Dr. Xiaohui Tao, PhD
Professor (Computer Science)
Computing Discipline Team Leader
School of Mathematics, Physics, and Computing
University of Southern Queensland, Australia
Tel: +61 7 4631 1576
Email: xiaohui DOT tao AT unisq DOT edu DOT au
http://www.tao-xiaohui.info
https://staffprofile.usq.edu.au/Profile/Xiaohui-Tao

Professor Dr. Xiaohui Tao holds a distinguished position at the University of Southern Queensland's (UniSQ) School of Mathematics, Physics, and Computing in Australia. He is the Computing Discipline Team Leader, and presides as the Chair of the ICT Programs’ Governance and Leadership Committee at UniSQ. Before assuming these pivotal roles, from 2016 to 2021, he provided esteemed leadership as the Director of various academic programs, including the Master of Data Science, Master of Information Technology, and Master of Science at UniSQ.

An esteemed scholar in Artificial Intelligence, Dr. Tao's research encompasses a wide spectrum, including but not limited to data analytics, machine learning, knowledge engineering, natural language processing, and health informatics. His academic contributions are well-recognized with over 200 publications in eminent journals such as TKDE, TOIS, TIST, INFFUS, IPM, and notable conferences including AAAI, IJCAI, SIGIR, EMNLP, ICDE, and CIKM. Beyond individual research, he spearheads a prominent research group that prioritizes innovative algorithms and systems with significant real-world applications. Additionally, he has exhibited exceptional mentorship, having successfully supervised ten doctoral candidates to completion.

Dr. Tao's contributions to the academic community have been acknowledged with prestigious awards like the Australia Research Council Grant and the Australian Endeavour Research Fellowship, as well as recognition from international conferences, namely DSinS'23, ACMHN’22, BESC’22, BI’21, WI-IAT’20, and WISE'20 and '19.

A Senior Member of both the IEEE and ACM professional bodies, Dr. Tao also contributes as the Deputy Chair of the IEEE Technical Committee on Intelligent Informatics (TCII). His editorial endeavours include serving as the Editor-in-Chief for Elsevier's Natural Language Processing Journal, the TCII Bulletin, and Web Intelligence (CCF C). He has further enhanced his profile by serving in key roles in conferences such as WI-IAT and BESC, and more.

Dr. Tao concluded his PhD in Information Technology from the Queensland University of Technology, Australia, in 2009.

NEWS RESEARCH PUBLICATIONS GRANTS INVITED TALKS TEACHING LEADERSHIP AND SERVICES

Selected Publications
Full list: Google Scholar Scopus DBLP Semantic Scholar ResearchGate

2024

Refereed Journal articles
  1. Jiaxing Yan, Hai Liu, Zhiqi Lei, Yanghui Rao, Guan Liu, Haoran Xie, Xiaohui Tao, and Fu Lee Wang. Two-Dimensional Data Partitioning for Non-negative Matrix Tri-Factorization. Big Data Research, 2024. doi: https://doi.org/10.1016/j.bdr.2024.100473 [Q1]
  2. Thanveer Shaik, Xiaohui Tao, Haoran Xie, Lin Li, Jianming Yong, and Yuefeng Li. Graph-enabled Reinforcement Learning for Time Series Forecasting with Adaptive Intelligence. IEEE Transactions on Emerging Topics in Computational Intelligence, 2024. doi: https://doi.org/10.1109/TETCI.2024.3398024 [Q1]
  3. Kaixi Hu, Lin Li, Xiaohui Tao, and Jianwei Zhang. Semantics and Geography Aware Hierarchical Learning for Sequential Crime Prediction. IEEE Signal Processing Letters, Volume 31, pages 1234–1238, 2024. doi: https://doi.org/10.1109/LSP.2024.3393863 [Q1]
  4. Xieling Chen, Haoran Xie, Xiaohui Tao, Lingling Xu, Jingjing Wang, Hong-Ning Dai, and Fu Lee Wang. A Topic Modelling-based Bibliometric Exploration of Automatic Summarization Research. WIREs Data Mining and Knowledge Discovery, 2024 (in press). https://doi.org/10.1002/widm.1540 [Q1]
  5. Hongzhi Kuai, Ning Zhong, and Xiaohui Tao. Never-Ending Learning for Explainable Brain Computing. Advanced Science, 2024. (in press) https://doi.org/10.1002/advs.202307647 [Q1, IF 15.1]
  6. Thanveer Shaik, Xiaohui Tao, Lin Li, Haoran Xie, Taotao Cai, Xiaofeng Zhu, and Qing Li. FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning. in IEEE Transactions on Knowledge and Data Engineering [CCF A, CORE A*, Q1] https://doi.org/10.1109/TKDE.2024.3382726.
  7. Ming Li, Lin Li, Xiaohui Tao, Zhongwei Xie, Qing Xie, and Jingjing Yuan. Boosting Healthiness Exposure in Category-constrained Meal Recommendation Using Nutritional Standards. ACM Transactions on Intelligent Systems and Technology (TIST), 2024. [Q1] https://doi.org/10.1145/3643859
  8. Xieling Chen, Haoran Xie, and Xiaohui Tao. Artificial Intelligence and Multimodal Data Fusion for Smart Healthcare: Topic Modeling and Bibliometrics. Artificial Intelligence Review, Volume 57, Article number 91, 2024. [Q1] https://doi.org/10.1145/3643859
  9. Simi Job, Xiaohui Tao, Lin Li, Haoran Xie, Taotao Cai, Jianming Yong, and Qin Li. Optimal Treatment Strategies for Critical Patients with Deep Reinforcement Learning. ACM Transactions on Intelligent Systems and Technology (TIST), Volume 15, Issue 2, Article No. 36, pp 1-22, 2024 (in press). https://doi.org/10.1145/3643856, [Q1]
  10. Kaixi Hu, Lin Li, Jianquan Liu, Xiaohui Tao, and Guandong Xu. Decoupled Progressive Distillation for Sequential Prediction with Interaction Dynamics. ACM Transactions on Information Systems (TOIS), Volume 42, Issue 3, Article No. 72, pages 1-35, 2024 https://doi.org/10.1145/3632403 [CCF A, Q1]
  11. Lingling Xu, Haoran Xie, Fu Lee Wang, Xiaohui Tao, Weiming Wang, and Qing Li. Contrastive Sentence Representation Learning with Adaptive False Negative Cancellation. Information Fusion, 102, 102065, 2024. https://doi.org/10.1016/j.in us.2023.102065, [Q1, IF 18.6]
Refereed Conference papers

2023

Refereed Journal articles
  1. Lingling Xu, Haoran Xie, Fu Lee Wang, Xiaohui Tao, Weiming Wang, and Qing Li. Contrastive Sentence Represen- tation Learning with Adaptive False Negative Cancellation. Information Fusion, 2023 (in press) [Q1, IF 18.6] https://doi.org/0.1016/j.inffus.2023.1020653.
  2. Thanveer Shaik, Xiaohui Tao, Lin Li, Haoran Xie, Juan D. Vel ́asquez. A Survey of Multimodal Information Fusion for Smart Healthcare: Mapping the Journey from Data to Wisdom. Information Fusion, 2023, 102040 [Q1, IF 18.6] https://doi.org/10.1016/j.inffus.2023.102040
  3. Matthew Squires, Xiaohui Tao, Soman Elangovan, Raj Gururajan, Xujuan Zhou, Yuefeng Li, and Rajendra U Acharya. Identifying Predictive Biomarkers for Repetitive Transcranial Magnetic Stimulation Response in Depression Patients With Explainability. Computer Methods and Programs in Biomedicine, Volume 242, December 2023, 107771. [Q1] https://doi.org/10.1016/j.cmpb.2023.107771
  4. Kaixi Hu, Lin Li, Xiaohui Tao, Juan D. Vel ́asquez, and Patrick Delaney. Information Fusion in Crime Event Analysis: A Decade Survey on Data, Features and Models. Information Fusion, Volume 100, December 2023, 101904. [Q1, IF 18.6] https://doi.org/10.1016/j.inffus.2023.101904
  5. Lin Li, Peipei Wang, Xinhao Zheng, Qing Xie, Xiaohui Tao, and Juan D. Vel ́asquez. Dual-interactive Fusion for Code-mixed Deep Representation Learning in Tag Recommendation. Information Fusion, Volume 99, November 2023, 101862. [Q1, IF 18.6] https://doi.org/10.1016/j.inffus.2023.101862
  6. Joshua Sheehy, Hamish Rutledge, U Rajendra Acharya, Hui Wen Loh, Raj Gururajan, Xiaohui Tao, Xujuan Zhou, Yuefeng Li, Tiana Gurney, Srinivas Kondalsamy-Chennakesavan, Gynecological cancer prognosis using machine learning techniques: A systematic review of last three decades (1990–2022), Artificial Intelligence in Medicine, 102536, Volume 139, May 2023 [Q1] https://doi.org/10.1016/j.artmed.2023.102536
  7. Matthew Squires, Xiaohui Tao, Soman, Raj Gururajan, Xujuan Zhou, Rajendra U Acharya, and Yuefeng Li, Deep Learning and Machine Learning in Psychiatry: A Survey of Current Progress in Depression Detection, Diagnosis and Treatment, Brain Informatics, 10, 10 (2023). https://doi.org/10.1186/s40708-023-00188-6
  8. Simi Job, Xiaohui Tao, Yuefeng Li, Lin Li, and Jianming Yong. Topic Integrated Opinion-based Drug Recommendation with Transformers. IEEE Transactions on Emerging Topics in Computational Intelligence, 2023 (in press) https://doi.org/10.1109/TETCI.2023.3246559
  9. Thanveer Shaik, Xiaohui Tao, Niall Higgins, Lin Li, Raj Gururajan, and Xujuan Zhou. Remote Patient Monitoring using Artificial Intelligence: Current State, Applications, and Challenges. WIREs Data Mining and Knowledge Discovery, 2023 (in press). [Q1] https://doi.org/10.1002/widm.1485
  10. Zongxi Li, Xianming Li, Haoran Xie, Fu Lee Wang, Mingming Leng, Qing Li, and Xiaohui Tao. A novel dropout mechanism with label extension schema toward text emotion classification. Information Processing and Management, Volume 60, Issue 2, March 2023, 103173. https://doi.org/10.1016/j.ipm.2022.103173 [Q1]
  11. Lin Li, Turghun Tayir, Yifeng Han, Xiaohui Tao, and Juan D. Velasquez. Multimodality Information Fusion for Automated Machine Translation. Information Fusion, Volume 91, March 2023, Pages 352–363. [Q1, IF 17.564] https://doi.org/10.1016/j.inffus.2022.10.018
Refereed Conference papers
  1. Dan Liu, Lin Li, Xiaohui Tao, Jian Cui, and Qing Xie. Descriptive Prompt Paraphrasing for Target-Oriented Multimodal Sentiment Classification. Accepted by the Findings of EMNLP track, the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP'23), 6-10 Dec 2023. https://doi.org/10.18653/v1/2023.findings-emnlp.275
  2. Ming Li, Lin Li, Xiaohui Tao, Qing Xie, Jingling Yuan. CateRec: Category-wise Meal Recommendation. In Proceedings of the 30th International Conference on Neural Information Processing (ICONIP'23), Changsha, China, November 20-23, 2023.
  3. Haole Ke, Lin Li, PeiPei Wang, Jingling Yuan, and Xiaohui Tao. Tree-like Interaction Learning for Bundle Recommendation, in Proceedings of the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'23), 4-10 June, Rhodes Island, Greece. https://doi.org/10.1109/ICASSP49357.2023.10096246
  4. Shugui Xie, Lin Li, Jingling Yuan, Qing Xie and Xiaohui Tao, Long Legal Article Question Answering via Cascaded Key Segment Learning, poster presentation in the 37th AAAI Conference on Artificial Intelligence (AAAI'23), Washington DC, USA, 7–14 Feb 2023. https://doi.org/10.1609/aaai.v37i13.27042

2022

Refereed Journal articles
  1. Thanveer Shaik, Xiaohui Tao, Niall Huggins, Raj Gururajan, Yuefeng Li, Xujuan Zhou and U R. Acharya. FedStack: Personalized Activity Monitoring using Stacked Federated Learning. Knowledge-Based Systems, Volume 257, 5 December 2022, 10992. [Q1] https://doi.org/10.1016/j.knosys.2022.109929
  2. Ru Wang, Lin Li, Xiaohui Tao, Peipei Wang, and Peiyu Liu. Contrastive and attentive graph learning for multi-view clustering. Information Processing and Management, Volume 59, Issue 4, July 2022, 102967. [Q1][https://doi.org/10.1016/j.ipm.2022.102967]
  3. Matthew Squires, Xiaohui Tao, Soman Elangovan, Raj Gururajan, Xujuan Zhou, and U Rajendra Acharya. A Novel Genetic Algorithm Based System for the Scheduling of Medical Treatments, Expert Systems with Applications, Volume 195, 1 June 2022, 116464. [Q1][https://doi.org/10.1016/j.eswa.2021.116464]
  4. Thuan Pham, Xiaohui Tao, Ji Zhang, Jianming Yong, Yuefeng Li, and Haoran Xie. Graph-based Multi-label Disease Prediction Model Learning from Medical Data and Domain Knowledge. Knowledge-Based Systems, Volume 235, 10 January 2022, 107662. [Q1] [https://doi.org/10.1016/j.knosys.2021.107662]
  5. Wang Gao, Lin Li, Xiaohui Tao, Jing Zhou, Jun Tao. Identifying informative tweets during a pandemic via a topic-aware neural language model. World Wide Web, 1–16, 16 Mar 2022. [https://doi.org/10.1007/s11280-022-01034-1]
  6. Hongzhi Kuai, Xiaohui Tao, and Ning Zhong. Web Intelligence meets Brain Informatics: towards the Future of Artificial Intelligence in the Connected World, World Wide Web, Springer, 2022. [https://doi.org/10.1007/s11280-022-01030-5]
Refereed Conference papers
  1. Xiaohua Wu, Lin Li, and Xiaohui Tao, Towards the Quantitative Interpretability Analysis of Citizens Happiness Prediction. In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI-ECAI'22), July 23-29, 2022, Messe Wien, Vienna, Austria, Pages 5094-5100. https://doi.org/10.24963/ijcai.2022/707
  2. Raid Lafta, Hisham Alshaheen, Biao Wang, Xiaohui Tao, Lingling Li, Kexin Zhang, and Ji Zhang. Fast Fourier Transform and Ensemble Model to Classify Epileptic EEG Signals. Accepted by 2022 IEEE International Conference on Big Data (IEEE BigData'22).

2021

Refereed Journal articles
  1. Thomas Body, Xiaohui Tao, Yuefeng Li, Lin Li, and Ning Zhong, Using Back-and-Forth Translation to Create Artificial Augmented Textual Data for Sentiment Analysis Models. Expert Systems With Applications, Volume 178, 15 September 2021, 115033 [Q1] [https://doi.org/10.1016/j.eswa.2021.115033]
  2. Ru Wang, Lin Li, Xiaohui Tao, Xiao Dong, Peipei Wang and Peiyu Liu. Trio-based collaborative multi-view graph clustering with multiple constraints, Information Processing and Management, Elsevier, Volume 58, Issue 3, May 2021, 102466, 2021 [Q1, SNIP 3.199] [https://doi.org/10.1016/j.ipm.2020.102466]
  3. Sujan Ghimire, Zaher Mundher Yaseen, Aitazaz A. Farooque, Ravinesh C. Deo, Ji Zhang, Xiaohui Tao. Stream ow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks. Scientific Reports, volume 11, Article number: 17497 (2021). [Q1] [https://doi.org/10.1038/s41598-021-96751-4]
  4. Xieling Chen, Xiaohui Tao, Fu Lee Wang and Haoran Xie, Global research on artificial intelligence-enhanced human electroencephalogram analysis, Neural Computing and Applications, Springer, 2021 [Q1] [https://doi.org/10.1007/s00521-020-05588-x]
  5. Faisal Nabi, Xiaohui Tao, Jianming Yong, Security Aspects in Modern Service Component Oriented Application Logic for Social Media Systems, Social Network Analysis and Mining, Springer, 11, 22, 2021 [Q1] [https://doi.org/10.1007/s13278-020-00717-9]
  6. Xiaohui Tao, Oliver Chi, Patrick J. Delaney, Lin Li and Jiajin Huang. Detecting Depression using an Ensemble Classifier Based on Quality of Life Scales. Brain Informatics, Springer, 8, 2, 2021. [Q1, SNIP: 2.333] [https://doi.org/10.1186/s40708-021-00125-5]
Refereed Conference papers
  1. Kaixi Hu, Lin Li, Qing Xie, Jianquan Liu and Xiaohui Tao, What is Next when Sequential Prediction Meets Implicitly Hard Interaction? In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM'21) 2021, 1-5 November 2021, Online and Gold Coast, Queensland, Australia [https://doi.org/10.1145/3459637.3482492]
  2. Wang Gao, Yuan Fang, Lin Li, and Xiaohui Tao. Event Detection in Social Media via Graph Neural Network. In: Zhang W., Zou L., Maamar Z., Chen L. (eds) Web Information Systems Engineering, WISE 2021. (WISE'21). Lecture Notes in Computer Science, vol 13080. Springer, Cham. https://doi.org/10.1007/978-3-030-90888-1_28

2020

Refereed Journal articles
  1. Raid Luaibi Lafta, Ji Zhang and Xiaohui Tao, A General Extensible Learning Approach for Multi-Disease Recommendations in a Telehealth Environment, Pattern Recognition Letters, Elsevier, Volume 132, page 106-114, April 2020 [Q1] [https://doi.org/10.1016/j.patrec.2018.11.006]
  2. Xieling Chen, Xinxin Zhang, Haoran Xie, Xiaohui Tao, Fu Lee Wang, Nengfu Xie and Tianyong Hao, A bibliometric and visual analysis of artificial intelligence technologies-enhanced brain MRI research, Multimedia Tools and Applications, 11 June 2020 [Q1] [https://doi.org/10.1007/s11042-020-09062-7]
  3. Ji Zhang, Leonard Tan, Xiaohui Tao, Thuan Pham and Bing Chan, Rational Intelligence Recognition in Online Social Networks - A Survey, Computer Science Review, volume 35, Feb 2020 [Q1] [https://doi.org/10.1016/j.cosrev.2019.100221]
  4. Moloud Abdar, Mariam Zomorodi-Moghadam, Xujuan Zhou, Raj Gururajan, Xiaohui Tao, Prabal D Barua and Rashmi Gururajan, A new nested ensemble technique for automated diagnosis of breast cancer, Pattern Recognition Letters, Elsevier, Volume 132, page 123-131, April 2020 [Q1] [https://doi.org/10.1016/j.patrec.2018.11.004]
  5. Da Ren, Pengfei Zhang, Qing Li, Xiaohui Tao, Junying Chen and Yi Cai, A Hybrid Representation Based Similar Component Extraction, Neural Computing and Applications, 2020. [Q1] [https://doi.org/10.1007/s00521-020-04818-6]
  6. Christopher Kok, V Jahmunah, Shu Lih Oh , Xujuan Zhou, Raj Gururajan, Xiaohui Tao, Kang Hao Cheong, Rashmi Gururajan, and U Rajendra Acharya, Automated Prediction of Sepsis Using Temporal Convolutional Network, Computers in Biology and Medicine, Volume 127, December 2020, 103957, 2020 [Q1] [https://doi.org/10.1016/j.compbiomed.2020.103957]
Refereed Conference papers
  1. Peiran Nai, Lin Li and Xiaohui Tao, A Densely Connected Encoder Stack Approach for Multi-type Legal Machine Reading Comprehension, accepted by International Conference on Web Information Systems Engineering (WISE'20), 2020. [Best Student Paper Award]
  2. Ru Wang, Lin Li, Peipei Wang, Xiaohui Tao, Peiyu Liu, Feature-aware unsupervised learning with joint variational attention and automatic clustering, accepted by the 25th International Conference on Pattern Recognition (ICPR'20), 2020.

2019 backward

Refereed Journal articles
  1. Wee Phong Goh, Xiaohui Tao, Ji Zhang, and Jianming Yong. Decision Support Systems for Adoption in Dental Clinics: A Survey. Knowledge-Based Systems, Elsevier, 104, 195-206 (2016). [Q1; SNIP: 2.757; SJR: 2.190; IF: 2.947; 5-yr IF: 3.011] [https://doi.org/10.1016/j.knosys.2016.04.022]
  2. Xiaohui Tao, Yuefeng Li, and Ning Zhong. A Personalised Ontology Model for Web Information Gathering. IEEE Transactions on Knowledge and Data Engineering, 23(4):496-511 (2011). [Q1, SNIP: 4.341] [https://doi.org/10.1109/TKDE.2010.145]
  3. Xiaohui Tao, Yuefeng Li, and Richi Nayak. A Knowledge Retrieval Model Using Ontology Mining and User Profiling, Integrated Computer-Aided Engineering, 15(4), pp313-329, (2008). [Q1, Impact Factor: 3.37, SNIP: 1.471][https://doi.org/10.3233/ICA-2008-15404 ]
Refereed Conference papers
  1. Ji Zhang, Leonard Tan, Xiaohui Tao, Dianwei Wang, Josh Jia-Ching Ying and Xin Wang, Learning Relational Fractals For Deep Knowledge Graph Embedding In Online Social Networks, Web Information Systems Engineering (WISE'19) 2019, Springer International Publishing, pp. 660-674, 2019 [Best Runner-up Paper Award]
  2. Wee Pheng Goh, Xiaohui Tao, Ji Zhang, and Jianming Yong, Personalised Drug Prescription for Dental Clinics Using Word Embedding, In: U L., Yang J., Cai Y., Karlapalem K., Liu A., Huang X. (eds) Web Information Systems Engineering. WISE'19. Communications in Computer and Information Science, vol 1155. Springer, Singapore https://doi.org/10.1007/978-981-15-3281-8_5
  3. Ji Zhang, Leonard Tan, Xiaohui Tao, Hongzhou Li, Fulong ChenYonglong Luo, SLIND+: Stable LINk Detection, In: U L., Yang J., Cai Y., Karlapalem K., Liu A., Huang X. (eds) Web Information Systems Engineering. WISE'19. Communications in Computer and Information Science, vol 1155. Springer, Singapore https://doi.org/10.1007/978-981-15-3281-8_8
  4. Ji Zhang, Leonard Tan, Xiaohui Tao, Jerry Chun-Wei Lin, Hongzhou Li and Liang Chang. On Link stability Detection for Online Social Networks. In Proceedings of 28th International Conference on Database and Expert Systems Applications (DEXA'18), pp 320-335. September 3-6, 2018, Germany.
  5. Raid Lafta, Ji Zhan, Xiaohui Tao, Jerry Chun-Wei Lin, Fulong Chen, Yonglong Luo and Xiaoyao Zheng. A Recommender System with Advanced Time Series Medical Data Analysis for Diabetes Patients in a Telehealth Environment. In Proceedings of 28th International Conference on Database and Expert Systems Applications (DEXA'18), pp 185-192, September 3-6, 2018, Germany.
  6. Ji Zhang, Leonard Tan, Xiaohui Tao, Xiaoyao Zheng, Yonglong Luo, and Jerry Chun-Wei Lin. SLIND: Identifying Stable Links in Online Social Networks. The 23rd International Conference on Database Systems for Advanced Applications (DASFFA'18), pp 813-816, May 21-24, 2018, Gold Coast, Australia.
  7. Wee Pheng Goh, Xiaohui Tao, Ji Zhang, and Jianming Yong. Mining Drug Properties for Decision Support in Dental Clinics. In Proceedings of the 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'17), pp. 375-387, 2017, Jeju, South Korea.
  8. Raid Lafta, Ji Zhang, Xiaohui Tao, Yan Li, Wessam Abbas, Yonglong Luo, Fulong Chen and Vincent S. Tseng. A fast Fourier transform-coupled machine learning-based ensemble model for disease risk prediction using a real-life dataset. In Proceedings of the 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'17), pp 654-670, 2017.
  9. Ji Zhang, HuaWang, Xiaohui Tao, and Lili Sun. SODIT: An Innovative System for Outlier Detection using Multiple Localised Thresholding and Interactive Feedback. In Proceedings of the 29th IEEE International Conference on Data Engineering (ICDE 2013), Brisbane, Australia, 8-12, April, 2013, pp. 1364-1367. [ERA A, Acceptance Rate: 19%]