Analytical model for fault section estimation and state identification of unobserved protective relays in power systems [电力系统故障诊断与不可观测保护状态识别的解析模型]

In recent years, some models have been proposed for the fault section estimation and state identification of unobserved protective relays (FSE-SIUPR) under the condition of incomplete state information of protective relays. In these models, the temporal alarm information from a faulted power system is not well explored although it is very helpful in compensating the incomplete state information of protective relays, quickly achieving definite fault diagnosis results and evaluating the operating status of protective relays and circuit breakers in complicated fault scenarios. In order to solve this problem, an integrated optimization mathematical model for the FSE-SIUPR, which takes full advantage of the temporal characteristics of alarm messages, is developed in the framework of the well-established temporal constraint network. With this model, the fault evolution procedure can be explained and some states of unobserved protective relays identified. The model is then solved by means of the Tabu search (TS) and finally verified by test results of fault scenarios in a practical power system.

Identification of key environmental issues for building materials

Manufacture, construction and use of buildings and building materials make a significant environmental impact internally (inside the building), locally (neighbourhood) and globally. Life cycle assessment (LCA) methodology is being applied for evaluating the environmental impact of building/or building materials. One of the major applications of LCA is to identify key issues of a product system from cradle to grave. Key issues identified in an LCA lead one to the right direction in assessing the environmental aspects of a product system and help to identify the areas for improvement of the environmental performance of a product as well. The purpose of this paper is to suggest two methods for identifying key issues using an integrated tool (LCADesign), which has been developed to provide a method of determining the best alternative for reducing environmental impacts from a building or building materials, and compare both methods in the case study. This paper assists the designers or marketers related to building or building materials in their decision making by giving information on activities or alternatives which are identified as key issues for environmental impacts.

Identification of barriers to and facilitators for the implementation of occupational road safety initiatives

To explore potential barriers to and facilitators for implementing occupational road safety initiatives, in-depth interviews were conducted with personnel from four major Australian organizations. Twenty-four participants were involved in the interviews comprising 16 front line employees and eight managers. The interviews identified that employees perceived six organizational characteristics as potential barriers to implementing occupational road safety initiatives. These included: prioritisation of production over safety; complacency towards occupational road risks; insufficient resources; diversity; limited employee input in safety decisions; and a perception that road safety initiatives were an unnecessary burden. Of these organizational characteristics, prioritisation of production over safety and complacency were the most frequently cited barriers. In regards to facilitators, participants perceived three organizational characteristics as potential facilitators to implementing occupational road safety initiatives. These included: management commitment; the presence of existing systems that could support the implementation of initiatives; and supportive relationships. Of these organizational characteristics, management commitment was the most frequently cited facilitator.

Identification of alcohol involvement in injury-related hospitalisations using routine data compared to medical record review

Objective: To quantify the extent to which alcohol related injuries are adequately identified in hospitalisation data using ICD-10-AM codes indicative of alcohol involvement. Method: A random sample of 4373 injury-related hospital separations from 1 July 2002 to 30 June 2004 were obtained from a stratified random sample of 50 hospitals across 4 states in Australia. From this sample, cases were identified as involving alcohol if they contained an ICD-10-AM diagnosis or external cause code referring to alcohol, or if the text description extracted from the medical records mentioned alcohol involvement. Results: Overall, identification of alcohol involvement using ICD codes detected 38% of the alcohol-related sample, whilst almost 94% of alcohol-related cases were identified through a search of the text extracted from the medical records. The resultant estimate of alcohol involvement in injury-related hospitalisations in this sample was 10%. Emergency department records were the most likely to identify whether the injury was alcohol-related with almost three-quarters of alcohol-related cases mentioning alcohol in the text abstracted from these records. Conclusions and Implications: The current best estimates of the frequency of hospital admissions where alcohol is involved prior to the injury underestimate the burden by around 62%. This is a substantial underestimate that has major implications for public policy, and highlights the need for further work on improving the quality and completeness of routine administrative data sources for identification of alcohol-related injuries.

Identification of acoustic emission wave modes for accurate source location in plate-like structures

Acoustic emission (AE) technique is a popular tool used for structural health monitoring of civil, mechanical and aerospace structures. It is a non-destructive method based on rapid release of energy within a material by crack initiation or growth in the form of stress waves. Recording of these waves by means of sensors and subsequent analysis of the recorded signals convey information about the nature of the source. Ability to locate the source of stress waves is an important advantage of AE technique; but as AE waves travel in various modes and may undergo mode conversions, understanding of the modes (‘modal analysis’) is often necessary in order to determine source location accurately. This paper presents results of experiments aimed at finding locations of artificial AE sources on a thin plate and identifying wave modes in the recorded signal waveforms. Different source locating techniques will be investigated and importance of wave mode identification will be explored.

Identification of dispersion-dependent hexagonal cavity modes of an individual ZnO nanonail

The hexagonal resonator characteristics of an individual ZnO-nanonail’s head were investigated via spatially resolved cathodoluminescence (CL) at room temperature. The positions of most of distinct CL peaks in visible range were well matched to those of whispering gallery modes (WGMs) of a hexagonal dielectric cavity when we took birefringence and dispersion of refractive indices into account. The broad and weak peaks for TE polarization in long wavelength range were consistent with refractive-index values below the threshold for total internal inflection. CL peaks that were not matched to WGMs were identified as either triangular quasi-WGM or Fabry–Pérot resonance modes.

Exploring the contested role of mandatory reporting laws in the identification of severe child abuse and neglect

Significant numbers of children are severely abused and neglected by parents and caregivers. Infants and very young children are the most vulnerable and are unable to seek help. To identify these situations and enable child protection and the provision of appropriate assistance, many jurisdictions have enacted ‘mandatory reporting laws’ requiring designated professionals such as doctors, nurses, police and teachers to report suspected cases of severe child abuse and neglect. Other jurisdictions have not adopted this legislative approach, at least partly motivated by a concern that the laws produce dramatic increases in unwarranted reports, which, it is argued, lead to investigations which infringe on people’s privacy, cause trauma to innocent parents and families, and divert scarce government resources from deserving cases. The primary purpose of this paper is to explore the extent to which opposition to mandatory reporting laws is valid based on the claim that the laws produce ‘overreporting’. The first part of this paper revisits the original mandatory reporting laws, discusses their development into various current forms, explains their relationship with policy and common law reporting obligations, and situates them in the context of their place in modern child protection systems. This part of the paper shows that in general, contemporary reporting laws have expanded far beyond their original conceptualisation, but that there is also now a deeper understanding of the nature, incidence, timing and effects of different types of severe maltreatment, an awareness that the real incidence of maltreatment is far higher than that officially recorded, and that there is strong evidence showing the majority of identified cases of severe maltreatment are the result of reports by mandated reporters. The second part of this paper discusses the apparent effect of mandatory reporting laws on ‘overreporting’ by referring to Australian government data about reporting patterns and outcomes, with a particular focus on New South Wales. It will be seen that raw descriptive data about report numbers and outcomes appear to show that reporting laws produce both desirable consequences (identification of severe cases) and problematic consequences (increased numbers of unsubstantiated reports). Yet, to explore the extent to which the data supports the overreporting claim, and because numbers of unsubstantiated reports alone cannot demonstrate overreporting, this part of the paper asks further questions of the data. Who makes reports, about which maltreatment types, and what are the outcomes of those reports? What is the nature of these reports; for example, to what extent are multiple numbers of reports made about the same child? What meaning can be attached to an ‘unsubstantiated’ report, and can such reports be used to show flaws in reporting effectiveness and problems in reporting laws? It will be suggested that available evidence from Australia is not sufficiently detailed or strong to demonstrate the overreporting claim. However, it is also apparent that, whether adopting an approach based on public health and or other principles, much better evidence about reporting needs to be collected and analyzed. As well, more nuanced research needs to be conducted to identify what can reasonably be said to constitute ‘overreports’, and efforts must be made to minimize unsatisfactory reporting practice, informed by the relevant jurisdiction’s context and aims. It is also concluded that, depending on the jurisdiction, the available data may provide useful indicators of positive, negative and unanticipated effects of specific components of the laws, and of the strengths, weaknesses and needs of the child protection system.

A multivariate approach to the identification of surrogate parameters for heavy metals in stormwater

Stormwater is a potential and readily available alternative source for potable water in urban areas. However, its direct use is severely constrained by the presence of toxic pollutants, such as heavy metals (HMs). The presence of HMs in stormwater is of concern because of their chronic toxicity and persistent nature. In addition to human health impacts, metals can contribute to adverse ecosystem health impact on receiving waters. Therefore, the ability to predict the levels of HMs in stormwater is crucial for monitoring stormwater quality and for the design of effective treatment systems. Unfortunately, the current laboratory methods for determining HM concentrations are resource intensive and time consuming. In this paper, applications of multivariate data analysis techniques are presented to identify potential surrogate parameters which can be used to determine HM concentrations in stormwater. Accordingly, partial least squares was applied to identify a suite of physicochemical parameters which can serve as indicators of HMs. Datasets having varied characteristics, such as land use and particle size distribution of solids, were analyzed to validate the efficacy of the influencing parameters. Iron, manganese, total organic carbon, and inorganic carbon were identified as the predominant parameters that correlate with the HM concentrations. The practical extension of the study outcomes to urban stormwater management is also discussed.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the a mission should be aborted due to mechanical or other failure. On-board cameras provide information that can be used in the determination of potential landing sites, which are continually updated and ranked to prevent injury and minimize damage. Pulse Coupled Neural Networks have been used for the detection of features in images that assist in the classification of vegetation and can be used to minimize damage to the aerial vehicle. However, a significant drawback in the use of PCNNs is that they are computationally expensive and have been more suited to off-line applications on conventional computing architectures. As heterogeneous computing architectures are becoming more common, an OpenCL implementation of a PCNN feature generator is presented and its performance is compared across OpenCL kernels designed for CPU, GPU and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images obtained during unmanned aerial vehicle trials to determine the plausibility for real-time feature detection.