Research Publications

Published and Accepted Journal Papers

  1. Almeida A, Dutta R, Franz T, Terhorst A, Smethurst P, Baillie C, and Worledge D, Combining Cosmic-Ray Neutron and Capacitance Sensors and Fuzzy Inference to Spatially Quantify Soil Moisture Distribution. IEEE Sensors Journal. 2014 14(10), 3465-3472.
  2. D'Este C, and Rahman A, Similarity weighted ensembles for relocating models of rare events. Multiple Classifier Systems: Springer; 2013. p. 25-36;
  3. D'Este C, Rahman A, and Turnbull A, Predicting shellfish farm closures with class balancing methods. AI 2012: Advances in Artificial Intelligence: Springer; 2012. p.39-48;
  4. D'Este C, Timms G, Turnbull A, and Rahman A, Ensemble aggregation methods for relocating models of rare events. Engineering Applications of Artificial Intelligence. June 2014; 34:58-65;
  5. Dutta R, Smith D, Rawnsley R, Bishop-Hurley G, Hills J, Timms G, and Henry D, Dynamic cattle behavioural classification using supervised ensemble classifiers. Computers and Electronics in Agriculture. December 2014; 18-28;
  6. Dutta R, and Terhorst A, Adaptive Neuro-Fuzzy Inference System-Based Remote Bulk Soil Moisture Estimation: Using CosmOz Cosmic Ray Sensor. Sensors Journal, IEEE. 2013;13(6):2374-81;
  7. Rahman A, Benthic Habitat Mapping from Seabed Images using Ensemble of Color, Texture, and Edge Features. International Journal of Computational Intelligence Systems. 2013; 6(6):1072-81;
  8. Rahman A, D'Este C, and Timms G, Dealing with Missing Sensor Values in Predicting Shellfish Farm Closure. 2013 Ieee Eighth International Conference on Intelligent Sensors,Sensor Networks and Information Processing. 2013:351-6;
  9. Rahman A, D'Este C, and Turnbull A, Shellfish Farm Closure Cause Identification and Prediction using Class Balancing Ensembles. Computers and Electronics in Agriculture 110:241-248, 2014.
  10. Rahman A, McCulloch J, and Mamun Q, Prediction With Uncertainty: A Novel Framework for Analyzing Sensor Data Streams. Sensors Journal, IEEE. 2015;15(1):382-6;
  11. Rahman A, and Shahriar MS, Algae Growth Prediction Through Identification Of Influential Environmental Variables: A Machine Learning Approach. International Journal of Computational Intelligence and Applications. 2013;12(02):1350008;
  12. Rahman A, Shahriar MS, D'Este C, Smith G, McCulloch J, and Timms G, Time-series prediction of shellfish farm closure: A comparison of alternatives. Information Processing in Agriculture. 2014;1(1):42-50;
  13. Rahman A, Smith D, and Timms G, A Novel Machine Learning Approach Toward Quality Assessment of Sensor Data. Sensors Journal, IEEE. 2014;14(4):1035-47;
  14. Rahman A, Zhang Q, and D'Este C, "An Ensemble Classifier Approach for Predicting with Missing Sensor Values," First revision with World Scientific Advances in Adaptive Data Analysis. (revision);
  15. Rahman A, Zhang Q, and D'Este C, A Multiple Classifier System for Predicting with Missing Sensor Values. Advances in Adaptive Data Analysis 6: Article 1450009, 2014.
  16. Shahriar MS, and McCulloch J, A Dynamic Data-driven Decision Support for Aquaculture Farm Closure. Procedia Computer Science. 2014;29:1236-45;
  17. Shahriar MS and McCulloch J, Predictive Analytics in Decision Support for Shellfish Farms, submitted in Ecological Informatics (Elsevier), 2014;
  18. Shahriar MS, Rahman A, and McCulloch J, Predicting shellfish farm closures using time series classification for aquaculture decision support. Computers and Electronics in Agriculture. 2014;102:85-97;
  19. Smith D, Dutta R, Hellicar A Bishop-Hurley G, Rawnsley R, Henry D, Hills J, and Timms G, Bag of Class Posteriors, a new multivariate time series classifier applied to animal behaviour identification. Expert Systems with Applications. Vol 42, Iss 7, May 2015, pp 3774–3784;

Published and Accepted Conference Papers

  1. Almeida R, Dutta A, Terhorst C, Baillie D, Worledge D, and Smethurst P, "Quantifying spatial distribution of soil moisture using a cosmic ray and capacitance sensor network", 12th IEEE Sensors Conference, Baltimore, USA, 3-6 November 2013;
  2. Alter K, Morash A, Frappell P, Andrewartha S, and Elliott N, "Physiological responses to environmental stress in abalone: Why is being a hybrid an advantage?" 'Comparative approaches to grand challenges in physiology' Conference, San Diego, CA, USA, 5-8 October 2014. American Physiological Society.
  3. Andrewartha S, Morash A, Elliott N, McCulloch J, and Frappell P,  "Biosensing to assist aquaculture productivity and sustainability". World Aquaculture Adelaide 2014 Conference, Adelaide, 7-11/6/14.
  4. Bishop-Hurley G, Henry D, Smith DV, Dutta R, Hellicar A, Rawnsley R, Hills J, Morshed A, Rahman A, Timms G, D'Este C, and Shu Y, "An investigation of cow feeding behavior using motion sensors", IEEE International Instrumentation and Measurement Conference, Montevideo, Uruguay, 12-15 May 2014;
  5. Cabral L, Compton K, and Mueller H, "A use case in semantic modelling and ranking for the sensor web". In 'Proceedings of the 13th International Semantic Web Conference (ISWC 14)', Italy, Oct 2014. LNCS 8796, Springer;
  6. Cabral L, Mueller H, and Morshed A (organisers), "Hands-on Guide to Linked Data Applications" tutorial in conjunction with the International Semantic Web Conference (ISWC 13);
  7. D' Este C, and Rahman A, "Similarity Weighted Ensembles for Relocating Models of Rare Events", Proc. International Workshop on Multiple Classifier Systems (MCS), Lecture Notes in Computer Science, pp. 25–36, Nanjing, China, May 15-17, 2013;
  8. D' Este C, Rahman A, and Turnbull A, "Predicting Shellfish Farm Closures with Class Balancing Methods," AAI 2012: Advances in Artificial Intelligence, Lecture Notes in Computer Science, pp. 39–48, 2012;
  9. Dutta R, Smith D, and Timms G, "Dynamic Annotation and Visualisation of the South Esk Hydrological Sensor Web", Presented at IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing 2013, Melbourne, Australia.
  10. Dutta R, Terhorst A, Hawdon A, and Cotching B, "Bulk Soil Moisture Estimation Using CosmOz Cosmic Ray Sensor and ANFIS", IEEE Sensors Proceedings, 978-1-4577-1767-3/12, pp 741 -744, Taipei, Taiwan, October 28-31, 2012;
  11. Evans K, and Cabral L, "The role of participatory research in the design of fit-for-purpose decision support". In 'Proceedings of the Symposium of the New Zealand Plant Protection Society', Taupo, Aug, 2014;
  12. Evans K, and Terhorst A, "Making sense of the vineyard environment", Proceedings of the 15th Australian Wine Industry Technical Conference 2013, Sydney NSW, 13-18 July 2013;
  13. Harvey R, Castray A, Timms G, Rawnsley R, and Smethurst P, "An economy-wide sensor network: how Sense-T is building the knowledge infrastructure for the future", presented at presentation at Digital Rural Futures Conference, Armidale, NSW, June 2013;
  14. Hellicar A, Rahman A, Smith D, Smith G, and McCulloch J, "A neural network and SOM based approach to analyse periodic signal: application to Oyster heart-rate data". 'Neural Networks (IJCNN)', IEEE International Joint Conference, Beijing, China, 6-11 July 2014;
  15. Morshed A, Dutta R, and Timms G, "Semantic Machine Learning and Linked Open Data Application (SML2OD2013) for Agricultural and Environmental Informatics", Workshop at International Semantic Web Conference, Sydney, 22 October 2013;
  16. Morshed A, Dutta R, and Aryal J, "Recommending Environmental Knowledge As Linked Open Data Cloud Using Semantic Machine Learning", Presented at 29th IEEE International Conference on Data Engineering 2013;
  17. Mueller H, Cabral, L, Morshed A, and Shu Y, "From RESTful to SPARQL: A Case Study on Generating Semantic Sensor Data". In: 6th International workshop on Semantic Sensor Networks in conjunction with ISWC 2013;
  18. Rahman A, D'Este C, Timms G, and Turnbull A, "Dealing with missing sensor values in predicting shellfish farm closure", 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Melbourne, Australia, 2-5 April 2013 (Acceptance rate: approx. 35%, Google Scholar Citations: 3);
  19. Rahman A, Smith D, and Timms G, "Multiple classifier system for automated quality assessment of marine sensor data", 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Melbourne, Australia, 2-5 April 2013 (Acceptance rate: approx. 35%, Google Scholar Citations: 2);
  20. Rahman A, D'Este C, and McCulloch J, "Ensemble Feature Ranking for Shellfish Farm Closure Cause Identification," Proc. Workshop on Machine Learning for Sensory Data Analysis in conjunction with Australian AI conference, DOI, 2013;
  21. Rahman A, D' Este C, and Timms G, "Dealing with Missing Sensor Values in Predicting Shellfish Farm Closure," Proceedings IEEE Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), pp. 351–356, Melbourne, 2013;
  22. Rahman A, Smith D, and Timms G, "Multiple Classifier System for Automated Quality Assessment of Marine Sensor Data," Proceedings IEEE Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), pp. 362–367, Melbourne, 2013;
  23. Rawnsley R, Hills J, Freeman M, Henry D, Bishop-Hurley G, and Timms G, "Monitoring grazing behaviour of dairy cows in pasture based systems", presented at Dairy Research Foundation (DRF) Symposium, Kiama, NSW, 4-5 July 2013;
  24. 'Sense-T viticulture project' at the SenseT/SensMA workshop hosted by the CSIRO Division of Computational Informatics, Battery Point, 27 March, 2013;
  25. 'Sense-T viticulture project' for a seminar series hosted by the Tasmanian Institute of Agriculture, Sandy Bay, 22 November, 2013;
  26. 'Sense-T: enhancing decision making' at the 'New Frontiers in Horticultural R&D' meeting hosted by Horticulture Australia Limited (HAL), Sydney, 20 August, 2013;
  27. Shahriar MS and Rahman A, "Spatio–temporal Prediction of Algal Bloom," Proc. IEEE International Conference on Natural Computation (ICNC), pp. 968–972, China, 2013;
  28. Shahriar MS and McCulloch J, "A Dynamic Data-driven Decision Support for Aquaculture Farm Closure", 14th International Conference on Computational Science (ICCS), Elsevier Procedia Computer Science Series, 10-12 June 2014, Cairns, Australia;
  29. Timms G, "Sense-T: Transforming the Tasmanian economy through federated sensing", 1st CSIRO Computational Informatics Conference, Gold Coast, 20 – 22 Nov 2013;
  30. Timms G, "Transforming the Tasmanian economy through federated sensing", presented at TTI/Vanguard Atoms' Matter Conference, Vienna, Austria, 9-10 July 2013;
  31. Timms G, Castray A, Dutta R, Rawnsley R, and Henry D, "Opportunities created for agricultural and environmental informatics through whole-of-economy federated sensing", presented at the International Semantic Web Conference (ISWC 2013), Sydney, October 2013;
  32. Zhang Q, Rahman A, and D'Este C, "Impute vs. Ignore: Missing Values for Prediction," Proc. IEEE International Joint Conference on Neural Networks (IJCNN), pp. 2193–2200, Dallas, Texas, 2013;

Workshops

  1. Edeson G, Morrison B, and Timms G, "Participatory research in rural digital projects", Workshop proposal submitted to Digital Rural Futures Conference, Toowoomba, Qld, June 2014.
  2. Timms G, "Sense-T: An economy-wide sensor network", invited tutorial at 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Melbourne, Australia, 2-5 April 2013