Showing items 1 - 20 of 12598

A DNA toolbox for non-invasive genetic studies of sambar deer (Rusa unicolor)

  • Authors: Davies, Chris , Wright, Wendy , Wedrowicz, Faye , Hogan, Fiona
  • Date: 2020
  • Type: Text , Journal article , Article
  • Relation: Australian Mammalogy Vol. 42, no. 1 (2020), p. 58-66
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  • Description: Invasive sambar deer (Rusa unicolor) are having significant detrimental impacts on natural environments in south-eastern Australia. Little, however, is known about their ecology, limiting evidence-based management strategies directed at reducing deer impacts. Genetic data, generated from DNA isolated from deer scats, can be used to fill ecological knowledge gaps. This study outlines a non-invasive genetic sampling strategy by which good-quality DNA from a single deer scat can be used to determine (1) species of origin, (2) sex and (3) a unique DNA profile. DNA from deer tissue and sambar deer scat samples were used to develop and optimise molecular methods to collect reliable genetic information. A DNA toolbox is presented that describes how to find, collect and store scat samples, isolate DNA and use molecular markers to generate informative genetic data. Generating genetic data using this approach will support studies aimed at acquiring ecological knowledge about sambar deer. Such knowledge will be critical for developing evidence-based recommendations to improve on-ground management decisions for sambar deer.

A review of code blue activations in a single regional Australian healthcare service : a retrospective descriptive study of RISKMAN data

  • Authors: Porter, Joanne , Peck, Blake , McNabb, Tiffinee , Missen, Karen
  • Date: 2020
  • Type: Text , Journal article , Article
  • Relation: Journal of Clinical Nursing Vol. 29, no. 1-2 (2020), p. 221-227
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  • Description: Background: In the case of life-threatening conditions such as respiratory or cardiac arrest, or the clinical deterioration of the patient, a Code Blue activation may be instigated. A Code Blue activation involves a team of advanced trained clinicians attending the emergency needs of the patient. Aims and objectives: The aim of the study was to explore the number of cases of Code Blue activations, looking at the timing, clinical ward, diagnosis and activation criteria while noting cases where escalation from a Medical Emergency Team (MET) call occurs in one Regional Healthcare Service in Victoria, Australia, over a six-year period. Methods: A quantitative retrospective descriptive study of Code Blue emergencies over a six-year period from June 2010 to June 2016 was conducted. Data collected from the RISKMAN program operating at a single site was imported into SPSS (V 22) for descriptive statistical analysis. A STROBE EQUATOR checklist was used for this study (see File S1). Findings: The majority of Code Blue activations were male (59%, n = 127) and aged between 70 and 89 years of age (43%, n = 93). A Code Blue activation was more likely to occur at 08:00 hr, 14:00 hr or 22:00 hr, corresponding to the nurses’ change in shift, with the majority of Code Blues (27.8%, n = 60) occurring in the emergency department. Cardiac arrest was the main activation criterion with 54.6% (n = 118) cases followed by respiratory arrest (14%, n = 32). Interestingly, 20% (n = 45) of the Code Blue activations were upgraded from a Medical Emergency Team (MET) call. Conclusion: This project has produced several interesting findings surrounding Code Blue activations at one regional healthcare service which are not present in existing literature and is worthwhile for further investigation. Relevance to clinical practice: Understanding Code Blue activation criteria, common timings (month, time of day) and patient demographics ensures clinicians can remain vigilant in watching for the signs of patient deterioration and improve staff preparedness Code Blue events. © 2019 John Wiley & Sons Ltd

A review of south pacific tropical cyclones : impacts of natural climate variability and climate change

  • Authors: Chand, Savin , Dowdy, Andrew , Bell, Samuel , Tory, Kevin
  • Date: 2020
  • Type: Text , Book chapter , Book Chapter
  • Relation: Springer Climate p. 251-273
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  • Description: Impacts of tropical cyclones in the South Pacific Island countries are of great significance. Now with the growing threats from human-induced climate change, the need for effective disaster risk management and adaptation strategies for these island countries is more important than before. In order to implement appropriate strategies, a comprehensive understanding of South Pacific tropical cyclone activity—and how it is likely to change as a result of human-induced climate change—is essential. While a number of past studies have examined various aspects of tropical cyclone activity in the South Pacific basin, a review that consolidates those studies with new information is essential. In this chapter, we first examine tropical cyclone data quality for the South Pacific basin and then review the robustness of the relationship between South Pacific tropical cyclones and drivers of natural climate variability. Note that an understanding of the limitations of the data quality is important to determine the extent of natural climate variability and signatures—if any—of human-induced climate change on tropical cyclones. We then examine the influence of climate change on tropical cyclones using up-to-date historical observations and climate model projections. © Springer Nature Switzerland AG 2020.

A Survey on Behavioral Pattern Mining from Sensor Data in Internet of Things

  • Authors: Rashid, Md Mamunur , Kamruzzaman, Joarder , Hassan, Mohammad , Shahriar Shafin, Sakib , Bhuiyan, Md Zakirul
  • Date: 2020
  • Type: Text , Journal article , Article
  • Relation: IEEE Access Vol. 8, no. (2020), p. 33318-33341
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  • Description: The deployment of large-scale wireless sensor networks (WSNs) for the Internet of Things (IoT) applications is increasing day-by-day, especially with the emergence of smart city services. The sensor data streams generated from these applications are largely dynamic, heterogeneous, and often geographically distributed over large areas. For high-value use in business, industry and services, these data streams must be mined to extract insightful knowledge, such as about monitoring (e.g., discovering certain behaviors over a deployed area) or network diagnostics (e.g., predicting faulty sensor nodes). However, due to the inherent constraints of sensor networks and application requirements, traditional data mining techniques cannot be directly used to mine IoT data streams efficiently and accurately in real-time. In the last decade, a number of works have been reported in the literature proposing behavioral pattern mining algorithms for sensor networks. This paper presents the technical challenges that need to be considered for mining sensor data. It then provides a thorough review of the mining techniques proposed in the recent literature to mine behavioral patterns from sensor data in IoT, and their characteristics and differences are highlighted and compared. We also propose a behavioral pattern mining framework for IoT and discuss possible future research directions in this area. © 2013 IEEE.

An enhancement to the spatial pyramid matching for image classification and retrieval

  • Authors: Karmakar, Priyabrata , Teng, Shyh , Lu, Guojun , Zhang, Dengsheng
  • Date: 2020
  • Type: Text , Journal article , Article
  • Relation: IEEE Access Vol. 8, no. (2020), p. 22463-22472
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  • Description: Spatial pyramid matching (SPM) is one of the widely used methods to incorporate spatial information into the image representation. Despite its effectiveness, the traditional SPM is not rotation invariant. A rotation invariant SPM has been proposed in the literature but it has many limitations regarding the effectiveness. In this paper, we investigate how to make SPM robust to rotation by addressing those limitations. In an SPM framework, an image is divided into an increasing number of partitions at different pyramid levels. In this paper, our main focus is on how to partition images in such a way that the resulting structure can deal with image-level rotations. To do that, we investigate three concentric ring partitioning schemes. Apart from image partitioning, another important component of the SPM framework is a weight function. To apportion the contribution of each pyramid level to the final matching between two images, the weight function is needed. In this paper, we propose a new weight function which is suitable for the rotation-invariant SPM structure. Experiments based on image classification and retrieval are performed on five image databases. The detailed result analysis shows that we are successful in enhancing the effectiveness of SPM for image classification and retrieval. © 2013 IEEE.

Anxiety and depression after a cardiac event : prevalence and predictors

  • Authors: Murphy, Barbara , Le Grande, Michael , Alvarenga, Marlies , Worcester, Marian , Jackson, Alun
  • Date: 2020
  • Type: Text , Journal article , Article
  • Relation: Frontiers in Psychology Vol. 10, no. (2020), p.
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  • Description: Introduction: Patients who are anxious or depressed after an acute cardiac event are at increased risk of a subsequent event and premature death. It is therefore important to identify these patients early in order to initiate supportive or even preventive measures. In the present study, we report on the prevalence of anxiety and depression during the first 12 months after an acute cardiac event, and the patient characteristics predictive of increased anxiety and depression risk in early and late convalescence. Methods: We recruited a sample of 911 patients with acute myocardial infarction (AMI), acute coronary syndrome (ACS), and/or unstable angina (UA), and/or undergoing coronary artery bypass graft surgery (CABGS). Patients completed the Hospital Anxiety and Depression Scale (HADS) close to the time of their event, and again during early (2–4 months post-event) and late (6–12 months post-event) convalescence. Using HADS-A and HADS-D cut-offs of 8+, prevalence rates for anxiety, depression, and comorbid anxiety and depression were determined for each timepoint. Chi-square tests and odds ratios were used to identify baseline patient characteristics associated with increased anxiety and depression risk over 12 months. Results: Anxiety rates were 43, 28, and 27% at the time of the event, early, and late convalescence. Depression rates were 22, 17, and 15%, respectively. Factors consistently associated with increased anxiety and depression risk were history of depression, financial strain, poor self-rated health, low socioeconomic status, younger age (<55 years), and smoking. Obesity, diabetes, and social isolation (living alone or being unpartnered) were identified as important albeit less significant risk factors. Neither sex nor event type were predictive of anxiety or depression. Conclusion: This large patient sample provided the opportunity to identify rates of anxiety and depression during the 12 months after a cardiac event and key patient characteristics for increased risk. These risk factors are easily identifiable at the time of the event, and could be used to guide the targeting of support programs for patients at risk. © Copyright © 2020 Murphy, Le Grande, Alvarenga, Worcester and Jackson.

Application of thermal fragmentation in Australian hard rock underground narrow-vein mining

  • Authors: Drake, Bradley , Koroznikova, Larissa , Tuck, Michael , Durkin, Steve
  • Date: 2020
  • Type: Text , Journal article , Article
  • Relation: Mining, Metallurgy and Exploration Vol. 37, no. 1 (2020), p. 219-229
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  • Description: This paper presents the results from the investigation of the application of thermal fragmentation in Australian hard rock underground narrow-vein mining. Two geologically similar samples from an underground narrow-vein hard rock gold mine were collected to obtain a measure of the technology’s ability to recover ore by the creation of large thermal openings to assess the applicability of the thermal method. Particle size distribution showed a higher generation of fine product, − 2 mm, by thermal fragmentation compared with selective blasting by 31%. The Bond work index for thermal ore (12.62 kWh/t) is half to that of the blasted ore value (25.32 kWh/t). The average grindability obtained for the thermal ore sample was greater than the blasted sample by a factor of 2.44, a higher value indicating a decrease in the energy required to grind. The thermal fragmentation method generates product with higher dissolution of gold in cyanide, by 14% for the − 9.5 + 2 mm size fraction samples. Additionally, the thermal fragmentation results in higher production of − 9.5 + 2 mm material by 15 % compared with selective blasting. © 2019, Society for Mining, Metallurgy & Exploration Inc.

Audit education in a socialist oriented market economy – the case of Vietnam

  • Authors: Dang, Ky
  • Date: 2020
  • Type: Text , Thesis , PhD
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  • Description: The objective of the research project is to contribute to the understanding of the auditing profession in Vietnam. In particular, it provides information on the challenges facing auditors in an emerging economy where economic transformation is in progress and where auditing, as a profession, is under development. Auditors operate in an environment of conflicting priorities where they must maintain independence and objectivity in discharging their responsibilities to stakeholders and society. In Vietnam, the audit profession only came into existence in 1986 when the country embarked on its new economic model. Whilst studies have been conducted on the status of current accounting practice in Vietnam, studies regarding the audit profession have been limited. In this research project an examination of the issues affecting audit quality in Vietnam are investigated and suggestions for changes to address the deficiencies are made. In particular, the project focuses on the relevance and appropriateness of the education of auditors. A national survey of accountants, auditors and accounting academics in Vietnam was undertaken. The survey results indicate that in Vietnam there are deficiencies in audit practices over and above those commonly observed in other countries. These deficiencies are the result of the unique history of Vietnam, the current stage of economic development and the education system for auditors. From an auditing perspective, the slow adaptation of the education system to the new economic environment is having negative effects on accounting graduates and their employment prospects. Although inadequate training was identified as the single most important factor affecting audit quality, the ineffective enforcement regime was also a contributing factor. This research project indicates that there is a need for an overhaul of the current education system in Vietnam and for universities to develop an accounting and auditing curriculum that meets the needs of employers while complying with government’s education objectives and international standards of auditing and accounting.
  • Description: Doctor of Philosophy

Biodiesels from three feedstock : The effect of graphene oxide (GO) nanoparticles diesel engine parameters fuelled with biodiesel

  • Authors: Hoseini, Seyed , Najafi, Gholamhassan , Ghobadian, Barat , Ebadi, Mohammad , Mamat, Rizalman , Yusaf, Talal
  • Date: 2020
  • Type: Text , Journal article
  • Relation: Renewable Energy Vol. 145, no. (2020), p. 190-201
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  • Description: Physicochemical characteristics of three type biodiesel feedstock and diesel engine parameters fuelled with graphene oxide (GO) nanoparticles addition in diesel/biodiesel blends have been investigated. Three types of oilseeds, namely Evening primrose (Oenothera lamarckiana), the fruit of Tree of heaven (Ailanthus altissima) and Camelina (Camelina sativa), were selected as suitable resources for Iran. The result showed that the Tree of heaven contains 38% oil which is higher than the Evening primrose (26%) and Camelina (29%). Physicochemical properties of the oils showed that the viscosity of the Camelina oilseeds was less than the Tree of heaven oilseeds and Evening primrose oilseeds. Therefore, in terms of viscosity, the Camelina oilseeds is preferable. Experimental results showed that the biodiesel from all three types of oilseeds are consistent with the ASTM biodiesel standards. However, Camelina biodiesel has better physicochemical properties than another feedstock. Therefore, biodiesel of Camelina oil can be an appropriate alternative to diesel fuels in Iran. Performance and emission parameters of diesel engine fuelled with graphene oxide (GO) nanoparticles addition in three biodiesel resources compared with diesel. A reduction in UHCs, CO, and BSFC with a penalty of increased NOx emissions was realized with all graphene oxide (GO) nanoparticles addition in diesel/biodiesel blends. Also, with Camelina biodiesel, the power increased.

Canonical dual finite element method for solving nonconvex mechanics and topology optimization problems

Climate change scenarios and projections for the pacific

  • Authors: Chand, Savin
  • Date: 2020
  • Type: Text , Book chapter , Book Chapter
  • Relation: Springer Climate 3 p. 171-199
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  • Description: Small island countries in the Pacific have characteristics which enhance their vulnerability and reduce their resilience to the effects of climate change, sea-level rise and extreme events. Over the past decade, a number of studies have been undertaken to improve our understanding of climate variability and change in the Pacific. This chapter provides an overview of those studies and discusses possible challenges associated with climate model projections for the small island countries in the Pacific. © Springer Nature Switzerland AG 2020.

Climate-mediated changes to grassland structure determine habitat suitability for the critically endangered plains-wanderer (pedionomus torquatus)

  • Authors: Antos, Mark , Schultz, Nick
  • Date: 2020
  • Type: Text , Journal article , Article
  • Relation: Emu Vol. 120, no. 1 (2020), p. 2-10
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  • Description: The critically endangered and iconic plains-wanderer (Pedionomus torquatus) is phylogenetically distinct and endemic to south eastern Australia, and is a high conservation priority. Furthermore, it relies on critically-endangered native grasslands for its survival, which vary temporally in structure and hence do not always provide suitable habitat. To manage the remaining native grasslands appropriately, it is essential to understand the temporal and spatial dynamics of plains-wanderer habitat preferences. We monitored plains-wanderers and habitat measurements for nine years to link habitat preferences to specific elements of grassland structure. We also observed habitat selection by plains-wanderers at two spatial scales–sites (paddocks) and at microsites (immediate vicinity of the birds). The plains-wanderer population declined rapidly after a dramatic increase in native grass cover in 2011, and recovery of the population since then has been slow. In 2015/16, plains-wanderers were generally encountered at microsites with higher bare ground and cryptogam cover. However, at the site scale, paddocks with plains-wanderers had similar cover of native grass and bare ground than those without plains-wanderers. The results suggest that observation of highly-localised habitat components alone may mask aspects of the habitat selection occurring at larger spatial scales. Plains-wanderers may require areas of denser perennial grass for nesting and shelter, as well as access to the open areas where they are commonly encountered. We discuss how private land used for commercial grazing may be crucial to plains-wanderer conservation. The results also prompt consideration of how we measure and interpret habitat selection for grassland birds globally. © 2019, © 2019 BirdLife Australia.

Compassion satisfaction and compassion fatigue in Australian emergency nurses : a descriptive cross-sectional study

  • Authors: O'Callaghan, Erin , Lam, Louisa , Cant, Robyn , Moss, Cheryle
  • Date: 2020
  • Type: Text , Journal article , Article
  • Relation: International Emergency Nursing Vol. 48, no. (Jan 2020), p. 8
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  • Description: Introduction: Emergency nurses are at risk of compassion fatigue. Compassion fatigue caused by exposure to suffering may compromise the individual's personal wellbeing and reduce work efficiency. Methods: A quantitative cross-sectional survey with open responses was conducted using the Professional Quality of Life: Compassion Satisfaction and Compassion Fatigue (ProQOL) scale and open-ended questions. Responses from a convenience sample of 86 nurses from two hospital emergency departments in Victoria, Australia, were analysed. Results: The median score for Compassion Satisfaction was 78% with all nurses reporting average to high scores. Most had average levels of Compassion Fatigue: Burnout median score was 53% and Secondary Traumatic Stress median score 49%. No statistically significant correlation was found between scales nor with influencing demographic characteristics. A qualification in emergency nursing was predictive of Compassion Satisfaction. Six descriptive job-associated factors contributed to nurses' stress: human resources, the organisation, job-specific components, patient mix and professional and personal components. Conclusion/s: Average to high levels of Compassion Satisfaction and low to average levels of Compassion Fatigue were found in emergency nurses. Issues contributing to stress were work and role related. An understanding of these stressors may help nurses and nurse managers to ameliorate emergency nurses' levels of stress and help limit staff burnout.

DEFINE : friendship detection based on node enhancement

  • Authors: Pan, Hanxiao , Guo, Teng , Bedru, Hayat , Qing, Qing , Zhang, Dongyu , Xia, Feng
  • Date: 2020
  • Type: Text , Conference paper , Conference Paper
  • Relation: 31st Australasian Database Conference, ADC 2019 Vol. 12008 LNCS, p. 81-92
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  • Description: Network representation learning (NRL) is a matter of importance to a variety of tasks such as link prediction. Learning low-dimensional vector representations for node enhancement based on nodes attributes and network structures can improve link prediction performance. Node attributes are important factors in forming networks, like psychological factors and appearance features affecting friendship networks. However, little to no work has detected friendship using the NRL technique, which combines students’ psychological features and perceived traits based on facial appearance. In this paper, we propose a framework named DEFINE (No enhancement based r e dship D tection) to detect students’ friend relationships, which combines with students’ psychological factors and facial perception information. To detect friend relationships accurately, DEFINE uses the NRL technique, which considers network structure and the additional attributes information for nodes. DEFINE transforms them into low-dimensional vector spaces while preserving the inherent properties of the friendship network. Experimental results on real-world friendship network datasets illustrate that DEFINE outperforms other state-of-art methods. © 2020, Springer Nature Switzerland AG.
  • Description: E1

Depth sequence coding with hierarchical partitioning and spatial-domain quantization

  • Authors: Shahriyar, Shampa , Murshed, Manzur , Ali, Mortuza , Paul, Manoranjan
  • Date: 2020
  • Type: Text , Journal article , Article
  • Relation: IEEE Transactions on Circuits and Systems for Video Technology Vol. 30, no. 3 (2020), p. 835-849
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  • Description: Depth coding in 3D-HEVC deforms object shapes due to block-level edge-approximation and lacks efficient techniques to exploit the statistical redundancy, due to the frame-level clustering tendency in depth data, for higher coding gain at near-lossless quality. This paper presents a standalone mono-view depth sequence coder, which preserves edges implicitly by limiting quantization to the spatial-domain and exploits the frame-level clustering tendency efficiently with a novel binary tree-based decomposition (BTBD) technique. The BTBD can exploit the statistical redundancy in frame-level syntax, motion components, and residuals efficiently with fewer block-level prediction/coding modes and simpler context modeling for context-adaptive arithmetic coding. Compared with the depth coder in 3D-HEVC, the proposed one has achieved significantly lower bitrate at lossless to near-lossless quality range for mono-view coding and rendered superior quality synthetic views from the depth maps, compressed at the same bitrate, and the corresponding texture frames. © 1991-2012 IEEE.

Development of pedotransfer functions by machine learning for prediction of soil electrical conductivity and organic carbon content

  • Authors: Benke, Kurt , Norng, Sorn , Robinson, Nathan , Chia, K. , Rees, David , Hopley, J.
  • Date: 2020
  • Type: Text , Journal article , Article
  • Relation: Geoderma Vol. 366, no. (2020)
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  • Description: The pedotransfer function is a mathematical model used to convert direct soil measurements into known and unknown soil properties. It provides information for modelling and simulation in soil research, hydrology, environmental science and climate change impacts, including investigating the carbon cycle and the exchange of carbon between soils and the atmosphere to support carbon farming. In particular, the pedotransfer function can provide input parameters for landscape design, soil quality assessment and economic optimisation. The objective of the study was to investigate the feasibility of using a generalised pedotransfer function derived with a machine learning method to predict soil electrical conductivity (EC) and soil organic carbon content (OC) for different regional locations in the state of Victoria, Australia. This strategy supports a unified approach to the interpolation and population of a single regional soils database, in contrast to a range of pedotransfer functions derived from local databases with measurement sets that may have limited transferability. The pedotransfer function generation was based on a machine learning algorithm incorporating the Generalized Linear Mixed Model with interactions and nested terms, with Residual Maximum Likelihood estimation, and a predictor-frequency ranking system with step-wise reduction of predictors to evaluate the predictive errors in reduced models. The source of the data was the Victorian Soil Information System (VSIS), which is a database administered for soil information and mapping purposes. The database contains soil measurements and information from locations across Victoria and is a repository of historical data, including monitoring studies. In total, data from 93 projects were available for inputs to modelling and analysis, with 5158 samples used to derive predictors for EC and 1954 samples used to derive predictors for OC. Over 500 models were tested by systematically reducing the number of predictors from the full model. Five-fold cross-validation was used for estimation of model mean-squared prediction error (MSPE) and mean-absolute percentage error (MAPE). The results were statistically significant with only a gradual reduction in error for the top-ranked 50 models. The prediction errors (MSPE and MAPE) of the top ranked model for EC are 0.686 and 0.635, and 0.413 and 0.474 for OC respectively. The four most frequently occurring predictors both for EC and OC prediction across the full set of models were found to be soil depth, pH, particle size distribution and geomorphological mapping unit. The possible advantages and disadvantages of this approach were discussed with respect to other machine learning approaches. © 2020 Elsevier B.V.

Direct contact ultrasound for fouling control and flux enhancement in air-gap membrane distillation

  • Authors: Naji, Osamah , Al-juboori, Raed , Bowtell, Les , Alpatova, Alla , Ghaffour, Noreddine
  • Date: 2020
  • Type: Text , Journal article , Article
  • Relation: Ultrasonics Sonochemistry Vol. 61, no. (2020), p.
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  • Description: Air Gap Membrane distillation (AGMD) is a thermally driven separation process capable of treating challenging water types, but its low productivity is a major drawback. Membrane fouling is a common problem in many membrane treatment systems, which exacerbates AGMD's low overall productivity. In this study, we investigated the direct application of low-power ultrasound (8–23 W), as an in-line cleaning and performance boosting technique for AGMD. Two different highly saline feedwaters, namely natural groundwater (3970 μS/cm) and RO reject stream water (12760 μS/cm) were treated using Polytetrafluoroethylene (PTFE) and polyvinylidene fluoride (PVDF) membranes. Theoretical calculations and experimental investigations are presented, showing that the applied ultrasonic power range only produced acoustic streaming effects that enhanced cleaning and mass transfer. Attenuated Total Reflection Fourier-Transform Infrared Spectroscopy (ATR FT-IR) analysis showed that ultrasound was capable of effectively removing silica and calcium scaling. Ultrasound application on a fouled membrane resulted in a 100% increase in the permeate flux. Cleaning effects accounted for around 30–50% of this increase and the remainder was attributed to mass transfer improvements. Contaminant rejection percentages were consistently high for all treatments (>99%), indicating that ultrasound did not deteriorate the membrane structure. Scanning Electron Microscopy (SEM) analysis of the membrane surface was used to confirm this observation. The images of the membrane surface demonstrated that ultrasound successfully cleaned the previously fouled membrane, with no signs of structural damage. The results of this study highlight the efficient and effective application of direct low power ultrasound for improving AGMD performance. © 2019 Elsevier B.V.

Directional metric pseudo subregularity of set-valued mappings: a general model

Dynamically recommending repositories for health data : a machine learning model

  • Authors: Uddin, Ashraf , Stranieri, Andrew , Gondal, Iqbal , Balasubramanian, Venkicopyright
  • Date: 2020
  • Type: Text , Conference proceedings , Conference Paper
  • Relation: 2020 Australasian Computer Science Week Multiconference, ACSW 2020
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  • Description: Recently, a wide range of digital health record repositories has emerged. These include Electronic Health record managed by the government, Electronic Medical Record (EMR) managed by healthcare providers, Personal Health Record (PHR) managed directly by the patient and new Blockchain-based systems mainly managed by technologies. Health record repositories differ from one another on the level of security, privacy, and quality of services (QoS) they provide. Health data stored in these repositories also varies from patient to patient in sensitivity, and significance depending on medical, personal preference, and other factors. Decisions regarding which digital record repository is most appropriate for the storage of each data item at every point in time are complex and nuanced. The challenges are exacerbated with health data continuously streamed from wearable sensors. In this paper, we propose a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The model maps health data to be stored in the repositories. The mapping between health data features and characteristics of each repository is learned using a machine learning-based classifier mediated through clinical rules. Evaluation results demonstrate the model's feasibility. © 2020 ACM.
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Emergency warning messages dissemination in vehicular social networks: a trust based scheme

  • Authors: Ullah, Noor , Kong, Xiangjie , Ning, Zhaolong , Tolba, Amr , Alrashoud, Mubarak , Xia, Feng
  • Date: 2020
  • Type: Text , Journal article , Article
  • Relation: Vehicular Communications Vol. 22, (2020)
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  • Description: To ensure users' safety on the road, a plethora of dissemination schemes for Emergency Warning Messages (EWMs) have been proposed in vehicular networks. However, the issue of false alarms triggered by malicious users still poses serious challenges, such as disruption of vehicular traffic especially on highways leading to precarious effects. This paper proposes a novel Trust based Dissemination Scheme (TDS) for EWMs in Vehicular Social Networks (VSNs) to solve the aforementioned issue. To ensure the authenticity of EWMs, we exploit the user-post credibility network for identifying true and false alarms. Moreover, we develop a reputation mechanism by calculating a trust-score for each node based on its social-utility, behavior, and contribution in the network. We utilize the hybrid architecture of VSNs by employing social-groups based dissemination in Vehicle-to-Infrastructure (V2I) mode, whereas nodes' friendship-network in Vehicle-to-Vehicle (V2V) mode. We analyze the proposed scheme for accuracy by extensive simulations under varying malicious nodes ratio in the network. Furthermore, we compare the efficiency of TDS with state-of-the-art dissemination schemes in VSNs for delivery ratio, transmission delay, number of transmissions, and hop-count. The experimental results validate the significant efficacy of TDS in accuracy and aforementioned network parameters. © 2019 Elsevier Inc.