'VisionZero': Is it achievable for rugby-related catastrophic injuries in South Africa?
- Authors: Brown, James , Viljoen, Wayne , Readhead, Clint , Baerecke, Gail , Lambert, Mike , Finch, Caroline
- Date: 2017
- Type: Text , Journal article
- Relation: British Journal of Sports Medicine Vol. 51, no. 15 (2017), p. 1106-1107
- Relation: http://purl.org/au-research/grants/nhmrc/1058737
- Full Text: false
- Reviewed:
- Description: The Chris Burger Petro Jackson Players’ Fund (CBPJPF) was founded by Morne Du Plessis when his provincial rugby teammate—Chris Burger—was fatally injured during a match (www.playersfund.org.za). The CBPJPF aims to assist all seriously injured rugby players through donations made by individuals and organisations, including SA RUGBY. These seriously injured players form the CBPJPF ‘membership’ who often mention their appreciation for this lifeline. However, the founding member of the CBPJPF—Morne Du Plessis—is quick to say ‘we don’t want any new members’.5
125th Anniversary Review: Bacteria in brewing: The good, the bad and the ugly
- Authors: Vriesekoop, Frank , Krahl, Moritz , Hucker, Barry , Menz, Garry
- Date: 2013
- Type: Text , Journal article
- Relation: Journal of the Institute of Brewing Vol. 118, no. 4 (2013), p. 335-345
- Full Text: false
- Reviewed:
- Description: Beer is a beverage that is produced in a multistage process, where some stages of that process are intentionally influenced by microorganisms, while at other stages of the production process microorganisms are actively discouraged. Most of the intentional microbial activity is facilitated by yeast; however bacteria also play an influential role in beer production. This paper will describe the beneficial role of bacteria in the beer production process (the Good), but will also pay due attention to the negative influences bacteria might have on the quality of beer as a commodity (the Bad), and the properties of beer that have given it the status of an inherently safe food for human consumption with regards to disease-causing bacteria (the Ugly). Copyright (C) 2013 The Institute of Brewing & Distilling
- Description: C1
2D dynamic analysis of cracks and interface cracks in piezoelectric composites using the SBFEM
- Authors: Li, Chao , Song, Chongmin , Man, Hou , Ooi, Ean Tat , Gao, Wei
- Date: 2014
- Type: Text , Journal article
- Relation: International Journal of Solids and Structures Vol. 51, no. 11-12 (June 2014), p. 2096-2108
- Full Text: false
- Reviewed:
- Description: The dynamic stress and electric displacement intensity factors of impermeable cracks in homogeneous piezoelectric materials and interface cracks in piezoelectric bimaterials are evaluated by extending the scaled boundary finite element method (SBFEM). In this method, a piezoelectric plate is divided into polygons. Each polygon is treated as a scaled boundary finite element subdomain. Only the boundaries of the subdomains need to be discretized with line elements. The dynamic properties of a subdomain are represented by the high order stiffness and mass matrices obtained from a continued fraction solution, which is able to represent the high frequency response with only 3-4 terms per wavelength. The semi-analytical solutions model singular stress and electric displacement fields in the vicinity of crack tips accurately and efficiently. The dynamic stress and electric displacement intensity factors are evaluated directly from the scaled boundary finite element solutions. No asymptotic solution, local mesh refinement or other special treatments around a crack tip are required. Numerical examples are presented to verify the proposed technique with the analytical solutions and the results from the literature. The present results highlight the accuracy, simplicity and efficiency of the proposed technique.
3D Finite element modeling of circular reinforced concrete columns confined with FRP using a plasticity based formulation
- Authors: Piscesa, Bambang , Attard, Mario , Samani, Ali Khajeh
- Date: 2018
- Type: Text , Journal article
- Relation: Composite Structures Vol. 194, no. (2018), p. 478-493
- Full Text: false
- Reviewed:
- Description: Strengthening reinforced concrete (RC) columns with external confining devices such as FRP wraps or steel tube is widely used in construction. By using external confining devices, both the strength and ductility of RC columns are significantly improved. However, numerical modeling to predict the capacity of strengthened RC columns is limited and often oversimplified. One of the biggest challenges in numerical modeling is to deal with unequal dilation between the concrete inner core (enclosed by both transverse steel and FRP wraps) and the concrete outer core (between the transverse steel and FRP wraps). Inaccurate modeling on the concrete dilatant behavior can lead to incorrect strength prediction. Sophisticated constitutive models which are able to model concrete dilation and robust modeling techniques are required. In this paper, three-dimensional non-linear finite element analysis (3D-NLFEA) of circular RC columns confined with conventional steel stirrups and FRP wraps is presented. In the FEA, the initial stiffness method with Process Modification (acceleration technique) is used to solve the equilibrium forces in the global solution. The constitutive model is based on the plasticity formulation proposed by the authors, which can capture the effective lateral modulus (EL) of the confining devices. This lateral modulus is obtained by observing the principal incremental stresses and strains at each element gauss point. It was found that, the lateral modulus is greatly affected by the boundary condition, dilatant behavior of the constitutive model and the Poisson's ratio of the external confining device. To validate the performance of the proposed model, several comparisons of the proposed model, using 3D-NLFEA, with experimental results is presented. The comparisons show that the predicted response using 3D-NLFEA and the experimental results of RC columns confined with FRP are in a good agreement.
A 3D object encryption scheme which maintains dimensional and spatial stability
- Authors: Jolfaei, Alireza , Wu, Xinwen , Muthukkumarasamy, Vallipuram
- Date: 2015
- Type: Text , Journal article
- Relation: IEEE Transactions on Information Forensics and Security Vol. 10, no. 2 (2015), p. 409-422
- Full Text:
- Reviewed:
- Description: Due to widespread applications of 3D vision technology, the research into 3D object protection is primarily important. To maintain confidentiality, encryption of 3D objects is essential. However, the requirements and limitations imposed by 3D objects indicate the impropriety of conventional cryptosystems for 3D object encryption. This suggests the necessity of designing new ciphers. In addition, the study of prior works indicates that the majority of problems encountered with encrypting 3D objects are about point cloud protection, dimensional and spatial stability, and robustness against surface reconstruction attacks. To address these problems, this paper proposes a 3D object encryption scheme, based on a series of random permutations and rotations, which deform the geometry of the point cloud. Since the inverse of a permutation and a rotation matrix is its transpose, the decryption implementation is very efficient. Our statistical analyses show that within the cipher point cloud, points are randomly distributed. Furthermore, the proposed cipher leaks no information regarding the geometric structure of the plain point cloud, and is also highly sensitive to the changes of the plaintext and secret key. The theoretical and experimental analyses demonstrate the security, effectiveness, and robustness of the proposed cipher against surface reconstruction attacks.
A call to capture fatalities in consensus statements for sports injury/illness surveillance
- Authors: Fortington, Lauren , Kucera, Kristen , Finch, Caroline
- Date: 2017
- Type: Text , Journal article , Editorial
- Relation: British Journal of Sports Medicine Vol. 51, no. 14 (2017), p. 1052-1053
- Full Text: false
- Reviewed:
A comparative study on the role of polyvinylpyrrolidone molecular weight on the functionalization of various carbon nanotubes and their composites
- Authors: Namasivayam, Muthuraman , Andersson, Mats , Shapter, Joseph
- Date: 2021
- Type: Text , Journal article
- Relation: Polymers Vol. 13, no. 15 (2021), p.
- Full Text:
- Reviewed:
- Description: Polyvinylidene fluoride (PVDF) nanocomposites filled with polyvinylpyrrolidone (PVP) wrapped carbon nanotubes were prepared via a solution casting technique. The effect of the molecular weight (polymer chain length) of the PVP on the ability to wrap different nanotube structures and its impact towards nanotube dispersibility in the polymer matrix was explored. The study was conducted with PVP of four different molecular weights and nanotubes of three different structures. The composites that exhibit an effective nanotube dispersion lead to a nanotube network that facilitates improved thermal, electrical, and mechanical properties. It was observed that nanotubes of different structures exhibit stable dispersions in the polymer matrix though PVP functionalization of different molecular weights, but the key is achieving an effective nanotube dispersion at low PVP concentrations. This is observed in MWNT and AP-SWNT based composites with PVP of low molecular weight, leading to a thermal conductivity enhancement of 147% and 53%, respectively, while for P3-SWNT based composites, PVP of high molecular weight yields an enhancement of 25% in thermal conductivity compared to the non-functionalized CNT-PVDF composite. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
A comprehensive spectrum trading scheme based on market competition, reputation and buyer specific requirements
- Authors: Hassan, Md Rakib , Karmakar, Gour , Kamruzzaman, Joarder , Srinivasan, Bala
- Date: 2015
- Type: Text , Journal article
- Relation: Computer Networks Vol. 84, no. (2015), p. 17-31
- Full Text:
- Reviewed:
- Description: In the exclusive-use model of spectrum trading, cognitive radio devices or secondary users can buy spectrum resources from licensed users or primary users for a short or long period of time. Considering such spectrum access, a trading model is introduced where a buyer can select a set of candidate sellers based on their reputation and their offers in fulfilling its requirements, namely, offered signal quality, contract duration, coverage and bandwidth. Similarly, a seller can assess a buyer as a potential trading partner considering the buyer's reliability, which the seller can derive from the buyer's reputation and financial profile. In our scheme, seller reputation or buyer reliability can be either obtained from a reputation brokerage service, if one exists, or calculated using our model. Since in a competitive market, the price of a seller depends on that of other sellers, game theory is used to model the competition among multiple sellers. An optimization technique is used by a buyer to select the best seller(s) and optimize purchase to maximize its utility. This may result in buying from multiple sellers of certain amount of bandwidth from each, depending on price and meeting requirements and budget constraints. Stability of the model is analyzed and performance evaluation shows that it benefits sellers and buyers in terms of profit and throughput, respectively. © 2015 Elsevier B.V. All rights reserved.
A DEM investigation on simple shear behavior of dense granular assemblies
- Authors: Shi, Danda , Xue, Jianfeng , Zhao, Zhenying , Shi, Jiyu
- Date: 2015
- Type: Text , Journal article
- Relation: Journal of Central South University Vol. 22, no. 12 (2015), p. 4844-4855
- Full Text: false
- Reviewed:
- Description: A micromechanical investigation on simple shear behavior of dense granular assemblies was carried out by discrete element method. Three series of numerical tests were performed to examine the effects of initial porosity, vertical stress and particle shape on simple shear behavior of the samples, respectively. It was found that during simple shear the directions of principal stress and principal strain increment rotate differently with shear strain level. The non-coaxiality between the two directions decreases with strain level and may greatly affect the shear behavior of the assemblies, especially their peak friction angles. The numerical modelling also reveals that the rotation of the principal direction of fabric anisotropy lags behind that of the major principal stress direction during simple shear, which is described as fabric hyteresis effect. The degrees of fabric and interparticle contact force anisotropies increase as particle angularity increases, whereas the orientations of these anisotropies have not been significantly influenced by particle shape. An extended stress-dilatancy relationship based on ROWE-DAVIS framework was proposed to consider the non-coaxiality effect under principal stress rotation. The model was validated by present numerical results as well as some published physical test and numerical modelled data. © 2015, Central South University Press and Springer-Verlag Berlin Heidelberg.
A direct optimization method for low group delay FIR filter design
- Authors: Wu, Changzhi , Gao, David , Lay Teo, Kok
- Date: 2013
- Type: Text , Journal article
- Relation: Signal Processing Vol. 93, no. 7 (2013), p. 1764-1772
- Full Text: false
- Reviewed:
- Description: This paper studies the design of FIR filter with low group delay, where the desired phase response is not being approximated. It is formulated as a constrained optimization problem, which is then solved globally. Numerical experiments show that our design method can produce a filter with smaller group delay than that obtained by the existing convex optimization method used in conjunction with a minimum phase spectral factorization method under the same design criteria. Furthermore, our formulation offers us the flexibility for the trade-off between the group delay and the magnitude response directly. It also allows the feasibility of imposing constraints on the group delay. © 2013 Elsevier B.V.
- Description: 2003011019
A distributed and anonymous data collection framework based on multilevel edge computing architecture
- Authors: Usman, Muhammad , Jan, Mian , Jolfaei, Alireza , Xu, Min , He, Xiangjian , Chen, Jinjun
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Transactions on Industrial Informatics Vol. 16, no. 9 (2020), p. 6114-6123
- Full Text: false
- Reviewed:
- Description: Industrial Internet of Things applications demand trustworthiness in terms of quality of service (QoS), security, and privacy, to support the smooth transmission of data. To address these challenges, in this article, we propose a distributed and anonymous data collection (DaaC) framework based on a multilevel edge computing architecture. This framework distributes captured data among multiple level-one edge devices (LOEDs) to improve the QoS and minimize packet drop and end-to-end delay. Mobile sinks are used to collect data from LOEDs and upload to cloud servers. Before data collection, the mobile sinks are registered with a level-two edge-device to protect the underlying network. The privacy of mobile sinks is preserved through group-based signed data collection requests. Experimental results show that our proposed framework improves QoS through distributed data transmission. It also helps in protecting the underlying network through a registration scheme and preserves the privacy of mobile sinks through group-based data collection requests. © 2005-2012 IEEE.
A fast scalable implementation of the two-dimensional triangular discrete element Method on a GPU platform
- Authors: Zhang, Ling , Quigley, Steven , Chan, Andrew
- Date: 2014
- Type: Text , Journal article
- Relation: Advances in Engineering Software Vol. 60-61, no. June-July (2014), p. 70-80
- Full Text: false
- Reviewed:
- Description: Real-time solution of the Discrete Element Method is a computational challenge that is hardly achievable on standard PCs, especially when a large number of triangular shaped particles are involved. This paper presents a scalable architecture, including a domain decomposition technique, of a GPU accelerator for the two-dimensional Discrete Element Method for triangular shaped particles. This approach achieved a speed up of about 140 times as a single core and about 80 after domain decomposition on a consumer level GPU compared to a similar algorithm run on a fast desktop PC.
A HMM-based adaptive fuzzy inference system for stock market forecasting
- Authors: Hassan, Md Rafiul , Ramamohanarao, Kotagiri , Kamruzzaman, Joarder , Rahman, Mustafizur , Hossain, Maruf
- Date: 2013
- Type: Text , Journal article
- Relation: Neurocomputing Vol. 104, no. (2013), p. 10-25
- Full Text: false
- Reviewed:
- Description: In this paper, we propose a new type of adaptive fuzzy inference system with a view to achieve improved performance for forecasting nonlinear time series data by dynamically adapting the fuzzy rules with arrival of new data. The structure of the fuzzy model utilized in the proposed system is developed based on the log-likelihood value of each data vector generated by a trained Hidden Markov Model. As part of its adaptation process, our system checks and computes the parameter values and generates new fuzzy rules as required, in response to new observations for obtaining better performance. In addition, it can also identify the most appropriate fuzzy rule in the system that covers the new data; and thus requires to adapt the parameters of the corresponding rule only, while keeping the rest of the model unchanged. This intelligent adaptive behavior enables our adaptive fuzzy inference system (FIS) to outperform standard FISs. We evaluate the performance of the proposed approach for forecasting stock price indices. The experimental results demonstrate that our approach can predict a number of stock indices, e.g., Dow Jones Industrial (DJI) index, NASDAQ index, Standard and Poor500 (S&P500) index and few other indices from UK (FTSE100), Germany (DAX) , Australia (AORD) and Japan (NIKKEI) stock markets, accurately compared with other existing computational and statistical methods.
A hybrid of multiobjective evolutionary algorithm and HMM-Fuzzy model for time series prediction
- Authors: Hassan, Md Rafiul , Nath, Gupta , Kirley, Michael , Kamruzzaman, Joarder
- Date: 2012
- Type: Text , Journal article
- Relation: Neurocomputing Vol. 81, no. April (2012), p. 1-11
- Full Text: false
- Reviewed:
- Description: In this paper, we introduce a new hybrid of Hidden Markov Model (HMM), Fuzzy Logic and multiobjective Evolutionary Algorithm (EA) for building a fuzzy model to predict non-linear time series data. In this hybrid approach, the HMM's log-likelihood score for each data pattern is used to rank the data and fuzzy rules are generated using the ranked data. We use multiobjective EA to find a range of trade-off solutions between the number of fuzzy rules and the prediction accuracy. The model is tested on a number of benchmark and more recent financial time series data. The experimental results clearly demonstrate that our model is able to generate a reduced number of fuzzy rules with similar (and in some cases better) performance compared with typical data driven fuzzy models reported in the literature.
A knowledge transfer scheme to bridge the gap between science and practice: An integration of existing research frameworks into a tool for practice
- Authors: Verhagen, Evert , Voogt, Nelly , Bruinsma, Anja , Finch, Caroline
- Date: 2014
- Type: Text , Journal article
- Relation: British Journal of Sports Medicine Vol. 48, no. 8 (April 2014), p. 698-701
- Relation: http://purl.org/au-research/grants/nhmrc/565900
- Full Text:
- Reviewed:
- Description: Evidence of effectiveness does not equal successful implementation. To progress the field, practical tools are needed to bridge the gap between research and practice and to truly unite effectiveness and implementation evidence. This paper describes the Knowledge Transfer Scheme integrating existing implementation research frameworks into a tool which has been developed specifically to bridge the gap between knowledge derived from research on the one side and evidence-based usable information and tools for practice on the other.
A lateral strain plasticity model for FRP confined concrete
- Authors: Piscesa, Bambang , Attard, Mario , Samani, Ali Khajeh
- Date: 2016
- Type: Text , Journal article
- Relation: Composite Structures Vol. 158, no. (2016), p. 160-174
- Full Text: false
- Reviewed:
- Description: This paper presents a plasticity constitutive formulation for actively and passively confined concrete. The loading surface is based on Menetrey and Willam's model with an additional frictional driver parameter. The frictional driver parameter controls the prediction of the peak stress and the residual stress level. The proposed flow rule has a plastic dilation rate control parameter which is a function of the restraining device or the local lateral modulus. A non-constant plastic dilation rate formulation is proposed to improve the prediction of the lateral strain behaviour of concrete. The proposed plastic dilation rate formulation is able to model plastic volumetric compaction caused by the use of very stiff confining devices, as well as the initial plastic compaction after the onset of localized cracking. Furthermore, the formulation is able to distinguish between active and passive confinement by monitoring the local lateral modulus. The accuracy of the proposed plastic dilation rate formulation is verified by comparison with experimental results for specimens subjected to either active or passive confinement from a variety of concrete strengths. The comparison between the proposed plasticity model and the experimental results for concrete under passive confinement (specimens with FRP confining material) was excellent. © 2016
A low-complexity equalizer for video broadcasting in cyber-physical social systems through handheld mobile devices
- 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 machine vision based automatic optical inspection system for measuring drilling quality of printed circuit boards
- Authors: Wang, Wei , Chen, Shang-Liang , Chen, Liang-Bi , Chang, Wan-Jung
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Access Vol. 5, no. (2017), p. 10817-10833
- Full Text:
- Reviewed:
- Description: In this paper, we develop and put into practice an automatic optical inspection (AOI) system based on machine vision to check the holes on a printed circuit board (PCB). We incorporate the hardware and software. For the hardware part, we combine a PC, the three-axis positioning system, a lighting device, and charge-coupled device cameras. For the software part, we utilize image registration, image segmentation, drill numbering, drill contrast, and defect displays to achieve this system. Results indicated that an accuracy of 5 mu m could be achieved in errors of the PCB holes allowing comparisons to be made. This is significant in inspecting the missing, the multi-hole, and the incorrect location of the holes. However, previous work only focuses on one or other feature of the holes. Our research is able to assess multiple features: missing holes, incorrectly located holes, and excessive holes. Equally, our results could be displayed as a bar chart and target plot. This has not been achieved before. These displays help users to analyze the causes of errors and immediately correct the problems. In addition, this AOI system is valuable for checking a large number of holes and finding out the defective ones on a PCB. Meanwhile, we apply a 0.1-mm image resolution, which is better than others used in industry. We set a detecting standard based on 2-mm diameter of circles to diagnose the quality of the holes within 10 s.
A new cascaded multilevel inverter topology with galvanic isolation
- Authors: Hasan, Mubashwar , Abu-Siada, Ahmed , Islam, Syed , Dahidah, Mohamed
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Transactions on Industry Applications Vol. 54, no. 4 (2018), p. 3463-3472
- Full Text:
- Reviewed:
- Description: IEEE This paper presents a new compact three-phase cascaded multilevel inverter (CMLI) topology with reduced device count and high frequency magnetic link. The proposed topology overcomes the predominant limitation of separate DC power supplies, which CMLI always require. The high frequency magnetic link also provides a galvanic isolation between the input and output sides of the inverter, which is essential for various grid-connected applications. The proposed topology utilizes an asymmetric inverter configuration that consists of cascaded H-bridge cells and a conventional three-phase two-level inverter. A toroidal core is employed for the high frequency magnetic link to ensure compact size and high-power density. Compared with counterpart CMLI topologies available in the literatures, the proposed inverter has the advantage of utilizing the least number of power electronic components without compromising the overall performance, particularly when a high number of output voltage levels is required. The feasibility of the proposed inverter is confirmed through extensive simulation and experimentally validated studies.
A new data driven long-term solar yield analysis model of photovoltaic power plants
- 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.