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Outputs (30)

Customer churn prediction in the telecommunication sector using a rough set approach (2016)
Journal Article
Amin, A., Anwar, S., Adnan, A., Nawaz, M., Alawfi, K., Hussain, A., & Huang, K. (2017). Customer churn prediction in the telecommunication sector using a rough set approach. Neurocomputing, 237, 242-254. https://doi.org/10.1016/j.neucom.2016.12.009

Customer churn is a critical and challenging problem affecting business and industry, in particular, the rapidly growing, highly competitive telecommunication sector. It is of substantial interest to both academic researchers and industrial practitio... Read More about Customer churn prediction in the telecommunication sector using a rough set approach.

An exploratory case study of interactive simulation for teaching Ecology (2016)
Presentation / Conference Contribution
Ameerbakhsh, O., Maharaj, S., Hussain, A., Paine, T., & Taiksi, S. (2016). An exploratory case study of interactive simulation for teaching Ecology. In 2016 15th International Conference on Information Technology Based Higher Education and Training (ITHE

This paper explores the effectiveness of interactive simulation for teaching a selected complex subject, Ecology, in higher education. Specifically, we carry out a lab intervention using interactive agent based simulation, to teach the complex concep... Read More about An exploratory case study of interactive simulation for teaching Ecology.

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.

A new biologically-inspired analytical worm propagation model for mobile unstructured peer-to-peer networks (2016)
Presentation / Conference Contribution
Alharbi, H., Aloufi, K., & Hussain, A. (2016). A new biologically-inspired analytical worm propagation model for mobile unstructured peer-to-peer networks. In Advances in Brain Inspired Cognitive Systems (251-263). https://doi.org/10.1007/978-3-319-49685

Millions of users world-wide are sharing content using the Peer-to-Peer (P2P) client network. While new innovations bring benefits, there are nevertheless some dangers associated with them. One of the main threats is P2P worms that can penetrate the... Read More about A new biologically-inspired analytical worm propagation model for mobile unstructured peer-to-peer networks.

A data driven approach to audiovisual speech mapping (2016)
Presentation / Conference Contribution
Abel, A., Marxer, R., Barker, J., Watt, R., Whitmer, B., Derleth, P., & Hussain, A. (2016). A data driven approach to audiovisual speech mapping. In Advances in Brain Inspired Cognitive Systems (331-342). https://doi.org/10.1007/978-3-319-49685-6_30

The concept of using visual information as part of audio speech processing has been of significant recent interest. This paper presents a data driven approach that considers estimating audio speech acoustics using only temporal visual information wit... Read More about A data driven approach to audiovisual speech mapping.

Comparing Oversampling Techniques to Handle the Class Imbalance Problem: A Customer Churn Prediction Case Study (2016)
Journal Article
Amin, A., Anwar, S., Adnan, A., Nawaz, M., Howard, N., Qadir, J., …Hussain, A. (2016). Comparing Oversampling Techniques to Handle the Class Imbalance Problem: A Customer Churn Prediction Case Study. IEEE Access, 4, 7940-7957. https://doi.org/10.1109/AC

Customer retention is a major issue for various service-based organizations particularly telecom industry, wherein predictive models for observing the behavior of customers are one of the great instruments in customer retention process and inferring... Read More about Comparing Oversampling Techniques to Handle the Class Imbalance Problem: A Customer Churn Prediction Case Study.

Distributed Reservoir Computing with Sparse Readouts [Research Frontier] (2016)
Journal Article
Scardapane, S., Panella, M., Comminiello, D., Hussain, A., & Uncini, A. (2016). Distributed Reservoir Computing with Sparse Readouts [Research Frontier]. IEEE Computational Intelligence Magazine, 11(4), 59-70. https://doi.org/10.1109/MCI.2016.2601759

In a network of agents, a widespread problem is the need to estimate a common underlying function starting from locally distributed measurements. Real-world scenarios may not allow the presence of centralized fusion centers, requiring the development... Read More about Distributed Reservoir Computing with Sparse Readouts [Research Frontier].

An Agent-Based Approach for Modelling Peer to Peer Networks (2016)
Presentation / Conference Contribution
Alharbi, H., & Hussain, A. (2016). An Agent-Based Approach for Modelling Peer to Peer Networks. In 2015 17th UKSim-AMSS International Conference on Modelling and Simulation (UKSim) (532-537). https://doi.org/10.1109/UKSim.2015.47

A promising modelling and simulation tool is Agent-based Modelling (ABM) that has proved to be an effective and powerful tool across a wide range of fields. However, its exploitation within the Peer to Peer (P2P) paradigm has only recently attracted... Read More about An Agent-Based Approach for Modelling Peer to Peer Networks.

Towards GPU-Based Common-Sense Reasoning: Using Fast Subgraph Matching (2016)
Journal Article
Tran, H., Cambria, E., & Hussain, A. (2016). Towards GPU-Based Common-Sense Reasoning: Using Fast Subgraph Matching. Cognitive Computation, 8(6), 1074-1086. https://doi.org/10.1007/s12559-016-9418-4

Background/Introduction Common-sense reasoning is concerned with simulating cognitive human ability to make presumptions about the type and essence of ordinary situations encountered every day. The most popular way to represent common-sense knowledg... Read More about Towards GPU-Based Common-Sense Reasoning: Using Fast Subgraph Matching.

A novel ontology and machine learning driven hybrid cardiovascular clinical prognosis as a complex adaptive clinical system (2016)
Journal Article
Farooq, K., & Hussain, A. (2016). A novel ontology and machine learning driven hybrid cardiovascular clinical prognosis as a complex adaptive clinical system. Complex Adaptive Systems Modeling, 4, https://doi.org/10.1186/s40294-016-0023-x

Purpose This multidisciplinary industrial research project sets out to develop a hybrid clinical decision support mechanism (inspired by ontology and machine learning driven techniques) by combining evidence, extrapolated through legacy patient data... Read More about A novel ontology and machine learning driven hybrid cardiovascular clinical prognosis as a complex adaptive clinical system.

Multilayered Echo State Machine: A Novel Architecture and Algorithm (2016)
Journal Article
Malik, Z., Hussain, A., & Wu, Q. (2017). Multilayered Echo State Machine: A Novel Architecture and Algorithm. IEEE Transactions on Cybernetics, 47(4), 946-959. https://doi.org/10.1109/TCYB.2016.2533545

In this paper, we present a novel architecture and learning algorithm for a multilayered echo state machine (ML-ESM). Traditional echo state networks (ESNs) refer to a particular type of reservoir computing (RC) architecture. They constitute an effec... Read More about Multilayered Echo State Machine: A Novel Architecture and Algorithm.

Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques (2016)
Journal Article
Dashtipour, K., Poria, S., Hussain, A., Cambria, E., Hawalah, A. Y. A., Gelbukh, A., & Zhou, Q. (2016). Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques. Cognitive Computation, 8(4), 757-771. https://doi.org/10.10

With the advent of Internet, people actively express their opinions about products, services, events, political parties, etc., in social media, blogs, and website comments. The amount of research work on sentiment analysis is growing explosively. How... Read More about Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques.

From Spin to Swindle: Identifying Falsification in Financial Text (2016)
Journal Article
Minhas, S., & Hussain, A. (2016). From Spin to Swindle: Identifying Falsification in Financial Text. Cognitive Computation, 8(4), 729-745. https://doi.org/10.1007/s12559-016-9413-9

Despite legislative attempts to curtail financial statement fraud, it continues unabated. This study makes a renewed attempt to aid in detecting this misconduct using linguistic analysis with data mining on narrative sections of annual reports/10-K f... Read More about From Spin to Swindle: Identifying Falsification in Financial Text.

Biologically Inspired Progressive Enhancement Target Detection from Heavy Cluttered SAR Images (2016)
Journal Article
Gao, F., Ma, F., Zhang, Y., Wang, J., Sun, J., Yang, E., & Hussain, A. (2016). Biologically Inspired Progressive Enhancement Target Detection from Heavy Cluttered SAR Images. Cognitive Computation, 8(5), 955-966. https://doi.org/10.1007/s12559-016-9405-9

High-resolution synthetic aperture radar (SAR) can provide a rich information source for target detection and greatly increase the types and number of target characteristics. How to efficiently extract the target of interest from large amounts of SAR... Read More about Biologically Inspired Progressive Enhancement Target Detection from Heavy Cluttered SAR Images.

A Neuro-Fuzzy Control System Based on Feature Extraction of Surface Electromyogram Signal for Solar-Powered Wheelchair (2016)
Journal Article
Kaiser, M., Chowdhury, Z., Mamun, S., Hussain, A., & Mahmud, M. (2016). A Neuro-Fuzzy Control System Based on Feature Extraction of Surface Electromyogram Signal for Solar-Powered Wheelchair. Cognitive Computation, 8(5), 946-954. https://doi.org/10.1007/s

This paper presents the design and implementation of a low-cost solar-powered wheelchair for physically challenged people. The signals necessary to maneuver the wheelchair are acquired from different muscles of the hand using surface electromyography... Read More about A Neuro-Fuzzy Control System Based on Feature Extraction of Surface Electromyogram Signal for Solar-Powered Wheelchair.

A New Spatio-Temporal Saliency-Based Video Object Segmentation (2016)
Journal Article
Tu, Z., Abel, A., Zhang, L., Luo, B., & Hussain, A. (2016). A New Spatio-Temporal Saliency-Based Video Object Segmentation. Cognitive Computation, 8(4), 629-647. https://doi.org/10.1007/s12559-016-9387-7

Humans and animals are able to segment visual scenes by having the natural cognitive ability to quickly identify salient objects in both static and dynamic scenes. In this paper, we present a new spatio-temporal-based approach to video object segment... Read More about A New Spatio-Temporal Saliency-Based Video Object Segmentation.

Towards a Biologically Inspired Soft Switching Approach for Cloud Resource Provisioning (2016)
Journal Article
Ullah, A., Li, J., Hussain, A., & Yang, E. (2016). Towards a Biologically Inspired Soft Switching Approach for Cloud Resource Provisioning. Cognitive Computation, 8(5), 992-1005. https://doi.org/10.1007/s12559-016-9391-y

Cloud elasticity augments applications to dynamically adapt to changes in demand by acquiring or releasing computational resources on the fly. Recently, we developed a framework for cloud elasticity utilizing multiple feedback controllers simultaneou... Read More about Towards a Biologically Inspired Soft Switching Approach for Cloud Resource Provisioning.

Unsupervised Commonsense Knowledge Enrichment for Domain-Specific Sentiment Analysis (2016)
Journal Article
Ofek, N., Poria, S., Rokach, L., Cambria, E., Hussain, A., & Shabtai, A. (2016). Unsupervised Commonsense Knowledge Enrichment for Domain-Specific Sentiment Analysis. Cognitive Computation, 8(3), 467-477. https://doi.org/10.1007/s12559-015-9375-3

Sentiment analysis in natural language text is a challenging task involving a deep understanding of both syntax and semantics. Leveraging the polarity of multiword expressions—or concepts—rather than single words can mitigate the difficulty of such a... Read More about Unsupervised Commonsense Knowledge Enrichment for Domain-Specific Sentiment Analysis.

ELM based algorithms for acoustic template matching in home automation scenarios: Advancements and performance analysis (2016)
Book Chapter
della Porta, G., Principi, E., Ferroni, G., Squartini, S., Hussain, A., & Piazza, F. (2016). ELM based algorithms for acoustic template matching in home automation scenarios: Advancements and performance analysis. In Recent Advances in Nonlinear Speech P

Speech and sound recognition in home automation scenarios has been gaining an increasing interest in the last decade. One interesting approach addressed in the literature is based on the template matching paradigm, which is characterized by ease of i... Read More about ELM based algorithms for acoustic template matching in home automation scenarios: Advancements and performance analysis.

Integrating twitter traffic information with kalman filter models for public transportation vehicle arrival time prediction (2016)
Book Chapter
Abidin, A. F., Kolberg, M., & Hussain, A. (2016). Integrating twitter traffic information with kalman filter models for public transportation vehicle arrival time prediction. In M. Trovati, R. Hill, A. Anjum, S. Ying Zhu, & L. Liu (Eds.), Big-Data Analyti

Accurate bus arrival time prediction is key for improving the attractiveness of public transport, as it helps users better manage their travel schedule. This paper proposes a model of bus arrival time prediction, which aims to improve arrival time ac... Read More about Integrating twitter traffic information with kalman filter models for public transportation vehicle arrival time prediction.