2Loud?: Community mapping of exposure to traffic noise with mobile phones

Abstract: Despite ample medical evidence of the adverse impacts of traffic noise on health, most policies for traffic noise management are arbitrary or incomplete, resulting in serious social and economic impacts. Surprisingly, there is limited information about citizen’s exposure to traffic noise worldwide. This paper presents the 2Loud? mobile phone application, developed and tested as a methodology to monitor, assess and map the level of exposure to traffic noise of citizens with focus on the night period and indoor locations, since sleep disturbance is one of the major triggers for ill health related to traffic noise. Based on a community participation experiment using the 2Loud? mobile phone application in a region close to freeways in Australia, the results of this research indicates a good level of accuracy for the noise monitoring by mobile phones and also demonstrates significant levels of indoor night exposure to traffic noise in the study area. The proposed methodology, through the data produced and the participatory process involved, can potentially assist in planning and management towards healthier urban environments.

Participatory sensing and education: helping the community mitigate sleep disturbance from traffic noise

Purpose – This paper aims to present a project in Australia, where participants use smartphones to measure the level of traffic noise in their homes. Through the data collected, participants learn if they are subjected to sleep disturbances and, if so, understand how they can manage the issue to protect their health. The project also has a secondary purpose: the local council would like to engage its community through the exercise and be seen as acting on the community’s problems.

Neuron’s spikes noise level classification using hidden markov models

Considering that the uncertainty noise produced the decline in the quality of collected neural signal, this paper proposes a signal quality assessment method for neural signal. The method makes an automated measure to detect the noise levels in neural signal. Hidden Markov Models were used to build a classification model that classifies the neural spikes based on the noise level associated with the signal. This neural quality assessment measure will help doctors and researchers to focus on the patterns in the signal that have high signal to noise ratio and carry more information.

Sparse coding for improved signal-to-noise ratio in MRI

Magnetic Resonance images (MRI) do not only exhibit sparsity but their sparsity take a certain predictable shape which is common for all kinds of images. That region based localised sparsity can be used to de-noise MR images from random thermal noise. This paper present a simple framework to exploit sparsity of MR images for image de-noising. As, noise in MR images tends to change its shape based on contrast level and signal itself, the proposed method is independent of noise shape and type and it can be used in combination with other methods.

Changing listening frequency to minimise white noise and hear indigenous voices

Listening… can involve the listener in an intense, efficacious, and complex set of communicative acts in which one is not speaking, discussing, or disclosing, but sitting quietly, watching, and feeling-the-place, through all the senses…. In the process, one becomes a part of the scene, hearing and feeling with it (Carbaugh 1999: 259).To listen this way involves much more than providing a chance for words to be spoken; it includes tuning in and getting the listening frequency clear. As a non-Indigenous person seeking to conduct qualitative research that listens to Aboriginal people, I need to ask how I can tune into the “active attentiveness” described by Carbaugh (1999) in order to listen in a manner that is appropriate, respectful and minimises my inherent white privilege. In addressing this question I draw on the work of Indigenous authors and academics, critical whiteness studies and my own experiences learning from Aboriginal people in a number of contexts over the past ten to fifteen years.History in Australia since colonization has created a situation where Aboriginal voices are white noise to the ears of many non-Indigenous people. This paper proposes that white privilege and the resulting white noise can be minimised and greater clarity given to Aboriginal voices by privileging Indigenous knowledge and ways of working when addressing Indigenous issues. To minimise the interference of white noise, non-Indigenous people would do well to adopt a position that recognises, acknowledges and utilises some of the strengths that can be learned from Aboriginal culture and Indigenous authors.This paper outlines a model of apprentice, allied listening for non-Indigenous researchers to adopt when preparing to conduct research alongside Indigenous people. Such an approach involves Re-learning of history, Reviewing of the researcher’s beliefs and placing Relating at the centre of the listening approach. Each of these aspects of listening is based on privileging of Indigenous voices.

Faster than the speed of white (noise): potential pressure points in research partnerships and processes

White noise occurs in the thinking, decision making and communication of dominant Settler cultures. It inhibits clear reception of messages, somewhat like the indistinct, fuzzy static of an un-tuned radio. As much a systemic issue as an individual one, it results from assumed privilege and lack of knowledge of worldviews other than the dominant. Until white noise is acknowledged, development of partnerships between Indigenous and non-Indigenous groups is likely to be limited by having to continually start at a point of inequality where nonIndigenous gaps in knowledge and understanding remain unrecognised. This paper/workshop considers challenges encountered while researching experiences of Aboriginal education in Western Australian prisons. Each pressure point occurred where the dominant world view prevailed without question. Discussion will focus on the specific pressure points of ethics approval, project development, informed consent and application of outcomes and findings. The paper asks the questions ‘Who decides what stories are created at these pressure points? What informs those stories?’ As individuals, we might not be able to crash through the white noise barrier but we can chip away and be transparent about its existence with the goal of eventually moving faster than the speed of white (noise).

Farmers’ work-day noise exposure

Objective: This study aims to understand the extent offarmers’ exposure to hazardous noise, and trial and testthe ability of an on-farm noise audit report to improve awareness and preventative action towards farm based noise hazards.Design: Visits were made to working farms where noiseand dosimetry measurements undertaken. During return visits, the noise measurements were explained ina brief report. A follow-up questionnaire was imple-mented gathering feedback on the use or otherwise ofthe report.Setting: Working farms in Western Victoria and SEQueensland including dairy, beef, wool, prime lamb andcropping.Participants: Participants were 14 female and 37 male farm workers.Interventions: Noise exposure assessment of dailyactivities through dosimetry; measurements of noisy tasks and machinery; supply and interpretation of anoise audit report.Main outcome measures: Participants were suppliedwith a ‘noise report’ of their workplace together with an explanation of the report’s meaning to farm workers.Results: Men and women have similar at risk expo-sures. The average noise exposure was 1.09 Pa2h(LAeq,8h= 85.3 dB). This implies 163 000 Australian agricultural workers are at risk from hazardous noise.On-farm noise audit reports were a relevant and valuable feedback to farmers in relation to their potential noise hazards.Conclusions: Of those measured 51%, and by extrapo-lation 163 000 Australian agricultural workers, have noise exposure levels greater than the recommendedAustralian Standard of 1.01 Pa2h (85 dB). Men and women are equally exposed. On-farm noise auditreports are an effective feedback to increase awareness and improve hearing health

Noise level classification for EEG using Hidden Markov Models

EEG signal is one of the most important signals for diagnosing some diseases. EEG is always recorded with an amount of noise, the more noise is recorded the less quality is the EEG signal. The included noise can represent the quality of the recorded EEG signal, this paper proposes a signal quality assessment method for EEG signal. The method generates an automated measure to detect the noise level of the recorded EEG signal. Mel-Frequency Cepstrum Coefficient is used to represent the signals. Hidden Markov Models were used to build a classification model that classifies the EEG signals based on the noise level associated with the signal. This EEG quality assessment measure will help doctors and researchers to focus on the patterns in the signal that have high signal to noise ratio and carry more information. Moreover, our model was applied on an uncontrolled environment and on controlled environment and a result comparison was applied.

Population, behavioural and physiological responses of an urban population of black swans to an intense annual noise event

Wild animals in urban environments are exposed to a broad range of human activities that have the potential to disturb their life history and behaviour. Wildlife responses to disturbance can range from emigration to modified behaviour, or elevated stress, but these responses are rarely evaluated in concert. We simultaneously examined population, behavioural and hormonal responses of an urban population of black swans Cygnus atratus before, during and after an annual disturbance event involving large crowds and intense noise, the Australian Formula One Grand Prix. Black swan population numbers were lowest one week before the event and rose gradually over the course of the study, peaking after the event, suggesting that the disturbance does not trigger mass emigration. We also found no difference in the proportion of time spent on key behaviours such as locomotion, foraging, resting or self-maintenance over the course of the study. However, basal and capture stress-induced corticosterone levels showed significant variation, consistent with a modest physiological response. Basal plasma corticosterone levels were highest before the event and decreased over the course of the study. Capture-induced stress levels peaked during the Grand Prix and then also declined over the remainder of the study. Our results suggest that even intensely noisy and apparently disruptive events may have relatively low measurable short-term impact on population numbers, behaviour or physiology in urban populations with apparently high tolerance to anthropogenic disturbance. Nevertheless, the potential long-term impact of such disturbance on reproductive success, individual fitness and population health will need to be carefully evaluated.

Knowledge disclosure as a weapon in technological change battles: straight shot or backfire?

This work aims at evaluating how effective is knowledge disclosure in attenuating institutional negative reactions caused by uncertainties brought by firms’ new strategies that respond to novel technologies. The empirical setting is from an era of technological ferment, the period of the introduction of the voice over internet protocol (VoIP) in the USA in the early 2000’s. This technology led to the convergence of the wireline telecommu- nications and cable television industries. The Institutional Brokers’ Estimate System (also known as the I/B/E/S system) was used to capture reactions of securities analysts, a revealed important source of institutional pressure on firms’ strategies. For assessing knowledge disclosure, a coding technique and a established content analysis framework were used to quantitatively measure the non-numerical and unstructured data of transcripts of business events occurred at that time. Eventually, several binary response models were tested in order to assess the effect of knowledge disclosure on the probability of institutional positive reactions. The findings are that the odds of favorable institutional reactions increase when a specific kind of knowledge is disclosed. It can be concluded that knowledge disclosure can be considered as a weapon in technological changes situations, attenuating adverse institutional reactions to the companies’ strategies in environments of technological changes.

Transfer function-noise modeling and spatial interpolation to evaluate the risk of extreme (shallow) water-table levels in the Brazilian Cerrados

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)