Simplified computation and generalization of the refined process structure tree

A business process is often modeled using some kind of a directed flow graph, which we call a workflow graph. The Refined Process Structure Tree (RPST) is a technique for workflow graph parsing, i.e., for discovering the structure of a workflow graph, which has various applications. In this paper, we provide two improvements to the RPST. First, we propose an alternative way to compute the RPST that is simpler than the one developed originally. In particular, the computation reduces to constructing the tree of the triconnected components of a workflow graph in the special case when every node has at most one incoming or at most one outgoing edge. Such graphs occur frequently in applications. Secondly, we extend the applicability of the RPST. Originally, the RPST was applicable only to graphs with a single source and single sink such that the completed version of the graph is biconnected. We lift both restrictions. Therefore, the RPST is then applicable to arbitrary directed graphs such that every node is on a path from some source to some sink. This includes graphs with multiple sources and/or sinks and disconnected graphs.

Flexible service systems

Service science combines scientific, management, and engineering disciplines to improve the understanding of how service systems cooperate to create business value. Service systems are complex configurations of people, technologies, and resources that coexist in a common environment of service provisioning. While the general concepts of service science are understood and agreed upon, the representation of service systems using models is still in its infancy. In this chapter, we look at business processes and their role in properly representing service systems. We propose flexible process graphs, a high-level process modeling language, and extend it in order to specify service systems and their compositions within shared environments in a flexible way. The discussion in this chapter is the first step towards a formal description of service science environment, including service systems, networks, and whole ecology.

Hypergraph-based modeling of ad-hoc business processes

Process models are usually depicted as directed graphs, with nodes representing activities and directed edges control flow. While structured processes with pre-defined control flow have been studied in detail, flexible processes including ad-hoc activities need further investigation. This paper presents flexible process graph, a novel approach to model processes in the context of dynamic environment and adaptive process participants’ behavior. The approach allows defining execution constraints, which are more restrictive than traditional ad-hoc processes and less restrictive than traditional control flow, thereby balancing structured control flow with unstructured ad-hoc activities. Flexible process graph focuses on what can be done to perform a process. Process participants’ routing decisions are based on the current process state. As a formal grounding, the approach uses hypergraphs, where each edge can associate any number of nodes. Hypergraphs are used to define execution semantics of processes formally. We provide a process scenario to motivate and illustrate the approach.

Semantic search as inference : applications in health informatics

This thesis developed new search engine models that elicit the meaning behind the words found in documents and queries, rather than simply matching keywords. These new models were applied to searching medical records: an area where search is particularly challenging yet can have significant benefits to our society.

Hydrogen-bonded two- and three-dimensional polymeric structures in the ammonium salts of 3,5-dinitrobenzoic acid, 4-nitrobenzoic acid and 2,4-dichlorobenzoic acid

The structures of the ammonium salts of 3,5-dinitrobenzoic acid, NH4+ C7H3N2O6- (I), 4-nitrobenzoic acid, NH4+ C7H4N2O4- . 2H2O (II) and 2,4-dichlorobenzoic acid, NH4+ C7H3Cl2O2- . 0.5H2O (III), have been determined and their hydrogen-bonded structures are described. All salts form hydrogen-bonded polymeric structures, three-dimensional in (I) and two-dimensional in (II) and (III). With (I), a primary cation-anion cyclic association is formed [graph set R3/4(10)] through N-H...O hydrogen bonds, involving a carboxyl O,O' group on one side and a single carboxyl O-atom on the other. Structure extension involves both N-H...O hydrogen bonds to both carboxyl and nitro O-atom acceptors. With structure (II), the primary inter-species interactions and structure extension into layers lying parallel to (0 0 1) are through conjoined cyclic hydrogen-bonding motifs: R3/4(10) [one cation, a carboxyl (O,O') group and two water molecules] and centrosymmetric R2/4(8) [two cations and two water molecules]. The structure of (III) also has conjoined R3/4(10) and centrosymmetric R2/4(8) motifs in the layered structure but these differ in that he first involves one cation, a carboxyl (O,O') as well as a carboxyl (O) group and one water molecule, the second, two cations and two carboxyl O-groups. The layers lie parallel to (1 0 0). The structures of the salt hydrates (II) and (III) reported in this work, giving two-dimensional layered arrays through conjoined hydrogen-bonded nets provide further illustrations of a previously indicated trend among ammonium salts of carboxylic acids, but the anhydrous three-dimensional structure of (I) is inconsistent.

Dictionary learning and sparse coding on Grassmann manifolds : an extrinsic solution

Recent advances in computer vision and machine learning suggest that a wide range of problems can be addressed more appropriately by considering non-Euclidean geometry. In this paper we explore sparse dictionary learning over the space of linear subspaces, which form Riemannian structures known as Grassmann manifolds. To this end, we propose to embed Grassmann manifolds into the space of symmetric matrices by an isometric mapping, which enables us to devise a closed-form solution for updating a Grassmann dictionary, atom by atom. Furthermore, to handle non-linearity in data, we propose a kernelised version of the dictionary learning algorithm. Experiments on several classification tasks (face recognition, action recognition, dynamic texture classification) show that the proposed approach achieves considerable improvements in discrimination accuracy, in comparison to state-of-the-art methods such as kernelised Affine Hull Method and graph-embedding Grassmann discriminant analysis.

Joint 2D and 3D cues for image segmentation towards robotic applications

This thesis investigates the fusion of 3D visual information with 2D image cues to provide 3D semantic maps of large-scale environments in which a robot traverses for robotic applications. A major theme of this thesis was to exploit the availability of 3D information acquired from robot sensors to improve upon 2D object classification alone. The proposed methods have been evaluated on several indoor and outdoor datasets collected from mobile robotic platforms including a quadcopter and ground vehicle covering several kilometres of urban roads.

Food security

INTRODUCTION Globally, one-third of food production is lost annually due to negligent authorities. India alone loses some 21 million tonnes of wheat per year even while it has 200 million food-insecure people in the nation. Disturbingly provocative as it may sound, it is amazing how national and international institutions and governments make use of human hunger for their own survival (Raghib 2013). The global food system is increasingly insecure. Challenges to long-term global food security are encapsulated by resource scarcity, environmental degradation, biodiversity loss, climate change, reductions of farm labour and a growing world population. These issues are caused and aggravated by the spread of corporatised and monopolised food systems, dietary change, and urbanisation. These factors have rapidly brought food insecurity under the umbrella of unconventional security threats (Heukelom 2011). For some, humanitarian crises associated with food insecurity, or what has been dubbed ‘the silent tsunami’, is a pending peril, notably for the world’s poorest and most vulnerable people. For others, the food production industry is an emerging market with unprecedented profits. Despite this problem of food scarcity we are witnessing extraordinary ‘food wastage’, notably in North America and Europe, on a scale that would reportedly be capable of feeding the world’s hungry six times over (Stuart 2012). As the opening quotation to this chapter suggests, governments and corporations are deeply involved in the contexts, politics, and resources associated with food related issues. As many economically developed and advanced industrial nations are reporting a rise out of recession, announcements are made by the world’s richest countries that they are to cut $US2 billion per year from food aid. The head of the World Food Aid Programme, Rosette Sheeran, warns that such cuts could result in ‘the loss of a generation’ (Walters 2011). The global food crisis has also reinvigorated debates about agricultural development and genetically modified (GM) food; as well as fuelling debates about poverty, debt and security. This chapter provides a discussion of the political economy of global food debates and explores the threats and opportunities surrounding food production and future food security.

A sparse hybrid map for vision-guided mobile robots

This paper introduces a minimalistic approach to produce a visual hybrid map of a mobile robot’s working environment. The proposed system uses omnidirectional images along with odometry information to build an initial dense posegraph map. Then a two level hybrid map is extracted from the dense graph. The hybrid map consists of global and local levels. The global level contains a sparse topological map extracted from the initial graph using a dual clustering approach. The local level contains a spherical view stored at each node of the global level. The spherical views provide both an appearance signature for the nodes, which the robot uses to localize itself in the environment, and heading information when the robot uses the map for visual navigation. In order to show the usefulness of the map, an experiment was conducted where the map was used for multiple visual navigation tasks inside an office workplace.

The slumbarumba jumbuck problem

The potential for simple linear relationships arising from a computer game to build student modelling and "world problem" skills is explored. The fundamental capability of the spreadsheet to tabulate and graph possible solutions is used to lay bare the problem structure for the students.

Crossword puzzle attack on NLS

NLS is one of the stream ciphers submitted to the eSTREAM project. We present a distinguishing attack on NLS by Crossword Puzzle (CP) attack method which is introduced in this paper. We build the distinguisher by using linear approximations of both the non-linear feedback shift register (NFSR) and the nonlinear filter function (NLF). Since the bias of the distinguisher depends on the Konst value, which is a key-dependent word, we present the graph showing how the bias of distinguisher vary with Konst. In result, we estimate the bias of the distinguisher to be around O(2^−30). Therefore, we claim that NLS is distinguishable from truly random cipher after observing O(2^60) keystream words. The experiments also show that our distinguishing attack is successful on 90.3% of Konst among 2^32 possible values. We extend the CP attack to NLSv2 which is a tweaked version of NLS. In result, we build a distinguisher which has the bias of around 2− 48. Even though this attack is below the eSTREAM criteria (2^−40), the security margin of NLSv2 seems to be too low.

Cut here : reshaping the ABC

Monday’s announcement that the ABC will make 80 positions redundant is just the latest move in an enforced process of change to the public service broadcaster. It has a long way yet to run. The announcement finally put the lie to Tony Abbott’s election eve pledge, live on national television, that there would be “no cuts to the ABC or SBS”. In concert with other recent announcements, it seems clear that public broadcasting – and in particular the ABC – is squarely in the government’s sights.

On secure multi-party computation in black-box groups

We study the natural problem of secure n-party computation (in the passive, computationally unbounded attack model) of the n-product function f G (x 1,...,x n ) = x 1 ·x 2 ⋯ x n in an arbitrary finite group (G,·), where the input of party P i is x i  ∈ G for i = 1,...,n. For flexibility, we are interested in protocols for f G which require only black-box access to the group G (i.e. the only computations performed by players in the protocol are a group operation, a group inverse, or sampling a uniformly random group element). Our results are as follows. First, on the negative side, we show that if (G,·) is non-abelian and n ≥ 4, then no ⌈n/2⌉-private protocol for computing f G exists. Second, on the positive side, we initiate an approach for construction of black-box protocols for f G based on k-of-k threshold secret sharing schemes, which are efficiently implementable over any black-box group G. We reduce the problem of constructing such protocols to a combinatorial colouring problem in planar graphs. We then give two constructions for such graph colourings. Our first colouring construction gives a protocol with optimal collusion resistance t < n/2, but has exponential communication complexity O(n*2t+1^2/t) group elements (this construction easily extends to general adversary structures). Our second probabilistic colouring construction gives a protocol with (close to optimal) collusion resistance t < n/μ for a graph-related constant μ ≤ 2.948, and has efficient communication complexity O(n*t^2) group elements. Furthermore, we believe that our results can be improved by further study of the associated combinatorial problems.

Pro bono partnerships in environmental law : enhancing outcomes for universities and CLCs

CLE can be a life-changing event in a law student’s education. It can open their eyes to the day-to-day operation of justice and provide them with examples of possible career paths they may never have thought existed. Yet it can also provide long-term benefits for CLCs and academics. Recent CLE models have moved towards partnerships with external organisations and away from on-site legal clinics. Some examples have exhibited success with a multidisciplinary approach involving students from non-law disciplines to provide a holistic approach to a CLC’s needs. Such a multidisciplinary approach is of particular benefit in community lawyering clinics where students are engaged in social change lawyering. The QUT/EDO partnership presents a new model in the environmental clinic landscape in Australia. Initial feedback suggests that the clinic has assisted students in gaining insight into the access to justice issues arising from mining activities and to raise the level of understanding and awareness among community members of their legal rights to protect the environment. Looking at ways to increase partnerships between universities and CLCs is of vital importance in the future, given recent federal government CLC funding cuts. The legal clinic model has great potential to evolve and contribute in ensuring the continued operation of legal initiatives to protect the environment in the public interest.

Development of gas sensing technology for ground and airborne applications powered by solar energy : methodology and experimental results

Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.