All Outputs (13)

A weighted ensemble of regression methods for gross error identification problem. (2023)
Conference Proceeding
DOBOS, D., DANG, T., NGUYEN, T.T., MCCALL, J., WILSON, A., CORBETT, H. and STOCKTON, P. 2023. A weighted ensemble of regression methods for gross error identification problem. In Proceedings of the 2023 IEEE (Institute of Electrical and Electronics Engineers) Symposium series on computational intelligence (SSCI 2023), 5-8 December 2023, Mexico City, Mexico. Piscataway: IEEE [online], pages 413-420. Available from: https://doi.org/10.1109/SSCI52147.2023.10371882

In this study, we proposed a new ensemble method to predict the magnitude of gross errors (GEs) on measurement data obtained from the hydrocarbon and stream processing industries. Our proposed model consists of an ensemble of regressors (EoR) obtaine... Read More about A weighted ensemble of regression methods for gross error identification problem..

Numerical study on the nucleation law of water vapor condensation in laval nozzle. (2023)
Conference Proceeding
NI, W., SUN, R., LIU, G., MA, F., FAN, C., XIE, C. and KANG, Y. 2023. Numerical study of the nucleation law of water vapor condensation in laval nozzle. In Proceedings of the 3rd International conference on new energy and power engineering 2023 (ICNEPE 2023), 24-26 November 2023, Huzhou, China. Piscataway: IEEE [online], pages 264-268. Available from: https://doi.org/10.1109/ICNEPE60694.2023.10429753

In order to explore the formation of condensed droplets and the process of agglomeration into droplets during the gas-liquid separation in the Laval nozzle, the wet gas is taken as the research object, and the numerical simulation model and control e... Read More about Numerical study on the nucleation law of water vapor condensation in laval nozzle..

Comparison of simulated annealing and evolution strategies for optimising cyclical rosters with uneven demand and flexible trainee placement. (2023)
Conference Proceeding
COLLINS, J., ZĂVOIANU, A.-C. and MCCALL, J.A.W. 2023. Comparison of simulated annealing and evolution strategies for optimising cyclical rosters with uneven demand and flexible trainee placement. In Bramer, M. and Stahl, F. (eds.) Artificial intelligence XL: proceedings of the 43rd SGAI (Specialist Group on Artificial Intelligence) Artificial intelligence international conference 2023 (AI-2023), 12-14 December 2023, Cambridge, UK. Lecture notes in computer science, 14381. Cham: Springer [online], pages 451-464. Available from: https://doi.org/10.1007/978-3-031-47994-6_39

Rosters are often used for real-world staff scheduling requirements. Multiple design factors such as demand variability, shift type placement, annual leave requirements, staff well-being and the placement of trainees need to be considered when constr... Read More about Comparison of simulated annealing and evolution strategies for optimising cyclical rosters with uneven demand and flexible trainee placement..

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..

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..

Vision based relative position estimation in surgical robotics. (2023)
Conference Proceeding
MUTHUKRISHNAN, R., KANNAN, S., PRABHU, R., ZHAO, Y., BHOWMICK, P. and HASAN, M.J. 2023. Vision based relative position estimation in surgical robotics. In Proceedings of the 2023 Network, multimedia and information technology international conference (NMITCON 2023), 1-2 September 2023, Bengaluru, India. Piscataway: IEEE [online], article number 10275973. Available from: https://doi.org/10.1109/NMITCON58196.2023.10275973

Teleoperation-based Robotic-Assisted Minimally In-vasive Surgery (RAMIS) has gained immense popularity in medical field. However, limited physical interaction between the surgeon and patient poses a significant challenge. In RAMIS, the surgeon operat... Read More about Vision based relative position estimation in surgical robotics..

Tracking and estimation of surgical instrument position and angle in surgical robot using vision system. (2023)
Conference Proceeding
MUTHUKRISHNAN, R., KANNAN, S., PRABHU, R., ZHAO, Y., BHOWMICK, P. and HASAN, M.J. 2023. Tracking and estimation of surgical instrument position and angle in surgical robot using vision system. In Proceedings of the 2023 Network, multimedia and information technology international conference (NMITCON 2023), 1-2 September 2023, Bengaluru, India. Piscataway: IEEE [online], article number 10275983. Available from: https://doi.org/10.1109/NMITCON58196.2023.10275983

A da Vinci robot endoscopic-camera gives surgeons a magnified 2D view of the operating area, but additional time is required to detect and estimate the location of the surgical-instrument during an operation. The main focus and novelty of this resear... Read More about Tracking and estimation of surgical instrument position and angle in surgical robot using vision system..

Explaining a staff rostering genetic algorithm using sensitivity analysis and trajectory analysis. (2023)
Conference Proceeding
FYVIE, M., MCCALL, J.A.W., CHRISTIE, L.A. and BROWNLEE, A.E.I. 2023. Explaining a staff rostering genetic algorithm using sensitivity analysis and trajectory analysis. In GECCO’23 companion: proceedings of the 2023 Genetic and evolutionary computation conference companion, 15-19 July 2023, Lisbon, Portugal. New York: ACM [online], pages 1648-1656. Available from: https://doi.org/10.1145/3583133.3596353

In the field of Explainable AI, population-based search metaheuristics are of growing interest as they become more widely used in critical applications. The ability to relate key information regarding algorithm behaviour and drivers of solution quali... Read More about Explaining a staff rostering genetic algorithm using sensitivity analysis and trajectory analysis..

Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models. (2023)
Conference Proceeding
SENANAYAKE, J., KALUTARAGE, H., AL-KADRI, M.O., PIRAS, L. and PETROVSKI, A. 2023. Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models. In De Capitani di Vimercati, S. and Samarati, P. (eds.) Proceedings of the 20th International conference on security and cryptography, 10-12 July 2023, Rome, Italy, volume 1. Setúbal: SciTePress [online], pages 659-666. Available from: https://doi.org/10.5220/0012060400003555

Ensuring the security of Android applications is a vital and intricate aspect requiring careful consideration during development. Unfortunately, many apps are published without sufficient security measures, possibly due to a lack of early vulnerabili... Read More about Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models..

Android code vulnerabilities early detection using AI-powered ACVED plugin. (2023)
Conference Proceeding
SENANAYAKE, J., KALUTARAGE, H., AL-KADRI, M.O., PETROVSKI, A. and PIRAS, L. 2023. Android code vulnerabilities early detection using AI-powered ACVED plugin. In Atluri, V. and Ferrara, A.L. (eds.) Data and applications security and privacy XXXVII; proceedings of the 37th annual IFIP WG (International Federation for Information Processing Working Group) 11.3 Data and applications security and privacy 2023 (DBSec 2023), 19-21 July 2023, Sophia-Antipolis, France. Lecture notes in computer science (LNCS), 13942. Cham: Springer [online], pages 339-357. Available from: https://doi.org/10.1007/978-3-031-37586-6_20

During Android application development, ensuring adequate security is a crucial and intricate aspect. However, many applications are released without adequate security measures due to the lack of vulnerability identification and code verification at... Read More about Android code vulnerabilities early detection using AI-powered ACVED plugin..

Advanced persistent threats detection based on deep learning approach. (2023)
Conference Proceeding
EKE, H.N. and PETROVSKI, A. 2023. Advanced persistent threats detection based on deep learning approach. In Proceedings of the 6th IEEE (Institute of Electrical and Electronics Engineers) International conference on Industrial cyber physical systems international conference 2023 (ICPS 2023), 8-11 May 2023, Wuhan, China. Piscataway: IEEE [online], pages 1-10. Available from: https://doi.org/10.1109/ICPS58381.2023.10128062

Advanced Persistent Threats (APTs) have been a major challenge in securing both Information Technology (IT) and Operational Technology (OT) systems. APT is a sophisticated attack that masquerade their actions to navigates around defenses, breach netw... Read More about Advanced persistent threats detection based on deep learning approach..

Bayesian optimized autoencoder for predictive maintenance of smart packaging machines. (2023)
Conference Proceeding
ARIFEEN, M. and PETROVSKI, A. 2023. Bayesian optimized autoencoder for predictive maintenance of smart packaging machines. In Proceedings of the 6th IEEE (Institute of Electrical and Electronics Engineers) International conference on Industrial cyber-physical systems 2023 (ICPS 2023), 8-11 May 2023, Wuhan, China. Piscataway: IEEE [online], 10128064. Available from: https://doi.org/10.1109/icps58381.2023.10128064

Smart packaging machines incorporate various components (blades, motors, films) to accomplish the packaging process and are involved in almost all types of the manufacturing industry. Proper maintenance and monitoring of the components over time can... Read More about Bayesian optimized autoencoder for predictive maintenance of smart packaging machines..

Ensemble common features technique for lightweight intrusion detection in industrial control system. (2023)
Conference Proceeding
OTOKWALA, U.J. and PETROVSKI, A. 2023. Ensemble common features technique for lightweight intrusion detection in industrial control system. In Proceedings of the 6th IEEE (Institute of Electrical and Electronics Engineers) International conference on Industrial cyber-physical systems 2023 (ICPS 2023), 8-11 May 2023, Wuhan, China. Piscataway: IEEE [online], 10128040. Available from: https://doi.org/10.1109/icps58381.2023.10128040

The integration of the Industrial Control System (ICS) with corporate intranets and the internet has exposed the previously isolated SCADA system to a wide range of cyber-attacks. Interestingly, the vulnerabilities in the Modbus protocol, with which... Read More about Ensemble common features technique for lightweight intrusion detection in industrial control system..