Self-organising zooms for decentralised redundancy management in visual sensor networks

When visual sensor networks are composed of cameras which can adjust the zoom factor of their own lens, one must determine the optimal zoom levels for the cameras, for a given task. This gives rise to an important trade-off between the overlap of the different cameras’ fields of view, providing redundancy, and image quality. In an object tracking task, having multiple cameras observe the same area allows for quicker recovery, when a camera fails. In contrast having narrow zooms allow for a higher pixel count on regions of interest, leading to increased tracking confidence. In this paper we propose an approach for the self-organisation of redundancy in a distributed visual sensor network, based on decentralised multi-objective online learning using only local information to approximate the global state. We explore the impact of different zoom levels on these trade-offs, when tasking omnidirectional cameras, having perfect 360-degree view, with keeping track of a varying number of moving objects. We further show how employing decentralised reinforcement learning enables zoom configurations to be achieved dynamically at runtime according to an operator’s preference for maximising either the proportion of objects tracked, confidence associated with tracking, or redundancy in expectation of camera failure. We show that explicitly taking account of the level of overlap, even based only on local knowledge, improves resilience when cameras fail. Our results illustrate the trade-off between maintaining high confidence and object coverage, and maintaining redundancy, in anticipation of future failure. Our approach provides a fully tunable decentralised method for the self-organisation of redundancy in a changing environment, according to an operator’s preferences.

Model Probability in Self-organising Maps

Growing models have been widely used for clustering or topology learning. Traditionally these models work on stationary environments, grow incrementally and adapt their nodes to a given distribution based on global parameters. In this paper, we present an enhanced unsupervised self-organising network for the modelling of visual objects. We first develop a framework for building non-rigid shapes using the growth mechanism of the self-organising maps, and then we define an optimal number of nodes without overfitting or underfitting the network based on the knowledge obtained from information-theoretic considerations. We present experimental results for hands and we quantitatively evaluate the matching capabilities of the proposed method with the topographic product.

Improving self organizing capabilities of local communities for sustainable development in decentralized Indonesia : the roles of procedural justice and social learning

The development planning process introduced under Law No. 25/2004 is said to be a better approach to increase public participation in decentralised Indonesia. This Law has introduced planning mechanisms, called Musyawarah Perencanaan Pembangunan (musrenbang), to provide a forum for development planning. In spite of the expressed intention of these mechanisms to improve public participation, some empirical observations have cast doubt on the outcomes. As a result, some local governments have tried to provide alternative mechanisms for participatory local development planning processes. Since planning constitutes one of the most effective ways to improve community empowerment, this paper aims to examine the extent to which the alternative local development planning process in Indonesia provides sufficient opportunities to improve the self organising capabilities of communities to sustain development programs to meet local needs. In so doing, this paper explores the key elements and approaches of the concept of community empowerment and shows how they can be incorporated within planning processes. Based on this, it then examines the problems encountered by musrenbang in increasing community empowerment. Having done this, it is argued that to change current unfavourable outcomes, procedural justice and social learning approaches need to be incorporated as pathways to community empowerment. Lastly the capacity of an alternative local planning process, called Sistem Dukungan (SISDUK), introduced in South Sulawesi, offering scope to incorporate procedural justice and social learning is explored as a means to improve the self organizing capabilities of local communities.

The roles of procedural justice and social learning in improving self organizing capabilities of local communities for sustainable development in decentralized Indonesia

The development planning process under Law No. 25/2004 is said to be a new approach to increase public participation in decentralised Indonesia. This Law has introduced planning mechanisms, called Musyawarah Perencanaan Pembangunan (Musrenbang), to provide a forum for development planning. In spite of the expressed intention of these mechanisms to improve public participation, some empirical observations have cast doubt on the outcomes. As a result, some local governments have tried to provide alternative mechanisms to promote for participation in local development planning. Since planning is often said to be one of the most effective ways to improve community empowerment, it is of particular concern, to examine the extent to which the current local development planning processes in Indonesia provide sufficient opportunities to improve the self organising capabilities of communities to sustain development programs to meet local needs. With this objective in mind, this paper examines problems encountered by the new local planning mechanism (Musrenbang) in increasing local community empowerment particularly regarding their self organising capabilities. The concept of community empowerment as a pathway to social justice is explored to identify its key elements and approaches and to show how they can be incorporated within planning processes. Having discussed this, it is then argued that to change current unfavorable outcomes, procedural justice and social learning approaches need to be adopted as pathways to community empowerment. Lastly it is also suggested that an alternative local planning process, called Sistem Dukungan (SISDUK), introduced in South Suluwezi in collaboration with JAICA in 2006 (?) offers scope to incorporate such procedural justice and social learning approaches to improve the self organizing capabilities of local communities.

Self-Organizing Maps of Molecular Descriptors for Sesquiterpene Lactones and Their Application to the Chemotaxonomy of the Asteraceae Family

The Asteraceae, one of the largest families among angiosperms, is chemically characterised by the production of sesquiterpene lactones (SLs). A total of 1,111 SLs, which were extracted from 658 species, 161 genera, 63 subtribes and 15 tribes of Asteraceae, were represented and registered in two dimensions in the SISTEMATX, an in-house software system, and were associated with their botanical sources. The respective 11 block of descriptors: Constitutional, Functional groups, BCUT, Atom-centred, 2D autocorrelations, Topological, Geometrical, RDF, 3D-MoRSE, GETAWAY and WHIM were used as input data to separate the botanical occurrences through self-organising maps. Maps that were generated with each descriptor divided the Asteraceae tribes, with total index values between 66.7% and 83.6%. The analysis of the results shows evident similarities among the Heliantheae, Helenieae and Eupatorieae tribes as well as between the Anthemideae and Inuleae tribes. Those observations are in agreement with systematic classifications that were proposed by Bremer, which use mainly morphological and molecular data, therefore chemical markers partially corroborate with these classifications. The results demonstrate that the atom-centred and RDF descriptors can be used as a tool for taxonomic classification in low hierarchical levels, such as tribes. Descriptors obtained through fragments or by the two-dimensional representation of the SL structures were sufficient to obtain significant results, and better results were not achieved by using descriptors derived from three-dimensional representations of SLs. Such models based on physico-chemical properties can project new design SLs, similar structures from literature or even unreported structures in two-dimensional chemical space. Therefore, the generated SOMs can predict the most probable tribe where a biologically active molecule can be found according Bremer classification.

Citizen Consultation from Above and Below : The Australian Perspective

In Australia, a range of Federal Government services have been provided online for some time, but direct, online citizen consultation and involvement in processes of governance is relatively new. Moves towards more extensive citizen involvement in legislative processes are now being driven in a “top-down” fashion by government agencies, or in a “bottom-up” manner by individuals and third-sector organisations. This chapter focusses on one example from each of these categories, as well as discussing the presence of individual politicians in online social networking spaces. It argues that only a combination of these approaches can achieve effective consultation between citizens and policymakers. Existing at a remove from government sites and the frameworks for public communication which govern them, bottom-up consultation tools may provide a better chance for functioning, self-organising user communities to emerge, but they are also more easily ignored by governments not directly involved in their running. Top-down consultation tools, on the other hand, may seem to provide a more direct line of communication to relevant government officials, but for that reason are also more likely to be swamped by users who wish simply to register their dissent rather than engage in discussion. The challenge for governments, politicians, and user communities alike is to develop spaces in which productive and undisrupted exchanges between citizens and policymakers can take place.

Dynamics of multi-articular coordination in neurobiological systems

Although previous work in nonlinear dynamics on neurobiological coordination and control has provided valuable insights from studies of single joint movements in humans, researchers have shown increasing interest in coordination of multi-articular actions. Multi-articular movement models have provided valuable insights on neurobiological systems conceptualised as degenerate, adaptive complex systems satisfying the constraints of dynamic environments. In this paper, we overview empirical evidence illustrating the dynamics of adaptive movement behavior in a range of multi-articular actions including kicking, throwing, hitting and balancing. We model the emergence of creativity and the diversity of neurobiological action in the meta-stable region of self organising criticality. We examine the influence on multi-articular actions of decaying and emerging constraints in the context of skill acquisition. We demonstrate how, in this context, transitions between preferred movement patterns exemplify the search for and adaptation of attractor states within the perceptual motor workspace as a function of practice. We conclude by showing how empirical analyses of neurobiological coordination and control have been used to establish a nonlinear pedagogical framework for enhancing acquisition of multi-articular actions.

The problem of measurement indeterminacy in complex neurobiological movement systems

In the study of complex neurobiological movement systems, measurement indeterminacy has typically been overcome by imposing artificial modelling constraints to reduce the number of unknowns (e.g., reducing all muscle, bone and ligament forces crossing a joint to a single vector). However, this approach prevents human movement scientists from investigating more fully the role, functionality and ubiquity of coordinative structures or functional motor synergies. Advancements in measurement methods and analysis techniques are required if the contribution of individual component parts or degrees of freedom of these task-specific structural units is to be established, thereby effectively solving the indeterminacy problem by reducing the number of unknowns. A further benefit of establishing more of the unknowns is that human movement scientists will be able to gain greater insight into ubiquitous processes of physical self-organising that underpin the formation of coordinative structures and the confluence of organismic, environmental and task constraints that determine the exact morphology of these special-purpose devices.

Robot navigation in sensor space

This thesis investigates the problem of robot navigation using only landmark bearings. The proposed system allows a robot to move to a ground target location specified by the sensor values observed at this ground target posi- tion. The control actions are computed based on the difference between the current landmark bearings and the target landmark bearings. No Cartesian coordinates with respect to the ground are computed by the control system. The robot navigates using solely information from the bearing sensor space. Most existing robot navigation systems require a ground frame (2D Cartesian coordinate system) in order to navigate from a ground point A to a ground point B. The commonly used sensors such as laser range scanner, sonar, infrared, and vision do not directly provide the 2D ground coordi- nates of the robot. The existing systems use the sensor measurements to localise the robot with respect to a map, a set of 2D coordinates of the objects of interest. It is more natural to navigate between the points in the sensor space corresponding to A and B without requiring the Cartesian map and the localisation process. Research on animals has revealed how insects are able to exploit very limited computational and memory resources to successfully navigate to a desired destination without computing Cartesian positions. For example, a honeybee balances the left and right optical flows to navigate in a nar- row corridor. Unlike many other ants, Cataglyphis bicolor does not secrete pheromone trails in order to find its way home but instead uses the sun as a compass to keep track of its home direction vector. The home vector can be inaccurate, so the ant also uses landmark recognition. More precisely, it takes snapshots and compass headings of some landmarks. To return home, the ant tries to line up the landmarks exactly as they were before it started wandering. This thesis introduces a navigation method based on reflex actions in sensor space. The sensor vector is made of the bearings of some landmarks, and the reflex action is a gradient descent with respect to the distance in sensor space between the current sensor vector and the target sensor vec- tor. Our theoretical analysis shows that except for some fully characterized pathological cases, any point is reachable from any other point by reflex action in the bearing sensor space provided the environment contains three landmarks and is free of obstacles. The trajectories of a robot using reflex navigation, like other image- based visual control strategies, do not correspond necessarily to the shortest paths on the ground, because the sensor error is minimized, not the moving distance on the ground. However, we show that the use of a sequence of waypoints in sensor space can address this problem. In order to identify relevant waypoints, we train a Self Organising Map (SOM) from a set of observations uniformly distributed with respect to the ground. This SOM provides a sense of location to the robot, and allows a form of path planning in sensor space. The navigation proposed system is analysed theoretically, and evaluated both in simulation and with experiments on a real robot.

The social role of design on collaborative destination branding : creating a new journey, a new story for the Waterfall Way, New South Wales, Australia.

This paper suggests that collaborative design can be an effective tool to promote social change. A co-design methodology and the results of its application in branding the Waterfall Way (New South Wales, Australia) as an eco- and nature-based tourism destination are presented as an example. The co-design exercise actively involved stakeholders in all stages of the design process, harnessing local tacit knowledge in relation to communication design, stimulating reflection upon what is special about the places, and consequently reinforcing a sense of belonging and the environmental and cultural conservation of place. The achieved results reflect the involvement and ownership of the community towards the design process. However, the application of a collaborative brand design methodology produced more than just a destination brand that is attractive to visitors, in line with local values, ways of living and the environment. It helped to catalyse a social network around tourism, triggering self-organising activity amongst stakeholders, who started to liaise with each other around the emergent regional identity - represented by the new brand they created together. The Waterfall Way branding process is a good example of social construction of shared understanding in and through design, showing that design exercises can have a significant social impact not only on the final product, but also on the realities of people involved in the process.

Silly Citizenship

This paper traces historical changes in the concept of citizenship, in order to show how it has shifted from a state enterprise to a form of self-organising, user-created, ludic association, modelled by online social networks in which children - formally non-citizens but crucial to the continuing and changing discursive practices of citizenship-formation - are active agents. The implications of this 'silly' citizenship for communication scholarship are considered.

A generative nervous system for the planet

Generative systems are now being proposed for addressing major ecological problems. The Complex Urban Systems Project (CUSP) founded in 2008 at the Queensland University of Technology, emphasises the ecological significance of the generative global networking of urban environments. It argues that the natural planetary systems for balancing global ecology are no longer able to respond sufficiently rapidly to the ecological damage caused by humankind and by dense urban conurbations in particular as evidenced by impacts such as climate change. The proposal of this research project is to provide a high speed generative nervous system for the planet by connecting major cities globally to interact directly with natural ecosystems to engender rapid ecological response. This would be achieved by active interactions of the global urban network with the natural ecosystem in the ecological principle of entropy. The key goal is to achieve ecologically positive cities by activating self-organising cities capable of full integration into natural eco-systems and to netowork the cities globally to provide the planet with a nervous system.