Design guidance using simulation-based Bayesian Belief Networks

In our work, the task of complex computer-based system design optimization involves exploration of a number of possible candidate designs matching the optimisation criteria. However, the process by which the possible candidate designs are generated and rated is fundamental to an optimal outcome. It is dependent upon the set of system characteristics deemed relevant by the designer given the systems requirements. We propose a method which is aimed at providing the designer with guidance based upon description of the possible causal relationships between various system characteristics and qualities. This guidance information is obtained by employing principles of multiparadigm simulation to generate a set of data which is then processed by an algorithm to generate a Bayesian Belief Network representation of causalities present in the source system. Furthermore, we address the issues and tools associated with application of the proposed method by presenting a detailed simulation and network generation effort undertaken as part of a significant industrial case study. © 2008 IEEE

Critique of network management systems and their practicality

Networks have become an integral part of the computing landscape, forming a global interconnection of a staggering number of heterogeneous systems and services. Current research focuses on policy based management and autonomous systems and involves the utilisation of very different languages and technologies in concert. This paper examines four current proposals for autonomous network management and analyses them using architectural modelling, against a measure of practicality, as expressed by scalability, reliability and maintainability. © 2010 IEEE

Towards an industry-collaborative, reflective software learning and development environment

A significant mismatch (88%) has been found between what employers and graduates perceived as important abilities and how universities had prepared graduates for employment. Conventional Teaching and Learning approaches fall short of providing the kind of learning experiences needed to prepare graduates for the realities of professional practice in industry. On the other hand, current students have very different learning styles than their forebears. Their learning preferences are experiential, working in teams, and using technology for learning. One solution to address this mismatch issue is the software development studio. Our aim is to provide an industry-collaborative, reflective learning environment that will effect the students development of holistic skills, such as teamwork, collaboration and communication, together with technical skills, in a discipline context. This paper further describes the design and validation via prototyping for our software development studio, the progress that we have made so far, and presents the preliminary insights gleaned from our studio prototyping. The prototypes raised issues of attitudinal change, communication, reflection, sharing, mentoring, use of process, `doing time, relationships and innovation

Architectural abstraction as transformation of poset labelled graphs

The design of large, complex computer based systems, based on their architecture, will benefit from a formal system that is intuitive, scalable and accessible to practitioners. The work herein is based in graphs which are an efficient and intuitive way of encoding structure, the essence of architecture. A model of system architectures and architectural abstraction is proposed, using poset labelled graphs and their transformations. The poset labelled graph formalism closely models several important aspects of architectures, namely topology, type and levels of abstraction. The technical merits of the formalism are discussed in terms of the ability to express and use domain knowledge to ensure sensible refinements. An abstraction / refinement calculus is introduced and illustrated with a detailed usage scenario. The paper concludes with an evaluation of the formalism in terms of its rigour, expressiveness, simplicity and practicality. © J.UCS

Things coming together: Learning experiences in a software studio

We have evidence that the software studio provides learning that genuinely prepares students for professional practice. Learning that entails dealing with complex technical problems and tools. Learning that involves working effectively in groups. Learning that results in the building of students'self-confidence and the conviction that they can successfully deal with the challenges of modern software system development. Learning that allows the accomplishment of the more elusive professional competencies. In order for students to achieve this type of deep learning, they need time to immerse themselves in complex problems within a rich environment - such as the software studio. The studio also enables each student group to develop and succeed according to their needs, and in different ways. The conclusions above arise from an ethnographic study in an undergraduate software studio prototype with two student groups and their mentors. Copyright © 2014 ACM

Smart communications network management through a synthesis of distributed intelligence and information

Demands on communications networks to support bundled, interdependent communications services (data, voice, video) are increasing in complexity. Smart network management techniques are required to meet this demand. Such management techniques are envisioned to be based on two main technologies: (i) embedded intelligence; and (ii) up-to-the-millisecond delivery of performance information. This paper explores the idea of delivery of intelligent network management as a synthesis of distributed intelligence and information, obtained through information mining of network performance. © 2008 International Federation for Information Processing

Managing the Enriched Experience Network - Learning-Outcome Approach to the Experimental Design Life-Cycle

Experimental design methods have long been used in scientific areas such as agriculture, biology and physics to minimise error and assure validity. Although most network researchers performing experiments with testbeds and simulations implicitly follow scientific method, until recently there has been little emphasis on improving experimental design methods. Traditional experimental design focuses on experiments where the scope and objectives are relatively constrained, however network research in innovative areas where there is little or no precedence often has changing objectives that evolve over time. We describe the learning-outcome approach to the experimental design life-cycle that applies the concepts of systems development life-cycle models used in software engineering, as well as learning taxonomies used in education. Our approach extends traditional experimental design by providing a more comprehensive and efficient way of decomposing an experimental research project into manageable stages that are designed rather than improvised, leading to a well-structured way of assessing the knowledge gained. We provide an insight into our experiences with this approach in the context of experimental research in management of Alcatel Australia's new-generation Enriched Experience Network

HL-1 cells express an inwardly rectifying K+ current activated via muscarinic receptors comparable to that in mouse atrial myocytes

An inwardly rectifying K^+ current is present in atrial cardiac myocytes that is activated by acetylcholine (I_{KACh}). Physiologically, activation of the current in the SA node is important in slowing the heart rate with increased parasympathetic tone. It is a paradigm for the direct regulation of signaling effectors by the Gβγ G-protein subunit. Many questions have been addressed in heterologous expression systems with less focus on the behaviour in native myocytes partly because of the technical difficulties in undertaking comparable studies in native cells. In this study, we characterise a potassium current in the atrial-derived cell line HL-1. Using an electrophysiological approach, we compare the characteristics of the potassium current with those in native atrial cells and in a HEK cell line expressing the cloned Kir3.1/3.4 channel. The potassium current recorded in HL-1 is inwardly rectifying and activated by the muscarinic agonist carbachol. Carbachol-activated currents were inhibited by pertussis toxin and tertiapin-Q. The basal current was time-dependently increased when GTP was substituted in the patch-clamp pipette by the non-hydrolysable analogue GTPγS. We compared the kinetics of current modulation in HL-1 with those of freshly isolated atrial mouse cardiomyocytes. The current activation and deactivation kinetics in HL-1 cells are comparable to those measured in atrial cardiomyocytes. Using immunofluorescence, we found GIRK4 at the membrane in HL-1 cells. Real-time RT-PCR confirms the presence of mRNA for the main G-protein subunits, as well as for M2 muscarinic and A1 adenosine receptors. The data suggest HL-1 cells are a good model to study IKAch