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Prajval Koul

Publications and source records attributed to Prajval Koul.

3 recordsLinked to original sources

On the Constructive Dimension Spectrum of Polynomials

Recently, Stull [18], [17] resolved a long-standing open problem posed by Lutz, on whether the set of effective Hausdorff dimensions of points on a straight line in $\mathbb{R}^2$ -- the effective dimension spectrum of the line -- contains a unit interval. This question is related to problems in classical fractal geometry like the Kakeya conjecture and Furstenberg sets. Stull posed an open question on the dimension spectra of polynomial curves. For the first result, with new techniques which adapt the theory of classical real root-finding of polynomials to the current setting, we show that the dimension spectra of every polynomial curve contains at least two points. This answers an open question posed by Stull [18], [17]. We use the main result to construct a class of polynomials which have width strictly greater than 1, answering a second problem stated in [18],[17]. Stull [18] resolved the dimension spectrum conjecture for planar lines, showing that it contains a unit interval. For the second result, we resolve the conjecture for a subfamily of polynomials whose coefficients form a "low" dimension point in $\mathbb{R}^{d+1}$.

math.GM

On Effective Banach-Mazur Games and an application to the Poincar\'e Recurrence Theorem for Category

The classical Banach-Mazur game characterizes sets of first category in a topological space. In this work, we show that an effectivized version of the game yields a characterization of sets of effective first category. Using this, we give a proof for the effective Banach Category Theorem. Further, we provide a game-theoretic proof of an effective theorem in dynamical systems, namely the category version of Poincar\'e Recurrence. The Poincar\'e Recurrence Theorem for category states that for a homeomorphism without open wandering sets, the set of non recurrent points forms a first category (meager) set. As an application of the effectivization of the Banach-Mazur game, we show that such a result holds true in effective settings as well.

math.LO

Spectral GUI for Automated Tissue and Lesion Segmentation of T1 Weighted Breast MR Images

We present Spectral GUI, a multiplatform breast MR image analysis tool designed to facilitate the segmentation of fibro glandular tissues and lesions in T1 weighted breast MR images via a graphical user interface (GUI). Spectral GUIR uses spectrum loft method [1] for breast MR image segmentation. Not only is it interactive, but robust and expeditious at the same time. Being devoid of any machine learning algorithm, it shows exceptionally high execution speed with minimal overheads. The accuracy of the results has been simultaneously measured using performance metrics and expert entailment. The validity and applicability of the tool are discussed in the paper along with a crisp contrast with traditional machine learning principles, establishing the unequivocal foundation of it as a competent tool in the field of image analysis.

eess.IV