Sensor-cloud computing : novel applications and research problems

Recent developments in sensor networks and cloud computing saw the emergence of a new platform called sensor-clouds. While the proposition of such a platform is to virtualise the management of physical sensor devices, we are seeing novel applications been created based on a new class of social sensors. Social sensors are effectively a human-device combination that sends torrent of data as a result of social interactions and social events. The data generated appear in different formats such as photographs, videos and short text messages. Unlike other sensor devices, social sensors operate on the control of individuals via their mobile devices such as a phone or a laptop. And unlike other sensors that generate data at a constant rate or format, social sensors generate data that are spurious and varied, often in response to events as individual as a dinner outing, or a news announcement of interests to the public. This collective presence of social data creates opportunities for novel applications never experienced before. This paper discusses such applications as a result of utilising social sensors within a sensor-cloud environment. Consequently, the associated research problems are also presented.

Working at the nexus between public health policy, practice and research : dynamics of knowledge sharing in the Netherlands

Background
Joining the domains of practice, research and policy is an important aspect of boosting the quality performance required to tackle complex public health problems. “Joining domains” implies a departure from the linear and technocratic knowledge-translation approach. Integrating the practice, research and policy triangle means knowing its elements, appreciating the barriers, identifying possible cooperation strategies and studying strategy effectiveness under specified conditions.
This article examines the dynamic process of developing an Academic Collaborative Centre for Public Health in the Netherlands, with the objective of achieving that the three domains of policy, practice and research become working partners on an equal footing.
Method
An interpretative hermeneutic approach was used to interpret the phenomenon of collaboration at the nexus between the three domains. The project was explicitly grounded in current organizational culture and routines, applied to nexus action. In the process of examination, we used both quantitative (e.g. records) and qualitative data (e.g., interviews and observations). The data were interpreted using the Actor-Network, Institutional Re-Design and Blurring the Boundaries theories.
Results
Results show commitment at strategic level. At the tactical level, however, managers were inclined to prioritize daily routine, while the policy domain remained absent. At the operational level, practitioners learned to do PhD research in real-life practice and researchers became acquainted with problems of practice and policy, resulting in new research initiatives.
Conclusion
We conclude that working at the nexus is an ongoing process of formation and reformation. Strategies based on Institutional Re-Design theories in particular might help to more actively stimulate managers’ involvement to establish mutually supportive networks.

Virtual design studio via social networks

With the advent of social networks, it became apparent that the social aspect of designing and learning plays a crucial role in students’ education. The ease of communication, leadership opportunity, democratic interaction, teamwork, and the sense of community are some of the aspects that are now in the centre of design interaction. Online interactions, multimedia, mobile computing and face-to-face learning create blended learning environments to which some Virtual Design Studios (VDS) have reacted. On the sample of a design studio at Deakin University the paper discusses details of the Social Network VDS, its pedagogical implications to PBL, and presents how it is successful in empowering architectural students to collaborate and communicate design proposals that integrate a variety of skills, deep learning, and construction of knowledge. It studies the effectiveness of the generated social intelligence and explores the facilitation of students’ self-directed learning. Hereby the paper studies the construction of knowledge via social interaction and how blended learning environments foster motivation and information exchange.

Lessons from large-scale conservation networks in Australia

Australia has seen a rapid growth in the establishment of networks of lands managed for connectivity conservation across tenures, at landscape and sub-continental scales. Such networks go under a variety of names, including biosphere reserves, biolinks, wildlife corridors and conservation management networks. Their establishment has varied from state government-led initiatives to those initiated by non-government organizations and interested landholders. We surveyed existing major landscape scale conservation initiatives for successes, failures and future directions and synthesized common themes. These themes included scale, importance of social and economic networks, leadership, governance, funding, conservation planning, the role of protected areas and communication. We discuss the emergence of national policy relating to National Wildlife Corridors in Australia and the relationship of this policy to the long standing commitment to build a comprehensive, adequate and representative National Reserve System. Finally we outline areas for further research for connectivity conservation projects in Australia.

Prediction intervals for electricity load forecasting using neural networks

Most of the research in time series is concerned with point forecasting. In this paper we focus on interval forecasting and its application for electricity load prediction. We extend the LUBE method, a neural network-based method for computing prediction intervals. The extended method, called LUBEX, includes an advanced feature selector and an ensemble of neural networks. Its performance is evaluated using Australian electricity load data for one year. The results showed that LUBEX is able to generate high quality prediction intervals, using a very small number of previous lag variables and having acceptable training time requirements. The use of ensemble is shown to be critical for the accuracy of the results.

Clinical translation of the research article titled "The influence of early drinking contexts on current drinking among adult lesbian and bisexual women"

The article reported on a questionnaire-based study of 94 lesbian and 51 bisexual women that investigated the relationship between current drinking and early alcohol drinking patterns associated with coming out and a variety of social networks. The findings were that there was a “more permissive drinking culture” among lesbian and bisexual women than among heterosexual women. Furthermore, the more exposed women were to this culture through socializing in lesbian/bisexual networks during coming out, the more likely they were to drink heavily later in life. There were no differences in early drinking patterns of bisexual compared with lesbian women. One of the central hypotheses of the study that an earlier age at coming out would increase current problem drinking was not borne out.

Factors affecting SME owner-managers' willingness to share knowledge online in rural local business networks

This article integrates typically separate SME research on e-commerce, business networking, and knowledge management into a model explaining factors influencing the willingness of SME owner-managers to share knowledge online in business networks in rural districts. This is important because e-commerce can assist owner-managers, often dispersed in rural districts, to share knowledge between face-to-face networking events. The main factors associated with willingness to share knowledge online were their willingness to share knowledge face-to-face and their intensity of Internet use. Entrepreneurial factors such as owner-managers' expectations of rapid growth, trading outside the district, and seeking information about customers/competitors were indirectly associated with online sharing via intensity of Internet use only. The model suggests network coordinators could encourage online knowledge sharing by assisting owner-managers to see the business value of e-commerce and by ensuring that networking events are suitable for owner-managers, whether or not they have entrepreneurial goals, to facilitate face-to-face knowledge sharing.

Policy and practice impacts of applied research: a case study analysis of the New South Wales Health Promotion Demonstration Research Grants Scheme 2000-2006

Background
Intervention research provides important information regarding feasible and effective interventions for health policy makers, but few empirical studies have explored the mechanisms by which these studies influence policy and practice. This study provides an exploratory case series analysis of the policy, practice and other related impacts of the 15 research projects funded through the New South Wales Health Promotion Demonstration Research Grants Scheme during the period 2000 to 2006, and explored the factors mediating impacts.

Methods
Data collection included semi-structured interviews with the chief investigators (n = 17) and end-users (n = 29) of each of the 15 projects to explore if, how and under what circumstances the findings had been used, as well as bibliometric analysis and verification using documentary evidence. Data analysis involved thematic coding of interview data and triangulation with other data sources to produce case summaries of impacts for each project. Case summaries were then individually assessed against four impact criteria and discussed at a verification panel meeting where final group assessments of the impact of research projects were made and key influences of research impact identified.

Results
Funded projects had variable impacts on policy and practice. Project findings were used for agenda setting (raising awareness of issues), identifying areas and target groups for interventions, informing new policies, and supporting and justifying existing policies and programs across sectors. Reported factors influencing the use of findings were: i) nature of the intervention; ii) leadership and champions; iii) research quality; iv) effective partnerships; v) dissemination strategies used; and, vi) contextual factors.

Conclusions
The case series analysis provides new insights into how and under what circumstances intervention research is used to influence real world policy and practice. The findings highlight that intervention research projects can achieve the greatest policy and practice impacts if they address proximal needs of the policy context by engaging end-users from the inception of projects and utilizing existing policy networks and structures, and using a range of strategies to disseminate findings that go beond traditional peer review publications.

Defense against packet dropping attacks in opportunistic networks

Opportunistic networks (OppNets) are an interesting topic that are seen to have a promising future. Many protocols have been developed to accommodate the features of OppNets such as frequent partitions, long delays, and no end-to-end path between the source and destination nodes. Embedding security into these protocols is challenging and has taken a lot of attention in research. One of the attacks that OppNets are exposed to is the packet dropping attack, where the malicious node attempts to drop some packets and forwards an incomplete number of packets which results in the distortion of the message. To increase the security levels in OppNets, this paper presents an algorithm developed to detect packet dropping attacks, and finds the malicious node that attempted the attack. The algorithm detects the attack by using an indicative field in the header section of each packet; the indicative field has 3 sub fields - the identification field, the flag field, and the offset field. These 3 fields are used to find if a node receives the complete original number of packets from the previous node. The algorithm will have the advantage of detecting packets dropped by each intermediate node, this helps solve the difficulties of finding malicious nodes by the destination node only.

Fabrication of conductive elastic nanocomposites via framing intact interconnected graphene networks

Electrically conductive elastic nanocomposites with well-organized graphene architectures offer significant improvement in various properties. However, achieving desirable graphene architectures in cross-linked rubber is challenging due to high viscosity and cross-linked nature of rubber matrices. Here, three dimensional (3D) interconnected graphene networks in natural rubber (NR) matrix are framed with self-assembly integrating latex compounding technology by employing electrostatic adsorption between poly(diallyldimethylammonium chloride) modified graphene (positively charged) and NR latex particles (negatively charged) as the driving force. The 3D graphene structure endows the resulted nanocomposites with excellent electrical conductivity of 7.31. S/m with a graphene content of 4.16. vol.%, extremely low percolation threshold of 0.21. vol.% and also analogous reinforcement in mechanical properties. The developed strategy will provide a practical approach for developing elastic nanocomposites with multi-functional properties. © 2014 Elsevier Ltd.

Modeling the propagation of worms in networks: a survey

There are the two common means for propagating worms: scanning vulnerable computers in the network and spreading through topological neighbors. Modeling the propagation of worms can help us understand how worms spread and devise effective defense strategies. However, most previous researches either focus on their proposed work or pay attention to exploring detection and defense system. Few of them gives a comprehensive analysis in modeling the propagation of worms which is helpful for developing defense mechanism against worms' spreading. This paper presents a survey and comparison of worms' propagation models according to two different spreading methods of worms. We first identify worms characteristics through their spreading behavior, and then classify various target discover techniques employed by them. Furthermore, we investigate different topologies for modeling the spreading of worms, analyze various worms' propagation models and emphasize the performance of each model. Based on the analysis of worms' spreading and the existing research, an open filed and future direction with modeling the propagation of worms is provided. © 2014 IEEE.

Mining mechanism of top-k influential nodes based on voting algorithm in mobile social networks

In recent years, evaluating the influence of nodes and finding top-k influential nodes in social networks, has drawn a wide attention and has become a hot-pot research issue. Considering the characteristics of social networks, we present a novel mechanism to mine the top-k influential nodes in mobile social networks. The proposed mechanism is based on the behaviors analysis of SMS/MMS (simple messaging service / multimedia messaging service) communication between mobile users. We introduce the complex network theory to build a social relation graph, which is used to reveal the relationship among people's social contacts and messages sending. Moreover, intimacy degree is also introduced to characterize social frequency among nodes. Election mechanism is hired to find the most influential node, and then a heap sorting algorithm is used to sort the voting results to find the k most influential nodes. The experimental results show that the mechanism can finds out the most influential top-k nodes efficiently and effectively. © 2013 IEEE.

Enhancing wireless sensor networks functionalities

 The main objective of this thesis is to develop solutions for the existing research problems in wireless sensor networks that negatively influence their performances. To achieve that four main research gaps from collecting, aggregating and transferring data with considering different deployment methods of sensor nodes were addressed.