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Unveiling the Weighted Set Cover Problem - Optimizing Resource Allocation

Introduction Problem Explanation Problem Definition Weighted Set Cover Solution Greedy Algorithm Implementation in SageMath Example Scenario Applications in Blockchain Technology and Machine Learning Blockchain Transaction Fee Optimization Machine Learning Feature Selection Relating to Karp Reduction Conc...

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Mastering Elliptic Curve Arithmetic - A Comprehensive Guide with SageMath Examples

Introduction Demystifying Elliptic Curves and Their Applications The Power of Elliptic Curve Cryptography (ECC) Unlocking the Potential of ECC with SageMath Understanding the Fundamentals of Elliptic Curves Definition of an Elliptic Curve Points on an Elliptic Curve Visualizing Points on an Ellip...

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Enhancing Ethereum Scalability with Product Codes and Danksharding - A Comprehensive Guide

This article would provide an in-depth understanding of how product codes from algebraic coding theory can be applied to Danksharding to improve Ethereum’s scalability. It would cover the fundamentals of product codes, their application in Danksharding, and the potential benefits for Ethereum’s network. Product Codes and Their Relation to Da...

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Efficient Computation of Frobenius Automorphism on BN254 Elliptic Curve

In this blog post, we will explore an efficient method to compute the Frobenius automorphism for the BN254 elliptic curve. The BN254 curve is a pairing-friendly elliptic curve that is widely used in cryptographic applications hackmd.io/@jpw. We will exploit the fact that $(p−1)/2$ is odd to compute the Frobenius automorphism efficiently. What i...

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Writing Zero Knowledge Proofs and Circuits in Four Different Languages - Dotproduct of Two Vectors

Overview We will implement dot product of two vectors of size N using Zero Knowledge Proofs (ZKP) in Circom, Halo2, . According to k12.libretexts.org, the dot product of two vectors A and B of size N is given by: A.B = a1*b1 + a2*b2 + ... + aN*bN Overview Process Flow of a Zero Knowledge Proof Circom Circuit for Dotproduct of Two Vect...

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Paper Review - Predicting the development of adverse cardiac events in patients with hypertrophic cardiomyopathy using machine learning

Overview The paper aimed to improve the prediction of adverse cardiac events in patients with hypertrophic cardiomyopathy (HCM) using machine learning methods. The study found that machine learning models demonstrated a superior ability to predict adverse cardiac events compared to conventional risk stratification. The authors suggest that thes...

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Paper Review - Machine learning of native T1 mapping radiomics for classification of hypertrophic cardiomyopathy phenotypes

Overview The paper presents a machine learning approach for classification of hypertrophic cardiomyopathy phenotypes using native T1 mapping radiomics. Citation of the Paper Antonopoulos, A.S., Boutsikou, M., Simantiris, S. et al. Machine learning of native T1 mapping radiomics for classification of hypertrophic cardiomyopathy phenotypes. Sci...

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