A study of Chinese private passenger cars based on BP neural network

This study employs BP neural network to simulate the development of Chinese private passenger cars. Considering the uncertain and complex environment for the development of private passenger cars, indicators of economy, population, price, infrastructure, income, energy and some other fields which have major impacts on it are selected at first. The network is proved to be operable to simulate the progress of chinese private passenger cars after modeling, training and generalization test. Based on the BP neural network model, sensitivity analysis of each indicator is carried on and shows that the sensitivity coefficients of fuel price change suddenly. This special phenomenon reveals that the development of Chinese private passenger cars may be seriously affected by the recent high fuel price. This finding is also consistent with facts and figures

Environmental monitoring of airborne nanoparticles

The aim of this work was to review the existing instrumental methods to monitor airborne nanoparticle in different types of indoor and outdoor environments in order to detect their presence and to characterise their properties. Firstly the terminology and definitions used in this field are discussed, which is followed by a review of the methods to measure particle physical characteristics including number concentration, size distribution and surface area. An extensive discussion is provided on the direct methods for particle elemental composition measurements, as well as on indirect methods providing information on particle volatility and solubility, and thus in turn on volatile and semivolatile compounds of which the particle is composed. A brief summary of broader considerations related to nanoparticle monitoring in different environments concludes the paper.

Developing a rural land investment performance index for New Zealand

Agricultural production is one of the major industries in New Zealand and accounts for over 60% of all export trade. The farming industry comprises 70,000 entities ranging in size from small individual run farms to large corporate operations. The reliance of the New Zealand economy to the international rural sector has seen considerable volatility in the rural land markets over the past four decades, with significant shifts in rural land prices based on location, land use and underlying international rural commodity prices. With the increasing attention being paid to the rural sector, especially in relation to food production and bio-fuels, there has been an increasing corporate interest in rural land ownership in relatively low subsidised agricultural producing countries such as New Zealand and Australia. A factor that has limited this participation of institutional investors previously has been a lack of reliable and up-to-date investment performance data for this asset class. This paper is the initial starting phase in the development of a New Zealand South Island rural land investment performance index and covers the period 1990-2007. The research in this paper analyses all rural sales transactions in the South Island and develops a capital return index for rural property based on major rural property land use. Additional work on this index will cover both total return performance and geographic location.

A constructivist approach to media literacy education: The role of the library

An informed citizenry is essential to the effective functioning of democracy. In most modern liberal democracies, citizens have traditionally looked to the media as the primary source of information about socio-political matters. In our increasingly mediated world, it is critical that audiences be able to effectively and accurately use the media to meet their information needs. Media literacy, the ability to access, understand, evaluate and create media content is therefore a vital skill for a healthy democracy. The past three decades have seen the rapid expansion of the information environment, particularly through Internet technologies. It is obvious that media usage patterns have changed dramatically as a result. Blogs and websites are now popular sources of news and information, and are for some sections of the population likely to be the first, and possibly only, information source accessed when information is required. What are the implications for media literacy in such a diverse and changing information environment? The Alexandria Manifesto stresses the link between libraries, a well informed citizenry and effective governance, so how do these changes impact on libraries? This paper considers the role libraries can play in developing media literate communities, and explores the ways in which traditional media literacy training may be expanded to better equip citizens for new media technologies. Drawing on original empirical research, this paper highlights a key shortcoming of existing media literacy approaches: that of overlooking the importance of needs identification as an initial step in media selection. Self-awareness of one’s actual information need is not automatic, as can be witnessed daily at reference desks in libraries the world over. Citizens very often do not know what it is that they need when it comes to information. Without this knowledge, selecting the most appropriate information source from the vast range available becomes an uncertain, possibly even random, enterprise. Incorporating reference interview-type training into media literacy education, whereby the individual will develop the skills to interrogate themselves regarding their underlying information needs, will enhance media literacy approaches. This increased focus on the needs of the individual will also push media literacy education into a more constructivist methodology. The paper also stresses the importance of media literacy training for adults. Media literacy education received in school or even university cannot be expected to retain its relevance over time in our rapidly evolving information environment. Further, constructivist teaching approaches highlight the importance of context to the learning process, thus it may be more effective to offer media literacy education relating to news media use to adults, whilst school-based approaches focus on types of media more relevant to young people, such as entertainment media. Librarians are ideally placed to offer such community-based media literacy education for adults. They already understand, through their training and practice of the reference interview, how to identify underlying information needs. Further, libraries are placed within community contexts, where the everyday practice of media literacy occurs. The Alexandria Manifesto stresses the link between libraries, a well informed citizenry and effective governance. It is clear that libraries have a role to play in fostering media literacy within their communities.

"I'm thinking 'bout moving in"... An examination of the issues impacting on the recruitment of secondary school graduates to the library and information profession

In recent years concern has been expressed internationally about the future of the library and information services (LIS) profession: recruitment and retention, changing skill sets and declining numbers of people choosing librarianship as a career are all factors contributing to an uncertain future. One area yet explored in any depth is the topic of why LIS studies are not perceived, let alone promoted, as a good first professional qualification for high school graduates. This paper considers the professional literature that examines the uptake of librarianship as a first qualification by school leavers and discusses, in the context of the Australian library sector, the role of professional associations, library schools, National and State Libraries, as well as individual libraries and librarians. Examples of best practice are presented to highlight the opportunities for inspiring and motivating students through well structured and stimulating work experience programs. The topic is relevant to all librarians who are interested in the future of the LIS profession. It is argued that the focus of the present conference on ‘moving up’ and ‘moving on’ can only have real significance when the profession has a more complete understanding of the barriers to and the opportunities for ‘moving in’.

Visuacy, imagination, and engagement

Australia’s National Review of Visual Education (DEEWR, 2009) asserts the primacy of visual language ability, or ‘visuacy” in problem-solving. This paper reports on a recent university/schools research project with ‘at risk’ middle school students in which visuacy was promoted as a primary medium for obtaining data relating to issues of immediate concern to the students. Using a students-as-researchers approach, the project investigated middle school students’ perspectives on school engagement and disengagement. In this project, novice researchers used a variety of data gathering methods including photography, video interviews and drawn images as well as more traditional verbal methods, such as interviews, and quantitative methods, such as questionnaires. Engaging student imagination was a key focus of the approach taken by the project, acknowledging that student participants may be reluctant to enter dialogue with teachers and researchers on matters to which they have previously had little input. Students who have previously been marginalized and prevented from contributing their voices to educational forums often have difficulty in adjusting to the novelty of collaborative research with adults (Rudduck, 2003) and may be uncertain of their own place in the relationship that defines teacher/student interactions. It is argued that the project’s promotion of visuacy, alongside more traditional literacies and numeracy in education research, helped to overcome these concerns, engaged the imaginations of the student researchers, and provided a medium for the expression of the voices of marginalised young people.

National consumer credit laws, financial exclusion and interest rate caps : The case for diversity within a centralised framework

Australia is going through a major reform of consumer credit regulation, with the implementation of a proposal to transfer regulatory responsibility from the State and Territory Governments to the Commonwealth Government. While the broad policy approach is supported, the reform process has missed a significant opportunity to engage directly with issues of financial exclusion and with the potential role of regulation to reduce financial exclusion. The imposition of an interest rate cap can limit the impact of financial exclusion. However, the future of the existing interest rate caps is uncertain, given the diversity of approaches, and the heated debate that surrounds this issue. In the absence of support for regulatory initiatives to increase the availability of low cost, small loans, permitting regulatory diversity on this issue of interest rate caps, within an otherwise centralised regulatory framework., can minimise the impact of financial exclusion on consumers.

Urban network travel time estimation from stop-line loop detector data and signal controller data

This paper presents a model to estimate travel time using cumulative plots. Three different cases considered are i) case-Det, for only detector data; ii) case-DetSig, for detector data and signal controller data and iii) case-DetSigSFR: for detector data, signal controller data and saturation flow rate. The performance of the model for different detection intervals is evaluated. It is observed that detection interval is not critical if signal timings are available. Comparable accuracy can be obtained from larger detection interval with signal timings or from shorter detection interval without signal timings. The performance for case-DetSig and for case-DetSigSFR is consistent with accuracy generally more than 95% whereas, case-Det is highly sensitive to the signal phases in the detection interval and its performance is uncertain if detection interval is integral multiple of signal cycles.

Information security culture : a behaviour compliance conceptual framework

Understanding the complex dynamic and uncertain characteristics of organisational employees who perform authorised or unauthorised information security activities is deemed to be a very important and challenging task. This paper presents a conceptual framework for classifying and organising the characteristics of organisational subjects involved in these information security practices. Our framework expands the traditional Human Behaviour and the Social Environment perspectives used in social work by identifying how knowledge, skills and individual preferences work to influence individual and group practices with respect to information security management. The classification of concepts and characteristics in the framework arises from a review of recent literature and is underpinned by theoretical models that explain these concepts and characteristics. Further, based upon an exploratory study of three case organisations in Saudi Arabia involving extensive interviews with senior managers, department managers, IT managers, information security officers, and IT staff; this article describes observed information security practices and identifies several factors which appear to be particularly important in influencing information security behaviour. These factors include values associated with national and organisational culture and how they manifest in practice, and activities related to information security management.

Improved detection and tracking of objects in surveillance video

Surveillance networks are typically monitored by a few people, viewing several monitors displaying the camera feeds. It is then very difficult for a human operator to effectively detect events as they happen. Recently, computer vision research has begun to address ways to automatically process some of this data, to assist human operators. Object tracking, event recognition, crowd analysis and human identification at a distance are being pursued as a means to aid human operators and improve the security of areas such as transport hubs. The task of object tracking is key to the effective use of more advanced technologies. To recognize an event people and objects must be tracked. Tracking also enhances the performance of tasks such as crowd analysis or human identification. Before an object can be tracked, it must be detected. Motion segmentation techniques, widely employed in tracking systems, produce a binary image in which objects can be located. However, these techniques are prone to errors caused by shadows and lighting changes. Detection routines often fail, either due to erroneous motion caused by noise and lighting effects, or due to the detection routines being unable to split occluded regions into their component objects. Particle filters can be used as a self contained tracking system, and make it unnecessary for the task of detection to be carried out separately except for an initial (often manual) detection to initialise the filter. Particle filters use one or more extracted features to evaluate the likelihood of an object existing at a given point each frame. Such systems however do not easily allow for multiple objects to be tracked robustly, and do not explicitly maintain the identity of tracked objects. This dissertation investigates improvements to the performance of object tracking algorithms through improved motion segmentation and the use of a particle filter. A novel hybrid motion segmentation / optical flow algorithm, capable of simultaneously extracting multiple layers of foreground and optical flow in surveillance video frames is proposed. The algorithm is shown to perform well in the presence of adverse lighting conditions, and the optical flow is capable of extracting a moving object. The proposed algorithm is integrated within a tracking system and evaluated using the ETISEO (Evaluation du Traitement et de lInterpretation de Sequences vidEO - Evaluation for video understanding) database, and significant improvement in detection and tracking performance is demonstrated when compared to a baseline system. A Scalable Condensation Filter (SCF), a particle filter designed to work within an existing tracking system, is also developed. The creation and deletion of modes and maintenance of identity is handled by the underlying tracking system; and the tracking system is able to benefit from the improved performance in uncertain conditions arising from occlusion and noise provided by a particle filter. The system is evaluated using the ETISEO database. The dissertation then investigates fusion schemes for multi-spectral tracking systems. Four fusion schemes for combining a thermal and visual colour modality are evaluated using the OTCBVS (Object Tracking and Classification in and Beyond the Visible Spectrum) database. It is shown that a middle fusion scheme yields the best results and demonstrates a significant improvement in performance when compared to a system using either mode individually. Findings from the thesis contribute to improve the performance of semi-automated video processing and therefore improve security in areas under surveillance.

Applying data mining to assess crash risk on curves

The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.

The moment of exchange : risk, vulnerability, responsibility

Any cycle of production and exchange – be it economic, cultural or aesthetic – involves an element of risk. It involves uncertainty, unpredictability, and a potential for new insight and innovation (the boom) as well as blockages, crises and breakdown (the bust). In performance, the risks are plentiful – economic, political, social, physical and psychological. The risks people are willing to take depend on their position in the exchange (performer, producer, venue manager or spectator), and their aesthetic preferences. This paper considers the often uncertain, confronting or ‘risky’ moment of exchange between performer, spectator and culture in Live Art practices. Encompassing body art, autobiographical art, site-specific art and other sorts of performative intervention in the public sphere, Live Art eschews the artifice of theatre, breaking down barriers between art and life, artist and spectator, to speak back to the public sphere, and challenge assumptions about bodies, identities, memories, relationships and histories. In the process, Live Art frequently privileges an uncertain, confrontational or ‘risky’ mode of exchange between performer, spectator and culture, as a way of challenging power structures. This paper examines the moment of exchange in terms of risk, vulnerability, responsibility and ethics. Why the romance with ‘risky’ behaviours and exchanges? Who is really taking a risk? What risk? With whose permission (or lack thereof)? What potential does a ‘risky’ exchange hold to destabilise aesthetic, social or political norms? Where lies the fine line between subversive intervention in the public sphere and sheer self-indulgence? What are the social and ethical implications of a moment of exchange that puts bodies, beliefs or social boundaries at ‘risk’? In this paper, these questions are addressed with reference to historical and contemporary practices under the broadly defined banner of Live Art, from the early work of Abrovamic and Burden, through to contemporary Australian practitioners like Fiona McGregor.

Decision support system for contractor pre-qualification : artificial neural network model

The selection criteria for contractor pre-qualification are characterized by the co-existence of both quantitative and qualitative data. The qualitative data is non-linear, uncertain and imprecise. An ideal decision support system for contractor pre-qualification should have the ability of handling both quantitative and qualitative data, and of mapping the complicated nonlinear relationship of the selection criteria, such that rational and consistent decisions can be made. In this research paper, an artificial neural network model was developed to assist public clients identifying suitable contractors for tendering. The pre-qualification criteria (variables) were identified for the model. One hundred and twelve real pre-qualification cases were collected from civil engineering projects in Hong Kong, and eighty-eight hypothetical pre-qualification cases were also generated according to the “If-then” rules used by professionals in the pre-qualification process. The results of the analysis totally comply with current practice (public developers in Hong Kong). Each pre-qualification case consisted of input ratings for candidate contractors’ attributes and their corresponding pre-qualification decisions. The training of the neural network model was accomplished by using the developed program, in which a conjugate gradient descent algorithm was incorporated for improving the learning performance of the network. Cross-validation was applied to estimate the generalization errors based on the “re-sampling” of training pairs. The case studies show that the artificial neural network model is suitable for mapping the complicated nonlinear relationship between contractors’ attributes and their corresponding pre-qualification (disqualification) decisions. The artificial neural network model can be concluded as an ideal alternative for performing the contractor pre-qualification task.

A robust reactive scheduling model for intensive care units

The ICU is an integral part of any hospital and is under great load from patient arrivals as well as resource limitations. Scheduling of patients in the ICU is complicated by the two general types; elective surgery and emergency arrivals. This complicated situation is handled by creating a tentative initial schedule and then reacting to uncertain arrivals as they occur. For most hospitals there is little or no flexibility in the number of beds that are available for use now or in the future. We propose an integer programming model to handle a parallel machine reacting system for scheduled and unscheduled arrivals.

The importance of a new kind of learning in collaborative networks

There is wide agreement that in order to manage the increasingly complex and uncertain tasks of business, government and community, organizations can no longer operate in supreme isolation, but must develop a more networked approach. Networks are not ‘business as usual’. Of particular note is what has been referred to as collaborative networks. Collaborative networks now constitute a significant part of our institutional infrastructure. A key driver for the proliferation of these multiorganizational arrangements is their ability to facilitate the learning and knowledge necessary to survive or to respond to increasingly complex social issues In this regard the emphasis is on the importance of learning in networks. Learning applies to networks in two different ways. These refer to the kinds of learning that occur as part of the interactive processes of networks. This paper looks at the importance of these two kinds of learning in collaborative networks. The first kind of learning relates to networks as learning networks or communities of practice. In learning networks people exchange ideas with each other and bring back this new knowledge for use in their own organizations. The second type of learning is referred to as network learning. Network learning refers to how people in collaborative networks learn new ways of communicating and behaving with each other. Network learning has been described as transformational in terms of leading to major systems changes and innovation. In order to be effective, all networks need to be involved as learning networks; however, collaborative networks must also be involved in network learning to be effective. In addition to these two kinds of learning in collaborative networks this paper also focuses on the importance of how we learn about collaborative networks. Maximizing the benefits of working through collaborative networks is dependent on understanding their unique characteristics and how this impacts on their operation. This requires a new look at how we specifically teach about collaborative networks and how this is similar to and/or different from how we currently teach about interorgnizational relations.