Reduction rules for reset/inhibitor nets

Reset/inhibitor nets are Petri nets extended with reset arcs and inhibitor arcs. These extensions can be used to model cancellation and blocking. A reset arc allows a transition to remove all tokens from a certain place when the transition fires. An inhibitor arc can stop a transition from being enabled if the place contains one or more tokens. While reset/inhibitor nets increase the expressive power of Petri nets, they also result in increased complexity of analysis techniques. One way of speeding up Petri net analysis is to apply reduction rules. Unfortunately, many of the rules defined for classical Petri nets do not hold in the presence of reset and/or inhibitor arcs. Moreover, new rules can be added. This is the first paper systematically presenting a comprehensive set of reduction rules for reset/inhibitor nets. These rules are liveness and boundedness preserving and are able to dramatically reduce models and their state spaces. It can be observed that most of the modeling languages used in practice have features related to cancellation and blocking. Therefore, this work is highly relevant for all kinds of application areas where analysis is currently intractable.

The sample complexity of pattern classification with neural networks: the size of the weights is more important than the size of the network

Sample complexity results from computational learning theory, when applied to neural network learning for pattern classification problems, suggest that for good generalization performance the number of training examples should grow at least linearly with the number of adjustable parameters in the network. Results in this paper show that if a large neural network is used for a pattern classification problem and the learning algorithm finds a network with small weights that has small squared error on the training patterns, then the generalization performance depends on the size of the weights rather than the number of weights. For example, consider a two-layer feedforward network of sigmoid units, in which the sum of the magnitudes of the weights associated with each unit is bounded by A and the input dimension is n. We show that the misclassification probability is no more than a certain error estimate (that is related to squared error on the training set) plus A3 √((log n)/m) (ignoring log A and log m factors), where m is the number of training patterns. This may explain the generalization performance of neural networks, particularly when the number of training examples is considerably smaller than the number of weights. It also supports heuristics (such as weight decay and early stopping) that attempt to keep the weights small during training. The proof techniques appear to be useful for the analysis of other pattern classifiers: when the input domain is a totally bounded metric space, we use the same approach to give upper bounds on misclassification probability for classifiers with decision boundaries that are far from the training examples.

Rademacher and Gaussian complexities: Risk bounds and structural results

We investigate the use of certain data-dependent estimates of the complexity of a function class, called Rademacher and Gaussian complexities. In a decision theoretic setting, we prove general risk bounds in terms of these complexities. We consider function classes that can be expressed as combinations of functions from basis classes and show how the Rademacher and Gaussian complexities of such a function class can be bounded in terms of the complexity of the basis classes. We give examples of the application of these techniques in finding data-dependent risk bounds for decision trees, neural networks and support vector machines.

Doorway to research : Issues in the development of an interactive website for international graduate students

This paper describes results of a study evaluating the content, functionality and design features of an innovative online website called the Doorway to Research (http://rsc.acid.net.au/Main.aspx) , which was developed to support international graduate students studying at universities in Australia. First, the key features of the website are described. Second, the result of a pilot study involving 12 students and faculty members who tested key aspects of the design, content and functionality of the website and provided written and oral feedback base on task-based questions and focus group discussions are explored. Finally, recommendations for future development are presented. Results of the study indicate general student satisfaction with the website and its design, content and functionality, with specific areas identified for further development.

On the data consumption benefits of accepting increased uncertainty

In the context of learning paradigms of identification in the limit, we address the question: why is uncertainty sometimes desirable? We use mind change bounds on the output hypotheses as a measure of uncertainty and interpret ‘desirable’ as reduction in data memorization, also defined in terms of mind change bounds. The resulting model is closely related to iterative learning with bounded mind change complexity, but the dual use of mind change bounds — for hypotheses and for data — is a key distinctive feature of our approach. We show that situations exist where the more mind changes the learner is willing to accept, the less the amount of data it needs to remember in order to converge to the correct hypothesis. We also investigate relationships between our model and learning from good examples, set-driven, monotonic and strong-monotonic learners, as well as class-comprising versus class-preserving learnability.

Binang gurri: turning a deaf ear to indigenous hearing loss

Objective: This paper asks whether Indigenous health policies might be improved if governments listened to Indigenous voices, both Australian and those who drafted the Declaration on the Rights of Indigenous Peoples, 2007. Methods: A fundamental tenet of the Declaration, which Australia endorsed in 2009, is respect for Indigenous knowledge and voice. The author analyses legal, cultural and historical sources for evidence of this respect. The metaphorical and empirical framework of the analysis is the epidemic of otitis media among Indigenous children. Results: A survey of Indigenous advice about health clearly demonstrates that access to their land and respect for the diversity of Indigenous cultures should inform health policies. Despite, however, claiming to consult Indigenous peoples, policy-makers have not been listening. In many Indigenous languages not listening, or ‘bad ears’, has connotations of disrespect. Conclusions: By turning a deaf ear to Indigenous knowledge governments are undermining any respect Indigenous peoples may have for them and their policies. A new approach is needed. Implications: The Declaration on the Rights of Indigenous Peoples can provide federal, state and territory governments with benchmarks against which health policy can be developed and implemented. Authentic consultation could restore Indigenous confidence in government policies.

High-probability regret bounds for bandit online linear optimization

We present a modification of the algorithm of Dani et al. [8] for the online linear optimization problem in the bandit setting, which with high probability has regret at most O ∗ ( √ T) against an adaptive adversary. This improves on the previous algorithm [8] whose regret is bounded in expectation against an oblivious adversary. We obtain the same dependence on the dimension (n 3/2) as that exhibited by Dani et al. The results of this paper rest firmly on those of [8] and the remarkable technique of Auer et al. [2] for obtaining high probability bounds via optimistic estimates. This paper answers an open question: it eliminates the gap between the high-probability bounds obtained in the full-information vs bandit settings.

REGAL : a regularization based algorithm for reinforcement learning in weakly communicating MDPs

We provide an algorithm that achieves the optimal regret rate in an unknown weakly communicating Markov Decision Process (MDP). The algorithm proceeds in episodes where, in each episode, it picks a policy using regularization based on the span of the optimal bias vector. For an MDP with S states and A actions whose optimal bias vector has span bounded by H, we show a regret bound of ~ O(HS p AT ). We also relate the span to various diameter-like quantities associated with the MDP, demonstrating how our results improve on previous regret bounds.

Interactive peer-based learning in a comparative case study : what do students gain?

As English increasingly becomes one of the most commonly spoken languages in the world today for a variety of economic, social and cultural reasons, education is impacted by globalisation, the internationalisation of universities and the diversity of learners in classrooms. The challenge for educators is to find more effective ways of teaching English language so that students are better able to create meaning and communicate in the target language as well as to transform knowledge and understanding into relevant skills for a rapidly changing world. This research focuses broadly on English language education underpinned by social constructivist principles informing communicative language teaching and in particular, interactive peer learning approaches. An intervention of interactive peer-based learning in two case study contexts of English as Foreign Language (EFL) undergraduates in a Turkish university and English as Second Language (ESL) undergraduates in an Australian university investigates what students gain from the intervention. Methodology utilising qualitative data gathered from student reflective logs, focus group interviews and researcher field notes emphasises student voice. The cross case comparative study indicates that interactive peer-based learning enhances a range of learning outcomes for both cohorts including engagement, communicative competence, diagnostic feedback as well as assisting development of inclusive social relationships, civic skills, confidence and self efficacy. The learning outcomes facilitate better adaptation to a new learning environment and culture. An iterative instructional matrix tool is a useful product of the research for first year university experiences, teacher training, raising awareness of diversity, building learning communities, and differentiating the curriculum. The study demonstrates that English language learners can experience positive impact through peer-based learning and thus holds an influential key for Australian universities and higher education.

SAP webflow made configurable: unifying workflow templates into a configurable model

To facilitate the implementation of workflows, enterprise and workflow system vendors typically provide workflow templates for their software. Each of these templates depicts a variant of how the software supports a certain business process, allowing the user to save the effort of creating models and links to system components from scratch by selecting and activating the appropriate template. A combination of the strengths from different templates is however only achievable by manually adapting the templates which is cumbersome. We therefore suggest in this paper to combine different workflow templates into a single configurable workflow template. Using the workflow modeling language of SAP’s WebFlow engine, we show how such a configurable workflow modeling language can be created by identifying the configurable elements in the original language. Requirements imposed on configurations inhibit invalid configurations. Based on a default configuration such configurable templates can be used as easy as the traditional templates. The suggested approach is also applicable to other workflow modeling languages

A Virtual Evaluation Track for Cross Language Link Discovery

The Wikipedia has become the most popular online source of encyclopedic information. The English Wikipedia collection, as well as some other languages collections, is extensively linked. However, as a multilingual collection the Wikipedia is only very weakly linked. There are few cross-language links or cross-dialect links (see, for example, Chinese dialects). In order to link the multilingual-Wikipedia as a single collection, automated cross language link discovery systems are needed – systems that identify anchor-texts in one language and targets in another. The evaluation of Link Discovery approaches within the English version of the Wikipedia has been examined in the INEX Link the-Wiki track since 2007, whilst both CLEF and NTCIR emphasized the investigation and the evaluation of cross-language information retrieval. In this position paper we propose a new virtual evaluation track: Cross Language Link Discovery (CLLD). The track will initially examine cross language linking of Wikipedia articles. This virtual track will not be tied to any one forum; instead we hope it can be connected to each of (at least): CLEF, NTCIR, and INEX as it will cover ground currently studied by each. The aim is to establish a virtual evaluation environment supporting continuous assessment and evaluation, and a forum for the exchange of research ideas. It will be free from the difficulties of scheduling and synchronizing groups of collaborating researchers and alleviate the necessity to travel across the globe in order to share knowledge. We aim to electronically publish peer-reviewed publications arising from CLLD in a similar fashion: online, with open access, and without fixed submission deadlines.

The undirected feedback vertex set problem has a Poly(k) Kernel

Resolving a noted open problem, we show that the Undirected Feedback Vertex Set problem, parameterized by the size of the solution set of vertices, is in the parameterized complexity class Poly(k), that is, polynomial-time pre-processing is sufficient to reduce an initial problem instance (G, k) to a decision-equivalent simplified instance (G', k') where k' � k, and the number of vertices of G' is bounded by a polynomial function of k. Our main result shows an O(k11) kernelization bound.

The influence of cultural selection on strategic communication

Strategic communication is held to be a key process by which organisations respond to environmental uncertainty. In the received view articulated in the literatures of organisational communication and public relations, strategic communication results from collaborative efforts by organisational members to create shared understanding about environmental uncertainty and, as a result of this collective understanding, formulate appropriate communication responses. In this study, I explore how such collaborative efforts towards the development of strategic communication are derived from, and bounded by, culturally shared values and assumptions. Study of the influences of an organisation‟s culture on the formulation of strategic communication is a fundamental conceptual challenge for public relations and, to date, a largely unaddressed area of research. This thesis responds to this challenge by describing a key property of organisational culture – the action of cultural selection (Durham, 1992). I integrate this property of cultural selection to extend and refine the descriptive range of Weick‟s (1969, 1979) classic sociocultural model of organizing. From this integration I propose a new model, the Cultural Selection of Strategic Communication (CSSC). Underpinning the CSSC model is the central proposition that because of the action of cultural selection during organizing processes, the inherently conservative properties of an organisation‟s culture constrain development of effective strategic communication in ways that may be unrelated to the outcomes of “environmental scanning” and other monitoring functions heralded by the public relations literature as central to organisational adaptation. Thus, by examining the development of strategic communication, I describe a central conservative influence on the social ecology of organisations. This research also responds to Butschi and Steyn‟s (2006) call for the development of theory focusing on strategic communication as well as Grunig (2006) and Sriramesh‟s (2007) call for research to further understand the role of culture in public relations practice. In keeping with the explorative and descriptive goals of this study, I employ organisational ethnography to examine the influence of cultural selection on the development of strategic communication. In this methodological approach, I use the technique of progressive contextualisation to compare data from two related but distinct cultural settings. This approach provides a range of descriptive opportunities to permit a deeper understanding of the work of cultural selection. Findings of this study propose that culture, operating as a system of shared and socially transmitted social knowledge, acts through the property of cultural selection to influence decision making, and decrease conceptual variation within a group. The findings support the view that strategic communication, as a cultural product derived from the influence of cultural selection, is an essential feature to understand the social ecology of an organisation.

Fundus image registration algorithms for a pc-based image processing system

We have developed digital image registration program for a MC 68000 based fundus image processing system (FIPS). FIPS not only is capable of executing typical image processing algorithms in spatial as well as Fourier domain, the execution time for many operations has been made much quicker by using a hybrid of "C", Fortran and MC6000 assembly languages.