The Abertay Code Bar – unlocking access to university-generated computer games intellectual poperty

Progress report on a digital platform and dual licensing model developed to unlock access to a University repository of new and legacy computer games based Intellectual Property (IP) assets for educational and commercial use. The digital creative industries have been identified by a number of governments as a priority area in delivering sustainable economic growth. Code Bar is an innovation that allows digital products to be commercially successful beyond the end of the Dare competition or coursework submission. To be selected for Code Bar, game products must be well designed for both player and market; technically robust (i.e. operating consistently and reliably on a single/multiple platforms), and be free from ambiguity around 3rd party IP. We describe various technical, pedagogic and legal challenges in developing the digital platform, licensing model and packaging of computer games products for release through the platform. The model is extendable beyond computer games to other software products

Shape and Texture Combined Face Recognition for Detection of Forged ID Documents

This paper proposes a face recognition system that can be used to effectively match a face image scanned from an identity (ID) doc-ument against the face image stored in the biometric chip of such a document. The purpose of this specific face recognition algorithm is to aid the automatic detection of forged ID documents where the photography printed on the document’s surface has been altered or replaced. The proposed algorithm uses a novel combination of texture and shape features together with sub-space representation techniques. In addition, the robustness of the proposed algorithm when dealing with more general face recognition tasks has been proven with the Good, the Bad & the Ugly (GBU) dataset, one of the most challenging datasets containing frontal faces. The proposed algorithm has been complement-ed with a novel method that adopts two operating points to enhance the reliability of the algorithm’s final verification decision.Final Accepted Versio

Determination of stability constants using genetic algorithms

A genetic algorithm (GA)-simplex hybrid approach has been developed for the determination of stability constants using calorimetric and polarographic data obtained from literature sources. The GA determined both the most suitable equilibrium model for the systems studied and the values of the stability constants and the heats of formation for the calorimetric studies. As such, a variable length chromosome format was devised to represent the equilibrium models and stability constants (and heats of formation). The polarographic data were obtained from studies of cadmium chloride and lead with the crown ether dicyclohexyl-18-crown-6. The calorimetric data were obtained from a study of a two step addition reaction of Hg(CN)2 with thiourea. The stability constants obtained using the GA-simplex hybrid approach compare favourably with the values quoted in the literature

The application of artificial neural networks and genetic algorithms to the estimation of electode response characteristics and stability constants

This introductory chapter establishes the theoretical and contextual background for the application of neural networks and genetic algorithms to solving chemical problems. This chapter is divided into three major sections, namely neural networks, genetic algorithms and a literature review of previous applications of these techniques. Each of these sections are further subdivided into subsections. In the case o f the neural networks section, the order of the subsections reflects a logical progression from small to large scale properties of biological neural systems. This progression is again expressed in the descriptions o f artificial neural networks (ANNs). A number of different ANN architectures which have found chemical applications or have been discussed in a cognitive context are described, with particular emphasis on the backpropagation training algorithm for feedforward networks. The genetic algorithms section mainly describes the formal framework underlying the use of the simple genetic algorithm (SGA) and Holland’s Schema Theorem. The applications section is divided into those applications which involved neural networks and those which involved genetic algorithms

Computational Thinking in Junior Classrooms in New Zealand

From 2020, the New Zealand technology curriculum will include computational thinking. The new curriculum content is being introduced to students from five-years-old onwards. In preparation for its introduction, online resources have been developed for teachers, including junior teachers (who teach new entrants to year three), that contain progress outcomes, lesson plans, exemplars and assessments. However, it is unclear whether New Zealand junior teachers are sufficiently prepared to teach computational thinking and what factors influence their preparedness to teach the new curriculum. This research explored the experiences of a small group of junior school teachers in the year prior to the official introduction of the technology curriculum. Research findings highlight that factors including professional development, assessment, schoolwide support, and time availability influence the uptake of the computational thinking curriculum by teachers in New Zealand junior classrooms

Associations between cytokines, endocrine stress response, and gastrointestinal symptoms in autism spectrum disorder

PosterAutism spectrum disorder (ASD) is characterized by impairments in social communication and abnormal repetitive behavior patterns. Recent studies have shown a strong association between ASD and gastrointestinal (GI) symptomatology. Some individuals with ASD show altered reactivity to stress, as well as altered immune markers, particularly stress responsive cytokines including TNF-alpha and IL-6. To assess potential relationships between GI symptoms and stress response, we examined whether GI symptoms are associated with increases in stress-associated endocrine markers and cytokines in ASD. We also conducted exploratory analyses the examine the relationship between IL-6, TNF-alpha, cortisol, and intelligence, as well as the effects of the presence or absence of co-occurring medical conditions on the relationship between IL-6, TNF-alpha, cortisol, and GI symptoms. Given the aforementioned findings, we expected to find positive relationships between GI symptoms and biomarkers of stress, including cortisol levels, IL-6, and TNF-alpha

Motivation to learn in online environments : an exploration of two tertiary education contexts : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Education at Massey University, Manawatu, New Zealand

Research evidence suggests that motivation is an important consideration for online learners. Notably, existing research has frequently focused on the design of motivating online learning environments. Alternatively, motivation has been viewed as a collection of relatively stable personal characteristics of learners. In contrast, a contemporary view that acknowledges the complexity and dynamic interplay of factors underlying and influencing motivation to learn (e.g., Turner & Patrick, 2008) is adopted here. From this „person in context‟ perspective, this study investigates the nature of motivation to learn in online distance learning environments. The study explores how student motivation relates to online participation in these contexts. In addition, social and contextual factors that foster and undermine motivation are identified. The research design utilises a case study approach which focuses on learners in two separate online distance courses within the same university programme. The boundary for each case study is defined by one piece of assessed work and the associated activities within each course. Interview and questionnaire data, supported by archived online data and course resources, were collected. Analysis of the data were made using the three conceptual lenses of self-determination theory (Deci & Ryan, 1985) and the continuum of human motivation encompassed within this theoretical framework. Findings indicate that the motivation of learners in online environments was multidimensional. Intrinsic motivation and various types of extrinsic motivation were shown to co-exist. Complex relationships were also shown to exist between motivation and participation that were sensitive to situational influences. Multiple factors fostered the expression of high quality (i.e. more self-determined) motivation. Most prominent among these were the relevance of the learning activity, the provision of clear guidelines, and ongoing support and feedback from the teacher that was responsive to learners‟ needs. Supportive caring relationships were also important. A range of factors also undermined the motivation of learners; most notably high workload, assessment pressure, and the perception that the learning activity lacked relevance