Investigations on road noise level spatial variability within a specially designed acoustic balcony

An investigation into the spatial distribution of road traffic noise levels on a balcony is conducted. A balcony constructed to a special acoustic design due to its elevation above an 8 lane motorway is selected for detailed measurements. The as-constructed balcony design includes solid parapets, side walls, ceiling shields and highly absorptive material placed on the ceiling. Road traffic noise measurements are conducted spatially using a five channel acoustic analyzer, where four microphones are located at various positions within the balcony space and one microphone placed outside the parapet at a reference position. Spatial distributions in both vertical and horizontal planes are measured. A theoretical model and prediction configuration is presented that assesses the acoustic performance of the balcony under existing traffic flow conditions. The prediction model implements a combined direct path, specular reflection path and diffuse reflection path utilizing image source and radiosity techniques. Results obtained from the prediction model are presented and compared to the measurement results. The predictions are found to correlate well with measurements with some minor differences that are explained. It is determined that the prediction methodology is acceptable to assess a wider range of street and balcony configuration scenarios.

Development and application of Palygorskite porous ceramsite in a biological aerated filter (BAF)

Novel filter Palygorskite porous ceramsite (PC) was prepared using Palygorskite clay, poreforming material sawdust, and sodium silicate with a mass ratio of 10:2:1 after sintering at 700°C for 180 min. PC was characterized with X-ray diffraction, X-ray fluorescence, scanning electron microscopy, elemental, and porosimetry. PC had a total porosity of 67% and specific surface area of 61 m2/g. In order to assess the usefulness of PC as a medium for biological aerated filters (BAF), PC and (commercially available ceramsite) CAC were used to treat wastewater city in two laboratory-scale upflow BAFs. The results showed that the reactor containing PC was more efficient than the reactor containing CAC in terms of total organic carbon (TOC), ammonia nitrogen (NH3-N), and the removal of total nitrogen (TN) and phosphorus (P). This system was found to be more efficient at water temperatures ranging from 20 to 26°C, an air–water (A/W) ratio of 3:1, dissolved oxygen concentration >4.00 mg/L, and hydraulic retention time (HRT) ranging from 0.5 to 7 h. The interconnected porous structure produced for PC was suitable for microbial growth, and primarily protozoan and metazoan organisms were found in the biofilm. Microorganism growth also showed that, under the same submerged culture conditions, the biological mass in PC was significantly higher than in CAC (34.1 and 2.2 mg TN/g, respectively). In this way, PC media can be considered suitable for the use as a medium in novel biological aerated filters for the simultaneous removal of nitrogen and phosphorus.

Effects of different surfaces on the perception of prey-generated noise by the Indian false vampire bat Megaderma lyra.

The low- and high-frequency components of a rustling sound, created when prey (freshly killed frog) was jerkily pulled on dry and wet sandy floors and asbestos, were recorded and played back to individual Indian false vampire bats (Megaderma lyra). Megaderma lyra responded with flight toward the speakers and captured dead frogs, that were kept as reward. The spectral peaks were at 8.6, 7.1 and 6.8 kHz for the low-frequency components of the sounds created at the dry, asbestos and wet floors, respectively. The spectral peaks for the high-frequency sounds created on the respective floors were at 36.8,27.2 and 23.3 kHz. The sound from the dry floor was more intense than that of from the other two substrata. Prey movements that generated sonic or ultrasonic sounds were both sufficient and necessary for the bats to detect and capture prey. The number of successful prey captures was significantly greater for the dry floor sound, especially to its high-frequency components. Bat-responses were low to the wet floor and moderate to the asbestos floor sounds. The bats did not respond to the sound of unrecorded parts of the tape. Even though the bats flew toward the speakers when the prey generated sounds were played back and captured the dead frogs we cannot rule out the possibility of M. lyra using echolocation to localize prey. However, the study indicates that prey that move on dry sandy floor are more vulnerable to predation by M. lyra.

Wide area control of SVCs for first swing stabilisation and damping in longitudinal systems

A non-linear Kalman filter based control strategy for SVCs located in major load groups is presented. This focusses on the limitation and damping of inter-area modes. It does this through treating local modes as noise and uses a tunable nonlinear control algorithm to improve both first swing stability and system damping. Simulation on a four machine system shows that the Kalman filer can successfully lock on to a desired inter-area mode and obtain a 31% improvement in critical clearing time as well as improved damping.

Corner detection in images under different noise levels

Corner detection has shown its great importance in many computer vision tasks. However, in real-world applications, noise in the image strongly affects the performance of corner detectors. Few corner detectors have been designed to be robust to heavy noise by now, partly because the noise could be reduced by a denoising procedure. In this paper, we present a corner detector that could find discriminative corners in images contaminated by noise of different levels, without any denoising procedure. Candidate corners (i.e., features) are firstly detected by a modified SUSAN approach, and then false corners in noise are rejected based on their local characteristics. Features in flat regions are removed based on their intensity centroid, and features on edge structures are removed using the Harris response. The detector is self-adaptive to noise since the image signal-to-noise ratio (SNR) is automatically estimated to choose an appropriate threshold for refining features. Experimental results show that our detector has better performance at locating discriminative corners in images with strong noise than other widely used corner or keypoint detectors.

A modified Density-Based Scanning Algorithm with Noise for spatial travel pattern analysis from Smart Card AFC data

Smart Card Automated Fare Collection (AFC) data has been extensively exploited to understand passenger behavior, passenger segment, trip purpose and improve transit planning through spatial travel pattern analysis. The literature has been evolving from simple to more sophisticated methods such as from aggregated to individual travel pattern analysis, and from stop-to-stop to flexible stop aggregation. However, the issue of high computing complexity has limited these methods in practical applications. This paper proposes a new algorithm named Weighted Stop Density Based Scanning Algorithm with Noise (WS-DBSCAN) based on the classical Density Based Scanning Algorithm with Noise (DBSCAN) algorithm to detect and update the daily changes in travel pattern. WS-DBSCAN converts the classical quadratic computation complexity DBSCAN to a problem of sub-quadratic complexity. The numerical experiment using the real AFC data in South East Queensland, Australia shows that the algorithm costs only 0.45% in computation time compared to the classical DBSCAN, but provides the same clustering results.

Real-time assessment of GNSS observation noise with single receivers

Stochastic modelling is critical in GNSS data processing. Currently, GNSS data processing commonly relies on the empirical stochastic model which may not reflect the actual data quality or noise characteristics. This paper examines the real-time GNSS observation noise estimation methods enabling to determine the observation variance from single receiver data stream. The methods involve three steps: forming linear combination, handling the ionosphere and ambiguity bias and variance estimation. Two distinguished ways are applied to overcome the ionosphere and ambiguity biases, known as the time differenced method and polynomial prediction method respectively. The real time variance estimation methods are compared with the zero-baseline and short-baseline methods. The proposed method only requires single receiver observation, thus applicable to both differenced and un-differenced data processing modes. However, the methods may be subject to the normal ionosphere conditions and low autocorrelation GNSS receivers. Experimental results also indicate the proposed method can result on more realistic parameter precision.

Noise Filtering of Process Execution Logs based on Outliers Detection

This paper presents a technique for the automated removal of noise from process execution logs. Noise is the result of data quality issues such as logging errors and manifests itself in the form of infrequent process behavior. The proposed technique generates an abstract representation of an event log as an automaton capturing the direct follows relations between event labels. This automaton is then pruned from arcs with low relative frequency and used to remove from the log those events not fitting the automaton, which are identified as outliers. The technique has been extensively evaluated on top of various auto- mated process discovery algorithms using both artificial logs with different levels of noise, as well as a variety of real-life logs. The results show that the technique significantly improves the quality of the discovered process model along fitness, appropriateness and simplicity, without negative effects on generalization. Further, the technique scales well to large and complex logs.

BPMN Miner: Automated Discovery of BPMN Process Models with Hierarchical Structure

Existing techniques for automated discovery of process models from event logs gen- erally produce flat process models. Thus, they fail to exploit the notion of subprocess as well as error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of hierarchical BPMN models con- taining interrupting and non-interrupting boundary events and activity markers. The technique employs functional and inclusion dependency discovery techniques in order to elicit a process-subprocess hierarchy from the event log. Given this hierarchy and the projected logs associated to each node in the hierarchy, parent process and subprocess models are then discovered using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. By employing approximate dependency discovery tech- niques, it is possible to filter out noise in the event log arising for example from data entry errors or missing events. A validation with one synthetic and two real-life logs shows that process models derived by the proposed technique are more accurate and less complex than those derived with flat process discovery techniques. Meanwhile, a validation on a family of synthetically generated logs shows that the technique is resilient to varying levels of noise.

Strength properties of composite clay balls containing additives from industry wastes as new filter media in water treatment

Pebble matrix filtration (PMF) is a water treatment technology that can remove suspended solids in highly turbid surface water during heavy storms. PMF typically uses sand and natural pebbles as filter media. Hand-made clay pebbles (balls) can be used as alternatives to natural pebbles in PMF treatment plants, where natural pebbles are not readily available. Since the high turbidity is a seasonal problem that occurs during heavy rains, the use of newly developed composite clay balls instead of pure clay balls have the advantage of removing other pollutants such as natural organic matter (NOM) during other times. Only the strength properties of composite clay balls are described here as the pollutant removal is beyond the scope of this paper. These new composite clay balls must be able to withstand dead and live loads under dry and saturated conditions in a filter assembly. Absence of a standard ball preparation process and expected strength properties of composite clay balls were the main reasons behind the present study. Five different raw materials from industry wastes: Red Mud (RM), Water Treatment Alum Sludge (S), Shredded Paper (SP), Saw Dust (SD), and Sugar Mulch (SM) were added to common clay brick mix (BM) in different proportions. In an effort to minimize costs, in this study clay balls were fired to 1100 0C at a local brick factory together with their bricks. A comprehensive experimental program was performed to evaluate crushing strength of composite hand-made clay balls, using uniaxial compression test to establish the best material combination on the basis of strength properties for designing sustainable filter media for water treatment plants. Performance at both construction and operating stages were considered by analyzing both strength properties under fully dry conditions and strength degradation after saturation in a water bath. The BM-75% as the main component produced optimum combination in terms of workability and strength. With the material combination of BM-75% and additives-25%, the use of Red Mud and water treatment sludge as additives produced the highest and lowest strength of composite clay balls, with a failure load of 5.4 kN and 1.4 kN respectively. However, this lower value of 1.4 kN is much higher than the effective load on each clay ball of 0.04 kN in a typical filter assembly (safety factor of 35), therefore, can still be used as a suitable filter material for enhanced pollutant removal.

Noise in my head: Voices from the ugly Australian underground

The Ugly Australian Underground documents the music, songwriting, aesthetics and struggles of fifty of Australia’s most innovative and significant bands and artists currently at the creative peak of their careers. The book provides a rare insight into the critically heralded cult music scene in Australia. The author, Jimi Kritzler, is both a journalist and a musician, and is personally connected to the musicians he interviews through his involvement in this music subculture. The interviews are extremely personal and reveal much more than any interview granted to street press or blogs. They deal with not only the music and songwriting processes of each band, but in some circumstances their struggles with drugs, involvement in crime and the death of band members.

The QUT-NOISE-SRE protocol for the evaluation of noisy speaker recognition

The QUT-NOISE-SRE protocol is designed to mix the large QUT-NOISE database, consisting of over 10 hours of back- ground noise, collected across 10 unique locations covering 5 common noise scenarios, with commonly used speaker recognition datasets such as Switchboard, Mixer and the speaker recognition evaluation (SRE) datasets provided by NIST. By allowing common, clean, speech corpora to be mixed with a wide variety of noise conditions, environmental reverberant responses, and signal-to-noise ratios, this protocol provides a solid basis for the development, evaluation and benchmarking of robust speaker recognition algorithms, and is freely available to download alongside the QUT-NOISE database. In this work, we use the QUT-NOISE-SRE protocol to evaluate a state-of-the-art PLDA i-vector speaker recognition system, demonstrating the importance of designing voice-activity-detection front-ends specifically for speaker recognition, rather than aiming for perfect coherence with the true speech/non-speech boundaries.