An attack-localizing watermarking scheme for natural language documents

We present a text watermarking scheme that embeds a bitstream watermark Wi in a text document P preserving the meaning, context, and flow of the document. The document is viewed as a set of paragraphs, each paragraph being a set of sentences. The sequence of paragraphs and sentences used to embed watermark bits is permuted using a secret key. Then, English language sentence transformations are used to modify sentence lengths, thus embedding watermarking bits in the Least Significant Bits (LSB) of the sentences’ cardinalities. The embedding and extracting algorithms are public, while the secrecy and security of the watermark depends on a secret key K. The probability of False Positives is extremely small, hence avoiding incidental occurrences of our watermark in random text documents. Majority voting provides security against text addition, deletion, and swapping attacks, further reducing the probability of False Positives. The scheme is secure against the general attacks on text watermarks such as reproduction (photocopying, FAX), reformatting, synonym substitution, text addition, text deletion, text swapping, paragraph shuffling and collusion attacks.

Lanthanum oxide nanostructured films synthesized using hot dense and extremely non-equilibrium plasma for nanoelectronic device applications

Lanthanum oxide (La2O3) nanostructured films are synthesized on a p-type silicon wafer by ablation of La2O3 pellet due to interaction with hot dense argon plasmas in a modified dense plasma focus (DPF) device. The nanostructured films are investigated using scanning electron microscopy (SEM), atomic force microscopy (AFM), and X-ray diffraction (XRD) spectra. SEM study shows the formation of nano-films having nano-size structures with the average nanostructures size ~25, ~53, and ~45 nm for one, two, and three DPF shots, respectively. The nanostructures sizes and morphology of nano-films are consistent between the AFM and SEM analyses. XRD spectra confirms nano-sized La2O3 with an average grain size ~34, ~51, and ~42 nm for one, two, and three DPF shots, respectively. The electrical properties such as current-voltage and capacitance-voltage (C-V) characteristics of the Al-La2O3-Si metal-oxide- semiconductor (MOS) capacitor structure are measured. The current conduction mechanism of the MOS capacitors is also demonstrated. The C-V characteristics are further used to obtain the electrical parameters such as the dielectric constant, oxide thickness, flat-band capacitance, and flat-band voltage of the MOS capacitors. These measurements demonstrate significantly lower leakage currents without any commonly used annealing or doping, thereby revealing a significant improvement of the MOS nanoelectronic device performance due to the incorporation of the DPF-produced La2O3 nano-films.

Extremely non-equilibrium synthesis of luminescent zinc oxide nanoparticles through energetic ion condensation in a dense plasma focus device

Luminescent ZnO nanoparticles have been synthesized on silicon and quartz substrates under extremely non-equilibrium conditions of energetic ion condensation during the post-focus phase in a dense plasma focus (DPF) device. Ar+, O+, Zn+ and ZnO+ ions are generated as a result of interaction of hot and dense argon plasma focus with the surfaces of ZnO pellets placed at the anode. It is found that the sizes, structural and photoluminescence (PL) properties of the ZnO nanoparticles appear to be quite different on Si(1 0 0) and quartz substrates. The results of x-ray diffractometry and atomic force microscopy show that the ZnO nanoparticles are crystalline and range in size from 5-7 nm on Si(1 0 0) substrates to 10-38 nm on quartz substrates. Room-temperature PL studies reveal strong peaks related to excitonic bands and defects for the ZnO nanoparticles deposited on Si (1 0 0), whereas the excitonic bands are not excited in the quartz substrate case. Raman studies indicate the presence of E2 (high) mode for ZnO nanoparticles deposited on Si(1 0 0).

Shared generation of pseudo-random functions

In Crypto’95, Micali and Sidney proposed a method for shared generation of a pseudo-random function f(·) among n players in such a way that for all the inputs x, any u players can compute f(x) while t or fewer players fail to do so, where 0⩽trandom collection of functions, among the n players, each player gets a subset of S, in such a way that any u players together hold all the secret seeds in S while any t or fewer players will lack at least one element from S. The pseudo-random function is then computed as where fsi(·)'s are poly-random functions. One question raised by Micali and Sidney is how to distribute the secret seeds satisfying the above condition such that the number of seeds, d, is as small as possible. In this paper, we continue the work of Micali and Sidney. We first provide a general framework for shared generation of pseudo-random function using cumulative maps. We demonstrate that the Micali–Sidney scheme is a special case of this general construction. We then derive an upper and a lower bound for d. Finally we give a simple, yet efficient, approximation greedy algorithm for generating the secret seeds S in which d is close to the optimum by a factor of at most u ln 2.

Shared generation of pseudo-random functions with cumulative maps

In Crypto’95, Micali and Sidney proposed a method for shared generation of a pseudo-random function f(·) among n players in such a way that for all the inputs x, any u players can compute f(x) while t or fewer players fail to do so, where 0 ≤ t < u ≤ n. The idea behind the Micali-Sidney scheme is to generate and distribute secret seeds S = s1, . . . , sd of a poly-random collection of functions, among the n players, each player gets a subset of S, in such a way that any u players together hold all the secret seeds in S while any t or fewer players will lack at least one element from S. The pseudo-random function is then computed as where f s i (·)’s are poly-random functions. One question raised by Micali and Sidney is how to distribute the secret seeds satisfying the above condition such that the number of seeds, d, is as small as possible. In this paper, we continue the work of Micali and Sidney. We first provide a general framework for shared generation of pseudo-random function using cumulative maps. We demonstrate that the Micali-Sidney scheme is a special case of this general construction.We then derive an upper and a lower bound for d. Finally we give a simple, yet efficient, approximation greedy algorithm for generating the secret seeds S in which d is close to the optimum by a factor of at most u ln 2.

'Not a Local Win': Rural Australian perceptions of the sustainable impacts of forest plantations

Australian forestry plantations have doubled in the past 15 years, with rural communities harbouring a diverse range of positive and negative of economic, environmental and social impacts – the so-called triple bottom line (TBL). Utilising two Australian rural communities in Eden/Gippsland and Tasmania as qualitative case studies, this research explores how 23 non-forestry affiliated rural residents perceived and experienced the TBL economic, environmental and social impacts of plantation forestry. Residents criticised the economic plantation forestry benefits because of lengthy periods of inactivity and limited local employment, explaining that their community was reliant on the industry yet the promised economic benefits had never fully materialised. There was a sense the industry ‘plant and walk away.’ Residents were concerned about the environment impact on water quality, water tables and fire hazards, although they praised plantation forestry for carbon sequestering, eradicating erosion and water run-off. Negative social impacts were described, specifically how the land-use change from farming to forestry had significantly reduced the local population, employment and need for services. Natural resource management and communication strategies are offered, derived from non-forestry affiliated rural resident perspectives on how best to ensure sustainable forest development in their community.

Cost efficiency of Japanese steam power generation companies : a Bayesian comparison of random and fixed frontier models

This study analyses and compares the cost efficiency of Japanese steam power generation companies using the fixed and random Bayesian frontier models. We show that it is essential to account for heterogeneity in modelling the performance of energy companies. Results from the model estimation also indicate that restricting CO2 emissions can lead to a decrease in total cost. The study finally discusses the efficiency variations between the energy companies under analysis, and elaborates on the managerial and policy implications of the results.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

Spatial analysis of risk factors for transmission of the Barmah forest virus in Queensland, Australia

Barmah Forest virus (BFV) disease is the second most common mosquito-borne disease in Australia but few data are available on the risk factors. We assessed the impact of spatial climatic, socioeconomic and ecological factors on the transmission of BFV disease in Queensland, Australia, using spatial regression. All our analyses indicate that spatial lag models provide a superior fit to the data compared to spatial error and ordinary least square models. The residuals of the spatial lag models were found to be uncorrelated, indicating that the models adequately account for spatial and temporal autocorrelation. Our results revealed that minimum temperature, distance from coast and low tide were negatively and rainfall was positively associated with BFV disease in coastal areas, whereas minimum temperature and high tide were negatively and rainfall was positively associated with BFV disease (all P-value.

Emerging methods in using GIS to analyse Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is an emerging mosquito-borne disease in Australia. We aimed to outline some recent methods in using GIS for the analysis of BFV disease in Queensland, Australia. A large database of geocoded BFV cases has been established in conjunction with population data. The database has been used in recently published studies conducted by the authors to determine spatio-temporal BFV disease hotspots and spatial patterns using spatial autocorrelation and semi-variogram analysis in conjunction with the development of interpolated BFV disease standardised incidence maps. This paper briefly outlines spatial analysis methodologies using GIS tools used in those studies. This paper summarises methods and results from previous studies by the authors, and presents a GIS methodology to be used in future spatial analytical studies in attempt to enhance the understanding of BFV disease in Queensland. The methodology developed is useful in improving the analysis of BFV disease data and will enhance the understanding of the BFV disease distribution in Queensland, Australia.

A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design

A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.

Forest reflections

Interactive art installation Artist in Residence Queensland Government grant. Awarded June 2011 for period July-September 2011. This project involved co-creating an interactive artwork on site and in the forest with Grovely Primary school children aged 6-10, some with high needs. Affiliated with the United Nations International Year of the Forest. Final work is tangible, real-time visualization created using participatory design methods.