Outputs (230)

The utilization of system usability scale in learning management systems: a case study of Jeddah Community College (2016)
Presentation / Conference Contribution
Binyamin, S., Rutter, M., & Smith, S. (2016). The utilization of system usability scale in learning management systems: a case study of Jeddah Community College. In ICERI2016 Proceedings (5314-5323). https://doi.org/10.21125/iceri.2016.2290

Learning Management Systems (LMS) have been widely adopted in many higher educational institutions to support teaching and learning activities. The study was conducted with the aim of investigating the usability of the learning management system (Bla... Read More about The utilization of system usability scale in learning management systems: a case study of Jeddah Community College.

Extracting online information from dual and multiple data streams (2016)
Journal Article
Malik, Z. K., Hussain, A., & Wu, Q. M. J. (2018). Extracting online information from dual and multiple data streams. Neural Computing and Applications, 30(1), 87-98. https://doi.org/10.1007/s00521-016-2647-3

In this paper, we consider the challenging problem of finding shared information in multiple data streams simultaneously. The standard statistical method for doing this is the well-known canonical correlation analysis (CCA) approach. We begin by deve... Read More about Extracting online information from dual and multiple data streams.

Visual attention model with a novel learning strategy and its application to target detection from SAR images (2016)
Presentation / Conference Contribution
Gao, F., Xue, X., Wang, J., Sun, J., Hussain, A., & Yang, E. (2016). Visual attention model with a novel learning strategy and its application to target detection from SAR images. In Advances in Brain Inspired Cognitive Systems (149-160). https://doi.org

The selective visual attention mechanism in human visual system helps human to act efficiently when dealing with massive visual information. Over the last two decades, biologically inspired attention model has drawn lots of research attention and man... Read More about Visual attention model with a novel learning strategy and its application to target detection from SAR images.

Predicting insulin resistance in children using a machine-learning-based clinical decision support system (2016)
Presentation / Conference Contribution
Hall, A. J., Hussain, A., & Shaikh, M. G. (2016). Predicting insulin resistance in children using a machine-learning-based clinical decision support system. In Advances in Brain Inspired Cognitive Systems (274-283). https://doi.org/10.1007/978-3-319-4968

This study proposes a new diagnostic approach based on application of machine learning techniques to anthropometric patient features in order to create a predictive model capable of diagnosing insulin resistance (HOMA-IR). As part of the study, a... Read More about Predicting insulin resistance in children using a machine-learning-based clinical decision support system.

PerSent: A freely available Persian sentiment lexicon (2016)
Presentation / Conference Contribution
Dashtipour, K., Hussain, A., Zhou, Q., Gelbukh, A., Hawalah, A. Y. A., & Cambria, E. (2016). PerSent: A freely available Persian sentiment lexicon. In Advances in Brain Inspired Cognitive Systems (310-320). https://doi.org/10.1007/978-3-319-49685-6_28

People need to know other people’s opinions to make well-informed decisions to buy products or services. Companies and organizations need to understand people’s attitude towards their products and services and use feedback from the customers to impro... Read More about PerSent: A freely available Persian sentiment lexicon.

Modified cat swarm optimization for clustering (2016)
Presentation / Conference Contribution
Razzaq, S., Maqbool, F., & Hussain, A. (2016). Modified cat swarm optimization for clustering. In Advances in Brain Inspired Cognitive Systems 8th International Conference, BICS 2016, Beijing, China, November 28-30, 2016, Proceedings (161-170). https://d

Clustering is one of the most challenging optimization problems. Many Swarm Intelligence techniques including Ant Colony optimization (ACO), Particle Swarm Optimization (PSO), and Honey Bee Optimization (HBO) have been used to solve clustering. Cat S... Read More about Modified cat swarm optimization for clustering.

Deep and sparse learning in speech and language processing: An overview (2016)
Presentation / Conference Contribution
Wang, D., Zhou, Q., & Hussain, A. (2016). Deep and sparse learning in speech and language processing: An overview. In Advances in Brain Inspired Cognitive Systems (171-183). https://doi.org/10.1007/978-3-319-49685-6_16

Large-scale deep neural models, e.g., deep neural networks (DNN) and recurrent neural networks (RNN), have demonstrated significant success in solving various challenging tasks of speech and language processing (SLP), including speech recognition, sp... Read More about Deep and sparse learning in speech and language processing: An overview.

Continuous time recurrent neural network model of recurrent collaterals in the hippocampus CA3 region (2016)
Presentation / Conference Contribution
Shiva, A. S., & Hussain, A. (2016). Continuous time recurrent neural network model of recurrent collaterals in the hippocampus CA3 region. In Advances in Brain Inspired Cognitive Systems: 8th International Conference, BICS 2016, Beijing, China, November

Recurrent collaterals in the brain represent the recollection and execution of various monotonous activities such as breathing, brushing our teeth, chewing, walking, etc. These recurrent collaterals are found throughout the brain, each pertaining to... Read More about Continuous time recurrent neural network model of recurrent collaterals in the hippocampus CA3 region.

An investigation of machine learning and neural computation paradigms in the design of clinical decision support systems (CDSSs) (2016)
Presentation / Conference Contribution
Wajid, S. K., Hussain, A., Luo, B., & Huang, K. (2016). An investigation of machine learning and neural computation paradigms in the design of clinical decision support systems (CDSSs). In Advances in Brain Inspired Cognitive Systems: 8th International C

This paper reviews the state of the art techniques for designing next generation CDSSs. CDSS can aid physicians and radiologists to better analyse and treat patients by combining their respective clinical expertise with complementary capabilities of... Read More about An investigation of machine learning and neural computation paradigms in the design of clinical decision support systems (CDSSs).

A novel fully automated liver and HCC tumor segmentation system using morphological operations (2016)
Presentation / Conference Contribution
Ali, L., Hussain, A., Li, J., Howard, N., Shah, A., Sudhakar, U., …Hussain, Z. (2016). A novel fully automated liver and HCC tumor segmentation system using morphological operations. In Advances in Brain Inspired Cognitive Systems (240-250). https://do

Early detection and diagnosis of Hepatocellular Carcinoma (HCC) is the most discriminating step in liver cancer management. Image processing is primarily used, where fast and accurate Computed Tomography (CT) liver image segmentation is required for... Read More about A novel fully automated liver and HCC tumor segmentation system using morphological operations.