A user driven data mining process model and learning system

This paper deals with the problem of using the data mining models in a real-world situation where the user can not provide all the inputs with which the predictive model is built. A learning system framework, Query Based Learning System (QBLS), is developed for improving the performance of the predictive models in practice where not all inputs are available for querying to the system. The automatic feature selection algorithm called Query Based Feature Selection (QBFS) is developed for selecting features to obtain a balance between the relative minimum subset of features and the relative maximum classification accuracy. Performance of the QBLS system and the QBFS algorithm is successfully demonstrated with a real-world application

Citizen journalism as social networking : reporting the 2007 Australian Federal Election

One of the perceived Achilles heels of online citizen journalism is its perceived inability to conduct investigative and first-hand reporting. A number of projects have recently addressed this problem, with varying success: the U.S.-based Assignment Zero was described as "a highly satisfying failure" (Howe 2007), while the German MyHeimat.de appears to have been thoroughly successful in attracting a strong community of contributors, even to the point of being able to generate print versions of its content, distributed free of charge to households in selected German cities. In Australia, citizen journalism played a prominent part in covering the federal elections held on 24 November 2007; news bloggers and public opinion Websites provided a strong counterpoint to the mainstream media coverage of the election campaign (Bruns et al., 2007). Youdecide2007.org, a collaboration between researchers at Queensland University of Technology and media practitioners at the public service broadcaster SBS, the public opinion site On Line Opinion, and technology company Cisco Systems, was developed as a dedicated space for a specifically hyperlocal coverage of the election campaign in each of Australia's 150 electorates from the urban sprawls of Sydney and Brisbane to the sparsely populated remote regions of outback Australia. YD07 provided training materials for would-be citizen journalists and encouraged them to contribute electorate profiles, interview candidates, and conduct vox-pops with citizens in their local area. The site developed a strong following especially in its home state of Queensland, and its interviewers influenced national public debate by uncovering the sometimes controversial personal views of mainstream and fringe candidates. At the same time, the success of YD07 was limited by external constraints determined by campaign timing and institutional frameworks. As part of a continuing action research cycle, lessons learnt from Youdecide2007.org are going to be translated into further iterations of the project, which will cover the local government elections in the Australian state of Queensland, to be held in March 2008, and developments subsequent to these elections. This paper will present research outcomes from the Youdecide2007.org project. In particular, it will examine the roles of staff contributors and citizen journalists in attracting members, providing information, promoting discussion, and fostering community on the site: early indications from a study of interaction data on the site indicate notably different contribution patterns and effects for staff and citizen participants, which may point towards the possibility of developing more explicit pro-am collaboration models in line with the Pro-Am phenomenon outlined by Leadbeater & Miller (2004). The paper will outline strengths and weaknesses of the Youdecide model and highlight requirements for the successful development of active citizen journalism communities. In doing so, it will also evaluate the feasibility of hyperlocal citizen journalism approaches, and their interrelationship with broader regional, state, and national journalism in both its citizen and industrial forms.

Mentoring preservice teachers in primary mathematics

A literature-based instrument gathered data about 147 final-year preservice teachers’ perceptions of their mentors’ practices related to primary mathematics teaching. Five factors characterized effective mentoring practices in primary mathematics teaching had acceptable Cronbach alphas, that is, Personal Attributes (mean scale score=3.97, SD [standard deviation]=0.81), System Requirements (mean scale score=2.98, SD=0.96), Pedagogical Knowledge (mean scale score=3.61, SD=0.89), Modelling (mean scale score=4.03, SD=0.73), and Feedback (mean scale score=3.80, SD=0.86) were .91, .74, .94, .89, and .86 respectively. Qualitative data (n=44) investigated mentors’ perceptions of mentoring these preservice teachers, including identification of successful mentoring practices and ways to enhance practices.

Understanding preservice teachers’ predispositions for teaching engineering education in Australian schools.

Engineering education is underrepresented in Australia at the primary, middle school and high school levels. Understanding preservice teachers’ preparedness to be involved in engineering will be important for developing an engineering curriculum. This study administered a literature-based survey to 36 preservice teachers, which gathered data about their perceptions of engineering and their predispositions for teaching engineering. Findings indicated that the four constructs associated with the survey had acceptable Cronbach alpha scores (i.e., personal professional attributes .88, student motivation .91, pedagogical knowledge .91, and fused curricula .89). However, there was no “disagree” or “strongly disagree” response greater than 22% for any of the 25 survey items. Generally, these preservice teachers indicated predispositions for teaching engineering in the middle school. Extensive scaffolding and support with education programs will assist preservice teachers to develop confidence in this field. Governments and education departments need to recognise the importance of engineering education, and universities must take a stronger role in developing engineering education curricula.

Fusion of in-vehicle sensor data to develop Intelligent Driver Training System (IDTS)

The over represented number of novice drivers involved in crashes is alarming. Driver training is one of the interventions aimed at mitigating the number of crashes that involve young drivers. To our knowledge, Advanced Driver Assistance Systems (ADAS) have never been comprehensively used in designing an intelligent driver training system. Currently, there is a need to develop and evaluate ADAS that could assess driving competencies. The aim is to develop an unsupervised system called Intelligent Driver Training System (IDTS) that analyzes crash risks in a given driving situation. In order to design a comprehensive IDTS, data is collected from the Driver, Vehicle and Environment (DVE), synchronized and analyzed. The first implementation phase of this intelligent driver training system deals with synchronizing multiple variables acquired from DVE. RTMaps is used to collect and synchronize data like GPS, vehicle dynamics and driver head movement. After the data synchronization, maneuvers are segmented out as right turn, left turn and overtake. Each maneuver is composed of several individual tasks that are necessary to be performed in a sequential manner. This paper focuses on turn maneuvers. Some of the tasks required in the analysis of ‘turn’ maneuver are: detect the start and end of the turn, detect the indicator status change, check if the indicator was turned on within a safe distance and check the lane keeping during the turn maneuver. This paper proposes a fusion and analysis of heterogeneous data, mainly involved in driving, to determine the risk factor of particular maneuvers within the drive. It also explains the segmentation and risk analysis of the turn maneuver in a drive.

Extending the advanced forensic format to accommodate multiple data sources, logical evidence, arbitrary information and forensic workflow

Forensic analysis requires the acquisition and management of many different types of evidence, including individual disk drives, RAID sets, network packets, memory images, and extracted files. Often the same evidence is reviewed by several different tools or examiners in different locations. We propose a backwards-compatible redesign of the Advanced Forensic Formatdan open, extensible file format for storing and sharing of evidence, arbitrary case related information and analysis results among different tools. The new specification, termed AFF4, is designed to be simple to implement, built upon the well supported ZIP file format specification. Furthermore, the AFF4 implementation has downward comparability with existing AFF files.

The enactment of the New Basics Project in a special school

This study investigates the impact of the New Basics Project on teachers at a special school for students with intellectual impairments. The study is aimed at exploring the complex nature of the work of special educators as they enact the New Basics curriculum with a particular focus on the teachers’ opinions about challenges that arose for their curriculum, pedagogy and assessment practices. Attention is also paid to how the principal’s leadership supported the enactment of the New Basics in respect to what he did and why he used particular strategies. The nine teachers and their principal were involved in a series of in-depth, semi-structured interviews from one of only three special schools in phase one of the New Basics trial in Queensland, Australia. These interviews produced data from the special educators as they were confronted with a new curriculum that challenged their previous teaching practices. The enactment of the New Basics curriculum occurred within the context of a state-sanctioned mandate to provide alternative programs to those offered in mainstream schools, for students with special needs. This thesis explores these teachers' experiences using critical theory as a basis for analyzing their opinions on issues such as the role of the special educator, tensions between old and new curricula, pedagogical and assessment practices, and connections between the at-school learning experiences for intellectually impaired students and the realities of post-school life. The investigation also examines the leadership conduct of the principal in changing times at the school. The findings suggest that the New Basics has played a significant role in providing structures for developing communities of practice amongst teachers; in supporting special educators to focus more on the educational needs of the students (e.g., literacy, numeracy, financial planning) and less on their medical needs (e.g., toileting, feeding, personal hygiene); and supporting school leadership that empowers and listens critically to teachers as essential components of the successful enactment of curriculum reforms like the New Basics.

A medical data reliability assessment model

There is currently a strong focus worldwide on the potential of large-scale Electronic Health Record (EHR) systems to cut costs and improve patient outcomes through increased efficiency. This is accomplished by aggregating medical data from isolated Electronic Medical Record databases maintained by different healthcare providers. Concerns about the privacy and reliability of Electronic Health Records are crucial to healthcare service consumers. Traditional security mechanisms are designed to satisfy confidentiality, integrity, and availability requirements, but they fail to provide a measurement tool for data reliability from a data entry perspective. In this paper, we introduce a Medical Data Reliability Assessment (MDRA) service model to assess the reliability of medical data by evaluating the trustworthiness of its sources, usually the healthcare provider which created the data and the medical practitioner who diagnosed the patient and authorised entry of this data into the patient’s medical record. The result is then expressed by manipulating health record metadata to alert medical practitioners relying on the information to possible reliability problems.

Data mining on prices of highway project main material based on WEB

The management of main material prices of provincial highway project quota has problems of lag and blindness. Framework of provincial highway project quota data MIS and main material price data warehouse were established based on WEB firstly. Then concrete processes of provincial highway project main material prices were brought forward based on BP neural network algorithmic. After that standard BP algorithmic, additional momentum modify BP network algorithmic, self-adaptive study speed improved BP network algorithmic were compared in predicting highway project main prices. The result indicated that it is feasible to predict highway main material prices using BP NN, and using self-adaptive study speed improved BP network algorithmic is the relatively best one.

What’s in a handshake? Exploring business-to-business relational exchange

Despite its importance in the development of competitive advantage, attempts to unify diverse classifications of business-to-business relational exchange have been largely unsuccessful. We used 18 semi-structured, in-depth interviews with managers from a wide range of industries to explain the business-to-business relational exchange construct. Analysis of the data revealed that business-to-business relational exchange comprises five key dimensions. These are communication, compatibility, commitment, trust and power symmetry. The research highlights the importance of personal interaction in business relationships and provided additional insights into the importance of affective commitment. In addition we reveal a number of negative consequences of affective commitment, which have been previously unexplored. A new conceptual model of business-to-business relational exchange is presented, which synthesises these findings and directs future research.

The reliability of information on work-related injuries available from hospitalisation data in Australia

Objective: To examine the reliability of work-related activity coding for injury-related hospitalisations in Australia. Method: A random sample of 4373 injury-related hospital separations from 1 July 2002 to 30 June 2004 were obtained from a stratified random sample of 50 hospitals across 4 states in Australia. From this sample, cases were identified as work-related if they contained an ICD-10-AM work-related activity code (U73) allocated by either: (i) the original coder; (ii) an independent auditor, blinded to the original code; or (iii) a research assistant, blinded to both the original and auditor codes, who reviewed narrative text extracted from the medical record. The concordance of activity coding and number of cases identified as work-related using each method were compared. Results: Of the 4373 cases sampled, 318 cases were identified as being work-related using any of the three methods for identification. The original coder identified 217 and the auditor identified 266 work-related cases (68.2% and 83.6% of the total cases identified, respectively). Around 10% of cases were only identified through the text description review. The original coder and auditor agreed on the assignment of work-relatedness for 68.9% of cases. Conclusions and Implications: The current best estimates of the frequency of hospital admissions for occupational injury underestimate the burden by around 32%. This is a substantial underestimate that has major implications for public policy, and highlights the need for further work on improving the quality and completeness of routine, administrative data sources for a more complete identification of work-related injuries.

Security metrics for object-oriented class designs

Measuring quality attributes of object-oriented designs (e.g. maintainability and performance) has been covered by a number of studies. However, these studies have not considered security as much as other quality attributes. Also, most security studies focus at the level of individual program statements. This approach makes it hard and expensive to discover and fix vulnerabilities caused by design errors. In this work, we focus on the security design of an object oriented application and define a number of security metrics. These metrics allow designers to discover and fix security vulnerabilities at an early stage, and help compare the security of various alternative designs. In particular, we propose seven security metrics to measure Data Encapsulation (accessibility) and Cohesion (interactions) of a given object-oriented class from the point of view of potential information flow.

The Children's Depression Scale : assessment of factor structure with data from a normal population

A study investigated the reliability and construct validity of the Children's Depression Scale. The revised subscales were shown to have strong construct and face validity and high reliability.

Development of the benefit finding in multiple sclerosis (MS) caregiving scale: A longitudinal study of relations between benefit finding and adjustment

Benefit finding is a meaning making construct that has been shown to be related to adjustment in people with MS and their carers. This study investigated the dimensions, stability and potency of benefit finding in predicting adjustment over a 12 month interval using a newly developed Benefit Finding in Multiple Sclerosis Scale (BFiMSS). Usable data from 388 persons with MS and 232 carers was obtained from questionnaires completed at Time 1 and 12 months later (Time 2). Factor analysis of the BFiMSS revealed seven psychometrically sound factors: Compassion/Empathy, Spiritual Growth, Mindfulness, Family Relations Growth, Life Style Gains, Personal Growth, New Opportunities. BFiMSS total and factors showed satisfactory internal and retest reliability coefficients, and convergent, criterion and external validity. Results of regression analyses indicated that the Time 1 BFiMSS factors accounted for significant amounts of variance in each of the Time 2 adjustment outcomes (positive states of mind, positive affect, anxiety, depression) after controlling for Time 1 adjustment, and relevant demographic and illness variables. Findings delineate the dimensional structure of benefit finding in MS, the differential links between benefit finding dimensions and adjustment and the temporal unfolding of benefit finding in chronic illness.