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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

Techniques for reducing the disruption of superior building blocks in genetic algorithms /

Corcoran, Arthur Leo, January 1994 (has links)
Thesis (Ph.D.)--University of Tulsa, 1994. / Includes bibliographical references (leaves 115-123).

Online exploration and search in graphs /

Trippen, Gerhard Wolfgang. January 2006 (has links)
Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2006. / Includes bibliographical references (leaves [78]-84). Also available in electronic version.

Non-blocking array-based algorithms for stacks and queues /

Shafiei, Niloufar. January 2007 (has links)
Thesis (M.Sc.)--York University, 2007. Graduate Programme in Computer Science and Engineering. / Typescript. Includes bibliographical references (leaves 170-173). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:MR38826

Improved results on models of greedy and primal-dual algorithms /

Kwon, Hyukjoon. January 2008 (has links)
Thesis (M.Sc.)--York University, 2008. Graduate Programme in Computer Science. / Typescript. Includes bibliographical references (leaves 49-51). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:MR45954

Scalable temporal latent space inference for link prediction in dynamic social networks (extended abstract)

Zhu, Linhong, Guo, Dong, Yin, Junming, Ver Steeg, Greg, Galstyan, Aram 04 1900 (has links)
Understanding and characterizing the processes driving social interactions is one of the fundamental problems in social network research. A particular instance of this problem, known as link prediction, has recently attracted considerable attention in various research communities. Link prediction has many important commercial applications, e.g., recommending friends in an online social network such as Facebook and suggesting interesting pins in a collection sharing network such as Pinterest. This work is focused on the temporal link prediction problem: Given a sequence of graph snapshots G1, · ··, Gt from time 1 to t, how do we predict links in future time t + 1? To perform link prediction in a network, one needs to construct models for link probabilities between pairs of nodes. A temporal latent space model is proposed that is built upon latent homophily assumption and temporal smoothness assumption. First, the proposed modeling allows to naturally incorporate the well-known homophily effect (birds of a feather flock together). Namely, each dimension of the latent space characterizes an unobservable homogeneous attribute, and shared attributes tend to create a link in a network.

A multi-fidelity analysis selection method using a constrained discrete optimization formulation

Stults, Ian Collier. January 2009 (has links)
Thesis (Ph.D)--Aerospace Engineering, Georgia Institute of Technology, 2010. / Committee Chair: Mavris, Dimitri; Committee Member: Beeson, Don; Committee Member: Duncan, Scott; Committee Member: German, Brian; Committee Member: Kumar, Viren. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Beneath the surface electrocardiogram: computer algorithms for the non-invasive assessment of cardiac electrophysiology

Torbey, Sami 03 October 2013 (has links)
The surface electrocardiogram (ECG) is a periodic signal portraying the electrical activity of the heart from the torso. The past fifty years have witnessed a proliferation of computer algorithms destined for ECG analysis. Signal averaging is a noise reduction technique believed to enable the surface ECG to act as a non-invasive surrogate for cardiac electrophysiology. The P wave and the QRS complex of the ECG respectively depict atrial and ventricular depolarization. QRS detection is a pre-requisite to P wave and QRS averaging. A novel algorithm for robust QRS detection in mice achieves a four-fold reduction in false detections compared to leading commercial software, while its human version boasts an error rate of just 0.29% on a public database containing ECGs with varying morphologies and degrees of noise. A fully automated P wave and QRS averaging and onset/offset detection algorithm is also proposed. This approach is shown to predict atrial fibrillation, a common cardiac arrhythmia which could cause stroke or heart failure, from normal asymptomatic ECGs, with 93% sensitivity and 100% specificity. Automated signal averaging also proves to be slightly more reproducible in consecutive recordings than manual signal averaging performed by expert users. Several studies postulated that high-frequency energy content in the signal-averaged QRS may be a marker of sudden cardiac death. Traditional frequency spectrum analysis techniques have failed to consistently validate this hypothesis. Layered Symbolic Decomposition (LSD), a novel algorithmic time-scale analysis approach requiring no basis function assumptions, is presented. LSD proves more reproducible than state-of-the-art algorithms, and capable of predicting sudden cardiac death in the general population from the surface ECG with 97% sensitivity and 96% specificity. A link between atrial refractory period and high-frequency energy content of the signal-averaged P wave is also considered, but neither LSD nor other algorithms find a meaningful correlation. LSD is not ECG-specific and may be effective in countless other signals with no known single basis function, such as other bio-potentials, geophysical signals, and socio-economic trends. / Thesis (Ph.D, Computing) -- Queen's University, 2013-09-30 23:54:21.137

Theory and computational studies of mechanochemical phenomena

Konda, Sai Sriharsha Manoj Varma 30 June 2014 (has links)
Mechanochemistry, or the modulation of chemical reactivity through the application of mechanical forces, has shown to facilitate a number of otherwise prohibitive chemical transformations. Computational approaches employing electronic structure calculations have explained a number of mechanochemically activated processes such as thermally inaccessible isomerizations and cycloreversions, symmetry-forbidden electrocyclic ring openings or activation of latent catalysts and, more recently, have been successfully used to design novel mechanosensitive systems. A significant limitation of such approaches, however, is their high computational cost, as finding force dependent transition states requires multiple saddle searches and consequently, multiple energy evaluations. To circumvent this problem, an approximation has been proposed, extending the well know "Bell formula", which estimates the force-dependent reaction barrier based on zero-force transition state properties. We demonstrate the numerical efficiency of this approximation termed as extended Bell theory (EBT) by comparing to existing theories and experiments. We also apply this method to suggest the unexplored, yet potentially useful possibility of suppressing chemical reactions through mechanical perturbation. Furthermore, in sharp contrast to simple, one-dimensional theories, our analysis reveals that the anti-Hammond effect is dominant in the mechanical activation of polyatomic molecules. Finally, we propose a numerical scheme to address the drawback of the EBT approximation, which is the failure to account for force-induced instabilities. Our approach provides a computationally efficient recipe to track the instabilities and follow the evolution of the reactant or transition states at any explicit force. We provide a classification of the different instability scenarios, and provide an illustrative example for each case. / text

Table look-up CORDIC: effective rotations through angle partitioning

Arbaugh, Jason, Todd 28 August 2008 (has links)
Not available / text

Adaptive CORDIC: using parallel angle recording to accelerate CORDIC rotations / Using parallel angle recording to accelerate CORDIC rotations

Rodrigues, Terence Keith, 1974- 29 August 2008 (has links)
This dissertation presents the Parallel Angle Recoding algorithm which is used to accelerate the calculation of CORDIC rotations. The CORDIC algorithm is used in the evaluation of a wide variety of elementary functions such as Sin, Cos, Tan, Log, Exp, etc. It is a simple and versatile algorithm, but its characteristic linear convergence causes it to suffer from long latency. It can be sped up by using the angle recoding algorithm which skips over certain intermediate CORDIC iterations to deliver the same precision while requiring 50% or fewer iterations. However because the selection of the angle constants is quite complex and must be performed off-line, its use has been limited to applications where the rotation angle is static and known a priori. This dissertation extends the low-latency advantage of the angle recoding method to dynamic situations too, where the incoming angle of rotation is allowed to take on any arbitrary value. The proposed method is called Parallel Angle Recoding and it makes use of a much simpler angle selection scheme to identify the angle constants needed by angle recoding. Because of its simplicity, it can be easily implemented in hardware without having to increase the cycle time. All the angle constants for angle recoding can be found in parallel in a single preliminary step by testing just the initial incoming rotation angle using range comparators -- there is no need to perform successive CORDIC iterations in order to identify them. With increasing precision, (N= 8, 16, 24, 32, etc.) the number of comparators which are needed by this scheme increases rapidly. The parallel angle recoding method can be re-formulated to apply to smaller groups of consecutive angle constants known as 'sections.' This limits the number of comparators that are needed, to a reasonable amount. There is an attendant savings in area and power consumption, but at the same time the evaluation of multiple sections introduces additional overhead cycles which reduces some of the gains made in latency by the Parallel Angle Recoding method. By interleaving multiple rotations and making use of a small buffer to store intermediate results, the number of overhead cycles can be reduced drastically. The Parallel Angle Recoding technique is modelled using Verilog, synthesised and mapped to a 65 nm. cell library. The latency and area characteristics that are obtained show that the method can improve the performance of the rotation mode in CORDIC, by delivering a reduced iteration count with no increase in the cycle time, and only a modest increase in power and area.

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