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The current state of quantum computers is characterized by its limited resources and high noise levels. These are known as Noisy Intermediate Scale Quantum Computing (NISQ). Reduction of noise is addressed at the technology level, while noise mitigation strategies have been proposed through the compilation process of quantum circuits. The compilation process entails a number of steps that are computationally intensive and scale poorly as the problems grow in size and resource usage. This paper addresses the problems associated with noise by proposing a noise aware qubit routing algorithm. This algorithm attempts to improve accuracy of circuits by using SWAP gates attempt to avoid links with high error rates. This differs from existing algorithms which try to minimize the amount of SWAP gates used. In addition, multiple metrics are evaluated for Qiskit's routing algorithms. The proposed algorithm improves the accuracy against circuits compiled using Qiskit’s basic routing algorithm, and against other more sophisticated routing algorithms, depending on the application circuit. Other metrics being considered, the routing algorithm also demonstrates to have minimal computational cost when compared to other approaches. Lastly, it is shown that different circuits benefit from different routing algorithms.

As population densities in urban areas increase, the associated demand on transportation infrastructure continues to exacerbate impacts on surrounding communities. These demands create a number of socioeconomic burdens including housing price impacts when communities are regularly exposed to excessive noise levels. Although noise impacts are not as commonly recognized or assessed in comparison to other environmental issues such as air, ground, or water pollution, it has been well documented in the literature that a wide range of health issues exist when communities are exposed to noise from transportation infrastructure. From a research perspective, the correlation of these health issues to the presence of impactful noise is difficult to quantify, as noise is subjective and requires translation into varying degrees of annoyance to deem it as detrimental from both health and economic perspectives. This dissertation utilizes spatial hedonic price (HP) models to estimate individuals’ marginal willingness-to-pay (MWTP) to reside in noise-impacted areas. These MWTP values can then be used to both valuate economic impacts and as a noise annoyance level proxy to identify zones that are at-risk due to excessive transportation noise exposure.The first analysis in this dissertation reviews salient transportation noise-related papers that have been published since Navrud’s comprehensive 2002 transportation noise literature review. In a review of recent literature, this dissertation found that transportation noise research has evolved to include advanced Geographic Information System data, and leverages increasingly powerful processors and statistical analysis programs. In addition, although significant transportation noise research has been conducted in Europe following EU Environmental Noise Directive 2002/49/EC, a relatively minimal number of studies have been conducted in the United States -- especially in Southern California, revealing a research gap that this dissertation helps to address.The second analysis investigates the impacts of aircraft operations around Los Angeles International Airport. Using a subset of 2010-2014 single-family home sales data from the Los Angeles County Office of the Assessor (LACOA), HP spatial autoregressive models with autoregressive disturbances (SARAR) were estimated. The study hypothesizes and confirms that a negative impact value would be observed for homes being located within noise-mapped zones around the airport, along with an improvement in estimation values compared to previous fixed spatial effects ordinary least squares techniques.The third analysis in this dissertation investigates two important topics. First, it hypothesizes negative home value impacts from nearby freight rail operations in the densely populated South Bay region of Los Angeles County. Noise from freight rail lines is analyzed using an HP SARAR model and confirm negative valuation impacts to homes located near these rail lines. Second, it hypothesizes that by using a subset of the master LACOA dataset above, varying levels of spatial homogeneity can be comparatively analyzed between two samples that use similar data and modeling techniques. Results indicate that when neighboring zones have distinct differences in jurisdiction, fixed spatial effect delineations remain statistically significant. However, when neighboring zones have similar jurisdictional or demographic characteristics, spatial model parameters are able to account for fixed delineations.

This dissertation examines the role of noise in shaping the form of several recent musical compositions. This study demonstrates how the contrast of noisy sounds and harmonic sounds can impact the structure of compositions. Depending on context, however, the specific use and function of noise can vary substantially from one work to the next. The first portion of this paper describes methods for quantifying noise content using FFT analysis procedures. A number of tests on instrumental and synthetic sound sources are described in order to demonstrate how the analysis system may react to certain sounds. The second part of this document consists of several analyses of whole musical works. Works for acoustic instruments are examined first, followed by works for electronic media. During these analyses, it becomes clear that while the use of noise in each work is based largely upon context, some common patterns do exist across different works. The final portion of the paper examines an original work which was written with the function of noise specifically in mind. The original work is put through the same analysis procedures as works seen earlier in the paper, and some conclusions are drawn regarding both the possibilities and limitations of noise analysis as a compositional tool.

In this dissertation, I analyzed Max Neuhaus’s (1939-2009) and R. Murray Schafer’s (b. 1932) commentary and work regarding noise, its control, and its relationship with the environment from the 1960 to the 1980s. Both Neuhaus and Schafer as well as those more directly involved with noise abatement research and policy were responding to the challenges and possibilities that noise posed in the latter twentieth century. In this project, I delved into these substantial links and argued that responding to and engaging with noise abatement policies was a key impetus to much of their work, which scholarship has yet to critically examine. Inspired by the listening strategies that Neuhaus and Schafer set forth, I also considered ways in which music educators and social activists might approach sound, becoming aural advocates or activists when working in their communities. The works selected for analysis reflected contemporaneous studies held in the USA and Canada investigating the psychological and physiological impact of noise on humans, animals, and their landscape. Just as these investigations grew into the 1970s, new attention developed towards acoustic ecology and public sound art, both fields dealing with the relationship between sounds, living beings, and the environment. Neuhaus’s works analyzed include the Listen series (1966-76), his New York Times op-ed piece titled “BANG, BOOooom, ThumP, EEEK, tinkle" (1974), and the Emergency Vehicle Siren Redesign project (1978-1989). These Neuhaus projects provided an alternative to the movement towards acoustic ecology put forward by his contemporary, Schafer. Analyses of Schafer and the World Soundscape Project’s (WSP) publications included Ear Cleaning (1967), The Book of Noise (1970), and A Survey of Community Noise Bylaws in Canada (1972). Featured were primary sources from the Max Neuhaus Papers (Columbia University Rare Book and Manuscript Library), newspaper reviews, and clippings. Also included were interviews with artists/associates of Neuhaus from his performance career (Phil Orenstein) and his Sirens project (Ray Gallon, Owen Greenspan, Herr Lugus, Julia Prospero, and Wolfgang Staehle) as well as Schafer's fellow WSP collaborator, Hildegard Westerkamp.

The major problem facing air transportation for the next decade is aircraft noise. The noise level due to the operation of large jet aircraft has created a very serious annoyance problem to the people living near of adjacent to jet airports. The noise problem has developed both for take-off and landing operations of these aircraft with take -off noise causing the greatest annoyance factor. A technique called Noise Exposure Forecast (NEF) has been developed to identify the annoyance factor of these noises to people and activities on the ground. With these NEF ratings or numbers, planners can better determine the type of buildings and activities to locate in the vicinity of airports. This paper presents a computer method for determining NEF areas or contours which eliminate the necessity of performing laborious hand calculations and iterations normally required to determine a given NEF locus about an airport. A land use compatibility table showing land use versus NEF numbers is given on page 3. A sample computer program is given on pages 21 through 25 of the appendix and a sample computer output page is given on page 26. The computer technique developed for this paper can be used for any airport.

Density-based clustering algorithms such as DBSCAN have been widely used for spatial knowledge discovery as they offer several key advantages compared to other clustering algorithms. They can discover clusters with arbitrary shapes, are robust to noise and do not require prior knowledge (or estimation) of the number of clusters. The idea of using a scan circle centered at each point with a search radius Eps to find at least MinPts points as a criterion for deriving local density is easily understandable and sufficient for exploring isotropic spatial point patterns. However, there are many cases that cannot be adequately captured this way, particularly if they involve linear features or shapes with a continuously changing density such as a spiral. In such cases, DBSCAN tends to either create an increasing number of small clusters or add noise points into large clusters. Therefore, in this paper, we propose a novel anisotropic density-based clustering algorithm (ADCN). To motivate our work, we introduce synthetic and real-world cases that cannot be sufficiently handled by DBSCAN (and OPTICS). We then present our clustering algorithm and test it with a wide range of cases. We demonstrate that our algorithm can perform as equally well as DBSCAN in cases that do not explicitly benefit from an anisotropic perspective and that it outperforms DBSCAN in cases that do. We show that our approach has the same time complexity as DBSCAN and OPTICS, namely O(n log n) when using a spatial index and O(n 2 ) otherwise. We provide an implementation and test the runtime over multiple cases. Finally, we apply DBSCAN, OPTICS, and ADCN to the task of extracting urban areas of interest (AOI) from geotagged photos in six cities. Visual comparison shows that, comparing to DBSCAN and OPTICS, ADCN is inclined to extract AOIs with linear shapes which follow the underline road networks. ADCN also turns out to connect clusters when the spatial distribution of them shows similar directions.

Most modem techniques for high resolution processing of closely spaced signals assume either uncorrelated noise or require knowledge of the noise covariance matrix. These assumptions are often invalid in practice. Here we propose a Pseudo-Autoregressive (PAR (M, p) model for estimation of an arbitrary number of signals M in the presence of a p-th order autoregressive (AR) noise environment. We derive the Cramer-Rao Lower Bound (CRLB) for the parameters of damped exponential signals in the colored noise case. A closed-form expression for the Cramer-Rao Lower Bound for the Pseudo-Autoregressive (PAR(M,p) model is obtained. Some special cases are investigated, for example, the PAR(M,p) model for p = 0, i.e., the white noise case, where our results agree with previous research results. We then evaluate the Cramer-Rao Lower Bound for two possibly closely spaced signals in a colored noise environment, showing that the colored noise assumption can lead to a much lower variance bound for the exponential parameters than under the white noise assumption. An algorithmic procedure is presented for the identification of the parameters of exponential signals, measured in colored noise. Previous papers on identifying sinusoids in noise have concentrated mainly on white noise disturbances. In a practical environment however, the disturbance is usually colored; sea-clutter in a radar context, is a lowpass type noise for example. When least squares type estimates are used in the colored noise environment, this usually leads to an unacceptable bias in the estimates. We propose an identification method, named Singular Value Decomposition Bias Elimination (SVDBE), in which it is assumed that the noise can be represented well by an AR process. The parameters of this noise model are then iteratively estimated along with the exponential signal parameters, via Singular Value Decomposition (SVD) based least squares. The iteration process starts with the white noise assumption, and improves on that by allowing the parameters in the noise model to vary away from the white noise case. A high order modal decomposition is found, and the best subset of the identified modes is selected. Simulations assess the merits of the introduced SVDBE algorithm, by comparison of the estimation results with the derived Cramer-Rao Lower Bound.

This paper aims to present a summary of the issues confronting landscape architects involved in the design of urban expressways, and to look in detail at the problems of noise and air pollution. By examining the problems and opportunities that urban expressways present, openings for effective treatment of these two pollutants can be recognised. A motorway offers a city four advantages over a conventional road network. It provides better access to the central business district, and thereby reduces the time required for the journey. It offers a safer journey as the number of potential hazards along the route are minimised by the elimination of intersections and the complete separation of pedestrians and traffic. Finally, a motorway can carry more traffic, thereby relieving congestion on other roads. Motorways, expressways and arterials form the primary road network of a city. These primary roads are fed by the secondary network comprising principal roads, collector roads and local roads.

This paper concerns an investigation for determining the feasibility of employing methods, similar to those used in conventional continuous tone photography, for determining the modulation transfer of variable area images on lithographic films. It deals with some of the special problems of separating the signal (the image) from the noise (the pattern of the screen), and describes the instruments and approaches to data read-out.