Analysis of Non-Stationary Flows Using Eulerian and Lagrangian Frameworks

Recent developments have made researchers to reconsider Lagrangian measurement techniques as an alternative to their Eulerian counterpart when investigating non-stationary flows. This thesis advances the state-of-the-art of Lagrangian measurement techniques by pursuing three different objectives: (i) developing new Lagrangian measurement techniques for difficult-to-measure, in situ flow environments; (ii) developing new post-processing strategies designed for unstructured Lagrangian data, as well as providing guidelines towards their use; and (iii) presenting the advantages that the Lagrangian framework has over their Eulerian counterpart in various non-stationary flow problems. Towards the first objective, a large-scale particle tracking velocimetry apparatus is designed for atmospheric surface layer measurements. Towards the second objective, two techniques, one for identifying Lagrangian Coherent Structures (LCS) and the other for characterizing entrainment directly from unstructured Lagrangian data, are developed. Finally, towards the third objective, the advantages of Lagrangian-based measurements are showcased in two unsteady flow problems: the atmospheric surface layer, and entrainment in a non-stationary turbulent flow. Through developing new experimental and post-processing strategies for Lagrangian data, and through showcasing the advantages of Lagrangian data in various non-stationary flows, the thesis works to help investigators to more easily adopt Lagrangian-based measurement techniques.

Improving Bangla ocr output through correction algorithms

Bangla OCR (Optical Character Recognition) is a long deserving software for Bengali community all over the world. Numerous e efforts suggest that due to the inherent complex nature of Bangla alphabet and its word formation process development of high fidelity OCR producing a reasonably acceptable output still remains a challenge. One possible way of improvement is by using post processing of OCR’s output; algorithms such as Edit Distance and the use of n-grams statistical information have been used to rectify misspelled words in language processing. This work presents the first known approach to use these algorithms to replace misrecognized words produced by Bangla OCR. The assessment is made on a set of fifty documents written in Bangla script and uses a dictionary of 541,167 words. The proposed correction model can correct several words lowering the recognition error rate by 2.87% and 3.18% for the character based n- gram and edit distance algorithms respectively. The developed system suggests a list of 5 (five) alternatives for a misspelled word. It is found that in 33.82% cases, the correct word is the topmost suggestion of 5 words list for n-gram algorithm while using Edit distance algorithm the first word in the suggestion properly matches 36.31% of the cases. This work will ignite rooms of thoughts for possible improvements in character recognition endeavour.

Creazione e validazione del modello fluidodinamico di un ventilatore centrifugo e possibili ottimizzazioni.

La seguente tesi nasce dall’esigenza di ottimizzare, da un punto di vista acustico e prestazionale, un ventilatore centrifugo preesistente in azienda. Nei primi tre capitoli si è analizzato il problema da un punto di vista teorico, mentre nel terzo e quarto capitolo da un punto di vista computazionale sfruttando tecniche CFD. Nel primo capitolo è stata fatta una trattazione generale dei ventilatori centrifughi, concentrandosi sul tipo di problematiche a cui questi vanno incontro. Nel secondo capitolo è stata presentata la teoria che sta alla base di una rilevazione sperimentale e di un’analisi acustica. Unitamente a ciò sono stati riportati alcuni articoli che mostrano tecniche di ottimizzazione acustica in ventilatori centrifughi. Nel terzo capitolo è stata riassunta la teoria alla base della fluidodinamica e di uno studio fluidodinamico. Nel quarto capitolo viene spiegato come è stato creato il modello fluidodinamico. Si è optato per un’analisi del problema in stato stazionario, sfruttando il Moving Reference Frame, e considerando l’aria come incomprimibile, visto il ridotto numero di Mach. L’analisi acustica è stata effettuata nel post-processing sfruttando il modello di Proudman. Infine è stata dimostrata la correlazione che intercorre tra i tre punti della curva resistente del ventilatore di funzionamento reale, permettendo di estendere i risultati ricavati dalla analisi di uno di questi agli altri due. Nel quinto capitolo è stata effettuata un’analisi dei risultati ottenuti dalle simulazioni fluidodinamiche e sono state proposte diverse modifiche della geometria. La modifica scelta ha visto un miglioramento delle prestazioni e una minore rumorosità. Infine sono state proposte nelle conclusioni ulteriori possibili strade da percorre per un’indagine e ottimizzazione del ventilatore più accurata.

Japanese plums (Prunus salicina Lindl.) and phytochemicals – breeding, horticultural practice, post-harvest storage, processing and bioactivity

Previous reviews of plum phytochemical content and health benefits have concentrated on the European plum, Prunus domestica L.. However, the potential bioactivity of red and dark red fleshed Japanese plum, Prunus salicina Lindl., so called blood plums, appears to warrant a significant increase in exposure as indicated in a recent review of the whole Prunus genus. Furthermore, Japanese plums are the predominate plum produced on an international basis. In this review the nutrient and phytochemical content, breeding programs, horticultural practice, post harvest treatment and processing as well as bioactivity (emphasizing in vivo studies) of Japanese plum are considered with a focus on the anthocyanin content that distinguishes the blood plums.

Insights into post-translational processing of beta-galactosidase in an animal model resembling late infantile human G-gangliosidosis

G(M1)-gangliosidosis is a lysosomal storage disorder caused by a deficiency of ss-galactosidase activity. Human GM1-gangliosidosis has been classified into three forms according to the age of clinical onset and specific biochemical parameters. In the present study, a canine model for type II late infantile human GM1-gangliosidosis was investigated 'in vitro' in detail. For a better understanding of the molecular pathogenesis underlying G(M1)-gangliosidosis the study focused on the analysis of the molecular events and subsequent intracellular protein trafficking of beta-galactosidase. In the canine model the genetic defect results in exclusion or inclusion of exon 15 in the mRNA transcripts and to translation of two mutant precursor proteins. Intracellular localization, processing and enzymatic activity of these mutant proteins were investigated. The obtained results suggested that the beta-galactosidase C-terminus encoded by exons 15 and 16 is necessary for correct C-terminal proteolytic processing and enzyme activity but does not affect the correct routing to the lysosomes. Both mutant protein precursors are enzymatically inactive, but are transported to the lysosomes clearly indicating that the amino acid sequences encoded by exons 15 and 16 are necessary for correct folding and association with protective protein/cathepsin A, whereas the routing to the lysosomes is not influenced. Thus, the investigated canine model is an appropriate animal model for the human late infantile form and represents a versatile system to test gene therapeutic approaches for human and canine G(M1)-gangliosidosis.

Automotive tape recorders. Volume 5. Data processing and post-calibration. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Memory Bias for Anxiety Prior to Academic Achievement Situations: Influences of Time, Mood, Personality and Post-Event-Processing

The current thesis examines memory bias for state anxiety prior to academic achievement situations like writing an exam and giving a speech. The thesis relies on the reconstruction principle, which assumes that memories for past emotions are reconstructed rather than stored permanently and accurately. This makes them prone to memory bias, which is af-fected by several influencing factors. A major aim is to include four important influencing factors simultaneously. Early research on mood and emotional autobiographical memory found evidence for the existence of a propositional associative network (Bower, 1981; Col-lins & Loftus, 1975), leading to mood congruent recall. But empirical findings gave also strong evidence for the existence of mood incongruent recall for one’s own emotions, which was for example linked to mood regulation via mood repair (e.g. Clark & Isen, 1982), which seems to be associated to the personality traits extraversion and neuroticism (Lischetzke & Eid, 2006; Ng & Diener, 2009). Moreover, neuroticism and trait anxiety are related to rumination, which is seen as negative post-event-processing (e.g. Wells & Clark, 1997). Overall, the elapsed time since the emotional event happened should have an impact on recall of emotions. Following the affect infusion model by Robinson and Clore (2002a), the influence of personality on memory bias should increase over time. Therefore, three longitudinal studies were realized, using naturally occurring as well as laboratory settings. The used paradigm was equivalent in all studies. Subjects were asked about their actual state anxiety prior to an academic achievement situation. Directly after the situation, cur-rent mood and recall of former anxiety were assessed. The same procedure was repeated a few weeks later. Personality traits and post-event-processing were also assessed. The results suggest a need to have a differentiated view on predicting memory bias. Study 1 (N = 131) as well as study 3 (N = 53) found evidence for mood incongruent memory in the sense of mood repair and downward regulation as a function of personality. Rumination was found to cause stable overestimation of pre-event anxiety in study 2 (N = 141) as well as in study 3. Although the relevance of the influencing factors changed over time, an increasing relevance of personality could not consistently be observed. The tremendously different effects of the laboratory study 2 indicated that such settings are not appropriate to study current issues. Theoretical and psychotherapeutically relevant conclusions are drawn and several limitations are discussed.

Design and Pilot Study for an Efficient High-Throughput Automated Computer-Vision Guided Intelligent De-Calyxing Machine for Post-Harvest Strawberry Processing

Strawberries harvested for processing as frozen fruits are currently de-calyxed manually in the field. This process requires the removal of the stem cap with green leaves (i.e. the calyx) and incurs many disadvantages when performed by hand. Not only does it necessitate the need to maintain cutting tool sanitation, but it also increases labor time and exposure of the de-capped strawberries before in-plant processing. This leads to labor inefficiency and decreased harvest yield. By moving the calyx removal process from the fields to the processing plants, this new practice would reduce field labor and improve management and logistics, while increasing annual yield. As labor prices continue to increase, the strawberry industry has shown great interest in the development and implementation of an automated calyx removal system. In response, this dissertation describes the design, operation, and performance of a full-scale automatic vision-guided intelligent de-calyxing (AVID) prototype machine. The AVID machine utilizes commercially available equipment to produce a relatively low cost automated de-calyxing system that can be retrofitted into existing food processing facilities. This dissertation is broken up into five sections. The first two sections include a machine overview and a 12-week processing plant pilot study. Results of the pilot study indicate the AVID machine is able to de-calyx grade-1-with-cap conical strawberries at roughly 66 percent output weight yield at a throughput of 10,000 pounds per hour. The remaining three sections describe in detail the three main components of the machine: a strawberry loading and orientation conveyor, a machine vision system for calyx identification, and a synchronized multi-waterjet knife calyx removal system. In short, the loading system utilizes rotational energy to orient conical strawberries. The machine vision system determines cut locations through RGB real-time feature extraction. The high-speed multi-waterjet knife system uses direct drive actuation to locate 30,000 psi cutting streams to precise coordinates for calyx removal. Based on the observations and studies performed within this dissertation, the AVID machine is seen to be a viable option for automated high-throughput strawberry calyx removal. A summary of future tasks and further improvements is discussed at the end.

The relationship between self-reported animal fear and ERP modulation : Evidence for enhanced processing and fear of harmless invertebrates in snake- and spider-fearful individuals

The present study used ERPs to compare processing of fear-relevant (FR) animals (snakes and spiders) and non-fear-relevant (NFR) animals similar in appearance (worms and beetles). EEG was recorded from 18 undergraduate participants (10 females) as they completed two animal-viewing tasks that required simple categorization decisions. Participants were divided on a post hoc basis into low snake/spider fear and high snake/spider fear groups. Overall, FR animals were rated higher on fear and elicited a larger LPC. However, individual differences qualified these effects. Participants in the low fear group showed clear differentiation between FR and NFR animals on subjective ratings of fear and LPC modulation. In contrast, participants in the high fear group did not show such differentiation between FR and NFR animals. These findings suggest that the salience of feared-FR animals may generalize on both a behavioural and electro-cortical level to other animals of similar appearance but of a non-harmful nature.

A tensor encoding model for semantic processing

This paper develops and evaluates an enhanced corpus based approach for semantic processing. Corpus based models that build representations of words directly from text do not require pre-existing linguistic knowledge, and have demonstrated psychologically relevant performance on a number of cognitive tasks. However, they have been criticised in the past for not incorporating sufficient structural information. Using ideas underpinning recent attempts to overcome this weakness, we develop an enhanced tensor encoding model to build representations of word meaning for semantic processing. Our enhanced model demonstrates superior performance when compared to a robust baseline model on a number of semantic processing tasks.