Participation and e-democracy how to utilize web 2.0 for policy decision-making

This paper investigates in how to utilize ICT and Web 2.0 technologies and e-democracy software for policy decision-making. It introduces a cutting edge decision-making system that integrates the practice of e-petitions, e-consultation, e-rulemaking, e-voting, and proxy voting. The paper demonstrates how under precondition of direct democracy through the use this system the collective intelligence (CI) of a population would be gathered and used throughout the policy process.

Asset life prediction and maintenance decision-making using a non-linear non-Gaussian state space model

Estimating and predicting degradation processes of engineering assets is crucial for reducing the cost and insuring the productivity of enterprises. Assisted by modern condition monitoring (CM) technologies, most asset degradation processes can be revealed by various degradation indicators extracted from CM data. Maintenance strategies developed using these degradation indicators (i.e. condition-based maintenance) are more cost-effective, because unnecessary maintenance activities are avoided when an asset is still in a decent health state. A practical difficulty in condition-based maintenance (CBM) is that degradation indicators extracted from CM data can only partially reveal asset health states in most situations. Underestimating this uncertainty in relationships between degradation indicators and health states can cause excessive false alarms or failures without pre-alarms. The state space model provides an efficient approach to describe a degradation process using these indicators that can only partially reveal health states. However, existing state space models that describe asset degradation processes largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires that failures and inspections only happen at fixed intervals. The discrete state assumption entails discretising continuous degradation indicators, which requires expert knowledge and often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This research proposes a Gamma-based state space model that does not have discrete time, discrete state, linear and Gaussian assumptions to model partially observable degradation processes. Monte Carlo-based algorithms are developed to estimate model parameters and asset remaining useful lives. In addition, this research also develops a continuous state partially observable semi-Markov decision process (POSMDP) to model a degradation process that follows the Gamma-based state space model and is under various maintenance strategies. Optimal maintenance strategies are obtained by solving the POSMDP. Simulation studies through the MATLAB are performed; case studies using the data from an accelerated life test of a gearbox and a liquefied natural gas industry are also conducted. The results show that the proposed Monte Carlo-based EM algorithm can estimate model parameters accurately. The results also show that the proposed Gamma-based state space model have better fitness result than linear and Gaussian state space models when used to process monotonically increasing degradation data in the accelerated life test of a gear box. Furthermore, both simulation studies and case studies show that the prediction algorithm based on the Gamma-based state space model can identify the mean value and confidence interval of asset remaining useful lives accurately. In addition, the simulation study shows that the proposed maintenance strategy optimisation method based on the POSMDP is more flexible than that assumes a predetermined strategy structure and uses the renewal theory. Moreover, the simulation study also shows that the proposed maintenance optimisation method can obtain more cost-effective strategies than a recently published maintenance strategy optimisation method by optimising the next maintenance activity and the waiting time till the next maintenance activity simultaneously.

Critical literacy finds a "Place": Writing and social action in a low-income Australian grade 2/3 classroom

In a study of socioeconomically disadvantaged children's acquisition of school literacies, a university research team investigated how a group of teachers negotiated critical literacies and explored notions of social power with elementary children in a suburban school located in an area of high poverty. Here we focus on a grade 2/3 classroom where the teacher and children became involved in a local urban renewal project and on how in the process the children wrote about place and power. Using the students' concerns about their neighborhood, the teacher engaged her class in a critical literacy project that not only involved a complex set of literate practices but also taught the children about power and the possibilities for local civic action. In particular, we discuss examples of children's drawing and writing about their neighborhoods and their lives. We explore how children's writing and drawing might be key elements in developing "critical literacies" in elementary school settings. We consider how such classroom writing can be a mediator of emotions, intellectual and academic learning, social practice, and political activism.

A grouping model for distributed pipeline assets maintenance decision

Distributed pipeline assets systems are crucial to society. The deterioration of these assets and the optimal allocation of limited budget for their maintenance correspond to crucial challenges for water utility managers. Decision makers should be assisted with optimal solutions to select the best maintenance plan concerning available resources and management strategies. Much research effort has been dedicated to the development of optimal strategies for maintenance of water pipes. Most of the maintenance strategies are intended for scheduling individual water pipe. Consideration of optimal group scheduling replacement jobs for groups of pipes or other linear assets has so far not received much attention in literature. It is a common practice that replacement planners select two or three pipes manually with ambiguous criteria to group into one replacement job. This is obviously not the best solution for job grouping and may not be cost effective, especially when total cost can be up to multiple million dollars. In this paper, an optimal group scheduling scheme with three decision criteria for distributed pipeline assets maintenance decision is proposed. A Maintenance Grouping Optimization (MGO) model with multiple criteria is developed. An immediate challenge of such modeling is to deal with scalability of vast combinatorial solution space. To address this issue, a modified genetic algorithm is developed together with a Judgment Matrix. This Judgment Matrix is corresponding to various combinations of pipe replacement schedules. An industrial case study based on a section of a real water distribution network was conducted to test the new model. The results of the case study show that new schedule generated a significant cost reduction compared with the schedule without grouping pipes.

Portrayal of librarians in Australian creative writing

An exploration is made of the ways in which librarians have been depicted in Australian creative writing. Reference is made to characters in novels, short stories, drama and poetry. With respect to novels, there is some consideration of characterisation and its relationship to plot.

Pedagogy of feedback on student academic writing : research supervisor practices for the end of the research degree candidature

All academic writing is advanced with the benefit of feedback about the writing. In the case of the academic writing genres of the research proposal and the dissertation, feedback is usually provided by the research supervisor. Given that academic writing development is a process, and in the case of the research proposal and dissertation, writing which develops over time, it seems likely that the nature of feedback on drafts written early in the candidature may be different from feedback provided by the research supervisor later in a student’s candidature. ----- ----- When a research supervisor has been reading a student’s writing over a period of time, their own familiarity with the writing generates a risk to their ability to provide critical and objective feedback. Particularly by the end of a student’s candidature, the research supervisor’s familiarity with the work may cause them to miss elements of writing improvement. ----- ----- The author, as a research supervisor, has developed a feedback grid to facilitate feedback on the final drafts of a dissertation. This feedback grid is generated by the embedded promises in the early sections of the dissertation, which are then used to audit the content of the final sections of the dissertation to ascertain whether promises made have been fulfilled. This provides a strategy for the research supervisor to step back from the work and read the dissertation with the agenda of a dissertation examiner. ----- ----- The grid is one strategy within a broader pedagogy of providing feedback on writing samples.

An obsession with storytelling : conducting oral history interviews for creative writing

Anna Hirsch and Clare Dixon (2008, 190) state that creative writers’ ‘obsession with storytelling…might serve as an interdisciplinary tool for evaluating oral histories.’ This paper enters a dialogue with Hirsch and Dixon’s statement by documenting an interview methodology for a practice-led PhD project, The Artful Life Story: Oral History and Fiction, which investigates the fictionalising of oral history. ----- ----- Alistair Thomson (2007, 62) notes the interdisciplinary nature of oral history scholarship from the 1980s onwards. As a result, oral histories are being used and understood in a variety of arts-based settings. In such contexts, oral histories are not valued so much for their factual content but as sources that are at once dynamic, emotionally authentic and open to a multiplicity of interpretations. How can creative writers design and conduct interviews that reflect this emphasis? ----- ----- The paper briefly maps the growing trend of using oral histories in fiction and ethnographic novels, in order to establish the need to design interviews for arts-based contexts. I describe how I initially designed the interviews to suit the aims of my practice. Once in the field, however, I found that my original methods did not account for my experiences. I conclude with the resulting reflection and understanding that emerged from these problematic encounters, focusing on the technique of steered monologue (Scagliola 2010), sometimes referred to as the Biographic Narrative Interpretative Method (Wengraf 2001, Jones 2006).

Attribute exclusion strategies in airline choice : accounting for exogenous information on decision maker processing strategies in models of discrete choice

We examine the impact of individual-specific information processing strategies (IPSs) on the inclusion/exclusion of attributes on the parameter estimates and behavioural outputs of models of discrete choice. Current practice assumes that individuals employ a homogenous IPS with regards to how they process attributes of stated choice (SC) experiments. We show how information collected exogenous of the SC experiment on whether respondents either ignored or considered each attribute may be used in the estimation process, and how such information provides outputs that are IPS segment specific. We contend that accounting the inclusion/exclusion of attributes will result in behaviourally richer population parameter estimates.

Maintenance strategy optimization using a continuous-state partially observable semi-Markov decision process

Due to the limitation of current condition monitoring technologies, the estimates of asset health states may contain some uncertainties. A maintenance strategy ignoring this uncertainty of asset health state can cause additional costs or downtime. The partially observable Markov decision process (POMDP) is a commonly used approach to derive optimal maintenance strategies when asset health inspections are imperfect. However, existing applications of the POMDP to maintenance decision-making largely adopt the discrete time and state assumptions. The discrete-time assumption requires the health state transitions and maintenance activities only happen at discrete epochs, which cannot model the failure time accurately and is not cost-effective. The discrete health state assumption, on the other hand, may not be elaborate enough to improve the effectiveness of maintenance. To address these limitations, this paper proposes a continuous state partially observable semi-Markov decision process (POSMDP). An algorithm that combines the Monte Carlo-based density projection method and the policy iteration is developed to solve the POSMDP. Different types of maintenance activities (i.e., inspections, replacement, and imperfect maintenance) are considered in this paper. The next maintenance action and the corresponding waiting durations are optimized jointly to minimize the long-run expected cost per unit time and availability. The result of simulation studies shows that the proposed maintenance optimization approach is more cost-effective than maintenance strategies derived by another two approximate methods, when regular inspection intervals are adopted. The simulation study also shows that the maintenance cost can be further reduced by developing maintenance strategies with state-dependent maintenance intervals using the POSMDP. In addition, during the simulation studies the proposed POSMDP shows the ability to adopt a cost-effective strategy structure when multiple types of maintenance activities are involved.

Investigating and theorizing discourse during analogy writing in chemistry

Explanations of the role of analogies in learning science at a cognitive level are made in terms of creating bridges between new information and students’ prior knowledge. In this empirical study of learning with analogies in an 11th grade chemistry class, we explore an alternative explanation at the "social" level where analogy shapes classroom discourse. Students in the study developed analogies within small groups and with their teacher. These classroom interactions were monitored to identify changes in discourse that took place through these activities. Beginning from socio-cultural perspectives and hybridity, we investigated classroom discourse during analogical activities. From our analyses, we theorized a merged discourse that explains how the analog discourse becomes intertwined with the target discourse generating a transitional state where meanings, signs, symbols, and practices are in flux. Three categories were developed that capture how students intertwined the analog and target discourses—merged words, merged utterances/sentences, and merged practices.

Developing an IS-Impact decision tool : a literature based design science roadmap

This paper derives from research-in-progress intending both Design Research (DR) and Design Science (DS) outputs; the former a management decision tool based in IS-Impact (Gable et al. 2008) kernel theory; the latter being methodological learnings deriving from synthesis of the literature and reflection on the DR ‘case study’ experience. The paper introduces a generic, detailed and pragmatic DS ‘Research Roadmap’ or methodology, deriving at this stage primarily from synthesis and harmonization of relevant concepts identified through systematic archival analysis of related literature. The scope of the Roadmap too has been influenced by the parallel study aim to undertake DR applying and further evolving the Roadmap. The Roadmap is presented in attention to the dearth of detailed guidance available to novice Researchers in Design Science Research (DSR), and though preliminary, is expected to evolve and gradually be substantiated through experience of its application. A key distinction of the Roadmap from other DSR methods is its breadth of coverage of published DSR concepts and activities; its detail and scope. It represents a useful synthesis and integration of otherwise highly disparate DSR-related concepts.

Developing a multidimensional scale for ethical decision making

This article reports on the development of the managerial ethical profile (MEP) scale. The MEP scale is a multilevel, self-reporting scale measuring the perceived influence that different dimensions of common ethical frameworks have on managerial decision making. The MEP scale measures on eight subscales: economic egoism, reputational egoism, act utilitarianism, rule utilitarianism, self-virtue of self, virtue of others, act deontology, and rule deontology. Confirmatory factor analysis (CFA) was used to provide evidence of scale validity. Future research needs and the value of this measure for business ethics are discussed.

Fault diagnosis of induction motor based on decision trees and adaptive neuro-fuzzy inference

This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection procedure to select pertinent features from data set. The crisp rules obtained from the decision tree are then converted to fuzzy if-then rules that are employed to identify the structure of ANFIS classifier. The hybrid of back-propagation and least squares algorithm are utilized to tune the parameters of the membership functions. In order to evaluate the proposed algorithm, the data sets obtained from vibration signals and current signals of the induction motors are used. The results indicate that the CART–ANFIS model has potential for fault diagnosis of induction motors.