Efficient algorithms for time synchronization, including compensation for clock drift, are essential in order to obtain reliable fusion of data samples from multiple wireless sensor nodes. This paper evaluates the performance of algorithms based on three different approaches; one that synchronizes the local clocks on the sensor nodes, and a second that uses a single clock on the receiving node (e.g. a mobile phone), and a third that uses broadcast messages. The performances of the synchronization algorithms are evaluated in wireless personal area networks, especially Bluetooth piconets and ZigBee/IEEE 802.15.4 networks. A new approach for compensation of clock drift and a realtime implementation of single node synchronization from the mobile phone are presented and tested. Finally, applications of data fusion and time synchronization are shown in two different use cases; a kayaking sports case, and monitoring of heart and respiration of prematurely born infants. / <p>QC 20130605</p>

The two main challenges of the twenty-first century are the scarcity of energy sources and global warming; trigged by the emission of greenhouse gases. In this context, solar energy became increasingly relevant. Because it makes optimal use of the resources, minimizes environmental impacts, and is sustainable over time. However, before installing solar panels, it is convenient pre-assessing the amount of energy that a building can harvest. This study proposes a methodology to semi-automatically generate information a building scale; on a large area. This thesis integrates airborne Light Detection and Ranging (LiDAR) and WoldView-2 satellite data for modelling the solar energy potential of building rooftops in San Francisco, California. The methodology involved building detection solar potential analysis, and estimations at building scale. First, the outline of building rooftops is extracted using an object-based approach. Next, the solar modelling is carried out using the solar radiation analysis tool in ArcGIS, Spatial Analyst. Then, energy that could potentially be harvested by each building rooftop is estimated. The energy estimation is defined in economic and environmental terms.

Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Jeff Shamma; Committee Member: Eric Feron; Committee Member: Magnus Egerstedt. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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With the purpose of classifying and modelling stress, different sensors, signal features, machine learning methods, and stress experiments have been compared. Two databases have been studied: the MIT driver stress database and a new experimental database, where three stress tasks have been performed for 9 subjects: the Trier Social Stress Test, the Socially Evaluated Cold Pressor Test and the d2 test, of which the latter is not classically used for generating stress. Support vector machine, naive Bayes, k-nearest neighbor and probabilistic neural network classification techniques were compared, with support vector machines achieving the highest performance in general (99.5 ±0.6 %$on the driver database and 91.4 ± 2.4 % on the experimental database). For both databases, relevant features include the mean of the heart rate and the mean of the galvanic skin response, together with the mean of the absolute derivative of the galvanic skin response signal. A new feature is also introduced with great performance in stress classification for the driver database. Continuous models for estimating stress levels have also been developed, based upon the perceived stress levels given by the subjects during the experiments, where support vector regression is more accurate than linear and variational Bayesian regression. / I syfte att klassificera och modellera stress har olika sensorer, signalegenskaper, maskininlärningsmetoder och stressexperiment jämförts. Två databaser har studerats: MIT:s förarstressdatabas och en ny databas baserad på egna experiment, där stressuppgifter har genomförts av nio försökspersoner: Trier Social Stress Test,  Socially Evaluated Cold Pressor Test och d2-testet, av vilka det sistnämnda inte normalt används för att generera stress. Support vector machine-, naive Bayes-, k-nearest neighbour- och probabilistic neural network-algoritmer har jämförts, av vilka support vector machine har uppnått den högsta prestandan i allmänhet (99.5 ± 0.6 % på förardatabasen, 91.4 ± 2.4 %  på experimenten). För båda databaserna har signalegenskaper såsom medelvärdet av hjärtrytmen och hudens ledningsförmåga, tillsammans med medelvärdet av beloppet av hudens ledningsförmågas derivata identifierats som relevanta. En ny signalegenskap har också introducerats, med hög prestanda i stressklassificering på förarstressdatabasen. En kontinuerlig modell har också utvecklats, baserad på den upplevda stressnivån angiven av försökspersonerna under experimenten, där support vector regression har uppnått bättre resultat än linjär regression och variational Bayesian regression.

No description available.

The two main challenges of the twenty-first century are the scarcity of energy sources and global warming; trigged by the emission of greenhouse gases. In this context, solar energy became increasingly relevant. Because it makes optimal use of the resources, minimizes environmental impacts, and is sustainable over time. However, before installing solar panels, it is convenient pre-assessing the amount of energy that a building can harvest. This study proposes a methodology to semi-automatically generate information a building scale; on a large area. This thesis integrates airborne Light Detection and Ranging (LiDAR) and WoldView-2 satellite data for modelling the solar energy potential of building rooftops in San Francisco, California. The methodology involved building detection solar potential analysis, and estimations at building scale. First, the outline of building rooftops is extracted using an object-based approach. Next, the solar modelling is carried out using the solar radiation analysis tool in ArcGIS, Spatial Analyst. Then, energy that could potentially be harvested by each building rooftop is estimated. The energy estimation is defined in economic and environmental terms.

Thesis (M.S.)--Rochester Institute of Technology, 2007. / Typescript. Includes bibliographical references (leaves 92-93).

Thesis (Ph.D.) -- McMaster University, 1997. / Includes bibliographical references Also available via World Wide Web.

Thesis (M.S.)--Auburn University, 2008. / Abstract. Vita. Includes bibliographical references (p. 58-62).