Suitability of chlorine bulk decay models for planning and management of water distribution systems

Effective disinfection planning and management in large, complex water distribution systems requires an accurate network water quality model. This model should be based on reaction kinetics, which describes disinfectant loss from bulk water over time, within experimental error. Models in the literature were reviewed for their ability to meet this requirement in real networks. Essential features were identified as accuracy, simplicity, computational efficiency, and ability to describe consistently the effects of initial chlorine dose, temperature variation, and successive rechlorinations. A reaction scheme of two organic constituents reacting with free chlorine was found to be necessary and sufficient to provide the required features. Recent release of the multispecies extension (MSX) to EPANET and MWH Soft's H2OMap Water MSX network software enables users to implement this and other multiple-reactant bulk decay models in real system simulations.

Latent variable models of need for uniqueness

The theory of uniqueness has been invoked to explain attitudinal and behavioral nonconformity with respect to peer-group, social-cultural, and statistical norms, as well as the development of a distinctive view of self via seeking novelty goods, adopting new products, acquiring scarce commodities, and amassing material possessions. Present research endeavors in psychology and consumer behavior are inhibited by uncertainty regarding the psychometric properties of the Need for Uniqueness Scale, the primary instrument for measuring individual differences in uniqueness motivation. In an important step toward facilitating research on uniqueness motivation, we used confirmatory factor analysis to evaluate three a priori latent variable models of responses to the Need for Uniqueness Scale. Among the a priori models, an oblique three-factor model best accounted for commonality among items. Exploratory factor analysis followed by estimation of unrestricted three- and four-factor models revealed that a model with a complex pattern of loadings on four modestly correlated factors may best explain the latent structure of the Need for Uniqueness Scale. Additional analyses evaluated the associations among the three a priori factors and an array of individual differences. Results of those analyses indicated the need to distinguish among facets of the uniqueness motive in behavioral research.

Flickr hypergroups

The amount of multimedia content available online constantly increases, and this leads to problems for users who search for content or similar communities. Users in Flickr often self-organize in user communities through Flickr Groups. These groups are particularly interesting as they are a natural instantiation of the content + relations social media paradigm. We propose a novel approach to group searching through hypergroup discovery. Starting from roughly 11,000 Flickr groups' content and membership information, we create three different bag-of-word representations for groups, on which we learn probabilistic topic models. Finally, we cast the hypergroup discovery as a clustering problem that is solved via probabilistic affinity propagation. We show that hypergroups so found are generally consistent and can be described through topic-based and similarity-based measures. Our proposed solution could be relatively easily implemented as an application to enrich Flickr's traditional group search.

Microeconomic models of intra-household activity time allocation

The primary purpose of this research is to analyze theoretically the group decisionmaking process leading to the allocation of activity time and the consumption of goods, with particular emphasis in the households. Each household is characterized as a group of individuals making joint decisions about their activity participations, alternative activity time allocations and consumption of various goods, such as independent and joint activity time allocations as well as private and shared consumption patterns. We firstly explore why individual-based models are not realistic in multi-person households, and secondly, we summarize various intra-household activity time allocation models based on different decision-making processes. All models are presented under microeconomic principle of utility maximization to represent the economic behavior of the households.

Fuzzy rule base assessment models : theoretical analyses and a case study

An assessment model is usually a mathematical model that produces a measuring index, in the form of a numerical score to a situation/object, with respect to the subject of measure. To allow a valid and useful comparison among various situations/objects according to their associated numerical scores to be made, two important properties, i.e., the monotone output property and output resolution properties, are essential in fuzzy inference-based assessment problems. In this paper, the conditions for a fuzzy assessment model to fulfill the monotone output property is investigated using a derivative approach. A guideline on how the input membership functions should be tuned is also provided. Besides, the output resolution property is defined as the derivative of the output of the assessment model with respect to the input, whereby the derivative should be greater than a minimum resolution. Based on the derivative, improvements to the output resolution property by refining the fuzzy production rules are suggested. A case study on the Bowles fuzzy RPN model to demonstrate the effectiveness of the properties is also included.

On the use of fuzzy inference techniques in assessment models : part I — theoretical properties

An assessment model is a mathematical model that produces a measuring index, either in the form of a numerical score or a category to a situation/object, with respect to the subject of measure. From the numerical score, decision can be made and action can be taken. To allow valid and useful comparisons among various situations/objects according to their associated numerical scores to be made, the monotone output property and the output resolution property are essential in fuzzy inference-based assessment problems. We investigate the conditions for a fuzzy assessment model to fulfill the monotone output property using a derivative approach. A guideline on how the input membership functions should be tuned is also provided. Besides, the output resolution property is defined as the derivative of the output of the assessment model with respect to its input. This derivative should be greater than the minimum resolution required. From the derivative, we suggest improvements to the output resolution property by refining the fuzzy production rules.

Finding a place for personal growth in an Australian community singing group for older people

As in many countries, Australia is faced with an aging population. This creates challenges for the maintenance of well-being which can be enhanced by active engagement in society. Music engagement encompasses a range of social participation and has the potential to recognise the contribution of older people to their local communities. Engagement in music by older people (50+) is positively related to individual and community well-being.  Music participation can contribute to a better quality of life, particularly in relation to health and happiness. The possible forms of music engagement are myriad.

This paper focuses on two members of a mixed voluntary singing group formed by older residents of an outer suburban community in Melbourne, Australia.  This study frames music as a positive way for older people to find a place for personal growth and fulfilment in a singing group. This phenomenological qualitative single case study focuses on two members of a small singing ensemble, the Skylarkers, formed to perform at retirement villages, nursing homes and facilities for senior citizens. In this study, data were gathered by interviews and analysed using interpretative phenomenological analysis.

Two significant themes emerged. The first concerned the nature of the choir and its fluid membership and notions of self-identity. The second theme concerns the validation offered to individual members by active music participation through which they gained a sense of purpose, fulfilment and personal growth. This emphasis is unusual in discussions of community music engagement that ordinarily identify the importance of social connections. Groups such as the Skylarkers provide a place for members to continue their active engagement with music performance and music learning.

Adolescent peer group orientation, parent/attachment styles and mental health

Jennette Robinson’s research examined peer group characteristics and their relationship to parent/peer attachment, parenting styles, and adolescent functioning. Secure parental attachments were not associated with easier group access or participation in a greater number of groups. Evidence supported a relationship between parenting style and both group establishment and membership hierarchy.

Medulloblastoma Down Under 2013 : a report from the third annual meeting of the International Medulloblastoma Working Group.

Medulloblastoma is curable in approximately 70% of patients. Over the past decade, progress in improving survival using conventional therapies has stalled, resulting in reduced quality of life due to treatment-related side effects, which are a major concern in survivors. The vast amount of genomic and molecular data generated over the last 5-10 years encourages optimism that improved risk stratification and new molecular targets will improve outcomes. It is now clear that medulloblastoma is not a single-disease entity, but instead consists of at least four distinct molecular subgroups: WNT/Wingless, Sonic Hedgehog, Group 3, and Group 4. The Medulloblastoma Down Under 2013 meeting, which convened at Bunker Bay, Australia, brought together 50 leading clinicians and scientists. The 2-day agenda included focused sessions on pathology and molecular stratification, genomics and mouse models, high-throughput drug screening, and clinical trial design. The meeting established a global action plan to translate novel biologic insights and drug targeting into treatment regimens to improve outcomes. A consensus was reached in several key areas, with the most important being that a novel classification scheme for medulloblastoma based on the four molecular subgroups, as well as histopathologic features, should be presented for consideration in the upcoming fifth edition of the World Health Organization's classification of tumours of the central nervous system. Three other notable areas of agreement were as follows: (1) to establish a central repository of annotated mouse models that are readily accessible and freely available to the international research community; (2) to institute common eligibility criteria between the Children's Oncology Group and the International Society of Paediatric Oncology Europe and initiate joint or parallel clinical trials; (3) to share preliminary high-throughput screening data across discovery labs to hasten the development of novel therapeutics. Medulloblastoma Down Under 2013 was an effective forum for meaningful discussion, which resulted in enhancing international collaborative clinical and translational research of this rare disease. This template could be applied to other fields to devise global action plans addressing all aspects of a disease, from improved disease classification, treatment stratification, and drug targeting to superior treatment regimens to be assessed in cooperative international clinical trials.

Averaging aggregation functions for preferences expressed as Pythagorean membership grades and fuzzy orthopairs

Rather than denoting fuzzy membership with a single value, orthopairs such as Atanassov's intuitionistic membership and non-membership pairs allow the incorporation of uncertainty, as well as positive and negative aspects when providing evaluations in fuzzy decision making problems. Such representations, along with interval-valued fuzzy values and the recently introduced Pythagorean membership grades, present particular challenges when it comes to defining orders and constructing aggregation functions that behave consistently when summarizing evaluations over multiple criteria or experts. In this paper we consider the aggregation of pairwise preferences denoted by membership and non-membership pairs. We look at how mappings from the space of Atanassov orthopairs to more general classes of fuzzy orthopairs can be used to help define averaging aggregation functions in these new settings. In particular, we focus on how the notion of 'averaging' should be treated in the case of Yager's Pythagorean membership grades and how to ensure that such functions produce outputs consistent with the case of ordinary fuzzy membership degrees.

Single-preference consensus measures based on models of ecological evenness

We investigate the relationship between consensus measures used in different settings depending on how voters or experts express their preferences. We propose some new models for single-preference voting, which we derive from the evenness concept in ecology, and show that some of these can be placed within the framework of existing consensus measures using the discrete distance. Finally, we suggest some generalizations of the single-preference consensus measures allowing the incorporation of more general notions of distance.

A two-stage dynamic group decision making method for processing ordinal information

In group decision making (GDM) problems, ordinal data provide a convenient way of articulating preferences from decision makers (DMs). A number of GDM models have been proposed to aggregate such kind of preferences in the literature. However, most of the GDM models that handle ordinal preferences suffer from two drawbacks: (1) it is difficult for the GDM models to manage conflicting opinions, especially with a large number of DMs; and (2) the relationships between the preferences provided by the DMs are neglected, and all DMs are assumed to be of equal importance, therefore causing the aggregated collective preference not an ideal representative of the group's decision. In order to overcome these problems, a two-stage dynamic group decision making method for aggregating ordinal preferences is proposed in this paper. The method consists of two main processes: (i) a data cleansing process, which aims to reduce the influence of conflicting opinions pertaining to the collective decision prior to the aggregation process; as such an effective solution for undertaking large-scale GDM problems is formulated; and (ii) a support degree oriented consensus-reaching process, where the collective preference is aggregated by using the Power Average (PA) operator; as such, the relationships of the arguments being aggregated are taken into consideration (i.e., allowing the values being aggregated to support each other). A new support function for the PA operator to deal with ordinal information is defined based on the dominance-based rough set approach. The proposed GDM model is compared with the models presented by Herrera-Viedma et al. An application related to controlling the degradation of the hydrographic basin of a river in Brazil is evaluated. The results demonstrate the usefulness of the proposed method in handling GDM problems with ordinal information.

Enhancing and assessing group and team learning in architecture and related design contexts

EXECUTIVE SUMMARYTeamwork skills are essential in the design industry where practitioners negotiate often-conflicting design options in multi-disciplinary teams. Indeed, many of the bodies that accredit design courses explicitly list teamwork skills as essential attributes of design graduates e.g., the Australian Institute of Architects (AIA), Royal Institute of British Architects (RIBA), the National Council of Architectural Registration Boards (NCARB) of the United States and the Institution of Engineers, Australia (IEAust). In addition to the need to meet the demands of the accrediting bodies, there are many reasons for the ubiquitous use of teamwork assignments in design schools. For instance, teamwork learning is seen as being representative of work in practice where design is nearly always a collaborative activity. Learning and teaching in teamwork contexts in design education are not without particular challenges. In particular, two broad issues have been identified: first, many students leave academia without having been taught the knowledge and skills of how to design in teams; second, teaching, assessment and assignment design need to be better informed by a clear understanding of what leads to effective teamwork and the learning of teamwork skills. In recognition of the lack of a structured approach to integrating teamwork learning into the curricula of design programs, this project set out to answer three primary research questions: • How do we teach teamwork skills in the context of design? • How do we assess teamwork skills?• How do design students best learn teamwork skills?In addition, four more specific questions were investigated:1. Is there a common range of learning objectives for group-and-team-work in architecture and related design disciplines that will enable the teaching of consistent and measurable outcomes?2. Do group and team formation methods, learning styles and team-role preferences impact students’ academic and course satisfaction outcomes?3. What combinations of group-and-team formation methods, teaching and assessment models significantly improve learning outcomes?4. For design students across different disciplines with different learning styles and cultural origins, are there significant differences in performance, student satisfaction (as measured through questionnaires and unit evaluations), group-and-team working abilities and student participation?To elucidate these questions, a design-based research methodology was followed comprising an iterative series of enquiries: (a) A literature review was completed to investigate: what constitutes effective teamwork, what contributes to effectiveness in teams, what leads to positive design outcomes for teams, and what leads to effective learning in teams. The review encompassed a range of contexts: from work-teams in corporate settings, to professional design teams, to education outside of and within the design disciplines. The review informed a theoretical framework for understanding what factors impact the effectiveness of student design teams. (b) The validity of this multi-factorial Framework of Effectiveness in Student Design Teams was tested via surveys of educators’ teaching practices and attitudes, and of students’ learning experiences. 638 students and 68 teachers completed surveys: two pilot surveys for participants at the four partner institutions, which then informed two national surveys completed by participants from the majority of design schools across Australia. (c) The data collected provided evidence for 22 teamwork factors impacting team effectiveness in student design teams. Pedagogic responses and strategies to these 22 teamwork factors were devised, tested and refined via case studies, focus groups and workshops. (d) In addition, 35 educators from a wide range of design schools and disciplines across Australia attended two National Teaching Symposiums. The first symposium investigated the wider conceptualisation of teamwork within the design disciplines, and the second focused on curriculum level approaches to structuring the teaching of teamwork skills identified in the Framework.The Framework of Effectiveness in Student Design Teams identifies 22 factors impacting effective teamwork, along with teaching responses and strategies that design educators might use to better support student learning. The teamwork factors and teaching strategies are categorised according to three groups of input (Task Characteristics, Individual Level Factors and Team Level Factors), two groups of processes (Teaching Practice & Support Structures and Team Processes), and three categories of output (Task Performance, Teamwork Skills, and Attitudinal Outcomes). Eight of the 22 teamwork factors directly relate to the skills that need to be developed in students, one factor relates to design outputs, and the other thirteen factors inform pedagogies that can be designed for better learning outcomes. In Table 10 of Section 4, we outline which of the 22 teamwork factors pertain to each of five stakeholder groups (curriculum leaders, teachers, students, employers and the professional bodies); thus establishing who will make best use the information and recommendations we make. In the body of this report we summarise the 22 teamwork factors and teaching strategies informed by the Framework of Effectiveness in Student Design Teams, and give succinct recommendations arising from them. This material is covered in depth by the project outputs. For instance, the teaching and assessment strategies will be expanded upon in a projected book on Teaching Teamwork in Design. The strategies are also elucidated by examples of good practice presented in our case studies, and by Manuals on Teamwork for Teachers and Students. Moreover, the project website ( visited by representatives of stakeholder groups in Australia and Canada), is seeding a burgeoning community of practice that promises dissemination, critical evaluation and the subsequent refinement of our materials, tools, strategies and recommendations. The following three primary outputs have been produced by the project in answer to the primary research questions:1. A theoretical Framework of Effectiveness in Student Design Teams;2. Manuals on Teamwork for Teachers and Students (available from the website);3. Case studies of good/innovative practices in teaching and assessing teamwork in design;In addition, five secondary outputs/outcomes have been produced that provide more nuanced responses:4. Detailed recommendations for the professional accrediting bodies and curriculum leaders;5. Online survey data (from over 700 participants), plus Team Effectiveness Scale to determine the factors influencing effective learning and successful outputs for student design teams;6. A community of practice in policy, programs, practice and dialogue;7. A detailed book proposal (with sample chapter), submitted to prospective publishers, on Teaching Teamwork in Design; 8. An annotated bibliography (accessed via the project website) on learning, teaching and assessing teamwork.The project has already had an international impact. As well as papers presented in Canada and New Zealand, the surveys were participated in by six Canadian schools of architecture, whose teaching leaders also provided early feedback on the project aims and objectives during visits made to them by the project leader. In addition, design schools in Vancouver, Canada, and San Diego in the USA have already utilised the Teacher’s Manual, and in February 2014 the project findings were discussed at Tel Aviv University in a forum focusing on the challenges for sustainability in architectural education.

Hierarchical Bayesian models of subtask learning

 The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking task, which logged participant actions, enabling measurement of strategy use and subtask performance. Model comparison was performed using deviance information criterion (DIC), posterior predictive checks, plots of model fits, and model recovery simulations. Results showed that although learning tended to be monotonically decreasing and decelerating, and approaching an asymptote for all subtasks, there was substantial inconsistency in learning curves both at the group- and individual-levels. This inconsistency was most apparent when constraining both the rate and the ratio of learning to asymptote to be equal across subtasks, thereby giving learning curves only 1 parameter for scaling. The inclusion of 6 strategy covariates provided improved prediction of subtask performance capturing different subtask learning processes and subtask trade-offs. In addition, strategy use partially explained the inconsistency in subtask learning. Overall, the model provided a more nuanced representation of how complex tasks can be decomposed in terms of simpler learning mechanisms.

Bayesian nonparametric multilevel clustering with group-level contexts

We present a Bayesian nonparametric framework for multilevel clustering which utilizes group- level context information to simultaneously discover low-dimensional structures of the group contents and partitions groups into clusters. Using the Dirichlet process as the building block, our model constructs a product base-measure with a nested structure to accommodate content and context observations at multiple levels. The proposed model possesses properties that link the nested Dinchiet processes (nDP) and the Dirichlet process mixture models (DPM) in an interesting way: integrating out all contents results in the DPM over contexts, whereas integrating out group-specific contexts results in the nDP mixture over content variables. We provide a Polyaurn view of the model and an efficient collapsed Gibbs inference procedure. Extensive experiments on real-world datasets demonstrate the advantage of utilizing context information via our model in both text and image domains.