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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. (2014, December). Electronics, communications and networks IV: Proceedings of the 4th international conference on electronics, communications and networks, 12-15 December 2014, Beijing, China. Presented at 4th International Conference on Electronics, Communications and Networks (CECNET IV), 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, December). Solar powered wheel chair for physically challenged people using surface EMG signal. Presented at 2015 IEEE Symposium Series on Computational Intelligence, Cape Town, South Africa

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.-L. (2015, August). Efficient text localization in born-digital images by local contrast-based segmentation. Presented at 2015 13th International Conference on Document Analysis and Recognition (ICDAR), Tunis, Tunisia

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.

Computational Intelligence for Changing Environments [Guest Editorial] (2015)
Journal Article
Hussain, A., Tao, D., Wu, J., & Zhao, D. (2015). Computational Intelligence for Changing Environments [Guest Editorial]. IEEE Computational Intelligence Magazine, 10(4), 10-11. https://doi.org/10.1109/MCI.2015.2472119

The articles in this special section focus on the growing interest in biologically inspired learning (BIL), which refers to a wide range of learning techniques, motivated by biology, that try to mimic specific biological functions or behaviors.

Sentiment Data Flow Analysis by Means of Dynamic Linguistic Patterns (2015)
Journal Article
Poria, S., Cambria, E., Gelbukh, A., Bisio, F., & Hussain, A. (2015). Sentiment Data Flow Analysis by Means of Dynamic Linguistic Patterns. IEEE Computational Intelligence Magazine, 10(4), 26-36. https://doi.org/10.1109/MCI.2015.2471215

Emulating the human brain is one of the core challenges of computational intelligence, which entails many key problems of artificial intelligence, including understanding human language, reasoning, and emotions. In this work, computational intelligen... Read More about Sentiment Data Flow Analysis by Means of Dynamic Linguistic Patterns.

A Novel Near-Infrared Spectroscopy Based Spatiotemporal Cognition Study of the Human Brain Using Clustering (2015)
Journal Article
Abdullah, A., Khan, I. H., Basuhail, A., & Hussain, A. (2015). A Novel Near-Infrared Spectroscopy Based Spatiotemporal Cognition Study of the Human Brain Using Clustering. Cognitive Computation, 7(6), 693-705. https://doi.org/10.1007/s12559-015-9358-4

In this study, we investigate how the two hemispheres of the brain are involved spatiotemporally in a cognitive-based setup when people relate different colors with different concepts (for example, the color ‘blue’ associated with the word ‘dependabl... Read More about A Novel Near-Infrared Spectroscopy Based Spatiotemporal Cognition Study of the Human Brain Using Clustering.

An online generalized eigenvalue version of Laplacian Eigenmaps for visual big data (2015)
Journal Article
Malik, Z. K., Hussain, A., & Wu, J. (2016). An online generalized eigenvalue version of Laplacian Eigenmaps for visual big data. Neurocomputing, 173(2), 127-136. https://doi.org/10.1016/j.neucom.2014.12.119

This paper presents a generalized incremental Laplacian Eigenmaps (GENILE), a novel online version of the Laplacian Eigenmaps, one of the most popular manifold-based dimensionality reduction techniques which solves the generalized eigenvalue problem.... Read More about An online generalized eigenvalue version of Laplacian Eigenmaps for visual big data.

Fusing audio, visual and textual clues for sentiment analysis from multimodal content (2015)
Journal Article
Poria, S., Cambria, E., Howard, N., Huang, G.-B., & Hussain, A. (2016). Fusing audio, visual and textual clues for sentiment analysis from multimodal content. Neurocomputing, 174(Part A), 50-59. https://doi.org/10.1016/j.neucom.2015.01.095

A huge number of videos are posted every day on social media platforms such as Facebook and YouTube. This makes the Internet an unlimited source of information. In the coming decades, coping with such information and mining useful knowledge from it w... Read More about Fusing audio, visual and textual clues for sentiment analysis from multimodal content.

A novel classification algorithm based on incremental semi-supervised support vector machine (2015)
Journal Article
Gao, F., Mei, J., Sun, J., Wang, J., Yang, E., & Hussain, A. (2015). A novel classification algorithm based on incremental semi-supervised support vector machine. PLOS ONE, 10(8), Article e0135709. https://doi.org/10.1371/journal.pone.0135709

For current computational intelligence techniques, a major challenge is how to learn new concepts in changing environment. Traditional learning schemes could not adequately address this problem due to a lack of dynamic data selection mechanism. In th... Read More about A novel classification algorithm based on incremental semi-supervised support vector machine.

Integrating SUMO and kalman filter models towards a social network based approach of public transport arrival time prediction (2015)
Journal Article
Abidin, A. F., Kolberg, M., & Hussain, A. (2015). Integrating SUMO and kalman filter models towards a social network based approach of public transport arrival time prediction. International Journal of Simulation: Systems, Science & Technology, 16(3), 5.1-5.9. https://doi.org/10.5013/IJSSST.a.16.03.05

Bus arrival time is a key service for improving public transport attractiveness by providing users with an accurate arrival time. In this research, a model of bus arrival time prediction, which aims to improve arrival time accuracy, is proposed. The... Read More about Integrating SUMO and kalman filter models towards a social network based approach of public transport arrival time prediction.

Local energy-based shape histogram feature extraction technique for breast cancer diagnosis (2015)
Journal Article
Wajid, S. K., & Hussain, A. (2015). Local energy-based shape histogram feature extraction technique for breast cancer diagnosis. Expert Systems with Applications, 42(20), 6990-6999. https://doi.org/10.1016/j.eswa.2015.04.057

This paper proposes a novel local energy-based shape histogram (LESH) as the feature set for recognition of abnormalities in mammograms. It investigates the implication of this technique on mammogram datasets of the Mammographic Image Analysis Societ... Read More about Local energy-based shape histogram feature extraction technique for breast cancer diagnosis.

Discriminative bi-term topic model for headline-based social news clustering (2015)
Presentation / Conference Contribution
Xia, Y., Tang, N., Hussain, A., & Cambria, E. (2015, May). Discriminative bi-term topic model for headline-based social news clustering. Presented at The Twenty-Eighth International Florida Artificial Intelligence Research Society Conference (FLAIRS), Hollywood, Florida

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 Biologically Inspired Vision-Based Approach for Detecting Multiple Moving Objects in Complex Outdoor Scenes (2015)
Journal Article
Tu, Z., Zheng, A., Yang, E., Luo, B., & Hussain, A. (2015). A Biologically Inspired Vision-Based Approach for Detecting Multiple Moving Objects in Complex Outdoor Scenes. Cognitive Computation, 7(5), 539-551. https://doi.org/10.1007/s12559-015-9318-z

In the human brain, independent components of optical flows from the medial superior temporal area are speculated for motion cognition. Inspired by this hypothesis, a novel approach combining independent component analysis (ICA) with principal compon... Read More about A Biologically Inspired Vision-Based Approach for Detecting Multiple Moving Objects in Complex Outdoor Scenes.

A localization toolkit for sentic net (2015)
Presentation / Conference Contribution
Xia, Y., Li, X., Cambria, E., & Hussain, A. (2014, December). A localization toolkit for sentic net. Presented at 2014 IEEE International Conference on Data Mining Workshop, Shenzhen, China

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.

Concept-Level Sentiment Analysis with Dependency-Based Semantic Parsing: A Novel Approach (2015)
Journal Article
Agarwal, B., Poria, S., Mittal, N., Gelbukh, A., & Hussain, A. (2015). Concept-Level Sentiment Analysis with Dependency-Based Semantic Parsing: A Novel Approach. Cognitive Computation, 7(4), 487-499. https://doi.org/10.1007/s12559-014-9316-6

Sentiment analysis from unstructured natural language text has recently received considerable attention from the research community. In the frame of biologically inspired machine learning approaches, finding good feature sets is particularly challeng... Read More about Concept-Level Sentiment Analysis with Dependency-Based Semantic Parsing: A Novel Approach.

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., Mahmud, M., Luo, B., & Slack, W. (2014, December). A novel cardiovascular decision support framework for effective clinical risk assessment. Presented at 2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE), Orlando, FL, USA

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. (2014, December). An efficient computer aided decision support system for breast cancer diagnosis using Echo State Network classifier. Presented at 2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE), Orlando, FL, USA

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. (2014, December). Cognitively inspired speech processing for multimodal hearing technology. Presented at 2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE), Orlando, FL, USA

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., Zakir, U., Yan, X., Luo, B., & Rajak, M. (2014, December). Intelligent image processing techniques for cancer progression detection, recognition and prediction in the human liver. Presented at 2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE), Orlando, FL, USA

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.