Skip to main content

Research Repository

Advanced Search

All Outputs (163)

An Improved Routing Protocol for Optimum Quality of Service in Device-to-Device and Energy Efficiency in 5G/B5G (2024)
Journal Article
Bunu, S. M., Alani, O. Y., & Saraee, M. (2024). An Improved Routing Protocol for Optimum Quality of Service in Device-to-Device and Energy Efficiency in 5G/B5G. Future Internet, 16(9), Article 347. https://doi.org/10.3390/fi16090347

Some challenges when implementing the optimized link state routing (OLSR) protocol on real-life devices and simulators are unmanageable: link quality, rapid energy depletion, and high processor loads. The causes of these challenges are link state pro... Read More about An Improved Routing Protocol for Optimum Quality of Service in Device-to-Device and Energy Efficiency in 5G/B5G.

Features in extractive supervised single-document summarization: case of Persian news (2024)
Journal Article
Rezaei, H., Mirhosseini, S. A. M., Shahgholian, A., & Saraee, M. (2024). Features in extractive supervised single-document summarization: case of Persian news. Language Resources and Evaluation, 58(4), 1073-1091. https://doi.org/10.1007/s10579-024-09739-7

Text summarization has been one of the most challenging areas of research in NLP. Much effort has been made to overcome this challenge by using either abstractive or extractive methods. Extractive methods are preferable due to their simplicity compar... Read More about Features in extractive supervised single-document summarization: case of Persian news.

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.

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.

Early dementia detection with speech analysis and machine learning techniques (2024)
Journal Article
Jahan, Z., Khan, S. B., & Saraee, M. (in press). Early dementia detection with speech analysis and machine learning techniques. #Journal not on list, 5(1), 65. https://doi.org/10.1007/s43621-024-00217-2

This in-depth study journey explores the context of natural language processing and text analysis in dementia detection, revealing their importance in a variety of fields. Beginning with an examination of the widespread and influence of text data. Th... Read More about Early dementia detection with speech analysis and machine learning techniques.

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.

Optimizing the Parameters of Relay Selection Model in D2D Network (2024)
Conference Proceeding
Bunu, S. M., Saraee, M., & Alani, O. (2024). Optimizing the Parameters of Relay Selection Model in D2D Network. . https://doi.org/10.1109/ISRITI60336.2023.10467664

The Fifth generation (5G) cellular network's traffic load is certain to expand significantly in the near future as a result of its flexibility, high speed, increased bandwidth, better connectivity and low latency. Consequently, it is necessary to inv... Read More about Optimizing the Parameters of Relay Selection Model in D2D Network.

Multiclass Classification and Defect Detection of Steel tube using modified YOLO (2023)
Conference Proceeding
Saraee, M., & khan, S. (2023). Multiclass Classification and Defect Detection of Steel tube using modified YOLO.

Steel tubes are widely used in hazardous high pressure environments such as petroleum, chemicals, natural gas and shale gas. Defects in steel tubes have serious negative consequences. Using deep learning object recognition to identify and detect defe... Read More about Multiclass Classification and Defect Detection of Steel tube using modified YOLO.

Regularized Contrastive Masked Autoencoder Model for Machinery Anomaly Detection Using Diffusion-Based Data Augmentation (2023)
Journal Article
Zahedi, E., Saraee, M., Masoumi, F. S., & Yazdinejad, M. (in press). Regularized Contrastive Masked Autoencoder Model for Machinery Anomaly Detection Using Diffusion-Based Data Augmentation. #Journal not on list, 16(9), 431. https://doi.org/10.3390/a16090431

Unsupervised anomalous sound detection, especially self-supervised methods, plays a crucial role in differentiating unknown abnormal sounds of machines from normal sounds. Self-supervised learning can be divided into two main categories: Generative a... Read More about Regularized Contrastive Masked Autoencoder Model for Machinery Anomaly Detection Using Diffusion-Based Data Augmentation.

Immediate and accessible grief treatment via cold reading chatbots (2023)
Thesis
Tracey, P. (2023). Immediate and accessible grief treatment via cold reading chatbots. (Thesis). University of Salford

This thesis presents a potential solution for prolonged grief disorder (PGD) sufferers waiting for psychological aid, by simulating the cold reading process through a chatbot model. PGD occurs in approximately 10% of all bereavements, and there is cu... Read More about Immediate and accessible grief treatment via cold reading chatbots.

Designing and Implementing a Blockchain-based Platform for the Exchange of Peerto-Peer Energy Trading and Modelling Vehicle-to-Grid(V2G) Residential Community (2023)
Journal Article
Debrah, P., & Saraee, M. (2023). Designing and Implementing a Blockchain-based Platform for the Exchange of Peerto-Peer Energy Trading and Modelling Vehicle-to-Grid(V2G) Residential Community. #Journal not on list, 6(1), 68

The expansion of renewable energy on the national grid has been a struggle throughout the past decade. Rooftop solar photovoltaics (PV) and electric vehicle to Grid (V2G) can function as either load or distributed energy sources. Consequently, presum... Read More about Designing and Implementing a Blockchain-based Platform for the Exchange of Peerto-Peer Energy Trading and Modelling Vehicle-to-Grid(V2G) Residential Community.

Deriving Environmental Risk Profiles for Autonomous Vehicles From Simulated Trips (2023)
Journal Article
Anih, J., Kolekar, S., Dargahi, T., Babaie, M., Saraee, M., & Wetherell, J. (2023). Deriving Environmental Risk Profiles for Autonomous Vehicles From Simulated Trips. IEEE Access, 11, 38385-38398. https://doi.org/10.1109/access.2023.3261245

The commercial adoption of Autonomous Vehicles (AVs) and the positive impact they are expected to have on traffic safety depends on appropriate insurance products due to the high potential losses. A significant proportion of these losses are expected... Read More about Deriving Environmental Risk Profiles for Autonomous Vehicles From Simulated Trips.

LIFT the AV: Location InFerence aTtack on Autonomous Vehicle Camera Data (2023)
Conference Proceeding
Adeboye, O., Abdullahi, A., Dargahi, T., Babaie, M., & Saraee, M. (2023). LIFT the AV: Location InFerence aTtack on Autonomous Vehicle Camera Data. . https://doi.org/10.1109/ccnc51644.2023.10060796

Connected and autonomous vehicles (CAVs) are one of the main representatives of cyber-physical systems (CPS), where the digital data generated in several forms, such as geolocation, distance, and camera data, are used for the physical functionality o... Read More about LIFT the AV: Location InFerence aTtack on Autonomous Vehicle Camera Data.

DeepClean : a robust deep learning technique for autonomous vehicle camera data privacy (2022)
Journal Article
Adeboye, O., Dargahi, T., Babaie, M., Saraee, M., & Yu, C. (2022). DeepClean : a robust deep learning technique for autonomous vehicle camera data privacy. IEEE Access, https://doi.org/10.1109/ACCESS.2022.3222834

Autonomous Vehicles (AVs) are equipped with several sensors which produce various forms of data, such as
geo-location, distance, and camera data. The volume and utility of these data, especially camera data, have
contributed to the advancement of h... Read More about DeepClean : a robust deep learning technique for autonomous vehicle camera data privacy.

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.

Machine learning-based optimized link state routing protocol for D2D communication in 5G/B5G (2022)
Presentation / Conference
Bunu, S., Saraee, M., & Alani, O. (2022, September). Machine learning-based optimized link state routing protocol for D2D communication in 5G/B5G. Presented at The 4th International Conference on Electrical Engineering and Informatics (ICELTICs) 2022, Banda Aceh, Indonesia

Device to Device (D2D) communication in Fifth
Generation (5G) and unavoidable in Beyond Fifth Generation
(B5G) technology is designed to increase network capacity by
offloading backhaul links and base stations traffic and
improving the performanc... Read More about Machine learning-based optimized link state routing protocol for D2D communication in 5G/B5G.

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.

Electricity distribution network : seasonality and the dynamics of equipment failures related network faults (2020)
Presentation / Conference
Silva, C., & Saraee, M. (2020, February). Electricity distribution network : seasonality and the dynamics of equipment failures related network faults. Presented at 2020 Advances in Science and Engineering Technology International Conferences (ASET), Dubai, United Arab Emirates

Power systems are inclined to frequent failures due to equipment malfunctions in the network. Equipment malfunctions can occur in any of the equipment in the network such as transformers, switchgear, overground cables or underground cables. Any failu... Read More about Electricity distribution network : seasonality and the dynamics of equipment failures related network faults.