46. Information and Computing Sciences
| Title | 46. Information and Computing Sciences |
|---|---|
| Parent | ANZSRC Field of Research |
Latest research outputs
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Introducing Technology for Learning in Prisons: Meeting Challenges and Realising Opportunities
Farley, Helen and Ware, Jason. 2023. "Introducing Technology for Learning in Prisons: Meeting Challenges and Realising Opportunities." Advancing Corrections: Journal of the International Corrections and Prisons Association. (16), pp. 24-35.Article
Bathymetric modelling for long-term monitoring of water dynamics of Ramsar-listed lakes using inundation frequency and photon-counting LiDAR data
Zhang, Zhenyu and Liu, Xiaoye. 2023. "Bathymetric modelling for long-term monitoring of water dynamics of Ramsar-listed lakes using inundation frequency and photon-counting LiDAR data." Ecohydrology and Hydrobiology. https://doi.org/10.1016/j.ecohyd.2023.10.003Article
An Adaptive Feature Fusion Network for Alzheimer’s Disease Prediction
Wei, Shicheng, Li, Yan and Yang, Wencheng. 2023. "An Adaptive Feature Fusion Network for Alzheimer’s Disease Prediction." 12th International Conference on Health Information Science (HIS 2023). Melbourne, Australia 23 - 24 Oct 2023 Germany. https://doi.org/10.1007/978-981-99-7108-4Paper
Assessing Organizational Readiness for Data-driven Innovation: A Review of Literature
Samarasinghe, Sasari Sanika Udanjala, Lokuge, Sachithra and Duan, Sophia. 2023. "Assessing Organizational Readiness for Data-driven Innovation: A Review of Literature." 28th Pacific Asia Conference on Information Systems (PACIS 2023). Nanchang, China 08 - 12 Jul 2023 China.Paper
Developing a Framework for Restrained Innovation: IT-Outsourcing Context
Lokuge, Sachithra and Sedera, Darshana. 2023. "Developing a Framework for Restrained Innovation: IT-Outsourcing Context." 28th Pacific Asia Conference on Information Systems (PACIS 2023). Nanchang, China 08 - 12 Jul 2023 China.Paper
An Introduction to Programming Physics-Informed Neural Network-Based Computational Solid Mechanics
Bai, Jinshuai, Jeong, Hyogu, Batuwatta-Gamage, C. P., Xiao, Shusheng, Wang, Qingxia, Rathnayaka, C.M., Alzubaidi, Laith, Liu, Gui-Rong and Gu, Yuantong. 2023. "An Introduction to Programming Physics-Informed Neural Network-Based Computational Solid Mechanics." International Journal of Computational Methods. 20 (10). https://doi.org/10.1142/S0219876223500135Article
Enhancing climate resilience by combining practice and insurance strategies: A case study for cotton crop
Nguyen-Huy, Thong and Battersby, Kerry. 2023. "Enhancing climate resilience by combining practice and insurance strategies: A case study for cotton crop." Queensland Disaster Management Research Forum 2023. Brisbane, Australia 07 - 07 Nov 2023Presentation
HGSOXGB: Hunger-Games-Search-Optimization-Based Framework to Predict the Need for ICU Admission for COVID-19 Patients Using eXtreme Gradient Boosting
Pinki, Farhana Tazmim, Awal, Md Abdul, Mumenin, Khondoker Mirazu, Hossain, Md. Shahadat, Faysal, Jabed Al, Rana, Rajib, Almuqren, Rajib, Ksibi, Amel and Samad, Md Abdus. 2023. "HGSOXGB: Hunger-Games-Search-Optimization-Based Framework to Predict the Need for ICU Admission for COVID-19 Patients Using eXtreme Gradient Boosting." Mathematics. 11 (18). https://doi.org/10.3390/math11183960Article
Information fusion in crime event analysis: A decade survey on data, features and models
Hu, Kaixi, Li, Lin, Tao, Xiaohui, Velasquez, Juan D. and Delaney, Patrick. 2023. "Information fusion in crime event analysis: A decade survey on data, features and models." Information Fusion. 100. https://doi.org/10.1016/j.inffus.2023.101904Article
Using ARDC Nectar VMs, Jupyter Hub and GitHub to Deploy Agricultural Modelling Applications on the AgReFed Platform
Gacenga, Francis and An-Vo, Duc-Anh. 2023. "Using ARDC Nectar VMs, Jupyter Hub and GitHub to Deploy Agricultural Modelling Applications on the AgReFed Platform." eResearch Australasia 2023 Conference. Brisbane, Australia 16 - 20 Oct 2023 Australia.Presentation
Making an Agricultural Research Dataset FAIR: A case study of the Australian Drought Monitor Dataset
Gacenga, Francis, An-Vo, Duc-Anh, Cobon, David, Young, Richard and McCulloch, Jillian. 2023. "Making an Agricultural Research Dataset FAIR: A case study of the Australian Drought Monitor Dataset." eResearch Australasia 2023 Conference. Brisbane, Australia 16 - 20 Oct 2023 Australia.Presentation
An ensemble machine learning-based intelligent system for human activity recognition using sensory data
Abdulla, Shahab, Diykh, Mohammed, Siuly, Siuly and Ali, Mumtaz. 2023. "An ensemble machine learning-based intelligent system for human activity recognition using sensory data." Sinha, G.R., Subudhi, Bidyadhar, Fan, Chih-Peng and Nisar, Humaira (ed.) Cognitive Sensing Technologies and Applications. Institution of Engineering and Technology (IET). pp. 119-130Edited book (chapter)
L2QA: Long Legal Article Question Answering with Cascaded Key Segment Learning
Xie, Shugui, Li, Lin, Yuan, Jingling, Xie, Qing and Tao, Xiaohui. 2023. "L2QA: Long Legal Article Question Answering with Cascaded Key Segment Learning." 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023). Tianjin, China 17 - 20 Apr 2023 Springer. https://doi.org/10.1007/978-3-031-30675-4_27Paper
Hierarchical Aggregation Based Knowledge Graph Embedding for Multi-task Recommendation
Wang, Yani, Zhang, Ji, Zhou, Xiangmin and Zhang, Yang. 2023. "Hierarchical Aggregation Based Knowledge Graph Embedding for Multi-task Recommendation." 6th International Joint Conference on Asia-Pacific Web and Web-Age Information Management (APWeb-WAIM 2022). Nanjing, China 25 - 27 Nov 2022 Switzerland . https://doi.org/10.1007/978-3-031-25201-3_13Paper
Query2Trip: Dual-Debiased Learning for Neural Trip Recommendation
Wang, Peipei, Li, Lin, Wang, Ru and Tao, Xizohui. 2023. "Query2Trip: Dual-Debiased Learning for Neural Trip Recommendation." 28th International Conference on Database Systems for Advanced Applications (DASFAA 2023). Tianjin, China 17 - 20 Apr 2023 Switzerland . Springer. pp. 80-96 https://doi.org/10.1007/978-3-031-30672-3_6Paper
A Power Efficient Solution to Determine Red Blood Cell Deformation Type Using Binarized DenseNet
Reza, Md Tanzim, Dipto, Shakib Mahmud, Parvez, Mohammad Zavid, Barua, Prabal Datta and Chakraborty, Subrata. 2023. "A Power Efficient Solution to Determine Red Blood Cell Deformation Type Using Binarized DenseNet." 2023 International Conference on Advances in Computing Research (ACR’23). Orlando, United States 08 - 10 May 2023 Switzerland. https://doi.org/10.1007/978-3-031-33743-7_21Paper
CNN-Based Handwriting Analysis for the Prediction of Autism Spectrum Disorder
Nawer, Nafisa, Parvez, Mohammad Zavid, Hossain, Muhammad Iqbal, Barua, Prabal Datta, Rahim, Mia and Chakraborty, Subrata. 2023. "CNN-Based Handwriting Analysis for the Prediction of Autism Spectrum Disorder." Second International Conference on Innovations in Computing Research (ICR’23). Madrid, Spain 04 - 06 Sep 2023 Switzerland . https://doi.org/10.1007/978-3-031-35308-6_14Paper
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
An Efficient Embedding Framework for Uncertain Attribute Graph
Jiang, Ting, Yu, Ting, Qiao, Xueting and Zhang, Ji. 2023. "An Efficient Embedding Framework for Uncertain Attribute Graph." 34th International Conference on Database and Expert Systems Applications (DEXA 2023). Penang, Malaysia 28 - 30 Aug 2023 Switzerland . https://doi.org/10.1007/978-3-031-39821-6_18Paper
Using Electroencephalography to Determine Student Attention in the Classroom
V, Indumathi and Kist, Alexander A. 2023. "Using Electroencephalography to Determine Student Attention in the Classroom." 2023 IEEE Global Engineering Education Conference (EDUCON). Kuwait, Kuwait 01 - 04 May 2023 Kuwait. https://doi.org/10.1109/EDUCON54358.2023.10125158Paper
An XAI Integrated Identification System of White Blood Cell Type Using Variants of Vision Transformer
Dipto, Shakib Mahmud, Reza, Md Tanzim, Rahman, Md Nowroz Junaed, Parvez, Mohammad Zavid, Barua, Prabal Datta and Chakraborty, Subrata. 2023. "An XAI Integrated Identification System of White Blood Cell Type Using Variants of Vision Transformer." Second International Conference on Innovations in Computing Research (ICR’23). Madrid, Spain 04 - 06 Sep 2023 Spain. https://doi.org/10.1007/978-3-031-35308-6_26Paper
Be-or-Not Prompt Enhanced Hard Negatives Generating For Memes Category Detection
Cui, Jian, Li, Lin and Tao, Xiaohui. 2023. "Be-or-Not Prompt Enhanced Hard Negatives Generating For Memes Category Detection." 2023 IEEE International Conference on Multimedia and Expo (ICME). Brisbane, Australia 10 - 14 Jul 2023 United Sates. https://doi.org/10.1109/ICME55011.2023.00038Paper
Brain Injury Localization and Size Estimation Using Electromagnetic Symmetric Crossing Lines Method
Zhu, Guohun, Bialkowski, Alina, Crozier, Stuart, Guo, Lei, Nguyen, Phong Thanh, Stancombe, Anthony E. and Abbosh, Amin. 2023. "Brain Injury Localization and Size Estimation Using Electromagnetic Symmetric Crossing Lines Method." IEEE Transactions on Instrumentation and Measurement. 72. https://doi.org/10.1109/TIM.2023.3295014Article
GraphTune: An Efficient Dependency-Aware Substrate to Alleviate Irregularity in Concurrent Graph Processing
Zhao, Jin, Zhang, Yu, He, Ligang, Li, Qikun, Zhang, Xiang, Jiang, Xinyu, Yu, Hui, Liao, Xiaofei, Jin, Hai, Gu, Lin, Liu, Haikun, He, Bingsheng, Zhang, Ji, Song, Xianzheng, Wang, Lin and Zhou, Jun. 2023. "GraphTune: An Efficient Dependency-Aware Substrate to Alleviate Irregularity in Concurrent Graph Processing." ACM Transactions on Architecture and Code Optimization. 20 (3), pp. 1-24. https://doi.org/10.1145/3600091Article
EGraph: Efficient Concurrent GPU-Based Dynamic Graph Processing
Zhang, Yu, Liang, Yuxuan, Zhao, Jin, Mao, Fubing, Gu, Lin, Liao, Xiaofei, Jin, Hai, Liu, Haikun, Guo, Song, Zeng, Yangqing, Hu, Hang, Li, Chen, Zhang, Ji and Wang, Biao. 2023. "EGraph: Efficient Concurrent GPU-Based Dynamic Graph Processing." IEEE Transactions on Knowledge and Data Engineering. 35 (6), pp. 5823-5836. https://doi.org/10.1109/TKDE.2022.3171588Article
DeepSafety: a deep neural network-based edge computing framework for detecting unsafe behaviors of construction workers
Zhang, Ji, Liu, Chia-Chun and Ying, Josh Jia-Ching. 2023. "DeepSafety: a deep neural network-based edge computing framework for detecting unsafe behaviors of construction workers." Journal of Ambient Intelligence and Humanized Computing. 14 (12), pp. 15997-16009. https://doi.org/10.1007/s12652-023-04554-4Article
An efficient hardware accelerator for monotonic graph algorithms on dynamic directed graphs
Yang, Yun, Yu, Hui, Zhao, Jin, Zhang, Yu, Liao, Xiaofei, Jiang, Xinyu, Jin, Hai, Liu, Haikun, Mao, Fubing, Zhang, Ji and Wang, Biao. 2023. "An efficient hardware accelerator for monotonic graph algorithms on dynamic directed graphs." Scientia Sinica Informationis. 53 (8), pp. 1575-1592. https://doi.org/10.1360/SSI-2022-0191Article
A Review of Homomorphic Encryption for Privacy-Preserving Biometrics
Yang, Wencheng, Wang, Song, Cui, Hui, Tang, Zhaohui and Li, Yan. 2023. "A Review of Homomorphic Encryption for Privacy-Preserving Biometrics." Sensors. 23 (7). https://doi.org/10.3390/s23073566Article
FDS_2D: rethinking magnitude-phase features for DeepFake detection
Yang, Gaoming, Wei, Anxing, Fang, Xianjin and Zhang, Ji. 2023. "FDS_2D: rethinking magnitude-phase features for DeepFake detection." Multimedia Systems. 29 (4), pp. 2399-2413. https://doi.org/10.1007/s00530-023-01118-6Article
Facial depth forgery detection based on image gradient
Xu, Kun, Yang, Gaoming, Fang, Xianjin and Zhang, Ji. 2023. "Facial depth forgery detection based on image gradient." Multimedia Tools and Applications. 82 (19), pp. 29501-29525. https://doi.org/10.1007/s11042-023-14626-4Article
Using multi-focus group method as an effective tool for eliciting business system requirements: Verified by a case study
Wu, Robert M. X., Wang, Yongwen, Shafiabady, Niusha, Zhang, Huan, Yan, Wanjun, Gou, Jinwen, Shi, Yong, Liu, Bao, Gide, Ergun, Kang, Changlong, Zhang, Zhongwu, Shen, Bo, Li, Xiaoquan, Fan, Jianfeng, He, Xiangqian, Soar, Jeffrey, Zhao, Haijun, Sun, Lei, Huo, Wenying and Wang, Ya. 2023. "Using multi-focus group method as an effective tool for eliciting business system requirements: Verified by a case study." PLoS ONE. 18 (3). https://doi.org/10.1371/journal.pone.0281603Article
Irregularly Sampled Multivariate Time Series Classification: A Graph Learning Approach
Wang, Zhen, Jiang, Ting, Xu, Zenghui, Zhang, Ji and Gao, Jianliang. 2023. "Irregularly Sampled Multivariate Time Series Classification: A Graph Learning Approach." IEEE Intelligent Systems. 38 (3), pp. 3-11. https://doi.org/10.1109/MIS.2023.3239797Article
Blockchain-Enhanced Smart Contract for Cost-Effective Insurance Claims Processing
Wang, Qiping, Lau, Raymond Yiu Keung, Si, Yain-Whar, Xie, Haoran and Tao, Xiaohui. 2023. "Blockchain-Enhanced Smart Contract for Cost-Effective Insurance Claims Processing." Journal of Global Information Management. 31 (7). https://doi.org/10.4018/JGIM.329927Article
Hybrid KD-NFT: A multi-layered NFT assisted robust Knowledge Distillation framework for Internet of Things
Wang, Nai, Chen, Junjun, Wu, Di, Yang, Wencheng, Xiang, Yong and Sajjanhar, Atul. 2023. "Hybrid KD-NFT: A multi-layered NFT assisted robust Knowledge Distillation framework for Internet of Things." Journal of Information Security and Applications. 75. https://doi.org/10.1016/j.jisa.2023.103483Article
SAGES: Scalable Attributed Graph Embedding With Sampling for Unsupervised Learning
Wang, Jialin, Qu, Xiaoru, Bai, Jinze, Li, Zhao, Zhang, Ji and Gao, Jun. 2023. "SAGES: Scalable Attributed Graph Embedding With Sampling for Unsupervised Learning." IEEE Transactions on Knowledge and Data Engineering. 35 (5), pp. 5216-5229. https://doi.org/10.1109/TKDE.2022.3148272Article
Mining Periodic-Frequent Patterns in Irregular Dense Temporal Databases Using Set compliments
Veena, Pamalla, Sreepada, Tarun, Kiran, Rage Uday, Dao, Minh-Son, Zettsu, Koli, Watanobe, Yutaka and Zhang, Ji. 2023. "Mining Periodic-Frequent Patterns in Irregular Dense Temporal Databases Using Set compliments." IEEE Access. 11, pp. 118676-118688. https://doi.org/10.1109/ACCESS.2023.3326419Article
Contribution of Geometric Feature Analysis for Deep Learning Classification Algorithms of Urban LiDAR Data
Tarsha Kurdi, Fayez, Amakhchan, Wijdan, Gharineiat, Zahra, Boulaassal, Hakim and Kharki, Omar El. 2023. "Contribution of Geometric Feature Analysis for Deep Learning Classification Algorithms of Urban LiDAR Data." Sensors. 23 (17). https://doi.org/10.3390/s23177360Article
Towards an understanding of the engagement and emotional behaviour of MOOC students using sentiment and semantic features
Tao, Xiaohui, Shannon-Honson, Aaron, Delaney, Patrick, Dann, Christopher, Xie, Haoran, Li, Yan and O'Neill, Shirley. 2023. "Towards an understanding of the engagement and emotional behaviour of MOOC students using sentiment and semantic features." Computers and Education: Artificial Intelligence. 4. https://doi.org/10.1016/j.caeai.2022.100116Article
A review of multi-factor authentication in the Internet of Healthcare Things
Suleski, Tance, Ahmed, Mohiuddin, Yang, Wencheng and Wang, Eugene. 2023. "A review of multi-factor authentication in the Internet of Healthcare Things." Digital Health. 9, pp. 1-20. https://doi.org/10.1177/20552076231177144Article
Exploring deep residual network based features for automatic schizophrenia detection from EEG
Siuly, Siuly, Guo, Yanhui, Alcin, Omer Faruk, Li, Yan, Wen, Peng and Wang, Hua. 2023. "Exploring deep residual network based features for automatic schizophrenia detection from EEG." Physical and Engineering Sciences in Medicine. 46 (2), pp. 561-574. https://doi.org/10.1007/s13246-023-01225-8Article