problem definition and problem solution that are developed in tandem through cognitive refinement of the problem, based on the analysis and judgement of the decision maker. The framework facilitates the separation of what is essentially a continuous process, into five distinct levels of abstraction of manager’s thinking, and suggests a structure for the underlying cognitive activities. Alter (2004) argues that decision support provides a richer basis than decision support systems, in both practice and research. The constituent literature on decision support, especially in regard to modern high profile systems, including Business Intelligence and Business analytics, can give the impression that all ‘smart’ organisations utilise decision support and data analytics capabilities for all of their key decision making activities. However this empirical investigation indicates a very different reality.

Posttranscriptional Regulation of Embryonic Neurogenesis by the Exon Junction Complex

The six-layered neuron structure in the cerebral cortex is the foundation for human mental abilities. In the developing cerebral cortex, neural stem cells undergo proliferation and differentiate into intermediate progenitors and neurons, a process known as embryonic neurogenesis. Disrupted embryonic neurogenesis is the root cause of a wide range of neurodevelopmental disorders, including microcephaly and intellectual disabilities. Multiple layers of regulatory networks have been identified and extensively studied over the past decades to understand this complex but extremely crucial process of brain development. In recent years, post-transcriptional RNA regulation through RNA binding proteins has emerged as a critical regulatory nexus in embryonic neurogenesis. The exon junction complex (EJC) is a highly conserved RNA binding complex composed of four core proteins, Magoh, Rbm8a, Eif4a3, and Casc3. The EJC plays a major role in regulating RNA splicing, nuclear export, subcellular localization, translation, and nonsense mediated RNA decay. Human genetic studies have associated individual EJC components with various developmental disorders. We showed previously that haploinsufficiency of Magoh causes microcephaly and disrupted neural stem cell differentiation in mouse. However, it is unclear if other EJC core components are also required for embryonic neurogenesis. More importantly, the molecular mechanism through which the EJC regulates embryonic neurogenesis remains largely unknown. Here, we demonstrated with genetically modified mouse models that both Rbm8a and Eif4a3 are required for proper embryonic neurogenesis and the formation of a normal brain. Using transcriptome and proteomic analysis, we showed that the EJC posttranscriptionally regulates genes involved in the p53 pathway, splicing and translation regulation, as well as ribosomal biogenesis. This is the first in vivo evidence suggesting that the etiology of EJC associated neurodevelopmental diseases can be ribosomopathies. We also showed that, different from other EJC core components, depletion of Casc3 only led to mild neurogenesis defects in the mouse model. However, our data suggested that Casc3 is required for embryo viability, development progression, and is potentially a regulator of cardiac development. Together, data presented in this thesis suggests that the EJC is crucial for embryonic neurogenesis and that the EJC and its peripheral factors may regulate development in a tissue-specific manner.

The effects of aging on the BTBR mouse model of autism spectrum disorder.

Autism spectrum disorder (ASD) is a complex heterogeneous neurodevelopmental disorder characterized by alterations in social functioning, communicative abilities, and engagement in repetitive or restrictive behaviors. The process of aging in individuals with autism and related neurodevelopmental disorders is not well understood, despite the fact that the number of individuals with ASD aged 65 and older is projected to increase by over half a million individuals in the next 20 years. To elucidate the effects of aging in the context of a modified central nervous system, we investigated the effects of age on the BTBR T + tf/j mouse, a well characterized and widely used mouse model that displays an ASD-like phenotype. We found that a reduction in social behavior persists into old age in male BTBR T + tf/j mice. We employed quantitative proteomics to discover potential alterations in signaling systems that could regulate aging in the BTBR mice. Unbiased proteomic analysis of hippocampal and cortical tissue of BTBR mice compared to age-matched wild-type controls revealed a significant decrease in brain derived neurotrophic factor and significant increases in multiple synaptic markers (spinophilin, Synapsin I, PSD 95, NeuN), as well as distinct changes in functional pathways related to these proteins, including "Neural synaptic plasticity regulation" and "Neurotransmitter secretion regulation." Taken together, these results contribute to our understanding of the effects of aging on an ASD-like mouse model in regards to both behavior and protein alterations, though additional studies are needed to fully understand the complex interplay underlying aging in mouse models displaying an ASD-like phenotype.

Hippocampal Transcriptomic and Proteomic Alterations in the BTBR Mouse Model of Autism Spectrum Disorder.

Autism spectrum disorders (ASD) are complex heterogeneous neurodevelopmental disorders of an unclear etiology, and no cure currently exists. Prior studies have demonstrated that the black and tan, brachyury (BTBR) T+ Itpr3tf/J mouse strain displays a behavioral phenotype with ASD-like features. BTBR T+ Itpr3tf/J mice (referred to simply as BTBR) display deficits in social functioning, lack of communication ability, and engagement in stereotyped behavior. Despite extensive behavioral phenotypic characterization, little is known about the genes and proteins responsible for the presentation of the ASD-like phenotype in the BTBR mouse model. In this study, we employed bioinformatics techniques to gain a wide-scale understanding of the transcriptomic and proteomic changes associated with the ASD-like phenotype in BTBR mice. We found a number of genes and proteins to be significantly altered in BTBR mice compared to C57BL/6J (B6) control mice controls such as BDNF, Shank3, and ERK1, which are highly relevant to prior investigations of ASD. Furthermore, we identified distinct functional pathways altered in BTBR mice compared to B6 controls that have been previously shown to be altered in both mouse models of ASD, some human clinical populations, and have been suggested as a possible etiological mechanism of ASD, including "axon guidance" and "regulation of actin cytoskeleton." In addition, our wide-scale bioinformatics approach also discovered several previously unidentified genes and proteins associated with the ASD phenotype in BTBR mice, such as Caskin1, suggesting that bioinformatics could be an avenue by which novel therapeutic targets for ASD are uncovered. As a result, we believe that informed use of synergistic bioinformatics applications represents an invaluable tool for elucidating the etiology of complex disorders like ASD.

An Interactive Model to Teach Motor Skills

There has been a tremendous increase in our knowledge of hum motor performance over the last few decades. Our theoretical understanding of how an individual learns to move is sophisticated and complex. It is difficult however to relate much of this information in practical terms to physical educators, coaches, and therapists concerned with the learning of motor skills (Shumway-Cook & Woolcott, 1995). Much of our knowledge stems from lab testing which often appears to bear little relation to real-life situations. This lack of ecological validity has slowed the flow of information from the theorists and researchers to the practitioners. This paper is concerned with taking some small aspects of motor learning theory, unifying them, and presenting them in a usable fashion. The intention is not to present a recipe for teaching motor skills, but to present a framework from which solutions can be found. If motor performance research has taught us anything, it is that every individual and situation presents unique challenges. By increasing our ability to conceptualize the learning situation we should be able to develop more flexible and adaptive responses to the challege of teaching motor skills. The model presented here allows a teacher, coach, or therapist to use readily available observations and known characteristics about a motor task and to conceptualize them in a manner which allows them to make appropriate teaching/learning decisions.

Model Development Guidelines for UML-RT: Conventions, Patterns and Antipatterns

Software development guidelines are a set of rules which can help improve the quality of software. These rules are defined on the basis of experience gained by the software development community over time. This paper discusses a set of design guidelines for model-based development of complex real-time embedded software systems. To be precise, we propose nine design conventions, three design patterns and thirteen antipatterns for developing UML-RT models. These guidelines have been identified based on our analysis of around 100 UML-RT models from industry and academia. Most of the guidelines are explained with the help of examples, and standard templates from the current state of the art are used for documenting the design rules.

Guiding public protest: assessing the propaganda model of China’s hybrid newspaper industry

This dissertation presents an account and analysis of published mainland Chinese media coverage surrounding three major events of public protest during the Hu-Wen era (2003-2013). The research makes a qualitative analysis of printed material drawn from a range of news outlets, differentiated by their specific political and commercial affiliations. The goal of the research is to better understand the role of mainstream media in social conflict resolution, a hitherto under-studied area, and to identify gradations within the ostensibly monolithic mainland Chinese media on issues of political sensitivity. China’s modern media formation displays certain characteristics of Anglophone media at its hyper-commercialised, populist core. However, the Chinese state retains an explicit, though often ambiguous, remit to engage with news production. Because of this, Chinese newspapers are often assumed to be one-dimensional propaganda ‘tools’ and, accordingly, easily dismissed from analyses of public protest. This research finds that, in an area where political actors have rescinded their monopoly on communicative power, a result of both policy decisions and the rise of Internet-based media platforms, established purveyors of news have acquired greater latitude to report on hitherto sensitive episodes of conflict but do so under the burden of having to correctly guide public opinion. The thesis examines the discursive resources that are deployed in this task, as well as reporting patterns which are suggestive of a new propaganda approach to handling social conflict within public media. Beside the explicitly political nature of coverage of protest events, the study sheds lights on gradations within China’s complex, hybrid media landscape both in terms of institutional purpose and qualitative performance.

Predicting the Dispersal Potential of an Invasive Polychaete Pest along a Complex Coastal Biome

Boccardia proboscidea is a recently introduced polychaete in South Africa where it is a notorious pest of commercially reared abalone. Populations were originally restricted to abalone farms but a recent exodus into the wild at some localities has raised conservation concerns due to the species’ invasive status in other parts of the world. Here, we assessed the dispersal potential of B. proboscidea by using a population genetic and oceanographic modeling approach. Since the worm is in its incipient stages of a potential invasion, we used the closely related Polydora hoplura as a proxy due its similar reproductive strategy and its status as a pest of commercially reared oysters in the country. Populations of P. hoplura were sampled from seven different localities and a section of the mtDNA gene, Cyt b and the intron ATPSa was amplified. A high resolution model of the coastal waters around southern Africa was constructed using the Regional Ocean Modeling System. Larvae were represented by passive drifters that were deployed at specific points along the coast and dispersal was quantified after a 12-month integration period. Our results showed discordance between the genetic and modeling data. There was low genetic structure (Φ = 0.04 for both markers) and no geographic patterning of mtDNA and nDNA haplotypes. However, the dispersal model found limited connectivity around Cape Point—a major phylogeographic barrier on the southern African coast. This discordance was attributed to anthropogenic movement of larvae and adult worms due to vectors such as aquaculture and shipping. As such, we hypothesized that cryptic dispersal could be overestimating genetic connectivity. Though wild populations of B. proboscidea could become isolated due to the Cape Point barrier, anthropogenic movement may play the critical role in facilitating the dispersal and spread of this species on the southern African coast.

Predicting the Dispersal Potential of an Invasive Polychaete Pest along a Complex Coastal Biome

Boccardia proboscidea is a recently introduced polychaete in South Africa where it is a notorious pest of commercially reared abalone. Populations were originally restricted to abalone farms but a recent exodus into the wild at some localities has raised conservation concerns due to the species’ invasive status in other parts of the world. Here, we assessed the dispersal potential of B. proboscidea by using a population genetic and oceanographic modeling approach. Since the worm is in its incipient stages of a potential invasion, we used the closely related Polydora hoplura as a proxy due its similar reproductive strategy and its status as a pest of commercially reared oysters in the country. Populations of P. hoplura were sampled from seven different localities and a section of the mtDNA gene, Cyt b and the intron ATPSa was amplified. A high resolution model of the coastal waters around southern Africa was constructed using the Regional Ocean Modeling System. Larvae were represented by passive drifters that were deployed at specific points along the coast and dispersal was quantified after a 12-month integration period. Our results showed discordance between the genetic and modeling data. There was low genetic structure (Φ = 0.04 for both markers) and no geographic patterning of mtDNA and nDNA haplotypes. However, the dispersal model found limited connectivity around Cape Point—a major phylogeographic barrier on the southern African coast. This discordance was attributed to anthropogenic movement of larvae and adult worms due to vectors such as aquaculture and shipping. As such, we hypothesized that cryptic dispersal could be overestimating genetic connectivity. Though wild populations of B. proboscidea could become isolated due to the Cape Point barrier, anthropogenic movement may play the critical role in facilitating the dispersal and spread of this species on the southern African coast.

Molecular basis of canalization in an ascidian species complex adapted to different thermal conditions

Canalization is a result of intrinsic developmental buffering that ensures phenotypic robustness under genetic variation and environmental perturbation. As a consequence, animal phenotypes are remarkably consistent within a species under a wide range of conditions, a property that seems contradictory to evolutionary change. Study of laboratory model species has uncovered several possible canalization mechanisms, however, we still do not understand how the level of buffering is controlled in natural populations. We exploit wild populations of the marine chordate Ciona intestinalis to show that levels of buffering are maternally inherited. Comparative transcriptomics show expression levels of genes encoding canonical chaperones such as Hsp70 and Hsp90 do not correlate with buffering. However the expression of genes encoding endoplasmic reticulum (ER) chaperones does correlate. We also show that ER chaperone genes are widely conserved amongst animals. Contrary to previous beliefs that expression level of Heat Shock Proteins (HSPs) can be used as a measurement of buffering levels, we propose that ER associated chaperones comprise a cellular basis for canalization. ER chaperones have been neglected by the fields of development, evolution and ecology, but their study will enhance understanding of both our evolutionary past and the impact of global environmental change.

Molecular basis of canalization in an ascidian species complex adapted to different thermal conditions

Canalization is a result of intrinsic developmental buffering that ensures phenotypic robustness under genetic variation and environmental perturbation. As a consequence, animal phenotypes are remarkably consistent within a species under a wide range of conditions, a property that seems contradictory to evolutionary change. Study of laboratory model species has uncovered several possible canalization mechanisms, however, we still do not understand how the level of buffering is controlled in natural populations. We exploit wild populations of the marine chordate Ciona intestinalis to show that levels of buffering are maternally inherited. Comparative transcriptomics show expression levels of genes encoding canonical chaperones such as Hsp70 and Hsp90 do not correlate with buffering. However the expression of genes encoding endoplasmic reticulum (ER) chaperones does correlate. We also show that ER chaperone genes are widely conserved amongst animals. Contrary to previous beliefs that expression level of Heat Shock Proteins (HSPs) can be used as a measurement of buffering levels, we propose that ER associated chaperones comprise a cellular basis for canalization. ER chaperones have been neglected by the fields of development, evolution and ecology, but their study will enhance understanding of both our evolutionary past and the impact of global environmental change.

Viewbrics: Formative Assessment of Complex Skills with Video-Enhanced Rubrics (VER) in Dutch Secondary Education

To learn complex skills, like collaboration, learners need to acquire a concrete and consistent mental model of what it means to master this skill. If learners know their current mastery level and know their targeted mastery level, they can better determine their subsequent learning activities. Rubrics support learners in judging their skill performance as they provide textual descriptions of skills’ mastery levels with performance indicators for all constituent subskills. However, text-based rubrics have a limited capacity to support the formation of mental models with contextualized, time-related and observable behavioral aspects of a complex skill. This paper outlines the design of a study that intends to investigate the effect of rubrics with video modelling examples compared to text-based rubrics on skills acquisition and feedback provisioning. The hypothesis is that video-enhanced rubrics, compared to text based rubrics, will improve mental model formation of a complex skill and improve the feedback quality a learner receives (from e.g. teachers, peers) while practicing a skill, hence positively effecting final mastery of a skill.

A First Step Towards Video Enhanced Rubrics for the Formative Assessment of Complex Skills : A literature review and a plea

Paper presentation at the TEA2016 conference, Tallinn, Estonia.

Semantic feature-based visual attention model for pedestrian detection

Objective
Pedestrian detection under video surveillance systems has always been a hot topic in computer vision research. These systems are widely used in train stations, airports, large commercial plazas, and other public places. However, pedestrian detection remains difficult because of complex backgrounds. Given its development in recent years, the visual attention mechanism has attracted increasing attention in object detection and tracking research, and previous studies have achieved substantial progress and breakthroughs. We propose a novel pedestrian detection method based on the semantic features under the visual attention mechanism.
Method
The proposed semantic feature-based visual attention model is a spatial-temporal model that consists of two parts: the static visual attention model and the motion visual attention model. The static visual attention model in the spatial domain is constructed by combining bottom-up with top-down attention guidance. Based on the characteristics of pedestrians, the bottom-up visual attention model of Itti is improved by intensifying the orientation vectors of elementary visual features to make the visual saliency map suitable for pedestrian detection. In terms of pedestrian attributes, skin color is selected as a semantic feature for pedestrian detection. The regional and Gaussian models are adopted to construct the skin color model. Skin feature-based visual attention guidance is then proposed to complete the top-down process. The bottom-up and top-down visual attentions are linearly combined using the proper weights obtained from experiments to construct the static visual attention model in the spatial domain. The spatial-temporal visual attention model is then constructed via the motion features in the temporal domain. Based on the static visual attention model in the spatial domain, the frame difference method is combined with optical flowing to detect motion vectors. Filtering is applied to process the field of motion vectors. The saliency of motion vectors can be evaluated via motion entropy to make the selected motion feature more suitable for the spatial-temporal visual attention model.
Result
Standard datasets and practical videos are selected for the experiments. The experiments are performed on a MATLAB R2012a platform. The experimental results show that our spatial-temporal visual attention model demonstrates favorable robustness under various scenes, including indoor train station surveillance videos and outdoor scenes with swaying leaves. Our proposed model outperforms the visual attention model of Itti, the graph-based visual saliency model, the phase spectrum of quaternion Fourier transform model, and the motion channel model of Liu in terms of pedestrian detection. The proposed model achieves a 93% accuracy rate on the test video.
Conclusion
This paper proposes a novel pedestrian method based on the visual attention mechanism. A spatial-temporal visual attention model that uses low-level and semantic features is proposed to calculate the saliency map. Based on this model, the pedestrian targets can be detected through focus of attention shifts. The experimental results verify the effectiveness of the proposed attention model for detecting pedestrians.