The capacity to form olfactory images has received less attention than the formation of visual and auditory images. The evidence in favor of such ability is also inconsistent. This thesis explored some of the characteristics of olfactory imagery through three empirical studies. Study I investigated the effects of blocking spontaneous sniffing during olfactory imagery. The results indicated that the prevention of spontaneous sniffing reduced olfactory but not visual imagery capacity. Study II studied the relation between olfactory awareness (as indexed by olfactory dreams, olfactory imagery, and olfactory interest) and olfactory functions (i.e., odor threshold, episodic odor memory, and odor identification). The main findings were that compared to low, high olfactory awareness was associated with better episodic odor memory and identification, but not with higher olfactory sensitivity. Study III investigated the neural correlates of odor evoked autobiographical memories (OEAMs) as (a) a function of cue modality (i.e., odors and their verbal referents), and (b) a function of memory remoteness. The results from Study III showed that OEAMs activated regions generally associated with autobiographical memory. In addition, verbally cued OEAMs were associated with activity linked to olfactory imagery. Odor cues activated the limbic and temporal polar regions more than verbal cues; a result that may explain the phenomenological differences found between the cued memories. Moreover, OEAMs from the first decade of life were associated with higher activity in the secondary olfactory cortex, whereas memories from young adulthood were related to areas linked to semantic memory processing. Taken together these studies favor the notion of a human capacity to form olfactory images.

Brain-computer interfacing (BCI) is a new method of human-machine interaction. It involves the extraction of information from the electroencephalogram (EEG) through signal processing and pattern recognition. The technology has far reaching implications for those with severe physical disabilities and has the potential to enhance machine interaction for the rest of the population. In this work we investigate time-frequency analysis in motor-imagery BCI. We consider two methods for signal analysis: adaptive autoregressive models (AAR) and wavelet transform (WAV). There are three major contributions of this research to single-trial analysis in motor-imagery BCI. First, we improve classification of AAR features over a conventional method by applying a temporal evidence accumulation (TEA) framework. Second, we compare the performance of AAR and WAV under the TEA framework for three subjects and find that WAV outperforms AAR for two subjects. The subject for whom AAR outperforms WAV has the lowest overall signal-to-noise ratio in their BCI output, an indication that the AAR model is more robust than WAV for noisier signals. Lastly, we find empirical evidence of complimentary information between AAR and WAV and propose a fusion scheme that increases the mutual information between the BCI output and classes.

Brain-computer interfacing (BCI) is a new method of human-machine interaction. It involves the extraction of information from the electroencephalogram (EEG) through signal processing and pattern recognition. The technology has far reaching implications for those with severe physical disabilities and has the potential to enhance machine interaction for the rest of the population. In this work we investigate time-frequency analysis in motor-imagery BCI. We consider two methods for signal analysis: adaptive autoregressive models (AAR) and wavelet transform (WAV). There are three major contributions of this research to single-trial analysis in motor-imagery BCI. First, we improve classification of AAR features over a conventional method by applying a temporal evidence accumulation (TEA) framework. Second, we compare the performance of AAR and WAV under the TEA framework for three subjects and find that WAV outperforms AAR for two subjects. The subject for whom AAR outperforms WAV has the lowest overall signal-to-noise ratio in their BCI output, an indication that the AAR model is more robust than WAV for noisier signals. Lastly, we find empirical evidence of complimentary information between AAR and WAV and propose a fusion scheme that increases the mutual information between the BCI output and classes.

As part of a beach erosion field experiment conducted at Cape Hatteras, NC in February 2010, this study focuses on quantifying longshore currents, which are the basic mechanism that drives longshore sediment transport. Using video imagery, the longshore currents in view of a video camera are estimated with the Optical Current Meter technique and the nearshore morphology is estimated by analyzing breaking wave patterns in standard deviation images. During a Nor‟easter storm event on February 12 and 13, 2010, the video longshore currents are compared to in situ data and it is found that the currents are most affected by the angle of incidence of incoming waves, increasing in magnitude as the angle becomes more oblique due to a larger component of radiation stress forcing in the longshore direction. The magnitude of the radiation stress forcing, which is at least an order of magnitude larger than the surface wind stress, increases as wave height increases or tide level decreases, which causes more wave breaking to occur. The normalized standard deviation images show wave breaking occurring at an inshore and offshore location, corresponding closely to the locations of an inner and outer bar indicated in survey data. Using two profiles from the survey data, one profile that intersects a trough and one that intersects a terrace, the video currents are also compared to currents simulated in one-dimension using the circulation module, SHORECIRC, and the wave module, REF/DIF-S, as part of the NearCoM system. Although the simulated currents greatly underpredict the video currents when the flow is only driven by radiation stresses, a mean water level difference between the two profiles creates a longshore pressure gradient. Superimposing a pressure gradient forcing term into the longshore momentum balance that assumes an equilibrium state of the flow, the magnitude of the simulated currents are much larger than the magnitude of the video estimated currents. Using analytical solutions of simplified forms of the mass and momentum equations to determine the effects of accelerations on the flow, it is seen that the acceleration term greatly affects the flow due to the relatively large mean water level difference that acts over a relatively short distance. Therefore, the pressure gradient forcing term is modified to include the effects of accelerations. By including the two-dimensional effects of the acceleration in the one-dimensional model through the modified pressure gradient, the quasi two-dimensional model simulated currents are very similar to the video estimated currents, indicating that the currents observed in the video may be pressure gradient driven.

<p>The purpose of this essay is to investigate how Joseph Conrad has used animal imagery and religious symbolism in “Heart of Darkness,” and determine if these tools are somehow linked to the theme of the story. Close reading has been applied in order to be able to go through the entire story in search of these often well-hidden tools. Considering the fact that the story in focus of the analysis is believed by some, including myself, to be a long short story rather than a short novel, this method of approach has proved to be highly useful. First a discussion about a possible theme in “Heart of Darkness” is presented, followed by a brief comment on Conrad’s personal life philosophy and view on the use of symbolic devices in literary works. In order to determine the differences between symbols and imagery, as well as theme, subject and topic, a short discussion of terminology has been included.</p><p>Much of the discussion in the analysis relies heavily upon articles and books by critics who have focused exclusively on symbolism and imagery in “Heart on Darkness” and other works by Conrad. The scholarly names worth mentioning in connection with the discussion about animal imagery are Olof Lagercrantz, John A. Palmer, and Samir Elbarbary. The critics Anthony Fothergill and Cedric Watts explore religious symbolism in general, whereas P.K. Saha and Rita A. Bergenholtz focus on particular aspects of it, such as Buddhism and Greek mythology.</p><p>The analysis section is for the most part a combination between my own personal interpretations of “Heart of Darkness” and those made by others. It is divided into two major sections, Animal Imagery and Religious Symbolism. The latter, furthermore, comprises two subgroups. The conclusion suggests that Conrad used symbolism and imagery as narratological tools in order to present us with the theme of morality in the story.</p>

Thesis (M.S.)--Indiana University, 2009. / Department of Geography, Indiana University-Purdue University Indianapolis (IUPUI). Advisor(s): Jeffrey S. Wilson, Lenore P. Tedesco, Daniel P. Johnson. Includes vitae. Includes bibliographical references (leaves 71-77).

One of the most important parts of engineered and biological systems is the ability to acquire and interpret information from the surrounding world accurately and in time-scales relevant to the tasks critical to system performance. This classical concept of efficient signal acquisition has been a cornerstone of signal processing research, spawning traditional sampling theorems (e.g. Shannon-Nyquist sampling), efficient filter designs (e.g. the Parks-McClellan algorithm), novel VLSI chipsets for embedded systems, and optimal tracking algorithms (e.g. Kalman filtering). Traditional techniques have made minimal assumptions on the actual signals that were being measured and interpreted, essentially only assuming a limited bandwidth. While these assumptions have provided the foundational works in signal processing, recently the ability to collect and analyze large datasets have allowed researchers to see that many important signal classes have much more regularity than having finite bandwidth. One of the major advances of modern signal processing is to greatly improve on classical signal processing results by leveraging more specific signal statistics. By assuming even very broad classes of signals, signal acquisition and recovery can be greatly improved in regimes where classical techniques are extremely pessimistic. One of the most successful signal assumptions that has gained popularity in recet hears is notion of sparsity. Under the sparsity assumption, the signal is assumed to be composed of a small number of atomic signals from a potentially large dictionary. This limit in the underlying degrees of freedom (the number of atoms used) as opposed to the ambient dimension of the signal has allowed for improved signal acquisition, in particular when the number of measurements is severely limited. While techniques for leveraging sparsity have been explored extensively in many contexts, typically works in this regime concentrate on exploring static measurement systems which result in static measurements of static signals. Many systems, however, have non-trivial dynamic components, either in the measurement system's operation or in the nature of the signal being observed. Due to the promising prior work leveraging sparsity for signal acquisition and the large number of dynamical systems and signals in many important applications, it is critical to understand whether sparsity assumptions are compatible with dynamical systems. Therefore, this work seeks to understand how dynamics and sparsity can be used jointly in various aspects of signal measurement and inference. Specifically, this work looks at three different ways that dynamical systems and sparsity assumptions can interact. In terms of measurement systems, we analyze a dynamical neural network that accumulates signal information over time. We prove a series of bounds on the length of the input signal that drives the network that can be recovered from the values at the network nodes~[1--9]. We also analyze sparse signals that are generated via a dynamical system (i.e. a series of correlated, temporally ordered, sparse signals). For this class of signals, we present a series of inference algorithms that leverage both dynamics and sparsity information, improving the potential for signal recovery in a host of applications~[10--19]. As an extension of dynamical filtering, we show how these dynamic filtering ideas can be expanded to the broader class of spatially correlated signals. Specifically, explore how sparsity and spatial correlations can improve inference of material distributions and spectral super-resolution in hyperspectral imagery~[20--25]. Finally, we analyze dynamical systems that perform optimization routines for sparsity-based inference. We analyze a networked system driven by a continuous-time differential equation and show that such a system is capable of recovering a large variety of different sparse signal classes~[26--30].

The aim of my examination work was to compare and research how russian respective swedish teachers make use of educational aesthetic methods such as drawing, drama, music and dance in the teaching of core school subjects – mathematics and swedish respective russian languages. The aim of this work was to find out which of these methods are used by pedagogues in the process of education and on what level are they integrated into the theoretical pedagogic work. The point was to also analyse the regulation documents used as pedagogical base in schools i've been doing my survey in. This was done to partly find out what arts perspective is given in the curriculum and partly to see what pieces of it are reflected in the process of education. I compared the pedagogic organisation and methods practiced in the classes I've researched. That helped to get the whole picture and possible image of overall students' performance. The questions I used as core: •    What aesthetic forms of expression are used by teachers in the process of education? •    On what level are they integrated into the theoretical work? •    What support to the art perspective is given in the curriculum? Secondary question that helped me to clarify the answers was: •    What parts of curriculum are reflected in the education process? My survey was built on a qualitative research method, that included my own observations and interviews with teachers in both Russian and Swedish schools.Summing up, I've learned that aesthetic forms of expression used by the russian teacher were: drawing, drama, dance and music. These methods integrate with mathematics and russian on different levels.The aesthetic forms of expression used by the swedish teacher are drawing, usually integrated with mathematics and language subjects, and music, used mostly in swedish lessons. The comparison of methods and organisation lined out great difference between how the learning proccess is organised by the russian and the swedish teachers. The bad part here is that it can influence pupils' performance, according to PISA studies.To sum up, I've come to a conclusion that the swedish curriculum is more supportive and contains more concrete examples on how the learning process should be organised, taking into account the art perspective, compared to the russian learning plan, that lack the art perspective for the major part.

The study aimed to examine whether an experimental imagery intervention, which elicited ecological representations of self, was more effective in enhancing vividness of movement imagery, action control and performance ability than a conventional imagery intervention and/or that of a standard, instruction intervention. In order to test this hypothesis, a sample of 36 young ballet dancers (11-13 years) were secured from five reputable ballet schools and randomly assigned to three groups (n = 12) for the purposes of conducting a true experiment: a standard control group, an imagery control group and an experimental imagery group. Descriptive statistics and frequencies were conducted for all instruments used to describe and represent single variables of interest. Parametric and nonparametric statistical procedures were used to determine whether significant differences existed between the three groups for measures of vividness of movement imagery, action control and performance ability. Additional emerging relationships and trends were explored through bivariate correlational analyses, multiple stepwise regression procedures, a factor analysis as well as MANOVA and ANOVA statistical procedures. The results of the study were varied and some interesting trends were observed. Contrary to what was expected, the results revealed significant differences across the three groups for mean difference scores of performance ability, in favour of the standard control group. In particular, the standard control group revealed positive benefits in performance ability while the imagery control and experimental imagery groups revealed deteriorations in performance ability. The experimental imagery group was found to be significantly different from the imagery control group for mean difference measures of internal vividness ofmovement imagery. However, the study failed to reveal significant variations in mean difference scores for action control across the three groups. Furthermore, the results indicated that external and internal vividness of movement imagery were found to be significantly correlated with performance ability for the entire sample (N = 36) and across the two imagery groups (N = 24) respectively. Finally, numerous significant and near-significant relationships were observed between measures of vividness of movement imagery, action control and performance ability. The results were discussed in relation to the literature on mental imagery, ecological self, action control and development. / Thesis (M.A.)-University of Natal, Pietermaritzburg, 2001.

This study examined the influence of state-confidence on aesthetic athletes’ precompetitive imagery function use. Important individual differences effecting functional imagery use require empirical confirmation. Proposed is state-confidence as a factor influencing the functions of imagery used immediately prior to competition. Also, sport type may also be a moderator of the relationship and thus, is constrained in this study. Female aesthetic athletes from Southern Alberta (N = 180, Mage = 14.64, SD = 1.88) completed measures of state-confidence, imagery ability, and frequency of imagery function use. One-way ANCOVA tests revealed that athletes with high state-confidence used significantly more cognitive specific, cognitive general, motivation general-arousal, and motivational general-mastery functions of imagery than low state-confident athletes. Findings imply that applied sport psychology consultants should be more encouraging of preparation strategies with low state-confident athletes. / xi, 64 leaves : ill. ; 28 cm