Description:
Video coding technique with a background frame, extracted from mixture of Gaussian (MoG) based background modeling, provides better rate distortion performance by exploiting coding efficiency in uncovered background areas compared to the latest video coding standard. However, it suffers from high computation time, low coding efficiency for dynamic videos, and prior knowledge requirement of video content. In this paper, we present a novel adaptive weighted non-parametric (WNP) background modeling technique and successfully embed it into HEVC video coding standard. Being non-parametric (NP), the proposed technique naturally exhibits superior performance in dynamic background scenarios compared to MoG-based technique without a priori knowledge of video data distribution. In addition, the WNP technique significantly reduces noise-related drawbacks of existing NP techniques to provide better quality video coding with much lower computation time as demonstrated through extensive comparative studies against NP, MoG and HEVC techniques.
Description:
Video coding technique with a background frame, extracted from mixture of Gaussian (MoG) based background modeling, provides better rate distortion performance by exploiting coding efficiency in uncovered background areas compared to the latest video coding standard. However, it suffers from high computation time, low coding efficiency for dynamic videos, and prior knowledge requirement of video content. In this paper, we present a novel adaptive weighted non-parametric (WNP) background modeling technique and successfully embed it into HEVC video coding standard. Being non-parametric (NP), the proposed technique naturally exhibits superior performance in dynamic background scenarios compared to MoG-based technique without a priori knowledge of video data distribution. In addition, the WNP technique significantly reduces noise-related drawbacks of existing NP techniques to provide better quality video coding with much lower computation time as demonstrated through extensive comparative studies against NP, MoG and HEVC techniques.
Description:
In 2007-08, fitness facilities contributed $872.9 million to the Australian economy and provided savings in direct health care costs estimated up to $107.9 million through their positive impact on physical inactivity and associated diseases (1). In 2011-12, more than 4.3 million Australians participated in sport and physical recreation at indoor sports or fitness facilities (2). However, research across Queensland (3) and in Victoria (4) showed low compliance with emergency plans and safety practices in fitness facilities. The aim of this study was to analyse emergency plans and procedures in fitness facilities in Australia. A nationwide online risk management survey of fitness professionals (n=1178, mean age=39.9), and observational audits at randomly selected regional and metropolitan fitness facilities (n=11) in New South Wales, South Australia, Victoria and Queensland were conducted. The findings indicated that most of the fitness professionals (68.1%) rated the emergency evacuation plans and other emergency procedures in their facilities as extremely/very good (n=640). Yet, more than one fourth (27.4%) of fitness professionals were somewhat aware (n=152), or very unaware/not at all aware (n=49) of the emergency evacuation plans and other emergency procedures in their facilities. The observational audits showed that most of the fitness facilities did not clearly display their emergency response plans (73%, n=8), emergency evacuation procedures (55%, n=6) or emergency telephone numbers (91%, n=10). Many fitness facilities (36.4%, n=4) did not have an appropriate first aid kit accessible by all staff. Our study shows a lack of emergency preparedness in many fitness facilities in Australia. Emergency response capability is crucial for fitness facility managers to satisfy their duty of care to manage risks of medical emergencies and disasters such as fire, explosion, and floods. Our study has implications for policy development and education of fitness facility managers to improve emergency plans and procedures in fitness facilities in Australia.
Description:
In 2007-08, fitness facilities contributed $872.9 million to the Australian economy and provided savings in direct health care costs estimated up to $107.9 million through their positive impact on physical inactivity and associated diseases (1). In 2011-12, more than 4.3 million Australians participated in sport and physical recreation at indoor sports or fitness facilities (2). However, research across Queensland (3) and in Victoria (4) showed low compliance with emergency plans and safety practices in fitness facilities. The aim of this study was to analyse emergency plans and procedures in fitness facilities in Australia. A nationwide online risk management survey of fitness professionals (n=1178, mean age=39.9), and observational audits at randomly selected regional and metropolitan fitness facilities (n=11) in New South Wales, South Australia, Victoria and Queensland were conducted. The findings indicated that most of the fitness professionals (68.1%) rated the emergency evacuation plans and other emergency procedures in their facilities as extremely/very good (n=640). Yet, more than one fourth (27.4%) of fitness professionals were somewhat aware (n=152), or very unaware/not at all aware (n=49) of the emergency evacuation plans and other emergency procedures in their facilities. The observational audits showed that most of the fitness facilities did not clearly display their emergency response plans (73%, n=8), emergency evacuation procedures (55%, n=6) or emergency telephone numbers (91%, n=10). Many fitness facilities (36.4%, n=4) did not have an appropriate first aid kit accessible by all staff. Our study shows a lack of emergency preparedness in many fitness facilities in Australia. Emergency response capability is crucial for fitness facility managers to satisfy their duty of care to manage risks of medical emergencies and disasters such as fire, explosion, and floods. Our study has implications for policy development and education of fitness facility managers to improve emergency plans and procedures in fitness facilities in Australia.
Description:
Interoperability among multi-vendor substations automation devices, is now achievable due to the introduction of IEC 61850 standard, which allows power system communication between substations. This standard does not mandatorily demands for redundancy in any type of substation neither does it mentions a specific type of substation design application. Ethernet based communication protocols for substation automation systems (SASs) are specified in IEC 61850 standard. The standards include Ethernet based process-level connections between switchyards and control rooms. However, their in-service performance is not well known. Moreover, IEC 61850 demands for a communication topology which is zero point failure proof and provides worthy data transmission rates, without pursuing any delays. In order to achieve these norms, Ethernet architectures must be modelled and analysed in detail. The performance of individual architecture must be analysed in terms of their reliability, availability and efficiency of data transfer. This paper presents the reliability and availability using the reliability block diagrams, along with OPNET network real-time simulations, which shows the efficiency of individual architecture along with comparing and synthesizing the most effective communication topology for the SASs.
Description:
Digital image processing (DIP) technique has been growing rapidly as an essential tool to interpret various image features for many applications of science and engineering. Condition monitoring and diagnosis are considered the main areas that relay on DIP. Frequency response analysis (FRA) technique has become a popular and reliable diagnostic tool in detecting various winding deformations within power transformers. However, interpretation of FRA signatures still requires high expertise because of its reliance on graphical analysis. This paper presents a new technique for the interpretation of transformers FRA signatures. The proposed technique relies on incorporating both magnitude and angle of the FRA signature in one polar plot, which is manipulated to extract some unique features using DIP techniques. The proposed technique can assess in identifying and quantifying various winding deformation within power transformers. The proposed technique is easy to implement in any frequency response analyser.
Description:
Doubly Fed Induction Generators (DFIGs) are nowadays extensively used in variable speed wind power plants due to their advantages that include reduced converter rating, low cost, reduced losses with an improved efficiency, easy implementation of power factor correction schemes, variable speed operation and four quadrants active and reactive power control capabilities. On the other hand, DFIG sensitivity to grid disturbances, especially for the voltage dip represents the main disadvantage of the equipment. This paper presents the application of superconducting magnetic energy storage (SMES) unit to improve the overall performance of a DFIG-based wind energy conversion systems (WECS). Two control approaches namely; hysteresis current controller (HCC) along with proportional integral (PI) controller and a fuzzy logic (FL) controller for the SMES unit are presented and compared. Various grid codes are used to examine the capability of the two proposed controllers to improve the low voltage ride through (LVRT) capability of the DFIG to maintain the wind turbine connection to the grid through fault durations.
Description:
IEEE Power and Energy Society General Meeting
Description:
This paper presents a new method for segmentation of LIDAR point cloud data for automatic building extraction. Using the ground height from a DEM (Digital Elevation Model), the non-ground points (mainly buildings and trees) are separated from the ground points. Points on walls are removed from the set of non-ground points by applying the following two approaches: If a plane fitted at a point and its neighbourhood is perpendicular to a fictitious horizontal plane, then this point is designated as a wall point. When LIDAR points are projected on a dense grid, points within a narrow area close to an imaginary vertical line on the wall should fall into the same grid cell. If three or more points fall into the same cell, then the intermediate points are removed as wall points. The remaining non-ground points are then divided into clusters based on height and local neighbourhood. One or more clusters are initialised based on the maximum height of the points and then each cluster is extended by applying height and neighbourhood constraints. Planar roof segments are extracted from each cluster of points following a region-growing technique. Planes are initialised using coplanar points as seed points and then grown using plane compatibility tests. If the estimated height of a point is similar to its LIDAR generated height, or if its normal distance to a plane is within a predefined limit, then the point is added to the plane. Once all the planar segments are extracted, the common points between the neghbouring planes are assigned to the appropriate planes based on the plane intersection line, locality and the angle between the normal at a common point and the corresponding plane. A rule-based procedure is applied to remove tree planes which are small in size and randomly oriented. The neighbouring planes are then merged to obtain individual building boundaries, which are regularised based on long line segments. Experimental results on ISPRS benchmark data sets show that the proposed method offers higher building detection and roof plane extraction rates than many existing methods, especially in complex urban scenes.
Description:
This paper presents a new method for segmentation of LIDAR point cloud data for automatic building extraction. Using the ground height from a DEM (Digital Elevation Model), the non-ground points (mainly buildings and trees) are separated from the ground points. Points on walls are removed from the set of non-ground points by applying the following two approaches: If a plane fitted at a point and its neighbourhood is perpendicular to a fictitious horizontal plane, then this point is designated as a wall point. When LIDAR points are projected on a dense grid, points within a narrow area close to an imaginary vertical line on the wall should fall into the same grid cell. If three or more points fall into the same cell, then the intermediate points are removed as wall points. The remaining non-ground points are then divided into clusters based on height and local neighbourhood. One or more clusters are initialised based on the maximum height of the points and then each cluster is extended by applying height and neighbourhood constraints. Planar roof segments are extracted from each cluster of points following a region-growing technique. Planes are initialised using coplanar points as seed points and then grown using plane compatibility tests. If the estimated height of a point is similar to its LIDAR generated height, or if its normal distance to a plane is within a predefined limit, then the point is added to the plane. Once all the planar segments are extracted, the common points between the neghbouring planes are assigned to the appropriate planes based on the plane intersection line, locality and the angle between the normal at a common point and the corresponding plane. A rule-based procedure is applied to remove tree planes which are small in size and randomly oriented. The neighbouring planes are then merged to obtain individual building boundaries, which are regularised based on long line segments. Experimental results on ISPRS benchmark data sets show that the proposed method offers higher building detection and roof plane extraction rates than many existing methods, especially in complex urban scenes.
Description:
This paper presents a segmentation of LIDAR point cloud data for automatic extraction of building footprint. Using the ground height information from a DEM (Digital Elevation Model), the non-ground points (mainly buildings and trees) are separated from the ground points. Points on walls are removed from the set of non-ground points. The remaining non-ground points are then divided into clusters based on height and local neighbourhood. Planar roof segments are extracted from each cluster of points following a region-growing technique. Planes are initialised using coplanar points as seed points and then grown using plane compatibility tests. Once all the planar segments are extracted, a rule-based procedure is applied to remove tree planes which are small in size and randomly oriented. The neighbouring planes are then merged to obtain individual building boundaries, which are regularised based on a new feature-based technique. Corners and line-segments are extracted from each boundary and adjusted using the assumption that each short building side is parallel or perpendicular to one or more neighbouring long building sides. Experimental results on five Australian data sets show that the proposed method offers higher correctness rate in building footprint extraction than a state-of-the-art method.
Description:
There are currently several automatic building extraction methods introduced in the literature, but none of them are capable to completely extract portions of a building that are below a pre-defined building minimum height threshold. This paper proposes a systematic method which analyzes the height differences between the extracted adjacent planes above and below the height threshold as well as the planes' connectivity, thereby, extracting all portions belonging to buildings more completely. In general, the height difference between the edges of the adjacent planes above and below the height threshold that belong to the same building is more uniform. In addition, the extracted planes below the height threshold that belong to a building and their adjacent ground planes also have a clear height difference. The proposed method incorporates such information to achieve better performance in building extraction. We have compared our proposed method to a current state-of-the-art building extraction method qualitatively and quantitatively. Our experimental results show that our proposed method successfully recovers portions of a building below the height threshold, thereby achieving relatively higher average completeness (an improvement of 1.14%) and quality (an improvement of 0.93%).
Description:
There are currently several automatic building extraction methods introduced in the literature, but none of them are capable to completely extract portions of a building that are below a pre-defined building minimum height threshold. This paper proposes a systematic method which analyzes the height differences between the extracted adjacent planes above and below the height threshold as well as the planes' connectivity, thereby, extracting all portions belonging to buildings more completely. In general, the height difference between the edges of the adjacent planes above and below the height threshold that belong to the same building is more uniform. In addition, the extracted planes below the height threshold that belong to a building and their adjacent ground planes also have a clear height difference. The proposed method incorporates such information to achieve better performance in building extraction. We have compared our proposed method to a current state-of-the-art building extraction method qualitatively and quantitatively. Our experimental results show that our proposed method successfully recovers portions of a building below the height threshold, thereby achieving relatively higher average completeness (an improvement of 1.14%) and quality (an improvement of 0.93%).
Description:
This paper presents a new LiDAR segmentation technique for automatic building detection and roof plane extraction. First, it uses a height threshold, based on the digital elevation model it divides the LiDAR point cloud into 'ground' and 'non-ground' points. Then, starting from the maximum LiDAR height, and decreasing the height at each iteration, it looks for points to form planar roof segments. At each height level, it clusters the points based on the distance and finds straight lines using the points. The nearest coplanar point to the midpoint of each line is used as a seed point and the plane is grown in a region growing fashion. Finally, a rule-based procedure is followed to remove planar segments in trees. The experimental results show that the proposed technique offers a high building detection and roof plane extraction rates while compared to other recently proposed techniques.
Description:
At Deakin, the Humanities Networked Infrastructure project (HuNI), has paved new ground for facilitating the effective use and re-use of humanities research data. HuNI is one of the first largescale eResearch infrastructure projects for the humanities in Australia and the first national, crossdisciplinary Virtual Laboratory (VL) worldwide. HuNI provides new information infrastructure services for both humanities researchers and members of the public. Its development has been funded by the National eResearch Collaboration Tools and Resources project (NeCTAR) and undertaken by a consortium of thirteen institutions led by Deakin University. A Deakin University Library team with skills in data description, curation, retrieval and preservation is exploring with digital humanities researchers and developers effective means to support and maintain the HuNI project. HuNI ingests and aggregates data from a total of 31 different Australian cultural datasets which cover a wide range of disciplines in the humanities and creative arts. The HuNI VL also provides a number of online research capabilities for humanities researchers to discover and work with the large-scale aggregation of data. The HuNI VL enables researchers to create, save and publish selections of data; to analyse and manipulate the data; share findings and to export the data for reuse in external environments. In a major innovation, HuNI also enables researchers to assert relationships between entities in the form of ‘socially linked’ data. This capability contributes to the building of a ‘vernacular’ network of associations between HuNI records that embody diverse perspectives on knowledge and ramify avenues for research discovery beyond keyword and phrase searches. This paper reports on key milestones in this project, the future role of Libraries as digital humanities research partners and the challenges and sustainability issues that face national digital humanities research projects that are developed in strategic library settings.
Description:
At Deakin, the Humanities Networked Infrastructure project (HuNI), has paved new ground for facilitating the effective use and re-use of humanities research data. HuNI is one of the first largescale eResearch infrastructure projects for the humanities in Australia and the first national, crossdisciplinary Virtual Laboratory (VL) worldwide. HuNI provides new information infrastructure services for both humanities researchers and members of the public. Its development has been funded by the National eResearch Collaboration Tools and Resources project (NeCTAR) and undertaken by a consortium of thirteen institutions led by Deakin University. A Deakin University Library team with skills in data description, curation, retrieval and preservation is exploring with digital humanities researchers and developers effective means to support and maintain the HuNI project. HuNI ingests and aggregates data from a total of 31 different Australian cultural datasets which cover a wide range of disciplines in the humanities and creative arts. The HuNI VL also provides a number of online research capabilities for humanities researchers to discover and work with the large-scale aggregation of data. The HuNI VL enables researchers to create, save and publish selections of data; to analyse and manipulate the data; share findings and to export the data for reuse in external environments. In a major innovation, HuNI also enables researchers to assert relationships between entities in the form of ‘socially linked’ data. This capability contributes to the building of a ‘vernacular’ network of associations between HuNI records that embody diverse perspectives on knowledge and ramify avenues for research discovery beyond keyword and phrase searches. This paper reports on key milestones in this project, the future role of Libraries as digital humanities research partners and the challenges and sustainability issues that face national digital humanities research projects that are developed in strategic library settings.
Description:
Sensitivity analysis results are presented to investigate the presence of single–phase rooftop Photovoltaic Cells (PV) in low voltage residential feeders, during short circuits in the overhead lines. The PV rating and location in the feeder and the fault location are considered as the variables of the sensitivity analysis. The single–phase faults are the main focus of this paper and the PV effect on fault current, current in distribution transformer secondary and the voltage at each bus of the feeder are investigated, during fault. Furthermore, to analyze the bus voltages and fault current in the presence of multiple PVs, each with different rating and location, a stochastic analysis is carried out to investigate the expected probability density function of these parameters, considering the uncertainties of PV rating and location as well as fault location.
Description:
Sensitivity analysis results are presented to investigate the presence of single–phase rooftop Photovoltaic Cells (PV) in low voltage residential feeders, during short circuits in the overhead lines. The PV rating and location in the feeder and the fault location are considered as the variables of the sensitivity analysis. The single–phase faults are the main focus of this paper and the PV effect on fault current, current in distribution transformer secondary and the voltage at each bus of the feeder are investigated, during fault. Furthermore, to analyze the bus voltages and fault current in the presence of multiple PVs, each with different rating and location, a stochastic analysis is carried out to investigate the expected probability density function of these parameters, considering the uncertainties of PV rating and location as well as fault location.
Description:
Recently, researchers show that the handwritten digit recognition is a challenging problem. In this paper first, we introduce a Modified Self Organizing Maps for vector quantization problem then we present a Convolutional Recursive ModifiedSOMto the problem of handwritten digit recognition. TheModifiedSOMis novel in the sense of initialization process and the topology preservation. The experimental result on the well known digit database of MNIST, denotes the superiority of the proposed algorithm over the existing SOM-based methods.
Description:
In recent years, the drive for the Healthcare Monitoring Application (HMA) aims to provide continuous remote monitoring of a patient's health. For this to happen, the sensors in the monitoring component of the Body Area Wireless Sensor Networks (BAWSN) need to continuously send data to a Healthcare Application. We show that to provide continuous health data, the BAWSN depends on the collective data delivered by all the sensor nodes and not on a single sensor because medical diagnosis is rarely performed from a single data point. In addition, the arrival time of data should occur within the expected time to be indicative of the actual health of the patient. In this paper, we characterize the HMA as a time-critical application because the BAWSN has stringent timing requirements concerning the arrival of data from the sensor nodes within the defined critical time. Thereby, we formulate the critical time parameters to evaluate the BAWSN operations.
Description:
Frequency response analysis (FRA) has become a widely accepted tool to detect power transformer winding deformation due to the development of FRA test equipment. Because FRA relies on graphical analysis, interpretation of its signature is a very specialized area that calls for skilled personnel, as so far, there is no reliable standard code for FRA signature classification and quantification. Many researchers investigated the impact of various mechanical winding deformations on the transformer FRA signature by changing particular electrical parameters of the transformer equivalent electrical circuit. None of them however, investigated the impact of physical fault levels on the transformer FRA signature as it is very difficult to implement faults within real transformer without damaging it. In this paper, the physical geometrical dimension of a power transformer is simulated using 3D finite element analysis to emulate the real transformer operation. Physical core deformation and disk space variation are simulated and the impact of each fault on the transformer FRA signature is investigated.
Description:
An algal response model is being developed to inform the operational characteristics of a water supply system. The intent of this research is to refocus approaches to water allocations from a contest over volume, towards a cooperative approach between all users with multiple socioeconomic and environmental benefits. The algal response model will ultimately be used to aid in the development of a framework, and operational principles, to configure consumptive water transfers to complement dedicated environmental flows. A constraint imposed within this framework will be that whilst providing beneficial environmental outcomes, any flow configuration identified will not compromise consumptive water users. Field trials have begun in the MacKenzie River in western Victoria, Australia. This River has experienced a highly modified flow regime since the construction of Wartook Reservoir in 1887. Water released from the reservoir is regulated at several locations for water supply and also, more recently, for the specific provision of environmental flows. With baseline monitoring of the waterway now completed, preliminary results are available to commence evaluating the complex environmental response patterns and benefits that may accrue from flows dedicated to consumptive use. A number of artificial substrates have also been deployed to elicit the broadest range of responses from algal communities present in the waterway.
Description:
Doubly Fed Induction Generators (DFIGs) are widely used in variable speed wind turbine owing to its superior advantages that include ability to extract more energy from turbine, capability to control active and reactive power independently and the use of reduced converter rating that reduces its overall cost. On the other side fluctuating output power, weak fault ride through capability and high sensitivity to grid disturbances are the main issues that affect DFIG performance. In this paper, superconducting magnetic energy storage (SMES) unit is proposed to improve the fault ride through (FRT) capability of DFIG-based wind energy conversion system (WECS) during voltage sag and voltage swell events in the grid side. A new control approach for SMES unit using hysteresis current controller (HCC) along with proportional integral (PI) controller is introduced. Australian grid codes are used to examine the capability of the proposed controller to improve the FRT of the DFIG and hence maintaining the wind turbine connection to the grid during studied faults. Simulations results show the effectiveness of the SMES controller in maintaining system parameters within safety margins that comply with the Australian grid codes.
Description:
UV Spectrophotometry is a non-intrusive test that can be employed to determine power transformer’s integrity. Light transmitted through transformer oil sample containing various contaminations is decreased by that fraction being absorbed and is detected as a function of wavelength. This paper investigates the impact of various contaminations and oil properties such as water content, acidity, interfacial tension and average voltage breakdown on the spectral response of the transformer oil. In this regard, various transformer oil samples are collected from in-service transformers and the aforementioned parameters are measured. Same oil samples are scanned with UV-Vis spectroscopic and the spectral responses are obtained and analysed.
Description:
With the growing demands for 3D and multi-view video content, efficient depth data coding becomes a vital issue in image and video coding area. In this paper, we propose a simple depth coding scheme using multiple prediction modes exploiting temporal correlation of depth map. Current depth coding techniques mostly depend on intra-coding mode that cannot get the advantage of temporal redundancy in the depth maps and higher spatial redundancy in inter-predicted depth residuals. Depth maps are characterized by smooth regions with sharp edges that play an important role in the view synthesis process. As depth maps are more sensitive to coding errors, use of transformation or approximation of edges by explicit edge modelling has impact on view synthesis quality. Moreover, lossy compression of depth map brings additional geometrical distortion to synthetic view. In this paper, we have demonstrated that encoding inter-coded depth block residuals with quantization at pixel domain is more efficient than the intra-coding techniques relying on explicit edge preservation. On standard 3D video sequences, the proposed depth coding has achieved superior image quality of synthesized views against the new 3D-HEVC standard for depth map bit-rate 0.25 bpp or higher.
Description:
High Efficiency Video Coding (HEVC) standard introduces a number of innovative tools which can reduce approximately 50% bit-rate compared to its predecessor H.264/AVC at the same perceptual video quality whereas the computational time has increased multiple times. To reduce the encoding time while preserving the expected video quality has become a real challenge today for video transmission and streaming especially using low-powered devices. Motion estimation (ME) and motion compensation (MC) using variable-size blocks (i.e., intermodes) require 60-80% of total computational time. In this paper we propose a new efficient intermode selection technique based on phase correlation and incorporate into HEVC framework to predict ME and MC modes and perform faster intermode selection based on three dissimilar motion types in different videos. Instead of exploring all the modes exhaustively we select a subset of modes using motion type and the final mode is selected based on the Lagrangian cost function. The experimental results show that compared to HEVC the average computational time can be downscaled by 34% while providing the similar rate-distortion (RD) performance.
Description:
High Efficiency Video Coding (HEVC) standard introduces a number of innovative tools which can reduce approximately 50% bit-rate compared to its predecessor H.264/AVC at the same perceptual video quality whereas the computational time has increased multiple times. To reduce the encoding time while preserving the expected video quality has become a real challenge today for video transmission and streaming especially using low-powered devices. Motion estimation (ME) and motion compensation (MC) using variable-size blocks (i.e., intermodes) require 60-80% of total computational time. In this paper we propose a new efficient intermode selection technique based on phase correlation and incorporate into HEVC framework to predict ME and MC modes and perform faster intermode selection based on three dissimilar motion types in different videos. Instead of exploring all the modes exhaustively we select a subset of modes using motion type and the final mode is selected based on the Lagrangian cost function. The experimental results show that compared to HEVC the average computational time can be downscaled by 34% while providing the similar rate-distortion (RD) performance.