Example-based methods are effective for parameter estimation problems when the underlying system is simple or the dimensionality of the input is low. For complex and high-dimensional problems such as pose estimation, the number of required examples and the computational complexity rapidly becme prohibitively high. We introduce a new algorithm that learns a set of hashing functions that efficiently index examples relevant to a particular estimation task. Our algorithm extends a recently developed method for locality-sensitive hashing, which finds approximate neighbors in time sublinear in the number of examples. This method depends critically on the choice of hash functions; we show how to find the set of hash functions that are optimally relevant to a particular estimation problem. Experiments demonstrate that the resulting algorithm, which we call Parameter-Sensitive Hashing, can rapidly and accurately estimate the articulated pose of human figures from a large database of example images.

This report describes a program which automatically characterizes the behavior of any driven, nonlinear, electrical circuit. To do this, the program autonomously selects interesting input parameters, drives the circuit, measures its response, performs a set of numeric computations on the measured data, interprets the results, and decomposes the circuit's parameter space into regions of qualitatively distinct behavior. The output is a two-dimensional portrait summarizing the high-level, qualitative behavior of the circuit for every point in the graph, an accompanying textual explanation describing any interesting patterns observed in the diagram, and a symbolic description of the circuit's behavior which can be passed on to other programs for further analysis.

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 78-82).

In recent years, the use of self-associating block copolymer based drug delivery systems have attracted increasing attention as nanoscopic carriers for the encapsulation and the controlled delivery of water insoluble drugs. Currently, most of the drug formulations proceed by trial and error method with no distinct method to predict the right combination of block copolymers and drugs to give all the desired functional properties. This is simply because such drug delivery systems involve complex intermolecular interactions and geometric fitting of molecules of different shapes. So, in the context of block copolymer design process, quantification and prediction of the interactions between potential block copolymers and the target drug are of great importance. Computer simulations that can predict the level and type of interactions encountered in drug/block copolymer pairs will enable researchers to make educated decisions on choosing a particular polymeric carrier for a given drug, avoiding time consuming and expensive trial and error based formulation experiments. In the present thesis, we reported the use of molecular dynamics (MD) simulation to predict the solubility of sets of hydrophobic drug molecules having different spatial distribution of hydrogen bond forming moieties in a series of micelle-forming PEO-b-PCL block copolymers with and without functionalized PCL blocks. The solubility predictions based on the MD results were then compared with those obtained from the solubility experiments and those obtained by the commonly used group contribution method (GCM). MD analysis techniques like radial distribution functions provided useful atomistic details to understand the molecular origin of miscibility and/or immiscibility observed between drugs and di-block copolymers. Based on the evidence of reported work, intermolecular specific interactions, intra-molecular interactions, local molecular packing, and stereochemistry of the hydrophobic block all play important roles in inducing miscibility between drugs and block copolymers. Additionally, not only the architecture of block copolymers but also the molecular characteristics of drug molecules, e.g., spatial distributions of hydrogen bond donors and acceptors on their molecules can affect the miscibility characteristics of binary mixtures. Depending on the groups present on drugs and block copolymers, any of the above factors can play vital role in the process of favouring encapsulation. The understanding of relative contributions of these interactions can help us to customize the performance of drug carriers by engineering the structure of block copolymers. / Chemical Engineering

Thesis (Ph. D.)--Chalmers tekniska högskola and Göteborgs universitet, 2006. / Includes bibliographical references (p. 219-224) and index.

Despite the immense progress made by molecular biology in cataloging andcharacterizing molecular elements of life and the success in genome sequencing, therehave not been comparable advances in the functional study of complex phenotypes.This is because isolated study of one molecule, or one gene, at a time is not enough byitself to characterize the complex interactions in organism and to explain the functionsthat arise out of these interactions. Mathematical modeling of biological systems isone way to meet the challenge.My research formulates the modeling of gene regulation as a control problem andapplies systems and control theory to the identification, analysis, and optimal controlof genetic regulatory networks. The major contribution of my work includes biologicallyconstrained estimation, dynamical analysis, and optimal control of genetic networks.In addition, parameter estimation of nonlinear models of biological networksis also studied, as a parameter estimation problem of a general nonlinear dynamicalsystem. Results demonstrate the superior predictive power of biologically constrainedstate-space models, and that genetic networks can have differential dynamic propertieswhen subjected to different environmental perturbations. Application of optimalcontrol demonstrates feasibility of regulating gene expression levels. In the difficultproblem of parameter estimation, generalized EM algorithm is deployed, and a set of explicit formula based on extended Kalman filter is derived. Application of themethod to synthetic and real world data shows promising results.

This thesis concerns the identification of dynamic models in systems biology. and is structured into two parts. Both parts concern building dynamic models from observed data, but are quite different in perspective, rationale and mathematics. The first part considers the development of novel identification techniques that are particularly tailored to (molecular) biology and considers two approaches. The first approach reformulates the parameter estimation problem as a feasibility problem. This reformulation allows the invalidation of models by analysing entire parameter regions. The second approach utilises nonlinear observers and a transformation of the model equations into parameter free coordinates. The parameter free coordinates allow the design of a globally convergent observer, which in turn estimates the parameter values, and further, allows to identify modelling errors or unknown inputs/influences. Both approaches are bottom up approaches that require a mechanistic understanding of the underlying processes (in terms of a biochemical reaction network) leading to complex nonlinear models. The second part is an example of what can be done with classical, well developed tools from systems identification when applied to hitherto unattended problems.In particular, part two of my thesis develops a modelling framework for rat movements in an experimental setup that it widely used to study learning and memory.The approach is a top down approach that is data driven resulting in simple linear models.

This thesis assesses the water quality of the River Nile around the city Khartoum in Khartoum State, Sudan Republic, and investigates eventual influences of the city on the River Nile by analysis of the following parameters: temperature, pH, and conductivity, and Adsorbable Organic Halogen (AOX), cadmium (Cd), lead (Pb), chromium (Cr), Total Organic Carbon(TOC) and Nitrate (NO3− ). A survey of the area is also included. It was concluded that the city Khartoum added small but legible concentrations of cadmium, lead, chromium and TOC to the river Nile. However, the resulting concentrations were all within acceptable levels. Also, the observed results showed that the Blue and White Nile, which merge together upstream on the outskirts of Khartoum, had concentrations of AOX resp. chromium, which were not suitable for drinking water.

We study the capture of a particle into resonance at a potential hole with dissipative perturbation and periodic outside force. The measure of resonance solutions is evaluated. We also derive an asymptotic formula for the parameter range of those solutions which are captured into resonance.

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