Integration of an internet-driven supply chain for a medium-size e-commerce company

This research aimed at discovering the benefits and challenges of integration across a company's e-supply chain. The research involved a single case study of an Australian e-commerce company. In our work, we first formed a framework of benefits and challenges for e-supply chain integration, which was based on the beliefs held by management consultants. After conducting interviews with various organisational stakeholders of an e-commerce company, we found that although some of the elicited opinions matched those expressed by consultants, others provided their refinement in respect to a medium size, rapidly evolving, start-up company. We also discovered challenges, seemingly ignored by the consultants, which concerned changing market conditions and limited economies of scale perceived as seriously impeding SCM integration. Also, the ability to develop and maintain scalable and effective information systems was found to impact the capacity to integrate services across the e-supply chain. The case study's single most important contribution was to bring to our attention the importance of organisational and environmental maturity in the strategic planning of the supply chain management process.

A statistical-driven approach for automatic classification of events in AFL video highlights

Due to the repetitive and lengthy nature, automatic content-based summarization is essential to extract a more compact and interesting representation of sport video. State-of-the art approaches have confirmed that high-level semantic in sport video can be detected based on the occurrences of specific audio and visual features (also known as cinematic). However, most of them still rely heavily on manual investigation to construct the algorithms for highlight detection. Thus, the primary aim of this paper is to demonstrate how the statistics of cinematic features within play-break sequences can be used to less-subjectively construct highlight classification rules. To verify the effectiveness of our algorithms, we will present some experimental results using six AFL (Australian Football League) matches from different broadcasters. At this stage, we have successfully classified each play-break sequence into: goal, behind, mark, tackle, and non-highlight. These events are chosen since they are commonly used for broadcasted AFL highlights. The proposed algorithms have also been tested successfully with soccer video.

Towards universal and statistical-driven heuristics for automatic classification of sports video events

Researchers worldwide have been actively seeking for the most robust and powerful solutions to detect and classify key events (or highlights) in various sports domains. Most approaches have employed manual heuristics that model the typical pattern of audio-visual features within particular sport events To avoid manual observation and knowledge, machine-learning can be used as an alternative approach. To bridge the gaps between these two alternatives, an attempt is made to integrate statistics into heuristic models during highlight detection in our investigation. The models can be designed with a modest amount of domain-knowledge, making them less subjective and more robust for different sports. We have also successfully used a universal scope of detection and a standard set of features that can be applied for different sports that include soccer, basketball and Australian football. An experiment on a large dataset of sport videos, with a total of around 15 hours, has demonstrated the effectiveness and robustness of our
aIlgorithms.

Limitations of market driven sustainability : the case of environmental management systems for food production in Australia

Environmental Management Systems (EMSs) address environmental risks in supply chains and certification of environmental claims. Governments supporting EMSs have encouraged producers to respond to anticipated consumer environmental concerns. Attempts at implementing EMSs have rarely been in direct response to market demand but are usually farmer organisation driven – to forestall increased regulation. In Australia, consumer demand for foods produced to environmentally sustainable standards is minimal because consumers don’t believe these products offer special benefits. EMS implementation is expensive and onerous; and the products require a market premium. Food consumers have difficulty differentiating the terms organic, environmentally-friendly, and sustainably-produced in food labelling.

Recognition of idle resources in time-driven activity-based costing and resource consumption accounting models

Despite its theoretical superiority over traditional volume-based costing models, the Activity-Based Costing (ABC) model has failed to replace traditional volume-based costing models in most organisations. In response to the problems of the model, Time-Driven Activity-Based Costing (TDABC) and Resource Consumption Accounting (RCA) models have been developed as costing models for next generation cost management systems. A key feature that distinguishes TDABC and RCA models from traditional volume-based costing models and the ABC model is the recognition of idle resources in resource pools.

This paper presents a discussion on implications of recognising idle resources in TDABC and RCA models on developments, maintenance and uses of cost management systems. A hypothetical case is presented to illustrate conversions of an ABC-based costing model to ones that are based on the TDABC and RCA models, and the resulting new allocation of resource costs.

Intelligent assistant to re-configure parameter-driven systems

Parameter-Driven Systems (PDS) are widely used in commerce for large-scale applications. Reusability is achieved with a PDS design by relocating implicit control structures in the software and the storage of explicit data in database files. This approach can accommodate various user requirements without tedious modification of the software. In order to specify appropriate parameters in a system, knowledge of both business activities and system behaviour are required. For large, complex software packages, this task becomes time consuming and requires specialist knowledge, yet the consistency and correctness still cannot be guaranteed. My research studied the types of knowledge required and agents involved in the PDS customisation. The work also identified the associated problems and constraints. A solution is proposed and implemented as an Intelligent Assistant prototype than a manual approach. Three areas of achievement have been highlighted: 1. The characteristics and problems of maintaining parameter instances in a PDS are defined. It is found that the verification is not complete with the technical/structural knowledge alone, but a context is necessary to provide semantic information and related business activities (thus the implemented parameters) so that mainline functions can relate with each other. 2. A knowledge-based modelling approach has been proposed and demonstrated via a practical implementation. A Specification Language was designed which can model various types of knowledge in a PDS and encapsulate relationships. The Knowledge-Based System (KBS) developed verifies parameters based on the interpreted model of a given context. 3. The performance of the Intelligent Assistant prototype was well received by the domain specialist from the participating organisation. The modelling and KBS approach developed in my research offers considerable promise in solving practical problems in the software industry.

Paradigmatic approach to managing complexity in knowledge-driven marketing

This research develops a measure of Customer Lifetime Value, extending existing measures, that provides organisations having large customer databases the means to place a financial value on customers. Using this measure, new models are developed that provide a framework to use knowledge to drive marketing decisions.

Dynamic request-driven scheme for data collectors in sensor networks

Wireless sensor networks lifetime is prolonged through a dynamic scheme for collecting sensory information using intelligent mobile elements. The data collection routes are optimised for fast and reliable delivery. The scheme minimises high levels of energy consumption to extend the network operational time.

Design tools for event-driven software systems

Proposes a design method for the development of software in Visual BASIC whose programming environment is multi-paradigm. Extensions to structure charts and pseudocode to incorporate the three paradigms have been developed based on the premise that procedural models, event-driven forms and objects are mutually exclusive in operation.

Request-driven cross-media content adaptation technique

Devices, standards and software develop rapidly, but still often independently of each other. This creates problems in terms of content suitability on various devices. Also, in mobile environment, user and system-level applications must execute subject to a variety of resource constraints. In order to deal with these constraints, content adaptation is required. In this chapter, we justify the need of distributed cross media content adaptation and the potential of utilizing Web Services as the adaptation providers. We introduce request-driven context to complement constraint-driven and utility-driven approaches. We describe the request context mapping and propose a novel path’s determination scheme for determining the optimal service proxies to facilitate the adaptation tasks. To better illustrate the disjoint portions in content passing between service proxies, two communication models were associated. Then, within Web Services, we explain the related protocols and socket connection between adaptation’s services. We conclude with discussion regarding the strengths of the proposed architecture.