The Inverse Iteration Method for Julia Sets in the 3-Dimensional Space

In this article, we introduce the adapted inverse iteration method to generate bicomplex Julia sets associated to the polynomial map $w^2+c$. The result is based on a full characterization of bicomplex Julia sets as the boundary of a particular bicomplex cartesian set and the study of the fixed points of $w^2+c$. The inverse iteration method is used in particular to generate and display in the usual 3-dimensional space bicomplex Julia sets that are dendrites.Comment: 16 pages, 4 figure

Cosmic Purpose and the Question of a Personal God

Purported evidence for purposeful divine action in the cosmos may appear to warrant describing God as personal, as Swinburne proposes. In this paper, however, I argue that the primary understanding of what is meant by a person is formed by the experience of ”I’ -- ”you’ or second-person relatedness, a mode of relation with God that is not part of natural theology. moreover, even among human beings, the recognition of purposeful agency does not invariably lead to the attribution of personhood in the usual sense. ”Person’ is therefore a misleading term to use of God on the evidence of cosmic purpose alone in the absence of suitable revelation

Image Encryption using Gingerbreadman Map And RC4A Stream Cipher

Day to day increasing flow of sensitive or confidential information, such as images, audio, video, etc., over unsecured medium (like Internet) has motivated more concentration for concrete crypto algorithms. In this paper, an image encryption algorithm based on a permutation and substitution cipher has been proposed. In permutation stage, image pixels are shuffled using gingerbreadman map while in substitution stage, pixels are bit-wise XOR-ed with the keystream generated using RC4A (Rivest Cipher 4A) stream cipher algorithm. For the proposed scheme, statistical analyses, like histogram, adjacent pixels correlation coefficient, and information entropy are given. Security analyses, like key sensitivity, occlusion analysis are also given in this paper. The occlusion analysis shows that the proposed method is resistant to the occlusion attack. These statistical and security analyses support the concreteness of the proposed method

Fractal Electromagnetic Showers

We study the self-similar structure of electromagnetic showers and introduce the notion of the fractal dimension of a shower. Studies underway of showers in various materials and at various energies are presented, and the range over which the fractal scaling behaviour is observed is discussed. Applications to fast shower simulations and identification, particularly in the context of extensive air showers, are also discussed.Comment: Talk to be presented at the XI International Symposium on Very High Energy Cosmic Ray Interaction

An Algorithm for Generating New Mandelbrot and Julia Sets

The present paper is motivated from the paper of John R. Tippetts (Tippetts 1992) in which he gave an algorithm to generate an interesting Mandelbrot set. We not only generate Julia sets using Tippetts algorithm (Tippetts 1992), but also generate some new Julia and Mandelbrot sets by slightly modifying the Tippetts algorithm. This approach yields a new class of algorithms to produce new and alluring fractals with virtually infinite complexity. Keywords: Mandelbrot set, Julia set, recursion formula, algorith

Automated Segmentation of Pulmonary Lobes using Coordination-Guided Deep Neural Networks

The identification of pulmonary lobes is of great importance in disease diagnosis and treatment. A few lung diseases have regional disorders at lobar level. Thus, an accurate segmentation of pulmonary lobes is necessary. In this work, we propose an automated segmentation of pulmonary lobes using coordination-guided deep neural networks from chest CT images. We first employ an automated lung segmentation to extract the lung area from CT image, then exploit volumetric convolutional neural network (V-net) for segmenting the pulmonary lobes. To reduce the misclassification of different lobes, we therefore adopt coordination-guided convolutional layers (CoordConvs) that generate additional feature maps of the positional information of pulmonary lobes. The proposed model is trained and evaluated on a few publicly available datasets and has achieved the state-of-the-art accuracy with a mean Dice coefficient index of 0.947 $\pm$ 0.044.Comment: ISBI 2019 (Oral