The master‘s thesis deals with the analysis of the hand-written text. There is a design and a realization of a system for the purpose of diagnosing a Parkinson’s desease based on the analysis of hand-written text. The system consists from several modules and it is programmed in the programming environment of MATLAB. The first module provides pre-processing of the records to adjust records to the form suitable for the segmentation. Afterwards, the records are divided into those with signals onto the surface of the tablet and those with the signals above the surface of the tablet. In the next module the records are segmented by the two-phase metod of automatic segmentation.High-level featuresare calculated from the extracted features. The results of the statistical analysis are exported in the form suitable for the classification process. The classification is performed by the proposed model made in the programming environment of RapidMiner. The output of designed system is the trained model capable of automatic classification of the Parkinson’s disease by the analysis of the hand-written text.

This diploma thesis deals with the speech signal processing and vowel analysis mainly to uncover differences in speech features depending on the emotional state of speaker. Created application ARePa for speech signal processing was developer in Matlab environment and contains Graphical User Interface (GUI) for better manipulation with ARePa and analysed records. The application includes a complete analysis of the speech signal and further comparison of current feature with feature values from database using histograms. Of course, the developer application allows the archivation of currently analysed records into database.

Tato práce se zabývá extrakcí vhodných příznaků pro rozpoznávání řečníka z delších časových úseků. Po představení současných technik pro extrakci takových příznaků navrhujeme a popisujeme novou metodu pracující v časovém rozsahu fonémů a využívající známou techniku i-vektorů. Velké úsilí bylo vynaloženo na nalezení vhodné reprezentace temporálních příznaků, díky kterým by mohly být systémy pro rozpoznávání řečníka robustnější, zejména modelování prosodie. Náš přístup nemodeluje explicitně žádné specifické temporální parametry řeči, namísto toho používá kookurenci řečových rámců jako zdroj temporálních příznaků. Tuto techniku testujeme a analyzujeme na řečové databázi NIST SRE 2008. Z výsledků bohužel vyplývá, že pro rozpoznávání řečníka tato technika nepřináší očekávané zlepšení. Tento fakt diskutujeme a analyzujeme ke konci práce.

<p>Hyporheic exchange is key to buffer water quality and temperatures in streams and rivers, while also providing localized downwelling and upwelling microhabitats. In this research, the effect of geomorphological parameters on hyporheic exchange has been assessed from a physical standpoint: surface and subsurface flow fields, pressure distribution across the sediment/water interface and the residence time in the bed.<br></p><p>First, we conduct a series of numerical simulations to systematically explore how the fractal properties of bedforms are related to hyporheic exchange.We compared the average interfacial flux and residence time distribution in the hyporheic zone with respect to the magnitude of the power spectrum and the fractal dimension of riverbeds. The results show that the average interfacial flux increases logarithmically with respect to the maximum spectral density whereas it increases exponentially with respect to fractal dimension.<br></p><p>Second, we demonstrate how the Froude number affects the free-surface profile, total head over sediment bed and hyporheic flux. When the water surface is fixed,the vertical velocity profile from the bottom to the air-water interface follows the law of the wall so that the velocity at the air-water interface has the maximum value. On the contrary, in the free-surface case, the velocity at the interface no longer has the maximum value: the location having the maximum velocity moves closer to the sediment bed. This results in increasing velocity near the bed and larger head gradients, accordingly.<br></p><p>Third,we investigate how boulder spacing and embeddedness affect the near-bed hydrodynamics and the surface-subsurface water exchange.When the embeddedness is small, the recirculation vortex is observed in both closely-packed and loosely-packed cases, but the size of vortex was smaller and less coherent in the closely-packed case. For these dense clusters, the inverse relationship between embeddedness and flux no longer holds. As embeddedness increases, the subsurface flowpaths move in the lateral direction, as the streamwise route is hindered by the submerged boulder. The average residence time therefore decreases as the embeddedness increases.<br></p><p>Lastly, we propose a general artificial neural network for predicting the pressure field at the channel bottom using point velocities at different level. We constructed three different data-driven models with multivariate linear regression, local linear regression and artificial neural network. The input variable is velocity in x, y, and z directions and the target variable is pressure at the sediment bed. Our artificial neural network model produces consistent and accurate prediction performance under various conditions whereas other linear surrogate models such as linear multivariate regression and local linear multivariate regression significantly depend on input variable.<br></p><p>As restoring streams and rivers has moved from aesthetics and form to a more holistic approach that includes processes, we hope our study can inform designs that benefit both structural and functional outcomes. Our results could inform a number of critical processes, such as biological filtering for example. It is possible to use our approach to predict hyporheic exchange and thus constrain the associated biogeochemical processing under different topographies. As river restoration projects become more holistic, geomorphological, biogeochemical and hydro-ecological aspects should also be considered.<br></p>

The aim of this work was to determine whether line-type features(straight lines found in geometry considered interesting by auser) could be identified in spatial map data of indoorenvironments produced by the Microsoft Hololens augmented realityheadset. Five different data sets were used in this work onwhich the feature detection was performed, these data sets wereprovided as sample data representing the spatial map of fivedifferent rooms scanned using the Hololens headset which areavailable as part of the Hololens emulator. Related work onfeature detection in point clouds and 3D meshes were investigatedto try and find a suitable method to achieve line-type featuredetection. The chosen detection method used LSQ-plane fitting andrelevant cutoff variables to achieve this, which was inspired byrelated work on the subject of feature identification and meshsimplification. The method was evaluated using user-placedvalidation features and the distance between them and the detectedfeatures, defined using the midpoint diistance metric was used asa measure of quality for the detected measures. The resultingfeatures were not accurate enough to reliably or consistentlymatch the validation features inserted in the data and furtherimprovements to the detection method would be necessary to achievethis. A local feature-edge detection using the SOD &amp; ESODoperators was considered and tested but was found to not besuitable for the spatial data provided by the Hololens emulator.The results shows that finding these features using the provideddata is possible, and the methods to produce them numerous. Thechoice of mehtod is however dependent on the ultimate applicationof these features, taking into account requirements for accuracyand performance.

Spelling development is a linguistic process which involves the interaction of phonological, orthographic, and morphological knowledge (Bahr, Silliman, & Berninger, in press). It is also clear these linguistic factors are influenced by a person's dialect. Previous research has indicated that use of African American English (AAE) does influence spelling performance (Kohler, Bahr, Silliman, Bryant, Apel, & Wilkinson, 2007); however, few studies have considered how dialect use influences spelling as a function of spelling task (i.e., real vs. non-word tasks), error category (phonological, orthographic, or morphological) or grade. A secondary goal was to note if dialectal or developmental errors predominated in the noted misspellings. The Phonological, Orthographic, and Morphological Assessment of Spelling (POMAS, Silliman, Bahr, & Peters, 2006) was used to provide a fine-grained analysis of the spelling errors of 80 typically developing African American children in grades 1 (n = 39) and 3 (n = 41). These children were screened for language ability and they were determined to be AAE speakers by observing their use of phonological and/or morphosyntactic dialect features when retelling a story. Age-appropriate real word and non-word spelling tasks were developed which incorporated common features of AAE. A three-way ANOVA revealed that differences in error frequency were dependent upon word type, error type and grade. On the real word spelling task, children in both grades made more orthographic errors than phonological or morphological errors. On the non-word spelling task, students in both grades made fewer orthographic errors and students in grade 3 made significantly more phonological errors, while the number of phonological errors noted remained fairly constant across tasks for the children in grade 1. Common misspelling patterns revealed developmental errors, as well as errors attributed to AAE. A closer look at the occurrence of AAE features revealed that first graders were more likely to reflect dialectal patterns in their spelling than the third graders. This is possibly due to differences in exposure to the academic register and experience in code-switching. Finally, the real words elicited more AAE features than non-words suggesting that phonetic and linguistic contexts might influence the occurrence and use of AAE.

This MA thesis focuses on the stylistically marked features that occur in an English radio debate called Any Questions? aired by BBC - Radio 4 and a Czech radio debate called Speciál Martina Veselovského aired on Český rozhlas 1 - Radiožurnál. Stylistically marked features are restricted to certain kinds of social context: in the case of this thesis, it is two radio debates broadcast by public service media. Those linguistics features that are considered stylistically marked in the two debates are identified on the morphological, syntactical and lexical level, and classified into categories based upon a view of their functions. Subsequently, they are described as standard or nonstandard. Some of the features found are shared by both debates. However, some are, due to the different language systems concerned, symptomatic of only one of the languages. The difference between the English and the Czech stylistically marked features is also revealed as to the frequency of their occurrence. Finally, the conclusions about the level of informality of the two debates are drawn.

In recent years wearable devices have been advancing at a rapid pace and one of the largest growing segments is the smart glass segment. In this thesis the feasibility of today’s ARM-based smart glasses are evaluated for automatic license plate recognition (ALPR). The license plate is by far the most prominent visual feature to identify a spe- cific vehicle, and exists on both old and newly produced vehicles. This thesis propose an ALPR system based on a sequence of vertical edge detection, a cascade classifier, verti- cal and horizontal projection as well as a general purpose optical character recognition library. The study further concludes that the optimal input resolution for license plate detection using vertical edges is 640x360 pixels and that the license plate need to be at least 20 pixels high or the characters 15 pixels high in order to successfully segment the plate and recognize each character. The separate stages were successfully implemented into a complete ALPR system that achieved 79.5% success rate while processing roughly 3 frames per second when running on a pair of Google Glass. / Under de senaste åren har området wearables avancerat i snabb takt, och ett av de snabbast växande segmenten är smarta glaögon. I denna examensuppsats utvärderas lämpligheten av dagens ARM-baserade smarta glasögon med avseende på automatisk registreringsskyltigenkänning. Registreringsskylten är den i särklass mest framträdande visuella egenskapen som kan användas för att identifiera ett specifikt fordon, och den finns på både gamla och nyproducerade fordon. Detta examensarbete föreslår ett system för automatisk registreringsskyltigenkänning baserat på en följd av vertikal kantdetektering, en kaskad av boostade klassificerare, vertikal och horisontell projektion samt ett optiskt teckenigenkänningsbibliotek. Studien konstaterar vidare att den optimala upplösningen för registreringsskyltdetektion med hjälp av vertikala kanter på smarta glasögonär 640x360 pixlar och att registreringsskylten måste vara minst 20 pixlar hög eller tecknen 15 pixlar höga för att registreringsskylten framgångsrikt skall kunna segmenteras samt tecken identifieras. De separata stegen implementerades framgångsrikt till ett system för automatisk registreringsskyltigenkänning på ett par Google Glass och lyckades känna igen 79,5% av de testade registreringsskyltarna, med en hastighet av ungefär 3 bilder per sekund.

A convertible bond (CB) is a financial derivative, a so called hybrid security. It is an issued contract from a company or a government, which is paid for up-front. The contract yields a known amount at the specified maturity date, unless the holder chooses to convert it into an amount of the underlying asset. This kind of financial products can have complex features affecting the contract price and the optimal exercising situation. The partial differential equation (PDE) approach used for pricing financial derivatives makes it possible to describe convertible bonds with a physical model, a reversed diffusion described by a parabolic PDE. One can sometimes find both analytical and numerical solutions for this type of PDEs and interpret the solutions from a financial point of view, as they suggest predictable behaviour of the contract price.

BACKGROUND: Physical activity for the majority of individuals is below recommended levels despite strong evidence of its significant health benefits. Activity tracker devices present as a promising and affordable tool to help promote physical activity and active choices. Additionally, young adults present as an ideal age group to implement behavior change interventions. OBJECTIVE: To determine what features of activity tracker hardware and software are helpful in motivating active choices. METHODS: This cross-sectional study included 149 participants ranging in age from 18-29 years old who wore an ActiGraph GT3X+ accelerometer for one week. They then continued to wear the accelerometer in addition to a randomly assigned activity tracker (Apple Watch, Fitbit Surge, Basis Peak, or Microsoft Band 2) for an additional week. They also used the corresponding app for their activity tracker. Participants filled out a survey about their experience at the end of the study RESULTS: Overall hardware rating (p = 0.162) and overall software rating (p = 0.125) did not differ between the four devices. Degree of motivation of the hardware (p = 0.177) and software (p = 0.120) was also similar for all the activity trackers. There were 625 positive comments made about tracker hardware with the majority of these comments concerning mode options (n = 149), other (n = 94), and battery (n = 79). There were 287 positive software comments with the majority in the categories of other (n = 78) and information (n = 68). CONCLUSIONS: The analyses of our data did not show a significant difference between devices in any category. Furthermore, results indicated a high number of positive comments for both hardware and software overall. Users also reported device hardware and software to be personally motivating.