Description:
This project aimed to scope existing methods of evaluating the application of universal design to built environments and to explore relevant knowledge of key stakeholders, such as architects, access consultants and people who experience disability. The project commenced in 2017. Ethics approval was gained and a mixed methods approach was employed. Methods of data collection included electronic survey and in-depth interview. Early survey findings are reported in this paper. A descriptive approach was used to analyse quantitative data. A total of 157 survey responses were received from across Australia (83%) and internationally (16.6%). Preliminary findings indicate that most survey respondents (72%) had been involved in the process of applying universal design to the design of built environments. Although evaluating the application of universal design was rated as “extremely important” by 85% of respondents, only 36% had such experience. Of these, 74% had used specific tools for this purpose. Non-standardised checklists and access audits were the most frequently used and preferred tools. Overall, stakeholders perceived themselves to have ‘some knowledge’ on universal design theory and application. This project offers insight into how universal design is understood and applied to the design of built environments. Findings suggest that evaluation is less common than application and that there is a need to strengthen existing methods of evaluation to provide greater detail on universal design processes and outcomes.
Description:
This project aimed to scope existing methods of evaluating the application of universal design to built environments and to explore relevant knowledge of key stakeholders, such as architects, access consultants and people who experience disability. The project commenced in 2017. Ethics approval was gained and a mixed methods approach was employed. Methods of data collection included electronic survey and in-depth interview. Early survey findings are reported in this paper. A descriptive approach was used to analyse quantitative data. A total of 157 survey responses were received from across Australia (83%) and internationally (16.6%). Preliminary findings indicate that most survey respondents (72%) had been involved in the process of applying universal design to the design of built environments. Although evaluating the application of universal design was rated as “extremely important” by 85% of respondents, only 36% had such experience. Of these, 74% had used specific tools for this purpose. Non-standardised checklists and access audits were the most frequently used and preferred tools. Overall, stakeholders perceived themselves to have ‘some knowledge’ on universal design theory and application. This project offers insight into how universal design is understood and applied to the design of built environments. Findings suggest that evaluation is less common than application and that there is a need to strengthen existing methods of evaluation to provide greater detail on universal design processes and outcomes.
Description:
Sulfur dioxide (SO2) is a major flue gas contaminant that has a direct effect on the performance of amine-based carbon dioxide capture units operating on power plant flue gases. In many countries, flue gas desulfurisation (FGD) is an essential upstream requirement to CO2 capture systems, thereby increasing the overall operational and capital cost of the capture system. In Australia, the efficacy of CO2 capture may be compromised by the accumulation of SO2 in the absorption solvent. CSIRO’s CS-Cap process is designed to capture of both these acidic gases in one absorption column, thereby eliminating the need for a separate FGD unit which could potentially save millions of dollars. Previous research at CSIRO’s post-combustion capture pilot plant at Loy Yang power station has shown that mono-ethanolamine (MEA) solvent absorbs both CO2 and SO2, resulting in a spent amine absorbent rich in sulfates. Further development of the CS-Cap concept requires a deeper understanding of the properties of the sulfate-rich absorbent and the conditions under which it can be effectively regenerated. In the present study, thermal reclamation and reactive crystallisation processes were investigated, allowing the parameters affecting the regeneration of sulfate-loaded amine to be identified. It was found that amine losses were considerably higher in thermal reclamation than in reactive precipitation. During thermal reclamation, vacuum conditions were more effective than atmospheric, and pH of the initial solution played a significant role in recovery of MEA from the sulfate-rich absorbent. Reactive crystallisation could be effectively accomplished with the addition of KOH. An advantage of this process was that high purity K2SO4 crystals (~99%) were formed, despite the presence of degradation products in the solvent.
Description:
Sulfur dioxide (SO2) is a major flue gas contaminant that has a direct effect on the performance of amine-based carbon dioxide capture units operating on power plant flue gases. In many countries, flue gas desulfurisation (FGD) is an essential upstream requirement to CO2 capture systems, thereby increasing the overall operational and capital cost of the capture system. In Australia, the efficacy of CO2 capture may be compromised by the accumulation of SO2 in the absorption solvent. CSIRO’s CS-Cap process is designed to capture of both these acidic gases in one absorption column, thereby eliminating the need for a separate FGD unit which could potentially save millions of dollars. Previous research at CSIRO’s post-combustion capture pilot plant at Loy Yang power station has shown that mono-ethanolamine (MEA) solvent absorbs both CO2 and SO2, resulting in a spent amine absorbent rich in sulfates. Further development of the CS-Cap concept requires a deeper understanding of the properties of the sulfate-rich absorbent and the conditions under which it can be effectively regenerated. In the present study, thermal reclamation and reactive crystallisation processes were investigated, allowing the parameters affecting the regeneration of sulfate-loaded amine to be identified. It was found that amine losses were considerably higher in thermal reclamation than in reactive precipitation. During thermal reclamation, vacuum conditions were more effective than atmospheric, and pH of the initial solution played a significant role in recovery of MEA from the sulfate-rich absorbent. Reactive crystallisation could be effectively accomplished with the addition of KOH. An advantage of this process was that high purity K2SO4 crystals (~99%) were formed, despite the presence of degradation products in the solvent.
Description:
This paper presents experimental investigation of nano power generation, less than 1 kW size, using Thermoelectric Generator (TEG). The heat source is expected from waste temperature of incinerator, but in the laboratory experimental it was from electric heat source controlled by electronics device. A prototype of 0.02 kW system, comprising 24 modules of TEG bismuth telluride type connected in series, was built. The system is attached with cooling and temperature control to investigate the characteristics. Preliminary experiments and analytical models of electric output power as function of specific temperature were presented. An optimum output power could be set at a certain condition.
Description:
Dynamic consolidation of Virtual Machines (VMs) can effectively enhance the resource utilization and energy-efficiency of the Cloud Data Centers (CDC). Existing research on Cloud resource reservation and scheduling signify that Cloud Service Users (CSUs) can play a crucial role in improving the resource utilization by providing valuable information to Cloud service providers. However, utilization of CSUs' provided information in minimization of energy consumption of CDC is a novel research direction. The challenges herein are twofold. First, finding the right benign information to be received from a CSU which can complement the energy-efficiency of CDC. Second, smart application of such information to significantly reduce the energy consumption of CDC. To address those research challenges, we have proposed a novel heuristic Dynamic VM Consolidation algorithm, RTDVMC, which minimizes the energy consumption of CDC through exploiting CSU provided information. Our research exemplifies the fact that if VMs are dynamically consolidated based on the time when a VM can be removed from CDC-a useful information to be received from respective CSU, then more physical machines can be turned into sleep state, yielding lower energy consumption. We have simulated the performance of RTDVMC with real Cloud workload traces originated from more than 800 PlanetLab VMs. The empirical figures affirm the superiority of RTDVMC over existing prominent Static and Adaptive Threshold based DVMC algorithms.
Description:
Dynamic consolidation of Virtual Machines (VMs) can effectively enhance the resource utilization and energy-efficiency of the Cloud Data Centers (CDC). Existing research on Cloud resource reservation and scheduling signify that Cloud Service Users (CSUs) can play a crucial role in improving the resource utilization by providing valuable information to Cloud service providers. However, utilization of CSUs' provided information in minimization of energy consumption of CDC is a novel research direction. The challenges herein are twofold. First, finding the right benign information to be received from a CSU which can complement the energy-efficiency of CDC. Second, smart application of such information to significantly reduce the energy consumption of CDC. To address those research challenges, we have proposed a novel heuristic Dynamic VM Consolidation algorithm, RTDVMC, which minimizes the energy consumption of CDC through exploiting CSU provided information. Our research exemplifies the fact that if VMs are dynamically consolidated based on the time when a VM can be removed from CDC-a useful information to be received from respective CSU, then more physical machines can be turned into sleep state, yielding lower energy consumption. We have simulated the performance of RTDVMC with real Cloud workload traces originated from more than 800 PlanetLab VMs. The empirical figures affirm the superiority of RTDVMC over existing prominent Static and Adaptive Threshold based DVMC algorithms.
Description:
Based on research seeking to understand mechanisms affecting the provision of small business advisory services in a Regional (non-metropolitan) Australian setting, by what are called Professional Business Advisors (PBAs), an emergent theme identifies government business programs and initiatives as significant conduits for regional business knowledge transmission. However, those programs and initiatives are also perceived to impose substantial constraints for PBAs providing services in regional communities. The identified constraining factors include issues of financial viability for PBAs, ineligibility of many regional small businesses to access government funded initiatives, capriciousness of government programs, and clash between technology utilisation and infrastructure reliability in some non-metropolitan regional areas. Regional Australian PBAs service a heterogeneous collection of businesses across large geographic areas. Yet, the potential influence that these PBAs have in the process of knowledge transmission is severely constrained by current government programs aimed both at start-up regional businesses and those pursuing organisational growth. Such constraints raise concerns that have regional policy implications.
Description:
Based on research seeking to understand mechanisms affecting the provision of small business advisory services in a Regional (non-metropolitan) Australian setting, by what are called Professional Business Advisors (PBAs), an emergent theme identifies government business programs and initiatives as significant conduits for regional business knowledge transmission. However, those programs and initiatives are also perceived to impose substantial constraints for PBAs providing services in regional communities. The identified constraining factors include issues of financial viability for PBAs, ineligibility of many regional small businesses to access government funded initiatives, capriciousness of government programs, and clash between technology utilisation and infrastructure reliability in some non-metropolitan regional areas. Regional Australian PBAs service a heterogeneous collection of businesses across large geographic areas. Yet, the potential influence that these PBAs have in the process of knowledge transmission is severely constrained by current government programs aimed both at start-up regional businesses and those pursuing organisational growth. Such constraints raise concerns that have regional policy implications.
Description:
Digital Communication is the future of High Voltage (HV) substation automation, protection and control. It not only offer ease of diagnostics but acts fast to isolate healthy feeders from faulty ones. The effect of this digital protection technology is being appreciated by many utilities and industries for the benefit it offers to them and looks to be the future. Some of the utilities are replacing their secondary copper wires with Fibre Optics (FO) and Ethernet wires as they want load the cable trays less and identify the FO better than the secondary copper wires. Conventional relays are being replaced with Intelligent Electronic Devices (IEDs) during asset management replacement program. Switchyard equipment such as instrument transformers filled with oil and SF6 gas are being replaced with Non-Conventional Instrument Transformer (NCITs). Ushering new devices into the network are not without challenges. These devices and peripherals cannot be put into use by the end user without proper assessment and needs to be validated with number of tests for its performances. To get end users acceptance, laboratory and field tests are carried out to study the propagation delays and performance issues as applicable to digital automation and protection scheme. This paper discusses an early detection of the loss of data packets in a star connected Ethernet Substation Automation Systems (SAS). Understanding a real model in a lab environment is an important step towards performance evaluation and identification of issues. With the involvement of multiple manufacturer in the digital substation, it is good to set a trial of the interoperability of equipment involving their products which could address critical protection issues. This paper focuses on a star connected architecture using an Optimized Network Engineering Tool (OPNET) lab-based software simulating the latency and delays of a digital protection scheme in a 132/22-kV zone substation.
Description:
The purpose of this study was to compare one repetition maximum (1RM), as well as biomechanical outputs across a range of loads (75-100%) in the power clean (PC) utilizing the hook grip (HG) or closed-grip (CG). Eleven well-trained males (PC 1RM=1.34xBW) with at least six months of HG experience volunteered. Following a familiarization session, PC 1RM testing with the HG and CG were completed in random order, 5-7 days apart on a force platform with linear position transducers and 2D motion capture. The HG condition resulted in greater PC 1RM (6.6%, ES=0.43), peak barbell velocity (2.9-5.2%, ES=0.41-0.70) and relative peak barbell power (5.7-15.1%, ES=0.32- 0.71) at all submaximal loads compared to CG. No substantial differences were found in horizontal bar-path (ES=-0.27-0.32). The results of this study suggest that athletes who implement weightlifting movements in their physical preparation should adopt the HG.
Description:
The purpose of this study was to compare one repetition maximum (1RM), as well as biomechanical outputs across a range of loads (75-100%) in the power clean (PC) utilizing the hook grip (HG) or closed-grip (CG). Eleven well-trained males (PC 1RM=1.34xBW) with at least six months of HG experience volunteered. Following a familiarization session, PC 1RM testing with the HG and CG were completed in random order, 5-7 days apart on a force platform with linear position transducers and 2D motion capture. The HG condition resulted in greater PC 1RM (6.6%, ES=0.43), peak barbell velocity (2.9-5.2%, ES=0.41-0.70) and relative peak barbell power (5.7-15.1%, ES=0.32- 0.71) at all submaximal loads compared to CG. No substantial differences were found in horizontal bar-path (ES=-0.27-0.32). The results of this study suggest that athletes who implement weightlifting movements in their physical preparation should adopt the HG.
Description:
Clustering similar images is an important task in image processing and computer vision. It requires a measure to quantify pairwise similarities of images. The performance of clustering algorithm depends on the choice of similarity measure. In this paper, we investigate the effectiveness of data independent (distance-based), data-dependent (mass-based) and hybrid (dis)similarity measures in the image clustering task using three benchmark image collections with different sets of features. Our results of K-Medoids clustering show that uses the hybrid Perceptual Dissimilarity Measure (PMD) produces better clustering results than distance-based l(p) - norm and mass-based m(p) - dissimilarity.
Description:
High speed communication is an essential feature of Substation Automation and Control. Existing International Electro-technical Commission (IEC) 61850 guidelines substation automation and communication systems have few shortcomings in the protection architecture which necessitated an upgrade to another guideline. This has been addressed better in IEC 62439-3 standard encompassing Parallel Redundancy Protocol (PRP) and High-availability Seamless Redundancy (HSR), Earlier there have been number of issues with IEC 61850, due to single port failure, data losses and interoperability related to multi-vendor equipment. The enhanced features of a Double Attached Node component based on IEC 62439-3, provide redundancy in protection by virtue of having two active frames circulating in the ring. These frames send out copies in the ring. Should one of them be lost, the destination node will receive alternate frame, ensuring flawless data transfer at a significant faster speed in a multi-vendor equipment ensuring the circuit is fault resilient. PRP and HSR topologies promise enhanced reliability over IEC 61850 standard due to faster processing capabilities, increased availability in the scheme with least delay time in circulating data packet in wireless communication in the network. This paper exhibit performance of PRP and HSR topologies addressing redundancy within the network ring leveraging on IEC 62439-3.
Description:
Most studies about deep learning are based on neural network models, where many layers of parameterized nonlinear differentiable modules are trained by backpropagation. Recently, it has been shown that deep learning can also be realized by non-differentiable modules without backpropagation training called deep forest. The developed representation learning process is based on a cascade of cascades of decision tree forests, where the high memory requirement and the high time cost inhibit the training of large models. In this paper, we propose a simple yet effective approach to improve the efficiency of deep forest. The key idea is to pass the instances with high confidence directly to the final stage rather than passing through all the levels. We also provide a theoretical analysis suggesting a means to vary the model complexity from low to high as the level increases in the cascade, which further reduces the memory requirement and time cost. Our experiments show that the proposed approach achieves highly competitive predictive performance with significantly reduced time cost and memory requirement by up to one order of magnitude.
Description:
Most studies about deep learning are based on neural network models, where many layers of parameterized nonlinear differentiable modules are trained by backpropagation. Recently, it has been shown that deep learning can also be realized by non-differentiable modules without backpropagation training called deep forest. The developed representation learning process is based on a cascade of cascades of decision tree forests, where the high memory requirement and the high time cost inhibit the training of large models. In this paper, we propose a simple yet effective approach to improve the efficiency of deep forest. The key idea is to pass the instances with high confidence directly to the final stage rather than passing through all the levels. We also provide a theoretical analysis suggesting a means to vary the model complexity from low to high as the level increases in the cascade, which further reduces the memory requirement and time cost. Our experiments show that the proposed approach achieves highly competitive predictive performance with significantly reduced time cost and memory requirement by up to one order of magnitude.
Description:
The objective of this paper is to provide a systematic review of the evolutionary trends in the research domain of information technology and organizational learning. Having surveyed various journals and key conferences between 2000 and 2018 on the topic, we observe that information technology (IT) has expanded from its general form to various contemporary information systems, e.g. knowledge organization systems, communication and collaborative systems and decision support systems. However, organization learning (OL) now essentially occurs through knowledge management activities, e.g. knowledge acquisition, storing, sharing and application of knowledge. The survey reported here not only validates the interplay of IT and OL but also reveals some important intervening factors between IT and OL, e.g. absorptive capacity, organization culture, user trust, acceptance and satisfaction that work as deterministic elements in the reciprocal relationship of IT and OL. We propose future research to explore interaction between big data analytical systems and organizational learning.
Description:
The objective of this paper is to provide a systematic review of the evolutionary trends in the research domain of information technology and organizational learning. Having surveyed various journals and key conferences between 2000 and 2018 on the topic, we observe that information technology (IT) has expanded from its general form to various contemporary information systems, e.g. knowledge organization systems, communication and collaborative systems and decision support systems. However, organization learning (OL) now essentially occurs through knowledge management activities, e.g. knowledge acquisition, storing, sharing and application of knowledge. The survey reported here not only validates the interplay of IT and OL but also reveals some important intervening factors between IT and OL, e.g. absorptive capacity, organization culture, user trust, acceptance and satisfaction that work as deterministic elements in the reciprocal relationship of IT and OL. We propose future research to explore interaction between big data analytical systems and organizational learning.
Description:
This paper investigates data dependent kernels that are derived directly from data. This has been an outstanding issue for about two decades which hampered the development of kernel-based methods. We introduce Isolation Kernel which is solely dependent on data distribution, requiring neither class information nor explicit learning to be a classifier. In contrast, existing data dependent kernels rely heavily on class information and explicit learning to produce a classifier. We show that Isolation Kernel approximates well to a data independent kernel function called Laplacian kernel under uniform density distribution. With this revelation, Isolation Kernel can be viewed as a data dependent kernel that adapts a data independent kernel to the structure of a dataset. We also provide a reason why the proposed new data dependent kernel enables SVM (which employs a kernel through other means) to improve its predictive accuracy. The key differences between Random Forest kernel and Isolation Kernel are discussed to examine the reasons why the latter is a more successful tree-based kernel.
Description:
Optical coherence tomography (OCT) is commonly used to analyze retinal layers for assessment of ocular diseases. In this paper, we propose a method for retinal layer segmentation and quantification of uncertainty based on Bayesian deep learning. Our method not only performs end-to-end segmentation of retinal layers, but also gives the pixel wise uncertainty measure of the segmentation output. The generated uncertainty map can be used to identify erroneously segmented image regions which is useful in downstream analysis. We have validated our method on a dataset of 1487 images obtained from 15 subjects (OCT volumes) and compared it against the state-of-the-art segmentation algorithms that does not take uncertainty into account. The proposed uncertainty based segmentation method results in comparable or improved performance, and most importantly is more robust against noise.
Description:
Natural ecosystems provide amenity to human populations in the form of ecosystem services. These services are grouped into four broad categories: Provisioning-food and water production; regulating-control of climate and disease; supporting-crop pollination; and cultural-spiritual and recreational benefits. Aquatic systems provide considerable service through the provision of potable water, fisheries and aquaculture production, nutrient mitigation and the psychological benefits that accrue from the aesthetic amenity provided from lakes, rivers and other wetlands. Further, littoral and riparian ecosystems, and aquifers, protect human communities from sea level encroachment, and tidal and river flooding. Catchment and water development provides critical resources for human consumption. Where these provisioning services are prioritized over others, the level and quality of production may be impacted. Further, the benefits from these provisioning services comes with the opportunity cost of diminishing regulating, supporting and cultural services. This imbalance flags concerns for humanity as it exceeds recognised safe operating spaces. These concepts are explored by reference to long term records of change in some of the world's largest river catchments and lessons are drawn that may enable other communities to consider the balance of ecosystems services in natural resource management.
Description:
Natural ecosystems provide amenity to human populations in the form of ecosystem services. These services are grouped into four broad categories: Provisioning-food and water production; regulating-control of climate and disease; supporting-crop pollination; and cultural-spiritual and recreational benefits. Aquatic systems provide considerable service through the provision of potable water, fisheries and aquaculture production, nutrient mitigation and the psychological benefits that accrue from the aesthetic amenity provided from lakes, rivers and other wetlands. Further, littoral and riparian ecosystems, and aquifers, protect human communities from sea level encroachment, and tidal and river flooding. Catchment and water development provides critical resources for human consumption. Where these provisioning services are prioritized over others, the level and quality of production may be impacted. Further, the benefits from these provisioning services comes with the opportunity cost of diminishing regulating, supporting and cultural services. This imbalance flags concerns for humanity as it exceeds recognised safe operating spaces. These concepts are explored by reference to long term records of change in some of the world's largest river catchments and lessons are drawn that may enable other communities to consider the balance of ecosystems services in natural resource management.
Description:
The use of smartphones and hand-held devices continues to increase with rapid development in underlying technology and widespread deployment of numerous applications including social network, email and financial transactions. Inevitably, malware attacks are shifting towards these devices. To detect mobile malware, features representing the characteristics of applications play a crucial role. In this work, we systematically studied the impact of all categories of features (i.e., permission, application programmers interface calls, inter component communication and dynamic features) of android applications in classifying a malware from benign applications. We identified the best combination of feature categories that yield better performance in terms of widely used metrics than blindly using all feature categories. We proposed a new technique to include contextual information in API calls into feature values and the study reveals that embedding such information enhances malware detection capability by a good margin. Information gain analysis shows that a significant number of features in ICC category is not relevant to malware prediction and hence, least effective. This study will be useful in designing better mobile malware detection system.