Dr SHAILY KABIR's Outputs (7)

An Interval Creation Approach to Construct Interval Type-2 Fuzzy Sets (2024)
Presentation / Conference Contribution
Amartya, P. S., Kabir, S., Babu, S. C. K., & Jahan, M. (2024, June). An Interval Creation Approach to Construct Interval Type-2 Fuzzy Sets. Presented at IEEE International Conference on Fuzzy Systems, Yokohama, Japan

Interval type-2 fuzzy sets (IT2 FSs) are more popular over type-1 fuzzy sets (T1 FSs) as they capture uncertainty in a better way in many real-world problems. Modelling uncertainty with an IT2 FS is relatively complex and solely depends on how to def... Read More about An Interval Creation Approach to Construct Interval Type-2 Fuzzy Sets.

A Trust Model for Edge-Driven Vehicular Ad Hoc Networks Using Fuzzy Logic (2023)
Journal Article
Hasan, M. M., Jahan, M., & Kabir, S. (2023). A Trust Model for Edge-Driven Vehicular Ad Hoc Networks Using Fuzzy Logic. IEEE Transactions on Intelligent Transportation Systems, 24(12), 14037-14050. https://doi.org/10.1109/tits.2023.3305342

Trust establishment among vehicles is essential for vehicular ad hoc networks (VANETs) as it directly impacts the security and privacy of vehicular communication. Many trust estimation approaches have been introduced, however, they often suffer from... Read More about A Trust Model for Edge-Driven Vehicular Ad Hoc Networks Using Fuzzy Logic.

An end-to-end authentication mechanism for Wireless Body Area Networks (2023)
Journal Article
Jahan, M., Tuz Zohra, F., Kamal Parvez, M., Kabir, U., Mohaimen Al Radi, A., & Kabir, S. (2023). An end-to-end authentication mechanism for Wireless Body Area Networks. Smart Health, 29, Article 100413. https://doi.org/10.1016/j.smhl.2023.100413

Wireless Body Area Network (WBAN) ensures a high-quality healthcare service to patients by providing remote and relentless monitoring of their health conditions. Nevertheless, the patients' health-related data are very sensitive and require security... Read More about An end-to-end authentication mechanism for Wireless Body Area Networks.

Towards Handling Uncertainty-at-Source in AI – A Review and Next Steps for Interval Regression (2023)
Journal Article
Kabir, S., Wagner, C., & Ellerby, Z. (2023). Towards Handling Uncertainty-at-Source in AI – A Review and Next Steps for Interval Regression. IEEE Transactions on Artificial Intelligence, 5(1), 3-22. https://doi.org/10.1109/TAI.2023.3234930

Most of statistics and AI draw insights through modelling discord or variance between sources (i.e., inter-source) of information. Increasingly however, research is focusing on uncertainty arising at the level of individual measurements (i.e., within... Read More about Towards Handling Uncertainty-at-Source in AI – A Review and Next Steps for Interval Regression.

Visualization of Interval Regression for Facilitating Data and Model Insight (2022)
Presentation / Conference Contribution
Kabir, S., & Wagner, C. (2022, July). Visualization of Interval Regression for Facilitating Data and Model Insight. Presented at IEEE World Congress on Computational Intelligence 2022 (IEEE WCCI 2022), Padova, Italy

With growing significance of interval-valued data, interest in artificial intelligence methods tailored to this data type is similarly increasing across a range of application domains. Here, regression, i.e., the modelling of the association between... Read More about Visualization of Interval Regression for Facilitating Data and Model Insight.

Interval-Valued Regression - Sensitivity to Data Set Features (2021)
Presentation / Conference Contribution
Kabir, S., & Wagner, C. (2021, July). Interval-Valued Regression - Sensitivity to Data Set Features. Presented at 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Luxembourg, Luxembourg

Regression represents one of the most basic building blocks of data analysis and AI. Despite growing interest in interval-valued data across various fields, approaches to establish regression models for interval-valued data which address and handle t... Read More about Interval-Valued Regression - Sensitivity to Data Set Features.

A Similarity Measure Based on Bidirectional Subsethood for Intervals (2020)
Journal Article
Kabir, S., Wagner, C., Havens, T. C., & Anderson, D. T. (2020). A Similarity Measure Based on Bidirectional Subsethood for Intervals. IEEE Transactions on Fuzzy Systems, 28(11), 2890-2904. https://doi.org/10.1109/tfuzz.2019.2945249

With a growing number of areas leveraging interval-valued data—including in the context of modelling human uncertainty (e.g., in Cyber Security), the capacity to accurately and systematically compare intervals for reasoning and computation is increas... Read More about A Similarity Measure Based on Bidirectional Subsethood for Intervals.