Management and organisational barriers in the acquisition of computer usage skills by mature age workers

Aim: To investigate workplace cultures in the acquisition of computer usage skills by mature age workers. Methods: Data were gathered through focus groups conducted at job network centres in the Greater Brisbane metropolitan region. Participants who took part were a mixture of workers and job-seekers. Results: The results suggest that mature age workers can be exposed to inappropriate computer training practices and age-insensitive attitudes towards those with low base computer skills. Conclusions: There is a need for managers to be observant of ageist attitudes in the work place and to develop age-sensitive strategies to help mature age workers learn computer usage skills. Mature age workers also need to develop skills in ways which are practical and meaningful to their work.

Human resource management and innovation: what are knowledge-intensive firms doing?

An undeniable shift in focus from traditional production companies to Knowledge-Intensive Firms (KIFs) poses challenges for academics and practioners alike. In particular, effective management of an organization's human resources has become a critical issue for ensuring sustained innovation capacity. The relationship between Human Resource Management (HRM) in KIFs is however still a largely unexplored arena. The objective of this paper is to explore this relationship in an effort to identify HRM practices that support innovation. To this end, the paper includes reviews of the literature relevant to HRM and innovation in KIFs and four case studies from companies in Denmark and Australia that have been recognized for excellence in innovation. On the basis of content analyses conducted on the case data, some preliminary conclusions are posited regarding the role of HRM in KIFs. More specifically, the findings from this study suggest that while there are commonalities between HRM practices in traditional manufacturing companies and KIFs, there are also important differences, especially in terms of staffing practices. The paper contributes by offering recommendations for management of HRM in innovative KIFs and potential avenues for research to further develop our understanding of how HRM can support innovation in KIFs.

Succession management as a knowledge management strategy

One of the most critical issues for building innovation capacity in organisations is the acquisition and maintenance of knowledge. As knowledge is the basis of human capital, then the ability to attract, retain and engage talent is argued to be an important element of innovation. By attracting and retaining good staff, the organisation is retaining organisational knowledge which is necessary particularly for exploitation of current capabilities, but will also contribute to capacity for exploration for future innovation. This paper addresses the importance of retaining and developing staff as a critical issue for knowledge management and addresses the issue of retaining talent through effective succession management practices. The findings from an exploratory study into current practices in the Australian rail sector, provides further insight into the potentially critical issues for the effective use of succession management as a knowledge management and employee retention tool for building innovation capacity.

A forward and backward secure key management in wireless sensor networks for PCS/SCADA

Process Control Systems (PCSs) or Supervisory Control and Data Acquisition (SCADA) systems have recently been added to the already wide collection of wireless sensor networks applications. The PCS/SCADA environment is somewhat more amenable to the use of heavy cryptographic mechanisms such as public key cryptography than other sensor application environments. The sensor nodes in the environment, however, are still open to devastating attacks such as node capture, which makes designing a secure key management challenging. In this paper, a key management scheme is proposed to defeat node capture attack by offering both forward and backward secrecies. Our scheme overcomes the pitfalls which Nilsson et al.'s scheme suffers from, and is not more expensive than their scheme.

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.

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

The interrelations among the project team’s conduit networks, knowledge network and its performance

From the perspective of network, a project team’s social capital consists of conduits network, and resource exchange network. Prior research intensively studies the effect of the structure of conduits network on the team’s performance, assuming knowledge transfer is the causal mechanism linking conduits network to performance. This paper attempts to explore the interrelations between conduits network and knowledge network, and further distinguish the different influence between various conduit networks, and hypothesizes that a project team’s knowledge network mediates the effect of various conduit networks on the team’s performance. This research can enrich our knowledge of disparate influence of the various conduit networks on knowledge transfer, and imply some management practices to enhance the organization’s social capital, and hence improve the organization’s performance.

The role of land use and psycho-social factors in high density residents' work travel mode choices : implications for sustainable transport policy

Imperatives to improve the sustainability of cities often hinge upon plans to increase urban residential density to facilitate greater reliance on sustainable forms of transport and minimise car use. However there is ongoing debate about whether high residential density land use in isolation results in sustainable transport outcomes. Findings from surveys with residents of inner-urban high density dwellings in Brisbane, Australia, suggest that solo car travel accounts for the greatest modal share of typical work journeys and attitudes toward dwelling and neighbourhood transport-related features, residential sorting factors and socio-demographics, alongside land use such as public transport availability, are significantly associated with work travel mode choice. We discuss the implications of our findings for transport policy and management including encouraging relatively sustainable intermodal forms of transport for work journeys.

Non-motorized public transport development : present scenario and future approach in developing cities

Over the last few decades, most large cities in the developing world have been experiencing rapid and imbalanced transport sector development resulting in severe congestion and poor levels of service. The most common response at a policy level under this circumstance has been to focus on private and public motorized transport modes, and especially on traffic control measures and mass transit systems. Despite their major role in the overall transport system in many developing cities in Asia & Latin America, relatively little attention is given to non-motorized transport (NMT) modes (walk, bicycle and cycle-rickshaw). In particular, this ideology is applicable to the paid category of non-motorized public transport (NMPT), notably three-wheeler cycle rickshaws that still have an important socio-economic, environmental and trip-making role in many developing cities. Despite, they are often seen as inefficient and backward; an impediment to progress; and inconsistent with modern urban image. Policy measures therefore, to restrict or eliminate non-motorized transport from urban arterials and other feeder networks have been implemented in cities as diverse as Dhaka, Delhi, Karachi, Bangkok, Jakarta, Manila, Surabaya and Beijing . This paper will primarily investigate the key contribution of NMPT in the sustainable transport system and urban fabric of developing cities, with Dhaka as case study. The paper will also highlight in detail the impediments towards NMPT development and provide introductory concept on possible role this mode is expected to play into the future of these cities

AITPM Email Newsletter Volume 0905, May 2009: Presidents Message

President’s Message Hello fellow AITPM members, We’ve been offered a lot of press lately about the Federal Government’s plan for the multibillion dollar rollout of its high speed broadband network, which at the moment is being rated to a speed of 100Mb/s. This seems fantastic in comparison to the not atypical 250 to 500kb/s that I receive on my metropolitan cable broadband, which incidentally my service provider rates at theoretical speeds of up to 8 Mb/s. I have no doubt that such a scheme will generate significant advantages to business and consumers. However, I also have some reservations. Only a few of years ago I marvelled at my first 256Mb USB stick, which cost my employer about $90. Last month I purchased a 16Gb stick with a free computer carry bag for $80, which on the back of my envelope has given me about 72 times the value of my first USB stick not including the carry bag! I am pretty sure the technology industry will find a way to eventually push a lot more than 100Mb/s down the optic fibre network just as they have done with pushing several Mb/s ADSL2 down antique copper wire. This makes me wonder about the general problem of inbuilt obsolescence of all things high-tech due to rapid advances in the tech industry. As a transport professional I then think to myself that our industry has been moving forward at somewhat of a slower pace. We certainly have had major milestones having significant impacts, such as the move from horse and cart to the self propelled motor vehicle, sealing and formal geometric design of roads, development of motorways, signalisation of intersections, coordination of networks, to simulation modelling for real time adaptive control (perhaps major change has been at a frequency of 30 years or so?). But now with ITS truly penetrating the transport market, largely thanks to the in-car GPS navigator, smart phone, e-toll and e-ticket, I believe that to avoid our own obsolescence we’re going to need to “plan for ITS” rather than just what we seem to have been doing up until now, that is, to get it out there. And we’ll likely need to do it at a faster pace. It will involve understanding how to data mine enormous data sets, better understanding the human/machine interface, keeping pace with automotive technology more closely, resolving the ethical and privacy chestnuts, and in the main actually planning for ITS to make peoples’ lives easier rather than harder. And in amongst this we’ll need to keep pace with the types of technology advances similar to my USB stick example above. All the while we’ll be making a brand new set of friends in the disciplines that will morph into ITS along with us. Hopefully these will all be “good” problems for our profession to have. I should close in reminding everyone again that AITPM’s flagship event, the 2009 AITPM National Conference, Traffic Beyond Tomorrow, is being held in Adelaide from 5 to 7 August. www.aitpm.com has all of the details about how to register, sponsor a booth, session, etc. Best regards all, Jon Bunker

A framework for network RTK data processing based on grid computing

Real-Time Kinematic (RTK) positioning is a technique used to provide precise positioning services at centimetre accuracy level in the context of Global Navigation Satellite Systems (GNSS). While a Network-based RTK (N-RTK) system involves multiple continuously operating reference stations (CORS), the simplest form of a NRTK system is a single-base RTK. In Australia there are several NRTK services operating in different states and over 1000 single-base RTK systems to support precise positioning applications for surveying, mining, agriculture, and civil construction in regional areas. Additionally, future generation GNSS constellations, including modernised GPS, Galileo, GLONASS, and Compass, with multiple frequencies have been either developed or will become fully operational in the next decade. A trend of future development of RTK systems is to make use of various isolated operating network and single-base RTK systems and multiple GNSS constellations for extended service coverage and improved performance. Several computational challenges have been identified for future NRTK services including: • Multiple GNSS constellations and multiple frequencies • Large scale, wide area NRTK services with a network of networks • Complex computation algorithms and processes • Greater part of positioning processes shifting from user end to network centre with the ability to cope with hundreds of simultaneous users’ requests (reverse RTK) There are two major requirements for NRTK data processing based on the four challenges faced by future NRTK systems, expandable computing power and scalable data sharing/transferring capability. This research explores new approaches to address these future NRTK challenges and requirements using the Grid Computing facility, in particular for large data processing burdens and complex computation algorithms. A Grid Computing based NRTK framework is proposed in this research, which is a layered framework consisting of: 1) Client layer with the form of Grid portal; 2) Service layer; 3) Execution layer. The user’s request is passed through these layers, and scheduled to different Grid nodes in the network infrastructure. A proof-of-concept demonstration for the proposed framework is performed in a five-node Grid environment at QUT and also Grid Australia. The Networked Transport of RTCM via Internet Protocol (Ntrip) open source software is adopted to download real-time RTCM data from multiple reference stations through the Internet, followed by job scheduling and simplified RTK computing. The system performance has been analysed and the results have preliminarily demonstrated the concepts and functionality of the new NRTK framework based on Grid Computing, whilst some aspects of the performance of the system are yet to be improved in future work.

The future of cognitive and behavioral therapies in the prevention and early management of psychosis : opportunities and risks

Behavioral and cognitive interventions for people with psychosis have a long and distinguished history, although the evidence for their application to young people remains limited. We anticipate that the next decades will show substantial research into psychological intervention for this population. Important targets will include the management of environmental stressors, reduction of substance misuse, and promotion of early treatment. Psychological management of positive symptoms, depression, and suicidal behavior will continue to be critical objectives. Important secondary prevention goals will be the retention of cognitive functioning, vocational options, social skills, and social network support, including appropriate family support. We expect primary prevention to include both universal programs and interventions for adolescents at particularly high risk. Technical innovations will include increasing use of Internet-based intervention and behavior cueing devices. Pressures for intervention brevity will continue, as will problems with the systematic delivery of effective procedures.

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.

A fuzzy neural network approach for contractor pre-qualification

Nonlinearity, uncertainty and subjectivity are the three predominant characteristics of contractors prequalification which cause the process more of an art than a scientific evaluation. A fuzzy neural network (FNN) model, amalgamating both the fuzzy set and neural network theories, has been developed aiming to improve the objectiveness of contractor prequalification. Through the FNN theory, the fuzzy rules as used by the prequalifiers can be identified and the corresponding membership functions can be transformed. Eighty-five cases with detailed decision criteria and rules for prequalifying Hong Kong civil engineering contractors were collected. These cases were used for training (calibrating) and testing the FNN model. The performance of the FNN model was compared with the original results produced by the prequalifiers and those generated by the general feedforward neural network (GFNN, i.e. a crisp neural network) approach. Contractor’s ranking orders, the model efficiency (R2) and the mean absolute percentage error (MAPE) were examined during the testing phase. These results indicate the applicability of the neural network approach for contractor prequalification and the benefits of the FNN model over the GFNN model. The FNN is a practical approach for modelling contractor prequalification.

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.