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Outputs (155)

An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction (2021)
Presentation / Conference Contribution
Kanwal, S., Rashid, J., Kim, J., Nisar, M. W., Hussain, A., Batool, S., & Kanwal, R. (2021). An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction. In 2021 International Conference

One of the most challenging problems in the telecommunications industry is predicting customer churn (CCP). Decision-makers and business experts stressed that acquiring new clients is more expensive than maintaining current ones. From current churn d... Read More about An Attribute Weight Estimation Using Particle Swarm Optimization and Machine Learning Approaches for Customer Churn Prediction.

Visual Speech In Real Noisy Environments (VISION): A Novel Benchmark Dataset and Deep Learning-Based Baseline System. (2020)
Presentation / Conference Contribution
Gogate, M., Dashtipour, K., & Hussain, A. (2020, October). Visual Speech In Real Noisy Environments (VISION): A Novel Benchmark Dataset and Deep Learning-Based Baseline System. Presented at Interspeech 2020, Shanghai, China

In this paper, we present VIsual Speech In real nOisy eNvironments (VISION), a first of its kind audio-visual (AV) corpus comprising 2500 utterances from 209 speakers, recorded in real noisy environments including social gatherings, streets, cafeteri... Read More about Visual Speech In Real Noisy Environments (VISION): A Novel Benchmark Dataset and Deep Learning-Based Baseline System..

Deep Neural Network Driven Binaural Audio Visual Speech Separation (2020)
Presentation / Conference Contribution
Gogate, M., Dashtipour, K., Bell, P., & Hussain, A. (2020, July). Deep Neural Network Driven Binaural Audio Visual Speech Separation. Presented at 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow

The central auditory pathway exploits the auditory signals and visual information sent by both ears and eyes to segregate speech from multiple competing noise sources and help disambiguate phonological ambiguity. In this study, inspired from this uni... Read More about Deep Neural Network Driven Binaural Audio Visual Speech Separation.

Advances in Brain Inspired Cognitive Systems: 10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings (2020)
Presentation / Conference Contribution
(2020). Advances in Brain Inspired Cognitive Systems: 10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings. In J. Ren, A. Hussain, H. Zhao, K. Huang, J. Zheng, J. Cai, …Y. Xiao (Eds.), Advances in Brain Inspired Co

This book constitutes the refereed proceedings of the 10th International Conference on Advances in Brain Inspired Cognitive Systems, BICS 2019, held in Guangzhou, China, in July 2019. The 57 papers presented in this volume were carefully reviewed... Read More about Advances in Brain Inspired Cognitive Systems: 10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings.

Height Prediction for Growth Hormone Deficiency Treatment Planning Using Deep Learning (2020)
Presentation / Conference Contribution
Ilyas, M., Ahmad, J., Lawson, A., Khan, J. S., Tahir, A., Adeel, A., …Hussain, A. (2020). Height Prediction for Growth Hormone Deficiency Treatment Planning Using Deep Learning. In Advances in Brain Inspired Cognitive Systems (76-85). https://doi.org/1

Prospective studies using longitudinal patient data can be used to help to predict responsiveness to Growth Hormone (GH) therapy and assess any suspected risks. In this paper, a novel Clinical Decision Support System (CDSS) is developed to predict gr... Read More about Height Prediction for Growth Hormone Deficiency Treatment Planning Using Deep Learning.

Self-focus Deep Embedding Model for Coarse-Grained Zero-Shot Classification (2020)
Presentation / Conference Contribution
Yang, G., Huang, K., Zhang, R., Goulermas, J. Y., & Hussain, A. (2020). Self-focus Deep Embedding Model for Coarse-Grained Zero-Shot Classification. In Advances in Brain Inspired Cognitive Systems. BICS 2019 (12-22). https://doi.org/10.1007/978-3-030-394

Zero-shot learning (ZSL), i.e. classifying patterns where there is a lack of labeled training data, is a challenging yet important research topic. One of the most common ideas for ZSL is to map the data (e.g., images) and semantic attributes to the s... Read More about Self-focus Deep Embedding Model for Coarse-Grained Zero-Shot Classification.

Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances (2020)
Presentation / Conference Contribution
Ahmed, R., Dashtipour, K., Gogate, M., Raza, A., Zhang, R., Huang, K., Hawalah, A., Adeel, A., & Hussain, A. (2019, July). Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances. Presented at 10th International Con

In pattern recognition, automatic handwriting recognition (AHWR) is an area of research that has developed rapidly in the last few years. It can play a significant role in broad-spectrum of applications rending from, bank cheque processing, applicati... Read More about Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances.

Generalized Adversarial Training in Riemannian Space (2020)
Presentation / Conference Contribution
Zhang, S., Huang, K., Zhang, R., & Hussain, A. (2020). Generalized Adversarial Training in Riemannian Space. In 2019 IEEE International Conference on Data Mining (ICDM) (826-835). https://doi.org/10.1109/icdm.2019.00093

Adversarial examples, referred to as augmented data points generated by imperceptible perturbations of input samples, have recently drawn much attention. Well-crafted adversarial examples may even mislead state-of-the-art deep neural network (DNN) mo... Read More about Generalized Adversarial Training in Riemannian Space.

Random Features and Random Neurons for Brain-Inspired Big Data Analytics (2020)
Presentation / Conference Contribution
Gogate, M., Hussain, A., & Huang, K. (2019, November). Random Features and Random Neurons for Brain-Inspired Big Data Analytics. Presented at 2019 International Conference on Data Mining Workshops (ICDMW), Beijing, China

With the explosion of Big Data, fast and frugal reasoning algorithms are increasingly needed to keep up with the size and the pace of user-generated contents on the Web. In many real-time applications, it is preferable to be able to process more data... Read More about Random Features and Random Neurons for Brain-Inspired Big Data Analytics.

Preface (2018)
Presentation / Conference Contribution
Ren, J., Hussain, A., Zheng, J., Liu, C., Luo, B., Zhao, H., & Zhao, X. (2018). Preface. In Advances in Brain Inspired Cognitive Systems (V-VI). https://doi.org/10.1007/978-3-030-00563-4

Adaptation of sentiment analysis techniques to Persian language (2018)
Presentation / Conference Contribution
Dashtipour, K., Hussain, A., & Gelbukh, A. (2018). Adaptation of sentiment analysis techniques to Persian language. In Computational Linguistics and Intelligent Text Processing (129-140). https://doi.org/10.1007/978-3-319-77116-8_10

In the recent years, people all around the world share their opinions about different fields with each other over Internet. Sentiment analysis techniques have been introduced to classify these rich data based on the polarity of the opinion. Sentiment... Read More about Adaptation of sentiment analysis techniques to Persian language.

Benchmarking multimodal sentiment analysis (2018)
Presentation / Conference Contribution
Cambria, E., Hazarika, D., Poria, S., Hussain, A., & Subramanyam, R. (2018). Benchmarking multimodal sentiment analysis. In Computational Linguistics and Intelligent Text Processing (166-179). https://doi.org/10.1007/978-3-319-77116-8_13

We propose a deep-learning-based framework for multimodal sentiment analysis and emotion recognition. In particular, we leverage on the power of convolutional neural networks to obtain a performance improvement of 10% over the state of the art by com... Read More about Benchmarking multimodal sentiment analysis.

A Novel Semi-supervised Classification Method Based on Class Certainty of Samples (2018)
Presentation / Conference Contribution
Gao, F., Yue, Z., Xiong, Q., Wang, J., Yang, E., & Hussain, A. (2018). A Novel Semi-supervised Classification Method Based on Class Certainty of Samples. . https://doi.org/10.1007/978-3-030-00563-4_30

The traditional classification method based on supervised learning classifies remote sensing (RS) images by using sufficient labelled samples. However, the number of labelled samples is limited due to the expensive and time-consuming collection. To e... Read More about A Novel Semi-supervised Classification Method Based on Class Certainty of Samples.

Comparison of Sentiment Analysis Approaches Using Modern Arabic and Sudanese Dialect (2018)
Presentation / Conference Contribution
Hussien, I., Dashtipour, K., & Hussain, A. (2018). Comparison of Sentiment Analysis Approaches Using Modern Arabic and Sudanese Dialect. In Advances in Brain Inspired Cognitive Systems (615-624). https://doi.org/10.1007/978-3-030-00563-4_60

Sentiment analysis mainly focused on the automatic recognition of opinions’ polarity, as positive or negative. Nowadays, sentiment analysis is replacing the web-based and traditional survey methods commonly conducted by companies for finding the publ... Read More about Comparison of Sentiment Analysis Approaches Using Modern Arabic and Sudanese Dialect.

Exploiting Deep Learning for Persian Sentiment Analysis (2018)
Presentation / Conference Contribution
Dashtipour, K., Gogate, M., Adeel, A., Ieracitano, C., Larijani, H., & Hussain, A. (2018). Exploiting Deep Learning for Persian Sentiment Analysis. In Advances in Brain Inspired Cognitive Systems (597-604). https://doi.org/10.1007/978-3-030-00563-4_58

The rise of social media is enabling people to freely express their opinions about products and services. The aim of sentiment analysis is to automatically determine subject’s sentiment (e.g., positive, negative, or neutral) towards a particular aspe... Read More about Exploiting Deep Learning for Persian Sentiment Analysis.

Saliency Detection via Bidirectional Absorbing Markov Chain (2018)
Presentation / Conference Contribution
Jiang, F., Kong, B., Adeel, A., Xiao, Y., & Hussain, A. (2018). Saliency Detection via Bidirectional Absorbing Markov Chain. . https://doi.org/10.1007/978-3-030-00563-4_48

Traditional saliency detection via Markov chain only consider boundaries nodes. However, in addition to boundaries cues, background prior and foreground prior cues play a complementary role to enhance saliency detection. In this paper, we propose an... Read More about Saliency Detection via Bidirectional Absorbing Markov Chain.

SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis (2018)
Presentation / Conference Contribution
Guellil, I., Adeel, A., Azouaou, F., & Hussain, A. (2018). SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis. . https://doi.org/10.1007/978-3-030-00563-4_54

Data annotation is an important but time-consuming and costly procedure. To sort a text into two classes, the very first thing we need is a good annotation guideline, establishing what is required to qualify for each class. In the literature, the dif... Read More about SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis.

Statistical Analysis Driven Optimized Deep Learning System for Intrusion Detection (2018)
Presentation / Conference Contribution
Ieracitano, C., Adeel, A., Gogate, M., Dashtipour, K., Morabito, F., Larijani, H., …Hussain, A. (2018). Statistical Analysis Driven Optimized Deep Learning System for Intrusion Detection. . https://doi.org/10.1007/978-3-030-00563-4_74

Attackers have developed ever more sophisticated and intelligent ways to hack information and communication technology (ICT) systems. The extent of damage an individual hacker can carry out upon infiltrating a system is well understood. A potentially... Read More about Statistical Analysis Driven Optimized Deep Learning System for Intrusion Detection.

Style Neutralization Generative Adversarial Classifier (2018)
Presentation / Conference Contribution
Jiang, H., Huang, K., Zhang, R., & Hussain, A. (2018). Style Neutralization Generative Adversarial Classifier. In BICS: International Conference on Brain Inspired Cognitive Systems (3-13). https://doi.org/10.1007/978-3-030-00563-4_1

Breathtaking improvement has been seen with the recently proposed deep Generative Adversarial Network (GAN). Purposes of most existing GAN-based models majorly concentrate on generating realistic and vivid patterns by a pattern generator with the aid... Read More about Style Neutralization Generative Adversarial Classifier.

Toward's Arabic multi-modal sentiment analysis (2018)
Presentation / Conference Contribution
Alqarafi, A., Adeel, A., Gogate, M., Dashitpour, K., Hussain, A., & Durrani, T. (2019). Toward's Arabic multi-modal sentiment analysis. . https://doi.org/10.1007/978-981-10-6571-2_290

In everyday life, people use internet to express and share opinions, facts, and sentiments about products and services. In addition, social media applications such as Facebook, Twitter, WhatsApp, Snapchat etc., have become important information shari... Read More about Toward's Arabic multi-modal sentiment analysis.

A comparative study of Persian sentiment analysis based on different feature combinations (2018)
Presentation / Conference Contribution
Dashtipour, K., Gogate, M., Adeel, A., Hussain, A., Alqarafi, A., & Durrani, T. (2017, July). A comparative study of Persian sentiment analysis based on different feature combinations. Presented at International Conference in Communications, Signal Proces

In recent years, the use of internet and correspondingly the number of online reviews, comments and opinions have increased significantly. It is indeed very difficult for humans to read these opinions and classify them accurately. Consequently, there... Read More about A comparative study of Persian sentiment analysis based on different feature combinations.

A novel brain-inspired compression-based optimised multimodal fusion for emotion recognition (2018)
Presentation / Conference Contribution
Gogate, M., Adeel, A., & Hussain, A. (2018). A novel brain-inspired compression-based optimised multimodal fusion for emotion recognition. . https://doi.org/10.1109/SSCI.2017.8285377

The curse of dimensionality is a well-established phenomenon. However, the properties of high dimensional data are often poorly understood and overlooked during the process of data modelling and analysis. Similarly, how to optimally fuse different mo... Read More about A novel brain-inspired compression-based optimised multimodal fusion for emotion recognition.

Deep learning driven multimodal fusion for automated deception detection (2018)
Presentation / Conference Contribution
Gogate, M., Adeel, A., & Hussain, A. (2018). Deep learning driven multimodal fusion for automated deception detection. . https://doi.org/10.1109/SSCI.2017.8285382

Humans ability to detect lies is no more accurate than chance according to the American Psychological Association. The state-of-the-art deception detection methods, such as deception detection stem from early theories and polygraph have proven to be... Read More about Deep learning driven multimodal fusion for automated deception detection.

Combining deep convolutional neural network and SVM to SAR image target recognition (2018)
Presentation / Conference Contribution
Gao, F., Huang, T., Wang, J., Sun, J., Yang, E., & Hussain, A. (2018). Combining deep convolutional neural network and SVM to SAR image target recognition. . https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData.2017.165

To address the challenging problem on target recognition from synthetic aperture radar (SAR) images, a novel method is proposed by combining Deep Convolutional Neural Network (DCNN) and Support Vector Machine (SVM). First, an improved DCNN is employe... Read More about Combining deep convolutional neural network and SVM to SAR image target recognition.

Knowledge-oriented leadership and innovation: A mediating role of knowledge creation: A case of software industry (2018)
Presentation / Conference Contribution
Mehmood, K., & Hussain, A. (2018). Knowledge-oriented leadership and innovation: A mediating role of knowledge creation: A case of software industry. . https://doi.org/10.1109/ICSAI.2017.8248548

This study describes the mediating role of knowledge creation between knowledge-oriented leadership and innovation. We investigate 150 respondents in the software industry of Pakistan. The path analysis demonstrates that knowledge creation mediates t... Read More about Knowledge-oriented leadership and innovation: A mediating role of knowledge creation: A case of software industry.

Managing association of information system outsourcing: A case of information technology (IT) service provider (2018)
Presentation / Conference Contribution
Mehmood, K., & Hussain, A. (2018). Managing association of information system outsourcing: A case of information technology (IT) service provider. . https://doi.org/10.1109/ICSAI.2017.8248558

Managing relationship is vital fundamental realistic concern in the accomplishment development of outsourcing information system (IS) and also begins to be a realistic dilemma that epidemic business of firms' information system. while the information... Read More about Managing association of information system outsourcing: A case of information technology (IT) service provider.

Predicting obesity using longitudinal near infra-red spectroscopy (NIRS) data (2017)
Presentation / Conference Contribution
Abdullah, A., Hussain, A., & Khan, I. (2017). Predicting obesity using longitudinal near infra-red spectroscopy (NIRS) data. In Proceedings of the International Conference on Compute and Data Analysis (123-128). https://doi.org/10.1145/3093241.3093286

Globally there has been a dramatic increase in obesity. Thus understanding, predicting and managing obesity has the potential to save lives and billions. Behavioral studies suggest that binging by obese persons is prompted by inflated brain reward ce... Read More about Predicting obesity using longitudinal near infra-red spectroscopy (NIRS) data.

Complex-valued computational model of hippocampal CA3 recurrent collaterals (2017)
Presentation / Conference Contribution
Shiva, A., Gogate, M., Howard, N., Graham, B., & Hussain, A. (2017). Complex-valued computational model of hippocampal CA3 recurrent collaterals. . https://doi.org/10.1109/ICCI-CC.2017.8109745

Complex planes are known to simplify the complexity of real world problems, providing a better comprehension of their functionality and design. The need for complex numbers in both artificial and biological neural networks is equally well established... Read More about Complex-valued computational model of hippocampal CA3 recurrent collaterals.

Formal Ontology Generation by deep machine learning (2017)
Presentation / Conference Contribution
Wang, Y., Valipour, M., Zatarain, O., Gavrilova, M., Hussain, A., Howard, N., & Patel, S. (2017). Formal Ontology Generation by deep machine learning. . https://doi.org/10.1109/ICCI-CC.2017.8109723

An ontology is a taxonomic hierarchy of lexical terms and their syntactic and semantic relations for representing a framework of structured knowledge. Ontology used to be problem-specific and manually built due to its extreme complexity. Based on the... Read More about Formal Ontology Generation by deep machine learning.

Machine learning based computer-aided diagnosis of liver tumours (2017)
Presentation / Conference Contribution
Ali, L., Khelil, K., Wajid, S. K., Hussain, Z. U., Shah, M. A., Howard, A., …Hussain, A. (2017). Machine learning based computer-aided diagnosis of liver tumours. . https://doi.org/10.1109/ICCI-CC.2017.8109742

Image processing plays a vital role in the early detection and diagnosis of Hepatocellular Carcinoma (HCC). In this paper, we present a computational intelligence based Computer-Aided Diagnosis (CAD) system that helps medical specialists detect and d... Read More about Machine learning based computer-aided diagnosis of liver tumours.

Persian Named Entity Recognition (2017)
Presentation / Conference Contribution
Dashtipour, K., Gogate, M., Adeel, A., Algarafi, A., Howard, N., & Hussain, A. (2017). Persian Named Entity Recognition. . https://doi.org/10.1109/ICCI-CC.2017.8109733

Named Entity Recognition (NER) is an important natural language processing (NLP) tool for information extraction and retrieval from unstructured texts such as newspapers, blogs and emails. NER involves processing unstructured text for classification... Read More about Persian Named Entity Recognition.

Improve deep learning with unsupervised objective (2017)
Presentation / Conference Contribution
Zhang, S., Huang, K., Zhang, R., & Hussain, A. (2017). Improve deep learning with unsupervised objective. . https://doi.org/10.1007/978-3-319-70087-8_74

We propose a novel approach capable of embedding the unsupervised objective into hidden layers of the deep neural network (DNN) for preserving important unsupervised information. To this end, we exploit a very simple yet effective unsupervised method... Read More about Improve deep learning with unsupervised objective.

Lung cancer detection using Local Energy-based Shape Histogram (LESH) feature extraction and cognitive machine learning techniques (2017)
Presentation / Conference Contribution
Wajid, S., Hussain, A., Huang, K., & Boulila, W. (2017). Lung cancer detection using Local Energy-based Shape Histogram (LESH) feature extraction and cognitive machine learning techniques. . https://doi.org/10.1109/ICCI-CC.2016.7862060

The novel application of Local Energy-based Shape Histogram (LESH) feature extraction technique was recently proposed for breast cancer diagnosis using mammogram images [22]. This paper extends our original work to apply the LESH technique to detect... Read More about Lung cancer detection using Local Energy-based Shape Histogram (LESH) feature extraction and cognitive machine learning techniques.

Genetic optimization of fuzzy membership functions for cloud resource provisioning (2017)
Presentation / Conference Contribution
Ullah, A., Li, J., Hussain, A., & Shen, Y. (2017). Genetic optimization of fuzzy membership functions for cloud resource provisioning. . https://doi.org/10.1109/SSCI.2016.7850088

The successful usage of fuzzy systems can be seen in many application domains owing to their capabilities to model complex systems by exploiting knowledge of domain experts. Their accuracy and performance are, however, primarily dependent on the desi... Read More about Genetic optimization of fuzzy membership functions for cloud resource provisioning.

Convolutional MKL based multimodal emotion recognition and sentiment analysis (2017)
Presentation / Conference Contribution
Poria, S., Chaturvedi, I., Cambria, E., & Hussain, A. (2016, December). Convolutional MKL based multimodal emotion recognition and sentiment analysis. Presented at 2016 IEEE 16th International Conference on Data Mining (ICDM), Barcelona, Spain

Technology has enabled anyone with an Internet connection to easily create and share their ideas, opinions and content with millions of other people around the world. Much of the content being posted and consumed online is multimodal. With billions o... Read More about Convolutional MKL based multimodal emotion recognition and sentiment analysis.

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.

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.

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 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.

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).

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.

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.

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.

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.

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.

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.

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.

A novel ontology and machine learning inspired hybrid cardiovascular decision support framework (2015)
Presentation / Conference Contribution
Hussain, A., Farooq, K., Luo, B., & Slack, W. (2015). A novel ontology and machine learning inspired hybrid cardiovascular decision support framework. In 2015 IEEE Symposium Series on Computational Intelligence (824-832). https://doi.org/10.1109/SSCI.201

Healthcare information management systems (HIMS) have a substantial amount of limitations such as rigidity and nonconformity to complex clinical processes like Electronic Healthcare records and effective utilisation of clinical practice guidelines to... Read More about A novel ontology and machine learning inspired hybrid cardiovascular decision support framework.

Electronics, communications and networks IV: Proceedings of the 4th international conference on electronics, communications and networks, 12-15 December 2014, Beijing, China (2015)
Presentation / Conference Contribution
Hussain, A., & Ivanovic, M. (2015). Electronics, communications and networks IV: Proceedings of the 4th international conference on electronics, communications and networks, 12-15 December 2014, Beijing, China.

The 4th International Conference on Electronic, Communications and Networks (CECNet2014) inherits the fruitfulness of the past three conferences and lays a foundation for the forthcoming next year in Shanghai. CECNet2014 was hosted by Hubei Universit... Read More about Electronics, communications and networks IV: Proceedings of the 4th international conference on electronics, communications and networks, 12-15 December 2014, Beijing, China.

Solar powered wheel chair for physically challenged people using surface EMG signal (2015)
Presentation / Conference Contribution
Kaiser, S., Chowdhury, Z. I., Mamun, S., Hussain, A., & Mahmud, M. (2015). Solar powered wheel chair for physically challenged people using surface EMG signal. In 2015 IEEE Symposium Series on Computational Intelligence (833-836). https://doi.org/10.1109

This paper presents the design of low cost solar powered wheel chair for physically challenged people. The signals necessary to maneuver the wheel chair are acquired from different muscles of the hand using surface Electromyography (sEMG) technique.... Read More about Solar powered wheel chair for physically challenged people using surface EMG signal.

Efficient text localization in born-digital images by local contrast-based segmentation (2015)
Presentation / Conference Contribution
Chen, K., Yin, F., Hussain, A., & Liu, C. (2015). Efficient text localization in born-digital images by local contrast-based segmentation. In 2015 13th International Conference on Document Analysis and Recognition (ICDAR) (291-295). https://doi.org/10.11

Text localization in born-digital images is usually performed using methods designed for scene text images. Based on the observation that text strokes in born-digital images mostly have complete contours and the pixels on the contours have high contr... Read More about Efficient text localization in born-digital images by local contrast-based segmentation.

Discriminative bi-term topic model for headline-based social news clustering (2015)
Presentation / Conference Contribution
Xia, Y., Tang, N., Hussain, A., & Cambria, E. (2015). Discriminative bi-term topic model for headline-based social news clustering. In Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference (311-316)

Social news are becoming increasingly popular. News organizations and popular journalists are starting to use social media more and more heavily for broadcasting news. The major challenge in social news clustering lies in the fact that textual conten... Read More about Discriminative bi-term topic model for headline-based social news clustering.

A localization toolkit for sentic net (2015)
Presentation / Conference Contribution
Xia, Y., Li, X., Cambria, E., & Hussain, A. (2015). A localization toolkit for sentic net. In 2014 IEEE International Conference on Data Mining Workshop (403-408). https://doi.org/10.1109/ICDMW.2014.179

SenticNet is a popular resource for concept-level sentiment analysis. Because SenticNet was created specifically for opinion mining in English language, however, its localization can be very laborious. In this work, a toolkit for creating non-English... Read More about A localization toolkit for sentic net.

A novel cardiovascular decision support framework for effective clinical risk assessment (2015)
Presentation / Conference Contribution
Farooq, K., Karasek, J., Atassi, H., Hussain, A., Yang, P., MacRae, C., …Slack, W. (2015). A novel cardiovascular decision support framework for effective clinical risk assessment. In 2014 IEEE Symposium on Computational Intelligence in Healthcare and

The aim of this study is to help improve the diagnostic and performance capabilities of Rapid Access Chest Pain Clinics (RACPC), by reducing delay and inaccuracies in the cardiovascular risk assessment of patients with chest pain by helping clinician... Read More about A novel cardiovascular decision support framework for effective clinical risk assessment.

An efficient computer aided decision support system for breast cancer diagnosis using Echo State Network classifier (2015)
Presentation / Conference Contribution
Wajid, S. K., Hussain, A., & Luo, B. (2015). An efficient computer aided decision support system for breast cancer diagnosis using Echo State Network classifier. In 2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE) (17

The paper presents Echo State Network (ESN) as classifier to diagnose the abnormalities in mammogram images. Abnormalities in mammograms can be of different types. An efficient system which can handle these abnormalities and draw correct diagnosis is... Read More about An efficient computer aided decision support system for breast cancer diagnosis using Echo State Network classifier.

Cognitively inspired speech processing for multimodal hearing technology (2015)
Presentation / Conference Contribution
Abel, A., Hussain, A., & Luo, B. (2015). Cognitively inspired speech processing for multimodal hearing technology. In 2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE) (56-63). https://doi.org/10.1109/CICARE.2014.70078

In recent years, the link between the various human communication production domains has become more widely utilised in the field of speech processing. Work by the authors and others has demonstrated that intelligently integrated audio and visual inf... Read More about Cognitively inspired speech processing for multimodal hearing technology.

Intelligent image processing techniques for cancer progression detection, recognition and prediction in the human liver (2015)
Presentation / Conference Contribution
Ali, L., Hussain, A., Li, J., Shah, A., Sudhakr, U., Mahmud, M., …Rajak, M. (2015). Intelligent image processing techniques for cancer progression detection, recognition and prediction in the human liver. In 2014 IEEE Symposium on Computational Intelli

Clinical Decision Support (CDS) aids in early diagnosis of liver cancer, a potentially fatal disease prevalent in both developed and developing countries. Our research aims to develop a robust and intelligent clinical decision support framework for d... Read More about Intelligent image processing techniques for cancer progression detection, recognition and prediction in the human liver.

The development of an intelligent tutorial system for system development (2015)
Presentation / Conference Contribution
Al-Jumeily, D., Hussain, A., Alghamdi, M., Lamb, D., & Hamdan, H. (2015). The development of an intelligent tutorial system for system development. In 2014 International Conference on Web and Open Access to Learning (ICWOAL). https://doi.org/10.1109/ICWO

Educational software has frequently been criticized as it has not been explicitly planned to meet the demands of educational environment. Therefore, there is an increasing demand for an intelligent computer technology to become used in the environmen... Read More about The development of an intelligent tutorial system for system development.

Classification of Fish Ectoparasite Genus Gyrodactylus SEM Images Using ASM and Complex Network Model (2014)
Presentation / Conference Contribution
Ali, R., Jiang, B., Man, M., Hussain, A., & Luo, B. (2014). Classification of Fish Ectoparasite Genus Gyrodactylus SEM Images Using ASM and Complex Network Model. In Neural Information Processing: 21st International Conference, ICONIP 2014, Kuching, Mala

Active Shape Models and Complex Network method are applied to the attachment hooks of several species of Gyrodactylus, including the notifiable pathogen G. salaris, to classify each species to their true species type. ASM is used as a feature extract... Read More about Classification of Fish Ectoparasite Genus Gyrodactylus SEM Images Using ASM and Complex Network Model.

Dependency-based semantic parsing for concept-level text analysis (2014)
Presentation / Conference Contribution
Poria, S., Agarwal, B., Gelbukh, A., Hussain, A., & Howard, N. (2014). Dependency-based semantic parsing for concept-level text analysis. In Computational Linguistics and Intelligent Text Processing: 15th International Conference, CICLing 2014, Kathmandu

Concept-level text analysis is superior to word-level analysis as it preserves the semantics associated with multi-word expressions. It offers a better understanding of text and helps to significantly increase the accuracy of many text mining tasks.... Read More about Dependency-based semantic parsing for concept-level text analysis.

Dependency tree-based rules for concept-level aspect-based sentiment analysis (2014)
Presentation / Conference Contribution
Poria, S., Ofek, N., Gelbukh, A., Hussain, A., & Rokach, L. (2014). Dependency tree-based rules for concept-level aspect-based sentiment analysis. In Semantic Web Evaluation Challenge: SemWebEval 2014 at ESWC 2014, Anissaras, Crete, Greece, May 25-29, 20

Over the last few years, the way people express their opinions has changed dramatically with the progress of social networks, web communities, blogs, wikis, and other online collaborative media. Now, people buy a product and express their opinion in... Read More about Dependency tree-based rules for concept-level aspect-based sentiment analysis.

A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle (2013)
Presentation / Conference Contribution
Yang, E., Hussain, A., & Gurney, K. (2013). A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle. In Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, China,

This paper presents a new brain-inspired, switching control approach for a car-like autonomous vehicle using a basal ganglia (BG) model as an action selection mechanism. The problem domain has challenging nonholonomic and state constraints which impl... Read More about A basal ganglia inspired soft switching approach to the motion control of a car-like autonomous vehicle.

A novel clinical expert system for chest pain risk assessment (2013)
Presentation / Conference Contribution
Farooq, K., Hussain, A., Atassi, H., Leslie, S., Eckl, C., MacRae, C., & Slack, W. (2013). A novel clinical expert system for chest pain risk assessment. In Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, C

Rapid access chest pain clinics (RACPC) enable clinical risk assessment, investigation and arrangement of a treatment plan for chest pain patients without a long waiting list. RACPC Clinicians often experience difficulties in the diagnosis of chest p... Read More about A novel clinical expert system for chest pain risk assessment.

A review of artificial intelligence and biologically inspired computational approaches to solving issues in narrative financial disclosure (2013)
Presentation / Conference Contribution
Minhas, S., Poria, S., Hussain, A., & Hussainey, K. (2013). A review of artificial intelligence and biologically inspired computational approaches to solving issues in narrative financial disclosure. In Advances in Brain Inspired Cognitive Systems: 6th I

Indisputably, financial reporting has a key role to play in the efficient workings of capitalist economies. Problems related to agency and asymmetric information (Jensen and Meckling, 1976) would abound and cripple financial markets, as it has done w... Read More about A review of artificial intelligence and biologically inspired computational approaches to solving issues in narrative financial disclosure.

Cognitive computation: A case study in cognitive control of autonomous systems and some future directions (2013)
Presentation / Conference Contribution
Hussain, A. (2013). Cognitive computation: A case study in cognitive control of autonomous systems and some future directions. In The 2013 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/IJCNN.2013.6706716

Cognitive computation is an emerging discipline linking together neurobiology, cognitive psychology and artificial intelligence. Springer Neuroscience has launched a journal in this exciting multidisciplinary topic, which seeks to publish biologicall... Read More about Cognitive computation: A case study in cognitive control of autonomous systems and some future directions.

Conceptual clustering of documents for automatic ontology generation (2013)
Presentation / Conference Contribution
Krishnan, R., Hussain, A., & Sherimon, S. P. C. (2013). Conceptual clustering of documents for automatic ontology generation. In Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proce

In Information retrieval, Keyword based retrieval is unsatisfactory for user needs since it can’t always retrieve relevant words according to the concept. Since different words can represent the same concept (polysemy) and one word can represent diff... Read More about Conceptual clustering of documents for automatic ontology generation.

Efficient clinical decision making by learning from missing clinical data (2013)
Presentation / Conference Contribution
Farooq, K., Yang, P., Hussain, A., Huang, K., MacRae, C., Eckl, C., & Slack, W. (2013). Efficient clinical decision making by learning from missing clinical data. In 2013 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE) (2

Clinical decision making frequently involves making decisions under uncertainty because of missing key patient data (e.g, demographics, episodic and clinical diagnosis details) - this information is essential for modern clinical decision support syst... Read More about Efficient clinical decision making by learning from missing clinical data.

Improved efficiency of road sign detection and recognition by employing Kalman filter (2013)
Presentation / Conference Contribution
Zakir, U., Hussain, A., Ali, L., & Luo, B. (2013). Improved efficiency of road sign detection and recognition by employing Kalman filter. In Advances in Brain Inspired Cognitive Systems: 6th International Conference, BICS 2013, Beijing, China, June 9-11,

This paper describes an efficient approach towards road sign detection, and recognition. The proposed system is divided into three sections namely: Road Sign Detection where Colour Segmentation of the road traffic signs is carried out using HSV colou... Read More about Improved efficiency of road sign detection and recognition by employing Kalman filter.

Advances in Brain Inspired Cognitive Systems: Preface (2013)
Presentation / Conference Contribution
Liu, D., Alippi, C., Zhao, D., & Hussain, A. (2013). Advances in Brain Inspired Cognitive Systems: Preface. . https://doi.org/10.1007/978-3-642-38786-9

This book constitutes the refereed proceedings of the 6th International Conference on Brain Inspired Cognitive Systems, BICS 2013, held in Beijing, China in June 2013. The 45 high-quality papers presented were carefully reviewed and selected from 68... Read More about Advances in Brain Inspired Cognitive Systems: Preface.

Music genre classification: A semi-supervised approach (2013)
Presentation / Conference Contribution
Poria, S., Gelbukh, A., Hussain, A., Bandyopadhyay, S., & Howard, N. (2013). Music genre classification: A semi-supervised approach. In Pattern Recognition: 5th Mexican Conference, MCPR 2013, Querétaro, Mexico, June 26-29, 2013. Proceedings (254-263). h

Music genres can be seen as categorical descriptions used to classify music basing on various characteristics such as instrumentation, pitch, rhythmic structure, and harmonic contents. Automatic music genre classification is important for music retri... Read More about Music genre classification: A semi-supervised approach.

Towards reduced EEG based brain-computer interfacing for mobile robot navigation (2013)
Presentation / Conference Contribution
Mahmud, M., & Hussain, A. (2013). Towards reduced EEG based brain-computer interfacing for mobile robot navigation. In Advances in Soft Computing and Its Applications: 12th Mexican International Conference on Artificial Intelligence, MICAI 2013, Mexico C

Rapid development in highly parallel neurophysiological recording techniques along with sophisticated signal processing tools allow direct communication with neuronal processes at different levels. One important level from the point of view of Rehabi... Read More about Towards reduced EEG based brain-computer interfacing for mobile robot navigation.

Sentic blending: Scalable multimodal fusion for the continuous interpretation of semantics and sentics (2013)
Presentation / Conference Contribution
Cambria, E., Howard, N., Hsu, J., & Hussain, A. (2013). Sentic blending: Scalable multimodal fusion for the continuous interpretation of semantics and sentics. In 2013 IEEE Symposium on Computational Intelligence for Human-like Intelligence (CIHLI) (108-

The capability of interpreting the conceptual and affective information associated with natural language through different modalities is a key issue for the enhancement of human-agent interaction. The proposed methodology, termed sentic blending, ena... Read More about Sentic blending: Scalable multimodal fusion for the continuous interpretation of semantics and sentics.

A brain-computer interface test-bench based on EEG signals for research and student training (2013)
Presentation / Conference Contribution
Raif, P., Mahmud, M., Hussain, A., Klos-Witkowska, A., & Suchanek, R. (2013). A brain-computer interface test-bench based on EEG signals for research and student training. In 2013 IEEE Symposium on Computational Intelligence in Healthcare and e-health (C

The paper describes a test-bench model for braincomputer interface research based on EEG signals. The test-bench is going to be used for students training and education. The goal is to prepare modern Brain-Computer Interface development environment i... Read More about A brain-computer interface test-bench based on EEG signals for research and student training.

A novel road traffic sign detection and recognition approach by introducing CCM and LESH (2012)
Presentation / Conference Contribution
Zakir, U., Usman, A., & Hussain, A. (2012). A novel road traffic sign detection and recognition approach by introducing CCM and LESH. In Neural Information Processing (629-636). https://doi.org/10.1007/978-3-642-34487-9_76

A real time road sign detection and recognition system can provide an additional level of driver assistance leading to an improved safety to passengers, road users and other vehicles. Such Advanced Driver Assistance Systems (ADAS) can be used to aler... Read More about A novel road traffic sign detection and recognition approach by introducing CCM and LESH.

Affective common sense knowledge acquisition for sentiment analysis (2012)
Presentation / Conference Contribution
Cambria, E., Xia, Y., & Hussain, A. (2012). Affective common sense knowledge acquisition for sentiment analysis.

Thanks to the advent of Web 2.0, the potential for opinion sharing today is unmatched in history. Making meaning out of the hugeamount of unstructured information available online, however, is extremely difficult as web-contents, despite being perfe... Read More about Affective common sense knowledge acquisition for sentiment analysis.

An intelligent multiple-controller framework for the integrated control of autonomous vehicles (2012)
Presentation / Conference Contribution
Hussain, A., Abdullah, R., Yang, E., & Gurney, K. (2012). An intelligent multiple-controller framework for the integrated control of autonomous vehicles. In Advances in Brain Inspired Cognitive Systems (92-101). https://doi.org/10.1007/978-3-642-31561-9_

This paper presents an intelligent multiple-controller framework for the integrated control of throttle, brake and steering subsystems of realistic validated nonlinear autonomous vehicles. In the developed multiple-controller framework, a fuzzy logic... Read More about An intelligent multiple-controller framework for the integrated control of autonomous vehicles.

An ontology driven and Bayesian Network based cardiovascular decision support framework (2012)
Presentation / Conference Contribution
Farooq, K., Hussain, A., Leslie, S., Eckl, C., MacRae, C., & Slack, W. (2012). An ontology driven and Bayesian Network based cardiovascular decision support framework. In Advances in Brain Inspired Cognitive Systems (31-41). https://doi.org/10.1007/978-3

Clinical risk assessment of chronic illnesses in the cardiovascular domain is quite a challenging and complex task which entails the utilization of standardized clinical practice guidelines and documentation procedures to ensure clinical governance,... Read More about An ontology driven and Bayesian Network based cardiovascular decision support framework.

Analysis of pesticide application practices using an intelligent Agriculture Decision Support System (ADSS) (2012)
Presentation / Conference Contribution
Abdullah, A., Barnawi, A., & Hussain, A. (2012). Analysis of pesticide application practices using an intelligent Agriculture Decision Support System (ADSS). In Advances in Brain Inspired Cognitive Systems (382-391). https://doi.org/10.1007/978-3-642-315

Pesticides are used for controlling pests, but at the same time they have impacts on the environment as well as the product itself. Although cotton covers 2.5% of the world’s cultivated land yet uses 16% of the world’s insecticides, more than any oth... Read More about Analysis of pesticide application practices using an intelligent Agriculture Decision Support System (ADSS).

Clustering social networks using interaction semantics and sentics (2012)
Presentation / Conference Contribution
Chandra, P., Cambria, E., & Hussain, A. (2012). Clustering social networks using interaction semantics and sentics. In Advances in Neural Networks – ISNN 2012 (379-385). https://doi.org/10.1007/978-3-642-31346-2_43

The passage from a static read-only Web to a dynamic read-write Web gave birth to a huge amount of online social networks with the ultimate goal of making communication easier between people with common interests. Unlike real world social networks, h... Read More about Clustering social networks using interaction semantics and sentics.

Decoding network activity from LFPS: A computational approach (2012)
Presentation / Conference Contribution
Mahmud, M., Travalin, D., & Hussain, A. (2012). Decoding network activity from LFPS: A computational approach. In Neural Information Processing (584-591). https://doi.org/10.1007/978-3-642-34475-6_70

Cognition is one of the main capabilities of mammal brain and understanding it thoroughly requires decoding brain’s information processing pathways which are composed of networks formed by complex connectivity between neurons. Mostly, scientists rely... Read More about Decoding network activity from LFPS: A computational approach.

Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis (2012)
Presentation / Conference Contribution
Poria, S., Gelbukh, A., Cambria, E., Yang, P., Hussain, A., & Durrani, T. (2012). Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis. . https://doi.org/10.1109/ICoSP.2012.6491803

SenticNet is currently one of the most comprehensive freely available semantic resources for opinion mining. However, it only provides numerical polarity scores, while more detailed sentiment-related information for its concepts is often desirable. A... Read More about Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis.

Neurobiologically-inspired soft switching control of autonomous vehicles (2012)
Presentation / Conference Contribution
Yang, E., Hussain, A., & Gurney, K. (2012). Neurobiologically-inspired soft switching control of autonomous vehicles. In Advances in Brain Inspired Cognitive Systems (82-91). https://doi.org/10.1007/978-3-642-31561-9_9

A novel soft switching control approach is presented in this paper for autonomous vehicles by using a new functional model for Basal Ganglia (BG). In the proposed approach, a family of fundamental controllers is treated as each of a set of basic cont... Read More about Neurobiologically-inspired soft switching control of autonomous vehicles.

Off-line handwritten Arabic word recognition using SVMs with normalized poly kernel (2012)
Presentation / Conference Contribution
Alalshekmubarak, A., Hussain, A., & Wang, Q. (2012). Off-line handwritten Arabic word recognition using SVMs with normalized poly kernel. In Neural Information Processing (85-91). https://doi.org/10.1007/978-3-642-34481-7_11

Handwriting recognition is a complicated process that many applications rely on, such as mail sorting, cheque processing, digitalisation and translation. The recognition of handwritten Arabic is still an ongoing challenge mainly due to the similarity... Read More about Off-line handwritten Arabic word recognition using SVMs with normalized poly kernel.

Retrieval of semantic concepts based on analysis of texts for automatic construction of ontology (2012)
Presentation / Conference Contribution
Krishnan, R., Hussain, A., & Sherimon, P. (2012). Retrieval of semantic concepts based on analysis of texts for automatic construction of ontology. In Neural Information Processing (524-532). https://doi.org/10.1007/978-3-642-34475-6_63

Ontology together with Semantic Web has a vital role in knowledge management on a global scale. Since manual construction of ontology leads to complex, time consuming and inconsistent results, automatic construction of ontology is more preferred. Thi... Read More about Retrieval of semantic concepts based on analysis of texts for automatic construction of ontology.

Road sign detection and recognition from video stream using HSV, contourlet transform and local energy based shape histogram (2012)
Presentation / Conference Contribution
Zakir, U., Edirishinghe, E., & Hussain, A. (2012). Road sign detection and recognition from video stream using HSV, contourlet transform and local energy based shape histogram. In Advances in Brain Inspired Cognitive Systems (411-419). https://doi.org/10

This paper describes an efficient approach towards road sign detection and recognition. The proposed system is divided into three sections namely; Colour Segmentation of the road traffic signs using the HSV colour space considering varying lighting c... Read More about Road sign detection and recognition from video stream using HSV, contourlet transform and local energy based shape histogram.

Semantically inspired electronic healthcare records (2012)
Presentation / Conference Contribution
Farooq, K., Hussain, A., Leslie, S., Eckl, C., MacRae, C., & Slack, W. (2012). Semantically inspired electronic healthcare records. In Advances in Brain Inspired Cognitive Systems (42-51). https://doi.org/10.1007/978-3-642-31561-9_5

The adoption of Electronic Healthcare Records (EHRs) holds the key for the success of next generation intelligent healthcare systems to improve the quality of healthcare and patient safety by facilitating the exchange of critical patient’s episodic i... Read More about Semantically inspired electronic healthcare records.

Sentic maxine: Multimodal affective fusion and emotional paths (2012)
Presentation / Conference Contribution
Hupont, I., Cambria, E., Cerezo, E., Hussain, A., & Baldassarri, S. (2012). Sentic maxine: Multimodal affective fusion and emotional paths. In Advances in Neural Networks – ISNN 2012 (555-565). https://doi.org/10.1007/978-3-642-31362-2_61

The capability of perceiving and expressing emotions through different modalities is a key issue for the enhancement of human-agent interaction. In this paper, an architecture for the development of intelligent multimodal affective interfaces is pres... Read More about Sentic maxine: Multimodal affective fusion and emotional paths.

Sentic neural networks: A novel cognitive model for affective common sense reasoning (2012)
Presentation / Conference Contribution
Mazzocco, T., Cambria, E., Hussain, A., & Wang, Q. (2012). Sentic neural networks: A novel cognitive model for affective common sense reasoning. In Advances in Brain Inspired Cognitive Systems (12-21). https://doi.org/10.1007/978-3-642-31561-9_2

In human cognition, the capacity to reason and make decisions is strictly dependent on our common sense knowledge about the world and our inner emotional states: we call this ability affective common sense reasoning. In previous works, graph mining a... Read More about Sentic neural networks: A novel cognitive model for affective common sense reasoning.

Single LFP sorting for high-resolution brain-chip interfacing (2012)
Presentation / Conference Contribution
Mahmud, M., Travalin, D., Hussain, A., Girardi, S., Maschietto, M., Felderer, F., & Vassanelli, S. (2012). Single LFP sorting for high-resolution brain-chip interfacing. In Advances in Brain Inspired Cognitive Systems (329-337). https://doi.org/10.1007/9

Understanding cognition has fascinated many neuroscientists and made them put their efforts in deciphering the brain’s information processing capabilities for cognition. Rodents perceive the environment through whisking during which tactile informati... Read More about Single LFP sorting for high-resolution brain-chip interfacing.

The hourglass of emotions (2012)
Presentation / Conference Contribution
Cambria, E., Livingstone, A., & Hussain, A. (2012). The hourglass of emotions. In Cognitive Behavioural Systems: COST 2102 International Training School, Dresden, Germany, February 21-26, 2011, Revised Selected Papers (144-157). https://doi.org/10.1007/9

Human emotions and their modelling are increasingly understood to be a crucial aspect in the development of intelligent systems. Over the past years, in fact, the adoption of psychological models of emotions has become a common trend among researcher... Read More about The hourglass of emotions.

The use of ASM feature extraction and machine learning for the discrimination of members of the fish ectoparasite genus gyrodactylus (2012)
Presentation / Conference Contribution
Ali, R., Hussain, A., Bron, J. E., & Shinn, A. P. (2012). The use of ASM feature extraction and machine learning for the discrimination of members of the fish ectoparasite genus gyrodactylus. In Neural Information Processing: 19th International Conferenc

Active Shape Models (ASM) are applied to the attachment hooks of several species of Gyrodactylus, including the notifiable pathogen G. salaris, to classify each species to their true species type. ASM is used as a feature extraction tool to select in... Read More about The use of ASM feature extraction and machine learning for the discrimination of members of the fish ectoparasite genus gyrodactylus.

Towards IMACA: Intelligent multimodal affective conversational agent (2012)
Presentation / Conference Contribution
Hussain, A., Cambria, E., Mazzocco, T., Grassi, M., Wang, Q., & Durrani, T. (2012). Towards IMACA: Intelligent multimodal affective conversational agent. In Neural Information Processing: 19th International Conference, ICONIP 2012, Doha, Qatar, November

A key aspect when trying to achieve natural interaction in machines is multimodality. Besides verbal communication, in fact, humans interact also through many other channels, e.g., facial expressions, gestures, eye contact, posture, and voice tone. S... Read More about Towards IMACA: Intelligent multimodal affective conversational agent.

Towards a Chinese common and common sense knowledge base for sentiment analysis (2012)
Presentation / Conference Contribution
Cambria, E., Hussain, A., Durrani, T., & Zhang, J. (2012). Towards a Chinese common and common sense knowledge base for sentiment analysis. In Advanced Research in Applied Artificial Intelligence: 25th International Conference on Industrial Engineering a

To date, the majority of sentiment analysis research has focused on English language. Recent studies, however, show that non-native English speakers heavily support the growing use of Internet. Chinese, specifically, is poised to outpace English as t... Read More about Towards a Chinese common and common sense knowledge base for sentiment analysis.

SenticNet 2: A semantic and affective resource for opinion mining and sentiment analysis (2012)
Presentation / Conference Contribution
Cambria, E., Havasi, C., & Hussain, A. (2012, May). SenticNet 2: A semantic and affective resource for opinion mining and sentiment analysis. Presented at 25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25, Florida,

Web 2.0 has changed the ways people communicate, collaborate, and express their opinions and sentiments. But despite social data on the Web being perfectly suitable for human consumption, they remain hardly accessible to machines. To bridge the cogni... Read More about SenticNet 2: A semantic and affective resource for opinion mining and sentiment analysis.

Water quality reliability based design of water distribution networks (2012)
Presentation / Conference Contribution
Gupta, R., Hussain, A., & Bhave, P. R. (2012). Water quality reliability based design of water distribution networks. In World Environmental and Water Resources Congress 2012: Crossing Boundaries (3320-3330). https://doi.org/10.1061/9780784412312.334

The performance of a water distribution network is affected by several factors, pipe failure being a major one of them. Several methodologies have been suggested for optimal design of water distribution networks (WDNs) to meet reliability criteria re... Read More about Water quality reliability based design of water distribution networks.

Isanette: A common and common sense knowledge base for opinion mining (2011)
Presentation / Conference Contribution
Cambria, E., Song, Y., Wang, H., & Hussain, A. (2011). Isanette: A common and common sense knowledge base for opinion mining. In 2011 IEEE 11th International Conference on Data Mining Workshops (315-322). https://doi.org/10.1109/ICDMW.2011.106

The ability to understand natural language text is far from being emulated in machines. One of the main hurdles to overcome is that computers lack both the common and the common sense knowledge humans normally acquire during the formative years of th... Read More about Isanette: A common and common sense knowledge base for opinion mining.

Multi-stage classification of Gyrodactylus species using machine learning and feature selection techniques (2011)
Presentation / Conference Contribution
Ali, R., Hussain, A., Bron, J. E., & Shinn, A. P. (2011). Multi-stage classification of Gyrodactylus species using machine learning and feature selection techniques. In 2011 11th International Conference on Intelligent Systems Design and Applications (45

This study explores the use of multi-stage machine learning based classifiers and feature selection techniques in the classification and identification of fish parasites. Accurate identification of pathogens is a key to their control and as a proof o... Read More about Multi-stage classification of Gyrodactylus species using machine learning and feature selection techniques.

Sentic avatar: Multimodal affective conversational agent with common sense (2011)
Presentation / Conference Contribution
Cambria, E., Hupont, I., Hussain, A., Cerezo, E., & Baldassarri, S. (2011). Sentic avatar: Multimodal affective conversational agent with common sense. In Toward Autonomous, Adaptive, and Context-Aware Multimodal Interfaces. Theoretical and Practical Iss

The capability of perceiving and expressing emotions through different modalities is a key issue for the enhancement of human-computer interaction. In this paper we present a novel architecture for the development of intelligent multimodal affective... Read More about Sentic avatar: Multimodal affective conversational agent with common sense.

Sentic medoids: Organizing affective common sense knowledge in a multi-dimensional vector space (2011)
Presentation / Conference Contribution
Cambria, E., Mazzocco, T., Hussain, A., & Eckl, C. (2011). Sentic medoids: Organizing affective common sense knowledge in a multi-dimensional vector space. In Advances in Neural Networks – ISNN 2011 8th International Symposium on Neural Networks, ISNN

Existing approaches to opinion mining and sentiment analysis mainly rely on parts of text in which opinions and sentiments are explicitly expressed such as polarity terms and affect words. However, opinions and sentiments are often conveyed implicitl... Read More about Sentic medoids: Organizing affective common sense knowledge in a multi-dimensional vector space.

Switching between different ways to think: Multiple approaches to affective common sense reasoning (2011)
Presentation / Conference Contribution
Cambria, E., Mazzocco, T., Hussain, A., & Durrani, T. (2011). Switching between different ways to think: Multiple approaches to affective common sense reasoning. In Analysis of Verbal and Nonverbal Communication and Enactment. The Processing Issues: COST

Emotions are different Ways to Think that our mind triggers to deal with different situations we face in our lives. Our ability to reason and make decisions, in fact, is strictly dependent on both our common sense knowledge about the world and our in... Read More about Switching between different ways to think: Multiple approaches to affective common sense reasoning.

SimConnector: An approach to testing disaster-alerting systems using agent based simulation models (2011)
Presentation / Conference Contribution
Niazi, M., Siddique, Q., Hussain, A., & Fortino, G. (2011). SimConnector: An approach to testing disaster-alerting systems using agent based simulation models. In 2011 Federated Conference on Computer Science and Information Systems (FedCSIS) (659-665)

The design, development and testing of intelligent disaster detection and alerting systems pose a set of non-trivial problems. Not only are such systems difficult to design as they need to accurately predict real-world outcomes using a distributed se... Read More about SimConnector: An approach to testing disaster-alerting systems using agent based simulation models.

Ontology-driven cardiovascular decision support system (2011)
Presentation / Conference Contribution
Farooq, K., Hussain, A., Leslie, S., Eckl, C., & Slack, W. (2011). Ontology-driven cardiovascular decision support system. In 2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops (283-286).

We discuss work-in-progress and propose an ontology driven framework for the development of a clinical expert system for chest pain risk assessment. The framework has the following key components: adaptive questionnaire, patient medical history, risk... Read More about Ontology-driven cardiovascular decision support system.

A side-effects mapping model in patients with lung, colorectal and breast cancer receiving chemotherapy (2011)
Presentation / Conference Contribution
Mazzocco, T., & Hussain, A. (2011). A side-effects mapping model in patients with lung, colorectal and breast cancer receiving chemotherapy. In 2011 IEEE 13th International Conference on e-Health Networking, Applications and Services (34-39). https://doi

Cancer treatments are now more effective than ever and, as a consequence, cancer is becoming a chronic disease. Chemotherapy is a frequently used treatment in people with cancer and it can cause a number of side-effects which if not properly managed... Read More about A side-effects mapping model in patients with lung, colorectal and breast cancer receiving chemotherapy.

Social network analysis of trends in the consumer electronics domain (2011)
Presentation / Conference Contribution
Niazi, M. A., & Hussain, A. (2011). Social network analysis of trends in the consumer electronics domain. In 2011 IEEE International Conference on Consumer Electronics (ICCE) (219-220). https://doi.org/10.1109/ICCE.2011.5722549

We present a study of the trends in the consumer electronics domain using Complex Social Network Analysis (SNA) of citation data retrieved from the Thomson Reuters Web of Knowledge. Our findings include the identification of the most influential pape... Read More about Social network analysis of trends in the consumer electronics domain.

Development of Multimodal Interfaces: Active Listening and Synchrony - Preface (2010)
Presentation / Conference Contribution
Esposito, A., Campbell, N., Vogel, C., Hussain, A., & Nijholt, A. (2010). Development of Multimodal Interfaces: Active Listening and Synchrony - Preface. In Development of Multimodal Interfaces: Active Listening and Synchrony. https://doi.org/10.1007/978

This volume brings together, through a peer-revision process, the advanced research results obtained by the European COST Action 2102: Cross-Modal Analysis of Verbal and Nonverbal Communication, primarily discussed for the first time at the Se... Read More about Development of Multimodal Interfaces: Active Listening and Synchrony - Preface.

Do not feel the trolls (2010)
Presentation / Conference Contribution
Cambria, E., Chandra, P., Sharma, A., & Hussain, A. (2010). Do not feel the trolls. In Proceedings of the 3rd International Workshop on Social Data on the Web (SDoW2010)

The passage from a read-only to a read-write Web gave people the possibility to freely interact, share and collaborate through social networks, online communities, blogs, wikis and other online collaborative media. The democracy of the Web is what ma... Read More about Do not feel the trolls.

Emotional vocal expressions recognition using the COST 2102 Italian database of emotional speech (2010)
Presentation / Conference Contribution
Atassi, H., Riviello, M. T., Smékal, Z., Hussain, A., & Esposito, A. (2010). Emotional vocal expressions recognition using the COST 2102 Italian database of emotional speech. In Development of Multimodal Interfaces: Active Listening and Synchrony Second

The present paper proposes a new speaker-independent approach to the classification of emotional vocal expressions by using the COST 2102 Italian database of emotional speech. The audio records extracted from video clips of Italian movies possess a c... Read More about Emotional vocal expressions recognition using the COST 2102 Italian database of emotional speech.

Sentic computing: Exploitation of common sense for the development of emotion-sensitive systems (2010)
Presentation / Conference Contribution
Cambria, E., Hussain, A., Havasi, C., & Eckl, C. (2010). Sentic computing: Exploitation of common sense for the development of emotion-sensitive systems. In Development of Multimodal Interfaces: Active Listening and Synchrony (148-156). https://doi.org/1

Emotions are a fundamental component in human experience, cognition, perception, learning and communication. In this paper we explore how the use of Common Sense Computing can significantly enhance computers’ emotional intelligence i.e. their capabil... Read More about Sentic computing: Exploitation of common sense for the development of emotion-sensitive systems.

SenticNet: A publicly available semantic resource for opinion mining (2010)
Presentation / Conference Contribution
Cambria, E., Speer, R., Havasi, C., & Hussain, A. (2010). SenticNet: A publicly available semantic resource for opinion mining. In Commonsense knowledge: Papers from the AAAI Fall Symposium (14-18)

Today millions of web-users express their opinions about many topics through blogs, wikis, fora, chats and social networks. For sectors such as e-commerce and e-tourism, it is very useful to automatically analyze the huge amount of social information... Read More about SenticNet: A publicly available semantic resource for opinion mining.

SenticSpace: Visualizing opinions and sentiments in a multi-dimensional vector space (2010)
Presentation / Conference Contribution
Cambria, E., Hussain, A., Havasi, C., & Eckl, C. (2010). SenticSpace: Visualizing opinions and sentiments in a multi-dimensional vector space. . https://doi.org/10.1007/978-3-642-15384-6_41

In a world in which millions of people express their feelings and opinions about any issue in blogs, wikis, fora, chats and social networks, the distillation of knowledge from this huge amount of unstructured information is a challenging task. In thi... Read More about SenticSpace: Visualizing opinions and sentiments in a multi-dimensional vector space.

Sentic computing for patient centered applications (2010)
Presentation / Conference Contribution
Cambria, E., Hussain, A., Durrani, T., Havasi, C., Eckl, C., & Munro, J. (2010). Sentic computing for patient centered applications. In IEEE 10th International Conference on Signal Processing Proceedings (1279-1282). https://doi.org/10.1109/ICOSP.2010.56

Next-generation patients are far from being peripheral to health-care. They are central to understanding the effectiveness and efficiency of services and how they can be improved. Today a lot of patients are used to reviewing local health services on... Read More about Sentic computing for patient centered applications.

Modeling and design of MPPT controller for a PV module using PSCAD/EMTDC (2010)
Presentation / Conference Contribution
Gupta, R., Gupta, G., Kastwar, D., Hussain, A., & Ranjan, H. (2010). Modeling and design of MPPT controller for a PV module using PSCAD/EMTDC. In 2010 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe). https://doi.org/10.1109/IS

This paper presents a modeling of photovoltaic (PV) module in PSCAD/EMTDC and design of maximum power point tracking (MPPT) using boost converter. The model can be used for simulation studies of grid interface applications using voltage source conver... Read More about Modeling and design of MPPT controller for a PV module using PSCAD/EMTDC.

Verification & validation of an agent-based forest fire simulation model (2010)
Presentation / Conference Contribution
Niazi, M. A., Siddique, Q., Hussain, A., & Kolberg, M. (2010). Verification & validation of an agent-based forest fire simulation model. In SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference. https://doi.org/10.1145/1878537.1878539

In this paper, we present the verification and validation of an agent-based model of forest fires. We use a combination of a Virtual Overlay Multi-Agent System (VOMAS) validation scheme with Fire Weather Index (FWI) to validate the forest fire Simula... Read More about Verification & validation of an agent-based forest fire simulation model.

A novel implicit adaptive pole-placement PID controller (2009)
Presentation / Conference Contribution
Zayed, A., El-Fandi, M., Hussain, A., & El-Fllah, A. (2009). A novel implicit adaptive pole-placement PID controller.

In this paper, a new computationally efficient multivariable self-tuning controller with a proportional plus integral plus derivative (PID) is derived. The algorithm features a combination of the self-tuning property, in which the controller paramete... Read More about A novel implicit adaptive pole-placement PID controller.

An investigation into audiovisual speech correlation in reverberant noisy environments (2009)
Presentation / Conference Contribution
Cifani, S., Abel, A., Hussain, A., Squartini, S., & Piazza, F. (2009). An investigation into audiovisual speech correlation in reverberant noisy environments. In Cross-Modal Analysis of Speech, Gestures, Gaze and Facial Expressions: COST Action 2102 Inte

As evidence of a link between the various human communication production domains has become more prominent in the last decade, the field of multimodal speech processing has undergone significant expansion. Many different specialised processing method... Read More about An investigation into audiovisual speech correlation in reverberant noisy environments.

Common sense computing: From the society of mind to digital intuition and beyond (2009)
Presentation / Conference Contribution
Cambria, E., Hussain, A., Havasi, C., & Eckl, C. (2009). Common sense computing: From the society of mind to digital intuition and beyond. In Biometric ID Management and Multimodal Communication (252-259). https://doi.org/10.1007/978-3-642-04391-8_33

What is Common Sense Computing? And why is it so important for the technological evolution of humankind? This paper presents an overview of past, present and future efforts of the AI community to give computers the capacity for Common Sense reasoning... Read More about Common sense computing: From the society of mind to digital intuition and beyond.

Controlled and automatic processing in animals and machines with application to autonomous vehicle control (2009)
Presentation / Conference Contribution
Gurney, K., Hussain, A., Chambers, J., & Abdullah, R. (2009). Controlled and automatic processing in animals and machines with application to autonomous vehicle control. In Artificial Neural Networks – ICANN 2009 (198-207). https://doi.org/10.1007/978-

There are two modes of control recognised in the cognitive psychological literature. Controlled processing is slow, requires serial attention to sub-tasks, and requires effortful memory retrieval and decision making. In contrast automatic control is... Read More about Controlled and automatic processing in animals and machines with application to autonomous vehicle control.

Maximising audiovisual correlation with automatic lip tracking and vowel based segmentation (2009)
Presentation / Conference Contribution
Abel, A., Hussain, A., Nguyen, Q., Ringeval, F., Chetouani, M., & Milgram, M. (2009). Maximising audiovisual correlation with automatic lip tracking and vowel based segmentation. In Biometric ID Management and Multimodal Communication (65-72). https://do

In recent years, the established link between the various human communication production domains has become more widely utilised in the field of speech processing. In this work, a state of the art Semi Adaptive Appearance Model (SAAM) approach develo... Read More about Maximising audiovisual correlation with automatic lip tracking and vowel based segmentation.

Multi-modal speech processing methods: an overview and future research directions using a MATLAB based audio-visual toolbox (2009)
Presentation / Conference Contribution
Abel, A., & Hussain, A. (2009). Multi-modal speech processing methods: an overview and future research directions using a MATLAB based audio-visual toolbox. In Multimodal Signals: Cognitive and Algorithmic Issues (121-129). https://doi.org/10.1007/978-3-

This paper presents an overview of the main multi-modal speech enhancement methods reported to date. In particular, a new MATLAB based Toolbox developed by Barbosa et al (2007) for processing audio-visual data is reviewed and its performance potentia... Read More about Multi-modal speech processing methods: an overview and future research directions using a MATLAB based audio-visual toolbox.

Speech recognition system and formant based analysis of spoken Arabic vowels (2009)
Presentation / Conference Contribution
Alotaibi, Y., & Hussain, A. (2009). Speech recognition system and formant based analysis of spoken Arabic vowels. In Future Generation Information Technology (50-60). https://doi.org/10.1007/978-3-642-10509-8_7

Arabic is one of the world’s oldest languages and is currently the second most spoken language in terms of number of speakers. However, it has not received much attention from the traditional speech processing research community. This study is specif... Read More about Speech recognition system and formant based analysis of spoken Arabic vowels.

Verification & validation of agent based simulations using the VOMAS (virtual overlay multi-agent system) approach (2009)
Presentation / Conference Contribution
Niazi, M. A., Hussain, A., & Kolberg, M. (2009). Verification & validation of agent based simulations using the VOMAS (virtual overlay multi-agent system) approach. In MALLOW'009: Multi-Agent Logics, Languages, and Organisations Federated Workshops: Proc

Agent Based Models are very popular in a number of different areas. For example, they have been used in a range of domains ranging from modeling of tumor growth, immune systems, molecules to models of social networks, crowds and computer and mobile s... Read More about Verification & validation of agent based simulations using the VOMAS (virtual overlay multi-agent system) approach.

A new hybrid agent-based modeling & simulation decision support system for breast cancer data analysis (2009)
Presentation / Conference Contribution
Siddiqa, A., Niazi, M., Mustafa, F., Bokhari, H., Hussain, A., Akram, N., …Iqbal, S. (2009). A new hybrid agent-based modeling & simulation decision support system for breast cancer data analysis. In 2009 International Conference on Information and Com

In this paper, we present a novel technique of building hybrid decision support systems which integrates traditional decision support systems with agent based models for use in breast cancer analysis for better prediction and recommendation. Our syst... Read More about A new hybrid agent-based modeling & simulation decision support system for breast cancer data analysis.

Emergent common functional principles in control theory and the vertebrate brain: A case study with autonomous vehicle control (2008)
Presentation / Conference Contribution
Hussain, A., Gurney, K., Abdullah, R., & Chambers, J. (2008). Emergent common functional principles in control theory and the vertebrate brain: A case study with autonomous vehicle control. In Artificial Neural Networks - ICANN 2008 (949-958). https://do

This paper describes emergent neurobiological characteristics of an intelligent multiple-controller that has been developed for controlling the throttle, brake and steering subsystems of a validated vehicle model. Simulation results demonstrate the e... Read More about Emergent common functional principles in control theory and the vertebrate brain: A case study with autonomous vehicle control.

Simulation of the research process (2008)
Presentation / Conference Contribution
Niazi, M., Hussain, A., Baig, A., & Bhatti, S. (2008). Simulation of the research process. In Proceedings - Winter Simulation Conference (1326-1334). https://doi.org/10.1109/WSC.2008.4736206

This paper presents first steps towards the development of a formal model of the research process. We evaluate the use of simulation as a tool for the evaluation of research strategies in nascent research organizations faced with the absence of signi... Read More about Simulation of the research process.

A novel psychoacoustically motivated multichannel speech enhancement system (2007)
Presentation / Conference Contribution
Hussain, A., Cifani, S., Squartini, S., Piazza, F., & Durrani, T. (2007). A novel psychoacoustically motivated multichannel speech enhancement system. In Verbal and Nonverbal Communication Behaviours COST Action 2102 International Workshop, Vietri sul Ma

The ubiquitous noise reduction / speech enhancement problem has gained an increasing interest in recent years. This is due both to progress made by microphone-array systems and to the successful introduction of perceptual models. In the last decade,... Read More about A novel psychoacoustically motivated multichannel speech enhancement system.

Using biclustering for automatic attribute selection to enhance global visualization (2007)
Presentation / Conference Contribution
Abdullah, A., & Hussain, A. (2007). Using biclustering for automatic attribute selection to enhance global visualization. In Pixelization Paradigm Visual Information Expert Workshop, VIEW 2006, Paris, France, April 24-25, 2006, Revised Selected Papers (3

Data mining involves useful knowledge discovery using a data matrix consisting of records and attributes or variables. Not all the attributes may be useful in knowledge discovery, as some of them may be redundant, irrelevant, noisy or even opposing.... Read More about Using biclustering for automatic attribute selection to enhance global visualization.

Fuzzy logic based switching and tuning supervisor for a multi-variable multiple controller (2007)
Presentation / Conference Contribution
Abdullah, R. A., Hussain, A., & Polycarpou, M. M. (2007). Fuzzy logic based switching and tuning supervisor for a multi-variable multiple controller. In 2007 IEEE International Fuzzy Systems Conference. https://doi.org/10.1109/FUZZY.2007.4295613

This paper presents a novel fuzzy-logic based switching and tuning supervisor for an intelligent multiple-controller framework. The fuzzy logic based supervisor operates at the highest level of the system and makes a switching decision, on the basis... Read More about Fuzzy logic based switching and tuning supervisor for a multi-variable multiple controller.

Dissimilarity analysis of signal processing methods for texture classification (2006)
Presentation / Conference Contribution
Qaiser, N., Hussain, M., Hussain, A., Iqbal, N., & Qaiser, N. (2006). Dissimilarity analysis of signal processing methods for texture classification. In 2005 Pakistan Section Multitopic Conference. https://doi.org/10.1109/INMIC.2005.334512

As observed from the literature survey, there is no commonly accepted quantitative definition of visual texture. As a consequence, researchers seeking a quantitative texture measure have been forced to search intuitively for texture features, and the... Read More about Dissimilarity analysis of signal processing methods for texture classification.

A new radial basis function neural network based multi-variable adaptive pole-zero placement controller (2006)
Presentation / Conference Contribution
Abdullah, R., Hussain, A., & Zayed, A. (2006). A new radial basis function neural network based multi-variable adaptive pole-zero placement controller. In 2006 IEEE International Conference on Engineering of Intelligent Systems. https://doi.org/10.1109/I

In this paper a new multi-variable adaptive controller algorithm for non-linear dynamical systems has been derived which employs the radial basis function (RBF) neural network. In the proposed controller, the unknown plant is represented by an equiva... Read More about A new radial basis function neural network based multi-variable adaptive pole-zero placement controller.

Blind equalization of communication channels with equal energy sources using a combined HOS-SOS approach (2006)
Presentation / Conference Contribution
Naveed, A., Qureshi, I., Hussain, A., & Cheema, T. (2006). Blind equalization of communication channels with equal energy sources using a combined HOS-SOS approach. In 2006 IEEE International Conference on Engineering of Intelligent Systems. https://doi.

This paper presents a combined higher order statistics (HOS) and second order statistics (SOS) approach to blind equalization of white as well as colored sources. Remarkable convergence speed has been achieved through an additional term in the cost f... Read More about Blind equalization of communication channels with equal energy sources using a combined HOS-SOS approach.

Heuristics and meta-heuristics for bandwidth minimization of sparse matrices (2006)
Presentation / Conference Contribution
Abdullah, A., & Hussain, A. (2006). Heuristics and meta-heuristics for bandwidth minimization of sparse matrices. In 2006 IEEE International Conference on Engineering of Intelligent Systems. https://doi.org/10.1109/ICEIS.2006.1703188

In this paper a new crossing minimization based method is proposed to solve the well-known matrix bandwidth minimization problem, which is to permute the rows and columns of the matrix so as to bring all the non-zero elements of the matrix to reside... Read More about Heuristics and meta-heuristics for bandwidth minimization of sparse matrices.

Non-linear predictors based on the functionally expanded neural networks for speech feature extraction (2006)
Presentation / Conference Contribution
Chetouani, M., Hussain, A., Gas, B., & Zarader, J. (2006). Non-linear predictors based on the functionally expanded neural networks for speech feature extraction. In 2006 IEEE International Conference on Engineering of Intelligent Systems. https://doi.or

In this paper we focus on the design of the feature extractor stage of the speech recognition system which aims to compute optimal vectors for the next phoneme classification stage. We propose a new non-linear feature extraction method based on the l... Read More about Non-linear predictors based on the functionally expanded neural networks for speech feature extraction.

Stabilization of non-linear inertia wheel pendulum system using a new dynamic surface control based technique (2006)
Presentation / Conference Contribution
Qaiser, N., Iqbal, N., & Hussain, A. (2006). Stabilization of non-linear inertia wheel pendulum system using a new dynamic surface control based technique. In 2006 IEEE International Conference on Engineering of Intelligent Systems. https://doi.org/10.11

This paper considers the stabilization problem of inertia-wheel pendulum (IWP), a widely studied nonlinear mechanical system. The IWP is a classical example of flat under-actuated mechanical systems, for which the design of control laws becomes a cha... Read More about Stabilization of non-linear inertia wheel pendulum system using a new dynamic surface control based technique.

A new RBF neural network based non-linear self-tuning pole-zero placement controller (2005)
Presentation / Conference Contribution
Abdullah, R., Hussain, A., & Zayed, A. (2005). A new RBF neural network based non-linear self-tuning pole-zero placement controller. In Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005 15th International Conference, Warsaw,

In this paper a new self-tuning controller algorithm for non-linear dynamical systems has been derived using the Radial Basis Function Neural Network (RBF). In the proposed controller, the unknown non-linear plant is represented by an equivalent mode... Read More about A new RBF neural network based non-linear self-tuning pole-zero placement controller.

Biclustering gene expression data in the presence of noise (2005)
Presentation / Conference Contribution
Abdullah, A., & Hussain, A. (2005). Biclustering gene expression data in the presence of noise. In Artificial Neural Networks: Biological Inspirations – ICANN 2005 15th International Conference, Warsaw, Poland, September 11-15, 2005. Proceedings, Part

Production of gene expression chip involves a large number of error-prone steps that lead to a high level of noise in the corresponding data. Given the variety of available biclustering algorithms, one of the problems faced by biologists is the selec... Read More about Biclustering gene expression data in the presence of noise.

New neural network based mobile location estimation in a metropolitan area (2005)
Presentation / Conference Contribution
Muhammad, J., Hussain, A., Neskovic, A., & Magill, E. (2005). New neural network based mobile location estimation in a metropolitan area. In Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005 15th International Conference, Wa

This paper presents a new neural network based approach to the prediction of mobile locations using signal strength measurements in a simulated metropolitan area. The prediction of a mobile location using propagation path loss (signal strength) is a... Read More about New neural network based mobile location estimation in a metropolitan area.

New sub-band processing framework using non-linear predictive models for speech feature extraction (2005)
Presentation / Conference Contribution
Chetouani, M., Hussain, A., Gas, B., & Zarader, J. (2005). New sub-band processing framework using non-linear predictive models for speech feature extraction. In Nonlinear Analyses and Algorithms for Speech Processing (284-290). https://doi.org/10.1007/1

Speech feature extraction methods are commonly based on time and frequency processing approaches. In this paper, we propose a new framework based on sub-band processing and non-linear prediction. The key idea is to pre-process the speech signal by a... Read More about New sub-band processing framework using non-linear predictive models for speech feature extraction.

Non-linear predictive models for speech processing (2005)
Presentation / Conference Contribution
Chetouani, M., Hussain, A., Faundez-Zanuy, M., & Gas, B. (2005). Non-linear predictive models for speech processing. In Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005 15th International Conference, Warsaw, Poland, Septemb

This paper aims to provide an overview of the emerging area of non-linear predictive modelling for speech processing. Traditional predictors are linear based models related to the speech production model. However, non-linear phenomena involved in the... Read More about Non-linear predictive models for speech processing.

Nonlinear adaptive speech enhancement inspired by early auditory processing (2005)
Presentation / Conference Contribution
Hussain, A., Durrani, T. S., Alkulaibi, A., & Mtetwa, N. (2005). Nonlinear adaptive speech enhancement inspired by early auditory processing. In Nonlinear Speech Modeling and Applications: Advanced Lectures and Revised Selected Papers (291-316). https://

This paper presents non-linear adaptive speech enhancement schemes inspired by features of early auditory processing. A generic multi-microphone sub-band adaptive (MMSBA) framework is described which allows for the manipulation of several factors tha... Read More about Nonlinear adaptive speech enhancement inspired by early auditory processing.

Novel sub-band adaptive systems incorporating wiener filtering for binaural speech enhancement (2005)
Presentation / Conference Contribution
Hussain, A., Squartini, S., & Piazza, F. (2005). Novel sub-band adaptive systems incorporating wiener filtering for binaural speech enhancement. In Nonlinear Analyses and Algorithms for Speech Processing International Conference on Non-Linear Speech Proc

In this paper, new Wiener filtering based binaural sub-band schemes are proposed for adaptive speech-enhancement. The proposed architectures combine a Multi-Microphone Sub-band Adaptive (MMSBA) system with Wiener filtering in order to further reduce... Read More about Novel sub-band adaptive systems incorporating wiener filtering for binaural speech enhancement.

The COST-277 European action: An overview (2005)
Presentation / Conference Contribution
Faundez-Zanuy, M., Laine, U., Kubin, G., McLaughlin, S., Kleijn, B., Chollet, G., …Hussain, A. (2005). The COST-277 European action: An overview. In Nonlinear Analyses and Algorithms for Speech Processing International Conference on Non-Linear Speech P

This paper summarizes the rationale for proposing the COST-277 “nonlinear speech processing” action, and the work done during these last four years. In addition, future perspectives are described.

Temporal classification for fault-prediction in a real-world telecommunications network (2005)
Presentation / Conference Contribution
Jaudet, M., Iqbal, N., Hussain, A., & Sharif, K. (2005). Temporal classification for fault-prediction in a real-world telecommunications network. In Proceedings of the IEEE Symposium on Emerging Technologies, 2005 (209-214). https://doi.org/10.1109/ICET.

This paper presents a new temporal classification approach for fault-prediction in a Telecommunications Network. The countrywide data network of Pakistan Telecom (PTCL) has been selected as a basis for the investigation of classification algorithms t... Read More about Temporal classification for fault-prediction in a real-world telecommunications network.

Neural networks for fault-prediction in a telecommunications network (2004)
Presentation / Conference Contribution
Jaudet, M., Iqbal, N., & Hussain, A. (2004). Neural networks for fault-prediction in a telecommunications network. In 8th International Multitopic Conference, 2004. Proceedings of INMIC 2004 (315-320). https://doi.org/10.1109/INMIC.2004.1492896

The main topic of this paper is fault prediction from large alarm records stored in different databases of non-cooperating network management systems. We have chosen the countrywide data network of Pakistan Telecom (PTCL) as a basis for the investiga... Read More about Neural networks for fault-prediction in a telecommunications network.

New neural network based mobile location estimation in urban propagation models (2003)
Presentation / Conference Contribution
Muhammad, J., Hussain, A., & Ahmed, W. (2003). New neural network based mobile location estimation in urban propagation models. . https://doi.org/10.1109/INMIC.2003.1416679

Location estimation finds its applications in many important decisions in cellular networks. Hand offs, cellular fraud detection and location sensitive billing are some of the examples. Many different techniques are currently in use. This work first... Read More about New neural network based mobile location estimation in urban propagation models.

Novel non-linear PID based multiple-controller incorporating a neural network learning sub-model (2003)
Presentation / Conference Contribution
Zayed, A., & Hussain, A. (2003). Novel non-linear PID based multiple-controller incorporating a neural network learning sub-model. In 7th International Multi Topic Conference, 2003. INMIC 2003 (283-289). https://doi.org/10.1109/INMIC.2003.1416729

The paper proposes a new non-linear adaptive PID based multiple-controller incorporating a neural network learning sub-model. The unknown non-linear plant is represented by an equivalent model consisting of a linear time-varying sub-model plus a non-... Read More about Novel non-linear PID based multiple-controller incorporating a neural network learning sub-model.

Stability analysis of a new non-linear pole-zero placement controller incorporating neural networks (2003)
Presentation / Conference Contribution
Zayed, A., & Hussain, A. (2003). Stability analysis of a new non-linear pole-zero placement controller incorporating neural networks. In Proceedings - INMIC 2003: IEEE 7th International Multi Topic Conference (290-294). https://doi.org/10.1109/INMIC.2003

The stability analysis and parameter convergence of a newly reported self-tuning pole-zero placement controller algorithm for non-linear dynamic systems are studied. The original controller overcomes the shortcomings of other linear designs and provi... Read More about Stability analysis of a new non-linear pole-zero placement controller incorporating neural networks.

Attempting to Reduce the Vanishing Gradient Effect through a novel Recurrent Multiscale Architecture (2003)
Presentation / Conference Contribution
Squartini, S., Hussain, A., & Piazza, F. (2003). Attempting to Reduce the Vanishing Gradient Effect through a novel Recurrent Multiscale Architecture. In Proceedings of the International Joint Conference on Neural Networks (2819-2824). https://doi.org/10

This paper proposes a possible solution to the vanishing gradient problem in recurrent neural networks, occurring when such networks are applied to solving tasks where detection of long term dependencies is required. The main idea consists of pre-pro... Read More about Attempting to Reduce the Vanishing Gradient Effect through a novel Recurrent Multiscale Architecture.

Preprocessing based solution for the vanishing gradient problem in recurrent neural networks (2003)
Presentation / Conference Contribution
Squartini, S., Hussain, A., & Piazza, F. (2003). Preprocessing based solution for the vanishing gradient problem in recurrent neural networks. . https://doi.org/10.1109/ISCAS.2003.1206412

In this paper, a possible solution to the vanishing gradient problem in recurrent neural networks (RNN) is proposed. The main idea consists of pre-processing the signal (a time series typically) through a wavelet decomposition, in order to separate t... Read More about Preprocessing based solution for the vanishing gradient problem in recurrent neural networks.

A recurrent multiscale architecture for long-term memory prediction task (2003)
Presentation / Conference Contribution
Squartini, S., Hussain, A., & Piazza, F. (2003). A recurrent multiscale architecture for long-term memory prediction task. In 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03) (789-792). https

In the past few years, researchers have been extensively studying the application of recurrent neural networks (RNNs) to solving tasks where detection of long term dependencies is required. This paper proposes an original architecture termed the Recu... Read More about A recurrent multiscale architecture for long-term memory prediction task.

Stochastic resonance and finite resolution in a network of leaky integrate-and-fire neurons (2002)
Presentation / Conference Contribution
Mtetwa, N., Smith, L., & Hussain, A. (2002). Stochastic resonance and finite resolution in a network of leaky integrate-and-fire neurons. In Artificial Neural Networks — ICANN 2002 (117-122). https://doi.org/10.1007/3-540-46084-5_20

This paper discusses the effect of stochastic resonance in a network of leaky integrate-and-fire (LIF) neurons and investigates its realisation on a Field Programmable Gate Array (FPGA). We report in this study that stochastic resonance which is main... Read More about Stochastic resonance and finite resolution in a network of leaky integrate-and-fire neurons.

A new neural network and pole placement based adaptive composite controller (2002)
Presentation / Conference Contribution
Hussain, A., Zayed, A. S., & Smith, L. (2002). A new neural network and pole placement based adaptive composite controller. In Proceedings. IEEE International Multi Topic Conference, 2001. IEEE INMIC 2001. Technology for the 21st Century (267-271). https

The paper describes a new composite control method combining a neural network estimator with a conventional pole-placement based adaptive controller. The neural network estimation technique presented by Hussain (2000) is particularly effective when t... Read More about A new neural network and pole placement based adaptive composite controller.

A modified generalised minimum-variance stochastic self-tuning controller with pole-zero placement (2001)
Presentation / Conference Contribution
Zayed, A., Hussain, A., & Smith, L. (2001). A modified generalised minimum-variance stochastic self-tuning controller with pole-zero placement. In Proceedings. IEEE International Multi Topic Conference, 2001. IEEE INMIC 2001. Technology for the 21st Cen

The paper proposes a modified robust self-tuning controller, which minimises a cost function, incorporating system input, system output and set-point. It provides an adaptive mechanism which ensures that both the closed-loop poles and zeros are place... Read More about A modified generalised minimum-variance stochastic self-tuning controller with pole-zero placement.