With a growing interest in technical specifications among consumers, there is a need for accessible measurement tools that enable individuals to evaluate the performance of their equipment, including common speakers and car audio systems, beyond what the manufacturer provides. However, the existing measurement systems are often geared towards professionals. This thesis aims to address this gap by designing and developing a user-friendly measurement tool that empowers individuals to easily measure and evaluate the performance of their devices. The work started with identifying the key technical specifications that users are interested in, and three parameters were selected for estimation: the maximum sound pressure level the system can provide, the corresponding multi-tone distortion and total harmonic distortion. Each parameter's measurement method varies, particularly in the choice of test stimuli and data processing. The methods in this thesis were determined after comparing existing standards for acoustical output-based measurement. Furthermore, some problems in terms of measurement capabilities and accuracy when implementing measurements within the defined application scenarios were also discussed. Ideally, the tool can finally provide users with detailed insights into chosen technical specifications, allowing them to know their audio systems better and make informed decisions. The automatic control of playback and recording as well as the processing afterwards was implemented in Python with the help of some existing packages. A graphic user interface based on PyQt was also developed to improve the manipulation of the measurement. Thus, the functionality that the tool is supposed to have is initially fulfilled, although its accuracy needs further verifying and improvement and the scope of the tool can be extended. / Med ett växande intresse för tekniska specifikationer bland konsumenter finns det ett behov av tillgängliga mätverktyg som gör det möjligt för privatpersoner att utvärdera prestandan hos sin utrustning, inklusive vanliga högtalare och bilstereosystem, utöver vad tillverkaren tillhandahåller. De befintliga mätsystemen är dock ofta inriktade på professionella användare. Denna avhandling syftar till att åtgärda denna brist genom att utforma och utveckla ett användarvänligt mätverktyg som gör det möjligt för privatpersoner att enkelt mäta och utvärdera prestandan hos sina enheter. Arbetet inleddes med att identifiera de viktigaste tekniska specifikationerna som användarna är intresserade av, och tre parametrar valdes ut för uppskattning: den maximala ljudtrycksnivå som systemet kan ge, motsvarande multitondistorsion och total harmonisk distorsion. Mätmetoden för varje parameter varierar, särskilt när det gäller valet av teststimuli och databehandling. Metoderna i denna avhandling fastställdes efter jämförelse av befintliga standarder för akustisk effektbaserad mätning. Dessutom diskuterades vissa problem när det gäller mätkapacitet och noggrannhet vid implementering av mätningar inom de definierade tillämpningsscenarierna. I bästa fall kan verktyget slutligen ge användarna detaljerade insikter i valda tekniska specifikationer, så att de kan lära känna sina ljudsystem bättre och fatta välgrundade beslut. Den automatiska styrningen av uppspelning och inspelning samt bearbetningen i efterhand implementerades i Python med hjälp av några befintliga paket. Ett grafiskt användargränssnitt baserat på PyQt utvecklades också för att förbättra hanteringen av mätningen. Den funktionalitet som verktyget är tänkt att ha är således initialt uppfylld, även om dess noggrannhet behöver verifieras och förbättras ytterligare och verktygets omfattning kan utökas.

Coral reefs around the world are threatened by a variety of sources, from localized impacts, including overfishing and coastal development, to global temperature increases and ocean acidification. Conserving these marine biodiversity havens requires both global and local action informed by scientific research. In this thesis, I use data collected from the coral reefs around Kiritimati atoll (Republic of Kiribati) in the central equatorial Pacific, first to assess the applicability of two common metrics used in passive underwater acoustic research, and second to examine the effects of a marine heatwave and local human disturbance on an assemblage of corallivorous fish. Using acoustic data recorded in 2017 and 2018 on reefs around Kiritimati, I assess how sound pressure level (SPL) and the acoustic complexity index (ACI) respond to changes in fish sounds in a low frequency band (160 Hz – 1 kHz) and snapping shrimp snaps in a high frequency band (1 kHz – 22 kHz). I found that while SPL was positively correlated with increases in fish sounds and snap density, changes in ACI were dependent upon the settings chosen for its calculation, with the density of snaps negatively correlated with ACI across all settings. These findings provide evidence that despite its quick and prolific adoption, acoustic metrics like ACI should be thoroughly field-tested and standardized before they are applied to new ecosystems like coral reefs. Next, using underwater visual censuses (UVCs) of reef fish assemblages, I quantified how two functional groups of corallivores, obligate and facultative, responded to a mass coral mortality event created by the 2015-2016 El Niño. Declines in abundance of both groups were largely driven by the response of coral-associated damselfishes, Plectroglyphidodon johnstonianus in the obligate group and Plectroglyphidodon dickii in the facultative group, to heat stress and subsequent coral mortality. I also observed a significant decline in the species richness of obligate corallivores, and a continued decline in the abundance of obligate corallivores three years after the mass coral mortality event. Additionally, facultative corallivore abundance increased with disturbance, although the effect was modulated by year, likely due to their more adaptable diets. Corallivore assemblage structure was also influenced by the heat stress event, recovery, and local human disturbance. These results detail how an entire corallivorous assemblage is impacted by a coral mortality event and incidentally provide a timeline for corallivore decline. Together, these results provide information about new ways of monitoring coral reefs, and the ways in which two components of the reef fish community, obligate and facultative corallivores, respond to a mass coral mortality event. / Graduate / 2022-01-15

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Noise is defined as any undesired sound. Urban noise and its effect on citizens area significant environmental problem, and the increasing level of noise has become a critical problem in some cities. Fortunately, noise pollution can be mitigated by better planning of urban areas or controlled by administrative regulations. However, the execution of such actions requires well-established systems for noise monitoring. In this thesis, we present a solution for noise measurement and classification using a low-power and inexpensive IoT unit. To measure the noise level, we implement an algorithm for calculating the sound pressure level in dB. We achieve a measurement error of less than 1 dB. Our machine learning-based method for noise classification uses Mel-frequency cepstral coefficients for audio feature extraction and four supervised classification algorithms (that is, support vector machine, k-nearest neighbors, bootstrap aggregating, and random forest). We evaluate our approach experimentally with a dataset of about 3000 sound samples grouped in eight sound classes (such as car horn, jackhammer, or street music). We explore the parameter space of the four algorithms to estimate the optimal parameter values for the classification of sound samples in the dataset under study. We achieve noise classification accuracy in the range of 88% – 94%.