Inter-Frame Change Directing online clustering of multiple moving objects for video-based sensor networks

Recognition of multiple moving objects is a very important task for achieving user-cared knowledge to send to the base station in wireless video-based sensor networks. However, video based sensor nodes, which have constrained resources and produce huge amount of video streams continuously, bring a challenge to segment multiple moving objects from the video stream online. Traditional efficient clustering algorithms such as DBSCAN cannot run time-efficiently and even fail to run on limited memory space on sensor nodes, because the number of pixel points is too huge. This paper provides a novel algorithm named Inter-Frame Change Directing Online clustering (IFCDO clustering) for segmenting multiple moving objects from video stream on sensor nodes. IFCDO clustering only needs to group inter-frame different pixels, thus it reduces both space and time complexity while achieves robust clusters the same as DBSCAN. Experiment results show IFCDO clustering excels DBSCAN in terms of both time and space efficiency. © 2008 IEEE.

Preventive social health programs : are they Australia's answer to rising health care costs in rural communities?

Although we have good evidence to support the notion that early intervention, prevention and community education programs can mitigate the impact of preventable disease, expanded primary health care is also being promoted by Australian governments as a panacea for reducing growth in demand generally. While preventive programs do reduce acute demand, they may not do so the extent that resources, currently allocated to the acute sector, can be substituted to provide the additional primary care services necessary to reduce acute demand permanently. These developments have particular relevance for rural and isolated communities where access to acute services is already very limited. What appears to be occurring, in rural South Australia at least, is that traditional acute services are being reduced and replaced with lower level care and social intervention programs. This is well and good, but eventually the acute care being provided in rural health units now will still need to be provided by other units elsewhere and probably at much higher cost to the system and to consumers. Where rural communities have previously managed much of their own acute service demand, they may now be forced to send patients to more distant centres for care but at much greater social and economic cost to individuals and the system.

Wireless video-based sensor networks for surveillance of residential districts

Compared to traditional wired video sensor networks to supervise a residential district, Wireless Video-based Sensor Networks (WVSN) can provide more detail and precise information while reduce the cost. However, state-of-the-art low cost wireless video-based sensors have very constrained resources such as low bandwidth, small storage, limited processing capability, and limited energy resource. Also, due to the special sensing range of video-based sensors, cluster-based routing is not as effective as it apply to traditional sensor networks. This paper provides a novel real-time change mining algorithm based on an extracted profile model of moving objects learnt from frog's eyes. Example analysis shows the extracted profile would not miss any important semantic images to send to the Base Station for further hazards detection, while efficiently reducing futile video stream data to the degree that nowadays wireless video sensor can realize. Thus it makes WVSN available to surveillance of residential districts.

A performance evaluation of machine learning-based streaming spam tweets detection

The popularity of Twitter attracts more and more spammers. Spammers send unwanted tweets to Twitter users to promote websites or services, which are harmful to normal users. In order to stop spammers, researchers have proposed a number of mechanisms. The focus of recent works is on the application of machine learning techniques into Twitter spam detection. However, tweets are retrieved in a streaming way, and Twitter provides the Streaming API for developers and researchers to access public tweets in real time. There lacks a performance evaluation of existing machine learning-based streaming spam detection methods. In this paper, we bridged the gap by carrying out a performance evaluation, which was from three different aspects of data, feature, and model. A big ground-truth of over 600 million public tweets was created by using a commercial URL-based security tool. For real-time spam detection, we further extracted 12 lightweight features for tweet representation. Spam detection was then transformed to a binary classification problem in the feature space and can be solved by conventional machine learning algorithms. We evaluated the impact of different factors to the spam detection performance, which included spam to nonspam ratio, feature discretization, training data size, data sampling, time-related data, and machine learning algorithms. The results show the streaming spam tweet detection is still a big challenge and a robust detection technique should take into account the three aspects of data, feature, and model.

Understanding the use of social media by organisations for crisis communication

Many businesses have commenced using social media for crisis communication with stakeholders. However there is little guidance in literature to assist organisational crisis managers with the selection of an appropriate crisis response strategy. Traditional theories on crisis communication may not adequately represent the social media context. This study took a qualitative approach and explored organisational use of social media for crisis communication at seventeen large Australian organisations. An analysis of 15,650 Facebook and Twitter messages was conducted, drawing on the lens of Situational Crisis Communication Theory (SCCT) (Coombs & Holladay, 2002). Findings suggested that when large Australian organisations responded to crises via social media, they lacked an awareness of the potential of social media for crisis communication. Organisations often did not respond to stakeholder messages or selected crisis response strategies that may increase reputational risk. The paper contributes important understandings of organisational social media use for crisis communication. It also assists crisis managers by providing six crisis response positions and a taxonomy of social media crisis messages that stakeholders may send to organisations. Key implications are discussed.

Sustainable futures for learning in a climate of change: mobile apps, social media, and crisis informatics during emergencies and disasters

Emergencies and disasters are different types of crisis events which can affect students and staff in their on-campus roles and off-campus activities. In such events, mobile technologies, mobile software applications (apps), and mobile social networks are becoming increasingly relied upon to communicate, to swiftly send and received information and images, to deliver learning moments, and to check the safety of colleagues and friends. This paper investigates the intersection of mlearning, mobile social media, mobile apps, and crisis informatics in times of emergencies and disasters, using the recent Gipplsand earthquake in south-eastern Australia as an exemplar. It also discusses proactive preparation for educational resilience during emergencies and disasters.

Graph theory based QoE-driven cooperation stimulation for content dissemination in device-To-device communication

With multimedia dominating the digital contents, Device-To-Device (D2D) communication has been proposed as a promising data offloading solution in the big data area. As the quality of experience (QoE) is a major determining factor in the success of new multimedia applications, we propose a QoEdriven cooperative content dissemination (QeCS) scheme in this work. Specifically, all users predict the QoE of the potential connections characterized by the mean opinion score (MOS), and send the results to the content provider (CP). Then CP formulates a weighted directed graph according to the network topology and MOS of each potential connection. In order to stimulate cooperation among the users, the content dissemination mechanism is designed through seeking 1-factor of the weighted directed graph with the maximum weight thus achieving maximum total user MOS. Additionally, a debt mechanism is adopted to combat the cheat attacks. Furthermore, we extend the proposed QeCS scheme by considering a constrained condition to the optimization problem for fairness improvement. Extensive simulation results demonstrate that the proposed QeCS scheme achieves both efficiency and fairness especially in large scale and density networks.

Digital suburbs? Some policy implications of greater domestic connectivity

Since the mid-1990s there has occurred a communications revolution. With the development and widespread dissemination of Information Communications Technologies (ICTs), the capacity of virtually everyone in the developed world to send, receive and manipulate masses amounts of information has been transformed. In the light of high levels of internet uptake across Australian cities and the looming rollout of the National Broadband Network, it is timely to investigate just what the impacts may be on house design, service access, socialisation and connections to localities. The answer to these questions will potentially have profound implications for the future planning of Australian cities and suburbs. So, has the proliferation of domestic broadband led to more people working from home rather than commuting, on line socialising, and on line service access? Or has greater connectivity meant that the form and range of information flow has altered but the physicality of service provision, job access and socialisation is just, if not more, important? This paper will locate these questions within research on the economic, social and political impacts of ICTs before discussing how the digital revolution is having limited economic effects but profound social and political impacts on Melbourne’s western suburbs.

Two-factor data security protection mechanism for cloud storage system

In this paper, we propose a two-factor data security protection mechanism with factor revocability for cloud storage system. Our system allows a sender to send an encrypted message to a receiver through a cloud storage server. The sender only needs to know the identity of the receiver but no other information (such as its public key or its certificate). The receiver needs to possess two things in order to decrypt the ciphertext. The first thing is his/her secret key stored in the computer. The second thing is a unique personal security device which connects to the computer. It is impossible to decrypt the ciphertext without either piece. More importantly, once the security device is stolen or lost, this device is revoked. It cannot be used to decrypt any ciphertext. This can be done by the cloud server which will immediately execute some algorithms to change the existing ciphertext to be un-decryptable by this device. This process is completely transparent to the sender. Furthermore, the cloud server cannot decrypt any ciphertext at any time. The security and efficiency analysis show that our system is not only secure but also practical.