How to extract and expand randomness : a summary and explanation of existing results

We examine the use of randomness extraction and expansion in key agreement (KA) pro- tocols to generate uniformly random keys in the standard model. Although existing works provide the basic theorems necessary, they lack details or examples of appropriate cryptographic primitives and/or parameter sizes. This has lead to the large amount of min-entropy needed in the (non-uniform) shared secret being overlooked in proposals and efficiency comparisons of KA protocols. We therefore summa- rize existing work in the area and examine the security levels achieved with the use of various extractors and expanders for particular parameter sizes. The tables presented herein show that the shared secret needs a min-entropy of at least 292 bits (and even more with more realistic assumptions) to achieve an overall security level of 80 bits using the extractors and expanders we consider. The tables may be used to �nd the min-entropy required for various security levels and assumptions. We also �nd that when using the short exponent theorems of Gennaro et al., the short exponents may need to be much longer than they suggested.

Variations in MIMO-OFDM channel capacity due to random human movement in an indoor environment

Channel measurements and simulations have been carried out to observe the effects of pedestrian movement on multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) channel capacity. An in-house built MIMO-OFDM packet transmission demonstrator equipped with four transmitters and four receivers has been utilized to perform channel measurements at 5.2 GHz. Variations in the channel capacity dynamic range have been analysed for 1 to 10 pedestrians and different antenna arrays (2 × 2, 3 × 3 and 4 × 4). Results show a predicted 5.5 bits/s/Hz and a measured 1.5 bits/s/Hz increment in the capacity dynamic range with the number of pedestrian and the number of antennas in the transmitter and receiver array.

Random Indexing K-tree

Random Indexing K-tree is the combination of two algorithms suited for large scale document clustering.

Fundamental solution and discrete random walk model for time-space fractional diffusion equation

In this paper, we consider a time-space fractional diffusion equation of distributed order (TSFDEDO). The TSFDEDO is obtained from the standard advection-dispersion equation by replacing the first-order time derivative by the Caputo fractional derivative of order α∈(0,1], the first-order and second-order space derivatives by the Riesz fractional derivatives of orders β 1∈(0,1) and β 2∈(1,2], respectively. We derive the fundamental solution for the TSFDEDO with an initial condition (TSFDEDO-IC). The fundamental solution can be interpreted as a spatial probability density function evolving in time. We also investigate a discrete random walk model based on an explicit finite difference approximation for the TSFDEDO-IC.

Clustering with random indexing K-tree and XML structure

This paper describes the approach taken to the clustering task at INEX 2009 by a group at the Queensland University of Technology. The Random Indexing (RI) K-tree has been used with a representation that is based on the semantic markup available in the INEX 2009 Wikipedia collection. The RI K-tree is a scalable approach to clustering large document collections. This approach has produced quality clustering when evaluated using two different methodologies.

QoS-oriented sesource allocation and scheduling of multiple composite web services in a hybrid cloud using a random-key genetic algorithm

In cloud computing resource allocation and scheduling of multiple composite web services is an important challenge. This is especially so in a hybrid cloud where there may be some free resources available from private clouds but some fee-paying resources from public clouds. Meeting this challenge involves two classical computational problems. One is assigning resources to each of the tasks in the composite web service. The other is scheduling the allocated resources when each resource may be used by more than one task and may be needed at different points of time. In addition, we must consider Quality-of-Service issues, such as execution time and running costs. Existing approaches to resource allocation and scheduling in public clouds and grid computing are not applicable to this new problem. This paper presents a random-key genetic algorithm that solves new resource allocation and scheduling problem. Experimental results demonstrate the effectiveness and scalability of the algorithm.

Creativity, knowledge, engagement : keys to finding the right governance model for a regional community precinct

This paper investigates the Cooroy Mill community precinct (Sunshine Coast, Queensland), as a case study, seeking to understand the way local dynamics interplay and work with the community strengths to build a governance model of best fit. As we move to an age of ubiquitous computing and creative economies, the definition of public place and its governance take on new dimensions, which – while often utilizing models of the past – will need to acknowledge and change to the direction of the future. This paper considers a newly developed community precinct that has been built on three key principles: to foster creative expression with new media, to establish a knowledge economy in a regional area, and to subscribe to principles of community engagement. The study involved qualitative interviews with key stakeholders and a review of common practice models of governance along a spectrum from community control to state control. The paper concludes with a call for governance structures that are locally situated and tailored, inclusive, engaging, dynamic and flexible in order to build community capacity, encourage creativity, and build knowledge economies within emerging digital media cityscapes.

How do we reach them? Comparing random samples from mobile and landline phones

Quantitative studies of nascent entrepreneurs such as GEM and PSED are required to generate their samples by screening the adult population, usually by phone in developed economies. Phone survey research has recently been challenged by shifting patterns of ownership and response rates of landline versus mobile (cell) phones, particularly for younger respondents. This challenge is acutely intense for entrepreneurship which is a strongly age-dependent phenomenon. Although shifting ownership rates have received some attention, shifting response rates have remained largely unexplored. For the Australian GEM 2010 adult population study we conducted a dual-frame approach that allows comparison between samples of mobile and landline phones. We find a substantial response bias towards younger, male and metropolitan respondents for mobile phones – far greater than explained by ownership rates. We also found these response rate differences significantly biases the estimates of the prevalence of early stage entrepreneurship by both samples, even when each sample is weighted to match the Australian population.