Report : wireless data throughput testing on a mobile device using WiFi and GPRS

This project report presents the results of a study on wireless communication data transfer rates for a mobile device running a custombuilt construction defect reporting application. The study measured the time taken to transmit data about a construction defect, which included digital imagery and text, in order to assess the feasibility of transferring various types and sizes of data and the ICT-supported construction management applications that could be developed as a consequence. Data transfer rates over GPRS through the Telstra network and WiFi over a private network were compared. Based on the data size and data transfer time, the rate of transfer was calculated to determine the actual data transmission speeds at which the information was being sent using the wireless mobile communication protocols. The report finds that the transmission speeds vary considerably when using GPRS and can be significantly slower than what is advertised by mobile network providers. While WiFi is much faster than GPRS, the limited range of WiFi limits the protocol to residential-scale construction sites.

Report : stochastic analysis of road asset data for maintenance cost prediction

Reliable budget/cost estimates for road maintenance and rehabilitation are subjected to uncertainties and variability in road asset condition and characteristics of road users. The CRC CI research project 2003-029-C ‘Maintenance Cost Prediction for Road’ developed a method for assessing variation and reliability in budget/cost estimates for road maintenance and rehabilitation. The method is based on probability-based reliable theory and statistical method. The next stage of the current project is to apply the developed method to predict maintenance/rehabilitation budgets/costs of large networks for strategic investment. The first task is to assess the variability of road data. This report presents initial results of the analysis in assessing the variability of road data. A case study of the analysis for dry non reactive soil is presented to demonstrate the concept in analysing the variability of road data for large road networks. In assessing the variability of road data, large road networks were categorised into categories with common characteristics according to soil and climatic conditions, pavement conditions, pavement types, surface types and annual average daily traffic. The probability distributions, statistical means, and standard deviation values of asset conditions and annual average daily traffic for each type were quantified. The probability distributions and the statistical information obtained in this analysis will be used to asset the variation and reliability in budget/cost estimates in later stage. Generally, we usually used mean values of asset data of each category as input values for investment analysis. The variability of asset data in each category is not taken into account. This analysis method demonstrated that it can be used for practical application taking into account the variability of road data in analysing large road networks for maintenance/rehabilitation investment analysis.

Nonfatal heroin overdoses in Queensland, Australia : an analysis of ambulance data

In the past decade, the utilization of ambulance data to inform the prevalence of nonfatal heroin overdose has increased. These data can assist public health policymakers, law enforcement agencies, and health providers in planning and allocating resources. This study examined the 672 ambulance attendances at nonfatal heroin overdoses in Queensland, Australia, in 2000. Gender distribution showed a typical 70/30 male-to-female ratio. An equal number of persons with nonfatal heroin overdose were between 15 and 24 years of age and 25 and 34 years of age. Police were present in only 1 of 6 cases, and 28.1% of patients reported using drugs alone. Ambulance data are proving to be a valuable population-based resource for describing the incidence and characteristics of nonfatal heroin overdose episodes. Future studies could focus on the differences between nonfatal heroin overdose and fatal heroin overdose samples.

Benchmarks for recycling practices in commercial office building refurbishment : data collection challenges

In recent years considerable effort has gone into quantifying the reuse and recycling potential of waste generated by residential construction. Unfortunately less information is available for the commercial refurbishment sector. It is hypothesised that significant economic and environmental benefit can be derived from closer monitoring of the commercial construction waste stream. With the aim of assessing these benefits, the authors are involved in ongoing case studies to record both current standard practice and the most effective means of improving the eco-efficiency of materials use in office building refurbishments. This paper focuses on the issues involved in developing methods for obtaining the necessary information on better waste management practices and establishing benchmark indicators. The need to create databases to establish benchmarks of waste minimisation best practice in commercial construction is stressed. Further research will monitor the delivery of case study projects and the levels of reuse and recycling achieved in directly quantifiable ways

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

BioPatML : pattern sharing for the genomic sciences

Computational biology increasingly demands the sharing of sophisticated data and annotations between research groups. Web 2.0 style sharing and publication requires that biological systems be described in well-defined, yet flexible and extensible formats which enhance exchange and re-use. In contrast to many of the standards for exchange in the genomic sciences, descriptions of biological sequences show a great diversity in format and function, impeding the definition and exchange of sequence patterns. In this presentation, we introduce BioPatML, an XML-based pattern description language that supports a wide range of patterns and allows the construction of complex, hierarchically structured patterns and pattern libraries. BioPatML unifies the diversity of current pattern description languages and fills a gap in the set of XML-based description languages for biological systems. We discuss the structure and elements of the language, and demonstrate its advantages on a series of applications, showing lightweight integration between the BioPatML parser and search engine, and the SilverGene genome browser. We conclude by describing our site to enable large scale pattern sharing, and our efforts to seed this repository.

Investigating the role of ICT in improving productivity in construction supply chains in Australian construction industry.

The Australian construction industry is a fragmented and profoundly competitive industry with high levels of subcontracting resulting in complex supply chain formations. Traditional methods and forms of communication are being proven as inefficient and losing their charm while participants face heavy volumes of communications that often occurs on a daily basis between trading partners in a supply chain on projects. Information Communication Technologies (ICT), due to their robustness and the ability to quickly disseminate data/information, have the capacity to address highlighted communication issues in a structured and an efficient manner. Timesavings produced by these can be directly translated in terms of productivity gain. This paper presents perceptions of subcontractors working in the construction industry in Melbourne Australia on the use of ICT obtained through an exploratory study.

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.

A time-variant medical data trustworthiness assessment model

Electronic Health Record (EHR) systems are being introduced to overcome the limitations associated with paper-based and isolated Electronic Medical Record (EMR) systems. This is accomplished by aggregating medical data and consolidating them in one digital repository. Though an EHR system provides obvious functional benefits, there is a growing concern about the privacy and reliability (trustworthiness) of Electronic Health Records. Security requirements such as confidentiality, integrity, and availability can be satisfied by traditional hard security mechanisms. However, measuring data trustworthiness from the perspective of data entry is an issue that cannot be solved with traditional mechanisms, especially since degrees of trust change over time. In this paper, we introduce a Time-variant Medical Data Trustworthiness (TMDT) assessment model to evaluate the trustworthiness of medical data by evaluating the trustworthiness of its sources, namely the healthcare organisation where the data was created and the medical practitioner who diagnosed the patient and authorised entry of this data into the patient’s medical record, with respect to a certain period of time. The result can then be used by the EHR system to manipulate 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.