The effect of enacted capabilities on adoption of a government electronic procurement system by Malaysian SMEs

Prior studies have shown that innovative information systems (IS) adoption behaviour by small-and medium-sized enterprises (SMEs) is greatly dependent on organizational and environmental characteristics. Government influence (i.e., federal and local government agencies) was found to play an important role in the promotion or enforcement of innovative IS adoption by SMEs, and it is vital for ensuring adoption of nationwide innovative IS, particularly in developing economies. This study introduces the construct of enacted capabilities and examines the enacted capabilities that motivate SMEs to use innovative IS (i.e., a government's electronic procurement systems) to its full potential. A model of how enacted capabilities affect IS adoption behaviour through perceived net benefits and attitude is developed. A survey (and follow-up interviews) of CEOs/owners from Malaysian SMEs was conducted. Results indicate the enacted capabilities possessed by SMEs play a prominent role in determining the adoption of government electronic procurement systems by these enterprises.

Producing computer-generated tailored written information for stroke patients and their carers: System development and preliminary evaluation

Purpose: The aim of this project was to design and evaluate a system that would produce tailored information for stroke patients and their carers, customised according to their informational needs, and facilitate communication between the patient and, health professional. Method: A human factors development approach was used to develop a computer system, which dynamically compiles stroke education booklets for patients and carers. Patients and carers are able to select the topics about which they wish to receive information, the amount of information they want, and the font size of the printed booklet. The system is designed so that the health professional interacts with it, thereby providing opportunities for communication between the health professional and patient/carer at a number of points in time. Results: Preliminary evaluation of the system by health professionals, patients and carers was positive. A randomised controlled trial that examines the effect of the system on patient and carer outcomes is underway. (C) 2004 Elsevier Ireland Ltd. All rights reserved.

Hybrid knowledge representation in a blackboard KBS for liquid retaining structure design

This paper highlights the importance of design expertise, for designing liquid retaining structures, including subjective judgments and professional experience. Design of liquid retaining structures has special features different from the others. Being more vulnerable to corrosion problem, they have stringent requirements against serviceability limit state of crack. It is the premise of the study to transferring expert knowledge in a computerized blackboard system. Hybrid knowledge representation schemes, including production rules, object-oriented programming, and procedural methods, are employed to express engineering heuristics and standard design knowledge during the development of the knowledge-based system (KBS) for design of liquid retaining structures. This approach renders it possible to take advantages of the characteristics of each method. The system can provide the user with advice on preliminary design, loading specification, optimized configuration selection and detailed design analysis of liquid retaining structure. It would be beneficial to the field of retaining structure design by focusing on the acquisition and organization of expert knowledge through the development of recent artificial intelligence technology. (C) 2003 Elsevier Ltd. All rights reserved.

Ontological evaluation of enterprise systems interoperability using ebXML

Enterprise systems interoperability (ESI) is an important topic for business currently. This situation is evidenced, at least in part, by the number and extent of potential candidate protocols for such process interoperation, viz., ebXML, BPML, BPEL, and WSCI. Wide-ranging support for each of these candidate standards already exists. However, despite broad acceptance, a sound theoretical evaluation of these approaches has not yet been provided. We use the Bunge-Wand-Weber (BWW) models, in particular, the representation model, to provide the basis for such a theoretical evaluation. We, and other researchers, have shown the usefulness of the representation model for analyzing, evaluating, and engineering techniques in the areas of traditional and structured systems analysis, object-oriented modeling, and process modeling. In this work, we address the question, what are the potential semantic weaknesses of using ebXML alone for process interoperation between enterprise systems? We find that users will lack important implementation information because of representational deficiencies; due to ontological redundancy, the complexity of the specification is unnecessarily increased; and, users of the specification will have to bring in extra-model knowledge to understand constructs in the specification due to instances of ontological excess.

Analysis of stroke patients' and carers' reading ability and the content and design of written materials: Recommendations for improving written stroke information

Objective: This study (a) evaluated the reading ability of patients following stroke and their carers and the reading level and content and design characteristics of the written information provided to them, (b) explored the influence of sociodemographic and clinical characteristics on patients' reading ability, and (c) described an education package that provides well-designed information tailored to patients' and carers' informational needs. Methods: Fifty-seven patients and 12 carers were interviewed about their informational needs in an acute stroke unit. Their reading ability was assessed using the Rapid Estimate of Adult Literacy in Medicine (REALM). The written information provided to them in the acute stroke unit was analysed using the SMOG readability formula and the Suitability Assessment of Materials (SAM). Results: Thirteen (22.8%) patients and 5 (41.7%) carers had received written stroke information. The mean reading level of materials analysed was 11th grade while patients read at a mean of 7-8th grade. Most materials (89%) scored as only adequate in content and design. Patients with combined aphasia read significantly lower (4-6th grade) than other patients (p = 0.001). Conclusion: Only a small proportion of patients and carers received written materials about stroke and the readability level and content and design characteristics of most materials required improvement. Practice implications: When developing and distributing written materials about stroke, health professionals should consider the reading ability and informational needs of the recipients, and the reading level and content and design characteristics of the written materials. A computer system can be used to generate written materials tailored to the informational needs and literacy skills of patients and carers. (c) 2005 Elsevier Ireland Ltd. All rights reserved.

Fitness assessment of document model

Document classification is a supervised machine learning process, where predefined category labels are assigned to documents based on the hypothesis derived from training set of labelled documents. Documents cannot be directly interpreted by a computer system unless they have been modelled as a collection of computable features. Rogati and Yang [M. Rogati and Y. Yang, Resource selection for domain-specific cross-lingual IR, in SIGIR 2004: Proceedings of the 27th annual international conference on Research and Development in Information Retrieval, ACM Press, Sheffied: United Kingdom, pp. 154-161.] pointed out that the effectiveness of document classification system may vary in different domains. This implies that the quality of document model contributes to the effectiveness of document classification. Conventionally, model evaluation is accomplished by comparing the effectiveness scores of classifiers on model candidates. However, this kind of evaluation methods may encounter either under-fitting or over-fitting problems, because the effectiveness scores are restricted by the learning capacities of classifiers. We propose a model fitness evaluation method to determine whether a model is sufficient to distinguish positive and negative instances while still competent to provide satisfactory effectiveness with a small feature subset. Our experiments demonstrated how the fitness of models are assessed. The results of our work contribute to the researches of feature selection, dimensionality reduction and document classification.

A cognitive genetic algorithm for power distribution system planning

Power systems are large scale nonlinear systems with high complexity. Various optimization techniques and expert systems have been used in power system planning. However, there are always some factors that cannot be quantified, modeled, or even expressed by expert systems. Moreover, such planning problems are often large scale optimization problems. Although computational algorithms that are capable of handling large dimensional problems can be used, the computational costs are still very high. To solve these problems, in this paper, investigation is made to explore the efficiency and effectiveness of combining mathematic algorithms with human intelligence. It had been discovered that humans can join the decision making progresses by cognitive feedback. Based on cognitive feedback and genetic algorithm, a new algorithm called cognitive genetic algorithm is presented. This algorithm can clarify and extract human's cognition. As an important application of this cognitive genetic algorithm, a practical decision method for power distribution system planning is proposed. By using this decision method, the optimal results that satisfy human expertise can be obtained and the limitations of human experts can be minimized in the mean time.