Clipping noise compensation for OFDMA systems

This paper presents an efficient low-complexity clipping noise compensation scheme for PAR reduced orthogonal frequency division multiple access (OFDMA) systems. Conventional clipping noise compensation schemes proposed for OFDM systems are decision directed schemes which use demodulated data symbols. Thus these schemes fail to deliver expected performance in OFDMA systems where multiple users share a single OFDM symbol and a specific user may only know his/her own modulation scheme. The proposed clipping noise estimation and compensation scheme does not require the knowledge of the demodulated symbols of the other users, making it very promising for OFDMA systems. It uses the equalized output and the reserved tones to reconstruct the signal by compensating the clipping noise. Simulation results show that the proposed scheme can significantly improve the system performance.

Nation & internation practices in decision support tools in road asset management

This document provides a review of international and national practices in investment decision support tools in road asset management. Efforts were concentrated on identifying analytic frameworks, evaluation methodologies and criteria adopted by current tools. Emphasis was also given to how current approaches support Triple Bottom Line decision-making. Benefit Cost Analysis and Multiple Criteria Analysis are principle methodologies in supporting decision-making in Road Asset Management. The complexity of the applications shows significant differences in international practices. There is continuing discussion amongst practitioners and researchers regarding to which one is more appropriate in supporting decision-making. It is suggested that the two approaches should be regarded as complementary instead of competitive means. Multiple Criteria Analysis may be particularly helpful in early stages of project development, say strategic planning. Benefit Cost Analysis is used most widely for project prioritisation and selecting the final project from amongst a set of alternatives. Benefit Cost Analysis approach is useful tool for investment decision-making from an economic perspective. An extension of the approach, which includes social and environmental externalities, is currently used in supporting Triple Bottom Line decision-making in the road sector. However, efforts should be given to several issues in the applications. First of all, there is a need to reach a degree of commonality on considering social and environmental externalities, which may be achieved by aggregating the best practices. At different decision-making level, the detail of consideration of the externalities should be different. It is intended to develop a generic framework to coordinate the range of existing practices. The standard framework will also be helpful in reducing double counting, which appears in some current practices. Cautions should also be given to the methods of determining the value of social and environmental externalities. A number of methods, such as market price, resource costs and Willingness to Pay, are found in the review. The use of unreasonable monetisation methods in some cases has discredited Benefit Cost Analysis in the eyes of decision makers and the public. Some social externalities, such as employment and regional economic impacts, are generally omitted in current practices. This is due to the lack of information and credible models. It may be appropriate to consider these externalities in qualitative forms in a Multiple Criteria Analysis. Consensus has been reached in considering noise and air pollution in international practices. However, Australia practices generally omitted these externalities. Equity is an important consideration in Road Asset Management. The considerations are either between regions, or social groups, such as income, age, gender, disable, etc. In current practice, there is not a well developed quantitative measure for equity issues. More research is needed to target this issue. Although Multiple Criteria Analysis has been used for decades, there is not a generally accepted framework in the choice of modelling methods and various externalities. The result is that different analysts are unlikely to reach consistent conclusions about a policy measure. In current practices, some favour using methods which are able to prioritise alternatives, such as Goal Programming, Goal Achievement Matrix, Analytic Hierarchy Process. The others just present various impacts to decision-makers to characterise the projects. Weighting and scoring system are critical in most Multiple Criteria Analysis. However, the processes of assessing weights and scores were criticised as highly arbitrary and subjective. It is essential that the process should be as transparent as possible. Obtaining weights and scores by consulting local communities is a common practice, but is likely to result in bias towards local interests. Interactive approach has the advantage in helping decision-makers elaborating their preferences. However, computation burden may result in lose of interests of decision-makers during the solution process of a large-scale problem, say a large state road network. Current practices tend to use cardinal or ordinal scales in measure in non-monetised externalities. Distorted valuations can occur where variables measured in physical units, are converted to scales. For example, decibels of noise converts to a scale of -4 to +4 with a linear transformation, the difference between 3 and 4 represents a far greater increase in discomfort to people than the increase from 0 to 1. It is suggested to assign different weights to individual score. Due to overlapped goals, the problem of double counting also appears in some of Multiple Criteria Analysis. The situation can be improved by carefully selecting and defining investment goals and criteria. Other issues, such as the treatment of time effect, incorporating risk and uncertainty, have been given scant attention in current practices. This report suggested establishing a common analytic framework to deal with these issues.

Evaluation of valuation of noise amelioration treatments within and outside the road reserve

In urban environments road traffic volumes are increasing and the density of living is becoming higher. As a consequence the urban community is being exposed to increasing levels of road traffic noise. It is also evident that the noise reduction potential of within-the-road-reserve treatments such as noise barriers, mounding and pavement surfacing has been exhausted. This paper presents a strategy that involves the comparison of noise ameliorative treatments both within and outside the road reserve. The noise reduction resulting from the within-the-road-reserve component of treatments has been evaluated using a leading application of the CoRTN Model, developed by the UK Department of Transport 1988 [1], and the outside road reserve treatment has been evaluated in accordance with the Australian Standard 3671, Acoustics – Road traffic noise intrusion – Building sitting and construction [5]. The evaluation of noise treatments has been undertaken using a decision support tool (DST) currently being developed under the research program conducted at RMIT University and Department of Main Roads, Queensland. The case study has been based on data from a real project in Queensland, Australia. The research described here was carried out by the Australian Cooperative Research Centre for Construction Innovation [9], in collaboration with Department of Main Roads, Queensland, Department of Public Works, Queensland, Arup Pty. Ltd., Queensland University of technology and RMIT University.

Creating a proactive decision-support environment in managing road traffic noise

Properly designed decision support environments encourage proactive and objective decision making. The work presented in this paper inquires into developing a decision support environment and a tool to facilitate objective decision making in dealing with road traffic noise. The decision support methodology incorporates traffic amelioration strategies both within and outside the road reserve. The project is funded by the CRC for Construction Innovation and conducted jointly by the RMIT University and the Queensland Department of Main Roads (MR) in collaboration with the Queensland Department of Public Works, Arup Pty Ltd., and the Queensland University of Technology. In this paper, the proposed decision support framework is presented in the way of a flowchart which enabled the development of the decision support tool (DST). The underpinning concept is to establish and retain an information warehouse for each critical road segment (noise corridor) for a given planning horizon. It is understood that, in current practice, some components of the approach described are already in place but not fully integrated and supported. It provides an integrated user-friendly interface between traffic noise modeling software, noise management criteria and cost databases.

Estimation and compensation of clipping noise in OFDMA systems

We propose an efficient and low-complexity scheme for estimating and compensating clipping noise in OFDMA systems. Conventional clipping noise estimation schemes, which need all demodulated data symbols, may become infeasible in OFDMA systems where a specific user may only know his own modulation scheme. The proposed scheme first uses equalized output to identify a limited number of candidate clips, and then exploits the information on known subcarriers to reconstruct clipped signal. Simulation results show that the proposed scheme can significantly improve the system performance.

Evaluation of multiple sewage-associated bacteroides PCR markers for sewage pollution tracking

The host specificity of the five published sewage-associated Bacteroides markers (i.e., HF183, BacHum, HuBac, BacH and Human-Bac) was evaluated in Southeast Queensland, Australia by testing fecal DNA samples (n = 186) from 11 animal species including human fecal samples collected via influent to a sewage treatment plant (STP). All human fecal samples (n = 50) were positive for all five markers indicating 100% sensitivity of these markers. The overall specificity of the HF183 markers to differentiate between humans and animals was 99%. The specificities of the BacHum and BacH markers were > 94%, suggesting that these markers are suitable for sewage pollution in environmental waters in Australia. The BacHum (i.e., 63% specificity) and Human-Bac (i.e., 79% specificity) markers performed poorly in distinguishing between the sources of human and animal fecal samples. It is recommended that the specificity of the sewage-associated markers must be rigorously tested prior to its application to identify the sources of fecal pollution in environmental waters.

Microphone array shape calibration in diffuse noise fields

This correspondence presents a microphone array shape calibration procedure for diffuse noise environments. The procedure estimates intermicrophone distances by fitting the measured noise coherence with its theoretical model and then estimates the array geometry using classical multidimensional scaling. The technique is validated on noise recordings from two office environments.

Empirical Evidence Showing The Relationships Between Three Approaches for Pollution Control

Willingness to pay models have shown the theoretical relationships between the contingent valuation, cost of illness and the avertive behaviour approaches. In this paper, field survey data are used to compare the relationships between these three approaches and to demonstrate that contingent valuation bids exceed the sum of cost of illness and the avertive behaviour approach estimates. The estimates provide a validity check for CV bids and further support the claim that contingent valuation studies are theoretically consistent.

Evaluating sewage associated JCV and BKV polyomaviruses for sourcing human fecal pollution in a coastal river in Southeast Queensland Australia

In this study, the host-sensitivity and -specificity of JCV and BKV polyomaviruses were evaluated by testing wastewater/fecal samples from nine host groups in Southeast Queensland, Australia. The JCV and BKV polyomaviruses were detected in 48 human wastewater samples collected from the primary and secondary effluent suggesting high sensitivity of these viruses in human wastewater. Of the 81 animal wastewater/fecal samples tested, 80 were PCR negative for this marker. Only one sample from pig wastewater was positive. Nonetheless, the overall host-specificity of these viruses to differentiate between human and animal wastewater/fecal samples was 0.99. To our knowledge, this is the first study in Australia that reports the high specificity of JCV and BKV polyomaviruses. To evaluate the field application of these viruses to detect human fecal pollution, 20 environmental samples were collected from a coastal river. Of the 20 samples tested, 15% and 70% samples exceeded the regulatory guidelines for E. coli and enterococci levels for marine waters. In all, 5 (25%) samples were PCR positive for JCV and BKV indicated the presence of human fecal pollution in the studied river. The results suggest that JCV and BKV detection using PCR could be a useful tool for the identification of human sourced fecal pollution in coastal waters.

GIS-based mapping and statistical analysis of air pollution and mortality in Brisbane, Australia

In this thesis, the relationship between air pollution and human health has been investigated utilising Geographic Information System (GIS) as an analysis tool. The research focused on how vehicular air pollution affects human health. The main objective of this study was to analyse the spatial variability of pollutants, taking Brisbane City in Australia as a case study, by the identification of the areas of high concentration of air pollutants and their relationship with the numbers of death caused by air pollutants. A correlation test was performed to establish the relationship between air pollution, number of deaths from respiratory disease, and total distance travelled by road vehicles in Brisbane. GIS was utilized to investigate the spatial distribution of the air pollutants. The main finding of this research is the comparison between spatial and non-spatial analysis approaches, which indicated that correlation analysis and simple buffer analysis of GIS using the average levels of air pollutants from a single monitoring station or by group of few monitoring stations is a relatively simple method for assessing the health effects of air pollution. There was a significant positive correlation between variable under consideration, and the research shows a decreasing trend of concentration of nitrogen dioxide at the Eagle Farm and Springwood sites and an increasing trend at CBD site. Statistical analysis shows that there exists a positive relationship between the level of emission and number of deaths, though the impact is not uniform as certain sections of the population are more vulnerable to exposure. Further statistical tests found that the elderly people of over 75 years age and children between 0-15 years of age are the more vulnerable people exposed to air pollution. A non-spatial approach alone may be insufficient for an appropriate evaluation of the impact of air pollutant variables and their inter-relationships. It is important to evaluate the spatial features of air pollutants before modeling the air pollution-health relationships.

The effect of dialect mismatch on likelihood-maximising speech enhancement for noise-robust speech recognition

Traditional speech enhancement methods optimise signal-level criteria such as signal-to-noise ratio, but these approaches are sub-optimal for noise-robust speech recognition. Likelihood-maximising (LIMA) frameworks are an alternative that optimise parameters of enhancement algorithms based on state sequences generated for utterances with known transcriptions. Previous reports of LIMA frameworks have shown significant promise for improving speech recognition accuracies under additive background noise for a range of speech enhancement techniques. In this paper we discuss the drawbacks of the LIMA approach when multiple layers of acoustic mismatch are present – namely background noise and speaker accent. Experimentation using LIMA-based Mel-filterbank noise subtraction on American and Australian English in-car speech databases supports this discussion, demonstrating that inferior speech recognition performance occurs when a second layer of mismatch is seen during evaluation.

The relationship between particulate air pollution and emergency hospital visits for hypertension in Beijing, China

BACKGROUND: A number of epidemiological studies have examined the adverse effect of air pollution on mortality and morbidity. Also, several studies have investigated the associations between air pollution and specific-cause diseases including arrhythmia, myocardial infarction, and heart failure. However, little is known about the relationship between air pollution and the onset of hypertension. OBJECTIVE: To explore the risk effect of particulate matter air pollution on the emergency hospital visits (EHVs) for hypertension in Beijing, China. METHODS: We gathered data on daily EHVs for hypertension, fine particulate matter less than 2.5 microm in aerodynamic diameter (PM(2.5)), particulate matter less than 10 microm in aerodynamic diameter (PM(10)), sulfur dioxide, and nitrogen dioxide in Beijing, China during 2007. A time-stratified case-crossover design with distributed lag model was used to evaluate associations between ambient air pollutants and hypertension. Daily mean temperature and relative humidity were controlled in all models. RESULTS: There were 1,491 EHVs for hypertension during the study period. In single pollutant models, an increase in 10 microg/m(3) in PM(2.5) and PM(10) was associated with EHVs for hypertension with odds ratios (overall effect of five days) of 1.084 (95% confidence interval (CI): 1.028, 1.139) and 1.060% (95% CI: 1.020, 1.101), respectively. CONCLUSION: Elevated levels of ambient particulate matters are associated with an increase in EHVs for hypertension in Beijing, China.