Skip to main content

Research Repository

Advanced Search

Outputs (165)

Mining GPS logs to augment location models
Presentation / Conference
Saraee, M., & Yamaner, S. Mining GPS logs to augment location models. Presented at The Sixth International Conference on Data Mining, Text Mining and their Business Applications May 25 – 27, 2005, Skiathos, Greece., 2005, Skiathos, Greece

The availability of mobile computing and satellite technologies make it possible to develop applications that are aware of user location.However, as the amount of collected data grows quickly, coming up with techniques that ease interpretation of suc... Read More about Mining GPS logs to augment location models.

Improving genetic algorithm with the help of novel twin removal method
Presentation / Conference
Imani, M., Pakizeh, E., & Saraee, M. Improving genetic algorithm with the help of novel twin removal method. Presented at 10th IASTED International Conference on Artificial Intelligence and Applications, held February 15-17, 2010 in Innsbruck, Austria., Innsbruck, Austria

Evolutionary Algorithms is one of the fastest growing areas of computer science. The simple Genetic Algorithm is fairly representative of other EAs. As they all use the same steps, significant researches in this area focus on Genetic Algorithm (GA).... Read More about Improving genetic algorithm with the help of novel twin removal method.

Iris disease classifying using neuro-fuzzy medical diagnosis machine
Book Chapter
Moein, S., Saraee, M., & Moein, M. Iris disease classifying using neuro-fuzzy medical diagnosis machine. In The Sixth International Symposium on Neural Networks (ISNN 2009) (359-368). Springer Berlin / Heidelberg,. https://doi.org/10.1007/978-3-642-01216-7_38

Disease diagnosis is an essential task in the medical world. The use of computers in the practice of medicine is becoming more and more crucial. In this paper, we propose an intelligent system to help us diagnose the Iris disease. This system is base... Read More about Iris disease classifying using neuro-fuzzy medical diagnosis machine.

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.