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We study the effective resistance of small-world resistor networks. Utilizing recent analytic results for the propagator of the Edwards-Wilkinson process on small-world networks, we obtain the asymptotic behavior of the disorder-averaged two-point resistance in the large system-size limit. We find that the small-world structure suppresses large network resistances: both the average resistance and its standard deviation approaches a finite value in the large system-size limit for any non-zero density of random links. We also consider a scenario where the link conductance decays as a power of the length of the random links, $l^{-\alpha}$. In this case we find that the average effective system resistance diverges for any non-zero value of $\alpha$., Comment: 15 pages, 6 figures

We present a method for characterizing text based on a statistical analysis of word recurrence interval. This method can be used for extracting keywords from text, and also for comparing texts by an unknown author against a set of known authors. We also use these methods to comment on the controversial question of who wrote the letter to the Hebrews in the New Testament.

This paper reports the implementation of Systems Engineering (SE) processes by expatriate Indonesian engineers in their project or company with particular attention to awareness of cross-cultural issues within the project team. A web survey was conducted in which several questions are designed to investigate the engineers' awareness of how they manage their cultural background in implementing SE processes to achieve high quality project performance. The survey questions were designed using the results of a set of 18 interviews with Indonesian engineers working in several countries as expatriates. The interviews were used to surface the issues that would enable a tightly organized set of survey questions. The survey was answered by 291 Indonesian engineers working in various countries as expatriates. Several factors were identified as influencing productivity and performance in the implementation of SE Processes, as perceived by the Indonesian engineers. These factors include work ethic, social environment and educational background. This study reveals that engineers with an Indonesian cultural background typically exhibit several behaviors supporting a good work ethic such as discipline, responsibility, politeness and persistence. Other results from this study are that their social environment, educational background, and cultural background contributed to their awareness of their productivity and performance in implementation of SE processes. The purpose of this paper is to identify their awareness of how their cultural background influences the implementation of SE processes particularly in productivity and performance. Refereed/Peer-reviewed

Systems engineering practice performed by Indonesian expatriate engineers involves intra-project-team cultural diversity. In culturally diverse project teams, one of the key success factors in project performance is technology and knowledge sharing. This paper identifies elements of how technology and knowledge sharing work performed in systems engineering practices is influenced by cross-cultural adaptation in multicultural work environments. We interviewed 18 Indonesian engineers working outside Indonesia in multicultural teams, about the implementation of systems engineering practices in their experience and their knowledge of cross-cultural adaptation. The results indicate three factors that influence the technology and knowledge sharing strategy in culturally diverse project teams: communication; authority perception; and staff development strategy. Refereed/Peer-reviewed

Refereed/Peer-reviewed

Refereed/Peer-reviewed

The teaching of the systems engineering process is made problematic due to the enormity of experience required of a practising systems engineer. A 'gentle' project-based introduction to systems engineering practice is currently being investigated under the Microcosm programme. The Microcosm programme integrates a robotics-based system-ofsystems, as the first stages in building a systems engineering teaching environment. Lessons learnt have been collected from the Microcosm Stage One project and the systems engineering processes, used during the project, have been captured. This paper analyses the processes and lessons learnt, compares them against typical large-scale Defence systems engineering projects, and discusses the lesson learnt captured by the systems engineers who had been working in-the-small. While executing the case study it was found that the lessons learnt which are known to industry, would have been militated against their occurrence by the use of robust industrial systems engineering processes but that the Microcosm project schedule, with these industrial processes, would have been exceeded. As the Microcosm Stage One project was successfully completed, effort must now be expended to ensure that the participants understand the limitations and strengths of systems engineering in-the-small procedures and also understand the issues associated with the scaling up of the procedures.

We explore a variety of network models describing transmission across a network. In particular we focus on transmission across composite networks, or “networks of networks”, in which a finite number of networked objects are then themselves connected together into a network. In a disease context we introduce two interrelated viruses to hosts on a network, to model the infection of hosts in a classroom situation, with high rates of infection within a classroom, and lower rates of infection between classrooms. The hosts can be either susceptible to infection, infected, or recovering from each virus. During the infection stage and recovery stage there is some level of cross-immunity to related viruses. We explore the effects of immunizing sections of the community on transmission through social networks. In a stock market context we introduce memes, or virus-like ideas into a virtual agent-based model of a stock exchange. By varying the parameters of the individual traders and the way in which they are connected we are able to show emergent behaviour, including boom and bust cycles.

Electroencephalograph (EEG) analysis enables the neuronal behavior of a section of the brain to be examined. If the behavior is nonlinear then nonlinear tools can be used to glean information on brain behavior, and aid in the diagnosis of sleep abnormalities such as obstructive sleep apnea syndrome (OSAS). In this paper the sleep EEGs of a set of normal and mild OSAS children are evaluated for nonlinear behaviour. We consider how the behaviour of the brain changes with sleep stage and between normal and OSAS children., Comment: 9 pages, 2 figures, 4 tables

This paper reviews applications of signal processing techniques to a number of areas in the field of genetics. We focus on techniques for analyzing DNA sequences, and briefly discuss applications of signal processing to DNA sequencing, and other related areas in genetics that can provide biologically significant information to assist with sequence analysis.

This paper investigates the automated detection of a patient’s breathing rate and heart rate from their skin conductivity as well as sleep stage scoring and breathing event detection from their EEG. The software developed for these tasks is tested on data sets obtained from the sleep disorders unit at the Adelaide Women’s and Children’s Hospital. The sleep scoring and breathing event detection tasks used neural networks to achieve signal classification. The Fourier transform and the Higuchi fractal dimension were used to extract features for input to the neural network. The filtered skin conductivity appeared visually to bear a similarity to the breathing and heart rate signal, but a more detailed evaluation showed the relation was not consistent. Sleep stage classification was achieved with and accuracy of around 65% with some stages being accurately scored and others poorly scored. The two breathing events hypopnea and apnea were scored with varying degrees of accuracy with the highest scores being around 75% and 30%.

Cancer is viewed as a multistep process whereby a normal cell is transformed into a cancer cell through the acquisition of mutations. We reduce the complexities of cancer progression to a simple set of underlying rules that govern the transformation of normal cells to malignant cells. In doing so, we derive an ordinary differential equation model that explores how the balance of angiogenesis, cell death rates, genetic instability, and replication rates give rise to different kinetics in the development of cancer. The key predictions of the model are that cancer develops fastest through a particular ordering of mutations and that mutations in genes that maintain genomic integrity would be the most deleterious type of mutations to inherit. In addition, we perform a sensitivity analysis on the parameters included in the model to determine the probable contribution of each. This paper presents a novel approach to viewing the genetic basis of cancer from a systems biology perspective and provides the groundwork for other models that can be directly tied to clinical and molecular data., 12 pages, submitted to Journal of Theoretical Biology

Gene networks are composed of many different interacting genes and gene products (RNAs and proteins). They can be thought of as switching regions in n-dimensional space or as mass-balanced signaling networks. Both approaches allow for describing gene networks with the limited quantitative or even qualitative data available. We show how these approaches can be used in modeling the apoptosis gene network that has a vital role in tumor development. The open question is whether engineering changes to this network could be used as a possible cancer treatment.

Noise is present in the wide variety of signals obtained from sleep patients. This noise comes from a number of sources, from presence of extraneous signals to adjustments in signal amplification and shot noise in the circuits used for data collection. The noise needs to be removed in order to maximize the information gained about the patient using both manual and automatic analysis of the signals. Here we evaluate a number of new techniques for removal of that noise, and the associated problem of separating the original signal sources., Comment: 9 pages, 3 figures

This paper examines two methods for finding whether long-range correlations exist in DNA: a fractal measure and a mutual information technique. We evaluate the performance and implications of these methods in detail. In particular we explore their use comparing DNA sequences from a variety of sources. Using software for performing in silico mutations, we also consider evolutionary events leading to long range correlations and analyse these correlations using the techniques presented. Comparisons are made between these virtual sequences, randomly generated sequences, and real sequences. We also explore correlations in chromosomes from different species., Comment: 8 pages, 3 figures