General theory of stigmergy : modelling stigma semantics

Stigmergy is a biological term used when discussing a sub-set of insect swarm-behaviour describing the apparent organisation seen during their activities. Stigmergy describes a communication mechanism based on environment-mediated signals which trigger responses among the insects. This phenomenon is demonstrated in the behavior of ants and their food gathering process when following pheromone trails, where the pheromones are a form of environment-mediated communication. What is interesting with this phenomenon is that highly organized societies are achieved without an apparent management structure. Stigmergy is also observed in human environments, both natural and engineered. It is implicit in the Web where sites provide a virtual environment supporting coordinative contributions. Researchers in varying disciplines appreciate the power of this phenomenon and have studied how to exploit it. As stigmergy becomes more widely researched we see its definition mutate as papers citing original work become referenced themselves. Each paper interprets these works in ways very specific to the research being conducted. Our own research aims to better understand what improves the collaborative function of a Web site when exploiting the phenomenon. However when researching stigmergy to develop our understanding we discover a lack of a standardized and abstract model for the phenomenon. Papers frequently cited the same generic descriptions before becoming intimately focused on formal specifications of an algorithm, or esoteric discussions regarding sub-facets of the topic. None provide a holistic and macro-level view to model and standardize the nomenclature. This paper provides a content analysis of influential literature documenting the numerous theoretical and experimental papers that have focused on stigmergy. We establish that stigmergy is a phenomenon that transcends the insect world and is more than just a metaphor when applied to the human world. We present from our own research our general theory and abstract model of semantics of stigma in stigmergy. We hope our model will clarify the nuances of the phenomenon into a useful road-map, and standardise vocabulary that we witness becoming confused and divergent. Furthermore, this paper documents the analysis on which we base our next paper: Special Theory of Stigmergy: A Design Pattern for Web 2.0 Collaboration.

Laser-radar data fusion with Gaussian Process Implicit Surfaces

This work considers the problem of building high-fidelity 3D representations of the environment from sensor data acquired by mobile robots. Multi-sensor data fusion allows for more complete and accurate representations, and for more reliable perception, especially when different sensing modalities are used. In this paper, we propose a thorough experimental analysis of the performance of 3D surface reconstruction from laser and mm-wave radar data using Gaussian Process Implicit Surfaces (GPIS), in a realistic field robotics scenario. We first analyse the performance of GPIS using raw laser data alone and raw radar data alone, respectively, with different choices of covariance matrices and different resolutions of the input data. We then evaluate and compare the performance of two different GPIS fusion approaches. The first, state-of-the-art approach directly fuses raw data from laser and radar. The alternative approach proposed in this paper first computes an initial estimate of the surface from each single source of data, and then fuses these two estimates. We show that this method outperforms the state of the art, especially in situations where the sensors react differently to the targets they perceive.

From “anytime, anywhere” to “here and now”: place and time restrictions in mobile narratives to enhance situated engagement of mobile users

The usage of the mobile Internet has increased tremendously within the last couple of years, and thereby the vision of accessing information anytime, anywhere has become more realistic and a dominant design principle for providing content. However, this study challenges this paradigm of unlimited and unrestricted access, and explores the question whether constraints and restrictions can positively influence the motivation and enticement of mobile users to engage with location-specific content. Restrictions, such as a particular time or location that gives a user access to content, may be used to foster participation and engagement, as well as to support content production and to enhance the user’s experience. In order to explore this, a Mobile Narrative and a Narrative Map have been created. For the former, the access to individual chapters of the story was restricted. Authors can specify constraints, such as a location or time, which need to be met by the reader if they want to read the story. This concept allows creative writers of the story to exploit the fact that the reader’s context is known, by intensifying the user experience and integrating this knowledge into the writing process. The latter, the Narrative Map, provides users with extracts from stories or information snippets about authors at relevant locations. In both concepts, a feedback channel was also integrated, on which location, time, and size constraints were imposed. In a user-centred design process involving authors and potential readers, those concepts have been implemented, followed by an evaluation comprising four user studies. The results show that restrictions and constraints can indeed lead to more enticing and engaging user experiences, and restricted contribution opportunities can lead to a higher motivation to participate as well as to an improved quality of submissions. These findings are relevant for future developments in the area of mobile narratives and creative writing, as well as for common mobile services that aim for enticing user experiences.

Traversability estimation for a planetary rover via experimental kernel learning in a Gaussian process framework

A critical requirement for safe autonomous navigation of a planetary rover is the ability to accurately estimate the traversability of the terrain. This work considers the problem of predicting the attitude and configuration angles of the platform from terrain representations that are often incomplete due to occlusions and sensor limitations. Using Gaussian Processes (GP) and exteroceptive data as training input, we can provide a continuous and complete representation of terrain traversability, with uncertainty in the output estimates. In this paper, we propose a novel method that focuses on exploiting the explicit correlation in vehicle attitude and configuration during operation by learning a kernel function from vehicle experience to perform GP regression. We provide an extensive experimental validation of the proposed method on a planetary rover. We show significant improvement in the accuracy of our estimation compared with results obtained using standard kernels (Squared Exponential and Neural Network), and compared to traversability estimation made over terrain models built using state-of-the-art GP techniques.

Motion planning and stochastic control with experimental validation on a planetary rover

Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is difficult due to the complex interaction between the platform and its environment. In this paper, we propose a motion planning approach whereby the outcome of control actions is learned from experience and represented statistically using a Gaussian process regression model. This model is used to construct a control policy for navigation to a goal region in a terrain map built using an on-board RGB-D camera. The terrain includes flat ground, small rocks, and non-traversable rocks. We report the results of 200 simulated and 35 experimental trials that validate the approach and demonstrate the value of considering control uncertainty in maintaining platform safety.

A probabilistic framework to monitor a multi-mode outdoor robot

This paper presents an approach to autonomously monitor the behavior of a robot endowed with several navigation and locomotion modes, adapted to the terrain to traverse. The mode selection process is done in two steps: the best suited mode is firstly selected on the basis of initial information or a qualitative map built on-line by the robot. Then, the motions of the robot are monitored by various processes that update mode transition probabilities in a Markov system. The paper focuses on this latter selection process: the overall approach is depicted, and preliminary experimental results are presented

Process modelling and simulation of tissue damage during mechanical peeling of pumpkin as a tough skinned vegetable

Food waste is a current challenge that both developing and developed countries face. This project applied a novel combination of available methods in Mechanical, agricultural and food engineering to address these challenges. A systematic approach was devised to investigate possibilities of reducing food waste and increasing the efficiency of industry by applying engineering concepts and theories including experimental, mathematical and computational modelling methods. This study highlights the impact of comprehensive understanding of agricultural and food material response to the mechanical operations and its direct relation to the volume of food wasted globally.

The Royal Commission into the NSW Police Service : process corruption and the limits of judicial reflexivity

This paper will offer an examination of the Reports of the Royal Commission into the NSW Police Service (Interim Report February 1996; Interim Report: Immediate Measures November 1996; Final Report Vol I: Corruption; Final Report Vol II: Reform; Final Report Vol III: Appendices May 1997) excluding the Report on Paedophilia, August 1997. The examination will be confined essentially to one question: to what extent do the published Reports consider the part played by the judiciary, prosecutors and lawyers, in the construction of a form of criminal justice revealed by the Commission itself, to be disfigured by serious process corruption? The examination will be conducted by way of a chronological trawl through the Reports of the Commission in an attempt to identify all references to the role of the judiciary, prosecutors and lawyers. The adequacy of any such treatment will then be considered. In order to set the scene a brief and generalised overview of the Wood Commission will be offered together with the Commission's definition of process corruption.

A multiscale road map of cancer spheroids : incorporating experimental and mathematical modelling to understand cancer progression

Computational models represent a highly suitable framework, not only for testing biological hypotheses and generating new ones but also for optimising experimental strategies. As one surveys the literature devoted to cancer modelling, it is obvious that immense progress has been made in applying simulation techniques to the study of cancer biology, although the full impact has yet to be realised. For example, there are excellent models to describe cancer incidence rates or factors for early disease detection, but these predictions are unable to explain the functional and molecular changes that are associated with tumour progression. In addition, it is crucial that interactions between mechanical effects, and intracellular and intercellular signalling are incorporated in order to understand cancer growth, its interaction with the extracellular microenvironment and invasion of secondary sites. There is a compelling need to tailor new, physiologically relevant in silico models that are specialised for particular types of cancer, such as ovarian cancer owing to its unique route of metastasis, which are capable of investigating anti-cancer therapies, and generating both qualitative and quantitative predictions. This Commentary will focus on how computational simulation approaches can advance our understanding of ovarian cancer progression and treatment, in particular, with the help of multicellular cancer spheroids, and thus, can inform biological hypothesis and experimental design.

Sectional analysis of the pollutant wash-off process based on runoff hydrograph

The validity of using rainfall characteristics as lumped parameters for investigating the pollutant wash-off process such as first flush occurrence is questionable. This research study introduces an innovative concept of using sector parameters to investigate the relationship between the pollutant wash-off process and different sectors of the runoff hydrograph and rainfall hyetograph. The research outcomes indicated that rainfall depth and rainfall intensity are two key rainfall characteristics which influence the wash-off process compared to the antecedent dry period. Additionally, the rainfall pattern also plays a critical role in the wash-off process and is independent of the catchment characteristics. The knowledge created through this research study provides the ability to select appropriate rainfall events for stormwater quality treatment design based on the required treatment outcomes such as the need to target different sectors of the runoff hydrograph or pollutant species. The study outcomes can also contribute to enhancing stormwater quality modelling and prediction in view of the fact that conventional approaches to stormwater quality estimation is primarily based on rainfall intensity rather than considering other rainfall parameters or solely based on stochastic approaches irrespective of the characteristics of the rainfall event.

Criminal Laws : Materials and Commentary on Criminal Law and Process in NSW [Fifth Edition]

"The success of Criminal Laws lies both in its distinctive features and in its appeal to a range of readerships. As one review put it, it is simultaneously a "textbook, casebook, handbook and reference work". As such it is ideal for criminal law and criminal justice courses as a teaching text, combining as it does primary sources with extensive critical commentary and a contextual perspective. It is likewise indispensable to practitioners for its detailed coverage of substantive law and its extensive references and inter-disciplinary approach make it a first point of call for researchers from all disciplines. This fifth edition strengthens these distinctive features. All chapters have been systematically updated to incorporate the plethora of legislative, case law, statistical and research material which has emerged since the previous edition. The critical, thematic, contextual and interdisciplinary perspectives have been continued."--Publisher's website. Table of Contents: 1. Some themes -- 2. Criminalisation -- 3. The criminal process -- 4. Components of criminal offences -- 5. Homicide: murder and involuntary manslaughter -- 6. Defences -- 7. Assault and sexual assault -- 8. Public order offences -- 9. Drugs offences -- 10. Dishonest acquisition -- 11. Extending criminal liability: complicity, conspiracy and association -- 12. Sentencing and penality.

A data analytics case study assessing factors affecting pavement deflection values

Road networks are a national critical infrastructure. The road assets need to be monitored and maintained efficiently as their conditions deteriorate over time. The condition of one of such assets, road pavement, plays a major role in the road network maintenance programmes. Pavement conditions depend upon many factors such as pavement types, traffic and environmental conditions. This paper presents a data analytics case study for assessing the factors affecting the pavement deflection values measured by the traffic speed deflectometer (TSD) device. The analytics process includes acquisition and integration of data from multiple sources, data pre-processing, mining useful information from them and utilising data mining outputs for knowledge deployment. Data mining techniques are able to show how TSD outputs vary in different roads, traffic and environmental conditions. The generated data mining models map the TSD outputs to some classes and define correction factors for each class.

The consultative process used in outreach : a narrative account

Aim The aim of this paper was to provide a narrative account of the communication skills used in an effective outreach consultation utilizing Neighbour’s consultative model. Other consultation models were considered; however, because of their overly comprehensive approach or emphasis on behaviour modification, these were deemed inappropriate. Background The nursing profession has endured significant changes of late and as a result is developing more autonomous roles in both the community and the acute health care settings. In the past, the term consultancy was used within the medical context; nowadays, there are advance nurse practitioners for whom consultancy is an integral part of their role. Although every nursing interaction is in essence a consultation, the fact that nurses are taking up on new advanced roles highlights the necessity for nurses to develop their consultation skills even further. Therefore, it makes sense to explore what aspects of that consultancy role needs special consideration in order to ensure that positive outcomes are achieved. Conclusions This paper has used a narrative account to uncover those salient skills needed to enhance the therapeutic relationship with a patient requiring the services of outreach. Furthermore, the application of a recognized consultation model was used to elucidate the underpinning knowledge of systematic history taking and assessment as well as demonstrating the communication skills and strategies needed to increase the patient’s participation and empowerment throughout the consultation. Relevance to clinical practice Effective communication skills encompassed in a consultative model are integral to the success in safeguarding the well-being of patients requiring advanced levels of care. Prejudging or pre-empting information being conveyed can be detrimental to patient safety and may prolong or complicate treatment plans.

Impact of passenger group dynamics on an airport evacuation process using an agent-based model

The safety of passengers is a major concern to airports. In the event of crises, having an effective and efficient evacuation process in place can significantly aid in enhancing passenger safety. Hence, it is necessary for airport operators to have an in-depth understanding of the evacuation process of their airport terminal. Although evacuation models have been used in studying pedestrian behaviour for decades, little research has been done in considering the evacuees’ group dynamics and the complexity of the environment. In this paper, an agent-based model is presented to simulate passenger evacuation process. Different exits were allocated to passengers based on their location and security level. The simulation results show that the evacuation time can be influenced by passenger group dynamics. This model also provides a convenient way to design airport evacuation strategy and examine its efficiency. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.

A novel process of group-oriented question reduction for rule-based recommendation websites

Several websites utilise a rule-base recommendation system, which generates choices based on a series of questionnaires, for recommending products to users. This approach has a high risk of customer attrition and the bottleneck is the questionnaire set. If the questioning process is too long, complex or tedious; users are most likely to quit the questionnaire before a product is recommended to them. If the questioning process is short; the user intensions cannot be gathered. The commonly used feature selection methods do not provide a satisfactory solution. We propose a novel process combining clustering, decisions tree and association rule mining for a group-oriented question reduction process. The question set is reduced according to common properties that are shared by a specific group of users. When applied on a real-world website, the proposed combined method outperforms the methods where the reduction of question is done only by using association rule mining or only by observing distribution within the group.