All Outputs (9)

Towards Explainable Deep Learning Models for Fault Prediction based on IoT Sensor Data (2024)
Thesis
Mansouri, T. (2024). Towards Explainable Deep Learning Models for Fault Prediction based on IoT Sensor Data. (Thesis). University of Salford

This thesis addresses a pressing issue in the realm of IoT-based fault prediction using sensor data, focusing on the crucial yet challenging aspect of explainability within deep learning models. While deep learning has showcased remarkable advancemen... Read More about Towards Explainable Deep Learning Models for Fault Prediction based on IoT Sensor Data.

Enhancing Cybersecurity: Machine Learning and Natural Language Processing for Arabic Phishing Email Detection (2024)
Thesis
Salloum, S. (2024). Enhancing Cybersecurity: Machine Learning and Natural Language Processing for Arabic Phishing Email Detection. (Thesis). University of Salford

Phishing is a significant threat to the modern world, causing considerable financial losses. Although electronic mail has shown to be a valuable asset around the world in terms of facilitating communication for all parties involved, whether huge corp... Read More about Enhancing Cybersecurity: Machine Learning and Natural Language Processing for Arabic Phishing Email Detection.

A study and development of Bayesian exemplar based models (2008)
Thesis
Wu, J. A study and development of Bayesian exemplar based models. (Thesis). University of Salford

People think and reason about situations using past experience. Often, past experience consists of stereotypes and exemplars that depict common situations. In order for a computer to reason in a similar way, the identification and representation o... Read More about A study and development of Bayesian exemplar based models.

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.

Any time probabilistic sensor validation (1997)
Thesis
Ibarguengoytia, P. Any time probabilistic sensor validation. (Thesis). University of Salford, UK

Many applications of computing, such as those in medicine and the control of manufacturing and power plants, utilize sensors to obtain information. Unfortunately, sensors are prone to failures. Even with the most sophisticated instruments and control... Read More about Any time probabilistic sensor validation.

From English to formal specifications (1994)
Thesis
Meziane, F. From English to formal specifications. (Thesis). University of Salford

Specifications provide the foundation upon which a system can be formally developed. If a specification is wrong, then no matter what method of design is used, or what quality assurance procedures are in place, they will not result in a system that... Read More about From English to formal specifications.

Elliptical cost-sensitive decision tree algorithm - ECSDT
Thesis
Kassim, M. (in press). Elliptical cost-sensitive decision tree algorithm - ECSDT. (Thesis). University of Salford

Cost-sensitive multiclass classification problems, in which the task of assessing the impact of the costs associated with different misclassification errors, continues to be one of the major challenging areas for data mining and machine learning.... Read More about Elliptical cost-sensitive decision tree algorithm - ECSDT.

A framework for employee appraisals based on inductive logic programming and data mining methods
Thesis
Aqel, D. A framework for employee appraisals based on inductive logic programming and data mining methods. (Thesis). University of Salford

Employee performance appraisal systems are widely regarded as fundamental for evaluating employees’ performance and enhancing organisations’ success. Yet, there is evidence that employees doubt their benefits and fairness, organisations find them dif... Read More about A framework for employee appraisals based on inductive logic programming and data mining methods.

Cost-sensitive decision tree learning using a multi-armed bandit framework
Thesis
Lomax, S. Cost-sensitive decision tree learning using a multi-armed bandit framework. (Thesis). University of Salford

Decision tree learning is one of the main methods of learning from data. It has been applied to a variety of different domains over the past three decades. In the real world, accuracy is not enough; there are costs involved, those of obtaining the da... Read More about Cost-sensitive decision tree learning using a multi-armed bandit framework.