A cybernetic approach to land management issues

This work is a digital version of a dissertation that was first submitted in partial fulfillment of the Degree of Doctor of Philosophy at the Queensland University of Technology (QUT) in March 1994. The work was concerned with problems of self-organisation and organisation ranging from local to global levels of hierarchy. It considers organisations as living entities from local to global things that a living entity – more particularly, an individual, a body corporate or a body politic - must know and do to maintain an existence – that is to remain viable – or to be sustainable. The term ‘land management’ as used in 1994 was later subsumed into a more general concept of ‘natural resource management’ and then merged with ideas about sustainable socioeconomic and sustainable ecological development. The cybernetic approach contains many cognitive elements of human observation, language and learning that combine into production processes. The approach tends to highlight instances where systems (or organisations) can fail because they have very little chance of succeeding. Thus there are logical necessities as well as technical possibilities in designing, constructing, operating and maintaining production systems that function reliably over extended periods. Chapter numbers and titles to the original thesis are as follows: 1. Land management as a problem of coping with complexity 2. Background theory in systems theory and cybernetic principles 3. Operationalisation of cybernetic principles in Beer’s Viable System Model 4. Issues in the design of viable cadastral surveying and mapping organisation 5. An analysis of the tendency for fragmentation in surveying and mapping organisation 6. Perambulating the boundaries of Sydney – a problem of social control under poor standards of literacy 7. Cybernetic principles in the process of legislation 8. Closer settlement policy and viability in agricultural production 9. Rate of return in leasing Crown lands

Integrating information security policy management with corporate risk management for strategic alignment

Information security policy defines the governance and implementation strategy for information security in alignment with the corporate risk policy objectives and strategies. Research has established that alignment between corporate concerns may be enhanced when strategies are developed concurrently using the same development process as an integrative relationship is established. Utilizing the corporate risk management framework for security policy management establishes such an integrative relationship between information security and corporate risk management objectives and strategies. There is however limitation in the current literature on presenting a definitive approach that fully integrates security policy management with the corporate risk management framework. This paper presents an approach that adopts a conventional corporate risk management framework for security policy development and management to achieve alignment with the corporate risk policy. A case example is examined to illustrate the alignment achieved in each process step with a security policy structure being consequently derived in the process. It is shown that information security policy management outcomes become both integral drivers and major elements of the corporate-level risk management considerations. Further study should involve assessing the impact of the use of the proposed framework in enhancing alignment as perceived in this paper.

Application of reinforcement learning in an open railway access market price negotiation

In an open railway access market price negotiation, it is feasible to achieve higher cost recovery by applying the principles of price discrimination. The price negotiation can be modeled as an optimization problem of revenue intake. In this paper, we present the pricing negotiation based on reinforcement learning model. A negotiated-price setting technique based on agent learning is introduced, and the feasible applications of the proposed method for open railway access market simulation are discussed.

Scheduling coordination through negotiation between train service providers in an open railway access market

A schedule coordination problem involving two train services provided by different operators is modeled as an optimization of revenue intake. The coordination is achieved through the adjustment of commencement times of the train services by negotiation. The problem is subject to constraints regarding to passenger demands and idle costs of rolling-stocks from both operators. This paper models the operators as software agents having the flexibility to incorporate one of the two (and potentially more) proposed negotiation strategies. Empirical results show that agents employing different combination of strategies have significant impact on the quality of solution and negotiation time.

A prioritised fuzzy constraint satisfaction approach to model agent negotiation for railway scheduling

With the recent regulatory reforms in a number of countries, railways resources are no longer managed by a single party but are distributed among different stakeholders. To facilitate the operation of train services, a train service provider (SP) has to negotiate with the infrastructure provider (IP) for a train schedule and the associated track access charge. This paper models the SP and IP as software agents and the negotiation as a prioritized fuzzy constraint satisfaction (PFCS) problem. Computer simulations have been conducted to demonstrate the effects on the train schedule when the SP has different optimization criteria. The results show that by assigning different priorities on the fuzzy constraints, agents can represent SPs with different operational objectives.

Output feedback control of discrete-time systems in networked environments

This correspondence paper addresses the problem of output feedback stabilization of control systems in networked environments with quality-of-service (QoS) constraints. The problem is investigated in discrete-time state space using Lyapunov’s stability theory and the linear inequality matrix technique. A new discrete-time modeling approach is developed to describe a networked control system (NCS) with parameter uncertainties and nonideal network QoS. It integrates a network-induced delay, packet dropout, and other network behaviors into a unified framework. With this modeling, an improved stability condition, which is dependent on the lower and upper bounds of the equivalent network-induced delay, is established for the NCS with norm-bounded parameter uncertainties. It is further extended for the output feedback stabilization of the NCS with nonideal QoS. Numerical examples are given to demonstrate the main results of the theoretical development.

Multi-objective four-dimensional vehicle motion planning in large dynamic environments

This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.

Automatically detecting pain in video through facial action units

In a clinical setting, pain is reported either through patient self-report or via an observer. Such measures are problematic as they are: 1) subjective, and 2) give no specific timing information. Coding pain as a series of facial action units (AUs) can avoid these issues as it can be used to gain an objective measure of pain on a frame-by-frame basis. Using video data from patients with shoulder injuries, in this paper, we describe an active appearance model (AAM)-based system that can automatically detect the frames in video in which a patient is in pain. This pain data set highlights the many challenges associated with spontaneous emotion detection, particularly that of expression and head movement due to the patient's reaction to pain. In this paper, we show that the AAM can deal with these movements and can achieve significant improvements in both the AU and pain detection performance compared to the current-state-of-the-art approaches which utilize similarity-normalized appearance features only.

A new and efficient intelligent collaboration scheme for fashion design

Technology-mediated collaboration process has been extensively studied for over a decade. Most applications with collaboration concepts reported in the literature focus on enhancing efficiency and effectiveness of the decision-making processes in objective and well-structured workflows. However, relatively few previous studies have investigated the applications of collaboration schemes to problems with subjective and unstructured nature. In this paper, we explore a new intelligent collaboration scheme for fashion design which, by nature, relies heavily on human judgment and creativity. Techniques such as multicriteria decision making, fuzzy logic, and artificial neural network (ANN) models are employed. Industrial data sets are used for the analysis. Our experimental results suggest that the proposed scheme exhibits significant improvement over the traditional method in terms of the time–cost effectiveness, and a company interview with design professionals has confirmed its effectiveness and significance.

Maintenance chain integration using Petri-net enabled multiagent system modeling and implementation approach

Engineering asset management (EAM) is a broad discipline and the EAM functions and processes are characterized by its distributed nature. However, engineering asset nowadays mostly relies on self-maintained experiential rule bases and periodic maintenance, which is lacking a collaborative engineering approach. This research proposes a collaborative environment integrated by a service center with domain expertise such as diagnosis, prognosis, and asset operations. The collaborative maintenance chain combines asset operation sites, service center (i.e., maintenance operation coordinator), system provider, first tier collaborators, and maintenance part suppliers. Meanwhile, to realize the automation of communication and negotiation among organizations, multiagent system (MAS) technique is applied to enhance the entire service level. During the MAS design processes, this research combines Prometheus MAS modeling approach with Petri-net modeling methodology and unified modeling language to visualize and rationalize the design processes of MAS. The major contributions of this research include developing a Petri-net enabled Prometheus MAS modeling methodology and constructing a collaborative agent-based maintenance chain framework for integrated EAM.

Demand-compliant design

In this paper, we describe, in detail, a design method that assures that the designed product satisfies a set of prescribed demands while, at the same time, providing a concise representation of the design that facilitates communication in multidisciplinary design teams. This Demand Compliant Design (DeCoDe) method was in itself designed to comply with a set of demands. The demands on the method were determined by an analysis of some of the most widely used design methods and from the needs arising in the practice of design for quality. We show several modes of use of the DeCoDe method and illustrate with examples.

Enterprise information security policy assessment : an extended framework for metrics development utilising the goal-question-metric approach

Effective enterprise information security policy management requires review and assessment activities to ensure information security policies are aligned with business goals and objectives. As security policy management involves the elements of policy development process and the security policy as output, the context for security policy assessment requires goal-based metrics for these two elements. However, the current security management assessment methods only provide checklist types of assessment that are predefined by industry best practices and do not allow for developing specific goal-based metrics. Utilizing theories drawn from literature, this paper proposes the Enterprise Information Security Policy Assessment approach that expands on the Goal-Question-Metric (GQM) approach. The proposed assessment approach is then applied in a case scenario example to illustrate a practical application. It is shown that the proposed framework addresses the requirement for developing assessment metrics and allows for the concurrent undertaking of process-based and product-based assessment. Recommendations for further research activities include the conduct of empirical research to validate the propositions and the practical application of the proposed assessment approach in case studies to provide opportunities to introduce further enhancements to the approach.

The enterprise information security policy as a strategic business policy within the corporate strategic plan (extended abstract)

Information security has been recognized as a core requirement for corporate governance that is expected to facilitate not only the management of risks, but also as a corporate enabler that supports and contributes to the sustainability of organizational operations. In implementing information security, the enterprise information security policy is the set of principles and strategies that guide the course of action for the security activities and may be represented as a brief statement that defines program goals and sets information security and risk requirements. The enterprise information security policy (alternatively referred to as security policy in this paper) that represents the meta-policy of information security is an element of corporate ICT governance and is derived from the strategic requirements for risk management and corporate governance. Consistent alignment between the security policy and the other corporate business policies and strategies has to be maintained if information security is to be implemented according to evolving business objectives. This alignment may be facilitated by managing security policy alongside other corporate business policies within the strategic management cycle. There are however limitations in current approaches for developing and managing the security policy to facilitate consistent strategic alignment. This paper proposes a conceptual framework for security policy management by presenting propositions to positively affect security policy alignment with business policies and prescribing a security policy management approach that expounds on the propositions.

In the pursuit of effective affective computing : the relationship between features and registration

For facial expression recognition systems to be applicable in the real world, they need to be able to detect and track a previously unseen person's face and its facial movements accurately in realistic environments. A highly plausible solution involves performing a "dense" form of alignment, where 60-70 fiducial facial points are tracked with high accuracy. The problem is that, in practice, this type of dense alignment had so far been impossible to achieve in a generic sense, mainly due to poor reliability and robustness. Instead, many expression detection methods have opted for a "coarse" form of face alignment, followed by an application of a biologically inspired appearance descriptor such as the histogram of oriented gradients or Gabor magnitudes. Encouragingly, recent advances to a number of dense alignment algorithms have demonstrated both high reliability and accuracy for unseen subjects [e.g., constrained local models (CLMs)]. This begs the question: Aside from countering against illumination variation, what do these appearance descriptors do that standard pixel representations do not? In this paper, we show that, when close to perfect alignment is obtained, there is no real benefit in employing these different appearance-based representations (under consistent illumination conditions). In fact, when misalignment does occur, we show that these appearance descriptors do work well by encoding robustness to alignment error. For this work, we compared two popular methods for dense alignment-subject-dependent active appearance models versus subject-independent CLMs-on the task of action-unit detection. These comparisons were conducted through a battery of experiments across various publicly available data sets (i.e., CK+, Pain, M3, and GEMEP-FERA). We also report our performance in the recent 2011 Facial Expression Recognition and Analysis Challenge for the subject-independent task.