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Outputs (86)

FireNet-v2: Improved Lightweight Fire Detection Model for Real-Time IoT Applications (2023)
Journal Article
Shees, A., Ansari, M. S., Varshney, A., Asghar, M. N., & Kanwal, N. (2023). FireNet-v2: Improved Lightweight Fire Detection Model for Real-Time IoT Applications. Procedia Computer Science, 218, 2233-2242. https://doi.org/10.1016/j.procs.2023.01.199

Fire hazards cause huge ecological, social and economical losses in day to day life. Due to the rapid increase in the prevalence of fire accidents, it has become vital to equip the assets with fire prevention systems. There have been numerous researc... Read More about FireNet-v2: Improved Lightweight Fire Detection Model for Real-Time IoT Applications.

Empirical Study of the Evolution of Python Questions on StackOverflow (2023)
Journal Article
Syam, G., Lal, S., Chen, T., & Sangeeta, S. (2023). Empirical Study of the Evolution of Python Questions on StackOverflow. e-Informatica Software Engineering Journal (EISEJ), 17(1), 230107. https://doi.org/10.37190/e-inf230107

Background: Python is a popular and easy-to-use programming language. It is constantly expanding, with new features and libraries being introduced daily for a broad range of applications. This dynamic expansion needs a robust support structure for de... Read More about Empirical Study of the Evolution of Python Questions on StackOverflow.

Transnational In-Group Solidarity Networks in the Case of #Hellobrother (2023)
Journal Article
POOLE, E., RİCHARDSON, J. E., GİRAUD, E. H., & DE QUİNCEY, E. (in press). Transnational In-Group Solidarity Networks in the Case of #Hellobrother. Journal of Media and Religion Studies, 6(2), 14-22. https://doi.org/10.47951/mediad.1401093

This paper examines the dynamics of one hashtag, #hellobrother, shared on Twitter following the Christchurch terror attack on 15th March 2019. It was analysed as part of a larger study #Contesting Islamophobia: Representation and Appropriation in Med... Read More about Transnational In-Group Solidarity Networks in the Case of #Hellobrother.

A novel attention model across heterogeneous features for stuttering event detection (2023)
Journal Article
Al-Banna, A., Fang, H., & Edirisinghe, E. (2024). A novel attention model across heterogeneous features for stuttering event detection. Expert systems with applications, 244, Article 122967. https://doi.org/10.1016/j.eswa.2023.122967

Stuttering is a prevalent speech disorder affecting millions worldwide. To provide an automatic and objective stuttering assessment tool, Stuttering Event Detection (SED) is under extensive investigation for advanced speech research and applications.... Read More about A novel attention model across heterogeneous features for stuttering event detection.

The membership problem for subsemigroups of GL2(Z) is NP-complete (2023)
Journal Article
Bell, P. C., Hirvensalo, M., & Potapov, I. (2024). The membership problem for subsemigroups of GL2(Z) is NP-complete. Information and Computation, 296, Article 105132. https://doi.org/10.1016/j.ic.2023.105132

We show that the problem of determining if the identity matrix belongs to a finitely generated semigroup of 2x2 matrices from the General Linear Group GL(2,Z) is solvable in NP. We extend this to prove that the membership problem is decidable in NP f... Read More about The membership problem for subsemigroups of GL2(Z) is NP-complete.

Decision Questions for Probabilistic Automata on Small Alphabets (2023)
Journal Article
Bell, P. C., & Semukhin, P. (2023). Decision Questions for Probabilistic Automata on Small Alphabets. Logical Methods in Computer Science, 19(4), 1-36. https://doi.org/10.46298/lmcs-19%284%3A36%292023

We study the emptiness and lambda-reachability problems for unary and binary Probabilistic Finite Automata (PFA) and characterise the complexity of these problems in terms of the degree of ambiguity of the automaton and the size of its alphabet. Our... Read More about Decision Questions for Probabilistic Automata on Small Alphabets.

Smoclust: synthetic minority oversampling based on stream clustering for evolving data streams (2023)
Journal Article
Chiu, C. W., & Minku, L. L. (2024). Smoclust: synthetic minority oversampling based on stream clustering for evolving data streams. Machine Learning, 113(7), 4671-4721. https://doi.org/10.1007/s10994-023-06420-y

Many real-world data stream applications not only suffer from concept drift but also class imbalance. Yet, very few existing studies investigated this joint challenge. Data difficulty factors, which have been shown to be key challenges in class imbal... Read More about Smoclust: synthetic minority oversampling based on stream clustering for evolving data streams.

VidSearch: Privacy-by-Design Video Search and Retrieval System for Large-Scale CCTV Data (2023)
Presentation / Conference Contribution
Tahir, M., Qiao, Y., Kanwal, N., Lee, B., & Asghar, M. N. (2023, December). VidSearch: Privacy-by-Design Video Search and Retrieval System for Large-Scale CCTV Data. Presented at 2023 International Conference on Machine Learning and Applications (ICMLA), Jacksonville, FL, USA

The surge in surveillance camera deployment in the era of Big Data and the Internet of Things (IoT) has emphasized the paramount importance of safeguarding the privacy of individuals, objects, and locations they record. Therefore, this paper proposes... Read More about VidSearch: Privacy-by-Design Video Search and Retrieval System for Large-Scale CCTV Data.

Investigation of combustion model via the local collocation technique based on moving Taylor polynomial (MTP) approximation/domain decomposition method with error analysis (2023)
Journal Article
Abbaszadeh, M., Khodadadian, A., Parvizi, M., & Dehghan, M. (2024). Investigation of combustion model via the local collocation technique based on moving Taylor polynomial (MTP) approximation/domain decomposition method with error analysis. Engineering Analysis with Boundary Elements, 159, 288-301. https://doi.org/10.1016/j.enganabound.2023.11.010

In this paper, we develop a new meshless numerical procedure for simulating the combustion model. To that end, we employ a local meshless collocation method according to the moving Taylor polynomial (MTP) approximation. The space derivative is approx... Read More about Investigation of combustion model via the local collocation technique based on moving Taylor polynomial (MTP) approximation/domain decomposition method with error analysis.