The primary goal of retail environments is to stimulate positive behavior from consumers viewing the fulfilled plan of the designer or architect. This study explores the influence of the consumer trait, visual aesthetic sensitivity, upon the visual aesthetic design features of the store environment and consumer behavior. Treatment of the visual aesthetic design features of the retail environment as an integrated, holistic arrangement demonstrate the dynamic interrelation of the environment and perception as explained by Gestalt theory. Data was collected through traditional survey techniques. Statistical analyses using exploratory factor analysis, ANCOVA, and MANCOVA reveal distinct differences between consumers with high versus low visual aesthetic sensitivity in store environment evaluations and consumer behavior.

Stellare Magnetfelder spielen eine wichtige Rolle bei der Entstehung und Entwicklung von Sternen. Leider entziehen sie sich aber, aufgrund ihrer großen Entfernung zur Erde, einer direkten Beobachtung. Dies gilt zumindest für derzeitige und in naher Zukunft zur Verfügung stehende Instrumente. Um aber beispielsweise zu verstehen, ob Magnetfelder durch einen Dynamoprozess generiert werden oder Überbleibsel der Sternentstehung sind, ist es zwingend erforderlich, die Oberflächenstruktur und die zeitliche Entwicklung von stellaren Feldern zu untersuchen. Glücklicherweise haben wir mit der Dopplerverschiebung sowie der Polarisation von Licht Mittel zur Verfügung, um indirekt die Magnetfeldtopologie entfernter Sternen zu rekonstruieren, wenn auch nur die schnell rotierender. Die auf den beiden genannten Effekten basierende Rekonstruktionsmethode ist unter dem Namen Zeeman-Doppler Imaging (ZDI) bekannt. Sie stellt eine leistungsfähige Methode dar, um aus rotationsverbreiterten Stokes Profilen schnell rotierender Sterne Oberflächenkartierungen der Temperatur und Magnetfeldverteilung zu erstellen. Durch das ZDI konnten in den vergangenen Jahren die Magnetfeldverteilungen zahlreicher Sterne rekonstruiert werden. Diese Methode stellt allerdings sehr hohe Anforderungen sowohl an die Instrumentierung als auch an die Rechenleistung und ist deshalb häufig mit zahlreichen Annahmen und Näherungen verbunden. Ziel dieser Arbeit war es, Methoden für ein ZDI zu entwickeln, das darauf ausgelegt ist, zeitaufgelöste spektropolarimetrische Daten von aktiven späten Sternen zu invertieren. Es sollte also insbesondere den komplexen und lokalen Magnetfeldstrukturen dieser Sterne Rechnung getragen werden. Um die Orientierung und Stärke solcher Felder zuverlässig rekonstruieren zu können, sollte die Inversion im Stande sein, alle vier Stokes-Komponenten einzubeziehen. Ferner war vorgesehen auf vollständigen polarisierten Strahlungstransportmodellierungen aufzubauen. Dies ermöglicht eine simultane und selbstkonsistente Temperatur- und Magnetfeld-Inversion, die damit dem komplexen Zusammenspiel zwischen Temperatur und Magnetfeld gerecht wird. Schließlich sollte die Anwendung eines neu zu entwickelnden ZDI Programms auf Stokes I und V Beobachtungen von II Pegasi (kurz: II Peg) erste Magnefeldkarten dieses sehr aktiven Sterns liefern. Um den hohen Rechenaufwand, der mit der Inversionsmethode einhergeht, besser bewältigen zu können, wurde zunächst eine schnelle Approximationsmethode für den polarisierten Strahlungstransport entwickelt. Sie basiert auf einer Hauptkomponentenanalyse (PCA) sowie auf künstlichen Neuronalen Netzen. Letztere approximieren den funktionalen Zusammenhang zwischen atmosphärischen Parametern und den zugehörigen lokalen Stokes Profilen. Inverse Probleme sind potentiell schlecht gestellt und erfordern in der Regel eine Regularisierung. Der entwickelte Ansatz verwendet eine lokale Entropie, die auf die Besonderheiten bei der Rekonstruktion lokalisierter Magnetfeder eingeht. Ein weiterer neuartiger Ansatz befasst sich mit der Rauschreduktion polarimetrischer Beobachtungsdaten. Er macht sich die Hauptkomponentenanalyse zu Nutze, um mit Hilfe einer Vielzahl beobachteter Spektrallinien, einzelne Linien mit drastisch vergrößertem Signal-zu-Rausch-Verhältnis wieder zu geben. Diese Methode hat gegenüber anderen Multi-Spektrallinien-Verfahren den Vorteil, nach wie vor eine Inversion auf der Basis einzelner Spektrallinien durchführen zu können. Schließlich wurde das Inversionsprogramm iMap entwickelt, das die zuvor genannten Methoden implementiert. Detaillierte Testrechnungen demonstrieren die Funktionsfähigkeit und Genauigkeit der schnellen Synthese-Methode und weisen einen Zeitgewinn von nahezu drei Größenordnungen gegenüber der konventionellen Strahlungstransportberechnung auf. Desweiteren untersuchen wir den Einfluss der verschiedenen Stokes Komponenten (IV bzw. IVQU) auf die Zuverlässigkeit, ein bekanntes Magnetfeld zu rekonstruieren. Damit belegen wir die Zuverlässigkeit unseres Inversionsprogrammes und zeigen darüber hinaus auch Einschränkungen von Magnetfeldinversionen im allgemeinen auf. Eine erste Inversion von Stokes I und V Profilen von II Peg liefert zum ersten Mal für diesen Stern simultan Temperatur- und Magnetfeldverteilungen. / Stellar magnetic fields, as a crucial component of star formation and evolution, evade direct observation at least with current and near future instruments. However investigating whether magnetic fields are generated by a dynamo process or represent relics from the formation process, or whether they show a behavior similar to the sun or something very different, it is essential to investigate their structure and temporal evolution. Fortunately nature provides us with the possibility to indirectly observe surface topologies on distant stars by means of Doppler shift and polarization of light, though not without its challenges. Based on the mentioned effects, the so called Zeeman-Doppler Imaging technique is a powerful method to retrieve magnetic fields from rapid rotating stars based on measurements of spectropolarimetric observations in terms of Stokes profiles. In recent years, a large number of stellar magnetic field distributions could be reconstructed by Zeeman-Doppler Imaging (ZDI). However, the implementation of this method often relies on many approximations because, as an inversion method, it entails enormous computational requirements. The aim of this thesis is to develop methods for a ZDI, designed to invert time-resolved spectropolarimetric data of active late type stars, and to account for the expected complex and small scale magnetic fields on these stars. In order to reliably reconstruct the detailed field orientation and strength, the inversion method is employed to be able to use of all four Stokes components. Furthermore it is based on fully polarized radiative transfer calculations to account for the intricate interplay between temperature and magnetic field. Finally, the application of a newly developed ZDI code to Stokes I and V observations of II Pegasi (short: II Peg) was supposed to deliver the first magnetic surface maps for this highly active star. To accomplish the high computational burden of a radiative transfer based ZDI, we developed a novel approximation method to speed up the inversion process. It is based on Principal Component Analysis and Artificial Neural Networks. The latter approximate the functional mapping between atmospheric parameters and the corresponding local Stokes profiles. Inverse problems, as we are dealing with, are potentially ill-posed and require a regularization method. We propose a new regularization scheme, which implements a local entropy function that accounts for the peculiarities of the reconstruction of localized magnetic fields. To deal with the relatively large noise that is always present in polarimetric data, we developed a multi-line denoising technique based on Principal Component Analysis. In contrast to other multi-line techniques that extract from a large number of spectral lines a sort of mean profile, this method allows to extract individual spectral lines and thus allows for an inversion on the basis of specific lines. All these methods are incorporated in our newly developed ZDI code iMap, which is based on a conjugated gradient method. An in depth validation of our new synthesis method demonstrates the reliability and accuracy of this approach as well as a gain in computation time by almost three orders of magnitude relative to the conventional radiative transfer calculations. We investigated the influence of the different Stokes components (IV / IVQU) on the ability to reconstruct a known synthetic field configuration. In doing so we validate the capability of our inversion code, and we also assess limitations of magnetic field inversions in general. In a first application to II Peg, a K2 IV subgiant, we derived temperature and magnetic field surface distributions from spectropolarimetric data obtained in 2004 and 2007. It gives for the first time simultaneously the temporal evolution of the surface temperature and magnetic field distribution on II Peg.

In this thesis, product experiences were analyzed in human-product interaction context. The terminology to describe product experiences were gathered and grouped with the studies carried out during the thesis. The conceptual network of product experiences were attempted to be established by examining the stages of human-product interaction in the limitations of the studies. The gathered terminology was composed of both concrete and abstract product features. The abstract product features which are used for defining product personality characteristics took part in the lexicon. The lexicon for product experience related communication resulting from the thesis, was used in designed instructional game for Bachelor degree industrial design students, in order to be informed and develop themselves on the subject. Hereby, while the students have fun, they will explore the terminology to use in design communications easily.

Swedish national statistics suggest that the number of reported stranger rapes is steadily increasing. Stranger rape is one of the most difficult types of crime for the police to investigate because there is no natural tie between the victim and offender. As a result, there is a need for more knowledge about how crime scene features could be used to make inferences of likely offender characteristics that could help investigators narrow down the pool of suspects. The aim in Study I was to examine how offender behaviors interact with contextual features, victim behaviors, and the assault outcome. Results suggest that the stranger rapes could be distinguished by five different dynamic rape pattern themes, which mainly differed on two dimensions: level of violence to control the victim, and level of impulsivity/premeditation characterizing the rapes. The results also highlight the importance of including contextual features when studying offender behaviors. The aim in Study II was to examine how single-victim rapists and serial rapists can be differentiated by the actions at their first stranger rape. Results suggest that three behaviors in conjunction: kissed victim, controlled victim, and offender drank alcohol before the offense, could be used to predict whether the offender was a single-victim rapist or serial rapist with a classification accuracy of 80.4 %. The aim in Study III was to examine how stranger rapists could be differentiated from a normative sample on background characteristics, and if stranger rapists’ pre-assault and initial-attack behaviors could be used to predict likely offender characteristics. Results showed that the strongest predictions could be made for previous criminal convictions, offender age, and the distance traveled by the offender to offend. Overall, the present thesis has found some scientific support for the use of crime scene behaviors to make inferences of likely offender characteristics that could be useful for profiling purposes. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Submitted. Paper 3: Submitted.</p>

This thesis focuses on bare hand gesture recognition by proposing a new architecture to solve the problem of real-time vision-based hand detection, tracking, and gesture recognition for interaction with an application via hand gestures. The first stage of our system allows detecting and tracking a bare hand in a cluttered background using face subtraction, skin detection and contour comparison. The second stage allows recognizing hand gestures using bag-of-features and multi-class Support Vector Machine (SVM) algorithms. Finally, a grammar has been developed to generate gesture commands for application control. Our hand gesture recognition system consists of two steps: offline training and online testing. In the training stage, after extracting the keypoints for every training image using the Scale Invariance Feature Transform (SIFT), a vector quantization technique will map keypoints from every training image into a unified dimensional histogram vector (bag-of-words) after K-means clustering. This histogram is treated as an input vector for a multi-class SVM to build the classifier. In the testing stage, for every frame captured from a webcam, the hand is detected using my algorithm. Then, the keypoints are extracted for every small image that contains the detected hand posture and fed into the cluster model to map them into a bag-of-words vector, which is fed into the multi-class SVM classifier to recognize the hand gesture. Another hand gesture recognition system was proposed using Principle Components Analysis (PCA). The most eigenvectors and weights of training images are determined. In the testing stage, the hand posture is detected for every frame using my algorithm. Then, the small image that contains the detected hand is projected onto the most eigenvectors of training images to form its test weights. Finally, the minimum Euclidean distance is determined among the test weights and the training weights of each training image to recognize the hand gesture. Two application of gesture-based interaction with a 3D gaming virtual environment were implemented. The exertion videogame makes use of a stationary bicycle as one of the main inputs for game playing. The user can control and direct left-right movement and shooting actions in the game by a set of hand gesture commands, while in the second game, the user can control and direct a helicopter over the city by a set of hand gesture commands.

The purpose of this work is to investigate a series of biologically inspired modifications to state-of-the-art Mel- frequency cepstral coefficients (MFCCs) that may improve automatic speech recognition results. We have provided recommendations to improve speech recognition results de- pending on signal-to-noise ratio levels of input signals. This work has been motivated by noise-robust auditory features (NRAF). In the feature extraction technique, after a signal is filtered using bandpass filters, a spatial derivative step is used to sharpen the results, followed by an envelope detector (recti- fication and smoothing) and down-sampling for each filter bank before being compressed. DCT is then applied to the results of all filter banks to produce features. The Hidden- Markov Model Toolkit (HTK) is used as the recognition back-end to perform speech recognition given the features we have extracted. In this work, we investigate the role of filter types, window size, spatial derivative, rectification types, smoothing, down- sampling and compression and compared the final results to state-of-the-art Mel-frequency cepstral coefficients (MFCC). A series of conclusions and insights are provided for each step of the process. The goal of this work has not been to outperform MFCCs; however, we have shown that by changing the compression type from log compression to 0.07 root compression we are able to outperform MFCCs for all noisy conditions.

Intellectual disability (ID) affects approximately 1-3% of the population and is defined as having an IQ below 70 as well as a significant limitation in adaptive behavior. The implementation of chromosomal microarrays (CMA) into the field of clinical genetics has revolutionized the ability to find genetic aberrations responsible for different genetic disorders. Importantly. these technologies have allowed several new microdeletion and microduplication aberrations to be identified that otherwise would have escaped detection using more conventional methods. Finding the genetic etiology of a syndrome and its association to the phenotype is paramount to better health care, provision of tailored therapy, presymptomatic screening, accurate prognosis, recurrence risk evaluation and in some cases prenatal testing. Despite the plethora of new information available, there are still a number of clinical and genetic features we do not fully understand. The aim of this work was to identify regions and syndromes associated with ID by CMA analysis and to make a detailed clinical description of the affected patients’ phenotype. In paper I we studied the 22q11.2 duplication syndrome and presented two familial cases with a description of both their genotype and phenotype. Additionally, 36 cases harboring the duplication were reviewed to further delineate the phenotype of the syndrome. In paper II, we revealed two unrelated patients with a deletion at 6q14.1-q15 and a distinct phenotype. Together with one previously reported patient our study suggests that a novel, clinically recognizable microdeletion syndrome exists in these patients. In paper III the phenotype and genotype of six unrelated patients with partially overlapping microdeletions at 10p12.31-p11.21 were described. Taken together with a previously reported patient we propose that these findings represent a new contiguous gene syndrome. In paper IV, two sisters; one presenting with two tandem interstitial duplications and the other a large deletion over the same region (6q13-q16) were reported. The reason for the CNVs was a maternal de novo translocation. This is the first case describing the genotype and phenotype of this duplicated region at 6q13-q16. In conclusion, four different genetic aberrations involved in the etiology of ID and their corresponding phenotypes and candidate genes have been characterized.

Parkinson's disease (PD) is a degenerative illness whose cardinal symptoms include rigidity, tremor, and slowness of movement. In addition to its widely recognized effects PD can have a profound effect on speech and voice.The speech symptoms most commonly demonstrated by patients with PD are reduced vocal loudness, monopitch, disruptions of voice quality, and abnormally fast rate of speech. This cluster of speech symptoms is often termed Hypokinetic Dysarthria.The disease can be difficult to diagnose accurately, especially in its early stages, due to this reason, automatic techniques based on Artificial Intelligence should increase the diagnosing accuracy and to help the doctors make better decisions. The aim of the thesis work is to predict the PD based on the audio files collected from various patients.Audio files are preprocessed in order to attain the features.The preprocessed data contains 23 attributes and 195 instances. On an average there are six voice recordings per person, By using data compression technique such as Discrete Cosine Transform (DCT) number of instances can be minimized, after data compression, attribute selection is done using several WEKA build in methods such as ChiSquared, GainRatio, Infogain after identifying the important attributes, we evaluate attributes one by one by using stepwise regression.Based on the selected attributes we process in WEKA by using cost sensitive classifier with various algorithms like MultiPass LVQ, Logistic Model Tree(LMT), K-Star.The classified results shows on an average 80%.By using this features 95% approximate classification of PD is acheived.This shows that using the audio dataset, PD could be predicted with a higher level of accuracy.

Vi har i en tidigare kurs genomfört en uppgift innehållande bråk, då vi upptäckte att elever hade svårt att lära sig framförallt sammansatta bråk. Vi blev intresserade av att ta reda på hur man skapar förutsättningar för att eleverna ska lära sig bråk, vilket är denna studies syfte. Studien syftar även till att upptäcka vilka aspekter som är kritiska för att lära sig bråk samt ta reda på hur dessa kan varieras i undervisningen vid elevernas lärande av bråk. I studien används en learning study som kan ses som en typ av aktionsforskning där lärare forskar i sitt eget klassrum. Inom learning study används variationsteorin som är en guidande princip för att förstå och skapa förutsättningar för lärande. Lektionerna som genomfördes av oss, blivande lärare, vid tre olika tillfällen videofilmades. Dessa filmer transkriberades och analyserades därefter. Ur analysen av det transkriberade materialet, videoupptagningarna och observationsanteckningar från lektionerna samt för- och eftertest formulerades resultatet. I resultatet framkom att elevernas förutsättningar för att lära sig bråk ökade när läraren synliggjorde täljaren och nämnarens betydelse i kontrast till varandra samt genom att skapa ett tydligt mönster av variation och invarians av de kritiska aspekterna i undervisningen. / In a previous course, we completed a task containing fractions, and discovered that pupils had difficulties learning particular composite fractions. We became interested in finding out how the teacher can create conditions for the pupils to learn and understand fractions. This is also the aim of this study The study aims at identifying the critical aspects for learning fractions and how these can be varied in the teaching of fractions. In this study we have used a learning study which can be seen as a type of action research where the teachers are researching in their own classrooms. Within learning study, the theory of variation is used as for understanding and creating conditions for learning. The lessons were conducted by us, prospective teachers, on three separate occations, the lessons were video recorded. We transcribed these films and then analyzed them. From an analysis of the transcribed material, video recordings and observation notes from the lessons and pre- and post test we formulated the results. The results showed that conditions for learning fractions increased when the teacher made the role of the numerator and dominator visible by contrasting and by establishing a clear pattern of variation and invariance of the critical features.

The integration of image sensors and high performance processors into embedded systems enabled the development of intelligent vision systems. In this thesis, we developed an active autonomous system to be used for surveillance applications. The proposed system detects a single moving object in the field of view automatically and tracks it in a wide area by controlling the pan-tilt-zoom features of the camera. The system can also go to an alarm state to warn the user. The processing unit of the system is a Texas Instruments DM642 Evaluation Module which is a low-cost high performance video &amp / imaging development platform designed to develop and evaluate video based applications.