4611. Machine learning
| Title | 4611. Machine learning |
|---|---|
| Parent | 46. Information and Computing Sciences |
Latest research outputs
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Feasibility of Mental Health Triage Call Priority Prediction Using Machine Learning
Rana, Rajib, Higgins, Niall, Haque, Kazi Nazmul, Burke, Kylie, Turner, Kathryn and Stedman, Terry. 2024. "Feasibility of Mental Health Triage Call Priority Prediction Using Machine Learning." Nursing Reports. 14 (4), pp. 4162-4172. https://doi.org/10.3390/nursrep14040303Article
FedStack: Personalized Activity Monitoring using Stacked Federated Learning
Shaik, Thanveer, Tao, Xiaohui, Higgins, Niall, Gururajan, Raj, Li, Yuefeng, Zhou, Xujuan and Acharya, U Rajendra. 2022. "FedStack: Personalized Activity Monitoring using Stacked Federated Learning." Knowledge-Based Systems. 257, pp. 1-14. https://doi.org/10.1016/j.knosys.2022.109929Article
Forecasting standardized precipitation index using data intelligence models: regional investigation of Bangladesh
Yaseen, Zaher Mundher, Ali, Mumtaz, Sharafati, Ahmad, Al-Ansari, Nadhir and Shahid, Shamsuddin. 2021. "Forecasting standardized precipitation index using data intelligence models: regional investigation of Bangladesh." Scientific Reports. 11 (1), pp. 1-25. https://doi.org/10.1038/s41598-021-82977-9Article
Forecasting weekly reference evapotranspiration using Auto Encoder Decoder Bidirectional LSTM model hybridized with a Boruta-CatBoost input optimizer
Karbasi, Masoud, Jamei, Mehdi, Ali, Mumtaz, Malik, Anurag and Yaseen, Zaher Mundher. 2022. "Forecasting weekly reference evapotranspiration using Auto Encoder Decoder Bidirectional LSTM model hybridized with a Boruta-CatBoost input optimizer." Computers and Electronics in Agriculture. 198, pp. 1-17. https://doi.org/10.1016/j.compag.2022.107121Article
FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning
Shaik, Thanveer, Tao, Xiaohui, Li, Lin, Xie, Haoran, Cai, Taotao, Zhu, Xiaofeng and Li, Qing. 2024. "FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning ." IEEE Transactions on Knowledge and Data Engineering. 36 (10), pp. 5153-5167. https://doi.org/10.1109/TKDE.2024.3382726Article
Full series algorithm of automatic building extraction and modelling from LiDAR data
Tarsha Kurdi, Fayez, Gharineiat, Zahra, Campbell, Glenn, Dey, Emon Kumar and Awrangjeb, Mohammad. 2021. "Full series algorithm of automatic building extraction and modelling from LiDAR data." Zhou, Jun, Salvado, Olivier, Sohel, Ferdous, Borges, Paulo and Wang, Shilin (ed.) 2021 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2021). Gold Coast, Australia 29 Nov - 01 Dec 2021 United States.Paper
Fully Quanvolutional Networks for Time Series Classification
Orka, Nabil Anan, Haque, Ehtashamul, Awal, Md Abdul and Moni, Mohammad Ali. 2025. "Fully Quanvolutional Networks for Time Series Classification." 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '25). Toronto, Canada 03 - 07 Aug 2025 United States. Association for Computing Machinery (ACM). https://doi.org/10.1145/3711896.3736972Paper
Future Farm: Improving farmer confidence in targeted N management through automated sensing and decision support
Bramley, Rob, Whelan, Brett, Colaco, André, McCarthy, Alison, Richetti, Jonathan, Lawes, Roger, Fajardo, Mario, Bender, Asher, Pothula, Anand, Baillie, Craig, Perry, Eileen, Fitzgerald, Glenn, Clancy, Alex, Leo, Stephen and Grace, Peter. 2022. Future Farm: Improving farmer confidence in targeted N management through automated sensing and decision support. Australia. Grains Research and Development Corporation.Technical report
Gait velocity estimation using time-interleaved between consecutive passive IR sensor activations
Rana, Rajib, Austin, Daniel, Jacobs, Peter G., Karunanithi, Mohanraj and Kaye, Jeffrey. 2016. "Gait velocity estimation using time-interleaved between consecutive passive IR sensor activations." IEEE Sensors Journal. 16 (16), pp. 6351-6358. https://doi.org/10.1109/JSEN.2016.2577708Article
Graph-Enabled Reinforcement Learning for Time Series Forecasting With Adaptive Intelligence
Shaik, Thanveer, Tao, Xiaohui, Xie, Haoran, Li, Lin, Yong, Jianming and Li, Yuefeng. 2024. "Graph-Enabled Reinforcement Learning for Time Series Forecasting With Adaptive Intelligence." IEEE Transactions on Emerging Topics in Computational Intelligence. 8 (4), pp. 2908-2918. https://doi.org/10.1109/TETCI.2024.3398024Article
Guided Disentangled Representation Learning from Audio data for Transfer Learning
Haque, Kazi Nazmul. 2024. Guided Disentangled Representation Learning from Audio data for Transfer Learning. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/z9y75PhD by Publication
Guiding Ebola patients to suitable health facilities: an SMS-based approach
Trad, Mohamad-Ali, Jurdak, Raja and Rana, Rajib. 2015. "Guiding Ebola patients to suitable health facilities: an SMS-based approach." F1000Research. 4 (43). https://doi.org/10.12688/f1000research.6105.1Article
GWO-XGB: Grey Wolf Optimization-based eXtreme Gradient Boosting for Hypertension Prediction in Bangladesh
Tahsin, Tasfia, Mumenin, Khondoker Mirazul, Pinki, Farhana Tazmim, Tuli, Anamika Biswas, Sikder, Shahriar, Rahman, Md Ashfikur, Bulbul, Abdullah Al-Mamun and Awal, Md Abdul. 2021. "GWO-XGB: Grey Wolf Optimization-based eXtreme Gradient Boosting for Hypertension Prediction in Bangladesh." 2021 International Conference on Electronics, Communications and Information Technology (ICECIT). Khulna, Bangladesh 14 - 16 Sep 2021 Bangladesh. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ICECIT54077.2021.9641256Paper
Half-hourly electricity price prediction with a hybrid convolution neural network-random vector functional link deep learning approach
Ghimire, Sujan, Deo, Ravinesh C., Casillas-Perez, David, Sharma, Ekta, Salcedo-sanz, Sancho, Barua, Prabal and Acharya, U. Rajendra. 2024. "Half-hourly electricity price prediction with a hybrid convolution neural network-random vector functional link deep learning approach." Applied Energy. 374. https://doi.org/10.1016/j.apenergy.2024.123920Article
Harnessing machine learning for EEG signal analysis: Innovations in depth of anaesthesia assessment
Schmierer, Thomas, Li, Tianning and Li, Yan. 2024. "Harnessing machine learning for EEG signal analysis: Innovations in depth of anaesthesia assessment." Artificial Intelligence in Medicine. 151. https://doi.org/10.1016/j.artmed.2024.102869Article
HebCGNN: Hebbian-enabled causal classification integrating dynamic impact valuing
Job, Simi, Tao, Xiaohui, Cai, Taotao, Li, Lin, Xie, Haoran, Xu, Cai and Yong, Jianming. 2025. "HebCGNN: Hebbian-enabled causal classification integrating dynamic impact valuing." Knowledge-Based Systems. 311. https://doi.org/10.1016/j.knosys.2025.113094Article
High-fidelity audio generation and representation learning with guided adversarial autoencoder
Haque, Kazi Nazmul, Rana, Rajib and Schuller, Bjorn W.. 2020. "High-fidelity audio generation and representation learning with guided adversarial autoencoder." IEEE Access. 8, pp. 223509-223528. https://doi.org/10.1109/ACCESS.2020.3040797Article
Hong Kong home economics teachers' preparedness for teaching with technology
Ho, Kitty and Albion, Peter R.. 2010. "Hong Kong home economics teachers' preparedness for teaching with technology." Maddux, Cleborne D., Gibson, David and Dodge, Bernie (ed.) Research highlights in technology and teacher education 2010. Chesapeake, VA, United States. Society for Information Technology & Teacher Education (SITE). pp. 313-321Edited book (chapter)
How pupils use a model for abstract concepts in genetics
Venville, Grady and Donovan, Jenny. 2008. "How pupils use a model for abstract concepts in genetics." Journal of Biological Education. 43 (1), pp. 6-14. https://doi.org/10.1080/00219266.2008.9656143Article
Hybrid CNN–GRU model for hourly flood forecasting index: case studies from the Fiji islands
Chand, Ravinesh, Deo, Ravinesh C., Ghimire, Sujan, Nguyen-Huy, Thong and Ali, Mumtaz. 2025. "Hybrid CNN–GRU model for hourly flood forecasting index: case studies from the Fiji islands." Stochastic Environmental Research and Risk Assessment. 39 (5), pp. 2203-2229. https://doi.org/10.1007/s00477-025-02964-8Article
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions
Tao, Hai, Abba, Sani I., Al-Areeq, Ahmed M., Tangang, Fredolin, Samantaray, Sandeep, Sahoo, Abinash, Siqueira, Hugo Valadares, Maroufpoor, Saman, Demir, Vahdettin, Bokde, Neeraj Dhanraj, Goliatt, Leonardo, Jamei, Mehdi, Ahmadianfar, Iman, Bhagat, Suraj Kumar, Halder, Bijay, Guo, Tianli, Helman, Daniel S., Ali, Mumtaz, Sattar, Sabaa, ..., Yaseen, Zaher Mundher. 2024. "Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research directions ." Engineering Applications of Artificial Intelligence. 129. https://doi.org/10.1016/j.engappai.2023.107559Article
Hyperbolic Mutual Learning for Bundle Recommendation
Ke, Haole, Li, Lin, Wang, PeiPei, Yuan, Jingling and Tao, Xiaohui. 2023. "Hyperbolic Mutual Learning for Bundle Recommendation." 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023). Tianjin, China 17 - 20 Apr 2023 Switzerland . Springer. https://doi.org/10.1007/978-3-031-30672-3_28Paper
Identifying informative tweets during a pandemic via a topic‑aware neural language model
Gao, Wang, Li, Lin, Tao, Xiaohui, Zhou, Jing and Tao, Jun. 2023. "Identifying informative tweets during a pandemic via a topic‑aware neural language model." World Wide Web. 26 (1), pp. 55-70. https://doi.org/10.1007/s11280-022-01034-1Article
IEEE Access special section editorial: health informatics for the developing world
Qadir, Junaid, Mujeeb-U-Rahman, Muhammad, Rehmani, Mubashir Husain, Pathan, Al-Sakib Khan, Imran, Muhammad Ali, Hussain, Amir, Rana, Rajib and Luo, Bin. 2017. "IEEE Access special section editorial: health informatics for the developing world." IEEE Access. 5, pp. 27818-27823. https://doi.org/10.1109/ACCESS.2017.2783118Editorial
Improving Dry-Bulb Air Temperature Prediction Using a Hybrid Model Integrating Genetic Algorithms with a Fourier–Bessel Series Expansion-Based LSTM Model
Alabdally, Hussein, Ali, Mumtaz, Diykh, Mohammad, Deo, Ravinesh C., Aldhafeeri, Anwar Ali, Abdulla, Shahab and Farooque, Aitazaz Ahsan. 2025. "Improving Dry-Bulb Air Temperature Prediction Using a Hybrid Model Integrating Genetic Algorithms with a Fourier–Bessel Series Expansion-Based LSTM Model." Forecasting. 7 (3). https://doi.org/10.3390/forecast7030046Article
Influential Causes that Affect Largely for the Survival of a Patient with Heart-failure: A Machine Learning Perspective
Talin, Iffat Ara, Abid, Mahmudul Hasan, Awal, Md Abdul and Nahid, Abdullah-Al. 2022. "Influential Causes that Affect Largely for the Survival of a Patient with Heart-failure: A Machine Learning Perspective." 2021 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2). Rajshahi, Bangladesh 26 - 27 Dec 2021 Bangladesh. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/IC4ME253898.2021.9768462Paper
Innovative Multi-Temporal Evapotranspiration Forecasting Using Empirical Fourier Decomposition and Bidirectional Long Short-Term Memory
Karbasi, Masoud, Ali, Mumtaz, Randhawa, Gurjit S., Jamei, Mehdi, Malik, Anurag, Hussain, Syed Hamid Hussain, Bos, Melanie, Zaman, Qamar and Farooque, Aitazaz Ahsan. 2024. "Innovative Multi-Temporal Evapotranspiration Forecasting Using Empirical Fourier Decomposition and Bidirectional Long Short-Term Memory." Smart Agricultural Technology . 9. https://doi.org/10.1016/j.atech.2024.100619Article
Interpretation in design: modelling how the situation changes during design activity
Kelly, Nick and Gero, John S.. 2014. "Interpretation in design: modelling how the situation changes during design activity." Research in Engineering Design. 25 (2), pp. 109-124. https://doi.org/10.1007/s00163-013-0168-yArticle
Introductory Engineering Mathematics Students’ Weighted Score Predictions Utilising a Novel Multivariate Adaptive Regression Spline Model
Ahmed, Abul Abrar Masrur, Deo, Ravinesh C., Ghimire, Sujan, Downs, Nathan J., Devi, Aruna, Barua, Prabal D. and Yaseen, Zaher M.. 2022. "Introductory Engineering Mathematics Students’ Weighted Score Predictions Utilising a Novel Multivariate Adaptive Regression Spline Model." Sustainability. 14 (17), pp. 1-27. https://doi.org/10.3390/su141711070Article
Investigating the Emotional Response to COVID-19 News on Twitter: A Topic Modeling and Emotion Classification Approach
Oliveira, Francisco Braulio, Haque, Amanul, Mougouei, Davoud, Evans, Simon, Sichman, Jaime Simao and Singh, Munindar P.. 2022. "Investigating the Emotional Response to COVID-19 News on Twitter: A Topic Modeling and Emotion Classification Approach." IEEE Access. 10, pp. 16883-16897. https://doi.org/10.1109/ACCESS.2022.3150329Article
Kryptein: A Compressive-Sensing-Based Encryption Scheme for the Internet of Things
Xue, Wanli, Luo, Chengwen, Lan, Guohao, Rana, Rajib, Hu, Wen and Seneviratne, Aruna. 2017. "Kryptein: A Compressive-Sensing-Based Encryption Scheme for the Internet of Things." Zhang, Pei, Dutta, Prabal and Xing, Guoliang (ed.) 16th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2017). Pittsburgh, Pennsylvania, USA 18 - 21 Apr 2017 United States. https://doi.org/10.1145/3055031.3055079Paper
Layered Model Stacking: Enhancing DDoS Detection Through Advanced Ensemble Machine Learning Techniques
Haddad, Nabeel Mahdy, Sahi, Aqeel, Diykh, Mohammed, Aljbur, Kaled, Kutfan, Ali, Abdulla, Shahab and Al-Hraishawi, Hayder. 2025. "Layered Model Stacking: Enhancing DDoS Detection Through Advanced Ensemble Machine Learning Techniques ." Chen, F. (ed.) 2024 IEEE Region 10 Conference (TENCON 2024). Singapore 01 - 04 Dec 2024 IEEE. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/TENCON61640.2024.10902823Paper
Leveraging Advanced Data-Driven Approaches to Forecast Daily Floods Based on Rainfall for Proactive Prevention Strategies in Saudi Arabia
Aldhafiri, Anwar Ali, Ali, Mumtaz and Labban, Abdulhaleem H.. 2025. "Leveraging Advanced Data-Driven Approaches to Forecast Daily Floods Based on Rainfall for Proactive Prevention Strategies in Saudi Arabia." Water. 17 (11). https://doi.org/10.3390/w17111699Article
Lightweight federated learning for STIs/HIV prediction
Nguyen, Thi Phuoc Van, Yang, Wencheng, Tang, Zhaohui, Xia, Xiaoyu, Mullens, Amy B., Dean, Judith A. and Li, Yan. 2024. "Lightweight federated learning for STIs/HIV prediction." Scientific Reports. 14 (1). https://doi.org/10.1038/s41598-024-56115-0Article
Machinability of Polymeric Composites and Future Reinforcements — A Review
Shalwan, Abdullah, Alsaeed, Talal and Yousif, Belal. 2022. "Machinability of Polymeric Composites and Future Reinforcements — A Review." Journal of Materials Science and Chemical Engineering. 10 (5), pp. 40-72. https://doi.org/10.4236/msce.2022.105004Article
Machine Learning Algorithms for High-Resolution Prediction of Spatiotemporal Distribution of Air Pollution from Meteorological and Soil Parameters
Tao, Hai, Jawad, Ali H., Shather, A.H., Al-Khafaji, Zainab Al, Rashid, Tarik A., Ali, Mumtaz, Al-Ansari, Nadhir Al, Marhoon, Haydar Abdulameer, Shahid, Shamsuddin and Yaseen, Zaher Mundher. 2023. "Machine Learning Algorithms for High-Resolution Prediction of Spatiotemporal Distribution of Air Pollution from Meteorological and Soil Parameters." Environment International. 175. https://doi.org/10.1016/j.envint.2023.107931Article
Machine learning approaches for predicting hypertension and its associated factors using population-level data from three South Asian countries
Islam, Sheikh Mohammed Shariful, Talukder, Ashis, Awal, Md Abdul, Siddiqui, Md Muhammad Umer, Ahamad, Md Martuza, Ahammed, Benojir, Rawal, Lal B, Alizadehsani, Roohallah, Abawajy, Jemal, Laranjo, Liliana, Chow, Clara K. and Maddison, Ralph. 2022. "Machine learning approaches for predicting hypertension and its associated factors using population-level data from three South Asian countries." Frontiers in Cardiovascular Medicine. 9. https://doi.org/10.3389/fcvm.2022.839379Article
Machine learning models for classification and identification of significant attributes to detect type 2 diabetes
Howlader, Koushik Chandra, Satu, Md Shahriare, Awal, Md Abdul, Islam, Md Rabiul, Islam, Sheikh Mohammed Shariful, Quinn, Julian MW and Moni, Mohammad Ali. 2022. "Machine learning models for classification and identification of significant attributes to detect type 2 diabetes." Health Information Science and Systems. 10 (1). https://doi.org/10.1007/s13755-021-00168-2Article
Machine learning-based assessment of deforestation, successional stages, and carbon stocks in a tropical montane forest using radar and optical satellite imagery
Altarez, Richard Dein D.. 2024. Machine learning-based assessment of deforestation, successional stages, and carbon stocks in a tropical montane forest using radar and optical satellite imagery. PhD by Publication Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/z78z2PhD by Publication
Making generalisations in geometry: students' views on the process: a case study
Yevdokimov, Oleksiy. 2008. "Making generalisations in geometry: students' views on the process: a case study." Figueras, Olimpia, Cortina, Jose Luis, Alatorre, Silvia, Rojano, Teresa and Sepulveda, Armando (ed.) 2008 Annual Conference for the Psychology of Mathematics Education (PME 32): Mathematical Ideas: History, Education and Cognition. Morelia, Mexico 17 - 21 Jul 2008 Morelia, Mexico.Paper