ORCID Profile
0000-0002-1237-1664
Current Organisation
University of New South Wales
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Communication Technology and Digital Media Studies | Structural engineering | Architectural Science and Technology (incl. Acoustics, Lighting, Structure and Ecologically Sustainable Design) | Communication and Media Studies | Social and Cultural Anthropology | Information Systems | Law and Society | Distributed Computing | Information Systems Development Methodologies | Ubiquitous Computing | Neural, Evolutionary and Fuzzy Computation | Sociology and Social Studies of Science and Technology | Computer-Human Interaction | Civil engineering | Architecture | Aerospace Engineering not elsewhere classified | Infrastructure engineering and asset management | Interorganisational Information Systems and Web Services
ANZSRC Socio-Economic Objective (SEO)
Multimodal Transport | The Media | Expanding Knowledge in Built Environment and Design | Expanding Knowledge in Technology | Environmentally Sustainable Information and Communication Services not elsewhere classified | Information Processing Services (incl. Data Entry and Capture) | Evaluation of Health Outcomes | Expanding Knowledge in the Information and Computing Sciences | Structure, Delivery and Financing of Community Services |
Related Links
Publications
A Location-Query-Browse Graph for Contextual Recommendation
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2018
Modeling occupant behavior in buildings
Publisher: Elsevier BV
Date: 05-2020
Large-amplitude Bidirectional Anisotropy of Cosmic-Ray Intensity Observed with Worldwide Networks of Ground-based Neutron Monitors and Muon Detectors in 2021 November
Publisher: American Astronomical Society
Date: 10-2022
Abstract: We analyze the cosmic-ray variations during a significant Forbush decrease observed with worldwide networks of ground-based neutron monitors and muon detectors during 2021 November 3–5. Utilizing the difference between primary cosmic-ray rigidities monitored by neutron monitors and muon detectors, we deduce the rigidity spectra of the cosmic-ray density (or omnidirectional intensity) and the first- and second-order anisotropies separately for each hour of data. A clear two-step decrease is seen in the cosmic-ray density with the first ∼2% decrease after the interplanetary shock arrival followed by the second ∼5% decrease inside the magnetic flux rope (MFR) at 15 GV. Most strikingly, a large bidirectional streaming along the magnetic field is observed in the MFR with a peak litude of ∼5% at 15 GV, which is comparable to the total density decrease inside the MFR. The bidirectional streaming could be explained by adiabatic deceleration and/or focusing in the expanding MFR, which have stronger effects for pitch angles near 90°, or by selective entry of GCRs along a leg of the MFR. The peak anisotropy and density depression in the flux rope both decrease with increasing rigidity. The spectra vary dynamically, indicating that the temporal variations of density and anisotropy appear different in neutron monitor and muon detector data.
Federated Self-Supervised Learning of Multisensor Representations for Embedded Intelligence
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-01-2021
SECC: Simultaneous extraction of context and community from pervasive signals
Publisher: IEEE
Date: 03-2016
Location Contact Tracing: Penetration, Privacy, Position, and Performance
Publisher: Association for Computing Machinery (ACM)
Date: 31-07-2022
DOI: 10.1145/3532669
Abstract: The 2020 COVID-19 pandemic radically changed the world and how people interact, move, and behave. Following a lockdown that was imposed worldwide, although with different timing, Mobile Contact Tracing Apps (MCTAs) were proposed to digitally trace contacts between in iduals while gradually releasing mobility constraints mandated to contain the spread of disease. General concern for privacy regarding the use of GPS data shifted the efforts toward distributed applications, which use Bluetooth technology to trace proximity and potential infections. Nonetheless, GPS data would help more health operators to understand where hotbeds are and to what extent the spread is progressing and at what pace. In addition to these issues, in this work we take a closer look at the major pillars of MCTA: Penetration, Privacy, Position, and Performance. We focus on (i) how the penetration rate affects the ability of a tracing application to work (ii) the proposal of a novel method of tracing, which builds on the GPS technology (iii) how the position of infections is beneficial to rapidly reduce the infection and (iv) the discussion of the effects of such paradigms in different scenarios.
Crime event prediction with dynamic features
Publisher: Springer Science and Business Media LLC
Date: 19-10-2018
QDaS: Quality driven data summarisation for effective storage management in Internet of Things
Publisher: Elsevier BV
Date: 05-2019
A Peculiar ICME Event in August 2018 Observed With the Global Muon Detector Network
Publisher: American Geophysical Union (AGU)
Date: 22-02-2021
DOI: 10.1029/2020SW002531
Abstract: We demonstrate that global observations of high‐energy cosmic rays contribute to understanding unique characteristics of a large‐scale magnetic flux rope causing a magnetic storm in August 2018. Following a weak interplanetary shock on August 25, 2018, a magnetic flux rope caused an unexpectedly large geomagnetic storm. It is likely that this event became geoeffective because the flux rope was accompanied by a corotating interaction region and compressed by high‐speed solar wind following the flux rope. In fact, a Forbush decrease was observed in cosmic‐ray data inside the flux rope as expected, and a significant cosmic‐ray density increase exceeding the unmodulated level before the shock was also observed near the trailing edge of the flux rope. The cosmic‐ray density increase can be interpreted in terms of the adiabatic heating of cosmic rays near the trailing edge of the flux rope, as the corotating interaction region prevents free expansion of the flux rope and results in the compression near the trailing edge. A northeast‐directed spatial gradient in the cosmic‐ray density was also derived during the cosmic‐ray density increase, suggesting that the center of the heating near the trailing edge is located northeast of Earth. This is one of the best ex les demonstrating that the observation of high‐energy cosmic rays provides us with information that can only be derived from the cosmic ray measurements to observationally constrain the three‐dimensional macroscopic picture of the interaction between coronal mass ejections and the ambient solar wind, which is essential for prediction of large magnetic storms.
The mucinous domain of pancreatic carboxyl-ester lipase (CEL) contains core 1/core 2 O-glycans that can be modified by ABO blood group determinants
Publisher: Elsevier BV
Date: 12-2018
Shopping intent recognition and location prediction from cyber-physical activities via wi-fi logs
Publisher: ACM
Date: 07-11-2018
SD-HOC: Seasonal Decomposition Algorithm for Mining Lagged Time Series
Publisher: Springer Singapore
Date: 2018
A Simultaneous Extraction of Context and Community from pervasive signals using nested Dirichlet process
Publisher: Elsevier BV
Date: 07-2017
Analyzing Web behavior in indoor retail spaces
Publisher: Wiley
Date: 28-07-2015
DOI: 10.1002/ASI.23587
Heuristic evolution with genetic programming for traveling thief problem
Publisher: IEEE
Date: 05-2015
Using Big Spatial Data for Planning User Mobility
Publisher: Springer International Publishing
Date: 2018
Visualization Oriented Spatiotemporal Urban Data Management and Retrieval
Publisher: ACM
Date: 22-10-2015
Collaborative Design and Live Interaction with Parametric Models Using UbiMash
Publisher: SAGE Publications
Date: 09-2010
DOI: 10.1260/1478-0771.8.3.377
Abstract: Due to the complexity of parametric modeling, it has been the task of only a handful of experts in the design team to develop, build and modify parametric models. The complexity of parametric models increases exponentially with the number of design aspects it incorporates. The ambiguity of parametric models towards the modeled design intent explains that modifying the model is often isolated as an in idual exercise. Developments in physical and ubiquitous computing, however, allow for collaboration and interaction with parametric models in other ways. Communication, coordination, and interaction between parametric models and the physical and social environment are the context of this paper. The paper describes some of the projects that were outcomes of the SmartGeometry 2010 workshops. These projects are dealing with mass collaboration using Twitter, tangible interfaces, parametric design and construction coordination and geometrical interpretation of datasets.
Designing Architectural Morphing Skins with Elastic Modular Systems
Publisher: SAGE Publications
Date: 12-2011
DOI: 10.1260/1478-0771.9.4.397
Abstract: This paper discusses the issues of designing architectural skins that can be physically morphed to adapt to changing needs. To achieve this architectural vision, designers have focused on developing mechanical joints, components, and systems for actuation and kinetic transformation. However, the unexplored approach of using lightweight elastic form-changing materials provides an opportunity for designing responsive architectural skins and skeletons with fewer mechanical operations. This research aims to develop elastic modular systems that can be applied as a second skin or brise-soleil to existing buildings. The use of the second skin has the potential to allow existing buildings to perform better in various climatic conditions and to provide a visually compelling skin. This approach is evaluated through three design experiments with prototypes, namely Tent, Curtain and Blind, to serve two fundamental purposes: Comfort and Communication. These experimental prototypes explore the use of digital and physical computation embedded in form-changing materials to design architectural morphing skins that manipulate sunlight and act as responsive shading devices.
TERMCast: Temporal Relation Modeling for Effective Urban Flow Forecasting
Publisher: Springer International Publishing
Date: 2021
Continually Learning Out-of-Distribution Spatiotemporal Data for Robust Energy Forecasting
Publisher: Springer Nature Switzerland
Date: 2023
The unwritten manual of becoming a professor of HCI
Publisher: ACM
Date: 19-04-2023
Toward Social Role-Based Interruptibility Management
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Predicting Personality Traits From Physical Activity Intensity
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2019
Graphical Representation of XML Schema
Publisher: Springer Berlin Heidelberg
Date: 2004
Evolutionary Multi-objective Ensemble Learning for Multivariate Electricity Consumption Prediction
Publisher: IEEE
Date: 07-2018
Towards Detecting Tonic Information Processing Activities with Physiological Data
Publisher: ACM
Date: 08-10-2023
Multivariate electricity consumption prediction with Extreme Learning Machine
Publisher: IEEE
Date: 07-2016
GeSe-Based Ovonic Threshold Switching Volatile True Random Number Generator
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2020
On the Detection of Unauthorized Drones—Techniques and Future Perspectives: A Review
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-06-2022
Theft prediction with individual risk factor of visitors
Publisher: ACM
Date: 06-11-2018
Information gain-based metric for recognizing transitions in human activities
Publisher: Elsevier BV
Date: 07-2017
Wait Time Prediction for Airport Taxis Using Weighted Nearest Neighbor Regression
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Understanding Mobile Information Needs and Behaviours
Publisher: ACM
Date: 08-10-2023
AVERAGE SPATIAL DISTRIBUTION OF COSMIC RAYS BEHIND THE INTERPLANETARY SHOCK—GLOBAL MUON DETECTOR NETWORK OBSERVATIONS
Publisher: American Astronomical Society
Date: 07-07-2016
U&I aware: A framework using data mining and collision detection to increase awareness for intersection users
Publisher: IEEE
Date: 2007
Joint Modelling of Cyber Activities and Physical Context to Improve Prediction of Visitor Behaviors
Publisher: Association for Computing Machinery (ACM)
Date: 13-08-2020
DOI: 10.1145/3393692
Abstract: This article investigates the cyber-physical behavior of users in a large indoor shopping mall by leveraging anonymized (opt in) Wi-Fi association and browsing logs recorded by the mall operators. Our analysis shows that many users exhibit a high correlation between their cyber activities and their physical context. To find this correlation,propose a mechanism to semantically label a physical space with rich categorical information from DBPedia concepts and compute a contextual similarity that represents a user’s activities with the mall context. We demonstrate the application of cyber-physical contextual similarity in two situations: user visit intent classification and future location prediction. The experimental results demonstrate that exploitation of contextual similarity significantly improves the accuracy of such applications.
Predicting citywide passenger demand via reinforcement learning from spatio-temporal dynamics
Publisher: ACM
Date: 05-11-2018
Data-driven occupant modeling strategies and digital tools enabled by IEA EBC annex 79
Publisher: ACM
Date: 07-11-2018
THE TEMPERATURE EFFECT IN SECONDARY COSMIC RAYS (MUONS) OBSERVED AT THE GROUND: ANALYSIS OF THE GLOBAL MUON DETECTOR NETWORK DATA
Publisher: American Astronomical Society
Date: 14-10-2016
Transafe: a crowdsourced mobile platform for crime and safety perception management
Publisher: IEEE
Date: 05-2011
Because Every Sensor Is Unique, so Is Every Pair: Handling Dynamicity in Traffic Forecasting
Publisher: ACM
Date: 09-05-2023
Clustering big spatiotemporal-interval data
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2016
Drone-as-a-Service Composition Under Uncertainty
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Modelling urban-scale occupant behaviour, mobility, and energy in buildings: A survey
Publisher: Elsevier BV
Date: 10-2020
Road intersections as pervasive computing environments: Towards a multiagent real-time collision warning system
Publisher: IEEE
Date: 03-2008
Designing and Evaluating Presentation Strategies for Fact-Checked Content
Publisher: ACM
Date: 21-10-2023
D-Log: A WiFi Log-based differential scheme for enhanced indoor localization with single RSSI source and infrequent sampling rate
Publisher: Elsevier BV
Date: 06-2017
Analysis of Cosmic Rays' Atmospheric Effects and Their Relationships to Cutoff Rigidity and Zenith Angle Using Global Muon Detector Network Data
Publisher: American Geophysical Union (AGU)
Date: 12-2019
DOI: 10.1029/2019JA026651
Abstract: Cosmic rays are charged particles whose flux observed at Earth shows temporal variations related to space weather phenomena and may be an important tool to study them. The cosmic ray intensity recorded with ground‐based detectors also shows temporal variations arising from atmospheric variations. In the case of muon detectors, the main atmospheric effects are related to pressure and temperature changes. In this work, we analyze both effects using data recorded by the Global Muon Detector Network, consisting of four multidirectional muon detectors at different locations, in the period between 2007 and 2016. For each Global Muon Detector Network directional channel, we obtain coefficients that describe the pressure and temperature effects. We then analyze how these coefficients can be related to the geomagnetic cutoff rigidity and zenith angle associated with cosmic ray particles observed by each channel. In the pressure effect analysis, we found that the observed barometric coefficients show a very clear logarithmic correlation with the cutoff rigidity ided by the zenith angle cosine. On the other hand, the temperature coefficients show a good logarithmic correlation with the product of the cutoff and zenith angle cosine after adding a term proportional to the sine of geographical latitude of the observation site. This additional term implies that the temperature effect measured in the Northern Hemisphere detectors is stronger than that observed in the Southern Hemisphere. The physical origin of this term and of the good correlations found in this analysis should be studied in detail in future works.
Current practices and infrastructure for open data based research on occupant-centric design and operation of buildings
Publisher: Elsevier BV
Date: 06-2020
Genetic Programming for Channel Selection from Multi-stream Sensor Data with Application on Learning Risky Driving Behaviours
Publisher: Springer International Publishing
Date: 2014
Visualization of wireless sensor networks using ZigBee's Received Signal Strength Indicator (RSSI) for indoor localization and tracking
Publisher: IEEE
Date: 03-2014
Predicting the city foot traffic with pedestrian sensor data
Publisher: ACM
Date: 2018
Energy-oriented design tools for collaboration in the cloud
Publisher: SAGE Publications
Date: 12-2011
DOI: 10.1260/1478-0771.9.4.339
Abstract: Emerging from the challenge to reduce energy consumption in buildings is the need for energy simulation to be used more effectively to support integrated decision making in early design. As a critical response to a Green Star case study, we present DEEPA, a parametric modeling framework that enables architects and engineers to work at the same semantic level to generate shared models for energy simulation. A cloud-based toolkit provides web and data services for parametric design software that automate the process of simulating and tracking design alternatives, by linking building geometry more directly to analysis inputs. Data, semantics, models and simulation results can be shared on the fly. This allows the complex relationships between architecture, building services and energy consumption to be explored in an integrated manner, and decisions to be made collaboratively.
Context-Aware Ubiquitous Data Mining Based Agent Model for Intersection Safety
Publisher: Springer Berlin Heidelberg
Date: 2005
DOI: 10.1007/11596042_7
An Ambient–Physical System to Infer Concentration in Open-Plan Workplace
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2020
UTE: A Ubiquitous daTa Exploration platform for mobile sensing experiments
Publisher: IEEE
Date: 06-2016
DOI: 10.1109/MDM.2016.61
A Scalable Room Occupancy Prediction with Transferable Time Series Decomposition of CO2 Sensor Data
Publisher: Association for Computing Machinery (ACM)
Date: 27-11-2018
DOI: 10.1145/3217214
Abstract: Human occupancy counting is crucial for both space utilisation and building energy optimisation. In the current article, we present a semi-supervised domain adaptation method for carbon dioxide - Human Occupancy Counter Plus Plus (DA-HOC++), a robust way to estimate the number of people within one room by using data from a carbon dioxide sensor. In our previous work, the proposed Seasonal Decomposition for Human Occupancy Counting (SD-HOC) model can accurately predict the number of in iduals when the training and labelled data are adequately available. DA-HOC++ is able to predict the number of occupants with minimal training data: as little as 1 day’s data. DA-HOC++ accurately predicts indoor human occupancy for five different rooms across different countries using a model trained from a small room and adapted to other rooms. We evaluate DA-HOC++ with two baseline methods: a support vector regression technique and an SD-HOC model. The results demonstrate that DA-HOC++’s performance on average is better by 10.87% in comparison to SVR and 8.65% in comparison to SD-HOC.
RUP: Large Room Utilisation Prediction with carbon dioxide sensor
Publisher: Elsevier BV
Date: 06-2018
Topical event detection on Twitter
Publisher: Springer International Publishing
Date: 2016
Examining the Impact of Uncontrolled Variables on Physiological Signals in User Studies for Information Processing Activities
Publisher: ACM
Date: 18-07-2023
EnviS Tag, Scan, View: A Location-Based App for Visualizing Spatio-temporal Data from Sensor Cloud
Publisher: IEEE
Date: 07-2014
DOI: 10.1109/MDM.2014.47
Probing Streets and the Built Environment with Ambient and Community Sensing
Publisher: Informa UK Limited
Date: 04-2012
An Energy-Efficient Inter-organizational Wireless Sensor Data Collection Framework
Publisher: IEEE
Date: 06-2015
DOI: 10.1109/ICWS.2015.90
Human occupancy recognition with multivariate ambient sensors
Publisher: IEEE
Date: 03-2016
Cosmic-ray short burst observed with the global muon detector network (GMDN) on 2015 June 22
Publisher: American Astronomical Society
Date: 03-08-2018
Urban computing in the wild: A survey on large scale participation and citizen engagement with ubiquitous computing, cyber physical systems, and Internet of Things
Publisher: Elsevier BV
Date: 09-2015
Phone based fall detection by genetic programming
Publisher: ACM
Date: 25-11-2014
Simulated Intersection Environment and Learning of Collision and Traffic Data in the U&I Aware Framework
Publisher: Springer Berlin Heidelberg
Date: 2007
Shrink: Distance preserving graph compression
Publisher: Elsevier BV
Date: 09-2017
Summarizing Movement Graph for Mobility Pattern Analysis
Publisher: ACM
Date: 04-12-2017
Efficient meta-heuristics for the Multi-Objective Time-Dependent Orienteering Problem
Publisher: Elsevier BV
Date: 10-2016
Coact: A framework for context-aware trip planning using active transport
Publisher: IEEE
Date: 03-2018
TransCP: A Transformer Pointer Network for Generic Entity Description Generation with Explicit Content-Planning
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Exploring Human-Computer Interaction in Design Process
Publisher: Wiley
Date: 15-03-2014
Navigating multiple augmented reality overlays through occlusion-based triggers
Publisher: ACM
Date: 25-11-2014
Mining User Behavioral Rules from Smartphone Data Through Association Analysis
Publisher: Springer International Publishing
Date: 2018
Day type classification using cell tower connectivity data from smartphones
Publisher: ACM
Date: 25-11-2014
CAPRA: A contour-based accessible path routing algorithm
Publisher: Elsevier BV
Date: 04-2017
Relation Embedding for Personalised Translation-Based POI Recommendation
Publisher: Springer International Publishing
Date: 2020
Towards adaptive mobile mashups: opportunities for designing effective persuasive technology on the road
Publisher: IEEE
Date: 2010
Algorithmic Governance in Smart Cities: The Conundrum and the Potential of Pervasive Computing Solutions
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2018
UML documentation support for XML schema
Publisher: IEEE
Date: 2004
Multiple-level Point Embedding for Solving Human Trajectory Imputation with Prediction
Publisher: Association for Computing Machinery (ACM)
Date: 02-05-2023
DOI: 10.1145/3582427
Abstract: Sparsity is a common issue in many trajectory datasets, including human mobility data. This issue frequently brings more difficulty to relevant learning tasks, such as trajectory imputation and prediction. Nowadays, little existing work simultaneously deals with imputation and prediction on human trajectories. This work plans to explore whether the learning process of imputation and prediction could benefit from each other to achieve better outcomes. And the question will be answered by studying the coexistence patterns between missing points and observed ones in incomplete trajectories. More specifically, the proposed model develops an imputation component based on the self-attention mechanism to capture the coexistence patterns between observations and missing points among encoder-decoder layers. Meanwhile, a recurrent unit is integrated to extract the sequential embeddings from newly imputed sequences for predicting the following location. Furthermore, a new implementation called Imputation Cycle is introduced to enable gradual imputation with prediction enhancement at multiple levels, which helps to accelerate the speed of convergence. The experimental results on three different real-world mobility datasets show that the proposed approach has significant advantages over the competitive baselines across both imputation and prediction tasks in terms of accuracy and stability.
Software Openness: Evaluating Parameters of Parametric Modeling Tools to Support Creativity and Multidisciplinary Design Integration
Publisher: Springer Berlin Heidelberg
Date: 2010
Three-dimensional vectorial holography based on machine learning inverse design
Publisher: American Association for the Advancement of Science (AAAS)
Date: 17-04-2020
Abstract: 3D vectorial holography reconstructs an arbitrary 3D vectorial field–carrying wavefront using machine learning inverse design.
Traveling Officer Problem: Managing Car Parking Violations Efficiently Using Sensor Data
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2018
VDIM: vector-based diffusion and interpolation matrix for computing region-based crowdsourced ratings
Publisher: ACM
Date: 25-11-2014
Transfer learning for thermal comfort prediction in multiple cities
Publisher: Elsevier BV
Date: 05-2021
Qualitative spatial reasoning with uncertain evidence using Markov logic networks
Publisher: Informa UK Limited
Date: 06-08-2023
Understanding the predictability of user demographics from cyber-physical-social behaviours in indoor retail spaces
Publisher: Springer Science and Business Media LLC
Date: 03-01-2018
Predicting the city foot traffic with pedestrian sensor data
Publisher: ACM
Date: 07-11-2017
Crowd-enabled Processing of Trustworthy, Privacy-Enhanced and Personalised Location Based Services with Quality Guarantee
Publisher: Association for Computing Machinery (ACM)
Date: 27-12-2018
DOI: 10.1145/3287045
Abstract: We propose a novel approach for enabling trustworthy, privacy-enhanced and personalised location based services (LBSs) that find nearby points of interests (POIs) such as restaurants, ATM booths, and hospitals in a crowdsourced manner. In our crowdsourced approach, a user forms a group from the crowd and processes the LBS using the POI knowledge of the group members without involving an external service provider. We use personalised rating in addition to the distance of a POI for finding the answers of the location based queries. The personalised rating of a POI is computed using in idual POI ratings given by the group members and the query requestor's trust and similarity scores for the group members. The major challenges for the crowdsourced data are incompleteness and inaccuracy, which may result in lower quality answer for the LBS. In this paper, we first present techniques to select knowledgeable group members for processing LBSs and thereby increase the accuracy and the confidence level of the query answers. We then develop efficient algorithms to process LBSs in real time and enhance privacy by reducing the number of the group members' POIs shared with the query requestor. Finally, we run extensive experiments using real datasets to show the efficiency and effectiveness of our approach.
Inferring Transportation Mode and Human Activity from Mobile Sensing in Daily Life
Publisher: ACM
Date: 05-11-2018
Automated density-based clustering of spatial urban data for interactive data exploration
Publisher: IEEE
Date: 05-2017
Queue Context Prediction Using Taxi Driver Knowledge
Publisher: ACM
Date: 04-12-2017
Optimal time window for temporal segmentation of sensor streams in multi-activity recognition
Publisher: ACM
Date: 28-11-2016
Bledoorguard: a device-free person identification framework using bluetooth signals for door access
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2018
Collision pattern modeling and real-time collision detection at road intersections
Publisher: IEEE
Date: 09-2007
Related Organisations
Related Funding Activities
Discovery Projects - Grant ID: DP190101485
Start Date: 06-2019
End Date: 06-2023
Amount: $390,000.00
Funder: Australian Research Council
View Funded ActivityLinkage Projects - Grant ID: LP120200305
Start Date: 06-2013
End Date: 12-2018
Amount: $510,000.00
Funder: Australian Research Council
View Funded ActivityIndustrial Transformation Training Centres - Grant ID: IC230100015
Start Date: 2023
End Date: 12-2027
Amount: $5,000,000.00
Funder: Australian Research Council
View Funded ActivityLinkage Projects - Grant ID: LP150100246
Start Date: 03-2017
End Date: 12-2022
Amount: $223,436.00
Funder: Australian Research Council
View Funded ActivityARC Centres Of Excellence - Grant ID: CE200100005
Start Date: 08-2020
End Date: 08-2027
Amount: $31,783,576.00
Funder: Australian Research Council
View Funded Activity