Ethical trust and social moral norms simulation : a bio-inspired agent-based modelling approach

The understanding of the micro-macro link is an urgent need in the study of social systems. The complex adaptive nature of social systems adds to the challenges of understanding social interactions and system feedback and presents substantial scope and potential for extending the frontiers of computer-based research tools such as simulations and agent-based technologies. In this project, we seek to understand key research questions concerning the interplay of ethical trust at the individual level and the development of collective social moral norms as representative sample of the bigger micro-macro link of social systems. We outline our computational model of ethical trust (CMET) informed by research findings from trust, machine ethics and neural science. Guided by the CMET architecture, we discuss key implementation ideas for the simulations of ethical trust and social moral norms.

Matrix-based pairwise key establishment with pre and post deployment knowledge for wireless mesh networks

The nature of wireless transmission leads to vulnerabilities to many malicious activities, and communication in wireless mesh networks (WMNs) must be protected by proper security measures. This paper focuses on symmetric pair wise key establishment and presents a new matrix-based pair wise key establishment scheme for mesh clients. In WMNs, mesh routers are much more powerful than mesh clients, both in communication and computation. By taking advantage of this heterogeneity, our new scheme delegates energy-consuming operations to mesh routers when establishing pair wise keys for mesh clients. Additionally, neighbor mesh clients in our scheme can directly establish pair wise keys with significantly reduced communication and storage costs, due to the use of both pre and post deployment knowledge.

Short designated verifier signature scheme and its identity-based variant

The notion of strong designated verifier signature was put forth by Jakobsson, Sako and Impagliazzo in 1996, but the formal definition was defined recently by Saeednia, Kremer and Markowitch in 2003 and revisited by Laguil- laumie and Vergnaud in 2004. In this paper, we firstly propose the notion of short strong designated verifier sig- nature scheme, and extend it to the short identity-based strong designated verifier scheme. Then, we propose the first construction of short strong designated verifier sig- nature scheme. We also extend our scheme to construct a short identity-based strong designated verifier signature scheme. The size of the signature of our schemes is the shortest compared to any existing schemes reported in the literature. We provide formal security proofs for our schemes based on the random oracle model. Finally, we also discuss an extension of our scheme to construct a short strong designated verifier signature without random oracle.

Polynomial based key predistribution scheme in wireless mesh networks

Wireless mesh networks (WMNs) have the ability to integrate with other networks while providing a fast and cost-saving deployment. The network security is one of important challenge problems in this kind of networks. This paper is focused on key management between mesh and sensor networks. We propose an efficient key pre-distribution scheme based on two polynomials in wireless mesh networks by employing the nature of heterogeneity. Our scheme realizes the property of bloom filters, i.e., neighbor nodes can discover their shared keys but have no knowledge on the different keys possessed by the other node, without the probability of false positive. The analysis presented in this paper shows that our scheme has the ability to establish three different security level keys and achieves the property of self adaptive security for sensor networks with acceptable computation and communication consumption.

Focus group discussions of literacy assessment and world wide web-based reading intervention

Focus groups provide a means for participants in research to take on a greater role in the evaluation of the research and planning of its various stages. The role and outcomes of focus groups conducted with participants in a World Wide Web Project in literacy assessment and intervention are reported. Thirteen individuals with severe communication impairments participated in one of three focus groups. The groups were held after an assesment of reading skills and a trial period of intervention as part of the Web Project. The aim of the focus groups was to obtain feedback from participants about their involvement in the project and to discuss strategies for the next stage of the intervention. The focus groups offered a forum for participants to talk about what they did and did not like about the assessment and trial intervention. The discussions provided information about issues of both a practical and emotional nature that might have otherwise been unavailable to the researchers. Brainstorming of strategies provided valuable input for the next stage of the project and involved both the researchers and participants in a form of participatory action research.

Developing and using an S3R model to analyze reasoning in web-based cross-national exchanges on sustainability

Within the increasing body of research that examines students' reasoning on socioscientific issues, we consider in particular student reasoning concerning acute, open-ended questions that bring out the complexities and uncertainties embedded in ill-structured problems. In this paper, we propose a socioscientific sustainability reasoning (S3R) model to analyze students' reasoning exchanges on environmental socially acute questions (ESAQs). The paper describes the development of an epistemological analysis of how sustainability perspectives can be integrated into socioscientific reasoning, which emphasizes the need for S3R to be both grounded in context and collective. We argue the complexity of ESAQs requires a consideration of multiple dimensions that form the basis of our S3R analysis model: problematization, interactions, knowledge, uncertainties, values, and governance. For each dimension, in the model we have identified indicators of four levels of complexity. We investigated the usefulness of the model in identifying improvements in reasoning that flow from cross-national web-based exchanges between groups of French and Australian students, concerning a local and a global ESAQ. The S3R model successfully captured the nature of reasoning about socioscientific sustainability issues, with the collective negotiation of multiple forms of knowledge as a key characteristic in improving reasoning levels. The paper provides examples of collaborative argumentation in collective texts (wikis) to illustrate the various levels of reasoning in each dimension, and diagrammatic representation of the evolution of collective reflections. We observe that a staged process of construction and confrontation, involving groups representing to some extent different cultural and contextual stances, is powerful in eliciting reasoned argument of enhanced quality. © 2014 Wiley Periodicals, Inc.

Can primary care team-based transition to insulin improve outcomes in adults with type 2 diabetes: the stepping up to insulin cluster randomized controlled trial protocol

Type 2 diabetes (T2D) brings significant human and healthcare costs. Its progressive nature means achieving normoglycaemia is increasingly difficult, yet critical to avoiding long term vascular complications. Nearly one-half of people with T2D have glycaemic levels out of target. Insulin is effective in achieving glycaemic targets, yet initiation of insulin is often delayed, particularly in primary care. Given limited access to specialist resources and the size of the diabetes epidemic, primary care is where insulin initiation must become part of routine practice. This would also support integrated holistic care for people with diabetes. Our Stepping Up Program is based on a general practitioner (GP) and practice nurse (PN) model of care supported appropriately by endocrinologists and credentialed diabetes educator-registered nurses. Pilot work suggests the model facilitates integration of the technical work of insulin initiation within ongoing generalist care.

Exploring first year teachers’ identity transformation through theatre-based research

Why are beginning teachers leaving the profession in large numbers? Are they leaving because of their dissatisfaction with teaching? Are they leaving because of the conditions of their work that shape their identity? Teacher identity work emphasises it is important beginning teachers understand their professional identity as something shifting, fluid and emerging – not fixed. These and other water metaphors – such as ‘washout’, ‘sink or swim’, and ‘thrown in the deep end’ – are often used to describe beginning teachers’ experiences. Such words and metaphors assist to portray the fluid and unpredictable nature of identity transformation. However, these survival terms also influence beginning teachers to believe that their transition to teaching will be difficult. Recently there has been an increased concern over beginning teacher attrition linked to the difficulties they encounter in their early years of teaching. Yet the conditions of beginning teachers’ work in Victorian schools in Australia – including the contractual nature of employment of first year (1yr) teachers – encourage these 1yr practitioners to view their work as semi-permanent. As a result these 1yr teachers do not see themselves as teaching for extended periods of time, as was once the case. Throughout 2011 twelve 1yr teachers shared their experiences of identity transformation in semi-structured interviews with the researcher. Their interview data was analysed through a theatre-based research method, examining how first experiences shape teachers’ future practice and identity. This presentation includes excerpts from the theatre-based research performance ‘The First Time’, and expands on the methodological approaches taken to analyse the data in a way that reflects the fluid and unpredictable nature of teachers’ identity formation and transformation. This qualitative study allows categories of description to emerge from the data rather than pre-determining categories of investigation. As such the processes of scripting, rehearsing, and performing, were utilised to analyse and re-present the data. In an aim to uncover questions that have been buried by answers, the research is oriented as a phenomenographic inquiry. This mode of inquiry seeks to describe, analyse, and understand the qualitatively different experiences 1yr teachers undergo in their identity formation and transformation. The results of this research reveal that beginning teachers’ identity transformation through their first experiences have both individual features specific to each teacher’s roles and aspirations, and extra-individual factors such as interactions, affiliations, and status, which shape their identity. Categories of description that have emerged from the analysis include survival, liminal, and hegemonic discourses, artifacts as symbols of belonging, and the impact of the contractual nature of teaching. Implications of this research focus on the importance for beginning teachers to develop an understanding of the transformative nature of identity in relation to the practice of teaching, to counter the negative preconceptions beginning teachers are told to expect as rites of passage upon entering the profession. The research outcomes have implications for teacher educators and in-service teachers negotiating the waters of an ever-changing profession.

An accelerated particle swarm optimization based levenberg marquardt back propagation algorithm

The Levenberg Marquardt (LM) algorithm is one of the most effective algorithms in speeding up the convergence rate of the Artificial Neural Networks (ANN) with Multilayer Perceptron (MLP) architectures. However, the LM algorithm suffers the problem of local minimum entrapment. Therefore, we introduce several improvements to the Levenberg Marquardt algorithm by training the ANNs with meta-heuristic nature inspired algorithm. This paper proposes a hybrid technique Accelerated Particle Swarm Optimization using Levenberg Marquardt (APSO_LM) to achieve faster convergence rate and to avoid local minima problem. These techniques are chosen since they provide faster training for solving pattern recognition problems using the numerical optimization technique.The performances of the proposed algorithm is evaluated using some bench mark of classification’s datasets. The results are compared with Artificial Bee Colony (ABC) Algorithm using Back Propagation Neural Network (BPNN) algorithm and other hybrid variants. Based on the experimental result, the proposed algorithms APSO_LM successfully demonstrated better performance as compared to other existing algorithms in terms of convergence speed and Mean Squared Error (MSE) by introducing the error and accuracy in network convergence.

Enhancing the carbon yield of cellulose based carbon fibres with ionic liquid impregnates

Here we show that ionic liquids (ILs), protic or aprotic in nature containing a phosphate anion, can be used as effective impregnating compounds resulting in a 50% improvement of the carbon yield of cellulose based carbon fibres and a 70 °C reduction in the onset of the depolymerization temperature. Using 13C NMR and FTIR spectra, we characterize the carbonized fibres with and without IL impregnates. The oxidative step in the formation of carbon fibres from cellulose precursors is very important in determining the final material properties, as such we examine this stage and show that the IL reduces the onset of the cellulose depolymerization temperature while improving the oxidative stability. This study highlights the ability of ILs to act as novel impregnates which can successfully reduce the formation of tar and volatile substances during carbonization of cellulose based carbon fibres resulting in an improved carbon yield and significant cost savings due to reduced maintenance and wear of equipment. This journal is

Cloud-based non-invasive tele-rehabilitation exercise monitoring

Exercise based rehabilitation plays a vital role in the recovery of various conditions, such as stroke, Parkinson’s disease (PD), chronic pain, and so on. Recently, telerehabilitation has become increasingly popular quantitative nature in assessments particularly for systematic monitoring of progress as well as cost saving for the patients as well as for the health care sector at large. However, challenges do exist in implementing a distributed bio-feedback in a cost-effective and efficient way. In this paper, we present the associated conceptual framework of cloud-based tele-rehabilitation system employing affordable non-invasive Microsoft Kinect® allowing patients to perform rehabilitation exercises in non-clinical setting such as home environments without loosing the quality of patients care. More importantly, different from existing tele-rehabilitation systems, our system not only measures whether patients can perform rehabilitation tasks, but also how well they can finish the tasks. Preliminary experiments validate its potential in training healthy subject to perform exercise motions emulating the physical rehabilitation process.

A simple and effective method to ameliorate the interfacial properties of cellulosic fibre based bio-composites using poly (ethylene glycol) based amphiphiles

In order to overcome interfacial incompatibility issues in natural fibre reinforced polymer bio-composites, surface modifications of the natural fibres using complex and environmentally unfriendly chemical methods is necessary. In this paper, we demonstrate that the interfacial properties of cellulose-based bio-composites can be tailored through surface adsorption of polyethylene glycol (PEG) based amphiphilic block copolymers using a greener alternative methodology. Mixtures of water or water/acetone were used to form amphiphilic emulsions or micro-crystal suspensions of PEG based amphiphilic block copolymers, and their deposition from solution onto the cellulosic substrate was carried out by simple dip-coating. The findings of this study evidence that, by tuning the amphiphilicity and the type of building blocks attached to the PEG unit, the flexural and dynamic thermo-mechanical properties of cellulose-based bio-composites comprised of either polylactide (PLA) or high density polyethylene (HDPE) as a matrix, can be remarkably enhanced. The trends, largely driven by interfacial effects, can be ascribed to the combined action of the hydrophilic and hydrophobic components of these amphiphiles. The nature of the interactions formed across the fibre-matrix interface is discussed. The collective outcome from this study provides a technological template to significantly improve the performance of cellulose-based bio-composite materials.

Synthesis and preliminary investigations into norbornane-based amphiphiles and their self-assembly

A range of norbornane based amphiphiles, which possess a rigid 'kink' in the centre of amphiphiles, were accessed via a concise four step synthesis. The self-assembly properties of these novel compounds were then investigated and the critical aggregation concentration (CAC), hydrodynamic diameter (DH) by dynamic light scattering (DLS) and their morphology by cryogenic transmission electron microscopy (cryoTEM) and negatively stained transmission electron microscopy (TEM) were determined. These compounds while possessing similar CAC values (50-70 μM) exhibited a wide variety of particle size (60-140 nm) and morphologies, including vesicles, cigar-shaped aggregates and rod-like micelles. Considering the similarities in molecular structure we have proposed that the unique nature of the molecular 'kink' is affecting molecular assembly in which subtle changes in molecular structure have large ramifications on aggregate size and morphology.

Performing beginning teachers’ ‘firsts’: exploring a theatre-based research method

Theatre-based research methods have been employed in a variety of ways to transcend more traditional research methods, and bring research findings to a broader and relevant audience. Performing research to an 'expert' audience is transformative in nature. The audience share a collective understanding of the material presented, where their understandings can be challenged or confirmed. The ethical responsibilities of the theatre-based researcher are therefore paramount in presenting the research in a manner that respects the research participants, and allows the audience to make informed judgements.This paper outlines my experience in devising and performing 'The First Time' - a performance about twelve beginning teachers' firsts. The performance was constructed from their interview data and performed by teachers - most of who are drama teachers – in order to sensitively represent the real stories of the research participants. The research was framed within a practice theory approach (Schatzki 2001) with a focus on the transformation of practices situated within a particular time and place. The method of performing the research to an 'expert' audience of performing arts practitioners, teachers, and teacher educators created an opportunity for both the transformation of teaching practice and the transformation of theatre.The research findings focus on the importance of creativity and flexibility in an approach to both research and teaching. The outcomes of my research have implications for theatre-based researchers, as well as teacher educators, in-service teachers, and beginning teachers. All these practitioners are continually negotiating the waters of their ever-changing professions.

Prediction interval-based modelling of polymerization reactor: a new modelling strategy for chemical reactors

Precise and reliable modelling of polymerization reactor is challenging due to its complex reaction mechanism and non-linear nature. Researchers often make several assumptions when deriving theories and developing models for polymerization reactor. Therefore, traditional available models suffer from high prediction error. In contrast, data-driven modelling techniques provide a powerful framework to describe the dynamic behaviour of polymerization reactor. However, the traditional NN prediction performance is significantly dropped in the presence of polymerization process disturbances. Besides, uncertainty effects caused by disturbances present in reactor operation can be properly quantified through construction of prediction intervals (PIs) for model outputs. In this study, we propose and apply a PI-based neural network (PI-NN) model for the free radical polymerization system. This strategy avoids assumptions made in traditional modelling techniques for polymerization reactor system. Lower upper bound estimation (LUBE) method is used to develop PI-NN model for uncertainty quantification. To further improve the quality of model, a new method is proposed for aggregation of upper and lower bounds of PIs obtained from individual PI-NN models. Simulation results reveal that combined PI-NN performance is superior to those individual PI-NN models in terms of PI quality. Besides, constructed PIs are able to properly quantify effects of uncertainties in reactor operation, where these can be later used as part of the control process. © 2014 Taiwan Institute of Chemical Engineers.