All Outputs (13)

Arabic sentiment analysis using dependency-based rules and deep neural networks (2022)
Journal Article
Diwali, A., Dashtipour, K., Saeedi, K., Gogate, M., Cambria, E., & Hussain, A. (2022). Arabic sentiment analysis using dependency-based rules and deep neural networks. Applied Soft Computing, 127, Article 109377. https://doi.org/10.1016/j.asoc.2022.109377

With the growth of social platforms in recent years and the rapid increase in the means of communication through these platforms, a significant amount of textual data is available that contains an abundance of individuals’ opinions. Sentiment analysi... Read More about Arabic sentiment analysis using dependency-based rules and deep neural networks.

Artificial intelligence-enabled social media analysis for pharmacovigilance of COVID-19 vaccinations in the United Kingdom: Observational Study (2022)
Journal Article
Hussain, Z., Sheikh, Z., Tahir, A., Dashtipour, K., Gogate, M., Sheikh, A., & Hussain, A. (2022). Artificial intelligence-enabled social media analysis for pharmacovigilance of COVID-19 vaccinations in the United Kingdom: Observational Study. JMIR Public

Background: The roll-out of vaccines for SARS-CoV-2 in the United Kingdom, started in December 2020. Uptake has been high, and there has been a subsequent reduction in infections, hospitalisations and deaths in vaccinated individuals. However, vacci... Read More about Artificial intelligence-enabled social media analysis for pharmacovigilance of COVID-19 vaccinations in the United Kingdom: Observational Study.

A novel temporal attentive-pooling based convolutional recurrent architecture for acoustic signal enhancement (2022)
Journal Article
Hussain, T., Wang, W., Gogate, M., Dashtipour, K., Tsao, Y., Lu, X., Ahsan, A., & Hussain, A. (2022). A novel temporal attentive-pooling based convolutional recurrent architecture for acoustic signal enhancement. IEEE Transactions on Artificial Intelligen

Removing background noise from acoustic observations to obtain clean signals is an important research topic regarding numerous real acoustic applications. Owing to their strong model capacity in function mapping, deep neural network-based algorithms... Read More about A novel temporal attentive-pooling based convolutional recurrent architecture for acoustic signal enhancement.

Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform (2022)
Journal Article
Abd, M. H., Al-Suhail, G. A., Tahir, F. R., Ali Ali, A. M., Abbood, H. A., Dashtipour, K., …Ahmad, J. (2022). Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform. Remote Sensing, 14(9), Article 1984. https://doi.org/10.3390/

There is no doubt that chaotic systems are still attractive issues in various radar applications and communication systems. In this paper, we present a new 0.3 GHz mono-static microwave chaotic radar. It includes a chaotic system based on a time-dela... Read More about Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform.

Personalized wearable electrodermal sensing-based human skin hydration level detection for sports, health and wellbeing (2022)
Journal Article
Liaqat, S., Dashtipour, K., Rizwan, A., Usman, M., Shah, S. A., Arshad, K., …Ramzan, N. (2022). Personalized wearable electrodermal sensing-based human skin hydration level detection for sports, health and wellbeing. Scientific Reports, 12(1), Article 3

Personalized hydration level monitoring play vital role in sports, health, wellbeing and safety of a person while performing particular set of activities. Clinical staff must be mindful of numerous physiological symptoms that identify the optimum hyd... Read More about Personalized wearable electrodermal sensing-based human skin hydration level detection for sports, health and wellbeing.

A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls (2021)
Journal Article
Varone, G., Boulila, W., Lo Giudice, M., Benjdira, B., Mammone, N., Ieracitano, C., …Aguglia, U. (2022). A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls

Until now, clinicians are not able to evaluate the Psychogenic Non-Epileptic Seizures (PNES) from the rest-electroencephalography (EEG) readout. No EEG marker can help differentiate PNES cases from healthy subjects. In this paper, we have investigate... Read More about A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls.

Intrusion Detection Framework for the Internet of Things Using a Dense Random Neural Network (2021)
Journal Article
Latif, S., Huma, Z. E., Jamal, S. S., Ahmed, F., Ahmad, J., Zahid, A., …Abbasi, Q. H. (2022). Intrusion Detection Framework for the Internet of Things Using a Dense Random Neural Network. IEEE Transactions on Industrial Informatics, 18(9), 6435-6444. ht

The Internet of Things (IoT) devices, networks, and applications have become an integral part of modern societies. Despite their social, economic, and industrial benefits, these devices and networks are frequently targeted by cybercriminals. Hence, I... Read More about Intrusion Detection Framework for the Internet of Things Using a Dense Random Neural Network.

A Review and Comparison of the State-of-the-Art Techniques for Atrial Fibrillation Detection and Skin Hydration (2021)
Journal Article
Liaqat, S., Dashtipour, K., Zahid, A., Arshad, K., Ullah Jan, S., Assaleh, K., & Ramzan, N. (2021). A Review and Comparison of the State-of-the-Art Techniques for Atrial Fibrillation Detection and Skin Hydration. Frontiers in Communications and Networks,

Atrial fibrillation (AF) is one of the most common types of cardiac arrhythmia, with a prevalence of 1–2% in the community, increasing the risk of stroke and myocardial infarction. Early detection of AF, typically causing an irregular and abnormally... Read More about A Review and Comparison of the State-of-the-Art Techniques for Atrial Fibrillation Detection and Skin Hydration.

Radar Sensing for Activity Classification in Elderly People Exploiting Micro-Doppler Signatures Using Machine Learning (2021)
Journal Article
Taylor, W., Dashtipour, K., Shah, S. A., Hussain, A., Abbasi, Q. H., & Imran, M. A. (2021). Radar Sensing for Activity Classification in Elderly People Exploiting Micro-Doppler Signatures Using Machine Learning. Sensors, 21(11), Article 3881. https://doi.

The health status of an elderly person can be identified by examining the additive effects of aging along with disease linked to it and can lead to ‘unstable incapacity’. This health status is determined by the apparent decline of independence in act... Read More about Radar Sensing for Activity Classification in Elderly People Exploiting Micro-Doppler Signatures Using Machine Learning.

Novel Ensemble Algorithm for Multiple Activity Recognition in Elderly People Exploiting Ubiquitous Sensing Devices (2021)
Journal Article
Liaqat, S., Dashtipour, K., Shah, S. A., Rizwan, A., Alotaibi, A. A., Althobaiti, T., …Ramzan, N. (2021). Novel Ensemble Algorithm for Multiple Activity Recognition in Elderly People Exploiting Ubiquitous Sensing Devices. IEEE Sensors Journal, 21(16), 1

Ambient assisted living is good way to look after ageing population that enables us to detect human’s activities of daily living (ADLs) and postures, as number of older adults are increasing at rapid pace. Posture detection is used to provide the ass... Read More about Novel Ensemble Algorithm for Multiple Activity Recognition in Elderly People Exploiting Ubiquitous Sensing Devices.

A semi-supervised approach for sentiment analysis of arab (ic+ izi) messages: Application to the algerian dialect (2021)
Journal Article
Guellil, I., Adeel, A., Azouaou, F., Benali, F., Hachani, A., Dashtipour, K., …Hussain, A. (2021). A semi-supervised approach for sentiment analysis of arab (ic+ izi) messages: Application to the algerian dialect. SN Computer Science, 2, Article 118. ht

In this paper, we propose a semi-supervised approach for sentiment analysis of Arabic and its dialects. This approach is based on a sentiment corpus, constructed automatically and reviewed manually by Algerian dialect native speakers. This approach c... Read More about A semi-supervised approach for sentiment analysis of arab (ic+ izi) messages: Application to the algerian dialect.

Robust Visual Saliency Optimization Based on Bidirectional Markov Chains (2020)
Journal Article
Jiang, F., Kong, B., Li, J., Dashtipour, K., & Gogate, M. (2021). Robust Visual Saliency Optimization Based on Bidirectional Markov Chains. Cognitive Computation, 13, 69–80. https://doi.org/10.1007/s12559-020-09724-6

Saliency detection aims to automatically highlight the most important area in an image. Traditional saliency detection methods based on absorbing Markov chain only take into account boundary nodes and often lead to incorrect saliency detection when t... Read More about Robust Visual Saliency Optimization Based on Bidirectional Markov Chains.

CochleaNet: A robust language-independent audio-visual model for real-time speech enhancement (2020)
Journal Article
Gogate, M., Dashtipour, K., Adeel, A., & Hussain, A. (2020). CochleaNet: A robust language-independent audio-visual model for real-time speech enhancement. Information Fusion, 63, 273-285. https://doi.org/10.1016/j.inffus.2020.04.001

Noisy situations cause huge problems for the hearing-impaired, as hearing aids often make speech more audible but do not always restore intelligibility. In noisy settings, humans routinely exploit the audio-visual (AV) nature of speech to selectively... Read More about CochleaNet: A robust language-independent audio-visual model for real-time speech enhancement.