Human rights performance disclosure by companies having operations in high risk countries: Evidence from Australian mineral sector

The aim of this study is to explore whether Australian mineral companies operating in high human rights risk countries provide more human rights disclosures than companies operating in low risk countries. A content analysis instrument containing 88 specific human rights performance items derived from a number of international human rights guidelines has been developed to investigate the annual reports, social responsibility reports and corporate websites of the top 50 Australian mineral companies (2010/2011). The findings show that human rights performance disclosures by companies with operations in high human rights risk countries are significantly higher than companies with operations in the low risk countries. By disclosing extended human rights performance information, companies operating in high risk countries appear to ease community concerns about human rights violations. The finding is consistent with legitimacy theory which posits that organisations respond to community concerns in relation to particular social issues.

MAC design for heterogeneous application support in OFDM based wireless systems

With the increasing adoption of wireless technology, it is reasonable to expect an increase in file demand for supporting both real-time multimedia and high rate reliable data services. Next generation wireless systems employ Orthogonal Frequency Division Multiplexing (OFDM) physical layer owing, to the high data rate transmissions that are possible without increase in bandwidth. Towards improving file performance of these systems, we look at the design of resource allocation algorithms at medium-access layer, and their impact on higher layers. While TCP-based clastic traffic needs reliable transport, UDP-based real-time applications have stringent delay and rate requirements. The MAC algorithms while catering to the heterogeneous service needs of these higher layers, tradeoff between maximizing the system capacity and providing fairness among users. The novelly of this work is the proposal of various channel-aware resource allocation algorithms at the MAC layer. which call result in significant performance gains in an OFDM based wireless system.

OCR Prediction Using Support Vector Machine Based on Piezocone Data

The determination of the overconsolidation ratio (OCR) of clay deposits is an important task in geotechnical engineering practice. This paper examines the potential of a support vector machine (SVM) for predicting the OCR of clays from piezocone penetration test data. SVM is a statistical learning theory based on a structural risk minimization principle that minimizes both error and weight terms. The five input variables used for the SVM model for prediction of OCR are the corrected cone resistance (qt), vertical total stress (sigmav), hydrostatic pore pressure (u0), pore pressure at the cone tip (u1), and the pore pressure just above the cone base (u2). Sensitivity analysis has been performed to investigate the relative importance of each of the input parameters. From the sensitivity analysis, it is clear that qt=primary in situ data influenced by OCR followed by sigmav, u0, u2, and u1. Comparison between SVM and some of the traditional interpretation methods is also presented. The results of this study have shown that the SVM approach has the potential to be a practical tool for determination of OCR.

Water management capacity building to support rapidly developing mining economies

Many developing countries are experiencing rapid expansion in mining with associated water impacts. In most cases mining expansion is outpacing the building of national capacity to ensure that sustainable water management practices are implemented. Since 2011, Australia's International Mining for Development Centre (IM4DC) has funded capacity building in such countries including a program of water projects. Five projects in particular (principally covering experiences from Peru, Colombia, Ghana, Zambia, Indonesia, Philippines and Mongolia) have provided insight into water capacity building priorities and opportunities. This paper reviews the challenges faced by water stakeholders, and proposes the associated capacity needs. The paper uses the evidence derived from the IM4DC projects to develop a set of specific capacity-building recommendations. Recommendations include: the incorporation of mine water management in engineering and environmental undergraduate courses; secondments of staff to suitable partner organisations; training to allow site staff to effectively monitor water including community impacts; leadership training to support a water stewardship culture; training of officials to support implementation of catchment management approaches; and the empowerment of communities to recognise and negotiate solutions to mine-related risks. New initiatives to fund the transfer of multi-disciplinary knowledge from nations with well-developed water management practices are called for.

HealthMap: A cluster randomised trial of interactive health plans and self-management support to prevent coronary heart disease in people with HIV

Background The leading causes of morbidity and mortality for people in high-income countries living with HIV are now non-AIDS malignancies, cardiovascular disease and other non-communicable diseases associated with ageing. This protocol describes the trial of HealthMap, a model of care for people with HIV (PWHIV) that includes use of an interactive shared health record and self-management support. The aims of the HealthMap trial are to evaluate engagement of PWHIV and healthcare providers with the model, and its effectiveness for reducing coronary heart disease risk, enhancing self-management, and improving mental health and quality of life of PWHIV. Methods/Design The study is a two-arm cluster randomised trial involving HIV clinical sites in several states in Australia. Doctors will be randomised to the HealthMap model (immediate arm) or to proceed with usual care (deferred arm). People with HIV whose doctors are randomised to the immediate arm receive 1) new opportunities to discuss their health status and goals with their HIV doctor using a HealthMap shared health record; 2) access to their own health record from home; 3) access to health coaching delivered by telephone and online; and 4) access to a peer moderated online group chat programme. Data will be collected from participating PWHIV (n = 710) at baseline, 6 months, and 12 months and from participating doctors (n = 60) at baseline and 12 months. The control arm will be offered the HealthMap intervention at the end of the trial. The primary study outcomes, measured at 12 months, are 1) 10-year risk of non-fatal acute myocardial infarction or coronary heart disease death as estimated by a Framingham Heart Study risk equation; and 2) Positive and Active Engagement in Life Scale from the Health Education Impact Questionnaire (heiQ). Discussion The study will determine the viability and utility of a novel technology-supported model of care for maintaining the health and wellbeing of people with HIV. If shown to be effective, the HealthMap model may provide a generalisable, scalable and sustainable system for supporting the care needs of people with HIV, addressing issues of equity of access. Trial registration Universal Trial Number (UTN) U111111506489; ClinicalTrial.gov Id NCT02178930 submitted 29 June 2014

Support vector machine applied to settlement of shallow foundations on cohesionless soils

The determination of settlement of shallow foundations on cohesionless soil is an important task in geotechnical engineering. Available methods for the determination of settlement are not reliable. In this study, the support vector machine (SVM), a novel type of learning algorithm based on statistical theory, has been used to predict the settlement of shallow foundations on cohesionless soil. SVM uses a regression technique by introducing an ε – insensitive loss function. A thorough sensitive analysis has been made to ascertain which parameters are having maximum influence on settlement. The study shows that SVM has the potential to be a useful and practical tool for prediction of settlement of shallow foundation on cohesionless soil.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Is it the economy, stupid? The role of social versus economic factors in people’s support for hosting the Olympic Games: Evidence from 12 democratic countries

Public referenda have gained momentum as a democratic tool to legitimize public mega projects such as hosting the Olympic Games. Interest groups in favour of hosting the Olympics therefore try to influence voters through public campaigns that primarily focus on economic benefits. However, recent studies find no or hardly any economic impact of hosting the Olympics, instead providing evidence for a positive social impact. This raises the question whether citizens consider economic or social factors when deciding on hosting the Olympics. Based on representative survey data from 12 countries, our results suggest that economic factors can influence voting behaviour, although the influence of social factors is stronger.

Mixed pixel analysis for flood mapping using extended support vector machine

This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

Teacher peer support in social network sites

This paper describes the types of support that teachers are accessing through the Social Network Site (SNS) 'Facebook'. It describes six ways in which teachers support one another within online groups. It presents evidence from a study of a large, open group of teachers online over a twelve week period, repeated with multiple groups a year later over a one week period. The findings suggest that large open groups in SNSs can be a useful source of pragmatic advice for teachers but that these groups are rarely a place for reflection on or feedback about teaching practice.

Australian fly-in, fly-out operations: Impacts on communities, safety workers and their families

Background Australia’s mineral, resource and infrastructure sectors continues to expand as operations in rural and remote locations increasingly rely on fly-in, fly-out or drive-in, drive-out workforces in order to become economically competitive. The issues in employing these workforces are becoming more apparent and include a range of physical, mental, psychosocial, safety and community challenges. Objectives This review aims to consolidate a range of research conducted to communicate potential challenges for industry in relation to a wide variety of issues when engaging and using FIFO/DIDO workforces which includes roster design, working hours, fatigue, safety performance, employee wellbeing, turnover, psychosocial relationships and community concerns. Methods A wide literature review was performed using EBSCOhost and Google Scholar, with a focus on FIFO or DIDO workforces engaged within the resources sector. Results A number of existing gaps in the management of FIFO workforces and potential for future research were identified. This included the identification of various roster designs and hours worked across the resources industry and how to best understand the influences of roster swings, and work hours on fatigue, safety, psychological wellbeing and job satisfaction. Fatigue management, particularly in relation to travelling after extended work shifts can increase the risk for road safety and influence safety performance while at work due to a culmination of long hours, roster cycle and accumulated sleep debt. Further challenges associated with the engagement of this workforce include feelings of isolation, physiological and general health and lifestyle concerns. Conclusions FIFO workforces appear to be at an increased risk physically and mentally due to a wide range of influences of this unique lifestyle, particularly in relation to rosters, length of shift and feelings of community disengagement. Research and data collected has been limited in understanding the influences on employee engagement, satisfaction, retention and safety. Ensuring the challenges associated with FIFO employment are understood, addressed and communicated to workers and their families may assist.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Kantoaalto koulutuksesta työyhteisön viestintäosaamiseen : lyhytkestoisen viestintäkoulutuksen vaikuttavuuden avaintekijät

The purpose of this research is to examine whether short-term communication training can have an impact on the improvement of communication capacity of working communities, and what are prerequisites for the creation of such capacity. Subjects of this research were short-term communication trainings aimed at the managerial and expert levels of enterprises and communities. The research endeavors to find out how communication trainings with an impact should be devised and implemented, and what this requires from the client and provider of the training service. The research data is mostly comprised of quantitative feed-back collected at the end of a training day, as well as delayed interviews. The evaluations have been based on a stakeholder approach, and those concerned were participants to the trainings, clients having commissioned the trainings and communication trainers. The principal method of the qualitative analysis is that of a data-driven content analysis. Two research instruments have been constructed for the analysis and for the presentation of the results: an evaluation circle for the purposes of a holistic evaluation and a development matrix for the structuring of an effective training. The core concept of the matrix is a carrier wave effect, which is needed to carry the abstractions from the training into concrete functions in the everyday life. The relevance of the results has been tested in a pilot organization. The immediate assessment and delayed evaluations gave a very differing picture of the trainings. The immediate feedback was of nearly commendable level, but the effects carried forward into the everyday situations of the working community were small and that the learning rarely was applied into practice. A training session that receives good feedback does not automatically result in the development of individual competence, let alone that of the community. The results show that even short-term communication training can promote communication competence that eventually changes the working culture on an organizational level, provided that the training is designed into a process and that the connections into the participants’ work are ensured. It is essential that all eight elements of the carrier wave effect are taken into account. The entire purchaser-provider -process must function while not omitting the contribution of the participants themselves. The research illustrates the so called bow tie -model of an effective communication training based on the carrier wave effect. Testing the results in pilot trainings showed that a rather small change in the training approach may have a signi¬ficant effect on the outcome of the training as well as those effects that are carried on into the working community. The evaluation circle proved to be a useful tool, which can be used while planning, executing and evaluating training in practice. The development matrix works as a tool for those producing the training service, those using the service as well as those deciding on the purchase of the service in planning and evaluating training that sustainably improves communication capacity. Thus the evaluation circle also works to support and ensure the long-term effects of short-term trainings. In addition to communication trainings, the tools developed for this research are useable for many such needs, where an organization is looking to improve its operations and profitability through training.

Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.

Quality of support for multicasting over mobile ad-hoc networks

An ad hoc network is composed of mobile nodes without any infrastructure. Recent trends in applications of mobile ad hoc networks rely on increased group oriented services. Hence multicast support is critical for ad hoc networks. We also need to provide service differentiation schemes for different group of users. An efficient application layer multicast (APPMULTICAST) solution suitable for low mobility applications in MANET environment has been proposed in [10]. In this paper, we present an improved application layer multicast solution suitable for medium mobility applications in MANET environment. We define multicast groups with low priority and high priority and incorporate a two level service differentiation scheme. We use network layer support to build the overlay topology closer to the actual network topology. We try to maximize Packet Delivery Ratio. Through simulations we show that the control overhead for our algorithm is within acceptable limit and it achieves acceptable Packet Delivery Ratio for medium mobility applications.