Outputs (387)

When the timeline meets the pipeline: A survey on automated cyberbullying detection (2021)
Journal Article
Elsafoury, F., Katsigiannis, S., Pervez, Z., & Ramzan, N. (2021). When the timeline meets the pipeline: A survey on automated cyberbullying detection. IEEE Access, 9, 103541-103563. https://doi.org/10.1109/access.2021.3098979

Web 2.0 helped user-generated platforms to spread widely. Unfortunately, it also allowed for cyberbullying to spread. Cyberbullying has negative effects that could lead to cases of depression and low self-esteem. It has become crucial to develop tool... Read More about When the timeline meets the pipeline: A survey on automated cyberbullying detection.

Directions of the 100 most cited chatbot-related human behavior research: A review of academic publications (2021)
Journal Article
Wang, J., Hwang, G., & Chang, C. (2021). Directions of the 100 most cited chatbot-related human behavior research: A review of academic publications. Computers and Education: Artificial Intelligence, 2, https://doi.org/10.1016/j.caeai.2021.100023

Chatbots are becoming a common trend in the service industry, education, and daily life. Increasing evidence has shown that chatbots have the potential to change the way people learn and search for information in human behavior. However, a systematic... Read More about Directions of the 100 most cited chatbot-related human behavior research: A review of academic publications.

Computational Model for Predicting User Aesthetic Preference for GUI using DCNNs (2021)
Journal Article
Xing, B., Si, H., Chen, J., Ye, M., & Shi, L. (2021). Computational Model for Predicting User Aesthetic Preference for GUI using DCNNs. CCF Transactions on Pervasive Computing and Interaction, 3, 147-169. https://doi.org/10.1007/s42486-021-00064-4

Visual aesthetics is vital in determining the usability of the graphical user interface (GUI). It can strengthen the competitiveness of interactive online applications. Human aesthetic preferences for GUI are implicit and linked to various aspects of... Read More about Computational Model for Predicting User Aesthetic Preference for GUI using DCNNs.

Towards Designing Profitable Courses: Predicting Student Purchasing Behaviour in MOOCs (2021)
Journal Article
Alshehri, M., Alamri, A., Cristea, A. I., & Stewart, C. D. (2021). Towards Designing Profitable Courses: Predicting Student Purchasing Behaviour in MOOCs. International Journal of Artificial Intelligence in Education, 31(2), 215-233. https://doi.org/10.1007/s40593-021-00246-2

Since their ‘official’ emergence in 2012 (Gardner and Brooks 2018), massive open online courses (MOOCs) have been growing rapidly. They offer low-cost education for both students and content providers; however, currently there is a very low level of... Read More about Towards Designing Profitable Courses: Predicting Student Purchasing Behaviour in MOOCs.

BED: A new dataset for EEG-based biometrics (2021)
Journal Article
Arnau-González, P., Katsigiannis, S., Arevalillo-Herráez, M., & Ramzan, N. (2021). BED: A new dataset for EEG-based biometrics. IEEE Internet of Things Journal, 8(15), 12219-12230. https://doi.org/10.1109/jiot.2021.3061727

Various recent research works have focused on the use of electroencephalography (EEG) signals in the field of biometrics. However, advances in this area have somehow been limited by the absence of a common testbed that would make it possible to easil... Read More about BED: A new dataset for EEG-based biometrics.

A language learning support system using course-centered ontology and its evaluation (2014)
Journal Article
Wang, J., Mendori, T., & Xiong, J. (2014). A language learning support system using course-centered ontology and its evaluation. Computers & Education, 78, https://doi.org/10.1016/j.compedu.2014.06.009

A Knowledge Comparison Environment for Supporting Meaningful Learning of E-Book Users (2016)
Journal Article
Wang, J., Ogata, H., & Shimada, A. (2016). A Knowledge Comparison Environment for Supporting Meaningful Learning of E-Book Users. Systems, 4(2), https://doi.org/10.3390/systems4020021

Examining Human-Horse Interaction by Means of Affect Recognition via Physiological Signals (2019)
Journal Article
Althobaiti, T., Katsigiannis, S., West, D., & Ramzan, N. (2019). Examining Human-Horse Interaction by Means of Affect Recognition via Physiological Signals. IEEE Access, 7, 77857-77867. https://doi.org/10.1109/access.2019.2922037

For some time, equine-assisted therapy (EAT), i.e., the use of horse-related activities for therapeutic reasons, has been recognised as a useful approach in the treatment of many mental health issues such as post-traumatic stress disorder (PTSD), dep... Read More about Examining Human-Horse Interaction by Means of Affect Recognition via Physiological Signals.

2D-gel spot detection and segmentation based on modified image-aware grow-cut and regional intensity information (2015)
Journal Article
Kostopoulou, E., Katsigiannis, S., & Maroulis, D. (2015). 2D-gel spot detection and segmentation based on modified image-aware grow-cut and regional intensity information. Computer Methods and Programs in Biomedicine, 122(1), 26-39. https://doi.org/10.1016/j.cmpb.2015.06.007

Development and evaluation of a visualization system to support meaningful e-book learning (2020)
Journal Article
Wang, J., Shimada, A., Oi, M., Ogata, H., & Tabata, Y. (2020). Development and evaluation of a visualization system to support meaningful e-book learning. Interactive Learning Environments, 1-18. https://doi.org/10.1080/10494820.2020.1813178

A QoE and Simulator Sickness Evaluation of a Smart-Exercise-Bike Virtual Reality System via User Feedback and Physiological Signals (2019)
Journal Article
Katsigiannis, S., Willis, R., & Ramzan, N. (2019). A QoE and Simulator Sickness Evaluation of a Smart-Exercise-Bike Virtual Reality System via User Feedback and Physiological Signals. IEEE Transactions on Consumer Electronics, 65(1), 119-127. https://doi.org/10.1109/tce.2018.2879065

DREAMER: A Database for Emotion Recognition Through EEG and ECG Signals From Wireless Low-cost Off-the-Shelf Devices (2018)
Journal Article
Katsigiannis, S., & Ramzan, N. (2018). DREAMER: A Database for Emotion Recognition Through EEG and ECG Signals From Wireless Low-cost Off-the-Shelf Devices. IEEE Journal of Biomedical and Health Informatics, 22(1), 98-107. https://doi.org/10.1109/jbhi.2017.2688239

A Contourlet Transform Feature Extraction Scheme for Ultrasound Thyroid Texture Classification (2010)
Journal Article
Katsigiannis, S., Keramidas, E., & Maroulis, D. (2010). A Contourlet Transform Feature Extraction Scheme for Ultrasound Thyroid Texture Classification

Using wearable physiological sensors for affect-aware Intelligent Tutoring Systems (2020)
Journal Article
Alqahtani, F., Katsigiannis, S., & Ramzan, N. (2021). Using wearable physiological sensors for affect-aware Intelligent Tutoring Systems. IEEE Sensors Journal, 21(3), 3366-3378. https://doi.org/10.1109/jsen.2020.3023886

Intelligent Tutoring Systems (ITS) have shown great potential in enhancing the learning process by being able to adapt to the learner’s knowledge level, abilities, and difficulties. An aspect that can affect the learning process but is not taken into... Read More about Using wearable physiological sensors for affect-aware Intelligent Tutoring Systems.

A Customizable Language Learning Support System Using Ontology-Driven Engine (2013)
Journal Article
Wang, J., Mendori, T., & Xiong, J. (2013). A Customizable Language Learning Support System Using Ontology-Driven Engine. International Journal of Distance Education Technologies, 11(4), 81-96. https://doi.org/10.4018/ijdet.2013100106

The Reliability and Validity of Felder- Silverman Index of Learning Styles in Mandarin Version (2015)
Journal Article
Wang, J., & Mendori, T. (2015). The Reliability and Validity of Felder- Silverman Index of Learning Styles in Mandarin Version

Triaxial Accelerometer-Based Falls and Activities of Daily Life Detection Using Machine Learning (2020)
Journal Article
Althobaiti, T., Katsigiannis, S., & Ramzan, N. (2020). Triaxial Accelerometer-Based Falls and Activities of Daily Life Detection Using Machine Learning. Sensors, 20(13), Article 3777. https://doi.org/10.3390/s20133777

The detection of activities of daily living (ADL) and the detection of falls is of utmost importance for addressing the issue of serious injuries and death as a consequence of elderly people falling. Wearable sensors can provide a viable solution for... Read More about Triaxial Accelerometer-Based Falls and Activities of Daily Life Detection Using Machine Learning.

On the influence of affect in EEG-based subject identification (2018)
Journal Article
Arnau-González, P., Arevalillo-Herráez, M., Katsigiannis, S., & Ramzan, N. (2021). On the influence of affect in EEG-based subject identification. IEEE Transactions on Affective Computing, 12(2), 391-401. https://doi.org/10.1109/taffc.2018.2877986

MIGS-GPU: Microarray Image Gridding and Segmentation on the GPU (2017)
Journal Article
Katsigiannis, S., Zacharia, E., & Maroulis, D. (2017). MIGS-GPU: Microarray Image Gridding and Segmentation on the GPU. IEEE Journal of Biomedical and Health Informatics, 21(3), 867-874. https://doi.org/10.1109/jbhi.2016.2537922

Increased Levels of Coagulation Factor XI in Plasma Are Related to Alzheimer’s Disease Diagnosis (2020)
Journal Article
Begic, E., Hadzidedic, S., Obradovic, S., Begic, Z., & Causevic, M. (2020). Increased Levels of Coagulation Factor XI in Plasma Are Related to Alzheimer’s Disease Diagnosis. Journal of Alzheimer's Disease, 77(1), 375-386. https://doi.org/10.3233/jad-200358

Background:Alzheimer’s disease is a complex disorder of unclear etiology that develops in the elderly population. It is a debilitating, progressive neurodegeneration for which disease-modifying therapies do not exist. Previous studies have suggested... Read More about Increased Levels of Coagulation Factor XI in Plasma Are Related to Alzheimer’s Disease Diagnosis.