A fuzzy technique to control congestion in WSN

Congestion in wireless sensor networks (WSNs) is a crucial issue. That is due to the relatively high node density and source-to-sink communication pattern. Congestion not only causes packet loss, but also leads to excessive energy consumption as well as delay. Therefore, in order to prolong network lifetime and improve fairness and provide better quality of service, developing a novel solution for congestion estimation and control is important to be considered. To address this problem, we propose a type-2 fuzzy logic based algorithm to detect and control congestion level in WSNs. The proposed algorithm considers local information such as packet loss rate and delay to control congestion in the network. Simulation results show that our protocol performs better than a recently developed protocol in prolonging network lifetime as well as decreasing packet loss.

Community views on responding to a local asbestos disease epidemic : implications for policy and practice

The Latrobe Valley region of Victoria, Australia, has the highest rate of asbestos disease in the state due to extensive past use of asbestos in the power industry. Current responses to asbestos disease epidemics in Australia and internationally are dominated by medical, scientific, legal and government perspectives. The voices and perspectives of those most directly affected – exposed and diseased workers, their families and communities – are relatively rarely heard.A qualitative interview study was conducted to determine what people in the Latrobe Valley community think could or should be done following their own asbestos disease epidemic. Analysis identified several themes. Notably, these represent a sophisticated community understanding of issues that is largely consistent with state-of-the-art occupational health and public health knowledge.Some themes are well known already, eg the need for fair and timely compensation, adequate healthcare facilities and services, and more education. Others point to neglected possibilities, such as the need for reconciliation and social healing to complement the dominant individual medico-legal focus. Employer suppression of hazard information and denial of asbestos-related disease in past decades continues to have a profound effect on people's views in the present. Reconciliation in some form, eg acknowledgement of or apology for past wrongs, was identified as a necessary first step in developing new and better policy and practice responses; action in this regard has important implications for the implementation and effectiveness of other policy and practice interventions. Further, a need for substantive community participation in the development of policy and practice responses – currently lacking – was identified. Findings suggest that community is an under-recognised and under-utilised resource in responding to a local asbestos disease epidemic.The Latrobe Valley situation is a microcosm of the broader Australian and international story. It offers insights on the perspectives of those most affected by asbestos issues, how such people and their views can be used to strengthen current policy and practice responses, and how their participation is essential to building comprehensive public and social health responses to this global problem.

Gambling participation and problem gambling severity in a stratified random survey : Findings from the second social and economic impact study of gambling in Tasmania

Demographic characteristics associated with gambling participation and problem gambling severity were investigated in a stratified random survey in Tasmania, Australia. Computer-assisted telephone interviews were conducted in March 2011 resulting in a representative sample of 4,303 Tasmanian residents aged 18 years or older. Overall, 64.8 % of Tasmanian adults reported participating in some form of gambling in the previous 12 months. The most common forms of gambling were lotteries (46.5 %), keno (24.3 %), instant scratch tickets (24.3 %), and electronic gaming machines (20.5 %). Gambling severity rates were estimated at non-gambling (34.8 %), non-problem gambling (57.4 %), low risk gambling (5.3 %), moderate risk (1.8 %), and problem gambling (.7 %). Compared to Tasmanian gamblers as a whole significantly higher annual participation rates were reported by couples with no children, those in full time paid employment, and people who did not complete secondary school. Compared to Tasmanian gamblers as a whole significantly higher gambling frequencies were reported by males, people aged 65 or older, and people who were on pensions or were unable to work. Compared to Tasmanian gamblers as a whole significantly higher gambling expenditure was reported by males. The highest average expenditure was for horse and greyhound racing ($AUD 1,556), double the next highest gambling activity electronic gaming machines ($AUD 767). Compared to Tasmanian gamblers as a whole problem gamblers were significantly younger, in paid employment, reported lower incomes, and were born in Australia. Although gambling participation rates appear to be falling, problem gambling severity rates remain stable. These changes appear to reflect a maturing gambling market and the need for population specific harm minimisation strategies. © 2014 Springer Science+Business Media New York.

Control flow-based malware variant detection

Static detection of malware variants plays an important role in system security and control flow has been shown as an effective characteristic that represents polymorphic malware. In our research, we propose a similarity search of malware to detect these variants using novel distance metrics. We describe a malware signature by the set of control flowgraphs the malware contains. We use a distance metric based on the distance between feature vectors of string-based signatures. The feature vector is a decomposition of the set of graphs into either fixed size k-subgraphs, or q-gram strings of the high-level source after decompilation. We use this distance metric to perform pre-filtering. We also propose a more effective but less computationally efficient distance metric based on the minimum matching distance. The minimum matching distance uses the string edit distances between programs' decompiled flowgraphs, and the linear sum assignment problem to construct a minimum sum weight matching between two sets of graphs. We implement the distance metrics in a complete malware variant detection system. The evaluation shows that our approach is highly effective in terms of a limited false positive rate and our system detects more malware variants when compared to the detection rates of other algorithms. © 2013 IEEE.

Rapid Physarum Algorithm for shortest path problem

As shortest path (SP) problem has been one of the most fundamental network optimization problems for a long time, technologies for this problem are still being studied. In this paper, a new method by integrating a path finding mathematical model, inspired by Physarum polycephalum, with extracted one heuristic rule to solve SP problem has been proposed, which is called Rapid Physarum Algorithm (RPA). Simulation experiments have been carried out on three different network topologies with varying number of nodes. It is noted that the proposed RPA can find the optimal path as the path finding model does for most networks. What is more, experimental results show that the performance of RPA surpasses the path finding model on both iterations and solution time. © 2014 Elsevier B.V.

To shut them up or to clarify: restraining the spread of rumors in online social networks

Restraining the spread of rumors in online social networks (OSNs) has long been an important but difficult problem to be addressed. Currently, there are mainly two types of methods 1) blocking rumors at the most influential users or community bridges, or 2) spreading truths to clarify the rumors. Each method claims the better performance among all the others according to their own considerations and environments. However, there must be one standing out of the rest. In this paper, we focus on this part of work. The difficulty is that there does not exist a universal standard to evaluate them. In order to address this problem, we carry out a series of empirical and theoretical analysis on the basis of the introduced mathematical model. Based on this mathematical platform, each method will be evaluated by using real OSN data.We have done three types of analysis in this work. First, we compare all the measures of locating important users. The results suggest that the degree and betweenness measures outperform all the others in the Facebook network. Second, we analyze the method of the truth clarification method, and find that this method has a long-term performance while the degree measure performs well only in the early stage. Third, in order to leverage these two methods, we further explore the strategy of different methods working together and their equivalence. Given a fixed budget in the real world, our analysis provides a potential solution to find out a better strategy by integrating both types of methods together. From both the academic and technical perspective, the work in this paper is an important step towards the most practical and optimal strategies of restraining rumors in OSNs.

Joint resource allocation for max-min throughput in multicell networks

We investigate the resource-allocation problem in multicell networks targeting the max-min throughput of all cells. A joint optimization over power control, channel allocation, and user association is considered, and the problem is then formulated as a nonconvex mixed-integer nonlinear problem (MINLP). To solve this problem, we proposed an alternating-optimization-based algorithm, which applies branch-and-bound and simulated annealing in solving subproblems at each optimization step. We also demonstrate the convergence and efficiency of the proposed algorithms by thorough numerical experiments. The experimental results show that joint optimization over all resources outperforms the restricted optimization over individual resources significantly.

Certificate-based encryption resilient to key leakage

Certificate-based encryption (CBE) is an important class of public key encryption but the existing schemes are secure only under the premise that the decryption key (or private key) and master secret key are absolutely secret. In fact, a lot of side channel attacks and cold boot attacks can leak secret information of a cryptographic system. In this case, the security of the cryptographic system is destroyed, so a new model called leakage-resilient (LR) cryptography is introduced to solve this problem. While some traditional public key encryption and identity-based encryption with resilient-leakage schemes have been constructed, as far as we know, there is no leakage-resilient scheme in certificate-based cryptosystems. This paper puts forward the first certificate-based encryption scheme which can resist not only the decryption key leakage but also the master secret key leakage. Based on composite order bilinear group assumption, the security of the scheme is proved by using dual system encryption. The relative leakage rate of key is close to 1/3.

A preliminary adaptation of the Problem Gambling Severity Index for Indigenous Australians: internal reliability and construct validity

Objective: This paper describes the process employed to adapt the Problem Gambling Severity Index (PGSI) for use with Indigenous Australian populations.Methods: This study comprised a two-stage process: an initial consultation with Indigenous health workers, informing the textual and conceptual adaptation of items, followed by trial of the adjusted instrument with Indigenous community members (n=301).Results: Internal reliability was demonstrated: Australian Indigenous Problem Gambling Index (AIPGI) Cronbach's alpha α = 0.92 (Original PGSI, α = 0.84). Item-rest correlations confirmed that responses to items were consistent and related to the total score of remaining items. The AIPGI could predict gambling severity based on gambling frequency, when controlling for age and gender (OR=1.28, 95%CI 1.17–1.40).Conclusions: The adapted instrument is accessible to a cross-section of Indigenous Australians and has demonstrated properties of reliability and validity. An extended trial is needed to test the application of the instrument to a broader Indigenous audience and to further explore and confirm psychometric properties of the adapted instrument.Implications: This study introduces a culturally adapted tool for measuring rates of disordered gambling among Indigenous Australians.

Problem gambling, familial violence and alcohol misuse: exploring the triad for treatment-seekers

Research into the co-occurrence of problem gambling, familial violence, and alcohol misuse is limited. While these issues have been considered in combination (i.e.violence and alcohol misuse, problem gambling and alcohol misuse, problem gambling and violence), within Australia, in particular, there has been an absence of exploration of this triad. The current research attempts to fill the gap in the literature, to establish whether there is any difference between problem gamblers with co-occurring violence and problem gamblers who had not experienced violence in terms of their alcohol misuse and gambling behaviours. Interviews were conducted with 81 treatment- seeking problem gamblers to explore how a history of victimization only, perpetration only, victimization and perpetration, or no history of family violence impacted on gambling behaviours (including baseline Victorian Gambling Screen), as well as alcohol misuse. Results indicated that in this treatment-seeking sample there were no significant differences for gambling behaviours or alcohol misuse between problem gamblers with issues of violence and those without. Males demonstrated (on average) a greater tendency toward hazardous drinking or disordered alcohol use. It would be prudent for treatment services to routinely examine problem gamblers’ history of violence and alcohol misuse until research verifies the nature of this triad

The passage of authority: imagining the political transformation of Australia’s Christmas Island, from sovereignty to governance

In 2012, Australia’s Christmas Island is best known as an island of immigration detention, a key component of Australia’s growing offshore border security apparatus, where interdicted boat arrivals seeking asylum are detained and processed. This article offers one account of how the Island came to be what it is, by providing two snapshots of the operable set of power relations on Christmas Island, then and now: ‘Island in the Sun’, and ‘Tropics of Governance’. Side by side, their stark contrast reveals the passage of authority through time and place, from the embodied, unified voice of the sovereignty of the British Empire to the palliative communication and bureaucratic sincerity that characterise governance. By disclosing shifting patterns of emergence and decay and showing border security’s intimate relation to governance, this article seeks to offer a deepened understanding of the current detention situation in its immanence. What can now be seen as Christmas Island’s past follies also reveals the restless work of successive political imaginations, the shifting ways and means by which an island can be translated into a solution to a political problem, and how successive solutions tend toward wreck and ruin.

Experiences and perceptions of problem gamblers on cognitive and exposure therapies when taking part in a randomised controlled trial: a qualitative study

In South Australia (SA) problem gambling is mainly a result of the widespread availability of electronic gaming machines. A key treatment provider in SA offers free cognitive and behavioural therapy (CBT) to help-seeking problem gamblers. The CBT program focuses on the treatment of clients' urge to gamble using exposure therapy (ET) and cognitive therapy (CT) to restructure erroneous gambling beliefs. The aim of this study was to explore treatment specific and non-specific effects for CT alone and ET alone using qualitative interviews. Interviewees were a sub-sample of participants from a randomised trial that investigated the relative efficacy of CT versus ET. Findings revealed that all interviewees gained benefit from their respective therapies and their comments did not appear to favour one therapy over another. Both treatment specific and treatment non-specific effects were well supported as playing a therapeutic role to recovery. Participants' comments in both therapy groups suggested that symptom reduction was experienced on a gambling related urge-cognition continuum. In addition to symptom improvement from therapy-specific mechanisms, ET participants described a general acquisition of "rational thought" from their program of therapy and CT participants had "taken-over" their gambling urges. The findings also highlighted areas for further improvement including therapy drop-out.

An ensemble learning approach for addressing the class imbalance problem in twitter spam detection

Being an important source for real-time information dissemination in recent years, Twitter is inevitably a prime target of spammers. It has been showed that the damage caused by Twitter spam can reach far beyond the social media platform itself. To mitigate the threat, a lot of recent studies use machine learning techniques to classify Twitter spam and report very satisfactory results. However, most of the studies overlook a fundamental issue that is widely seen in real-world Twitter data, i.e., the class imbalance problem. In this paper, we show that the unequal distribution between spam and non-spam classes in the data has a great impact on spam detection rate. To address the problem, we propose an ensemble learning approach, which involves three steps. In the first step, we adjust the class distribution in the imbalanced data set using various strategies, including random oversampling, random undersampling and fuzzy-based oversampling. In the next step, a classification model is built upon each of the redistributed data sets. In the final step, a majority voting scheme is introduced to combine all the classification models. Experimental results obtained using real-world Twitter data indicate that the proposed approach can significantly improve the spam detection rate in data sets with imbalanced class distribution.

Converged network-cloud service composition with end-to-end performance guarantee

The crucial role of networking in Cloud computing calls for federated management of both computing and networkin resources for end-To-end service provisioning. Application of the Service-Oriented Architecture (SOA) in both Cloud computing an networking enables a convergence of network and Cloud service provisioning. One of the key challenges to high performanc converged network-Cloud service provisioning lies in composition of network and Cloud services with end-To-end performanc guarantee. In this paper, we propose a QoS-Aware service composition approach to tackling this challenging issue. We first present system model for network-Cloud service composition and formulate the service composition problem as a variant of Multi-Constraine Optimal Path (MCOP) problem. We then propose an approximation algorithm to solve the problem and give theoretical analysis o properties of the algorithm to show its effectiveness and efficiency for QoS-Aware network-Cloud service composition. Performanc of the proposed algorithm is evaluated through extensive experiments and the obtained results indicate that the proposed metho achieves better performance in service composition than the best current MCOP approaches Service (QoS).

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.