Subjective wellbeing and families : issues of measurement and data interpretation

Since April 2001 we have been monitoring the Subjective Wellbeing (SWB) of the Australian population using the Personal Wellbeing Index. Our aims are to establish normative values and to identify people with abnormally low SWB. Each of 18 surveys has involved a new sample of 2,000 people, randomly chosen but representing the geographical distribution of the population. The data are remarkable for their stability, with the variation in population mean scores being just 3.2 percentage points. The cause of such high reliability is Subjective Wellbeing Homeostasis. Here, in a manner analogous to the management of body temperature, the SWB for each person is normally held positive and within a narrow set-point range. However, all homeostatic systems have a limited capacity to absorb challenge and when aversive experiences are both strong and sustained, homeostasis fails. If this occurs, people lose their normal positive view of themselves and become depressed. Therefore, the second aim of these studies is to reveal the demographic character of families in distress, who are in need of additional resources. Our data reveal the extent to which family structure and responsibilities impact on wellbeing. They also yield important diagnostic information about individuals, and point to SWB as a crucial measure of intervention outcome. In sum, the Personal Wellbeing Index is a simple, reliable and valid measure of SWB. The measures it yields are theoretically embedded, they can be compared against solid normative data, and their interpretation is enhanced through an understanding of SWB homeostasis.

A comparison of participants with non-participants in a population-based epidemiologic study: the Melbourne Visual Impairment Project

PURPOSE: Adequate participation in population-based studies in essential to ensure that the sample is representative of the population under investigation. Participants may differ from non-participants on important variables such as age, sex socioeconomic status, and general health factors. The Melbourne Visual Impairment Project (Melbourne VIP) is a population-based study designed to increase understanding of the prevalence and severity of common ocular disorders affecting people 40 years of age and over. AIM: The aim of this study was to determine the potential for any non-response bias by comparing data from participants and non-participants of the Melbourne VIP. METHODS: Specific demographic and general variables were compared between the two groups. The variables included age, sex, education level, and social status. The reason for non-attendance was also recorded. RESULTS: A total of 3271 (83%) eligible residents from the 9 sample areas were screened; 46% males and 54% females. Language spoken at home was significantly associated with participation. Residents whose main language at home was not English were less likely to attend the screening centre. (OR: 0.60; CI: 0.44-0.81). The main reasons given for non-attendance by eligible residents were lack of interest (6%), too busy to attend (4%), personal illness (2%), and attend own eye specialist (2%). CONCLUSION: We believe these results will not impact significantly on the interpretation of gender and age-specific data from the Melbourne VIP.

Integrating data to facilitate clinical research : a case study

The integration of routine clinical administrative activities into ongoing rigorous clinical research poses challenges for both clinicians and researchers. This case study describes the development of a responsive database system used to facilitate comprehensive longitudinal research into the outcomes of patients waiting for hip and knee replacement surgery in a large public teaching hospital. The initial research procedure was paper-based, with manual patient matching and data entry. This process was time-consuming and associated with substantial risk of error and omissions, necessitating the design of a better system. An integrated database system was designed to receive daily electronic updates of the orthopaedic waiting-list and scheduled clinic and surgery dates. Using readily available software (Microsoft Access), new patients were identified through specifying inclusion and exclusion criteria which allowed rapid and complete recruitment at time of entry to the waiting-list. The integrated system specified the appropriate timing of multiple follow-up assessments, provided prompt information on recruitment for reporting purposes and integrated multiple linked research projects within one database. Seamless exporting of data to statistical programs for analysis was also enabled. This simple integrated approach facilitated efficient execution of a longitudinal study from recruitment to statistical analysis while maximising confidentiality and minimising resources required. This case study describes the development and design of a simple system which could be easily adapted for database management in hospital or clinic-based settings according to local requirements.

Innovative analytical chemistry for monitoring wine production

This study monitored concentration changes in the major constituents of wine during its production, through the development of new and innovative methodologies for a range of analytical instrumentation. Chemometrics (statistical analysis) was employed to enhance data interpretation, which provided insight into the reactions occurring between the key chemical species present.

PPFSCADA: Privacy preserving framework for SCADA data publishing

Supervisory Control and Data Acquisition (SCADA) systems control and monitor industrial and critical infrastructure functions, such as electricity, gas, water, waste, railway, and traffic. Recent attacks on SCADA systems highlight the need for stronger SCADA security. Thus, sharing SCADA traffic data has become a vital requirement in SCADA systems to analyze security risks and develop appropriate security solutions. However, inappropriate sharing and usage of SCADA data could threaten the privacy of companies and prevent sharing of data. In this paper, we present a privacy preserving strategy-based permutation technique called PPFSCADA framework, in which data privacy, statistical properties and data mining utilities can be controlled at the same time. In particular, our proposed approach involves: (i) vertically partitioning the original data set to improve the performance of perturbation; (ii) developing a framework to deal with various types of network traffic data including numerical, categorical and hierarchical attributes; (iii) grouping the portioned sets into a number of clusters based on the proposed framework; and (iv) the perturbation process is accomplished by the alteration of the original attribute value by a new value (clusters centroid). The effectiveness of the proposed PPFSCADA framework is shown through several experiments on simulated SCADA, intrusion detection and network traffic data sets. Through experimental analysis, we show that PPFSCADA effectively deals with multivariate traffic attributes, producing compatible results as the original data, and also substantially improving the performance of the five supervised approaches and provides high level of privacy protection. © 2014 Published by Elsevier B.V. All rights reserved.

Data management challenges in analysis and synthesis in the ecosystem sciences

Open-data has created an unprecedented opportunity with new challenges for ecosystem scientists. Skills in data management are essential to acquire, manage, publish, access and re-use data. These skills span many disciplines and require trans-disciplinary collaboration. Science synthesis centres support analysis and synthesis through collaborative 'Working Groups' where domain specialists work together to synthesise existing information to provide insight into critical problems. The Australian Centre for Ecological Analysis and Synthesis (ACEAS) served a wide range of stakeholders, from scientists to policy-makers to managers. This paper investigates the level of sophistication in data management in the ecosystem science community through the lens of the ACEAS experience, and identifies the important factors required to enable us to benefit from this new data-world and produce innovative science. ACEAS promoted the analysis and synthesis of data to solve transdisciplinary questions, and promoted the publication of the synthesised data. To do so, it provided support in many of the key skillsets required. Analysis and synthesis in multi-disciplinary and multi-organisational teams, and publishing data were new for most. Data were difficult to discover and access, and to make ready for analysis, largely due to lack of metadata. Data use and publication were hampered by concerns about data ownership and a desire for data citation. A web portal was created to visualise geospatial datasets to maximise data interpretation. By the end of the experience there was a significant increase in appreciation of the importance of a Data Management Plan. It is extremely doubtful that the work would have occurred or data delivered without the support of the Synthesis centre, as few of the participants had the necessary networks or skills. It is argued that participation in the Centre provided an important learning opportunity, and has resulted in improved knowledge and understanding of good data management practices.

Statistical detection of online drifting twitter spam

Spam has become a critical problem in online social networks. This paper focuses on Twitter spam detection. Recent research works focus on applying machine learning techniques for Twitter spam detection, which make use of the statistical features of tweets. We observe existing machine learning based detection methods suffer from the problem of Twitter spam drift, i.e., the statistical properties of spam tweets vary over time. To avoid this problem, an effective solution is to train one twitter spam classifier every day. However, it faces a challenge of the small number of imbalanced training data because labelling spam samples is time-consuming. This paper proposes a new method to address this challenge. The new method employs two new techniques, fuzzy-based redistribution and asymmetric sampling. We develop a fuzzy-based information decomposition technique to re-distribute the spam class and generate more spam samples. Moreover, an asymmetric sampling technique is proposed to re-balance the sizes of spam samples and non-spam samples in the training data. Finally, we apply the ensemble technique to combine the spam classifiers over two different training sets. A number of experiments are performed on a real-world 10-day ground-truth dataset to evaluate the new method. Experiments results show that the new method can significantly improve the detection performance for drifting Twitter spam.

Generalised 2D-correlation NMR analysis of a wine fermentation

A wine fermentation has been monitored on a daily basis by 1H NMR spectroscopy. Following data pre-processing that includes synthesis of the spectra to ensure all peaks are of constant half-width, the series of spectra were examined using generalised two-dimensional correlation techniques. Synchronous and asynchronous data maps have been generated and employed to interpret the changes in the fermentation process as a function of time. The results illustrate the potential of high resolution NMR with multivariate data analysis as a tool for process monitoring and the manner in which two-dimensional correlation mapping can aid in data interpretation.

Cross-cultural methodological issues in ethical research

Despite the fundamental and administrative difficulties associated with cross-cultural research the rewards are significant and, given an increasing trend toward globalisation, the move away from singular location studies to more comparative research is to be encouraged. In order to facilitate this research process it is imperative, however, that considerable attention is given to the methodological issues that can beset cross-cultural research, specifically as these issues relate to the primary domain or discipline of investigation, which in this instance is research on business ethics. Utilising the experience of a four country comparative study of both Asian and Western cultures in the field of business ethics, the following presents a discussion of methodological concerns under the three broad areas of operationalising culture, operationalising business ethics, and data interpretation.

Is this a meaningful learning experience? Interactive critical self-inquiry as investigation

What conditions enable educators to engage in meaningful learning experiences with peers and beginning practitioners? This article documents a self-study on our actions-in-practice in a peer mentoring project. The investigation involved an iterative process to improve our knowledge as teacher educators, reflective practitioners, and researchers. Data sets included: video-stimulated reflections; audiotaped reflexive dialogue; individual and shared reflective writings. Data analyzed through the iterative process revealed competing tensions that were not addressed by the triad, leading to a less than meaningful learning experience. We sought to name the dilemmas and document how they impeded meaningful learning; identifying tensions proved useful in data interpretation. The research led us to focus on the tension between collegiality and criticality. Managing this tension requires being authentic with and accepting of the other and working with cognitive dissonances. Collegiality and criticality together promote reflexivity and increase growth, leading to new professional knowledge.

Review of critical issues in carbon dioxide corrosion testing and monitoring techniques

This paper presents a brief review of major techniques applied in carbon dioxide corrosion testing and monitoring. The focus is on the advantages and disadvantages of variously designed testing apparatus and monitoring devices for localized corrosion detection and assessment. Critical factors affecting the reliability and accuracy of major corrosion testing techniques are briefly discussed. It is concluded that major reasons that lead to reporting of inaccurate corrosion rates and patterns include: (i) limitations in conventional electrochemical and nonelectrochemical methods for localized corrosion measurements, and difficulties in data interpretation; (ii) challenges in simulating localized corrosion mechanisms and their changes with the extension of corrosion testing. Underdeposit corrosion testing is presented as a case to illustrate challenges in simulating localized corrosion processes and mechanisms. Experiment data have been presented to show potential difficulties of the artificial pit electrode method in evaluating underdeposit corrosion and its inhibitors. The wire beam electrode method has been used to study underdeposit corrosion with and without inhibitor present. Several interesting corrosion mechanisms have been revealed at different stages of underdeposit corrosion processes.

You just change the channel if you don't like what you're going to hear: gamblers' attitudes towards, and interactions with, social marketing campaigns

OBJECTIVES: To investigate how gamblers interact with, and respond to, downstream social marketing campaigns that focus on the risks and harms of problem gambling and/or encourage help seeking. METHODS: Qualitative study of 100 gamblers with a range of gambling behaviours (from non-problem to problem gambling). We used a Social Constructivist approach. Our constant comparative method of data interpretation focused on how participants' experiences and interactions with gambling influenced their opinions towards, and interactions with social marketing campaigns. RESULTS: Three key themes emerged from the narratives. (i) Participants felt that campaigns were heavily skewed towards encouraging individuals to take personal responsibility for their gambling behaviours or were targeted towards those with severe gambling problems. (ii) Participants described the difficulty for campaigns to achieve 'cut through' because of the overwhelming volume of positive messages about the benefits of gambling that were given by the gambling industry. (iii) Some participants described that dominant discourses about personal responsibility prevented them from seeking help and reinforced perceptions of stigma. CONCLUSIONS AND IMPLICATIONS: Social marketing campaigns have an important role to play in the prevention of gambling risk behaviours and the promotion of help seeking. Social marketers should explore how to more effectively target campaigns to different audience segments, understand the role of environmental factors in undermining the uptake of social marketing strategies and anticipate the potential unforeseen consequences of social marketing strategies.

Multiple task transfer learning with small sample sizes

Prognosis, such as predicting mortality, is common in medicine. When confronted with small numbers of samples, as in rare medical conditions, the task is challenging. We propose a framework for classification with data with small numbers of samples. Conceptually, our solution is a hybrid of multi-task and transfer learning, employing data samples from source tasks as in transfer learning, but considering all tasks together as in multi-task learning. Each task is modelled jointly with other related tasks by directly augmenting the data from other tasks. The degree of augmentation depends on the task relatedness and is estimated directly from the data. We apply the model on three diverse real-world data sets (healthcare data, handwritten digit data and face data) and show that our method outperforms several state-of-the-art multi-task learning baselines. We extend the model for online multi-task learning where the model parameters are incrementally updated given new data or new tasks. The novelty of our method lies in offering a hybrid multi-task/transfer learning model to exploit sharing across tasks at the data-level and joint parameter learning.