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All Outputs (12)

Improving Predictive Process Analytics with Deep Learning and XAI (2024)
Thesis
Obuzor, P. (2024). Improving Predictive Process Analytics with Deep Learning and XAI. (Thesis). University of Salford

In this doctoral thesis, we explore the innovative application of the Tab Transformer architecture in the realm of predictive process mining, marking a significant advancement in forecasting subsequent events within activity sequences. Utilising th... Read More about Improving Predictive Process Analytics with Deep Learning and XAI.

A Decentralised Peer-to-Peer Energy Trading Platform for Residential Homes (2024)
Thesis
Debrah, K. (2024). A Decentralised Peer-to-Peer Energy Trading Platform for Residential Homes. (Thesis). University of Salford

To achieve a sustainable and low-carbon energy system, it is necessary to develop novel solutions for the way household energy is consumed. Homes that have solar photovoltaic (PV) systems, electric vehicles (EVs), and microgrids can potentially trans... Read More about A Decentralised Peer-to-Peer Energy Trading Platform for Residential Homes.

Developing a Framework to Identify Professional Skills Required for Banking Sector Employee in UK using Natural Language Processing (NLP) Techniques (2024)
Thesis
Anthony, G. (2024). Developing a Framework to Identify Professional Skills Required for Banking Sector Employee in UK using Natural Language Processing (NLP) Techniques. (Thesis). University of Salford

The banking sector is changing dramatically, and new studies reveal that many financial institutions are having challenges keeping up with technology advancements and an acute shortage of skilled workers. The banking industry is changing into a dynam... Read More about Developing a Framework to Identify Professional Skills Required for Banking Sector Employee in UK using Natural Language Processing (NLP) Techniques.

DeepClean: a robust deep learning approach for autonomous vehicle camera data privacy (2022)
Thesis
Adeboye, O. DeepClean: a robust deep learning approach for autonomous vehicle camera data privacy. (Thesis). University of Salford

Autonomous Vehicles (AVs) generate several forms of tracking data, such as geolocation, distance, and camera data. The utility of these data, especially camera data for computer vision projects, has contributed to the advancement of high-performance... Read More about DeepClean: a robust deep learning approach for autonomous vehicle camera data privacy.

A framework for dynamic heterogeneous information networks change discovery based on knowledge engineering and data mining methods (2021)
Thesis
Umer, S. A framework for dynamic heterogeneous information networks change discovery based on knowledge engineering and data mining methods. (Thesis). University of Salford

Information Networks are collections of data structures that are used to model interactions in social and living phenomena. They can be either homogeneous or heterogeneous and static or dynamic depending upon the type and nature of relations between... Read More about A framework for dynamic heterogeneous information networks change discovery based on knowledge engineering and data mining methods.

Towards forecasting and prediction of faults in electricity distribution network : a novel data mining & machine learning approach (2020)
Thesis
Silva, H. Towards forecasting and prediction of faults in electricity distribution network : a novel data mining & machine learning approach. (Thesis). University of Salford

The electricity supply system includes a large-scale power generation installation and a convoluted network of electrical circuits that work together to efficiently and reliably supply electricity to consumers. Faults in the electricity distribution... Read More about Towards forecasting and prediction of faults in electricity distribution network : a novel data mining & machine learning approach.

Analyzing frequent patterns in data streams using a dynamic compact stream pattern algorithm (2019)
Thesis
Oyewale, A. (in press). Analyzing frequent patterns in data streams using a dynamic compact stream pattern algorithm. (Thesis). University of Salford

As a result of modern technology and the advancement in communication, a large amount of data streams are continually generated from various online applications, devices and sources. Mining frequent patterns from these streams of data is now an impor... Read More about Analyzing frequent patterns in data streams using a dynamic compact stream pattern algorithm.

Optimisation techniques for finding connected components in large graphs using GraphX (2018)
Thesis
Turifi, M. (in press). Optimisation techniques for finding connected components in large graphs using GraphX. (Thesis). The University of Salford

The problem of finding connected components in undirected graphs has been well studied. It is an essential pre-processing step to many graph computations, and a fundamental task in graph analytics applications, such as social network analysis, web gr... Read More about Optimisation techniques for finding connected components in large graphs using GraphX.

TempoMiner: towards mining time-oriented data (2000)
Thesis
Saraee, M. TempoMiner: towards mining time-oriented data. (Thesis). University of Manchester, Institute of Science and Technology

The time dimension is a unique and powerful dimension in every enterprise data. In dynamic application such as financial and medical applications representing data as it changes overtime is a common problem. There are diverse applications that requir... Read More about TempoMiner: towards mining time-oriented data.

Optimum parameter machine learning classification and prediction of Internet of Things (IoT) malwares using static malware analysis techniques
Thesis
Shaukat, S. (in press). Optimum parameter machine learning classification and prediction of Internet of Things (IoT) malwares using static malware analysis techniques. (Dissertation). University of Salford

Application of machine learning in the field of malware analysis is not a new concept, there have been lots of researches done on the classification of malware in android and windows environments. However, when it comes to malware analysis in the int... Read More about Optimum parameter machine learning classification and prediction of Internet of Things (IoT) malwares using static malware analysis techniques.

Classifying advanced malware into families based on instruction link analysis
Thesis
Tabatabaei, S. (in press). Classifying advanced malware into families based on instruction link analysis. (Dissertation). University of Salford

With the ever-increasing growth of network resources, a great number of organizations are extremely dependent on the internet for operational activities as such, exposing their sensitive and confidential information to intrusion or invasion by sabote... Read More about Classifying advanced malware into families based on instruction link analysis.