Risk assessment of SARS-CoV-2 in Antarctic wildlife
- Barbosa, Andres, Varsani, Arvind, Morandini, Virginia, Grimaldi, Wray, Vanstreels, Ralph, Diaz, Julia, Boulinier, Thierry, Dewar, Meagan, González-Acuña, Daniel, Gray, Rachael, McMahon, Clive, Miller, Gary, Power, Michelle, Gamble, Amandine, Wille, Michelle
- Authors: Barbosa, Andres , Varsani, Arvind , Morandini, Virginia , Grimaldi, Wray , Vanstreels, Ralph , Diaz, Julia , Boulinier, Thierry , Dewar, Meagan , González-Acuña, Daniel , Gray, Rachael , McMahon, Clive , Miller, Gary , Power, Michelle , Gamble, Amandine , Wille, Michelle
- Date: 2021
- Type: Text , Journal article
- Relation: Science of the Total Environment Vol. 755, no. 2 (2021), p. 1-8
- Full Text:
- Reviewed:
- Description: The coronavirus disease 2019 (COVID-19) pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This pathogen has spread rapidly across the world, causing high numbers of deaths and significant social and economic impacts. SARS-CoV-2 is a novel coronavirus with a suggested zoonotic origin with the potential for cross-species transmission among animals. Antarctica can be considered the only continent free of SARS-CoV-2. Therefore, concerns have been expressed regarding the potential human introduction of this virus to the continent through the activities of research or tourism to minimise the effects on human health, and the potential for virus transmission to Antarctic wildlife. We assess the reverse-zoonotic transmission risk to Antarctic wildlife by considering the available information on host susceptibility, dynamics of the infection in humans, and contact interactions between humans and Antarctic wildlife. The environmental conditions in Antarctica seem to be favourable for the virus stability. Indoor spaces such as those at research stations, research vessels or tourist cruise ships could allow for more transmission among humans and depending on their movements between different locations the virus could be spread across the continent. Among Antarctic wildlife previous in silico analyses suggested that cetaceans are at greater risk of infection whereas seals and birds appear to be at a low infection risk. However, caution needed until further research is carried out and consequently, the precautionary principle should be applied. Field researchers handling animals are identified as the human group posing the highest risk of transmission to animals while tourists and other personnel pose a significant risk only when in close proximity (< 5 m) to Antarctic fauna. We highlight measures to reduce the risk as well as identify of knowledge gaps related to this issue. © 2020 The Authors
- Authors: Barbosa, Andres , Varsani, Arvind , Morandini, Virginia , Grimaldi, Wray , Vanstreels, Ralph , Diaz, Julia , Boulinier, Thierry , Dewar, Meagan , González-Acuña, Daniel , Gray, Rachael , McMahon, Clive , Miller, Gary , Power, Michelle , Gamble, Amandine , Wille, Michelle
- Date: 2021
- Type: Text , Journal article
- Relation: Science of the Total Environment Vol. 755, no. 2 (2021), p. 1-8
- Full Text:
- Reviewed:
- Description: The coronavirus disease 2019 (COVID-19) pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This pathogen has spread rapidly across the world, causing high numbers of deaths and significant social and economic impacts. SARS-CoV-2 is a novel coronavirus with a suggested zoonotic origin with the potential for cross-species transmission among animals. Antarctica can be considered the only continent free of SARS-CoV-2. Therefore, concerns have been expressed regarding the potential human introduction of this virus to the continent through the activities of research or tourism to minimise the effects on human health, and the potential for virus transmission to Antarctic wildlife. We assess the reverse-zoonotic transmission risk to Antarctic wildlife by considering the available information on host susceptibility, dynamics of the infection in humans, and contact interactions between humans and Antarctic wildlife. The environmental conditions in Antarctica seem to be favourable for the virus stability. Indoor spaces such as those at research stations, research vessels or tourist cruise ships could allow for more transmission among humans and depending on their movements between different locations the virus could be spread across the continent. Among Antarctic wildlife previous in silico analyses suggested that cetaceans are at greater risk of infection whereas seals and birds appear to be at a low infection risk. However, caution needed until further research is carried out and consequently, the precautionary principle should be applied. Field researchers handling animals are identified as the human group posing the highest risk of transmission to animals while tourists and other personnel pose a significant risk only when in close proximity (< 5 m) to Antarctic fauna. We highlight measures to reduce the risk as well as identify of knowledge gaps related to this issue. © 2020 The Authors
A continuous flow elevator to lift ore vertically for deep mine haulage using a cable disc elevator
- Authors: Webb, Colin
- Date: 2020
- Type: Text , Thesis , PhD
- Full Text:
- Description: Vertical continuous ore haulage with elevators in mining for deep haulage is virtually non-existent. In this, research investigations concentrated on a cable disc elevator. The problem of using a cable disc elevator is the friction between the elevator fixed tube and the moving ore on the disc. This research establishes the friction forces existing as the elevator cable and discs are elevated up a stationary tube. Then the focus is to find a way to eliminate that friction. The method involved developing three test rigs: Test Rig 1 measures static friction with the ore placed on a disc in a tube mounted on load cells to measure the resistance with the ore on the disc lifted by a counterweight. This is relevant for an elevator that has stopped under load. Test Rig 2 measures the dynamic friction in an operational 5-inch elevator with the tube on the lifting side held stationary by load cells when the cable discs are lifting the ore. Test Rig 3 eliminates friction in the lifting tube by using a pipe conveyor that travels vertically at the same speed as the cable disc elevator to contain the ore on the cable disc elevator. The cable disc elevator does all the ore lifting. The research generated results for static and dynamic friction for gravel, granite and coal. Cable tension required for ore lift of 1000 metres and the maximum hoisting distance for some existing cables are calculated. Implications of this research are that the cable disc elevator has the potential to haul from depths greater than existing elevators, has a small footprint in a mine, and with some further development could eliminate the need for truck haulage in open cut and underground mining from the mine.
- Description: Doctor of Philosophy
- Authors: Webb, Colin
- Date: 2020
- Type: Text , Thesis , PhD
- Full Text:
- Description: Vertical continuous ore haulage with elevators in mining for deep haulage is virtually non-existent. In this, research investigations concentrated on a cable disc elevator. The problem of using a cable disc elevator is the friction between the elevator fixed tube and the moving ore on the disc. This research establishes the friction forces existing as the elevator cable and discs are elevated up a stationary tube. Then the focus is to find a way to eliminate that friction. The method involved developing three test rigs: Test Rig 1 measures static friction with the ore placed on a disc in a tube mounted on load cells to measure the resistance with the ore on the disc lifted by a counterweight. This is relevant for an elevator that has stopped under load. Test Rig 2 measures the dynamic friction in an operational 5-inch elevator with the tube on the lifting side held stationary by load cells when the cable discs are lifting the ore. Test Rig 3 eliminates friction in the lifting tube by using a pipe conveyor that travels vertically at the same speed as the cable disc elevator to contain the ore on the cable disc elevator. The cable disc elevator does all the ore lifting. The research generated results for static and dynamic friction for gravel, granite and coal. Cable tension required for ore lift of 1000 metres and the maximum hoisting distance for some existing cables are calculated. Implications of this research are that the cable disc elevator has the potential to haul from depths greater than existing elevators, has a small footprint in a mine, and with some further development could eliminate the need for truck haulage in open cut and underground mining from the mine.
- Description: Doctor of Philosophy
A DNA toolbox for non-invasive genetic studies of sambar deer (Rusa unicolor)
- Davies, Chris, Wright, Wendy, Wedrowicz, Faye, Hogan, Fiona
- Authors: Davies, Chris , Wright, Wendy , Wedrowicz, Faye , Hogan, Fiona
- Date: 2020
- Type: Text , Journal article
- Relation: Australian Mammalogy Vol. 42, no. 1 (2020), p. 58-66
- Full Text:
- Reviewed:
- 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.
- Authors: Davies, Chris , Wright, Wendy , Wedrowicz, Faye , Hogan, Fiona
- Date: 2020
- Type: Text , Journal article
- Relation: Australian Mammalogy Vol. 42, no. 1 (2020), p. 58-66
- Full Text:
- Reviewed:
- 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 good sheep run. Letters from New South Wales in Scottish newspapers between 1820 and 1850 with potential to influence decisions on emigration
- Authors: Hannaford, Graham
- Date: 2020
- Type: Text , Thesis , PhD
- Full Text:
- Description: The primary aim of this thesis is to contribute to ongoing historical research into migration to and settlement in Australia by Scots. It achieves this by identifying and examining letters sent from the colonies in New South Wales which were printed in historic Scottish newspapers between 1820 and 1850. In examining the material, this thesis argues that the letters had potential to influence emigration decisions by Scots. The study shows some of the ways in which New South Wales was reported in the Scottish press and compares those reports with conditions in Scotland at the time. The comparisons and analyses of the letters, with consideration of their authors and likely readers as well as the newspapers in which they were printed demonstrate that the letters did have potential to influence emigration decisions. Its particular contribution to knowledge arises from demonstrating how mostly private letters which became publicly available through publication in newspapers had potential to influence emigrants’ decisions about moving to Australia. Rather than claiming direct evidence of the publication of particular letters as having influenced emigration, it shows how reporting of conditions in Australia when set into a context of contemporary events and conditions in Scotland had potential to influence decisions. It is grounded in the body of historical research about colonial Australia and sits within this Australian historiographical context. Given the motivations and attractions of Scots to colonial Australia this thesis also engages with techniques and theoretical approaches associated with Scottish diaspora studies, an area of research that often emphasises other Scottish migration patterns to Canada, New Zealand and the USA. When considered together both of these historiographical approaches lend themselves to primary source material analysis and a methodological approach that this doctoral study uses to examine the motivations of Scots who migrated to colonial Australia.
- Description: Doctor of Philosophy
- Authors: Hannaford, Graham
- Date: 2020
- Type: Text , Thesis , PhD
- Full Text:
- Description: The primary aim of this thesis is to contribute to ongoing historical research into migration to and settlement in Australia by Scots. It achieves this by identifying and examining letters sent from the colonies in New South Wales which were printed in historic Scottish newspapers between 1820 and 1850. In examining the material, this thesis argues that the letters had potential to influence emigration decisions by Scots. The study shows some of the ways in which New South Wales was reported in the Scottish press and compares those reports with conditions in Scotland at the time. The comparisons and analyses of the letters, with consideration of their authors and likely readers as well as the newspapers in which they were printed demonstrate that the letters did have potential to influence emigration decisions. Its particular contribution to knowledge arises from demonstrating how mostly private letters which became publicly available through publication in newspapers had potential to influence emigrants’ decisions about moving to Australia. Rather than claiming direct evidence of the publication of particular letters as having influenced emigration, it shows how reporting of conditions in Australia when set into a context of contemporary events and conditions in Scotland had potential to influence decisions. It is grounded in the body of historical research about colonial Australia and sits within this Australian historiographical context. Given the motivations and attractions of Scots to colonial Australia this thesis also engages with techniques and theoretical approaches associated with Scottish diaspora studies, an area of research that often emphasises other Scottish migration patterns to Canada, New Zealand and the USA. When considered together both of these historiographical approaches lend themselves to primary source material analysis and a methodological approach that this doctoral study uses to examine the motivations of Scots who migrated to colonial Australia.
- Description: Doctor of Philosophy
A guide to the short, long and circular RNAs in hypertension and cardiovascular disease
- Prestes, Priscilla, Maier, Michelle, Woods, Bradley, Charchar, Fadi
- Authors: Prestes, Priscilla , Maier, Michelle , Woods, Bradley , Charchar, Fadi
- Date: 2020
- Type: Text , Journal article , Review
- Relation: International Journal of Molecular Sciences Vol. 21, no. 10 (2020)
- Full Text:
- Reviewed:
- Description: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in adults in developed countries. CVD encompasses many diseased states, including hypertension, coronary artery disease and atherosclerosis. Studies in animal models and human studies have elucidated the contribution of many genetic factors, including non-coding RNAs. Non-coding RNAs are RNAs not translated into protein, involved in gene expression regulation post-transcriptionally and implicated in CVD. Of these, circular RNAs (circRNAs) and microRNAs are relevant. CircRNAs are created by the back-splicing of pre-messenger RNA and have been underexplored as contributors to CVD. These circRNAs may also act as biomarkers of human disease, as they can be extracted from whole blood, plasma, saliva and seminal fluid. CircRNAs have recently been implicated in various disease processes, including hypertension and other cardiovascular disease. This review article will explore the promising and emerging roles of circRNAs as potential biomarkers and therapeutic targets in CVD, in particular hypertension. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Prestes, Priscilla , Maier, Michelle , Woods, Bradley , Charchar, Fadi
- Date: 2020
- Type: Text , Journal article , Review
- Relation: International Journal of Molecular Sciences Vol. 21, no. 10 (2020)
- Full Text:
- Reviewed:
- Description: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in adults in developed countries. CVD encompasses many diseased states, including hypertension, coronary artery disease and atherosclerosis. Studies in animal models and human studies have elucidated the contribution of many genetic factors, including non-coding RNAs. Non-coding RNAs are RNAs not translated into protein, involved in gene expression regulation post-transcriptionally and implicated in CVD. Of these, circular RNAs (circRNAs) and microRNAs are relevant. CircRNAs are created by the back-splicing of pre-messenger RNA and have been underexplored as contributors to CVD. These circRNAs may also act as biomarkers of human disease, as they can be extracted from whole blood, plasma, saliva and seminal fluid. CircRNAs have recently been implicated in various disease processes, including hypertension and other cardiovascular disease. This review article will explore the promising and emerging roles of circRNAs as potential biomarkers and therapeutic targets in CVD, in particular hypertension. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
A low-complexity equalizer for video broadcasting in cyber-physical social systems through handheld mobile devices
- Solyman, Ahmad, Attar, Hani, Khosravi, Mohammad, Menon, Varun, Jolfaei, Alireza, Balasubramanian, Venki, Selvaraj, Buvana, Tavallali, Pooya
- Authors: Solyman, Ahmad , Attar, Hani , Khosravi, Mohammad , Menon, Varun , Jolfaei, Alireza , Balasubramanian, Venki , Selvaraj, Buvana , Tavallali, Pooya
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 67591-67602
- Full Text:
- Reviewed:
- Description: In Digital Video Broadcasting-Handheld (DVB-H) devices for cyber-physical social systems, the Discrete Fractional Fourier Transform-Orthogonal Chirp Division Multiplexing (DFrFT-OCDM) has been suggested to enhance the performance over Orthogonal Frequency Division Multiplexing (OFDM) systems under time and frequency-selective fading channels. In this case, the need for equalizers like the Minimum Mean Square Error (MMSE) and Zero-Forcing (ZF) arises, though it is excessively complex due to the need for a matrix inversion, especially for DVB-H extensive symbol lengths. In this work, a low complexity equalizer, Least-Squares Minimal Residual (LSMR) algorithm, is used to solve the matrix inversion iteratively. The paper proposes the LSMR algorithm for linear and nonlinear equalizers with the simulation results, which indicate that the proposed equalizer has significant performance and reduced complexity over the classical MMSE equalizer and other low complexity equalizers, in time and frequency-selective fading channels. © 2013 IEEE.
- Authors: Solyman, Ahmad , Attar, Hani , Khosravi, Mohammad , Menon, Varun , Jolfaei, Alireza , Balasubramanian, Venki , Selvaraj, Buvana , Tavallali, Pooya
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 67591-67602
- Full Text:
- Reviewed:
- Description: In Digital Video Broadcasting-Handheld (DVB-H) devices for cyber-physical social systems, the Discrete Fractional Fourier Transform-Orthogonal Chirp Division Multiplexing (DFrFT-OCDM) has been suggested to enhance the performance over Orthogonal Frequency Division Multiplexing (OFDM) systems under time and frequency-selective fading channels. In this case, the need for equalizers like the Minimum Mean Square Error (MMSE) and Zero-Forcing (ZF) arises, though it is excessively complex due to the need for a matrix inversion, especially for DVB-H extensive symbol lengths. In this work, a low complexity equalizer, Least-Squares Minimal Residual (LSMR) algorithm, is used to solve the matrix inversion iteratively. The paper proposes the LSMR algorithm for linear and nonlinear equalizers with the simulation results, which indicate that the proposed equalizer has significant performance and reduced complexity over the classical MMSE equalizer and other low complexity equalizers, in time and frequency-selective fading channels. © 2013 IEEE.
A new data driven long-term solar yield analysis model of photovoltaic power plants
- Ray, Biplob, Shah, Rakibuzzaman, Islam, Md Rabiul, Islam, Syed
- Authors: Ray, Biplob , Shah, Rakibuzzaman , Islam, Md Rabiul , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 136223-136233
- Full Text:
- Reviewed:
- Description: Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV system) in Australia to obtain the trade-off between accuracy and efficacy. The historical dataset from 1990-2013 in Australian locations (e.g. North Queensland) are used to train the model. The model is developed using the combination of multivariate long and short-term memory (LSTM) and convolutional neural network (CNN). The proposed hybrid deep learning (LSTM-CNN) is compared with the existing neural network ensemble (NNE), random forest, statistical analysis, and artificial neural network (ANN) based techniques to assess the performance. The proposed model could be useful for generation planning and reserve estimation in power systems with high penetration of solar photovoltaics (PVs) or other renewable energy sources (RESs). © 2013 IEEE.
- Authors: Ray, Biplob , Shah, Rakibuzzaman , Islam, Md Rabiul , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 136223-136233
- Full Text:
- Reviewed:
- Description: Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV system) in Australia to obtain the trade-off between accuracy and efficacy. The historical dataset from 1990-2013 in Australian locations (e.g. North Queensland) are used to train the model. The model is developed using the combination of multivariate long and short-term memory (LSTM) and convolutional neural network (CNN). The proposed hybrid deep learning (LSTM-CNN) is compared with the existing neural network ensemble (NNE), random forest, statistical analysis, and artificial neural network (ANN) based techniques to assess the performance. The proposed model could be useful for generation planning and reserve estimation in power systems with high penetration of solar photovoltaics (PVs) or other renewable energy sources (RESs). © 2013 IEEE.
A pupil-positioning method based on the starburst model
- Yu, Pingping, Duan, Wenjie, Sun, Yi, Cao, Ning, Wang, Zhenzhou, Lu, Guojun
- Authors: Yu, Pingping , Duan, Wenjie , Sun, Yi , Cao, Ning , Wang, Zhenzhou , Lu, Guojun
- Date: 2020
- Type: Text , Journal article
- Relation: Cmc-Computers Materials & Continua Vol. 64, no. 2 (2020), p. 1199-1217
- Full Text:
- Reviewed:
- Description: Human eye detection has become an area of interest in the field of computer vision with an extensive range of applications in human-computer interaction, disease diagnosis, and psychological and physiological studies. Gaze-tracking systems are an important research topic in the human-computer interaction field. As one of the core modules of the head-mounted gaze-tracking system, pupil positioning affects the accuracy and stability of the system. By tracking eye movements to better locate the center of the pupil, this paper proposes a method for pupil positioning based on the starburst model. The method uses vertical and horizontal coordinate integral projections in the rectangular region of the human eye for accurate positioning and applies a linear interpolation method that is based on a circular model to the reflections in the human eye. In this paper, we propose a method for detecting the feature points of the pupil edge based on the starburst model, which clusters feature points and uses the RANdom SAmple Consensus (RANSAC) algorithm to perform ellipse fitting of the pupil edge to accurately locate the pupil center. Our experimental results show that the algorithm has higher precision, higher efficiency and more robustness than other algorithms and excellent accuracy even when the image of the pupil is incomplete.
- Description: Science and Technology Support Plan Project of Hebei Province (grant numbers 17210803D and 19273703D Science and Technology Spark Project of the Hebei Seismological Bureau (grant number DZ20180402056) Education Department of Hebei Province (grant number QN2018095) Polytechnic College of Hebei University of Science and Technology
- Authors: Yu, Pingping , Duan, Wenjie , Sun, Yi , Cao, Ning , Wang, Zhenzhou , Lu, Guojun
- Date: 2020
- Type: Text , Journal article
- Relation: Cmc-Computers Materials & Continua Vol. 64, no. 2 (2020), p. 1199-1217
- Full Text:
- Reviewed:
- Description: Human eye detection has become an area of interest in the field of computer vision with an extensive range of applications in human-computer interaction, disease diagnosis, and psychological and physiological studies. Gaze-tracking systems are an important research topic in the human-computer interaction field. As one of the core modules of the head-mounted gaze-tracking system, pupil positioning affects the accuracy and stability of the system. By tracking eye movements to better locate the center of the pupil, this paper proposes a method for pupil positioning based on the starburst model. The method uses vertical and horizontal coordinate integral projections in the rectangular region of the human eye for accurate positioning and applies a linear interpolation method that is based on a circular model to the reflections in the human eye. In this paper, we propose a method for detecting the feature points of the pupil edge based on the starburst model, which clusters feature points and uses the RANdom SAmple Consensus (RANSAC) algorithm to perform ellipse fitting of the pupil edge to accurately locate the pupil center. Our experimental results show that the algorithm has higher precision, higher efficiency and more robustness than other algorithms and excellent accuracy even when the image of the pupil is incomplete.
- Description: Science and Technology Support Plan Project of Hebei Province (grant numbers 17210803D and 19273703D Science and Technology Spark Project of the Hebei Seismological Bureau (grant number DZ20180402056) Education Department of Hebei Province (grant number QN2018095) Polytechnic College of Hebei University of Science and Technology
A robust forgery detection method for copy-move and splicing attacks in images
- Islam, Mohammad, Karmakar, Gour, Kamruzzaman, Joarder, Murshed, Manzur
- Authors: Islam, Mohammad , Karmakar, Gour , Kamruzzaman, Joarder , Murshed, Manzur
- Date: 2020
- Type: Text , Journal article
- Relation: Electronics Vol. 9, no. 9 (2020), p. 1-22
- Full Text:
- Reviewed:
- Description: Internet of Things (IoT) image sensors, social media, and smartphones generate huge volumes of digital images every day. Easy availability and usability of photo editing tools have made forgery attacks, primarily splicing and copy-move attacks, effortless, causing cybercrimes to be on the rise. While several models have been proposed in the literature for detecting these attacks, the robustness of those models has not been investigated when (i) a low number of tampered images are available for model building or (ii) images from IoT sensors are distorted due to image rotation or scaling caused by unwanted or unexpected changes in sensors' physical set-up. Moreover, further improvement in detection accuracy is needed for real-word security management systems. To address these limitations, in this paper, an innovative image forgery detection method has been proposed based on Discrete Cosine Transformation (DCT) and Local Binary Pattern (LBP) and a new feature extraction method using the mean operator. First, images are divided into non-overlapping fixed size blocks and 2D block DCT is applied to capture changes due to image forgery. Then LBP is applied to the magnitude of the DCT array to enhance forgery artifacts. Finally, the mean value of a particular cell across all LBP blocks is computed, which yields a fixed number of features and presents a more computationally efficient method. Using Support Vector Machine (SVM), the proposed method has been extensively tested on four well known publicly available gray scale and color image forgery datasets, and additionally on an IoT based image forgery dataset that we built. Experimental results reveal the superiority of our proposed method over recent state-of-the-art methods in terms of widely used performance metrics and computational time and demonstrate robustness against low availability of forged training samples.
- Description: This research was funded by Research Priority Area (RPA) scholarship of Federation University Australia.
- Authors: Islam, Mohammad , Karmakar, Gour , Kamruzzaman, Joarder , Murshed, Manzur
- Date: 2020
- Type: Text , Journal article
- Relation: Electronics Vol. 9, no. 9 (2020), p. 1-22
- Full Text:
- Reviewed:
- Description: Internet of Things (IoT) image sensors, social media, and smartphones generate huge volumes of digital images every day. Easy availability and usability of photo editing tools have made forgery attacks, primarily splicing and copy-move attacks, effortless, causing cybercrimes to be on the rise. While several models have been proposed in the literature for detecting these attacks, the robustness of those models has not been investigated when (i) a low number of tampered images are available for model building or (ii) images from IoT sensors are distorted due to image rotation or scaling caused by unwanted or unexpected changes in sensors' physical set-up. Moreover, further improvement in detection accuracy is needed for real-word security management systems. To address these limitations, in this paper, an innovative image forgery detection method has been proposed based on Discrete Cosine Transformation (DCT) and Local Binary Pattern (LBP) and a new feature extraction method using the mean operator. First, images are divided into non-overlapping fixed size blocks and 2D block DCT is applied to capture changes due to image forgery. Then LBP is applied to the magnitude of the DCT array to enhance forgery artifacts. Finally, the mean value of a particular cell across all LBP blocks is computed, which yields a fixed number of features and presents a more computationally efficient method. Using Support Vector Machine (SVM), the proposed method has been extensively tested on four well known publicly available gray scale and color image forgery datasets, and additionally on an IoT based image forgery dataset that we built. Experimental results reveal the superiority of our proposed method over recent state-of-the-art methods in terms of widely used performance metrics and computational time and demonstrate robustness against low availability of forged training samples.
- Description: This research was funded by Research Priority Area (RPA) scholarship of Federation University Australia.
A role for MAIT cells in colorectal cancer
- Berzins, Stuart, Wallace, Morgan, Kannourakis, George, Kelly, Jason
- Authors: Berzins, Stuart , Wallace, Morgan , Kannourakis, George , Kelly, Jason
- Date: 2020
- Type: Text , Journal article , Review
- Relation: Frontiers in Immunology Vol. 11, no. (2020), p.
- Full Text:
- Reviewed:
- Description: MAIT cells are MR1-restricted T cells that are well-known for their anti-microbial properties, but they have recently been associated with different forms of cancer. Several studies have reported activated MAIT cells within the microenvironment of colorectal tumors, but there is conjecture about the nature of their response and whether they are contributing to anti-tumor immunity, or to the progression of the disease. We have reviewed the current state of knowledge about the role of MAIT cells in colorectal cancer, including their likely influence when activated and potential sources of stimulation in the tumor microenvironment. The prospects for MAIT cells being used in clinical settings as biomarkers or as targets of new immunotherapies designed to harness their function are discussed. © Copyright © 2020 Berzins, Wallace, Kannourakis and Kelly.
- Authors: Berzins, Stuart , Wallace, Morgan , Kannourakis, George , Kelly, Jason
- Date: 2020
- Type: Text , Journal article , Review
- Relation: Frontiers in Immunology Vol. 11, no. (2020), p.
- Full Text:
- Reviewed:
- Description: MAIT cells are MR1-restricted T cells that are well-known for their anti-microbial properties, but they have recently been associated with different forms of cancer. Several studies have reported activated MAIT cells within the microenvironment of colorectal tumors, but there is conjecture about the nature of their response and whether they are contributing to anti-tumor immunity, or to the progression of the disease. We have reviewed the current state of knowledge about the role of MAIT cells in colorectal cancer, including their likely influence when activated and potential sources of stimulation in the tumor microenvironment. The prospects for MAIT cells being used in clinical settings as biomarkers or as targets of new immunotherapies designed to harness their function are discussed. © Copyright © 2020 Berzins, Wallace, Kannourakis and Kelly.
A shared bus profiling scheme for smart cities based on heterogeneous mobile crowdsourced data
- Kong, Xiangjie, Xia, Feng, Li, Jianxin, Hou, Mingliang, Li, Menglin, Xiang, Yong
- Authors: Kong, Xiangjie , Xia, Feng , Li, Jianxin , Hou, Mingliang , Li, Menglin , Xiang, Yong
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Transactions on Industrial Informatics Vol. 16, no. 2 (2020), p. 1436-1444
- Full Text:
- Reviewed:
- Description: Mobile crowdsourcing (MCS), as an effective and crucial technique of Industrial Internet of Things, is enabling smart city initiatives in the real world. It aims at incorporating the intelligence of dynamic crowds to collect and compute decentralized ubiquitous sensing data that can be used to solve major urbanization problems such as traffic congestion. The shared bus, as a neotype transportation mode, aims at improving the resource utilization rate and maintaining the advantages of convenience and economy. In this article, we provide a scheme to profile shared buses through heterogeneous mobile crowdsourced data (TRProfiling). First, we design an MCS-based shared bus data generation and collection solution to overcome the aforementioned data scarcity issue. Then, we propose a travel profiling to profile resident travel and design a method called multiconstraint evolution algorithm to optimize the routes. Experimental results demonstrate that TRProfiling has an excellent performance in satisfying passengers' travel requirements. © 2005-2012 IEEE.
- Authors: Kong, Xiangjie , Xia, Feng , Li, Jianxin , Hou, Mingliang , Li, Menglin , Xiang, Yong
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Transactions on Industrial Informatics Vol. 16, no. 2 (2020), p. 1436-1444
- Full Text:
- Reviewed:
- Description: Mobile crowdsourcing (MCS), as an effective and crucial technique of Industrial Internet of Things, is enabling smart city initiatives in the real world. It aims at incorporating the intelligence of dynamic crowds to collect and compute decentralized ubiquitous sensing data that can be used to solve major urbanization problems such as traffic congestion. The shared bus, as a neotype transportation mode, aims at improving the resource utilization rate and maintaining the advantages of convenience and economy. In this article, we provide a scheme to profile shared buses through heterogeneous mobile crowdsourced data (TRProfiling). First, we design an MCS-based shared bus data generation and collection solution to overcome the aforementioned data scarcity issue. Then, we propose a travel profiling to profile resident travel and design a method called multiconstraint evolution algorithm to optimize the routes. Experimental results demonstrate that TRProfiling has an excellent performance in satisfying passengers' travel requirements. © 2005-2012 IEEE.
A survey dataset to evaluate the changes in mobility and transportation due to COVID-19 travel restrictions in Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa, United States
- Barbieri, Diego, Lou, Baowen, Passavanti, Marco, Hui, Cang, Lam, Louisa
- Authors: Barbieri, Diego , Lou, Baowen , Passavanti, Marco , Hui, Cang , Lam, Louisa
- Date: 2020
- Type: Text , Journal article
- Relation: Data in Brief Vol. 33, no. (2020), p.
- Full Text:
- Reviewed:
- Description: COVID-19 pandemic has heavily impacted the global community. To curb the viral transmission, travel restrictions have been enforced across the world. The dataset documents the mobility disruptions and the modal shifts that have occurred as a consequence of the restrictive measures implemented in ten countries: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. An online questionnaire was distributed during the period from the 11st to the 31st of May 2020, with a total of 9 394 respondents. The first part of the survey has characterized the frequency of use of all transport modes before and during the enforcement of the restrictions, while the second part of the survey has dealt with perceived risks of contracting COVID-19 from different transport modes and perceived effectiveness of travel mitigation measures. Overall, the dataset (stored in a repository publicly available) can be conveniently used to quantify and understand the modal shifts and people's cognitive behavior towards travel due to COVID-19. The collected responses can be further analysed by considering other demographic and socioeconomic covariates. © 2020 The Author(s). *Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Louisa Lam” is provided in this record*
- Authors: Barbieri, Diego , Lou, Baowen , Passavanti, Marco , Hui, Cang , Lam, Louisa
- Date: 2020
- Type: Text , Journal article
- Relation: Data in Brief Vol. 33, no. (2020), p.
- Full Text:
- Reviewed:
- Description: COVID-19 pandemic has heavily impacted the global community. To curb the viral transmission, travel restrictions have been enforced across the world. The dataset documents the mobility disruptions and the modal shifts that have occurred as a consequence of the restrictive measures implemented in ten countries: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. An online questionnaire was distributed during the period from the 11st to the 31st of May 2020, with a total of 9 394 respondents. The first part of the survey has characterized the frequency of use of all transport modes before and during the enforcement of the restrictions, while the second part of the survey has dealt with perceived risks of contracting COVID-19 from different transport modes and perceived effectiveness of travel mitigation measures. Overall, the dataset (stored in a repository publicly available) can be conveniently used to quantify and understand the modal shifts and people's cognitive behavior towards travel due to COVID-19. The collected responses can be further analysed by considering other demographic and socioeconomic covariates. © 2020 The Author(s). *Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Louisa Lam” is provided in this record*
A Survey on Behavioral Pattern Mining from Sensor Data in Internet of Things
- Rashid, Md Mamunur, Kamruzzaman, Joarder, Hassan, Mohammad, Shahriar Shafin, Sakib, Bhuiyan, Md Zakirul
- Authors: Rashid, Md Mamunur , Kamruzzaman, Joarder , Hassan, Mohammad , Shahriar Shafin, Sakib , Bhuiyan, Md Zakirul
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 33318-33341
- Full Text:
- Reviewed:
- 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.
- Authors: Rashid, Md Mamunur , Kamruzzaman, Joarder , Hassan, Mohammad , Shahriar Shafin, Sakib , Bhuiyan, Md Zakirul
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 33318-33341
- Full Text:
- Reviewed:
- 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.
Aberrant pregnancy-associated plasma protein-A expression in breast cancers prognosticates clinical outcomes
- Prithviraj, Prashanth, Anaka, Matthew, Thompson, Erik, Sharma, Revati, Walkiewicz, Marzena, Tutuka, Candani, Behren, Andreas, Kannourakis, George, Jayachandran, Aparna
- Authors: Prithviraj, Prashanth , Anaka, Matthew , Thompson, Erik , Sharma, Revati , Walkiewicz, Marzena , Tutuka, Candani , Behren, Andreas , Kannourakis, George , Jayachandran, Aparna
- Date: 2020
- Type: Text , Journal article
- Relation: Scientific Reports Vol. 10, no. 1 (2020), p.
- Full Text:
- Reviewed:
- Description: Elevated levels of pregnancy-associated plasma protein-A (PAPP-A) have been implicated in the pathogenesis of various malignancies, including breast cancers. Breast cancer is one of the most frequent carcinomas and is the second most common cancer type detected in women of child-bearing age. Throughout pregnancy PAPP-A is produced and secreted by the placental syncytiotrophoblast cells; co-incidentally pregnancy-associated breast cancers often have an aggressive clinical course. The components of the PAPP-A/IGF axis was assessed in a panel of breast cancer cell lines. Using neutralising antibodies the impact of PAPP-A/IGF axis on cell motility was evaluated. PAPP-A was expressed in four of the twelve breast cancer cell lines tested. Blocking PAPP-A and IGFBP4 with neutralising antibodies significantly decreased motiliy of MDA-MB-231 cells. Upregulation of PAPP-A expression in breast tumours resulted in a trend towards worse overall survival. Notably, PAPP-A expression also positively correlated with epithelial-to-mesenchymal transition markers. In conclusion, these results indicate that PAPP-A plays an important role in breast cancer progression and it may be a promising therapeutic target in breast cancer. © 2020, The Author(s).
- Authors: Prithviraj, Prashanth , Anaka, Matthew , Thompson, Erik , Sharma, Revati , Walkiewicz, Marzena , Tutuka, Candani , Behren, Andreas , Kannourakis, George , Jayachandran, Aparna
- Date: 2020
- Type: Text , Journal article
- Relation: Scientific Reports Vol. 10, no. 1 (2020), p.
- Full Text:
- Reviewed:
- Description: Elevated levels of pregnancy-associated plasma protein-A (PAPP-A) have been implicated in the pathogenesis of various malignancies, including breast cancers. Breast cancer is one of the most frequent carcinomas and is the second most common cancer type detected in women of child-bearing age. Throughout pregnancy PAPP-A is produced and secreted by the placental syncytiotrophoblast cells; co-incidentally pregnancy-associated breast cancers often have an aggressive clinical course. The components of the PAPP-A/IGF axis was assessed in a panel of breast cancer cell lines. Using neutralising antibodies the impact of PAPP-A/IGF axis on cell motility was evaluated. PAPP-A was expressed in four of the twelve breast cancer cell lines tested. Blocking PAPP-A and IGFBP4 with neutralising antibodies significantly decreased motiliy of MDA-MB-231 cells. Upregulation of PAPP-A expression in breast tumours resulted in a trend towards worse overall survival. Notably, PAPP-A expression also positively correlated with epithelial-to-mesenchymal transition markers. In conclusion, these results indicate that PAPP-A plays an important role in breast cancer progression and it may be a promising therapeutic target in breast cancer. © 2020, The Author(s).
Adventures in software engineering : plugging HCI & acessibility gaps with open source solutions
- Authors: Lansley, Alastair
- Date: 2020
- Type: Text , Thesis , PhD
- Full Text:
- Description: There has been a great deal of research undertaken in the field of Human-Computer Interfaces (HCI), input devices, and output modalities in recent years. From touch-based and voice control input mechanisms such as those found on modern smart-devices to the use of touch-free input through video-stream/image analysis (including depth streams and skeletal mapping) and the inclusion of gaze tracking, head tracking, virtual reality and beyond - the availability and variety of these I/O (Input/Output) mechanisms has increased tremendously and progressed both into our living rooms and into our lives in general. With regard to modern desktop computers and videogame consoles, at present many of these technologies are at a relatively immature stage of development - their use often limited to simple adjuncts to the staple input mechanisms of mouse, keyboard, or joystick / joypad inputs. In effect, we have these new input devices - but we're not quite sure how best to use them yet; that is, where their various strengths and weaknesses lie, and how or if they can be used to conveniently and reliably drive or augment applications in our everyday lives. In addition, much of this technology is provided by proprietary hardware and software, providing limited options for customisation or adaptation to better meet the needs of specific users. Therefore, this project investigated the development of open source software solutions to address various aspects of innovative user I/O in a flexible manner. Towards this end, a number of original software applications have been developed which incorporate functionality aimed at enhancing the current state of the art in these areas and making that software freely available for use by any who may find it beneficial.
- Description: Doctor of Philosophy
- Authors: Lansley, Alastair
- Date: 2020
- Type: Text , Thesis , PhD
- Full Text:
- Description: There has been a great deal of research undertaken in the field of Human-Computer Interfaces (HCI), input devices, and output modalities in recent years. From touch-based and voice control input mechanisms such as those found on modern smart-devices to the use of touch-free input through video-stream/image analysis (including depth streams and skeletal mapping) and the inclusion of gaze tracking, head tracking, virtual reality and beyond - the availability and variety of these I/O (Input/Output) mechanisms has increased tremendously and progressed both into our living rooms and into our lives in general. With regard to modern desktop computers and videogame consoles, at present many of these technologies are at a relatively immature stage of development - their use often limited to simple adjuncts to the staple input mechanisms of mouse, keyboard, or joystick / joypad inputs. In effect, we have these new input devices - but we're not quite sure how best to use them yet; that is, where their various strengths and weaknesses lie, and how or if they can be used to conveniently and reliably drive or augment applications in our everyday lives. In addition, much of this technology is provided by proprietary hardware and software, providing limited options for customisation or adaptation to better meet the needs of specific users. Therefore, this project investigated the development of open source software solutions to address various aspects of innovative user I/O in a flexible manner. Towards this end, a number of original software applications have been developed which incorporate functionality aimed at enhancing the current state of the art in these areas and making that software freely available for use by any who may find it beneficial.
- Description: Doctor of Philosophy
Alcohol_focused drowning prevention campaigns : what do we know and what should we do now?
- Calverley, Hannah, Petrass, Lauren, Blitvich, Jennifer
- Authors: Calverley, Hannah , Petrass, Lauren , Blitvich, Jennifer
- Date: 2020
- Type: Text , Journal article
- Relation: International Journal of Aquatic Research and Education Vol. 12, no. 2 (2020), p.
- Full Text:
- Reviewed:
- Description: Alcohol and drugs have been identified as key risk factors for youth (aged 15-24 years) and adult drownings in high-income countries (HIC). Whilst alcohol specific drowning prevention education programs have been developed and implemented, youth continue to be over-represented in drowning statistics, including those linked with alcohol. Therefore, this project aimed to: (i) review and assess all alcohol themed drowning prevention campaigns within HICs; (ii) determine whether the campaign had undergone evaluation for effectiveness; and (iii) provide recommendations to improve the effectiveness of future interventions. For each of the eighty-one HICs identified for the 2019 fiscal year, searches of peer-reviewed literature (through academic databases) and grey literature (through webpages and emails to organisations) were conducted. Twelve alcohol focused campaigns were identified, with only two providing limited information about program evaluation. For most campaigns identified, there was a dearth of information available and therefore assessment of campaign quality was unfeasible. This brief report highlights a lack of alcohol themed drowning prevention campaigns in HIC, and an absence of evaluations on their effectiveness. Implications associated with a lack of program evaluation are discussed and adoption of the recommendations from this brief report should enhance the quality of future research in this area. © 2020 Human Kinetics Publishers Inc.. All rights reserved.
- Authors: Calverley, Hannah , Petrass, Lauren , Blitvich, Jennifer
- Date: 2020
- Type: Text , Journal article
- Relation: International Journal of Aquatic Research and Education Vol. 12, no. 2 (2020), p.
- Full Text:
- Reviewed:
- Description: Alcohol and drugs have been identified as key risk factors for youth (aged 15-24 years) and adult drownings in high-income countries (HIC). Whilst alcohol specific drowning prevention education programs have been developed and implemented, youth continue to be over-represented in drowning statistics, including those linked with alcohol. Therefore, this project aimed to: (i) review and assess all alcohol themed drowning prevention campaigns within HICs; (ii) determine whether the campaign had undergone evaluation for effectiveness; and (iii) provide recommendations to improve the effectiveness of future interventions. For each of the eighty-one HICs identified for the 2019 fiscal year, searches of peer-reviewed literature (through academic databases) and grey literature (through webpages and emails to organisations) were conducted. Twelve alcohol focused campaigns were identified, with only two providing limited information about program evaluation. For most campaigns identified, there was a dearth of information available and therefore assessment of campaign quality was unfeasible. This brief report highlights a lack of alcohol themed drowning prevention campaigns in HIC, and an absence of evaluations on their effectiveness. Implications associated with a lack of program evaluation are discussed and adoption of the recommendations from this brief report should enhance the quality of future research in this area. © 2020 Human Kinetics Publishers Inc.. All rights reserved.
Almost simplicial polytopes : the lower and upper bound theorems
- Nevo, Eran, Pineda-Villavicencio, Guillermo, Ugon, Julien, Yost, David
- Authors: Nevo, Eran , Pineda-Villavicencio, Guillermo , Ugon, Julien , Yost, David
- Date: 2020
- Type: Text , Journal article
- Relation: Canadian Journal of Mathematics Vol. 72, no. 2 (2020), p. 537-556. http://purl.org/au-research/grants/arc/DP180100602
- Full Text:
- Reviewed:
- Description: We study -vertex -dimensional polytopes with at most one nonsimplex facet with, say, vertices, called almost simplicial polytopes. We provide tight lower and upper bound theorems for these polytopes as functions of, and, thus generalizing the classical Lower Bound Theorem by Barnette and the Upper Bound Theorem by McMullen, which treat the case where s = 0. We characterize the minimizers and provide examples of maximizers for any. Our construction of maximizers is a generalization of cyclic polytopes, based on a suitable variation of the moment curve, and is of independent interest. © 2018 Canadian Mathematical Society.
- Authors: Nevo, Eran , Pineda-Villavicencio, Guillermo , Ugon, Julien , Yost, David
- Date: 2020
- Type: Text , Journal article
- Relation: Canadian Journal of Mathematics Vol. 72, no. 2 (2020), p. 537-556. http://purl.org/au-research/grants/arc/DP180100602
- Full Text:
- Reviewed:
- Description: We study -vertex -dimensional polytopes with at most one nonsimplex facet with, say, vertices, called almost simplicial polytopes. We provide tight lower and upper bound theorems for these polytopes as functions of, and, thus generalizing the classical Lower Bound Theorem by Barnette and the Upper Bound Theorem by McMullen, which treat the case where s = 0. We characterize the minimizers and provide examples of maximizers for any. Our construction of maximizers is a generalization of cyclic polytopes, based on a suitable variation of the moment curve, and is of independent interest. © 2018 Canadian Mathematical Society.
An application of high-dimensional statistics to predictive modeling of grade variability
- Hinz, Juri, Grigoryev, Igor, Novikov, Alexander
- Authors: Hinz, Juri , Grigoryev, Igor , Novikov, Alexander
- Date: 2020
- Type: Text , Journal article
- Relation: Geosciences (Switzerland) Vol. 10, no. 4 (2020), p.
- Full Text:
- Reviewed:
- Description: The economic viability of a mining project depends on its efficient exploration, which requires a prediction of worthwhile ore in a mine deposit. In this work, we apply the so-called LASSO methodology to estimate mineral concentration within unexplored areas. Our methodology outperforms traditional techniques not only in terms of logical consistency, but potentially also in costs reduction. Our approach is illustrated by a full source code listing and a detailed discussion of the advantages and limitations of our approach. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Hinz, Juri , Grigoryev, Igor , Novikov, Alexander
- Date: 2020
- Type: Text , Journal article
- Relation: Geosciences (Switzerland) Vol. 10, no. 4 (2020), p.
- Full Text:
- Reviewed:
- Description: The economic viability of a mining project depends on its efficient exploration, which requires a prediction of worthwhile ore in a mine deposit. In this work, we apply the so-called LASSO methodology to estimate mineral concentration within unexplored areas. Our methodology outperforms traditional techniques not only in terms of logical consistency, but potentially also in costs reduction. Our approach is illustrated by a full source code listing and a detailed discussion of the advantages and limitations of our approach. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
An approach to map geography mark-up language data to resource description framework schema
- Faqir, Ammara, Mahmood, Aqsa, Qazi, Kiran, Malik, Saleem
- Authors: Faqir, Ammara , Mahmood, Aqsa , Qazi, Kiran , Malik, Saleem
- Date: 2020
- Type: Text , Conference paper
- Relation: 2nd International Conference on Intelligent Technologies and Applications, INTAP 2019 Vol. 1198, p. 343-354
- Full Text:
- Reviewed:
- Description: GML serves as premier modeling language used to represent data of geographic information related to geography locations. However, a problem of GML is its ability to integrate with a variety of geographical and GPS applications. Since, GML saves data in coordinates and in topology for the purpose to integrate data with variety of applications on semantic web, data be mapped to Resource Description Framework (RDF) and Resource Description Framework Schema (RDFS). An approach of mapping GML metadata to RDFS is presented in this paper. This study focuses on the methodology to convert GML data in semantics to represent in extended and enriched form such as RDFS as representation in RDF is not sufficient over semantic web. Firstly, we have GML script from case study and parse it using GML parser and get XML file. XML file parse using Java and get text file to extract GML features and then get a graph form of these features. After that we designed methodology of prototype tool to map GML features to RDFS. Tool performed features by features mapping and extracted results are represented in the tabular form of mapping GML metadata to RDFS. © 2020, Springer Nature Singapore Pte Ltd.
- Description: E1
- Authors: Faqir, Ammara , Mahmood, Aqsa , Qazi, Kiran , Malik, Saleem
- Date: 2020
- Type: Text , Conference paper
- Relation: 2nd International Conference on Intelligent Technologies and Applications, INTAP 2019 Vol. 1198, p. 343-354
- Full Text:
- Reviewed:
- Description: GML serves as premier modeling language used to represent data of geographic information related to geography locations. However, a problem of GML is its ability to integrate with a variety of geographical and GPS applications. Since, GML saves data in coordinates and in topology for the purpose to integrate data with variety of applications on semantic web, data be mapped to Resource Description Framework (RDF) and Resource Description Framework Schema (RDFS). An approach of mapping GML metadata to RDFS is presented in this paper. This study focuses on the methodology to convert GML data in semantics to represent in extended and enriched form such as RDFS as representation in RDF is not sufficient over semantic web. Firstly, we have GML script from case study and parse it using GML parser and get XML file. XML file parse using Java and get text file to extract GML features and then get a graph form of these features. After that we designed methodology of prototype tool to map GML features to RDFS. Tool performed features by features mapping and extracted results are represented in the tabular form of mapping GML metadata to RDFS. © 2020, Springer Nature Singapore Pte Ltd.
- Description: E1
An efficient 3-D model for remaining wall thicknesses of cast iron pipes in nondestructive testing
- Authors: Nguyen, Linh , Miro, Jaime
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Sensors Letters Vol. 4, no. 7 (2020), p.
- Full Text:
- Reviewed:
- Description: Over 50% of global pipes have been made of cast iron, and most of them are aging. In order to effectively estimate possibilities of their failures, which is paramount for efficiently managing asset infrastructures, it requires the remaining wall thickness (RWT) of a pipe to be known. In fact, RWT of the cast iron pipes can be primarily measured by the magnetism based nondestructive testing technologies though they are quite slow. To speed up the inspection process, it is proposed to sense RWT of a part of a pipe and then employ a model to predict RWT in the rest. Thus, this letter introduces a 3-D model to efficiently represent RWT of a pipe given measurements collected intermittently on the pipe's surface. The proposed model first transforms 3-D cylindrical coordinates to 3-D Cartesian coordinates before modeling RWT by Gaussian processes (GP). The transformation allows GP to work properly on RWT data gathered on a cylindrical pipe and effectively predict RWT at unmeasured locations. Moreover, periodicity of RWT along circumference of the pipe is naturally integrated. The effectiveness of the proposed approach is demonstrated by implementation in two real life inservice aging cast iron pipes, where the obtained results are highly promising. © 2017 IEEE.
- Authors: Nguyen, Linh , Miro, Jaime
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Sensors Letters Vol. 4, no. 7 (2020), p.
- Full Text:
- Reviewed:
- Description: Over 50% of global pipes have been made of cast iron, and most of them are aging. In order to effectively estimate possibilities of their failures, which is paramount for efficiently managing asset infrastructures, it requires the remaining wall thickness (RWT) of a pipe to be known. In fact, RWT of the cast iron pipes can be primarily measured by the magnetism based nondestructive testing technologies though they are quite slow. To speed up the inspection process, it is proposed to sense RWT of a part of a pipe and then employ a model to predict RWT in the rest. Thus, this letter introduces a 3-D model to efficiently represent RWT of a pipe given measurements collected intermittently on the pipe's surface. The proposed model first transforms 3-D cylindrical coordinates to 3-D Cartesian coordinates before modeling RWT by Gaussian processes (GP). The transformation allows GP to work properly on RWT data gathered on a cylindrical pipe and effectively predict RWT at unmeasured locations. Moreover, periodicity of RWT along circumference of the pipe is naturally integrated. The effectiveness of the proposed approach is demonstrated by implementation in two real life inservice aging cast iron pipes, where the obtained results are highly promising. © 2017 IEEE.