Journal Articles
Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915
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Item Device-Free Localization Using Privacy-Preserving Infrared Signatures Acquired from Thermopiles and Machine Learning(IEEE, 4/06/2021) Faulkner N; Alam F; Legg M; Demidenko SThe development of an accurate passive localization system utilizing thermopile sensing and artificial intelligence is discussed in this paper. Several machine learning techniques are explored to create robust angular and radius coordinate models for a localization target with respect to thermopile sensors. These models are leveraged to develop a reconfigurable passive localization system that can use a varying number of thermopiles without the need for retraining. The proposed robust system achieves high localization accuracy (with the median error between 0.13 m and 0.2 m) while being trained using a single human subject and tested against multiple other subjects. It is shown that the proposed system does not experience any significant performance deterioration when localizing a subject at different ambient temperatures or with different configurations of the thermopile sensors placement.Item A Machine Learning Approach to Enhance the Performance of D2D-Enabled Clustered Networks(IEEE, 20/01/2021) Aslam S; Alam F; Hasan SF; Rashid MAClustering has been suggested as an effective technique to enhance the performance of multicasting networks. Typically, a cluster head is selected to broadcast the cached content to its cluster members utilizing Device-to-Device (D2D) communication. However, some users can attain better performance by being connected with the Evolved Node B (eNB) rather than being in the clusters. In this article, we apply machine learning algorithms, namely Support Vector Machine, Random Forest, and Deep Neural Network to identify the users that should be serviced by the eNB. We therefore propose a mixed-mode content distribution scheme where the cluster heads and eNB service the two segregated groups of users to improve the performance of existing clustering schemes. A D2D-enabled multicasting scenario has been set up to perform a comprehensive simulation study that demonstrates that by utilizing the mixed-mode scheme, the performance of individual users, as well as the whole network, improve significantly in terms of throughput, energy consumption, and fairness. This study also demonstrates the trade-off between eNB loading and performance improvement for various parameters.Item SpringLoc: A device-free localization technique for indoor positioning and tracking using adaptive RSSI spring relaxation(Institute of Electrical and Electronics Engineers (IEEE), 5/05/2019) Konings D; Alam F; Noble F; Lai EDevice-free localization (DFL) algorithms using the received signal strength indicator (RSSI) metrics have become a popular research focus in recent years as they allow for location-based service using commercial-off-the-shelf (COTS) wireless equipment. However, most existing DFL approaches have limited applicability in realistic smart home environments as they typically require extensive offline calibration, large node densities, or use technology that is not readily available in commercial smart homes. In this paper, we introduce SpringLoc and a DFL algorithm that relies on simple parameter tuning and does not require offline measurements. It localizes and tracks an entity using an adaptive spring relaxation approach. The anchor points of the artificial springs are placed in regions containing the links that are affected by the entity. The affected links are determined by comparing the kernel-based histogram distance of successive RSSI values. SpringLoc is benchmarked against existing algorithms in two diverse and realistic environments, showing significant improvement over the state-of-the-art, especially in situations with low-node deployment density.Item The Prospect for an Australian–Asian Power Grid: A Critical Appraisal(MDPI AG, 15/01/2018) Halawa E; Shi X; Nepal R; Sari NH; James GAustralia is an energy net self-sufficient country rich in energy resources, from fossil-based to renewable energy. Australia, a huge continent with low population density, has witnessed impressive reduction in energy consumption in various sectors of activity in recent years. Currently, coal and natural gas are two of Australia's major export earners, yet its abundant renewable energy resources such as solar, wind, and tidal, are still underutilized. The majority of Asian countries, on the other hand, are in the middle of economic expansion, with increasing energy consumption and lack of energy resources or lack of energy exploration capability becoming a serious challenge. Electricity interconnection linking two or more independent grids within a country or at cross-border or regional levels has found its way into electricity markets worldwide. This concept allows for electricity exchanges that lead to optimized use and sharing of electricity generated from different sources. The interconnection also enables the long distance exploitation of renewable energy which would otherwise be physically impossible. ASEAN (Association of Southeast Asian Nations) and other regional groupings in Asia have initiated a number of interconnections to gain economic benefits. Asian's hunger for energy for its economic development, climate change that has become a global and urgent issue to be solved, and Australia's abundant renewable energy resources have all prompted increasing interest in a super-grid interconnection linking Australia to Asian grids, the Australian-Asian (Power) Grid (AAG). This paper overviews the existing grid interconnections as well as current initiatives at domestic, sub-regional, and regional levels worldwide, with a particular focus on Asia. The paper concludes with a critical appraisal on the benefits, potential, challenges and issues to be encountered by the AAG initiative.Item CapLoc: Capacitive Sensing Floor for Device-Free Localization and Fall Detection(IEEE Xplore, 12/10/2020) Faulkner N; Parr B; Alam F; Legg M; Demidenko SPassive indoor positioning, also known as Device-Free Localization (DFL), has applications such as occupancy sensing, human-computer interaction, fall detection, and many other location-based services in smart buildings. Vision-, infrared-, wireless-based DFL solutions have been widely explored in recent years. They are characterized by respective strengths and weaknesses in terms of the desired accuracy, feasibility in various real-world scenarios, etc. Passive positioning by tracking the footsteps on the floor has been put forward as one of the promising options. This article introduces CapLoc, a floor-based DFL solution that can localize a subject in real-time using capacitive sensing. Experimental results with three individuals walking 39 paths on the CapLoc show that it can detect and localize a single target's footsteps accurately with a median localization error of 0.026 m. The potential for fall detection is also shown with the outlines of various poses of the subject lying upon the floor.Item Clinical risk factors, bone density and fall history in the prediction of incident fracture among men and women(2013) Edwards MH; Jameson K; Denison H; Harvey NC; Sayer AA; Dennison EM; Cooper CThe FRAX(tr) algorithm uses clinical risk factors (CRF) and bone mineral density (BMD) to predict fracture risk but does not include falls history in the calculation. Using results from the Hertfordshire Cohort Study, we examined the relative contributions of CRFs, BMD and falls history to fracture prediction. We studied 2299 participants at a baseline clinic that included completion of a health questionnaire and anthropometric data. A mean of 5.5years later (range 2.9-8.8years) subjects completed a postal questionnaire detailing fall and fracture history. In a subset of 368 men and 407 women, bone densitometry was performed using a Hologic QDR 4500 instrument. There was a significantly increased risk of fracture in men and women with a previous fracture. A one standard deviation drop in femoral neck BMD was associated with a hazards ratio (HR) of incident fracture (adjusted for CRFs) of 1.92 (1.04-3.54) and 1.77 (1.16-2.71) in men and women respectively. A history of any fall since the age of 45years resulted in an unadjusted HR of fracture of 7.31 (3.78-14.14) and 8.56 (4.85-15.13) in men and women respectively. In a ROC curve analysis, the predictive capacity progressively increased as BMD and previous falls were added into an initial model using CRFs alone. Falls history is a further independent risk factor for fracture. Falls risk should be taken into consideration when assessing whether or not to commence medication for osteoporosis and should also alert the physician to the opportunity to target falls risk directly.Item Synthea: An approach, method, and software mechanism for generating synthetic patients and the synthetic electronic health care record(Oxford University Press (OUP), 30/08/2017) Walonoski J; Kramer M; Nichols J; Quina A; Moesel; Hall D; Duffett C; Dube K; Gallagher T; McLachlan SObjective: Our objective is to create a source of synthetic electronic health records that is readily available; suited to industrial, innovation, research, and educational uses; and free of legal, privacy, security, and intellectual property restrictions. Materials and Methods: We developed Synthea, an open-source software package that simulates the lifespans of synthetic patients, modeling the 10 most frequent reasons for primary care encounters and the 10 chronic conditions with the highest morbidity in the United States. Results: Synthea adheres to a previously developed conceptual framework, scales via open-source deployment on the Internet, and may be extended with additional disease and treatment modules developed by its user community. One million synthetic patient records are now freely available online, encoded in standard formats (eg, Health Level-7 [HL7] Fast Healthcare Interoperability Resources [FHIR] and Consolidated-Clinical Document Architecture), and accessible through an HL7 FHIR application program interface. Discussion: Health care lags other industries in information technology, data exchange, and interoperability. The lack of freely distributable health records has long hindered innovation in health care. Approaches and tools are available to inexpensively generate synthetic health records at scale without accidental disclosure risk, lowering current barriers to entry for promising early-stage developments. By engaging a growing community of users, the synthetic data generated will become increasingly comprehensive, detailed, and realistic over time. Conclusion: Synthetic patients can be simulated with models of disease progression and corresponding standards of care to produce risk-free realistic synthetic health care records at scale.Item Who is most likely to offend in my store now? Statistical steps towards retail crime prevention with Auror(Australian Mathematical Society, 14/08/2017) McDonald BW; Hall L; Zhang XPAuror is establishing itself both locally and internationally as a leader in retail crime solutions. In mid-2015 a study group of mathematicians and statisticians teamed up with Auror to analyse data from the first two and a half years of their venture to identify and prevent retail theft. The aim was to explore methods for nominating the top ten individuals most likely to offend in a particular store at a particular time. Various methods were employed to explore the relationships between retail crime incidents, including generalised linear models, regression trees and similarity matrices. The relationships identified were then used to inform predictions on individuals most likely to reoffend. The focus of the current analysis is to model the behaviour of reoffenders. At the time of the study group the project was still in the early phases of data collection. As data collection proceeds, prediction methods will likely give better and better intelligence to aid crime prevention efforts.Item The importance of fall history in fracture risk assessment(2013) Edwards MH; Jameson KA; Denison H; Harvey NC; Sayer AA; Dennison EM; Cooper CItem Dual-band waveform generator with ultra-wide low-frequency tuning-range(Institute of Electrical and Electronics Engineers (IEEE), 22/04/2016) AL-DARKAZLY IAA; Hasan SMRThis paper presents a novel mixed-signal low-power dual-band square/triangular waveform generator (WFG) chip with a wide low-frequency tuning range for medical bio-electric stimulation therapy. It consists of a relaxation oscillator comprising a hysteresis Schmitt trigger and a timing integrator, along with frequency divider (FD) stages and path selector output for driving an electrode from 16 selectable channels. It was fabricated using Global Foundries 8RF-DM 130-nm CMOS process with a supply voltage of ±1 V for the oscillator and +1 V for logic circuits. The WFG provides an output of around 1.5 Vp-p at a nominal low oscillation frequency of 17 kHz using small-size on-chip passive components of values 10 kΩ and 10 pF. The WFG core (band I) can be tuned in the range 6.44-1003 kHz through bias current adjustment, while a lower frequency (band II) in the range 0.1 Hz-502 kHz can be provided digitally through a 2 stage. The power consumption was only 0.457 mW for the WFG and 2.1 mW for the FD circuit while occupying a total silicon area of only 18 426 μm2.
