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All Outputs (90)

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.

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.

Predicting average annual electricity outage using electricity distribution network operator's performance indicators (2020)
Presentation / Conference
Silva, C., & Saraee, M. (2020, February). Predicting average annual electricity outage using electricity distribution network operator's performance indicators. Presented at 2020 Advances in Science and Engineering Technology International Conferences (ASET), Dubai, United Arab Emirates

Electricity Distribution network operators (DNO) may receive a monetary reward or have a penalty reliant on their performance against the target set by the regulators. Customer minutes lost (CML) is one of the primary performance indicators which lea... Read More about Predicting average annual electricity outage using electricity distribution network operator's performance indicators.

Predicting road traffic accident severity using decision trees and time-series calendar heatmaps (2019)
Presentation / Conference
Silva, H., & Saraee, M. (2019, November). Predicting road traffic accident severity using decision trees and time-series calendar heatmaps. Presented at The 6th IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (2019 IEEE CSUDET), Penang, Malaysia

The European Commission estimates that around 135,000 people are seriously injured on Europe's roads each year. The road traffic injuries are a significant but neglected global general public health problem, needing rigorous attempts for effectiv... Read More about Predicting road traffic accident severity using decision trees and time-series calendar heatmaps.

Predictive modelling in mental health : a data science approach (2019)
Presentation / Conference
Saraee, M., Silva, H., & Saraee, M. (2019, November). Predictive modelling in mental health : a data science approach. Presented at 2019 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (IEEE CSUDET), Penang, Malaysia

In national and local level, understanding of factors associated with public health issues like mental health is paramount important. This framework evaluation aims to use the decision Tree technique to improve the degree of understanding of the ment... Read More about Predictive modelling in mental health : a data science approach.

Understanding causes of low voltage (LV) faults in electricity distribution network using association rule mining and text clustering (2019)
Presentation / Conference
Silva, H., & Saraee, M. (2019, June). Understanding causes of low voltage (LV) faults in electricity distribution network using association rule mining and text clustering. Presented at 3RD IEEE Industrial and Commercial Power System Europe (I&CPS), Genoa, Italy

In-depth understanding of a fault cause in electricity distribution network has always been of paramount importance to Distributed Network Operators (DNO) for a reliable power supply. Faults in the network have direct effect on its stability, availab... Read More about Understanding causes of low voltage (LV) faults in electricity distribution network using association rule mining and text clustering.

Diabetics’ self-management systems : drawbacks and potential enhancements (2019)
Presentation / Conference
Darwish, F., Silva, H., & Saraee, M. (2019, March). Diabetics’ self-management systems : drawbacks and potential enhancements. Presented at 2nd International Conference on Geoinformatics and Data Analysis (ICGDA), Prague, Czech Republic

Diabetes is a pandemic that is growing globally, and by the year 2030 it is expected to effect three people every 10 minutes. In the UK, it is estimated that by 2025, 5 million people will have diabetes. Diabetes is currently costing the British Nati... Read More about Diabetics’ self-management systems : drawbacks and potential enhancements.

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.

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.

Particle emissions from Euro 6 diesel cars during real world driving conditions (2017)
Presentation / Conference
Babaie, M., Cooper, J., Molden, N., Silva, C., & Saraee, M. (2017, July). Particle emissions from Euro 6 diesel cars during real world driving conditions. Poster presented at 7th International Congress of Energy and Environment Engineering and Management, Canary Islands, Spain

CO, NOx, HC and Particle mass have been monitored in different vehicle emission standards and Particle number (PN) has been added to standards recently. The EU has proposed a solid particle PN limit in Euro 5b and Euro 6. The PN limit for low duty v... Read More about Particle emissions from Euro 6 diesel cars during real world driving conditions.

Mining the crime survey to support crime profiling (2016)
Presentation / Conference
Wu, J., Meziane, F., Saraee, M., Aspin, R., & Hope, T. (2016, October). Mining the crime survey to support crime profiling. Presented at 2016 International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM), Reggio Calabria, Italy

Crime surveys are conducted to record crimes by the Office for National Statistics (ONS) in the United Kingdom every year. They contain rich information about crime. They record the crimes that are not reported to the police. However, their exploitat... Read More about Mining the crime survey to support crime profiling.

Semantic aware Bayesian network model for actionable knowledge discovery in linked data (2016)
Presentation / Conference
Alharbi, H., & Saraee, M. (2016, July). Semantic aware Bayesian network model for actionable knowledge discovery in linked data. Presented at 12th International Conference, MLDM 2016, New York, NY, USA

The majority of the conventional mining algorithms treat the mining process as an isolated data-driven procedure and overlook the semantic of the targeted data. As a result, the generated patterns are abundant and end users cannot act upon them seaml... Read More about Semantic aware Bayesian network model for actionable knowledge discovery in linked data.

Mars image segmentation with most relevant features among wavelet and color features (2015)
Presentation / Conference
Rashno, A., Saraee, M., & Sadri, S. (2015, April). Mars image segmentation with most relevant features among wavelet and color features. Presented at AI & Robotics (IRANOPEN), 2015

Mars rover is a robot which explores the Mars surface, is equipped to front-line Panoramic Camera (Pancam). Automatic processing and segmentation of images taken by Pancam is one of the most important and most significant tasks of Mars rover since th... Read More about Mars image segmentation with most relevant features among wavelet and color features.

Finding association rules in linked data, a centralization approach (2013)
Presentation / Conference
Ramezani, R., Saraee, M., & Nematbakhsh, M. (2013, May). Finding association rules in linked data, a centralization approach. Presented at 21st Iranian Conference on Electrical Engineering (ICEE), 2013, Mashhad, Iran

Linked Data is used in the Web to create typed links between data from different sources. Connecting diffused data by using these links provides new data which could be employed in different applications. Association Rules Mining (ARM) is a data mini... Read More about Finding association rules in linked data, a centralization approach.

Sentiment classification in Persian: Introducing a mutual information-based method for feature selection (2013)
Presentation / Conference
Bagheri, A., Saraee, M., & de Jong, F. (2013, May). Sentiment classification in Persian: Introducing a mutual information-based method for feature selection. Presented at 21st Iranian Conference on Electrical Engineering (ICEE), 2013, Mashhad, Iran

With the enormous growth of online reviews in Internet, sentiment analysis has received more and more attention in information retrieval and natural language processing community. Up to now there are very few researches conducted on sentiment analysi... Read More about Sentiment classification in Persian: Introducing a mutual information-based method for feature selection.

A multi-armed bandit approach to cost-sensitive decision tree learning (2012)
Presentation / Conference
Lomax, S., Vadera, S., & Saraee, M. (2012, December). A multi-armed bandit approach to cost-sensitive decision tree learning. Presented at 2012 IEEE 12th International Conference on Data Mining Workshops, Brussels, Belgium

Several authors have studied the problem of inducing decision trees that aim to minimize costs of misclassification and take account of costs of tests. The approaches adopted vary from modifying the information theoretic attribute selection measure u... Read More about A multi-armed bandit approach to cost-sensitive decision tree learning.

Privacy preserving mining of association rules on horizontally distributed databases (2012)
Presentation / Conference
distributed databases. Presented at International Conference on Software and Computer Applications ICSCA 2012, Singapore

These protocols are based on two main approaches named as: the Randomization approach and the Cryptographic approach. The first one is based on perturbation of the valuable information while the second one uses cryptographic techniques. The randomiza... Read More about Privacy preserving mining of association rules on horizontally distributed databases.

Hybrid rule threshold adjustment system for intrusion detection (2011)
Presentation / Conference
Moghimi, M., & Saraee, M. (2011, September). Hybrid rule threshold adjustment system for intrusion detection. Presented at The 8th International ISC Conference on Information Security and Cryptology (ISCISC 2011), September 14-15, 2011 - Ferdowsi University of Mashhad,, Mashhad, Iran

Generally, multiple IDSs generates huge volume of alerts every minute and to manage these alerts, rule-based alert management systems are very important. It is critical to keep the rules inside these systems updated, based on the ever changing networ... Read More about Hybrid rule threshold adjustment system for intrusion detection.