Wireless sensor networks allow us to instrument our world in novel ways providing detailed insight that had not been possible earlier. Since these networks provide an interface to the physical world, it is necessary for each sensor node to learn its location in the physical space. The availability of location information at individual sensor nodes allows the network to provide higher layer services such as location stamped event reporting, geographic routing, in-network processing etc. A wide range of these sensor network protocols do not require absolute node coordinates and can work with relative node positions. This motivates for the need of anchor free localization algorithms that localize the individual sensor nodes with respect to each other in a local coordinate system. Such algorithms allow the sensor networks to be decoupled from external infrastructure and become truly place and play systems. The primary contributions of this thesis include two anchor free localization algorithms and one location refinement algorithm for ad-hoc wireless sensor networks. Our distributed anchor free localization algorithms do not require any external infrastructure in the form of landmark or manually initialized anchor nodes. These algorithms use measured inter-node distances among some node pairs and localize the entire network in a local coordinate system up to a global translation, rotation and reflection. The relative or virtual coordinates assigned by these algorithms can be readily used with a range of sensor network services like geographic routing, data aggregation, topology control etc. Our first localization algorithm is based on a distributed collaborative approach where all of the nodes in the network collaborate with each other to select a set of nodes. These nodes are localized and then used as reference nodes for the remaining sensor nodes. The novelty of this approach is that instead of solving the localization problem for the entire network upfront, first a small well-formed localization problem is solved and then these results are used to solve the localization problem for the remaining nodes in the network. Our second localization algorithm borrows ideas from the data visualization field and exploits the general undirected graph drawing theory to solve the sensor network localization problem. This algorithm divides the network into a large number of small overlapping clusters and creates local coordinate systems for each of the clusters. These clusters are then merged together in a single coordinate system using a novel distributed algorithm that seeks to minimize the error during this merge process. Our final contribution is a distributed location refinement algorithm that can be used with any of the range based localization algorithms to refine the sensor node coordinates to conform to the measured inter-node distances. We model this coordinate refinement problem as an unconstrained non-linear optimization problem and then transform this optimization problem into an aggregate computation problem. We propose two different approaches to solve this aggregate computation problem in a distributed manner. We evaluate our algorithms with detailed simulations using both Matlab and TinyOS simulator TOSSIM. We also validate our simulation results with experimentation carried out on a real network of MIT Cricket motes. We conclude this thesis with lessons learned during this research and discuss some future directions which can be explored to advance the research in sensor network localization.

Wireless sensor networks allow us to instrument our world in novel ways providing detailed insight that had not been possible earlier. Since these networks provide an interface to the physical world, it is necessary for each sensor node to learn its location in the physical space. The availability of location information at individual sensor nodes allows the network to provide higher layer services such as location stamped event reporting, geographic routing, in-network processing etc. A wide range of these sensor network protocols do not require absolute node coordinates and can work with relative node positions. This motivates for the need of anchor free localization algorithms that localize the individual sensor nodes with respect to each other in a local coordinate system. Such algorithms allow the sensor networks to be decoupled from external infrastructure and become truly place and play systems. The primary contributions of this thesis include two anchor free localization algorithms and one location refinement algorithm for ad-hoc wireless sensor networks. Our distributed anchor free localization algorithms do not require any external infrastructure in the form of landmark or manually initialized anchor nodes. These algorithms use measured inter-node distances among some node pairs and localize the entire network in a local coordinate system up to a global translation, rotation and reflection. The relative or virtual coordinates assigned by these algorithms can be readily used with a range of sensor network services like geographic routing, data aggregation, topology control etc. Our first localization algorithm is based on a distributed collaborative approach where all of the nodes in the network collaborate with each other to select a set of nodes. These nodes are localized and then used as reference nodes for the remaining sensor nodes. The novelty of this approach is that instead of solving the localization problem for the entire network upfront, first a small well-formed localization problem is solved and then these results are used to solve the localization problem for the remaining nodes in the network. Our second localization algorithm borrows ideas from the data visualization field and exploits the general undirected graph drawing theory to solve the sensor network localization problem. This algorithm divides the network into a large number of small overlapping clusters and creates local coordinate systems for each of the clusters. These clusters are then merged together in a single coordinate system using a novel distributed algorithm that seeks to minimize the error during this merge process. Our final contribution is a distributed location refinement algorithm that can be used with any of the range based localization algorithms to refine the sensor node coordinates to conform to the measured inter-node distances. We model this coordinate refinement problem as an unconstrained non-linear optimization problem and then transform this optimization problem into an aggregate computation problem. We propose two different approaches to solve this aggregate computation problem in a distributed manner. We evaluate our algorithms with detailed simulations using both Matlab and TinyOS simulator TOSSIM. We also validate our simulation results with experimentation carried out on a real network of MIT Cricket motes. We conclude this thesis with lessons learned during this research and discuss some future directions which can be explored to advance the research in sensor network localization.

Thesis (Ph. D.)--University of Alabama at Birmingham, 2007. / Description based on contents viewed Feb. 12, 2009; title from PDF t.p. Includes bibliographical references (p. 75-77).

Thesis (M.S.)--Missouri University of Science and Technology, 2009. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed August 25, 2009) Includes bibliographical references.

A cubic lattice with random parameters is reduced to a linear chain by the means of the projection technique. The continued fraction expansion (c.f.e.) approach is herein applied to the density of states. Coefficients of the c.f.e. are obtained numerically by the recursion procedure. Properties of the non-stationary second moments (correlations and dispersions) of their distribution are studied in a connection with the other evidences of transport in a one-dimensional Mori chain. The second moments and the spectral density are computed for the various degrees of disorder in the prototype lattice. The possible directions of the further development are outlined. The physical problem that is addressed in the dissertation is the possibility of the existence of a non-Anderson disorder of a specific type. More precisely, this type of a disorder in the one-dimensional case would result in a positive localization threshold. A specific type of such non-Anderson disorder was obtained by adopting a transformation procedure which assigns to the matrix expressing the physics of the multidimensional crystal a tridiagonal Hamiltonian. This Hamiltonian is then assigned to an equivalent one-dimensional tight-binding model. One of the benefits of this approach is that we are guaranteed to obtain a linear crystal with a positive localization threshold. The reason for this is the existence of a threshold in a prototype sample. The resulting linear model is found to be characterized by a correlated and a nonstationary disorder. The existence of such special disorder is associated with the absence of Anderson localization in specially constructed one-dimensional lattices, when the noise intensity is below the non-zero critical value. This work is an important step towards isolating the general properties of a non-Anderson noise. This gives a basis for understanding of the insulator to metal transition in a linear crystal with a subcritical noise.

Thesis (Ph.D.)--McMaster University (Canada), 1990. / Source: Dissertation Abstracts International, Volume: 52-10, Section: B, page: 5315. Supervisor: Bruno J. Muller.

This research studied the Anderson localization of electrons in two-channel wires with correlated disorder and in DNA molecules. It involved an analytical calculation part where the formula for the inverse localization length for electron states in a two-channel wire is derived. It also involved a computational part where the localization length is calculated for some DNA molecules. Electron localization in two-channel wires with correlated disorder was studied using a single-electron tight-binding model. Calculations were within second-order Born-approximation to second-order in disorder parameters. An analytical expression for localization length as a functional of correlations in potentials was found. Anderson localization in DNA molecules were studied in single-channel wire and two-channel models for electron transport in DNA. In both of the models, some DNA sequences exhibited delocalized electron states in their energy spectrum. Studies with two-channel wire model for DNA yielded important link between electron localization properties and genetic information.

In this work, we investigate the application of Bayesian filtering techniques such as Kalman Filtering and Particle filtering to the problems of network time synchronization, self-localization and radio-frequency (RF) tomography in wireless networks. Networks of large numbers of small, cheap, mobile wireless devices have shown enormous potential in applications ranging from intrusion detection to environmental monitoring. These applications require the devices to have accurate time and position estimates, however traditional techniques may not be available. Additionally RF tomography offers a new paradigm to sense the network environment and could greatly enhance existing network capabilities. While there are some existing works addressing these problems, they all suffer from limitations. Current time synchronization methods are not energy efficient on small wireless devices with low quality oscillators. Existing localization methods do not consider additional sources of information available to nodes in the network such as measurements from accelerometers or models of the shadowing environment in the network. RF tomography has only been examined briefly in such networks, and current algorithms can not handle node mobility and rely on shadowing models that have not been experimentally verified. We address the time synchronization problem by analyzing the characteristics of the clocks in small wireless devices, developing a model for it, and then applying a Kalman filter to track both clock offset and skew. In our investigation into RF tomography, we present a method using a Kalman filter which jointly estimates and tracks static and dynamic objects in the environment. We also use channel measurements collected from a field test of our RF tomography testbed to compare RF shadowing models. For the localization problem, we present two algorithms incorporating additional information for improved localization: one based on a distributed extended Kalman filter that combines local acceleration measurements with signal strength measurements for improved localization, and another that uses a distributed particle filter to incorporate a model of the channel environment.

Tyrimo tikslas – nustatyti įsitraukimo į biodegalų gamybą veiksnius ir įvertinti šalies įsitraukimą į biodegalų gamybą integralumo nacionalinėje ekonomikoje požiūriu. Darbo praktinė vertė. Biodegalų gamyba yra viena iš šiuolaikinės bioekonomikos sričių, kuria susidomi vis daugiau pasaulio šalių. Pastarasis dešimtmetis gali būti apibūdinamas kaip intensyvios biodegalų gamybos plėtros laikotarpis. Šalys, įsitraukdamos į biodegalų gamybą, siekia prisidėti prie darnios energetikos vystymosi. Darbe analizuojama, kaip šalies įsitraukimo į biodegalų gamybą veiksniai varijuoja priklausomai nuo šalies turtingumo naftos ištekliais. Nustatyta, kokie yra dominuojantys įsitraukimo į biodegalų gamybą veiksniai specifinėse šalių grupėse ir kokiu integralumu nacionalinėje ekonomikoje biodegalų gamyba pasižymi šiose šalyse. Tyrimas patvirtina, kad net ir paskatintas politinių iniciatyvų, biodegalų pramonės steigimasis šalyje paprastai grindžiamas išskirtinai didesniu apsirūpinimu biodegalų gamybos ištekliais arba didesne iškastinių energetinių išteklių stoka. Gautos tyrimo išvados gali pasitarnauti formuojant valstybės energetinės politikos gaires alternatyvios energetikos plėtotei. Mokslinio darbo naujumas. Šalies įsitraukimo į biodegalų gamybą vertinimo rezultatai papildo ekonomikos mokslo žinias apie egzistuojančius ryšius tarp ekonominių veiklų plėtojimo ir joms reikalingų gamybos išteklių šalyje gausos. Šių ryšių egzistavimas darbe atskleidžiamas analizuojant bioetanolio gamybą. Tyrimas... [toliau žr. visą tekstą] / Research aim – to identify factors behind engagement in biofuel production and evaluate engagement by a country in terms of production integration in the national economy. Practical value of the research. The production of biofuels is one of the most modern areas of the bioeconomy, which involves more and more countries around the world. The last decade can be described as an intense period of the development of biofuel production. Engaging in the production of biofuels countries seek to contribute to the sustainable energy development. In this research the analysis of factors of country’s engagement in biofuel production, depending on the oil richness of the country, is performed. It was analysed which factors determine the engagement in biofuel production in different groups of countries and which parameters of biofuel production integration in national economy are satisfied in these counties. The study confirms that biofuel industry establishment in the country, even promoted by political initiatives, is usually based on purely larger self-sufficiency in production resources or higher scarcity of fossil energy resource. The resulting findings can serve in shaping the state's energy policy guidelines for the development of alternative energy sources. Originality of the research work. The obtained results supplement the scientific knowledge in economics about the existence of the relationships between development economic activities and the abundance of necessary production... [to full text]

Actions can fail - even though this is well known, little is known about what distinguishes neurophysiological processes preceding errors and correct actions. In this study, relying on the Theory of Event Coding, we test the assumption that only specific aspects of information coded in EEG activity are relevant for understanding processes leading to response errors. We examined N = 69 healthy participants who performed a mental rotation task and combined temporal EEG signal decomposition with multivariate pattern analysis (MVPA) and source localization analyses. We show that fractions of the EEG signal, primarily representing stimulus-response translation (event file) processes and motor response representations, are essential. Stimulus representations were less critical. The source localization results revealed widespread activity modulations in structures including the frontopolar, the middle and superior frontal, the anterior cingulate cortex, the cuneus, the inferior parietal cortex, and the ventral stream regions. These are associated with differential effects of the neural dynamics preceding correct/erroneous responses. The temporal-generalization MVPA showed that event file representations and representations of the motor response were already distinct 200 ms after stimulus presentation and this lasted till around 700 ms. The stability of this representational content was predictive for the magnitude of posterror slowing, which was particularly strong when there was no clear distinction between the neural activity profile of event file representations associated with a correct or an erroneous response. The study provides a detailed analysis of the dynamics leading to an error/correct response in connection to an overarching framework on action control.