Description:
This paper will focus on children's views on their making and design capabilities. There is a paucity of research investigating learning in makerspaces particularly for younger children. Theoretical ideas based on constructionism (Papert), Vygotsky (socio-constructivism) and Dewey's pragmatic, inquiry based and reflective learning underpin this study. Fourteen group interviews were conducted with 34 young children (five to eight years old). Their responses were inductively and thematically analysed. Children provided rich insights into new pedagogical approaches, like makerspaces, and identified challenges with the use of the digital tools (3D App and 3D printers). Children enjoyed directing their own learning and viewed their experiences as creative. This research will advance knowledge on how makerspaces and design thinking skills can be integrated in early childhood and early primary education.
Description:
Much has been written about ethical and human-centred Information Systems (IS) design, most recently regarding the deleterious outcomes and negative affect of some machine learning applications that embed and perpetuate unethical or even inhumane automation. Terms such as ‘harm’, ‘damage’, and surprisingly, ‘weapon’ have entered the language of this discourse. However, these characteristics are not unique to applications of data science but have long manifested in IS that can also can exhibit opacity and establish tight vicious cycles. These, when coupled with a lack of governance feedback, can perpetuate injustice that has community or sector-wide reach. In this paper, we explore how IS design that sets out with the best of intentions or at least, conceived as a ‘neutral’ system for managing transactional information, can emerge as ‘tools that punish’. We argue that there are crucial principles to be taken from Recordkeeping Informatics, concerned as it is with the entanglement of information and people across space and through time on multi-generational timescales. In particular we discuss how transdisciplinary and critical approaches are necessary to cover more of the design space and surface issues, rights, stakeholders, and, most importantly, values that may be otherwise hidden from a here-and-now, transactional viewpoint.
Description:
Slug flow induces vibration in pipelines, which may, in some cases, result in fatigue failure. This can result from dynamic stresses, induced by the deflection and bending moment in the pipe span, growing to levels above the endurance limits of the pipeline material. As such, it is of paramount importance to understand and quantify the size of the pipeline response to slug flow under given speed and damping conditions. This paper utilizes the results of an optimization procedure to devise a surrogate closed-form model, which can be employed to calculate the maximum values of the pipeline loadings at given values of speed and damping parameters. The surrogate model is intended to replace the computationally costly numerical procedure needed for the analysis. The maximum values of the lateral deflection and bending moment, along with their locations, have been calculated using the optimization method of stochastic perturbation and successive approximations ( SPSA). The accuracy of the proposed surrogate model will be validated numerically, and the model will be subsequently used in a numerical example to demonstrate its applicability in industrial situations. An accompanying spreadsheet with this worked example is also given.
Description:
Abstract Objectives Internationally, children's movement competence levels are low. This study's aim was to evaluate the effectiveness of a 16 week gymnastics curriculum on stability, locomotive and object control skills and general body coordination. It was hypothesised that the gymnastics intervention group would demonstrate significant improvements beyond a PE comparison group. Design This study used a non-randomised control design. The intervention and comparison groups were drawn from three primary schools. The study followed the Transparent Reporting of Evaluations with Nonrandomized Designs (TREND) statement for reporting. Methods A total of 333 children (51% girls, 41% intervention) with a mean age of 8.1 years ( sd = 1.1) participated. Intervention children (16 weeks x 2 hrs of gymnastics) were compared to children who received (16 × 2 hrs) standard PE curriculum. Children's movement competence was assessed using the Test of Gross Motor Development–2, Stability Skills Assessment and the Körper-Koordinationstest für Kinder. Multilevel linear mixed models, accounting for variation at the class level and adjusted for age and sex, were used to assess intervention relative to comparison differences in all aspects of movement competence. Results Stability and object control skills showed a significant ( p < .05) intervention x time interaction effect. No difference was found in locomotor skills or general coordination. Conclusions Gymnastics is effective at developing stability skills and object control skills without hindering the development of locomotor skills or general coordination. Accelerated learning of stability skills may support the development of more complex movement skills.
Description:
Makerspaces have been heralded as an effective way to support the development of 21st Century and STEM capabilities, yet there is a paucity of systematic, multiple-case analysis to guide educator and researcher practice. This collective case study examined 24 primary school classroom contexts to understand what supports and constrains learning and teaching in technology-oriented makerspaces. Thematic analysis of 24 teacher in-situ reflective journals and focus group interviews of all teacher participants revealed 19 supports and 11 constraints, relating to pedagogy, task design, learner attributes, technological factors, the school environment, and teacher capabilities and beliefs. These were used to form an evidence-based framework for learning and teaching in makerspaces. Findings are discussed in relation to previous research which has tended to be anecdotal and based on single cases. Implications for future teaching, research and policy initiatives are also detailed.
Description:
Remote and regional areas are usually supplied by isolated and self-sufficient electricity systems, which are called as microgrids (MGs). To reduce the overall cost of electricity production, MGs rely on non-dispatchable renewable sources. Emergencies such as overloading or excessive generation by renewable sources can result in a substantial voltage or frequency deviation in MGs. This paper presents a supervisory controller for such emergencies. The key idea is to remedy the emergencies by optimal internal or external support. A multi-level controller with soft, intermedial and hard actions is proposed. The soft actions include the adjustment of the droop parameters of the sources and the controlling of the charge/discharge of energy storages. The intermedial action is exchanging power with neighboring MGs, which is highly probable in large remote areas. As the last remedying resort, curtailing loads or renewable sources are assumed as hard actions. The proposed controller employs an optimization technique consisting of certain objectives such as reducing power loss in the tie-lines amongst MGs and the dependency of an MG to other MGs, as well as enhancing the contribution of renewable sources in electricity generation. Minimization of the fuel consumption and emissions of conventional generators, along with frequency and voltage deviation, is the other desired objectives. The performance of the proposal is evaluated by several numerical analyses in MATLAB (R).
Description:
Remote and regional areas are usually supplied by isolated and self-sufficient electricity systems, which are called as microgrids (MGs). To reduce the overall cost of electricity production, MGs rely on non-dispatchable renewable sources. Emergencies such as overloading or excessive generation by renewable sources can result in a substantial voltage or frequency deviation in MGs. This paper presents a supervisory controller for such emergencies. The key idea is to remedy the emergencies by optimal internal or external support. A multi-level controller with soft, intermedial and hard actions is proposed. The soft actions include the adjustment of the droop parameters of the sources and the controlling of the charge/discharge of energy storages. The intermedial action is exchanging power with neighboring MGs, which is highly probable in large remote areas. As the last remedying resort, curtailing loads or renewable sources are assumed as hard actions. The proposed controller employs an optimization technique consisting of certain objectives such as reducing power loss in the tie-lines amongst MGs and the dependency of an MG to other MGs, as well as enhancing the contribution of renewable sources in electricity generation. Minimization of the fuel consumption and emissions of conventional generators, along with frequency and voltage deviation, is the other desired objectives. The performance of the proposal is evaluated by several numerical analyses in MATLAB (R).
Description:
Heterogeneous wireless sensor networks (WSNs) consist of resource-starving nodes that face a challenging task of handling various issues such as data redundancy, data fusion, congestion control, and energy efficiency. In these networks, data fusion algorithms process the raw data generated by a sensor node in an energy-efficient manner to reduce redundancy, improve accuracy, and enhance the network lifetime. In literature, these issues are addressed individually, and most of the proposed solutions are either application-specific or too complex that make their implementation unrealistic, specifically, in a resource-constrained environment. In this paper, we propose a novel node-level data fusion algorithm for heterogeneous WSNs to detect noisy data and replace them with highly refined data. To minimize the amount of transmitted data, a hybrid data aggregation algorithm is proposed that performs in-network processing while preserving the reliability of gathered data. This combination of data fusion and data aggregation algorithms effectively handle the aforementioned issues by ensuring an efficient utilization of the available resources. Apart from fusion and aggregation, a biased traffic distribution algorithm is introduced that considerably increases the overall lifetime of heterogeneous WSNs. The proposed algorithm performs the tedious task of traffic distribution according to the network's statistics, ie, the residual energy of neighboring nodes and their importance from a network's connectivity perspective. All our proposed algorithms were tested on a real-time dataset obtained through our deployed heterogeneous WSN in an orange orchard and also on publicly available benchmark datasets. Experimental results verify that our proposed algorithms outperform the existing approaches in terms of various performance metrics such as throughput, lifetime, data accuracy, computational time, and delay.
Description:
Heterogeneous wireless sensor networks (WSNs) consist of resource-starving nodes that face a challenging task of handling various issues such as data redundancy, data fusion, congestion control, and energy efficiency. In these networks, data fusion algorithms process the raw data generated by a sensor node in an energy-efficient manner to reduce redundancy, improve accuracy, and enhance the network lifetime. In literature, these issues are addressed individually, and most of the proposed solutions are either application-specific or too complex that make their implementation unrealistic, specifically, in a resource-constrained environment. In this paper, we propose a novel node-level data fusion algorithm for heterogeneous WSNs to detect noisy data and replace them with highly refined data. To minimize the amount of transmitted data, a hybrid data aggregation algorithm is proposed that performs in-network processing while preserving the reliability of gathered data. This combination of data fusion and data aggregation algorithms effectively handle the aforementioned issues by ensuring an efficient utilization of the available resources. Apart from fusion and aggregation, a biased traffic distribution algorithm is introduced that considerably increases the overall lifetime of heterogeneous WSNs. The proposed algorithm performs the tedious task of traffic distribution according to the network's statistics, ie, the residual energy of neighboring nodes and their importance from a network's connectivity perspective. All our proposed algorithms were tested on a real-time dataset obtained through our deployed heterogeneous WSN in an orange orchard and also on publicly available benchmark datasets. Experimental results verify that our proposed algorithms outperform the existing approaches in terms of various performance metrics such as throughput, lifetime, data accuracy, computational time, and delay.
Description:
In this paper, we argue that Design research is basic to countries' national productivity and competition agendas at the same time that vagaries of research training presents as one of the barriers faced by Design Higher Degree by Research students in engaging those agendas. We argue that, given industry requirements for research-trained recruits, students have the right to expect that research training will provide the foundations of a successful career on an academic or research pathway or a professional pathway, but that universities have yet to address problems in their provision of research training for Design doctoral students. We suggest that to facilitate this, rigorous research conducted on the provision of Doctoral programs in Design would serve to inform future activities in Design research in productive ways.