All Outputs (497)

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., & 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. (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.

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.

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. (2014, November). The development of an intelligent tutorial system for system development. Presented at 2014 International Conference on Web and Open Access to Learning (ICWOAL), Dubai, United Arab Emirates

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.

Convergence Analysis of a New Self Organizing Map Based Optimization (SOMO) Algorithm (2015)
Journal Article
Khan, A., Xue, L. Z., Wei, W., Qu, Y. P., Hussain, A., & Vencio, R. Z. N. (2015). Convergence Analysis of a New Self Organizing Map Based Optimization (SOMO) Algorithm. Cognitive Computation, 7(4), 477-486. https://doi.org/10.1007/s12559-014-9315-7

The self-organizing map (SOM) approach has been used to perform cognitive and biologically inspired computing in a growing range of cross-disciplinary fields. Recently, the SOM based neural network framework was adapted to solve continuous derivative... Read More about Convergence Analysis of a New Self Organizing Map Based Optimization (SOMO) Algorithm.

A novel refined track initiation algorithm for group targets based on group model (2014)
Journal Article
Gao, F., Ren, H., Wang, J., Hussain, A., & Durrani, T. S. (2014). A novel refined track initiation algorithm for group targets based on group model. Chinese Journal of Electronics, 23(4), 851-856

Traditional refined track initiation methods for group targets have mistakes or loss of tracks when tracking irregular motions, for the reason that they rely on a stable relative position of group members. To solve the problem, a group dynamic model... Read More about A novel refined track initiation algorithm for group targets based on group model.

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, November). Classification of Fish Ectoparasite Genus Gyrodactylus SEM Images Using ASM and Complex Network Model. Presented at 21st International Conference on Neural Information Processing, ICONIP 2014, Kuching, Malaysia

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, April). Dependency-based semantic parsing for concept-level text analysis. Presented at 15th International Conference, CICLing 2014, Kathmandu, Nepal

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.