258 resultados para Electronic Noise
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The role of particular third sector organisations, Social Clubs, in supporting gambling through the use of EGMs in venues presents as a difficult social issue. Social Clubs gain revenue from gambling activities; but also contribute to social well-being through the provision of services to communities. The revenues derived from gambling in specific geographic locales has been seen by government as a way to increase economic development particularly in deprived areas. However there are also concerns about accessibility of low-income citizens to Electronic Gaming Machines (EGMS) and the high level of gambling overall in these deprived areas. We argue that social capital can be viewed as a guard against deleterious effects of unconstrained use of EGM gambling in communities. However, it is contended that social capital may also be destroyed by gambling activity if commercial business actors are able to use EGMs without community obligations to service provision. This paper examines access to gambling through EGMs and its relationship to social capital and the consequent effect on community resilience, via an Australian case study. The results highlight the potential two-way relationship between gambling and volunteering, such that volunteering (and social capital more generally) may help protect against problems of gambling, but also that volunteering as an activity may be damaged by increased gambling activity. This suggests that, regardless of the direction of causation, it is necessary to build up social capital via volunteering and other social capital activities in areas where EGMS are concentrated. The study concludes that Social Clubs using EGMs to derive funds are uniquely positioned within the community to develop programs that foster social capital creation and build community resilience in deprived areas.
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A combined specular reflection and diffusion model using the radiosity technique was developed to calculate road traffic noise level on residential balconies. The model is capable of numerous geometrical configurations for a single balcony situated in the centre of a street canyon. The geometry of the balcony and the street can be altered with width,length and height. The model was used to calculate for three different geometrical and acoustic absorption characteristics for a balcony. The calculated results are presented in this paper.
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In this globalized environment, Taiwanese firms have been very successful in achieving growth via international market expansion. In particular, the Taiwanese electronics industry has shown a dynamism lacking in comparable industries around the world. However, in recent years there has been a move by many of the larger Taiwanese manufacturing firms to outsource their manufacturing to low-cost producers such as China in order to remain competitive. Conversely, most Taiwanese small- to medium-sized enterprises (SMEs) have retained their production facilities in Taiwan. These SMEs seek to expand their sales beyond the domestic market by employing an export strategy, making a significant socioeconomic contribution to the domestic and regional economies. This paper highlights the key dimensions such as enhancing factors (benefits/advantages), inhibiting factors (barriers/costs), and managerial factors (characteristics/commitment) that play an important role in the internationalization of SMEs located within the Taiwanese electronics industry. A logistic regression model is used to predict the probability of a firm being an exporter.
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This silent swarm of stylized crickets is downloading data from Internet and catalogue searches being undertaken by the public at the State Library Queensland. These searches are being displayed on the screen on their backs. Each cricket downloads the searches and communicates this information with other crickets. Commonly found searches spread like a meme through the swarm. In this work memes replace the crickets’ song, washing like a wave through the swarm and changing on the whim of Internet users. When one cricket begins calling others, the swarm may respond to produce emergent patterns of text. When traffic is slow or of now interest to the crickets, they display onomatopoeia. The work is inspired by R. Murray Schafer’s research into acoustic ecologies. In the 1960’s Schafer proposed that many species develop calls that fit niches within their acoustic environment. An increasing background of white noise dominates the acoustic environment of urban human habitats, leaving few acoustic niches for other species to communicate. The popularity of headphones and portable music may be seen as an evolution of our acoustic ecology driven by our desire to hear expressive, meaningful sound, above the din of our cities. Similarly, the crickets in this work are hypothetical creatures that have evolved to survive in a noisy human environment. This speculative species replaces auditory calls with onomatopoeia and information memes, communicating with the swarm via radio frequency chirps instead of sound. Whilst these crickets cannot make sound, each individual has been programmed respond to sound generated by the audience, by making onomatopoeia calls in text. Try talking to a cricket, blowing on its tail, or making other sounds to trigger a call.
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This paper presents a method of voice activity detection (VAD) suitable for high noise scenarios, based on the fusion of two complementary systems. The first system uses a proposed non-Gaussianity score (NGS) feature based on normal probability testing. The second system employs a histogram distance score (HDS) feature that detects changes in the signal through conducting a template-based similarity measure between adjacent frames. The decision outputs by the two systems are then merged using an open-by-reconstruction fusion stage. Accuracy of the proposed method was compared to several baseline VAD methods on a database created using real recordings of a variety of high-noise environments.
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This paper presents a robust place recognition algorithm for mobile robots. The framework proposed combines nonlinear dimensionality reduction, nonlinear regression under noise, and variational Bayesian learning to create consistent probabilistic representations of places from images. These generative models are learnt from a few images and used for multi-class place recognition where classification is computed from a set of feature-vectors. Recognition can be performed in near real-time and accounts for complexity such as changes in illumination, occlusions and blurring. The algorithm was tested with a mobile robot in indoor and outdoor environments with sequences of 1579 and 3820 images respectively. This framework has several potential applications such as map building, autonomous navigation, search-rescue tasks and context recognition.
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This paper presents a method of voice activity detection (VAD) for high noise scenarios, using a noise robust voiced speech detection feature. The developed method is based on the fusion of two systems. The first system utilises the maximum peak of the normalised time-domain autocorrelation function (MaxPeak). The second zone system uses a novel combination of cross-correlation and zero-crossing rate of the normalised autocorrelation to approximate a measure of signal pitch and periodicity (CrossCorr) that is hypothesised to be noise robust. The score outputs by the two systems are then merged using weighted sum fusion to create the proposed autocorrelation zero-crossing rate (AZR) VAD. Accuracy of AZR was compared to state of the art and standardised VAD methods and was shown to outperform the best performing system with an average relative improvement of 24.8% in half-total error rate (HTER) on the QUT-NOISE-TIMIT database created using real recordings from high-noise environments.
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Since the launch of the ‘Clean Delhi, Green Delhi’ campaign in 2003, slums have become a significant social and political issue in India’s capital city. Through this campaign, the state, in collaboration with Delhi’s middle class through the ‘Bhagidari system’ (literally translated as ‘participatory system’), aims to transform Delhi into a ‘world-class city’ that offers a sanitised, aesthetically appealing urban experience to its citizens and Western visitors. In 2007, Delhi won the bid to host the 2010 Commonwealth Games; since then, this agenda has acquired an urgent, almost violent, impetus to transform Delhi into an environmentally friendly, aesthetically appealing and ‘truly international city’. Slums and slum-dwellers, with their ‘filth, dirt, and noise’, have no place in this imagined city. The violence inflicted upon slum-dwellers, including the denial of their judicial rights, is justified on these accounts. In addition, the juridical discourse since 2000 has ‘re-problematised slums as ‘nuisance’. The rising antagonism of the middle-classes against the poor, supported by the state’s ambition to have a ‘world-class city’, has allowed a new rhetoric to situate the slums in the city. These representations articulate slums as homogenised spaces of experience and identity. The ‘illegal’ status of slum-dwellers, as encroachers upon public space, is stretched to involve ‘social, cultural, and moral’ decadence and depravity. This thesis is an ethnographic exploration of everyday life in a prominent slum settlement in Delhi. It sensually examines the social, cultural and political materiality of slums, and the relationship of slums with the middle class. In doing so, it highlights the politics of sensorial ordering of slums as ‘filthy, dirty, and noisy’ by the middle classes to calcify their position as ‘others’ in order to further segregate, exclude and discriminate the slums. The ethnographic experience in the slums, however, highlights a complex sensorial ordering and politics of its own. Not only are the interactions between diverse communities in slums highly restricted and sensually ordained, but the middle class is identified as a sensual ‘other’, and its sensual practices prohibited. This is significant in two ways. First, it highlights the multiplicity of social, cultural experience and engagement in the slums, thereby challenging its homogenised representation. Second, the ethnographic exploration allowed me to frame a distinct sense of self amongst the slums, which is denied in mainstream discourses, and allowed me to identify the slums’ own ’others’, middle class being one of them. This thesis highlights sound – its production, performances and articulations – as an act with social, cultural, and political implications and manifestations. ‘Noise’ can be understood as a political construct to identify ‘others’ – and both slum-dwellers and the middle classes identify different sonic practices as noise to situate the ‘other’ sonically. It is within this context that this thesis frames the position of Listener and Hearer, which corresponds to their social-political positions. These positions can be, and are, resisted and circumvented through sonic practices. For instance, amplification tactics in the Karimnagar slums, which are understood as ‘uncultured, callous activities to just create more noise’ by the slums’ middle-class neighbours, also serve definite purposes in shaping and navigating the space through the slums’ soundscapes, asserting a presence that is otherwise denied. Such tactics allow the residents to define their sonic territories and scope of sonic performances; they are significant in terms of exerting one’s position, territory and identity, and they are very important in subverting hierarchies. The residents of the Karimnagar slums have to negotiate many social, cultural, moral and political prejudices in their everyday lives. Their identity is constantly under scrutiny and threat. However, the sonic cultures and practices in the Karimnagar slums allow their residents to exert a definite sonic presence – which the middle class has to hear. The articulation of noise and silence is an act manifesting, referencing and resisting social, cultural, and political power and hierarchies.
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This paper describes algorithms that can musically augment the realtime performance of electronic dance music by generating new musical material by morphing. Note sequence morphing involves the algorithmic generation of music that smoothly transitions between two existing musical segments. The potential of musical morphing in electronic dance music is outlined and previous research is summarised; including discussions of relevant music theoretic and algorithmic concepts. An outline and explanation is provided of a novel Markov morphing process that uses similarity measures to construct transition matrices. The paper reports on a ‘focus-concert’ study used to evaluate this morphing algorithm and to compare its output with performances from a professional DJ. Discussions of this trial include reflections on some of the aesthetic characteristics of note sequence morphing. The research suggests that the proposed morphing technique could be effectively used in some electronic dance music contexts.
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Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text mining methods adopted term-based approaches, they all suffer from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern (or phrase) based approaches should perform better than the term-based ones, but many experiments did not support this hypothesis. This paper presents an innovative technique, effective pattern discovery which includes the processes of pattern deploying and pattern evolving, to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information. Substantial experiments on RCV1 data collection and TREC topics demonstrate that the proposed solution achieves encouraging performance.
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Signal Processing (SP) is a subject of central importance in engineering and the applied sciences. Signals are information-bearing functions, and SP deals with the analysis and processing of signals (by dedicated systems) to extract or modify information. Signal processing is necessary because signals normally contain information that is not readily usable or understandable, or which might be disturbed by unwanted sources such as noise. Although many signals are non-electrical, it is common to convert them into electrical signals for processing. Most natural signals (such as acoustic and biomedical signals) are continuous functions of time, with these signals being referred to as analog signals. Prior to the onset of digital computers, Analog Signal Processing (ASP) and analog systems were the only tool to deal with analog signals. Although ASP and analog systems are still widely used, Digital Signal Processing (DSP) and digital systems are attracting more attention, due in large part to the significant advantages of digital systems over the analog counterparts. These advantages include superiority in performance,s peed, reliability, efficiency of storage, size and cost. In addition, DSP can solve problems that cannot be solved using ASP, like the spectral analysis of multicomonent signals, adaptive filtering, and operations at very low frequencies. Following the recent developments in engineering which occurred in the 1980's and 1990's, DSP became one of the world's fastest growing industries. Since that time DSP has not only impacted on traditional areas of electrical engineering, but has had far reaching effects on other domains that deal with information such as economics, meteorology, seismology, bioengineering, oceanology, communications, astronomy, radar engineering, control engineering and various other applications. This book is based on the Lecture Notes of Associate Professor Zahir M. Hussain at RMIT University (Melbourne, 2001-2009), the research of Dr. Amin Z. Sadik (at QUT & RMIT, 2005-2008), and the Note of Professor Peter O'Shea at Queensland University of Technology. Part I of the book addresses the representation of analog and digital signals and systems in the time domain and in the frequency domain. The core topics covered are convolution, transforms (Fourier, Laplace, Z. Discrete-time Fourier, and Discrete Fourier), filters, and random signal analysis. There is also a treatment of some important applications of DSP, including signal detection in noise, radar range estimation, banking and financial applications, and audio effects production. Design and implementation of digital systems (such as integrators, differentiators, resonators and oscillators are also considered, along with the design of conventional digital filters. Part I is suitable for an elementary course in DSP. Part II (which is suitable for an advanced signal processing course), considers selected signal processing systems and techniques. Core topics covered are the Hilbert transformer, binary signal transmission, phase-locked loops, sigma-delta modulation, noise shaping, quantization, adaptive filters, and non-stationary signal analysis. Part III presents some selected advanced DSP topics. We hope that this book will contribute to the advancement of engineering education and that it will serve as a general reference book on digital signal processing.