All Outputs (100)

Explaining a staff rostering problem by mining trajectory variance structures. (2023)
Conference Proceeding
FYVIE, M., MCCALL, J.A.W., CHRISTIE, L.A., ZĂVOIANU, A.-C., BROWNLEE, A.E.I. and AINSLIE, R. 2023. Explaining a staff rostering problem by mining trajectory variance structures. In Bramer, M. and Stahl, F. (eds.) Artificial intelligence XL: proceedings of the 43rd SGAI international conference on artificial intelligence (AI-2023), 12-14 December 2023, Cambridge, UK. Lecture notes in computer science, 14381. Cham: Springer [online], pages 275-290. Available from: https://doi.org/10.1007/978-3-031-47994-6_27

The use of Artificial Intelligence-driven solutions in domains involving end-user interaction and cooperation has been continually growing. This has also lead to an increasing need to communicate crucial information to end-users about algorithm behav... Read More about Explaining a staff rostering problem by mining trajectory variance structures..

Object-aware multi-criteria decision-making approach using the heuristic data-driven theory for intelligent transportation systems. (2023)
Conference Proceeding
MEKALA, M.S., EYAD, E. and SRIVASTAVA, G. 2023. Object-aware multi-criteria decision-making approach using the heuristic data-driven theory for intelligent transportation systems. In Proceedings of the 10th IEEE (Institute of Electrical and Electronics Engineers) Data science and advanced analytics international conference 2023 (DSAA 2023), 9-13 October 2023, Thessaloniki, Greece. Piscataway: IEEE [online], 10302554. Available from: https://doi.org/10.1109/DSAA60987.2023.10302554

Sharing up-to-date information about the surrounding measured by On-Board Units (OBUs) and Roadside Units (RSUs) is crucial in accomplishing traffic efficiency and pedestrians safety towards Intelligent Transportation Systems (ITS). Transferring meas... Read More about Object-aware multi-criteria decision-making approach using the heuristic data-driven theory for intelligent transportation systems..

Siamese residual neural network for musical shape evaluation in piano performance assessment. (2023)
Conference Proceeding
LI, X., WEISS, S., YAN, Y., LI, Y., REN, J., SORAGHAN, J. and GONG, M. 2023. Siamese residual neural network for musical shape evaluation in piano performance assessment. In Proceedings of the 31st European signal processing conference 2023 (EUSIPCO 2023), 4-8 September 2023, Helsinki, Finland. Piscataway: IEEE [online], pages 216-220. Available from: https://doi.org/10.23919/EUSIPCO58844.2023.10289901

Understanding and identifying musical shape plays an important role in music education and performance assessment. To simplify the otherwise time- and cost-intensive musical shape evaluation, in this paper we explore how artificial intelligence (AI)... Read More about Siamese residual neural network for musical shape evaluation in piano performance assessment..

Unmasking the imposters: towards improving the generalisation of deep learning methods for face presentation attack detection. (2023)
Thesis
ABDULLAKUTTY, F.C. 2023. Unmasking the imposters: towards improving the generalisation of deep learning methods for face presentation attack detection. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-2270640

Identity theft has had a detrimental impact on the reliability of face recognition, which has been extensively employed in security applications. The most prevalent are presentation attacks. By using a photo, video, or mask of an authorized user, att... Read More about Unmasking the imposters: towards improving the generalisation of deep learning methods for face presentation attack detection..

Robust cardiac segmentation corrected with heuristics. (2023)
Journal Article
CERVANTES-GUZMÁN, A., MCPHERSON, K., OLVERES, J., MORENO-GARCÍA, C.F., ROBLES, F.T., ELYAN, E. and ESCALANTE-RAMÍREZ, B. 2023. Robust cardiac segmentation corrected with heuristics. PLoS ONE [online], 18(10), article e0293560. https://doi.org/10.1371/journal.pone.0293560

Cardiovascular diseases related to the right side of the heart, such as Pulmonary Hypertension, are some of the leading causes of death among the Mexican (and worldwide) population. To avoid invasive techniques such as catheterizing the heart, improv... Read More about Robust cardiac segmentation corrected with heuristics..

3R: a reliable multi agent reinforcement learning based routing protocol for wireless medical sensor networks. (2023)
Journal Article
HAJAR, M.S., KALUTARAGE, H.K. and AL-KADRI, M.O. 2023. 3R: a reliable multi agent reinforcement learning based routing protocol for wireless medical sensor networks. Computer networks [online], 237, article number 110073. Available from: https://doi.org/10.1016/j.comnet.2023.110073

Interest in the Wireless Medical Sensor Network (WMSN) is rapidly gaining attention thanks to recent advances in semiconductors and wireless communication. However, by virtue of the sensitive medical applications and the stringent resource constraint... Read More about 3R: a reliable multi agent reinforcement learning based routing protocol for wireless medical sensor networks..

Early detection of citrus anthracnose caused by Colletotrichum gloeosporioides using hyperspectral imaging. (2023)
Journal Article
TANG, Y., YANG, J., ZHUANG, J., HOU, C., MIAO, A., REN, J., HUANG, H., TAN, Z. and PALIWAL, J. 2023. Early detection of citrus anthracnose caused by Colletotrichum gloeosporioides using hyperspecral imaging. Computers and electronics in agriculture [online], 214, article number 108348. Available from: https://doi.org/10.1016/j.compag.2023.108348

Citrus fruit are susceptible to Colletotrichum gloeosporioides infestation during postharvest and shelf storage. Early and accurate detection of citrus anthracnose is conducive for carrying out targeted pesticide control and mitigating the potential... Read More about Early detection of citrus anthracnose caused by Colletotrichum gloeosporioides using hyperspectral imaging..

ASXC2 approach: a service-X cost optimization strategy based on edge orchestration for IIoT. (2023)
Journal Article
MEKALA, M.S., DHIMAN, G., PARK, J.H., JUNG, H.-Y. and VIRIYASITAVAT, W. 2023. ASXC2 approach: a service-X cost optimization strategy based on edge orchestration for IIoT. IEEE transactions on industrial informatics [online], Early Access. Available from: https://doi.org/10.1109/TII.2023.3315744

Most computation-intensive industry applications and servers encounter service-reliability challenges due to the limited resource capability of the edge. Achieving quality data fusion and accurate service reliability with optimized service-x executio... Read More about ASXC2 approach: a service-X cost optimization strategy based on edge orchestration for IIoT..

Detecting contradictory COVID-19 drug efficacy claims from biomedical literature. (2023)
Conference Proceeding
SOSA, D.N., SURESH, M., POTTS, C. and ALTMAN, R.B. 2023. Detecting contradictory COVID-19 drug efficacy claims from biomedical literature. In Rogers, A., Boyd-Graber, J. and Okazaki, N. (eds.) Proceedings of the 61st Association for Computational Linguistics annual meeting 2023 (ACL 2023), 9-14 July 2023, Toronto, Candada. Stroudsburg, PA: ACL [online], volume 2: short papers, pages 694-713. Available from: https://doi.org/10.18653/v1/2023.acl-short.61

The COVID-19 pandemic created a deluge of questionable and contradictory scientific claims about drug efficacy – an "infodemic" with lasting consequences for science and society. In this work, we argue that NLP models can help domain experts distill... Read More about Detecting contradictory COVID-19 drug efficacy claims from biomedical literature..

Towards feasible counterfactual explanations: a taxonomy guided template-based NLG method. (2023)
Conference Proceeding
SALIMI, P., WIRATUNGA, N., CORSAR, D. and WIJEKOON, A. 2023. Towards feasible counterfactual explanations: a taxonomy guided template-based NLG method. In Gal, K., Nowé, A., Nalepa, G.J., Fairstein, R. and Rădulescu, R. (eds.) ECAI 2023: proceedings of the 26th European conference on artificial intelligence (ECAI 2023), 30 September - 4 October 2023, Kraków, Poland. Frontiers in artificial intelligence and applications, 372. Amsterdam: IOS Press [online], pages 2057-2064. Available from: https://doi.org/10.3233/FAIA230499

Counterfactual Explanations (cf-XAI) describe the smallest changes in feature values necessary to change an outcome from one class to another. However, many cf-XAI methods neglect the feasibility of those changes. In this paper, we introduce a novel... Read More about Towards feasible counterfactual explanations: a taxonomy guided template-based NLG method..

RLIS: resource limited improved security beyond fifth generation networks using deep learning algorithms. (2023)
Journal Article
SELVARAJAN, S., MANOHARAN, H., KHADIDOS, A.O., SHANKAR, A., MEKALA, M.S. and KHADIDOS, A.O. 2023. RLIS: resource limited improved security beyond fifth generation networks using deep learning algorithms. IEEE open journal of the Communications Society [online], 4, pages 2383-2396. Available from: https://doi.org/10.1109/OJCOMS.2023.3318860

This study explores the feasibility of allocating finite resources beyond fifth generation networks for extended reality applications through the implementation of enhanced security measures via offloading analysis (RLIS). The quantification of resou... Read More about RLIS: resource limited improved security beyond fifth generation networks using deep learning algorithms..

Gated recurrent unit autoencoder for fault detection in penicillin fermentation process. (2023)
Conference Proceeding
PETROVSKI, A., ARIFEEN, M. and PETROVSKI, S. 2023. Gated recurrent unit autoencoder for fault detection in penicillin fermentation process. In Kovalev, S., Kotenko, I. and Sukhanov, A. (eds.) Proceedings of the 7th Intelligent information technologies for industry international scientific conference 2023 (IITI'23), 20-25 September 2023, St. Petersburg, Russia, volume 1. Lecture notes in networks and systems (LNNS), 776. Cham: Springer [online], pages 86-95. Available from: https://doi.org/10.1007/978-3-031-43789-2_8

The penicillin fermentation process is a fed-batch system to generate industrial-scale penicillin for antibiotic production. Any fault in the fermentation tank can lead to low-quality penicillin products, which may cause a severe impact on final anti... Read More about Gated recurrent unit autoencoder for fault detection in penicillin fermentation process..

Hyperspectral imaging based corrosion detection in nuclear packages. (2023)
Journal Article
ZABALZA, J., MURRAY, P., BENNETT, S., CAMPBELL, A.J., MARSHALL, S., REN, J., YAN, Y., BERNARD, R., HEPWORTH, S., MALONE, S., COCKBAIN, N., OFFIN, D. and HOLLIDAY, C. 2023. Hyperspectral imaging based corrosion detection in nuclear packages. IEEE sensors journal [online], 23(21), pages 25607-25617. Available from: https://doi.org/10.1109/jsen.2023.3312938

In the Sellafield nuclear site, intermediate level waste and special nuclear material is stored above ground in stainless steel packages or containers, with thousands expected to be stored for several decades before permanent disposal in a geological... Read More about Hyperspectral imaging based corrosion detection in nuclear packages..

Proceedings of the 6th International workshop on knowledge discovery from healthcare data (KDH@IJCAI 2023) (2023)
Conference Proceeding
IBRAHIM, Z., WU, H. and WIRATUNGA, N. (eds.) 2023. Proceedings of the 6th International workshop on knowledge discovery from healthcare data (KDH@IJCAI 2023), co-located with the 32nd International joint conference on artificial intelligence (IJCAI 2023), 20 August 2023, Macao, China. CEUR workshop proceedings, 3479. Aachen: CEUR-WS [online]. Available from: https://ceur-ws.org/Vol-3479/

This workshop is centred around novel AI methodologies that aim to solve some of the grand challenges associated with medical data. Held in conjunction with the International Joint Conference on Artificial Intelligence (IJCAI 2023), this year's works... Read More about Proceedings of the 6th International workshop on knowledge discovery from healthcare data (KDH@IJCAI 2023).

They gave me an opportunity, and I took it: motivations and concerns of adult apprentices. (2023)
Journal Article
SMITH, S., FABIAN, K., TAYLOR-SMITH, E., BARR, M., BERG, T., BRATTON, A., KOLBERG, M., PATERSON, J. and ZARB, M. 2023. They gave me an opportunity, and I took it: motivations and concerns of adult apprentices. Journal of vocational education and training [online] Latest Articles. Available from: https://doi.org/10.1080/13636820.2023.2255576

In the UK context of an ageing population, degree apprenticeships represent a new opportunity to study for a degree while working. Apprentices are full-time employees granted time to study for a degree with a significant workplace learning component.... Read More about They gave me an opportunity, and I took it: motivations and concerns of adult apprentices..

Evaluation of attention-based LSTM and Bi-LSTM networks for abstract text classification in systematic literature review automation. (2023)
Journal Article
OFORI-BOATENG, R., ACEVES-MARTINS, M., JAYNE, C., WIRATUNGA, N. and MORENO-GARCIA, C.F. 2023. Evaluation of attention-based LSTM and Bi-LSTM networks for abstract text classification in systematic literature review automation. Porcedia computer science [online], 222: selected papers from the 2023 International Neural Network Society workshop on deep learning innovations and applications (INNS DLIA 2023), co-located with the 2023 International joint conference on neural networks (IJCNN), 18-32 June 2023, Gold Coast, Australia, pages 114-126. Available from: https://doi.org/10.1016/j.procs.2023.08.149

Systematic Review (SR) presents the highest form of evidence in research for decision and policy-making. Nonetheless, the structured steps involved in carrying out SRs make it demanding for reviewers. Many studies have projected the abstract screenin... Read More about Evaluation of attention-based LSTM and Bi-LSTM networks for abstract text classification in systematic literature review automation..

Beyond vanilla: improved autoencoder-based ensemble in-vehicle intrusion detection system. (2023)
Journal Article
RAJAPAKSHA, S., KALUTARAGE, H., AL-KADRI, M.O., PETROVSKI, A. and MADZUDZO, G. 2023. Beyond vanilla: improved autoencoder-based ensemble in-vehicle intrusion detection system. Journal of information security and applications [online], 77, article number 103570. Available from: https://doi.org/10.1016/j.jisa.2023.103570

Modern automobiles are equipped with a large number of electronic control units (ECUs) to provide safe driver assistance and comfortable services. The controller area network (CAN) provides near real-time data transmission between ECUs with adequate... Read More about Beyond vanilla: improved autoencoder-based ensemble in-vehicle intrusion detection system..

Three-dimensional singular spectrum analysis for precise land cover classification from UAV-borne hyperspectral benchmark datasets. (2023)
Journal Article
FU, H., SUN, G., ZHANG, L., ZHANG, A., REN, J., JIA, X. and LI, F. 2023. Three-dimensional singular spectrum analysis for precise land cover classification from UAV-borne hyperspectral benchmark datasets. ISPRS journal of photogrammetry and remote sensing [online], 203, pages 115-134. Available from: https://doi.org/10.1016/j.isprsjprs.2023.07.013

The precise classification of land covers with hyperspectral imagery (HSI) is a major research-focused topic in remote sensing, especially using unmanned aerial vehicle (UAV) systems as the abundant data sources have brought severe intra-class spectr... Read More about Three-dimensional singular spectrum analysis for precise land cover classification from UAV-borne hyperspectral benchmark datasets..

A quantum-inspired sensor consolidation measurement approach for cyber-physical systems. (2023)
Journal Article
MEKALA, M.S., SRIVASTAVA, G., GANDOMI, A.H., PARK, J.H. and JUNG, H.-Y. 2024. A quantum-inspired sensor consolidation measurement approach for cyber-physical systems. IEEE transactions on network science and engineering [online], 11(1), pages 511-524. Available from: https://doi.org/10.1109/TNSE.2023.3301402

Cyber-Physical System (CPS) devices interconnect to grab data over a common platform from industrial applications. Maintaining immense data and making instant decision analysis by selecting a feasible node to meet latency constraints is challenging.... Read More about A quantum-inspired sensor consolidation measurement approach for cyber-physical systems..

Unmasking the imposters: task-specific feature learning for face presentation attack detection. (2023)
Conference Proceeding
ABDULLAKUTTY, F., ELYAN, E. and JOHNSTON, P. 2023. Unmasking the imposters: task-specific feature learning for face presentation attack detection. In Proceedings of the 2023 International joint conference on neural networks (IJCNN2023), 18-23 June 2023, Gold Coast, Australia. Piscataway: IEEE [online], 10191953. Available from: https://doi.org/10.1109/IJCNN54540.2023.10191953

Presentation attacks pose a threat to the reliability of face recognition systems. A photograph, a video, or a mask representing an authorised user can be used to circumvent the face recognition system. Recent research has demonstrated high accuracy... Read More about Unmasking the imposters: task-specific feature learning for face presentation attack detection..