All Outputs (555)

Challenges Faced by International Students in Understanding British Accents and Their Mitigation Strategies—A Mixed Methods Study (2024)
Journal Article
Vasquez Diaz, K. R., & Iqbal, J. (2024). Challenges Faced by International Students in Understanding British Accents and Their Mitigation Strategies—A Mixed Methods Study. Education Sciences, 14(7), Article 784. https://doi.org/10.3390/educsci14070784

The massive relocation of international students calls for a thorough investigation of diverse difficulties faced by them, among which language-related barriers are reported to have serious consequences. The main goal of this research is to investiga... Read More about Challenges Faced by International Students in Understanding British Accents and Their Mitigation Strategies—A Mixed Methods Study.

Artificial Intelligence in Education: An automatic Rule-Based Chatbot to generate guidance from lecture recordings (2024)
Journal Article
Hing, W., Gordon, N., & Al Jaber, T. (2024). Artificial Intelligence in Education: An automatic Rule-Based Chatbot to generate guidance from lecture recordings. Acta Scientific Computer Sciences, 6(7), 64-74

In a new era of educational and research-based chatbots, implementing personalised interactive learning resources is critical in enhancing students' academic experiences. Whilst general purpose chatbots are now available with a range of platforms, th... Read More about Artificial Intelligence in Education: An automatic Rule-Based Chatbot to generate guidance from lecture recordings.

AI enabled: a novel IoT-based fake currency detection using millimeter wave (mmWave) sensor (2024)
Journal Article
Niaz, F., Zhang, J., Khalid, M., Qureshi, K. N., Zheng, Y., Younas, M., & Imran, N. (in press). AI enabled: a novel IoT-based fake currency detection using millimeter wave (mmWave) sensor. Computing, https://doi.org/10.1007/s00607-024-01300-2

In recent years, the significance of millimeter wave sensors has achieved a paramount role, especially in the non-invasive and ubiquitous analysis of various materials and objects. This paper introduces a novel IoT-based fake currency detection using... Read More about AI enabled: a novel IoT-based fake currency detection using millimeter wave (mmWave) sensor.

Fuzzy-Augmented Model Reference Adaptive PID Control Law Design for Robust Voltage Regulation in DC–DC Buck Converters (2024)
Journal Article
Saleem, O., Rasheed Ahmad, K., & Iqbal, J. (2024). Fuzzy-Augmented Model Reference Adaptive PID Control Law Design for Robust Voltage Regulation in DC–DC Buck Converters. Mathematics, 12(12), Article 1893. https://doi.org/10.3390/math12121893

This paper presents a novel fuzzy-augmented model reference adaptive voltage regulation strategy for the DC–DC buck converters to enhance their resilience against random input variations and load-step transients. The ubiquitous proportional-integral-... Read More about Fuzzy-Augmented Model Reference Adaptive PID Control Law Design for Robust Voltage Regulation in DC–DC Buck Converters.

Improving stability and adaptability of automotive electric steering systems based on a novel optimal integrated algorithm (2024)
Journal Article
Nguyen, T. A., & Iqbal, J. (2024). Improving stability and adaptability of automotive electric steering systems based on a novel optimal integrated algorithm. Engineering Computations, 41(4), 991-1034. https://doi.org/10.1108/EC-10-2023-0675

Purpose: Design a novel optimal integrated control algorithm for the automotive electric steering system to improve the stability and adaptation of the system. Design/methodology/approach: Simulation and calculation. Findings: The output signals foll... Read More about Improving stability and adaptability of automotive electric steering systems based on a novel optimal integrated algorithm.

Fuzzy Fault-tolerant Controller With Guaranteed Performance for MIMO Systems Under Uncertain Initial State (2024)
Journal Article
Yin, C. W., Riaz, S., Uppal, A. A., & Iqbal, J. (2024). Fuzzy Fault-tolerant Controller With Guaranteed Performance for MIMO Systems Under Uncertain Initial State. International journal of control, automation and systems, 22(6), 2038-2054. https://doi.org/10.1007/s12555-023-0327-5

It is always problematic that the initial value of the trajectory tracking error must be inside the area included in the prescribed performance constraint function. To overcome this problem, a novel fault-tolerant control strategy is designed for a s... Read More about Fuzzy Fault-tolerant Controller With Guaranteed Performance for MIMO Systems Under Uncertain Initial State.

Not So Robust after All: Evaluating the Robustness of Deep Neural Networks to Unseen Adversarial Attacks (2024)
Journal Article
Garaev, R., Rasheed, B., & Khan, A. M. (2024). Not So Robust after All: Evaluating the Robustness of Deep Neural Networks to Unseen Adversarial Attacks. Algorithms, 17, Article 162. https://doi.org/10.3390/a17040162

Deep neural networks (DNNs) have gained prominence in various applications, but remain vulnerable to adversarial attacks that manipulate data to mislead a DNN. This paper aims to challenge the efficacy and transferability of two contemporary defense... Read More about Not So Robust after All: Evaluating the Robustness of Deep Neural Networks to Unseen Adversarial Attacks.

Bayesian relative composite quantile regression approach of ordinal latent regression model with L1/2 regularization (2024)
Journal Article
Tian, Y.-Z., Wu, C.-H., Tai, L.-N., Mian, Z., & Tian, M.-Z. (2024). Bayesian relative composite quantile regression approach of ordinal latent regression model with L1/2 regularization. Statistical Analysis and Data Mining, 17(2), Article e11683. https://doi.org/10.1002/sam.11683

Ordinal data frequently occur in various fields such as knowledge level assessment, credit rating, clinical disease diagnosis, and psychological evaluation. The classic models including cumulative logistic regression or probit regression are often us... Read More about Bayesian relative composite quantile regression approach of ordinal latent regression model with L1/2 regularization.

Computation Tree Logic Model Checking of Multi-Agent Systems Based on Fuzzy Epistemic Interpreted Systems (2024)
Journal Article
Li, X., Ma, Z., Mian, Z., Liu, Z., Huang, R., & He, N. (2024). Computation Tree Logic Model Checking of Multi-Agent Systems Based on Fuzzy Epistemic Interpreted Systems. Computers, Materials & Continua, 78(3), 4129-4152. https://doi.org/10.32604/cmc.2024.047168

Model checking is an automated formal verification method to verify whether epistemic multi-agent systems adhere to property specifications. Although there is an extensive literature on qualitative properties such as safety and liveness, there is sti... Read More about Computation Tree Logic Model Checking of Multi-Agent Systems Based on Fuzzy Epistemic Interpreted Systems.

Minimum Distance and Minimum Time Optimal Path Planning With Bioinspired Machine Learning Algorithms for Faulty Unmanned Air Vehicles (2024)
Journal Article
Tutsoy, O., Asadi, D., Ahmadi, K., Nabavi-Chashmi, S. Y., & Iqbal, J. (2024). Minimum Distance and Minimum Time Optimal Path Planning With Bioinspired Machine Learning Algorithms for Faulty Unmanned Air Vehicles. IEEE Transactions on Intelligent Transportation Systems, https://doi.org/10.1109/TITS.2024.3367769

Unmanned air vehicles operate in highly dynamic and unknown environments where they can encounter unexpected and unseen failures. In the presence of emergencies, autonomous unmanned air vehicles should be able to land at a minimum distance or minimum... Read More about Minimum Distance and Minimum Time Optimal Path Planning With Bioinspired Machine Learning Algorithms for Faulty Unmanned Air Vehicles.

Adaptive-optimal MIMO nonsingular terminal sliding mode control of twin-rotor helicopter system: meta-heuristics and super-twisting based control approach (2024)
Journal Article
Rezoug, A., Messah, A., Messaoud, W. A., Baizid, K., & Iqbal, J. (2024). Adaptive-optimal MIMO nonsingular terminal sliding mode control of twin-rotor helicopter system: meta-heuristics and super-twisting based control approach. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 46(3), Article 162. https://doi.org/10.1007/s40430-024-04714-3

This research proposes a novel hybrid control technique based on nonsingular terminal sliding mode (NTSM) control, metaheuristic optimization algorithms and adaptive super-twisting based on Lyapunov stability analysis for controlling Quanser aero sim... Read More about Adaptive-optimal MIMO nonsingular terminal sliding mode control of twin-rotor helicopter system: meta-heuristics and super-twisting based control approach.

Tailored risk assessment and forecasting in intermittent claudication (2024)
Journal Article
Ravindhran, B., Prosser, J., Lim, A., Lathan, R., Mishra, B., Hitchman, L., Smith, G. E., Carradice, D., Thakker, D., Chetter, I. C., & Pymer, S. (2024). Tailored risk assessment and forecasting in intermittent claudication. BJS Open, 8(1), Article zrad166. https://doi.org/10.1093/bjsopen/zrad166

Background: Guidelines recommend cardiovascular risk reduction and supervised exercise therapy as the first line of treatment in intermittent claudication, but implementation challenges and poor patient compliance lead to significant variation in man... Read More about Tailored risk assessment and forecasting in intermittent claudication.

Application of Artificial Intelligence and Data Science in Detecting the Impact of Usability from Evaluation of Mobile Health Applications (2024)
Journal Article
Kayode, O., Al Jaber, T., & Gordon, N. (2024). Application of Artificial Intelligence and Data Science in Detecting the Impact of Usability from Evaluation of Mobile Health Applications. International Journal on Engineering Technologies and Informatics, 5(1), 1-9. https://doi.org/10.51626/ijeti.2024.05.00070

Mobile health (mHealth) applications have demonstrated immense potential for facilitating preventative care and disease management through intuitive platforms. However, realizing transformational health objectives relies on creating accessible tools... Read More about Application of Artificial Intelligence and Data Science in Detecting the Impact of Usability from Evaluation of Mobile Health Applications.

A LDA-Based Social Media Data Mining Framework for Plastic Circular Economy (2024)
Journal Article
Xue, Y., Kambhampati, C., Cheng, Y., Mishra, N., Wulandhari, N., & Deutz, P. (2024). A LDA-Based Social Media Data Mining Framework for Plastic Circular Economy. International Journal of Computational Intelligence Systems, 17(1), Article 8. https://doi.org/10.1007/s44196-023-00375-7

The mass production of plastic waste has caused an urgent worldwide public health crisis. Although government policies and industrial innovation are the driving forces to meet this challenge, trying to understand public attitudes may improve the effi... Read More about A LDA-Based Social Media Data Mining Framework for Plastic Circular Economy.

Using outlier elimination to assess learning-based correspondence matching methods (2024)
Journal Article
Ding, X., Luo, Y., Jie, B., Li, Q., & Cheng, Y. (2024). Using outlier elimination to assess learning-based correspondence matching methods. Information Sciences, 659, Article 120056. https://doi.org/10.1016/j.ins.2023.120056

Recently, deep learning (DL) technology has been widely used in correspondence matching. The learning-based models are usually trained on benign image pairs with partial overlaps. Since DL model is usually data-dependent, non-overlapping images may b... Read More about Using outlier elimination to assess learning-based correspondence matching methods.

Robust GDI-based adaptive recursive sliding mode control (RGDI-ARSMC) for a highly nonlinear MIMO system with varying dynamics of UAV (2024)
Journal Article
Abbas, N., Liu, X., & Iqbal, J. (2024). Robust GDI-based adaptive recursive sliding mode control (RGDI-ARSMC) for a highly nonlinear MIMO system with varying dynamics of UAV. Journal of mechanical science and technology, 38(3), https://doi.org/10.1007/s12206-024-0234-6

The novelty of the proposed work lies in the control technique, referred to as the robust generalized dynamic inversion based adaptive recursive sliding mode control (RGDI-ARSMC), for addressing various challenges to control a highly coupled and pert... Read More about Robust GDI-based adaptive recursive sliding mode control (RGDI-ARSMC) for a highly nonlinear MIMO system with varying dynamics of UAV.

NeuFG: Neural Fuzzy Geometric Representation for 3D Reconstruction (2024)
Journal Article
Hong, Q., Yang, C., Chen, J., Li, Z., Wu, Q., Li, Q., & Tian, J. (2024). NeuFG: Neural Fuzzy Geometric Representation for 3D Reconstruction. IEEE Transactions on Fuzzy Systems, https://doi.org/10.1109/TFUZZ.2024.3447088

3D reconstruction from multi-view images is considered as a longstanding problem in computer vision and graphics. In order to achieve high-fidelity geometry and appearance of 3D scenes, this paper proposes a novel geometric object learning method for... Read More about NeuFG: Neural Fuzzy Geometric Representation for 3D Reconstruction.

NEAT Activity Detection using Smartwatch (2024)
Journal Article
Dewan, A., Gunturi, V., & Naik, V. (2024). NEAT Activity Detection using Smartwatch. International Journal of Ad Hoc and Ubiquitous Computing, 45(1), 36-51. https://doi.org/10.1504/IJAHUC.2024.136141

This paper presents a system for distinguishing non-exercise activity thermogenesis (NEAT) and non-NEAT activities at home. NEAT includes energy expended on activities apart from sleep, eating, or traditional exercise. Our study focuses on specific N... Read More about NEAT Activity Detection using Smartwatch.

Pyramid Hierarchical Spatial-Spectral Transformer for Hyperspectral Image Classification (2024)
Journal Article
Ahmad, M., Butt, M. H. F., Mazzara, M., Distefano, S., Khan, A. M., & Altuwaijri, H. A. (2024). Pyramid Hierarchical Spatial-Spectral Transformer for Hyperspectral Image Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 17681-17689. https://doi.org/10.1109/jstars.2024.3461851

The Transformer model encounters challenges with variable-length input sequences, leading to efficiency and scalability concerns. To overcome this, we propose a pyramid-based hierarchical Spatial-Spectral Transformer (PyFormer). This innovative appro... Read More about Pyramid Hierarchical Spatial-Spectral Transformer for Hyperspectral Image Classification.

Exploring the Impact of Conceptual Bottlenecks on Adversarial Robustness of Deep Neural Networks (2024)
Journal Article
Rasheed, B., Abdelhamid, M., Khan, A., Menezes, I., & Masood Khatak, A. (2024). Exploring the Impact of Conceptual Bottlenecks on Adversarial Robustness of Deep Neural Networks. IEEE Access, 12, 131323-131335. https://doi.org/10.1109/ACCESS.2024.3457784

Deep neural networks (DNNs), while powerful, often suffer from a lack of interpretability and vulnerability to adversarial attacks. Concept bottleneck models (CBMs), which incorporate intermediate high-level concepts into the model architecture, prom... Read More about Exploring the Impact of Conceptual Bottlenecks on Adversarial Robustness of Deep Neural Networks.