Evidencing learning outcomes: a multi-level, multi-dimensional course alignment model

This conceptual framework proposes a multi-level, multi-dimensional course alignment model to implement a contextualised constructive alignment of rubric design that authentically evidences and assesses learning outcomes. By embedding quality control mechanisms at each level for each dimension, this model facilitates the development of an aligned curriculum. The use of rubrics is a crucial theme for many higher education institutions owing to the binding requirement by universities to provide evidence to quality assurance agencies. The success of evidencing learning outcomes through rubrics, however, is only one piece of the puzzle. The other is the contextualised constructive alignment of intertwined factors. Despite the significance of embedding these factors, there has been little, if any, systematic framework in this area. The two key instrumental forces underpinning the conception of this model are: seeking external accreditation and the implementation of programme enhancement thus realising the strategic agenda for an Australian university.

Information discovery in multi-dimensional autonomous wireless sensor networks

 The thesis proposed four novel algorithms of information discovery for Multidimensional Autonomous Wireless Sensor Networks (WSNs) that can significantly increase network lifetime and minimize query processing latency, resulting in quality of service improvements that are of immense benefit to Multidimensional Autonomous WSNs are deployed in complex environments (e.g., mission-critical applications).

Multi-dimensional liquid chromatography and metabolomics, are two dimensions better than one?

 While data processing methods in metabolomic studies often work with 'n' number of dimensions, analytical techniques, with the notable exception of NMR, have mostly stuck only to one. Peak overlap continues to be a problem and there is an ever-present demand to maximize the number of metabolites that can be separated and identified in a single run. One method that might help to overcome these issues is multidimensional liquid chromatography, which uses two columns of different phases. A sequential collection of aliquots is made from the first column and reinjected onto a second, and the resulting data are then plotted in 2D or 3D space. The total peak capacity of such a system is the combined peak capacities of each column. The 'offline' version of this technique, using a fraction collector, was introduced over 30 years ago but with recent advances in instrumentation and software, particularly the 'online' approach using automated switching valves, has led to increasing interest in the technique. Both offline and online methods can be carried out as a comprehensive procedure, or via 'heart-cutting', in which only specific peaks are analysed in the second dimension. Past applications include proteomics, natural product chemistry, forensic science and pharmaceutical analysis. These successes are likely to be built on in the future as new column chemistries and bio-informatic approaches are developed. In this review an overview of the theory of twodimensional liquid chromatography is presented, its potential in the field of metabolomics is assessed and predictions for future research directions are made.

Functional observer design with application to pre-compensated multi-variable systems

Partial state estimation of dynamical systems provides significant advantages in practical applications. Likewise, pre-compensator design for multi variable systems invokes considerable increase in the order of the original system. Hence, applying functional observer to pre-compensated systems can result in lower computational costs and more practicability in some applications such as fault diagnosis and output feedback control of these systems. In this note, functional observer design is investigated for pre-compensated systems. A lower order pre-compensator is designed based on a H2 norm optimization that is designed as the solution of a set of linear matrix inequalities (LMIs). Next, a minimum order functional observer is designed for the pre-compensated system. An LTI model of an irreversible chemical reactor is used to demonstrate our design algorithm, and to highlight the benefits of the proposed schemes.

Fast and energy efficient data storage for information discovery in multi-dimensional WSNs

Multidimensional WSNs are deployed in complex environments to sense and collect data relating to multiple attributes (multi-dimensional data). An efficient information dis-covery for multi-dimensional WSNs deployed in mission–critical environments has become an essential research consideration. Timely and energy efficient information discovery is very impor-tant to maintain the QoS of such mission critical applications. An inefficient information discovery mechanism will result in high transmission of data packets over the network creating bottlenecks leading to unbalanced energy consumption over the network. High latency and inefficient energy consumption will have a direct effect on the QoS of mission-critical applications of particular importance in this regard is the minimization of hotspots.

Stability analysis and resource allocation for space-based multi-access systems

In space-based networks, the data relay satellites can assist low-earth-orbit satellites in relaying data to other satellites or the ground station and improve the real time system throughput. To take full advantage of transmission resource of the cooperative relays, this paper proposes a multiple access and resource allocation strategy, in which relays can receive and transmit simultaneously according to channel characteristics of space-based systems. Based on the queueing theoretic formulation, the stability of the proposed protocol is analyzed and the maximum stable throughput region is derived, which would provide the appropriate guidance for the design of the system optimal control. Simulation results exhibit multiple factors that affect the stable throughput and verify the theoretical analysis.

The equity raw-score matrix - a multi-dimensional indicator of potential disadvantage in higher education

Issues surrounding student participation, transition, retention and successful completion in higher education are topical. While the Australian federal government has identified broad groupings of under-represented students, these do not shed light on the complexities underlying the issues of the educationally disadvantaged, such as the compounding problems of multiple equity-group membership or the overlay of the acute or chronic effects of equity sub-group membership. This paper details the Equity Raw-Score Matrix. The matrix is a multi-dimensional indicator of potential disadvantage in learners, created for the specific purposes of diagnosing the complexities of educational disadvantage and creating pre-emptive strategies for the participation, transition and retention of students who are disadvantaged. The paper also describes the qualitative research study that was the catalyst for the creation of the matrix.

UGI: a multi-dimensional ultrasonic-based interaction approach

We are currently witnessing an era where interaction with computers is no longer limited to conventional methods (i.e. keyboard and mouse). Human Computer Interaction (HCI) as a progressive field of research, has opened up alternatives to the traditional interaction techniques. Embedded Infrared (IR) sensors, Accelerometers and RGBD cameras have become common inputs for devices to recognize gestures and body movements. These sensors are vision based and as a result the devices that incorporate them will be reliant on presence of light. Ultrasonic sensors on the other hand do not suffer this limitation as they utilize properties of sound waves. These sensors however, have been mainly used for distance detection and not with HCI devices. This paper presents our approach in developing a multi-dimensional interaction input method and tool Ultrasonic Gesture-based Interaction (UGI) that utilizes ultrasonic sensors. We demonstrate how these sensors can detect object movements and recognize gestures. We present our approach in building the device and demonstrate sample interactions with it. We have also conducted a user study to evaluate our tool and its distance and micro gesture detection accuracy. This paper reports these results and outlines our future work in the area.

Development of an instrument to evaluate the quality of delivered information systems

Delivered information systems are an integral part of many organisations’ information technology infrastructure. Their dynamic nature creates new challenges, not the least of which is the need to measure the quality/effectiveness of these systems. Given the size of investment in these systems, it would be invaluable for business to formulate a fresh, simple, easy to administer, multi-dimensional instrument capable of measuring the quality of delivered information systems or applications. Such an instrument would provide a practical and efficient means to pinpoint areas that key stakeholders, ranging from end-users to managers, perceive as requiring attention. In this paper, we report on the development of one such instrument. This instrument addresses key areas of performance and uses multiple statements to enhance stakeholders’ understanding of these areas.

Quality as the criterion for delivered information systems effectiveness

One of the major challenges of MIS activities is the difficulty in measuring the effectiveness of delivered systems. The principal purpose of my research is to explore this field in order to develop an instrument by which to measure such effectiveness. Conceptualisation of Information System (IS) Effectiveness has been substantially framed by DeLone and McLean's (1992) Success; Model. But with the innovation in Information Technology (IT) over the past decade, and the constant pressure in IT to improve performance, there is merit in undertaking a fresh appraisal of the issue. This study built on the model of IS Success developed by DeLone and MeLean, but was broadened to include related research from the domains of IS, Management and Marketing. This analysis found that an effective IS function is built on three pillars: the systems implemented; the information held and delivered by these systems; and, the service provided in support of the IS function. A common foundation for these pillars is the concept of stakeholder needs. In seeking to appreciate the effectiveness: of delivered IS applications in relation to the job performance of stakeholders, this research developed an understanding of what quality means in an IT context I argue that quality is a more useful criterion for effectiveness than the more customary measures of use and user satisfaction. Respecification of the IS Success Model was then proposed. The second phase of the research was to test this model empirically through judgment panels, focus groups and interviews. Results consistently supported the structure and components of the respecified model. Quality was determined as a multi-dimensional construct, with the key dimensions for the quality of delivered IS differing from those used in the research from other disciplines. Empirical work indicated that end-user stakeholders derived their evaluations of quality by internally evaluating perceived performance of delivered IS in relation to their expectations for such performance. A short trial explored whether, when overt measurement of expectations was concurrent with the measurement of perceptions, a more revealing appraisal of delivered IS quality was provided than when perceptions alone were measured. Results revealed a difference between the two measures. Using the New IS Success Model as the foundation, and drawing upon the related theoretical and empirical research, an instrument was developed to measure the quality/effectiveness of delivered IS applications. Four trials of this instrument, QUALIT, are documented. Analysis of results from preliminary trials indicates promise in terms of business value: the instrument is simple to administer and has the capacity to pinpoint areas of weakness. The research related to the respecification of the New IS Success Model and the associated empirical studies, including the development of QTJALIT, have both contributed to the development of theory about IS Effectiveness. More precisely, my research has reviewed the components of an information system, the dimensions comprising these components and the indicators of each, and based upon these findings, formulated an instrument by which to measure the effectiveness of a delivered IS.

Systematic evaluation of a virtual environment-based training systems

This paper explores the application of three constructs that deemed to be essential to quantify virtual environments (VE) efficacy: cognitive, skill-based, and affective learning outcomes. The authors discuss the implementation of these constructs in a user-centered evaluation of a VE training system. By transforming both the conceptual and operational cohorts for training evaluation the authors illustrate the benefits of the development of a Multi-dimensional User-centered Systematic Training Evaluation (MUSTe) method for quantifying VEs efficacy. Importantly, MUSTe acknowledges the importance of combining holistic and analytical approaches in conducting systematic user-based evaluation. Furthermore, it also emphasizes that quantifying VEs efficacy must reflect the perception and preferences of the users rather than the imposition of efficacy on single measures of task outcome. An empirical study that applied MUSTe evaluation method in quantifying a VE training system efficacy provided valuable evidence of the theoretical construct and content validity of the method.

M-Dimension : multi-characteristics based routing protocol in human associated delay-tolerant networks with improved performance over one dimensional classic models

Human associated delay-tolerant network (HDTN) is a new delay-tolerant network where mobile devices are associated with humans. It can be viewed from both their geographic and social dimensions. The combination of these different dimensions can enable us to more accurately comprehend a delay-tolerant network and consequently use this multi-dimensional information to improve overall network efficiency. Alongside the geographic dimension of the network which is concerned with geographic topology of routing, social dimensions such as social hierarchy can be used to guide the routing message to improve not only the routing efficiency for individual nodes, but also efficiency for the entire network.

We propose a multi-dimensional routing protocol (M-Dimension) for the human associated delay-tolerant network which uses the local information derived from multiple dimensions to identify a mobile node more accurately. Each dimension has a weight factor and is organized by the Distance Function to select an intermediary and applies multi-cast routing. We compare M-Dimension to existing benchmark routing protocols using the MIT Reality Dataset, a well-known benchmark dataset based on a human associated mobile network trace file. The results of our simulations show that M-Dimension has a significant increase in the average success ratio and is very competitive when End-to-End Delay of packet delivery is used in comparison to other multi-cast DTN routing protocols.

Agent-Based Hybrid Intelligent Systems: An Agent-Based Framework for Complex Problem Solving

Pt. I. Fundamentals of hybrid intelligent systems and agents -- 1. Introduction -- 2. Basics of hybrid intelligent systems -- 3. Basics of agents and multi-agent systems -- Pt. II. Methodology and framework -- 4. Agent-oriented methodologies -- 5. Agent-based framework for hybrid intelligent systems --6. Matchmaking in middle agents -- Pt. III. Application systems -- 7. Agent-based hybrid intelligent system for financial investment
planning -- 8. Agent-based hybrid intelligent system for data mining -- Pt. IV. Concluding remarks -- 9. The less the more -- App. Sample source codes of the agent-based financial planning system

A multi-agent framework for financial investment planning

If a company or person wants to invest a lot of money, where, when, and how should the investment go? A multi-agent based Financial Investment Planner may give some reasonable answers to the above question. Good advice is mainly based on adequate information, rich knowledge, and great
skills to use knowledge and information. To this end, this planner consists of four principal components information gathering agents that are responsible for gathering relevant information on the Internet, data mining agents that are in charge of discovering knowledge from retrieved information as well as other relevant databases, group decision making agents that can effectively use available knowledge and appropriate information to make reasonable decisions (investment advice), and a graphical user interface that interacts with users. This paper is focused on the group decision making part. The design and implementation of an agent-based hybrid intelligent system - agent-based soft computing society are detailed.

Applying a reconfigurable multi-agent scheduler to product distribution

More intelligent scheduling methods are required for manufacturing scheduling due to the move to more agile systems. Multi-agent methods are one such approach. This paper describes the application of a reconfigurable multi-agent scheduler to the problem of allocating orders to warehouses in a distribution supply chain. This multi-agent system was originally developed for allocation of orders to machines in a highly reconfigurable manufacturing system and this work was aimed at investigating the ease of applying this same scheduler to other problems. It was found that this new application was readily achieved because of the modular structure of the scheduler. This paper shows how the application to the new problem was achieved.