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ITC/USA 2006 Conference Proceedings / The Forty-Second Annual International Telemetering Conference and Technical Exhibition / October 23-26, 2006 / Town and Country Resort & Convention Center, San Diego, California / This paper describes the design and successful development of an acoustic modem for potential use in underwater ecological sensor networks. The presentation includes theoretical study, design and development of both software and hardware, laboratory experiments, full-scale field tests, and the documentation and analysis of field-test results.

ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada / Underwater acoustic (UWA) telemetry requires wideband waveforms for anti-multipath which are simultaneously easy to equalize and demodulate. The Walsh/m-sequence waveforms proposed here are robust to multipath and with appropriate time-guard bands do not require equalization. For example, in the UCSB prototype acoustic modem, a data rate of 133 bps is achieved using 8-ary Walsh signaling with an 11.2 msec. symbol duration. Demodulation is performed using noncoherent detection, and hence accurate phase tracking, which is difficult to achieve in the UWA channel, is not required. However, telemetry from unmanned underwater vehicles (UUVs) is more problematic due to large Doppler shifts resulting from platform motion. A new receiver algorithm based on Matching Pursuits is proposed which combines channel and Doppler shift estimation. Symbol-error rate (SER) simulation results are presented for the UWA modem under realistic Doppler/multipath conditions.

The improved spectral resolution of modern hyperspectral sensors provides a means for discriminating subtly different classes of on ground materials in remotely sensed images. However, in order to obtain statistically reliable classification results, the number of necessary training samples can increase exponentially as the number of spectral bands increases. Obtaining the necessary number of training signals for these high-dimensional datasets may not be feasible. The problem can be overcome by preprocessing the data to reduce the dimensionality and thus reduce the number of required training samples. In this thesis, three dimensionality reduction methods, all based on parametric projection pursuits, are investigated. These methods are the Sequential Parametric Projection Pursuits (SPPP), Parallel Parametric Projection Pursuits (PPPP), and Projection Pursuits Best Band Selection (PPBBS). The methods are applied to very high spectral resolution data to transform the hyperspectral data to a lower-dimension subspace. Feature extractors and classifiers are then applied to the lower-dimensional data to obtain target detection accuracies. The three projection pursuit methods are compared to each other, as well as to the case of using no dimensionality reduction preprocessing. When applied to hyperspectral data in a precision agriculture application, discriminating sicklepod and cocklebur weeds, the results showed that the SPPP method was optimum in terms of accuracy, resulting in a classification accuracy of >95% when using a nearest mean, maximum likelihood, or nearest neighbor classifier. The PPPP method encountered optimization problems when the hyperspectral dimensionality was very high, e.g. in the thousands. The PPBBS method resulted in high classification accuracies, >95%, when the maximum likelihood classifier was utilized; however, this method resulted in lower accuracies when the nearest mean or nearest neighbor classifiers were used. When using no projection pursuit preprocessing, the classification accuracies ranged between ~50% and 95%; however, for this case the accuracies greatly depended on the type of classifier being utilized.

This thesis investigates the use of sequential parametric projection pursuits (SPPP) for hyperspectral dimensionality reduction and invasive species target recognition. The SPPP method is implemented in a top-down fashion, where hyperspectral bands are used to form an increasing number of smaller groups, with each group being projected onto a subspace of dimensionality one. Both supervised and unsupervised potential projections are investigated for their use in the SPPP method. Fisher?s linear discriminant analysis (LDA) is used as a potential supervised projection. Average, Gaussian-weighted average, and principal component analysis (PCA) are used as potential unsupervised projections. The Bhattacharyya distance is used as the SPPP performance index. The performance of the SPPP method is compared to two other currently used dimensionality reduction techniques, namely best spectral band selection (BSBS) and best wavelet coefficient selection (BWCS). The SPPP dimensionality reduction method is combined with a nearest mean classifier to form an automated target recognition (ATR) system. The ATR system is tested on two invasive species hyperspectral datasets: a terrestrial case study of Cogongrass versus Johnsongrass and an aquatic case study of Waterhyacinth versus American Lotus. For both case studies, the SPPP approach either outperforms or performs on par with the BSBS and BWCS methods in terms of classification accuracy; however, the SPPP approach requires significantly less computational time. For the Cogongrass and Waterhyacinth applications, the SPPP method results in overall classification accuracy in the mid to upper 90?s.

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The theoretical problem of finding the solution to an underdeterminedset of linear equations has for several years attracted considerable attentionin the literature. This problem has many practical applications.One example of such an application is compressed sensing (cs), whichhas the potential to revolutionize how we acquire and process signals. Ina general cs setup, few measurement coefficients are available and thetask is to reconstruct a larger, sparse signal.In this thesis we focus on algorithm design and selected applicationsfor cs. The contributions of the thesis appear in the following order:(1) We study an application where cs can be used to relax the necessityof fast sampling for power spectral density estimation problems. Inthis application we show by experimental evaluation that we can gainan order of magnitude in reduced sampling frequency. (2) In order toimprove cs recovery performance, we extend simple well-known recoveryalgorithms by introducing a look-ahead concept. From simulations it isobserved that the additional complexity results in significant improvementsin recovery performance. (3) For sensor networks, we extend thecurrent framework of cs by introducing a new general network modelwhich is suitable for modeling several cs sensor nodes with correlatedmeasurements. Using this signal model we then develop several centralizedand distributed cs recovery algorithms. We find that both thecentralized and distributed algorithms achieve a significant gain in recoveryperformance compared to the standard, disconnected, algorithms.For the distributed case, we also see that as the network connectivity increases,the performance rapidly converges to the performance of thecentralized solution. / <p>QC 20120229</p>

Syftet med detta examensarbete är att studera och bidra med nya insikter om vad som är meningsfull kunskap för eleverna på en gymnasiesärskolas individuella program. Anledningen till att jag vill undersöka detta är att jag i mitt arbete inom denna skolform nästan dagligen möter ett dilemma i frågan om vad som är det viktigaste för den enskilda eleven att lära sig för att ha de bästa förutsättningarna i sitt framtida vuxenliv. Styrdokumenten för gymnasiesärskolans individuella program lämnar ett stort utrymme till individuella anpassningar, både beträffande stöd och kunskapsutveckling, och därmed blir också tolkningsutrymmet stort. Därför vill jag undersöka vilka uppfattningar lärare och elever, bland andra, har kring vad som är meningsfulla kunskaper för eleverna att få med från utbildningen ut i vuxenlivet. För att finna svar på detta har jag utgått från ett fenomenologiskt inspirerat metodval med kvalitativa, semistrukturerade intervjuer. I analysen av resultatet av intervjuerna har jag tagit hjälp av teorier om KASAM och pliktetik respektive konsekvensetik för att belysa och perspektivera empirin. Huvuddragen i resultatet handlar om att meningsfulla kunskaper för eleverna på den undersökta gymnasiesärskolan utgår från elevernas framtidsbehov kopplat till vuxenliv och framtida sysselsättning. Följaktligen är det viktigt att få en bild av hur respektive elevs framtida liv kan se ut beträffande sysselsättning och vuxenliv. Eftersom det flesta eleverna, efter gymnasiet, går vidare till daglig verksamhet framstår det också som viktigt att eleverna i skolan arbetar med kunskaper relaterade till denna sysselsättning. Därmed framträder också en tydlig bild av att samarbetet mellan skolan och daglig verksamhet skulle behöva stärkas, bland annat i syfte att skapa samsyn kring vilka kunskaper som kan vara relevanta för den enskilda eleven utifrån framtida potentiella sysselsättningar. / The purpose of this thesis is to study and contribute with new insights about what is meaningful knowledge for the students who study the individual program on a special needs upper secondary school. The reason I want to investigate this is that I, in my work within this school form, almost daily meet a dilemma in the question about what´s the most important for the specific student to learn to get the best possibilities in their future adult life. The control documents regarding the special needs upper secondary school gives great opportunities to individual adjustments, concerning both support and learning and thereby the interpretation space is large. Therefore, I want to investigate the opinions of teachers and students, amongst others, about what is meaningful knowledge for the students to bring along into the adult life. To find answers to my questions I have used a phenomenologically inspired method including qualitative, semi-structured interviews. In the analysis of the results of the interviews I have applied theories about SOC together with duty ethics and impact ethics to help me illuminate and get perspectives on the empirical. The main results of the study indicate that meaningful knowledge for the students of the concerned special needs upper secondary school depend on the student’s future needs regarding adult life and future pursuits. Consequently, it is important to have an understanding on what the adult life and future pursuits of the specific student may consist of. Since the main part of the students, after leaving secondary school, continues in daily activities it also appears important to work with abilities linked to this kind of employment. Therefore, there is also a clear picture of the fact that the cooperation between school and daily activities would need to be strengthened, for instance to create consensus about what knowledges are relevant to the individual student regarding potential future pursuits.

This thesis investigates the development of commercial leisure in a northern community, Halifax, over a period of 200 years. It examines a range of leisure pursuits including the public house, theatre and sports and traces their development during a period of population growth and industrialization which came to be based increasingly around the factory. It analyses whether Halifax was typical in the way commercial leisure developed or whether particular local conditions influenced the development of commercial leisure. During the period, Halifax, an ancient town, developed from an important centre of the textile trade in England into a classic Victorian mill town supporting a broad base of industries. Leisure developed from a leisure culture based around traditional holidays and pastimes to a highly commercialized leisure experience increasingly provided by regional and national companies and a sporting calendar that included structured leagues with professional clubs and games played seasonally.

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