Classification of advance malware for autonomous vehicles by using stochastic logic (2018)
Presentation / Conference
Alsadat tabatabaei, S., Saraee, M., & Dehghantanha, A. (2018, September). Classification of advance malware for autonomous vehicles by using stochastic logic. Presented at 11th IEEE International Conference on Developments in eSystems Engineering DeSE2018, Cambridge, UK

Connectivity of vehicles allows the seamless power of communication over the internet but is not without its cyber
risks. Many IoT communication systems - such as vehicle-to-vehicle or vehicle-to-roadside - may require latencies
below a few tens of... Read More about Classification of advance malware for autonomous vehicles by using stochastic logic.

Diabetes self-management system : review of existing systems and potential enhancements (2018)
Presentation / Conference
systems and potential enhancements. Presented at 11th IEEE International Conference on Developments in eSystems Engineering (DeSE2018), Cambridge, UK

Diabetes is a global pandemic with growing devastating human, social and economic impacts. By 2025 it is estimated that in the UK five million people will be diagnosed with diabetes and by 2030 diabetes will claim three lives every ten minutes. Accor... Read More about Diabetes self-management system : review of existing systems and potential enhancements.

Geometrical-based approach for robust human image detection (2018)
Journal Article
Al-Hazaimeh, O., Al-Nawashi, M., & Saraee, M. (2019). Geometrical-based approach for robust human image detection. Multimedia Tools and Applications, 78(6), 7029-7053. https://doi.org/10.1007/s11042-018-6401-y

In recent years, object detection and classification has been gaining more attention, thus, there are several human object detection algorithms being used to locate and recognize human objects in images. The research of image processing and analyzing... Read More about Geometrical-based approach for robust human image detection.

Analyzing data streams using a dynamic compact stream pattern algorithm (2018)
Presentation / Conference
Oyewale, A., Hughes, C., & Saraee, M. (2018, July). Analyzing data streams using a dynamic compact stream pattern algorithm. Presented at The Eighth International Conference on Advances in Information Mining and Management, Barcelona, Spain

In order to succeed in the global competition, organizations need to understand and monitor the rate of data influx. The acquisition of continuous data has been extremely outstretched as a concern in many fields. Recently, frequent patterns in data s... Read More about Analyzing data streams using a dynamic compact stream pattern algorithm.

A new data science framework for analysing and mining geospatial big data (2018)
Presentation / Conference
Saraee, M., & Silva, H. (2018, April). A new data science framework for analysing and mining geospatial big data. Presented at International Conference on Geoinformatics and Data Analysis (ICGDA 2018), Prague, Czech Republic

Finding influential users for different time bounds in social networks using multi-objective optimization (2018)
Journal Article
Mohammadi, A., & Saraee, M. (2018). Finding influential users for different time bounds in social networks using multi-objective optimization. Swarm and Evolutionary Computation, 40, 158-165. https://doi.org/10.1016/j.swevo.2018.02.003

Online social networks play an important role in marketing services. Influence maximization is a major challenge, in which the goal is to find the most influential users in a social network. Increasing the number of influenced users at the end of a d... Read More about Finding influential users for different time bounds in social networks using multi-objective optimization.

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.