Jonathan Liono
RMIT University
21 Papers
46 Citations
Jonathan Liono is an academic researcher from RMIT University. The author has contributed to research in topics: Computer science & Mobile computing. The author has an hindex of 9, co-authored 20 publications. Previous affiliations of Jonathan Liono include Monash University.
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Papers
Learning About Work Tasks to Inform Intelligent Assistant Design
Johanne R. Trippas,Damiano Spina,Falk Scholer,Ahmed Hassan Awadallah,Peter Bailey,Paul N. Bennett,Ryen W. White,Jonathan Liono,Yongli Ren,Flora D. Salim,Mark Sanderson +10 more
- 08 Mar 2019
TL;DR: A classification of work-related tasks is presented, and their key characteristics are analyzed, including the frequency of their self-reported tasks, the environment in which they undertake the tasks, and which, if any, electronic devices are used.
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QDaS: Quality driven data summarisation for effective storage management in Internet of Things
TL;DR: The proposed QDaS framework incorporates a novel data summarisation mechanism that uses an innovative data quality estimation technique that computes the quality of data without requiring any feedback from users of this IoT data or domain awareness of the data.
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Predicting the city foot traffic with pedestrian sensor data
Xianjing Wang,Jonathan Liono,William Alex McIntosh,Flora D. Salim +3 more
- 07 Nov 2017
TL;DR: The empirical evaluation of this experiment shows that the proposed ARIMA model is effective in modelling both weekdays and weekend patterns, outperforming other state-of-art models for short-term prediction of pedestrian counts.
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OccuSpace: Towards a Robust Occupancy Prediction System for Activity Based Workplace
Mohammad Saiedur Rahaman,Harsh Pare,Jonathan Liono,Flora D. Salim,Yongli Ren,Jeffrey Chan,Shaw Kudo,Tim Rawling,Alex Sinickas +8 more
- 11 Mar 2019
TL;DR: This research provides a robust system called OccuSpace to predict occupancy of different atomic zones in large ABW environments by using statistical features engineered from Received Signal Strength Indicator of Bluetooth card beacons carried by workers while they are within the ABW environment.
19
Interactive self-adaptive clutter-aware visualisation for mobile data mining
Mohamed Medhat Gaber,Shonali Krishnaswamy,Brett James Gillick,Hasnain Altaiar,Nicholas Nicoloudis,Jonathan Liono,Arkady Zaslavsky +6 more
- 01 May 2013
TL;DR: A generic theory for visualisation on small screens that is based on Adaptive Clutter Reduction ACR is proposed and a novel data stream clustering result visualisation technique that is developed and experimentally validated called Clutter-Aware Clustering Visualiser CACV and its enhancement of enabling user interactivity that is named iCACV are presented.
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