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Pitcher is a prototype which makes it easier for inexperienced guitar players to tune their guitars without any prior knowledge required. This thesis will explore how the construction varies between the usage of DC and a stepper motor, how reliable the tuner is and how long it takes to tune the guitar. The tuner will capture sound with a microphone and calculate the current frequency of the string with YIN autocorrelation. Based on the frequency a control system regulator is used to determine the speed and direction of a motor which turns the tuning peg, this is repeated until the string is in tune. 30 tests were conducted from different starting frequencies, and the time it took for the tuner to find the right pitch and the string’s corresponding frequency was measured. Some of the measurements were a couple of Hz off pitch, and only about half of the frequencies measured belonged to the interval where there is no noticeable dierence of the pitch, therefore the tuner could not be considered reliable. The time it takes to tune the guitar is dependent on how far off pitch the string is andthe dierence in time does not depend linearly with the starting frequency, it increases faster the further off pitch the string is.The tuner is portable and to apply the tuner to the guitar it is held and placed on the tuning peg with one hand as the other hand is plucking the string. / Den automatiska gitarrstämmaren, Pitcher, är en prototyp som möjliggör för oerfarna gitarranvändare utan förkunskaper att stämma en gitarr. Den här avhandlingen kommer att undersöka hur konstruktionen skiljer sig åt vidanvändning utav en stegmotor respektive en likströmsmotor, hur lång tid det tar att stämma gitarren samt hur tillförlitligprototypen är. Stämmaren avläser ljudsignaler med en mikrofon och beräknar sedan frekvensen av strängen med hjälp av YIN autokorrelation. Den beräknade frekvensen behandlas i en regulator som avgör vilken hastighet och i vilken riktningmotorn ska rotera stämskruven. Detta repeteras tills korrekt frekvens erhålls. 30 test gjordes då gitarren stämdes från olika startfrekvenser där tiden att stämma strängen respektive dess frekvens mättes. Några mätningar hade en frekvens som avvek flera Hz från korrekt frekvens, och cirka hälften av frekvenserna från alla mätningar tillhörde frekvensintervallet där ingen skillnad kan höras på tonen, därför kan gitarrstämmaren ej anses vara tillförlitlig. Tidendet tar att stämma en sträng är beroende på hur ostämd den är och skillnaden i tid beror inte linjärt av startfrekvens, utan den ökar snabbare desto mer ostämd gitarren är. Stämmaren är portabel och för att applicera den på gitarren placeras munstycket på stämskruven medan den andra handen slår an strängen.

On December 22nd, 2003, the Mw=6.5 San Simeon earthquake occurred 12 kilometers east of San Simeon, California, causing damage to buildings, roads, and other infrastructure throughout the central coast. The community of Oceano, 80 kilometers southeast of the epicenter, experienced damage to foundations, roads, and utilities due to liquefaction and lateral spreading. The unique geologic environment in Oceano caused a local amplification of ground motions, liquefaction, and lateral spreading. This study entailed developing ten liquefaction case histories from Oceano during the 2003 San Simeon earthquake. Four of the ten case histories are liquefaction cases and six are non-liquefaction cases, with Cyclic Stress Ratio (CSR) ranging from 0.17 to 0.43 and average corrected cone tip resistance (qc1) ranging from 2.67 to 23.53 kN/m^2. Subsurface data used to represent the geologic conditions in each case history included CPT soundings provided by the United States Geological Survey (Holzer et al., 2004). Ground motion data used to represent the earthquake conditions in each case history included the nearest relatively free field ground motion recordings from the SLO Rec Center Seismic Monitoring Station provided by the PEER strong motion center (PEER Ground Motions Database, 2003). CPT soundings were grouped together to develop representative case histories, allowing for averaging of parameters. The stratum with the single highest potential for liquefaction was selected and used as the ‘critical layer’ in each case history. To accurately represent the ground motion felt by each critical layer, a site response model was used to calculate average shear stress, which was used to calculate Cyclic Stress Ratio. The site response model was built using DEEPSOIL V6.1 with measured seismic shear wave velocities. Velocities were measured using passive geophysical methods in conjunction with Spatial Autocorrelation (SPAC) methods to process the data into shear wave velocity profiles. Measured velocities ranged from approximately 117 to 469 meters per second at depths ranging from 0 to 50 meters below the ground and were normally dispersive.

Mathematical methods of assessing the spatial autocorrelation associated with individual tree characteristics in forest stands were identified. These measures were used to investigate the spatial autocorrelation of discrete tree characteristics including the species, product, and defect classifications. With the exception of the species classification, none of the discrete tree characteristics examined showed any evidence of significant (α = 0.05) levels of spatial autocorrelation in loblolly pine stands. The significant autocorrelation of the species classification was probably due to past stand history or microsite variability rather than overall stand conditions such as age, density, or percent pine. The relationship between the level of spatial autocorrelation associated with basal area and several descriptive stand characteristics was also examined. No strong relationships were identified but trends were noticed between the autocorrelation measures and measures of stand competition such as basal area and crown competition factor. The measures of spatial association indicate positive autocorrelation between the characteristics of neighboring trees at very low levels of competition with the autocorrelation becoming increasingly negative as competition increases. At extremely high levels of competition, the spatial autocorrelation measures become positive again, reflecting the stagnated condition of the stand. Methods were developed, using the measures of spatial autocorrelation, to assign characteristics to individual trees in computer generated stands. These methods, applicable for discrete or continuous characteristics; assign the characteristics to individual trees depending on the spatial location of the individual tree and the locations and characteristics of its neighbors. / Ph. D.

Landscape is about the relationship between people and place and in 2000 was defined by the European Landscape Commission (ELC) as "an area as perceived by people whose character is the result of natural and human actions and interactions”. In the 70s the reason for studying the landscape was because of the necessity of attributing a value to it. Nowadays the motivations behind managing, conserving and enhancing the landscape is because the landscape is the place where people belong to and, consciously or not, recognise themselves. In addition, people identify different landscapes on the basis of the particular combinations of the elements in the landscape. As a consequence a landscape can be distinguished from another on the basis of its character which, according to the Landscape Character Assessment (LCA) guidance for England and Scotland (C. Swanwick and Land Use Consultant, 2002), is defined as “a distinct, recognisable and consistent pattern of elements in the landscape that makes one landscape different from the other rather than better or worse”. This definition was the starting point of a PhD research project aimed at developing and implementing a methodology able to identify and quantify the character of the Scottish landscape through the application of GIS and statistics. The reason for doing this research was to provide the landscape architects and practitioners with a tool that could help them to define the landscape character types in a more consistent, objective, and scientifically robust way. One of the objectives of the research was to identify the spatial patterns formed by the landscape elements by taking into account the influence of the spatial location. The first law of geography, which states that "everything is related to everything else but near things are more related than distant ones" (W Tobler, 1970), was transposed in the assumption of the presence of spatial autocorrelation amongst the data which contributes to form spatial patterns within the data. Since landscape comprises of many elements, data were also multivariate, thus the analysis required a method of calculation able to deal simultaneously with multivariate and spatial autocorrelation issues. MULTISPATI-PCA, a spatially constrained Principal Component Analysis, was the statistical technique applied for the analysis of the data whose results showed that it was possible to detect the spatial structure of the data and that each spatial pattern corresponded to a distinct landscape. Despite their importance in forming the character of the landscape, aesthetic and perceptual aspects were not inlcuded in MULTISPATI-PCA analysis. It was preferred to test the technique only on data that were quantifiable in a more objective way. Perhaps taking into account the human perception of the landscape can be the starting point for future investigation.

The motivation for this research is to leverage the increasing deployment of the phasor measurement unit (PMU) technology by electric utilities in order to improve situational awareness in power systems. PMUs provide unprecedentedly fast and synchronized voltage and current measurements across the system. Analyzing the big data provided by PMUs may prove helpful in reducing the risk of blackouts, such as the Northeast blackout in August 2003, which have resulted in huge costs in past decades. In order to provide deeper insight into early warning signs (EWS) of catastrophic events in power systems, this dissertation studies changes in statistical properties of high-resolution measurements as a power system approaches a critical transition. The EWS under study are increases in variance and autocorrelation of state variables, which are generic signs of a phenomenon known as critical slowing down (CSD). Critical slowing down is the result of slower recovery of a dynamical system from perturbations when the system approaches a critical transition. CSD has been observed in many stochastic nonlinear dynamical systems such as ecosystem, human body and power system. Although CSD signs can be useful as indicators of proximity to critical transitions, their characteristics vary for different systems and different variables within a system. The dissertation provides evidence for the occurrence of CSD in power systems using a comprehensive analytical and numerical study of this phenomenon in several power system test cases. Together, the results show that it is possible extract information regarding not only the proximity of a power system to critical transitions but also the location of the stress in the system from autocorrelation and variance of measurements. Also, a semi-analytical method for fast computation of expected variance and autocorrelation of state variables in large power systems is presented, which allows one to quickly identify locations and variables that are reliable indicators of proximity to instability.

The utilization of thermal fluctuations or Johnson/Nyquist noise as a spectroscopic method to determine transport properties in conductors or semiconductors is developed in this paper. The autocorrelation function is obtained from power spectral density measurements thus enabling electronic transport property calculation through the Green-Kubo formalism. This experimental approach is distinct from traditional numerical methods such as molecular dynamics simulations, which have been used to extract the autocorrelation function and directly related physics only. This work reports multi-transport property measurements consisting of the electronic relaxation time, resistivity, mobility, diffusion coefficient, electronic contribution to thermal conductivity and Lorenz number from experimental data. Double validation of the experiment was accomplished through the use of a standard reference material and a standard measurement method, i.e. four-probe collinear resistivity technique. The advantages to this new experimental technique include the elimination of any required thermal or potential gradients, multi-transport property measurements within one experiment, very low error and the ability to apply controlled boundary conditions while gathering data. This research has experimentally assessed the gas pressure and flow effects of helium and argon on 30 nm Au and Cu thin films. The results show a reduction in Au and Cu electronic thermal conductivity and electrical resistivity when subjected to helium and argon pressure and flow. The perturbed electronic transport coefficients, attributed to increased electron scattering at the surface, were so dominant that further data was collected through straight-forward resistance measurements. The resistance data confirmed the thermal noise measurements thus lending considerable evidence to the presence of thin film surface scattering due to elastic and inelastic gas particle scattering effects with the electron ensemble.