Skip to main content

Research Repository

Advanced Search

Outputs (76)

Decision support methods in diabetic patient management by insulin administration neural network vs. induction methods for knowledge classification (2000)
Presentation / Conference
Ambrosiadou, B., Vadera, S., Shankararaman, V., & Goulis, D. (2000, May). Decision support methods in diabetic patient management by insulin administration neural network vs. induction methods for knowledge classification. Presented at Proc of the ICSC Symposium on Neural Computation, Berlin, Germany

Diabetes mellitus is now recognised as a major worldwide public health problem. At present, about 100 million people are registered as diabetic patients. Many clinical, social and economic problems occur as a consequence of insulin-dependent diab... Read More about Decision support methods in diabetic patient management by insulin administration neural network vs. induction methods for knowledge classification.

Decision support methods in diabetic patient management by insulin administration neural network vs. induction methods for knowledge classification (2000)
Presentation / Conference
Ambrosiadou, B., Vadera, S., Shankararaman, V., & Goulis, D. (2000, May). Decision support methods in diabetic patient management by insulin administration neural network vs. induction methods for knowledge classification. Presented at Proc of the ICSC Symposium on Neural Computation, Berlin, Germany

Diabetes mellitus is now recognised as a major worldwide public health problem. At present, about 100 million people are registered as diabetic patients. Many clinical, social and economic problems occur as a consequence of insulin-dependent diab... Read More about Decision support methods in diabetic patient management by insulin administration neural network vs. induction methods for knowledge classification.

Intelligent systems in manufacturing: current developments and future prospects (2000)
Journal Article
Meziane, F., Vadera, S., Kobbacy, K., & Proudlove, N. (2000). Intelligent systems in manufacturing: current developments and future prospects. https://doi.org/10.1108/09576060010326221

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Tra... Read More about Intelligent systems in manufacturing: current developments and future prospects.

Any time probabilistic reasoning for sensor validation (1998)
Presentation / Conference
Ibarguengoytia, P., Sucar, E., & Vadera, S. (1998, March). Any time probabilistic reasoning for sensor validation. Presented at Fourteenth Conference on Uncertainty in Artificial Intelligence, University of Wisconsin Business School, Madison, Wisconsin, USA

For many real time applications, it is important to validate the information received form the sensors before entering higher levels of reasoning. This paper presents an any time probabilistic algorithm for validating the information provided by sens... Read More about Any time probabilistic reasoning for sensor validation.

Any time probabilistic reasoning for sensor validation (1998)
Presentation / Conference
Ibarguengoytia, P., Sucar, E., & Vadera, S. (1998, March). Any time probabilistic reasoning for sensor validation. Presented at Fourteenth Conference on Uncertainty in Artificial Intelligence, University of Wisconsin Business School, Madison, Wisconsin, USA

For many real time applications, it is important to validate the information received form the sensors before entering higher levels of reasoning. This paper presents an any time probabilistic algorithm for validating the information provided by sens... Read More about Any time probabilistic reasoning for sensor validation.

A probabilistic examplar based model (1998)
Thesis
Rodriguez Martinez, A. A probabilistic examplar based model. (Thesis). University of Salford

A central problem in case based reasoning (CBR) is how to store and retrieve cases. One approach to this problem is to use exemplar based models, where only the prototypical cases are stored. However, the development of an exemplar based model (EB... Read More about A probabilistic examplar based model.

A layered any time approach to sensor validation (1997)
Book Chapter
Ibarguengoyatia, P., Vadera, S., & Sucar, E. (1997). A layered any time approach to sensor validation. In Lecture Notes in AI. Springer

Sensors are the most usual source of information in many automatic systems such as automatic control These computerised systems utilise different models of the process being served which usually assume the value of the variables as a correct read... Read More about A layered any time approach to sensor validation.

A layered any time approach to sensor validation (1997)
Book Chapter
Ibarguengoyatia, P., Vadera, S., & Sucar, E. (1997). A layered any time approach to sensor validation. In Lecture Notes in AI. Springer

Sensors are the most usual source of information in many automatic systems such as automatic control These computerised systems utilise different models of the process being served which usually assume the value of the variables as a correct read... Read More about A layered any time approach to sensor validation.

Tools for producing formal specifications : a view of current architectures and future directions (1997)
Journal Article
Vadera, S., & Meziane, F. (1997). Tools for producing formal specifications : a view of current architectures and future directions. Annals of Software Engineering, 3(1), 273-290. https://doi.org/10.1023/A%3A1018950324254

During the last decade, one important contribution towards requirements engineering has been the advent of formal specification languages. They offer a well-defined notation that can improve consistency and avoid ambiguity in specifications. However... Read More about Tools for producing formal specifications : a view of current architectures and future directions.