Outputs (14)

CAM: A Combined Attention Model for Natural Language Inference (2018)
Conference Proceeding
Gajbhiye, A., Jaf, S., Al-Moubayed, N., Bradley, S., & McGough, A. S. (2018). CAM: A Combined Attention Model for Natural Language Inference. In N. Abe, H. Liu, C. Pu, X. Hu, N. Ahmed, M. Qiao, …J. Saltz (Eds.), 2018 IEEE International Conference on Big Data (Big Data) ; proceedings (1009-1014). https://doi.org/10.1109/bigdata.2018.8622057

Natural Language Inference (NLI) is a fundamental step towards natural language understanding. The task aims to detect whether a premise entails or contradicts a given hypothesis. NLI contributes to a wide range of natural language understanding appl... Read More about CAM: A Combined Attention Model for Natural Language Inference.

An Exploration of Dropout with RNNs for Natural Language Inference (2018)
Conference Proceeding
Gajbhiye, A., Jaf, S., Al-Moubayed, N., McGough, A. S., & Bradley, S. (2018). An Exploration of Dropout with RNNs for Natural Language Inference. In V. Kurková, Y. Manolopoulos, B. Hammer, L. S. Iliadis, & I. G. Maglogiannis (Eds.), Artificial neural networks and machine learning - ICANN 2018 : 27th international Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, proceedings. Part III (157-167). https://doi.org/10.1007/978-3-030-01424-7_16

Dropout is a crucial regularization technique for the Recurrent Neural Network (RNN) models of Natural Language Inference (NLI). However, dropout has not been evaluated for the effectiveness at different layers and dropout rates in NLI models. In thi... Read More about An Exploration of Dropout with RNNs for Natural Language Inference.

Combining Machine Learning Classifiers for the Task of Arabic Characters Recognition (2018)
Journal Article
Alabbas, M., Jaf, S., & Khudeyer, S. R. (2018). Combining Machine Learning Classifiers for the Task of Arabic Characters Recognition. Journal of Chinese Language and Computing, 28(1), 1-12

There is a number of machine learning algorithms for recognizing Arabic characters. In this paper, we investigate a range of strategies for multiple machine learning algorithms for the task of Arabic characters recognition, where we are faced with im... Read More about Combining Machine Learning Classifiers for the Task of Arabic Characters Recognition.

BotDet: A System for Real Time Botnet Command and Control Traffic Detection (2018)
Journal Article
Ghafir, I., Prenosil, V., Hammoudeh, M., Baker, T., Jabbar, S., Khalid, S., & Jaf, S. (2018). BotDet: A System for Real Time Botnet Command and Control Traffic Detection. IEEE Access, 6, 38947-38958. https://doi.org/10.1109/access.2018.2846740

Over the past decade, the digitization of services transformed the healthcare sector leading to a sharp rise in cybersecurity threats. Poor cybersecurity in the healthcare sector, coupled with high value of patient records attracted the attention of... Read More about BotDet: A System for Real Time Botnet Command and Control Traffic Detection.

Security Threats to Critical Infrastructure: The Human Factor (2018)
Journal Article
Ghafir, I., Saleem, J., Hammoudeh, M., Faour, H., Prenosil, V., Jaf, S., …Baker, T. (2018). Security Threats to Critical Infrastructure: The Human Factor. Journal of Supercomputing, 74(10), 4986-5002. https://doi.org/10.1007/s11227-018-2337-2

In the 21st century, globalisation made corporate boundaries invisible and difficult to manage. This new macroeconomic transformation caused by globalisation introduced new challenges for critical infrastructure management. By replacing manual tasks... Read More about Security Threats to Critical Infrastructure: The Human Factor.

Improved Arabic Characters Recognition by Combining Multiple Machine Learning Classifiers (2017)
Conference Proceeding
Alabbas, M., Khudeyer, R., Jaf, S., Dong, M., Tseng, Y., Lu, Y., …Li, H. (2017). Improved Arabic Characters Recognition by Combining Multiple Machine Learning Classifiers. In Proceedings of the 2016 International Conference on Asian Language Processing (IALP), 21-23 November 2016, Tainan, Taiwan (262-265). https://doi.org/10.1109/ialp.2016.7875982

In this paper, we investigate a range of strategies for combining multiple machine learning techniques for recognizing Arabic characters, where we are faced with imperfect and dimensionally variable input characters. Experimental results show that co... Read More about Improved Arabic Characters Recognition by Combining Multiple Machine Learning Classifiers.

A Semi-automatic Approach to Identifying and Unifying Ambiguously Encoded Arabic-Based Characters (2017)
Conference Proceeding
Jaf, S., Dong, M., Tseng, Y., Lu, Y., Yu, L., Lee, L., …Li, H. (2017). A Semi-automatic Approach to Identifying and Unifying Ambiguously Encoded Arabic-Based Characters. In Proceedings of the 2016 International Conference on Asian Language Processing (IALP), 21-23 November 2016, Tainan, Taiwan (228-231). https://doi.org/10.1109/ialp.2016.7875974

In this study, we outline a potential problem in normalising texts that are based on a modified version of the Arabic alphabet. One of the main resources available for processing resource-scarce languages is raw text collected from the Internet. Many... Read More about A Semi-automatic Approach to Identifying and Unifying Ambiguously Encoded Arabic-Based Characters.

Optimize BpNN using new breeder genetic algorithm (2016)
Conference Proceeding
Alabass, M., Jaf, S., Abdullah, A. M., Hassanien, A. E., Shaalan, K., Gaber, T., …Tolba, M. F. (2017). Optimize BpNN using new breeder genetic algorithm. In Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2016 (373-382). https://doi.org/10.1007/978-3-319-48308-5_36

In this paper, the ability of genetic algorithms in designing artificial neural network (ANN) is investigated. The multi-layer network (MLN) is taken into account as the ANN structure to be optimized. The idea presented here is to use the genetic alg... Read More about Optimize BpNN using new breeder genetic algorithm.

A Simple Approach to Unify Ambiguously Encoded Kurdish Characters (2016)
Conference Proceeding
Jaf, S. (2016). A Simple Approach to Unify Ambiguously Encoded Kurdish Characters.

In this study we outline a potential problem in the normalisation stage of processing texts that are based on a modified version of the Arabic alphabet. The main source of resources available for processing resource-scarce languages is raw text. We h... Read More about A Simple Approach to Unify Ambiguously Encoded Kurdish Characters.

The Selection of Classifiers for a Data-driven Parser (2015)
Conference Proceeding
Jaf, S., Ramsay, A., Sharp, B., Lubaszewski, W., & Delmonte, R. (2015). The Selection of Classifiers for a Data-driven Parser. In Natural language processing and cognitive science : proceedings 2015 (39-49)

There is a large number of classifiers that can be used for generating a parse model; i.e., as an oracle for guiding data-driven parsers when parsing natural languages. In this paper we present a general and simple approach for generating a parse mod... Read More about The Selection of Classifiers for a Data-driven Parser.