ORCID Profile
0000-0001-7517-0782
Current Organisation
Queensland University of Technology
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Publisher: Elsevier BV
Date: 04-2015
DOI: 10.1016/J.TIBTECH.2015.01.003
Abstract: The global movement of people and goods has increased the risk of biosecurity threats and their potential to incur large economic, social, and environmental costs. Conventional manual biosecurity surveillance methods are limited by their scalability in space and time. This article focuses on autonomous surveillance systems, comprising sensor networks, robots, and intelligent algorithms, and their applicability to biosecurity threats. We discuss the spatial and temporal attributes of autonomous surveillance technologies and map them to three broad categories of biosecurity threat: (i) vector-borne diseases (ii) plant pests and (iii) aquatic pests. Our discussion reveals a broad range of opportunities to serve biosecurity needs through autonomous surveillance.
Publisher: The Royal Society
Date: 03-2015
Abstract: We present a simple model to study Lévy-flight foraging with a power-law step-size distribution in a finite landscape with countable targets. We find that different optimal foraging strategies characterized by a wide range of power-law exponent μ opt , from ballistic motion ( μ opt → 1) to Lévy flight (1 μ opt 3) to Brownian motion ( μ opt ≥ 3), may arise in adaptation to the interplay between the termination of foraging, which is regulated by the number of foraging steps, and the environmental context of the landscape, namely the landscape size and number of targets. We further demonstrate that stochastic returning can be another significant factor that affects the foraging efficiency and optimality of foraging strategy. Our study provides a new perspective on Lévy-flight foraging, opens new avenues for investigating the interaction between foraging dynamics and the environment and offers a realistic framework for analysing animal movement patterns from empirical data.
Publisher: IEEE
Date: 2005
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-12-2022
Publisher: ACM
Date: 16-04-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2010
Publisher: IEEE
Date: 07-2022
Publisher: Association for Computing Machinery (ACM)
Date: 12-2009
Abstract: The efficient management of scarce network resources, including energy and bandwidth, represents a central challenge for wireless sensor networks. The current trend in resource management relies on the introduction of control mechanisms, such as control message exchanges, node-specific addressing, and storage of partial network state information. These mechanisms typically incur communication and processing overhead that does not scale well for larger or denser networks. Instead of introducing control mechanisms for network resource management, this article proposes and evaluates a Directed Broadcast with Overhearing (DBO) approach for sensor networks that combines directed broadcast at the network layer with CSMA and packet overhearing at the MAC layer. Through avoidance of control messaging and exchange of network state information, DBO trades off limited packet duplication overhead for control messaging overhead. This article introduces an analytical model that provides the basis for DBO evaluation and for analysis of the approach's transient packet retransmissions, route convergence, and energy consumption in the average and worst cases. We also present the model implementation details and the simulation experiments that explore the suitability of DBO for networks of different sizes with three different radio models that vary the width of grey regions, and we compare DBO's energy consumption against conventional unicast beacon-based and snooping-based routing protocols. The results indicate that that DBO's route convergence requires an average of five hops for ideal radio reception, seven hops for narrow grey regions, and twelve hops for wide grey regions. These results confirm that DBO shifts energy consumption from critical nodes near the base station to nodes near the source. The overall energy consumption of limited packet duplication overhead with DBO compared to unicast routing shrinks for medium- to large-size networks, rendering it more favorable than conventional communication approaches for large and dense sensor networks.
Publisher: ISCA
Date: 25-10-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2023
Publisher: ACM Press
Date: 2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Publisher: ISCA
Date: 25-10-2020
Publisher: IEEE
Date: 05-2019
Publisher: Springer Science and Business Media LLC
Date: 30-06-2011
Publisher: IEEE
Date: 09-2020
Publisher: MDPI AG
Date: 22-12-2017
DOI: 10.3390/S18010011
Publisher: IEEE
Date: 06-2007
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-08-2020
Publisher: IEEE
Date: 07-2018
Publisher: IEEE
Date: 10-2011
Publisher: IEEE
Date: 03-05-2021
Publisher: IEEE
Date: 05-12-2022
Publisher: ACM
Date: 03-11-2010
Publisher: ACM
Date: 12-04-2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2016
DOI: 10.1109/MPRV.2016.36
Publisher: Public Library of Science (PLoS)
Date: 12-11-2020
DOI: 10.1371/JOURNAL.PONE.0241612
Abstract: Infectious diseases are still a major global burden for modern society causing 13 million deaths annually. One way to reduce the morbidity and mortality rates from infectious diseases is through pre-emptive or targeted vaccinations. Current theoretical vaccination strategies based on contact networks, however, rely on highly specific in idual contact information which is difficult and costly to obtain, in order to identify influential spreading in iduals. Current approaches also focus only on direct contacts between in iduals for spreading, and disregard indirect transmission where a pathogen can spread between one infected in idual and one susceptible in idual who visit the same location within a short time-frame without meeting. This paper presents a novel vaccination strategy which relies on coarse-grained contact information, both direct and indirect, that can be easily and efficiently collected. Rather than tracking exact contact degrees of in iduals, our strategy uses the types of places people visit to estimate a range of contact degrees for in iduals, considering both direct and indirect contacts. We conduct extensive computer simulations to evaluate the performance of our strategy in comparison to state-of-the-art vaccination strategies. Results show that, when considering indirect links, our lower cost vaccination strategy achieves comparable performance to the contact-degree based approach and outperforms other existing strategies without requiring over-detailed information.
Publisher: IEEE
Date: 12-2017
Publisher: ACM
Date: 11-2015
Publisher: Springer International Publishing
Date: 13-11-2015
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: IEEE
Date: 11-2007
Publisher: ISCA
Date: 20-08-2023
Publisher: No publisher found
Date: 2018
Publisher: IEEE
Date: 12-2020
Publisher: Routledge
Date: 05-2015
Publisher: IEEE
Date: 10-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2019
Publisher: Association for Computing Machinery (ACM)
Date: 2014
DOI: 10.1145/2530291
Abstract: Radio connectivity in wireless sensor networks is highly intermittent due to unpredictable and time-varying noise and interference patterns in the environment. Because link qualities are not predictable prior to deployment, current deterministic solutions to unreliable links, such as increasing network density or transmission power, require overprovisioning of network resources and do not always improve reliability. We propose a new dual-radio network architecture to improve communication reliability in wireless sensor networks. Specifically, we show that radio transceivers operating at well-separated frequencies and spatially separated antennas offer robust communication, high link ersity, and better interference mitigation. We derive the optimal parameters for the dual-transceiver setup from frequency and space ersity in theory. We observe that frequency ersity holds the most benefits as long as the antennas are sufficiently separated to prevent coupling. Our experiments on an indoor/outdoor testbed confirm the theoretical predictions and show that radio ersity can significantly improve end-to-end delivery rates and network stability at only a small increase in energy cost over a single radio. Simulation experiments further validate the improvements in multiple topology configurations, but also reveal that the benefits of radio ersity are coupled to the number of available routing paths to the destination.
Publisher: Springer Science and Business Media LLC
Date: 24-08-2016
DOI: 10.1038/SREP31967
Abstract: Understanding the drivers of animal movement is significant for ecology and biology. Yet researchers have so far been unable to fully understand these drivers, largely due to low data resolution. In this study, we analyse a high-frequency movement dataset for a group of grazing cattle and investigate their spatiotemporal patterns using a simple two-state ‘stop-and-move’ mobility model. We find that the dispersal kernel in the moving state is best described by a mixture exponential distribution, indicating the hierarchical nature of the movement. On the other hand, the waiting time appears to be scale-invariant below a certain cut-off and is best described by a truncated power-law distribution, suggesting that the non-moving state is governed by time-varying dynamics. We explore possible explanations for the observed phenomena, covering factors that can play a role in the generation of mobility patterns, such as the context of grazing environment, the intrinsic decision-making mechanism or the energy status of different activities. In particular, we propose a new hypothesis that the underlying movement pattern can be attributed to the most probable observable energy status under the maximum entropy configuration. These results are not only valuable for modelling cattle movement but also provide new insights for understanding the underlying biological basis of grazing behaviour.
Publisher: IEEE
Date: 10-2015
Publisher: Elsevier BV
Date: 06-2018
Publisher: Proceedings of the National Academy of Sciences
Date: 26-12-2019
Abstract: This study infers probabilistic infection routes of a vector-borne disease, by modeling internal dynamics of metapopulations driven by human mobility as multivariate stochastic processes. In this way, our proposed model uncovers the self-excitation and mutual excitation nature of disease spread across a heterogeneous social system with rich context. Our model is a general extension of networked Hawkes processes, providing flexibilities to add constraints (presence of diffusion medium) and to use domain knowledge (cross-metapopulation connectivity), enabling covering of direct and indirect diffusion processes such as contact-based and vector-borne disease spread. Our model is readily applicable to a wide range of intragroup and intergroup diffusion processes in social and natural systems and can infer probabilistic causality between discrete events.
Publisher: IEEE
Date: 22-03-2021
Publisher: Elsevier BV
Date: 09-2022
Publisher: IEEE
Date: 02-05-2022
Publisher: IEEE
Date: 04-2018
Publisher: IEEE
Date: 04-2018
Publisher: IEEE
Date: 12-2022
Publisher: Elsevier BV
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2007
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2022
Publisher: IEEE
Date: 10-2016
Publisher: ACM
Date: 12-11-2020
Publisher: IEEE
Date: 2006
DOI: 10.1109/ICDT.2006.2
Publisher: Elsevier BV
Date: 08-2022
Publisher: IEEE
Date: 08-2022
Publisher: IEEE
Date: 03-2020
Publisher: Wiley
Date: 22-10-2022
Publisher: Springer International Publishing
Date: 20-12-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Auerbach Publications
Date: 19-05-2010
Publisher: IEEE
Date: 08-2015
Publisher: IEEE
Date: 03-2019
Publisher: CRC Press
Date: 18-11-2016
DOI: 10.1201/B19065-6
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: CRC Press
Date: 18-11-2016
DOI: 10.1201/B19065-9
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Publisher: IEEE
Date: 07-2019
Publisher: Elsevier BV
Date: 12-2014
Publisher: Association for Computing Machinery (ACM)
Date: 31-01-2022
DOI: 10.1145/3517189
Abstract: Industrial processes rely on sensory data for decision-making processes, risk assessment, and performance evaluation. Extracting actionable insights from the collected data calls for an infrastructure that can ensure the dissemination of trustworthy data. For the physical data to be trustworthy, it needs to be cross validated through multiple sensor sources with overlapping fields of view. Cross-validated data can then be stored on the blockchain, to maintain its integrity and trustworthiness. Once trustworthy data is recorded on the blockchain, product lifecycle events can be fed into data-driven systems for process monitoring, diagnostics, and optimized control. In this regard, digital twins (DTs) can be leveraged to draw intelligent conclusions from data by identifying the faults and recommending precautionary measures ahead of critical events. Empowering DTs with blockchain in industrial use cases targets key challenges of disparate data repositories, untrustworthy data dissemination, and the need for predictive maintenance. In this survey, while highlighting the key benefits of using blockchain-based DTs, we present a comprehensive review of the state-of-the-art research results for blockchain-based DTs. Based on the current research trends, we discuss a trustworthy blockchain-based DTs framework. We also highlight the role of artificial intelligence in blockchain-based DTs. Furthermore, we discuss the current and future research and deployment challenges of blockchain-supported DTs that require further investigation.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2022
Publisher: Wiley
Date: 08-2005
DOI: 10.1002/WCM.312
Publisher: Elsevier BV
Date: 11-2008
Publisher: Springer International Publishing
Date: 2023
Publisher: Springer International Publishing
Date: 2023
Publisher: Springer International Publishing
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2021
Publisher: Springer International Publishing
Date: 2023
Publisher: IEEE
Date: 04-2018
Publisher: Springer International Publishing
Date: 2023
Publisher: Springer International Publishing
Date: 2023
Publisher: Elsevier BV
Date: 2014
Publisher: Elsevier BV
Date: 07-2022
Publisher: Springer International Publishing
Date: 31-08-2018
Publisher: IEEE
Date: 03-2020
Publisher: IEEE
Date: 12-2021
Publisher: Springer International Publishing
Date: 2023
Publisher: Elsevier BV
Date: 09-2023
Publisher: Elsevier BV
Date: 2021
Publisher: Springer International Publishing
Date: 2023
Publisher: Elsevier BV
Date: 08-2016
Publisher: F1000 Research Ltd
Date: 12-02-2015
DOI: 10.12688/F1000RESEARCH.6105.1
Abstract: Access to appropriate health services is a fundamental problem in developing countries, where patients do not have access to information and to the nearest health service facility. We propose building a recommendation system based on simple SMS text messaging to help Ebola patients readily find the closest health service with available and appropriate resources. The system will map people’s reported symptoms to likely Ebola case definitions and suitable health service locations. In addition to providing a valuable in idual service to people with curable diseases, the proposed system will also predict population-level disease spread risk for infectious diseases using crowd-sourced symptoms from the population. Health workers will be able to better plan and anticipate responses to the current Ebola outbreak in West Africa. Patients will have improved access to appropriate health care. This system could also be applied in other resource poor or rich settings.
Publisher: Association for Computing Machinery (ACM)
Date: 22-06-2023
DOI: 10.1145/3589648
Publisher: IEEE
Date: 05-2020
Publisher: Elsevier
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2016
Publisher: IEEE
Date: 02-05-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2017
Publisher: Elsevier BV
Date: 07-2022
Publisher: Elsevier BV
Date: 05-2021
Publisher: IEEE
Date: 08-2016
Publisher: IEEE
Date: 12-2022
Publisher: IEEE
Date: 06-2015
Publisher: ACM
Date: 09-09-2019
Publisher: ACM
Date: 05-11-2018
Publisher: Springer Singapore
Date: 25-09-2020
Publisher: Elsevier BV
Date: 07-2023
Publisher: Springer Science and Business Media LLC
Date: 16-02-2008
Publisher: IEEE
Date: 10-2013
Publisher: IEEE
Date: 03-2017
Publisher: ACM
Date: 07-07-2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: ACM
Date: 12-04-2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: IEEE
Date: 10-2019
Publisher: Elsevier BV
Date: 03-2019
Publisher: Association for Computing Machinery (ACM)
Date: 30-12-2015
DOI: 10.1145/2629593
Abstract: Long-term sensor network deployments demand careful power management. While managing power requires understanding the amount of energy harvestable from the local environment, current solar prediction methods rely only on recent local history, which makes them susceptible to high variability. In this article, we present a model and algorithms for distributed solar current prediction based on multiple linear regression to predict future solar current based on local, in situ climatic and solar measurements. These algorithms leverage spatial information from neighbors and adapt to the changing local conditions not captured by global climatic information. We implement these algorithms on our Fleck platform and run a 7-week-long experiment validating our work. In analyzing our results from this experiment, we determined that computing our model requires an increased energy expenditure of 4.5mJ over simpler models (on the order of 10 -7 % of the harvested energy) to gain a prediction improvement of 39.7%.
Publisher: CRC Press
Date: 18-11-2015
DOI: 10.1201/B19065
Publisher: IEEE
Date: 11-2018
Publisher: Public Library of Science (PLoS)
Date: 08-08-2016
Publisher: IEEE
Date: 06-2008
Publisher: IEEE
Date: 05-2023
Publisher: IEEE
Date: 03-2017
Publisher: IEEE
Date: 10-2007
Publisher: IEEE
Date: 05-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2019
Publisher: IEEE
Date: 04-2015
Publisher: MDPI AG
Date: 26-05-2017
DOI: 10.3390/S17061221
Publisher: ACM
Date: 18-04-2017
Publisher: Elsevier BV
Date: 06-2015
Publisher: Elsevier BV
Date: 10-2022
Publisher: IEEE
Date: 2005
DOI: 10.1109/ICW.2005.76
Publisher: Elsevier BV
Date: 03-2021
Publisher: Elsevier BV
Date: 08-2018
Publisher: MDPI AG
Date: 24-11-2008
DOI: 10.3390/S8117493
Publisher: ACM
Date: 11-06-2007
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-09-2021
Publisher: Elsevier BV
Date: 07-2016
Publisher: The Royal Society
Date: 08-2019
DOI: 10.1098/RSOS.190845
Abstract: Interaction patterns at the in idual level influence the behaviour of diffusion over contact networks. Most of the current diffusion models only consider direct interactions, capable of transferring infectious items among in iduals, to build transmission networks of diffusion. However, delayed indirect interactions, where a susceptible in idual interacts with infectious items after the infected in idual has left the interaction space, can also cause transmission events. We define a diffusion model called the same place different time transmission (SPDT)-based diffusion that considers transmission links for these indirect interactions. Our SPDT model changes the network dynamics where the connectivity among in iduals varies with the decay rates of link infectivity. We investigate SPDT diffusion behaviours by simulating airborne disease spreading on data-driven contact networks. The SPDT model significantly increases diffusion dynamics with a high rate of disease transmission. By making the underlying connectivity denser and stronger due to the inclusion of indirect transmissions, SPDT models are more realistic than same place same time transmission (SPST)-based models for the study of various airborne disease outbreaks. Importantly, we also find that the diffusion dynamics including indirect links are not reproducible by the current SPST models based on direct links, even if both SPDT and SPST networks assume the same underlying connectivity. This is because the transmission dynamics of indirect links are different from those of direct links. These outcomes highlight the importance of the indirect links for predicting outbreaks of airborne diseases.
Publisher: ACM
Date: 18-04-2017
Publisher: SCITEPRESS - Science and Technology Publications
Date: 2019
Publisher: IEEE
Date: 05-2023
Publisher: IEEE
Date: 03-2016
Publisher: Springer International Publishing
Date: 2023
Publisher: Springer International Publishing
Date: 2014
Publisher: CSIRO
Date: 2013
Publisher: Elsevier BV
Date: 12-2019
Publisher: IEEE
Date: 05-01-2021
Publisher: IEEE
Date: 10-2021
Publisher: Association for Computing Machinery (ACM)
Date: 07-2012
Abstract: Location awareness is a key requirement for many pervasive applications. Collaborative localization can improve accuracy and coverage indoors and improve power consumption by duty-cycling GPS outdoors. We use Bluetooth for collaborative localization of mobile personal devices. Specifically, we embed information in Bluetooth device names to improve latency of information exchange between participating nodes. We identify and demonstrate on real hardware two problems in the Bluetooth stack that negatively impact localization accuracy: a) device name caching that introduces significant device-specific delays in transmitting information between nodes, and b) poor accuracy of time synchronization in modern mobile devices. Our solution is to append additional time information to the device name and track time offsets between nodes. We verify experimentally that this helps to both detect outliers and correct for time-synchronization errors and thus mitigate localization errors.
Publisher: IEEE
Date: 08-2020
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: IEEE
Date: 04-2015
Publisher: Elsevier BV
Date: 07-2009
Publisher: MDPI AG
Date: 06-12-2016
DOI: 10.3390/JSAN5040018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: JMIR Publications Inc.
Date: 27-10-2020
DOI: 10.2196/19874
Abstract: The use of location-based data in clinical settings is often limited to real-time monitoring. In this study, we aim to develop a proximity-based localization system and show how its longitudinal deployment can provide operational insights related to staff and patients' mobility and room occupancy in clinical settings. Such a streamlined data-driven approach can help in increasing the uptime of operating rooms and more broadly provide an improved understanding of facility utilization. The aim of this study is to measure the accuracy of the system and algorithmically calculate measures of mobility and occupancy. We developed a Bluetooth low energy, proximity-based localization system and deployed it in a hospital for 30 days. The system recorded the position of 75 people (17 patients and 55 staff) during this period. In addition, we collected ground-truth data and used them to validate system performance and accuracy. A number of analyses were conducted to estimate how people move in the hospital and where they spend their time. Using ground-truth data, we estimated the accuracy of our system to be 96%. Using mobility trace analysis, we generated occupancy rates for different rooms in the hospital occupied by both staff and patients. We were also able to measure how much time, on average, patients spend in different rooms of the hospital. Finally, using unsupervised hierarchical clustering, we showed that the system could differentiate between staff and patients without training. Analysis of longitudinal, location-based data can offer rich operational insights into hospital efficiency. In particular, they allow quick and consistent assessment of new strategies and protocols and provide a quantitative way to measure their effectiveness.
Publisher: Springer Science and Business Media LLC
Date: 04-09-2020
Publisher: Elsevier BV
Date: 09-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2023
Publisher: IEEE
Date: 05-2016
Publisher: IEEE
Date: 10-2009
Publisher: IEEE
Date: 03-01-2023
Publisher: IEEE
Date: 11-2015
Publisher: ACM
Date: 18-04-2017
Publisher: Public Library of Science (PLoS)
Date: 08-07-2015
Publisher: Elsevier BV
Date: 10-2023
Publisher: ACM Press
Date: 2017
Publisher: Springer International Publishing
Date: 20-12-2014
Publisher: IEEE
Date: 05-2023
Publisher: Elsevier BV
Date: 07-2023
Publisher: IEEE
Date: 11-2012
Publisher: Association for Computing Machinery (ACM)
Date: 12-2012
Abstract: Improved performance and a proven deployment strategy make SPDY a potential successor to HTTP.
Publisher: Unpublished
Date: 2016
Publisher: Public Library of Science (PLoS)
Date: 18-10-2021
DOI: 10.1371/JOURNAL.PONE.0258332
Abstract: Disease surveillance and response are critical components of epidemic preparedness. The disease response, in most cases, is a set of reactive measures that follow the outcomes of the disease surveillance. Hence, timely surveillance is a prerequisite for an effective response. We apply epidemiological soundness criteria in combination with the Latent Influence Point Process and time-to-event models to construct a disease spread network. The network implicitly quantifies the fertility (whether a case leads to secondary cases) and reproduction (number of secondary cases per infectious case) of the cases as well as the size and generations (of the infection chain) of the outbreaks. We test our approach by applying it to historic dengue case data from Australia. Using the data, we empirically confirm that high morbidity relates positively with delay in disease response. Moreover, we identify what constitutes timely surveillance by applying various thresholds of disease response delay to the network and report their impact on case fertility, reproduction, number of generations and ultimately, outbreak size. We observe that enforcing a response delay threshold of 5 days leads to a large average reduction across all parameters (occurrence 87%, reproduction 83%, outbreak size 80% and outbreak generations 47%), whereas extending the threshold to 10 days, in comparison, significantly limits the effectiveness of the response actions. Lastly, we identify the components of the disease surveillance system that can be calibrated to achieve the identified thresholds. We identify practically achievable, timely surveillance thresholds (on temporal scale) that lead to an effective response and identify how they can be satisfied. Our approach can be utilized to provide guidelines on spatially and demographically targeted resource allocation for public awareness c aigns as well as to improve diagnostic abilities and turn-around times for the doctors and laboratories involved.
Publisher: CRC Press
Date: 30-01-2023
Publisher: Association for Computing Machinery (ACM)
Date: 03-2013
Abstract: GPS is a commonly used and convenient technology for determining absolute position in outdoor environments, but its high power consumption leads to rapid battery depletion in mobile devices. An obvious solution is to duty cycle the GPS module, which prolongs the device lifetime at the cost of increased position uncertainty while the GPS is off. This article addresses the trade-off between energy consumption and localization performance in a mobile sensor network application. The focus is on augmenting GPS location with more energy-efficient location sensors to bound position estimate uncertainty while GPS is off. Empirical GPS and radio contact data from a large-scale animal tracking deployment is used to model node mobility, radio performance, and GPS. Because GPS takes a considerable, and variable, time after powering up before it delivers a good position measurement, we model the GPS behavior through empirical measurements of two GPS modules. These models are then used to explore duty cycling strategies for maintaining position uncertainty within specified bounds. We then explore the benefits of using short-range radio contact logging alongside GPS as an energy-inexpensive means of lowering uncertainty while the GPS is off, and we propose strategies that use RSSI ranging and GPS back-offs to further reduce energy consumption. Results show that our combined strategies can cut node energy consumption by one third while still meeting application-specific positioning criteria.
Publisher: Springer US
Date: 2007
Publisher: ACM
Date: 12-04-2010
Publisher: ACM
Date: 13-11-2013
Publisher: IEEE
Date: 2006
Publisher: Wiley
Date: 15-03-2019
Publisher: Springer Science and Business Media LLC
Date: 20-08-2021
DOI: 10.1186/S12889-021-11616-9
Abstract: Novel coronavirus disease (COVID-19) has spread across the world at an unprecedented pace, reaching over 200 countries and territories in less than three months. In response, many governments denied entry to travellers arriving from various countries affected by the virus. While several industries continue to experience economic losses due to the imposed interventions, it is unclear whether the different travel restrictions were successful in reducing COVID-19 importations. Here we develop a comprehensive probabilistic framework to model daily COVID-19 importations, considering different travel bans. We quantify the temporal effects of the restrictions and elucidate the relationship between incidence rates in other countries, travel flows and the expected number of importations into the country under investigation. As a cases study, we evaluate the travel bans enforced by the Australian government. We find that international travel bans in Australia lowered COVID-19 importations by 87.68% (83.39 - 91.35) between January and June 2020. The presented framework can further be used to gain insights into how many importations to expect should borders re-open. While travel bans lowered the number of COVID-19 importations overall, the effectiveness of bans on in idual countries varies widely and directly depends on the change in behaviour in returning residents and citizens. Authorities may consider the presented information when planning a phased re-opening of international borders.
Publisher: MDPI AG
Date: 19-10-2012
DOI: 10.3390/JSAN1030183
Abstract: Long-term outdoor localization remains challenging due to the high energy profiles of GPS modules. Duty cycling the GPS module combined with inertial sensors can improve energy consumption. However, inertial sensors that are kept active all the time can also drain mobile node batteries. This paper proposes duty cycling strategies for inertial sensors to maintain a target position accuracy and node lifetime. We present a method for duty cycling motion sensors according to features of movement events, and evaluate its energy and accuracy profile for an empirical data trace of cattle movement. We further introduce the concept of group-based duty cycling, where nodes that cluster together can share the burden of motion detection to reduce their duty cycles. Our evaluation shows that both variants of motion sensor duty cycling yield up to 78% improvement in overall node power consumption, and that the group-based method yields an additional 20% power reduction during periods of low mobility.
Publisher: Elsevier BV
Date: 08-2021
Publisher: IEEE
Date: 05-2006
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Publisher: Informa UK Limited
Date: 13-02-2023
Publisher: MDPI AG
Date: 03-08-2015
DOI: 10.3390/JSAN4030189
Publisher: University of Queensland Library
Date: 2015
Publisher: IEEE
Date: 08-2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2023
Publisher: Auerbach Publications
Date: 19-05-2010
Publisher: Institution of Engineering and Technology (IET)
Date: 15-11-2022
DOI: 10.1049/ESI2.12047
Publisher: Springer International Publishing
Date: 2022
Publisher: IEEE
Date: 05-2023
Publisher: Elsevier BV
Date: 04-2021
Publisher: Acoustical Society of America (ASA)
Date: 05-2015
DOI: 10.1121/1.4919298
Abstract: Large scale networks of embedded wireless sensor nodes can passively capture sound for species detection. However, the acoustic recordings result in large amounts of data requiring in-network classification for such systems to be feasible. The current state of the art in the area of in-network bioacoustics classification targets narrowband or long-duration signals, which render it unsuitable for detecting species that emit impulsive broadband signals. In this study, impulsive broadband signals were classified using a small set of spectral and temporal features to aid in their automatic detection and classification. A prototype system is presented along with an experimental evaluation of automated classification methods. The sound used was recorded from a freshwater invasive fish in Australia, the spotted tilapia (Tilapia mariae). Results show a high degree of accuracy after evaluating the proposed detection and classification method for T. mariae sounds and comparing its performance against the state of the art. Moreover, performance slightly improves when the original signal was down-s led from 44.1 to 16 kHz. This indicates that the proposed method is well-suited for detection and classification on embedded devices, which can be deployed to implement a large scale wireless sensor network for automated species detection.
Publisher: Wiley
Date: 08-2011
DOI: 10.1002/WCM.826
Publisher: Springer International Publishing
Date: 2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2022
Publisher: IEEE
Date: 2004
Publisher: Springer International Publishing
Date: 2022
Publisher: ACM
Date: 08-11-2021
Publisher: Canadian Center of Science and Education
Date: 21-05-2013
DOI: 10.5539/MAS.V7N6P59
Publisher: Springer International Publishing
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2004
Publisher: IEEE
Date: 05-2014
Publisher: Elsevier BV
Date: 03-2020
Publisher: IEEE
Date: 05-2023
Publisher: JMIR Publications Inc.
Date: 05-05-2020
Abstract: he use of location-based data in clinical settings is often limited to real-time monitoring. In this study, we aim to develop a proximity-based localization system and show how its longitudinal deployment can provide operational insights related to staff and patients' mobility and room occupancy in clinical settings. Such a streamlined data-driven approach can help in increasing the uptime of operating rooms and more broadly provide an improved understanding of facility utilization. he aim of this study is to measure the accuracy of the system and algorithmically calculate measures of mobility and occupancy. e developed a Bluetooth low energy, proximity-based localization system and deployed it in a hospital for 30 days. The system recorded the position of 75 people (17 patients and 55 staff) during this period. In addition, we collected ground-truth data and used them to validate system performance and accuracy. A number of analyses were conducted to estimate how people move in the hospital and where they spend their time. sing ground-truth data, we estimated the accuracy of our system to be 96%. Using mobility trace analysis, we generated occupancy rates for different rooms in the hospital occupied by both staff and patients. We were also able to measure how much time, on average, patients spend in different rooms of the hospital. Finally, using unsupervised hierarchical clustering, we showed that the system could differentiate between staff and patients without training. nalysis of longitudinal, location-based data can offer rich operational insights into hospital efficiency. In particular, they allow quick and consistent assessment of new strategies and protocols and provide a quantitative way to measure their effectiveness.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2020
Publisher: Elsevier BV
Date: 04-2018
Publisher: IEEE
Date: 05-2019
Publisher: ISCA
Date: 15-09-2019
Publisher: Public Library of Science (PLoS)
Date: 04-12-2019
Publisher: IEEE
Date: 06-2019
Publisher: Elsevier BV
Date: 2011
Publisher: IEEE
Date: 12-2021
Publisher: IEEE
Date: 12-2021
Publisher: IEEE
Date: 04-2020
Publisher: IEEE
Date: 2020
Publisher: IEEE
Date: 03-2016
Publisher: Unpublished
Date: 2011
Publisher: IEEE
Date: 21-03-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2010
DOI: 10.1109/TMC.2010.35
Publisher: IEEE
Date: 09-2018
Publisher: Public Library of Science (PLoS)
Date: 13-11-2013
Publisher: Springer Science and Business Media LLC
Date: 17-08-2022
DOI: 10.1186/S12879-022-07664-0
Abstract: COVID-19 has had a substantial impact globally. It spreads readily, particularly in enclosed and crowded spaces, such as public transport carriages, yet there are limited studies on how this risk can be reduced. We developed a tool for exploring the potential impacts of mitigation strategies on public transport networks, called the Systems Analytics for Epidemiology in Transport (SAfE Transport). SAfE Transport combines an agent-based transit assignment model, a community-wide transmission model, and a transit disease spread model to support strategic and operational decision-making. For this simulated COVID-19 case study, the transit disease spread model incorporates both direct (person-to-person) and fomite (person-to-surface-to-person) transmission modes. We determine the probable impact of wearing face masks on trains over a seven day simulation horizon, showing substantial and statistically significant reductions in new cases when passenger mask wearing proportions are greater than 80%. The higher the level of mask coverage, the greater the reduction in the number of new infections. Also, the higher levels of mask coverage result in an earlier reduction in disease spread risk. These results can be used by decision makers to guide policy on face mask use for public transport networks.
Publisher: IEEE
Date: 05-2022
Publisher: IEEE
Date: 10-2017
Publisher: ACM
Date: 07-07-2009
Publisher: IEEE
Date: 08-2008
Publisher: IEEE
Date: 04-2020
Publisher: CRC Press
Date: 25-02-2022
Publisher: ACM
Date: 03-11-2010
Publisher: IEEE
Date: 06-2022
Publisher: Cold Spring Harbor Laboratory
Date: 27-03-2020
DOI: 10.1101/2020.03.25.20043877
Abstract: The rapid global spread of coronavirus disease (COVID-19) is unprecedented. The outbreak has quickly spread to more than 100 countries reporting over 100,000 confirmed cases. Australia reported its first case of COVID-19 on 25 th January 2020 and has since implemented travel restrictions to stop further introduction of the virus. We analysed daily global COVID-19 data published by the World Health Organisation to investigate the spread of the virus thus far. To assess the current risk of COVID-19 importation and local spread in Australia we predict international passenger flows into Australia during 2020. Our analysis of global data shows that Australia can expect a similar growth rate of reported cases as observed in France and the United States. We identify travel patterns of Australian citizens/residents and foreign travellers that can inform the implementation of new and the alteration of existing travel restrictions related to COVID-19. Our findings identify the risk reduction potential of current travel bans, based on the proportion of returning travellers to Australia that are residents or visitors. The similarity of the exponential growth in the epidemic curve in Australia to other countries guides forecasts of COVID-19 growth in Australia, and opportunities for drawing lessons from other countries with more advanced outbreaks.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2023
Publisher: Elsevier BV
Date: 09-2013
No related grants have been discovered for Raja Jurdak.