Donald Kerr

Milk Production estimates using feed forward artificial neural networks

The accuracy of milk production forecasts on dairy farms using a ffann (feed forward artificial neural network) with polynomial post-processing, is reported. Historical milk production data was used to derive models that are able to predict milk production from farm inputs, using a standard ffann, a ffann with polynomial post-processing and multiple linear regression. Forecasts obtained from the models were then compared with each other. Within the scope of the available data, it was found that the standard ffann did not improve on the multiple regression technique, but the ffann with polynomial post processing did.

Factors influencing the Development and Adoption of Knowledge Based Decision Support Systems for Small, Owner-Operated Rural Business

This paper provides an analysis of existing literature and practical problems associated with the adoption of a developed knowledge-based decision support system (KBDSS) within small rural businesses. The rural small businesses selected for this study were individual farms within the Australian dairy industry and the developed KBDSS was called DairyPro. The object was to determine the factors that could help with future KBDSS development and improve adoption rates. These factors were tested against DairyPro to determine their effectiveness. This analysis indicates that system developers need to have a good working knowledge of the target industry and to understand the types of decisions that are made by managers in order to develop systems that will be used. A review of the literature also suggests that adoption rates can be influenced by cultural, political, educational and age factors as well as individual characteristics of information technology itself. Small business managers needed more ownership in the process of KBDSS development. The author suggests that the factors affecting KBDSS adoption by dairy farmers can be equally applicable to other small, owner-operated rural businesses. This approach advocates the use of domain experts to provide estimates of expected production levels rather than that of the traditional approach of using the results from mathematical or simulation models to make these estimates.

A study into the creation of feral information systems as a response to an ERP implementation within the supply chain of a large government-owned corporation

This paper investigates the creation of feral systems as a response to an Enterprise Resources Planning (ERP) systems implementation of Systems, Applications and Products (SAP) in the supply chain of a large Government-Owned Corporation (GOC). Using a case study approach and extensive interviews, the researchers found that a SAP system was rigid, highly structured and ignored by some elements of the social system. Moreover, it focused on technical prowess of the SAP solution at the apparent expense of supporting real-world activity. Such a focus allowed the spontaneous creation of feral systems that involved ad hoc processes used to get around the SAP solution, to complete important work. This paper begins with an analysis of the feral systems concept and then examines the case study of feral systems in the organisation in question. This paper concludes with a call for future research into feral systems and their effectiveness on ERP systems to support real-world activity.

A methodology to allow rural extension professionals to build target-specific expert systems for Australian rural business operators

Expert systems (ES) development technology has been used to build rural business applications in the past but these have usually been developed using traditional expert systems shells. This paper introduces a new architecture for the development of a design environment where the domain experts can build a knowledge base for target-specific ES for rural business operators. The system allows rural business operators to use their own knowledge in building their own, target-specific ES for tailored development to their own specific requirements. At this stage, this reusable design environment caters for the Australian dairy industry but in the long run we claim it will be useful for the other livestock based rural industries such as beef cattle and sheep. This approach of developing target-specific ES contributes new knowledge in that it provides a new way of developing decision support by allowing human domain experts to develop relevant ES for different livestock farming business. An evolutionary prototyping approach was employed for initial development of a proof of concept example and as a method of outlining the solution environment. Multiple qualitative data collection methods were engaged to facilitate knowledge acquisition in the domain of milk protein enhancement for dairy operations. This paper also describes the generic development procedure used in this project.

Effective Teaching in the Multicultural Business Classroom

Abstract Universities continue to attract growing numbers of international students, so addressing how teachers deal with cultural diversity in the classroom has become increasingly important. This paper outlines the development of a program aimed at enhancing the effectiveness of teaching a university business course in the multicultural classroom. Initially, data were collected from focus groups comprising international students and experienced teachers. Following these focus groups, the problems experienced by teachers working with international students in business tutorials were further explored by collecting survey data from experienced teachers. These data were then used to develop a training program with the aim of improving the skills of teachers in the multicultural classroom. The training program focused on four broad areas: recognition of different teaching models; communication; improving participation and assessment strategies.

Ontology Development for Context-Sensitive Decision Support

Smart and swift resource allocation is a fundamental issue to accomplish high performance on grid workflow. In this paper, we study the cost-aware grid workflow resource allocation problem based on a market model of grid resource management architectures. We model the problem as the multiple choice knapsack problem (MCKP) and design the resource allocation optimization algorithm to minimize the average turnaround time of the grid workflow. The complexity analysis shows that the optimization algorithm leads to more efficient and appropriate resource allocation than many current algorithms.Semantics have become acceptable techniques for data integration, data interoperability and data visualization in many software engineering domains and Web developments over the past few years. This paper describes a software development where semantic ontology techniques have been used for developing a generic knowledge model applicable across rural industries. This technique enables us to outline a single access point for building end-user specific knowledge based systems. We have called the new solution prototype an end-user enabled design environment (EUEDE) where the knowledge components from the problem ontology is used in building specific decision systems that are context-sensitive to end-user factors. Illustrating with an application from the dairy industry, we describe the design architecture and theory, and argue its generic capability to application in other problem domains.

Problems and Prospects in Teaching Multi-disciplinary Courses: A Case Study of Human Resource Information Systems

This paper identifies and explores the issues, challenges and strategies in the design, development and administration of a suitable Human Resource Information System (HRIS) curriculum. Many academics have limited experience in teaching cross-disciplinary subjects and are further constrained by the cost and technical difficulties in deploying relevant software packages for hands-on experience by students. Another challenge is the variation in students abilities when undertaking such a course with classes typically having a mix of information systems and human resource students. The paper uses a case study approach to analyse key issues and explore possible strategies for improvement.

Managing Security Issues and the Hidden Dangers of Wearable Technologies

Advances in mobile computing have provided numerous innovations that make peoples daily lives easier and more convenient. However, as technology becomes more ubiquitous, corresponding risks increase as well. Managing Security Issues and the Hidden Dangers of Wearable Technologies examines the positive and negative ramifications of emerging wearable devices and their potential threats to individuals, as well as organizations. Highlighting socio-ethical issues, policy implementation, and appropriate usage, this book is a pivotal reference source for professionals, policy makers, academics, managers, and students interested in the security and privacy implications of wearable digital devices.

Feral Information Systems Development: Managerial Implications

Management invests in large information systems in order to improve the effectiveness of their organization. However, when these systems fail to meet the needs of organizational employees, feral information systems (FIS) are created in order to assist workers with their jobs or to avoid existing organizational information systems. Feral Information Systems Development: Managerial Implications seeks to accelerate the collective understandings and implications on the management of business organizations; with an emphasis on theoretical explanations on the development of feral information systems. This book is an essential reference work aimed at providing a more clearly defined and better informed starting point for researchers, consultants, and practitioners who are eager to advance both their practical applications and theoretical understandings of complex and challenging phenomena surrounding FISs.