Morning Overview on MSN

Scientists discover a new meteor shower raining down from a crumbling asteroid no one knew about

Somewhere in the inner solar system, an asteroid nobody has ever seen through a telescope is falling apart, scattering a ...
Assembly Magazine

Machine Learning Detects Fastening Errors

Ford engineers are studying whether AI can play a role in detecting faulty run-downs. To do that, they first had to determine ...
Frontiers

A graph clustering algorithm with hypergraph learning and a core-attachment strategy for protein complex identification

Protein complexes play a crucial role in cellular biological processes. Identifying these complexes is essential for understanding cellular functions and biological mechanisms. Graph clustering ...
Johns Hopkins Newsletter

Sohini Ramachandran discusses population genetics and computational clustering algorithms

Family has always been important to those working in population genetics. When Sohini Ramachandran was a postdoc, the issue of relatives in a dataset causing inaccurate results was considered a major ...
Scientific Research Publishing

On Prediction of Stock Return and Volatility Using Clustering Techniques: Taking an Example of Japanese Stock Market ()

Stock returns exhibit nonlinear dynamics and volatility clustering. It is well known that we cannot forecast the movements of stock prices under the condition that market is efficient. In most ...
financefeeds

Good and Bad Crypto Algorithms Explained Simply

Cryptography secures communication in banking, messaging, and blockchain. Good algorithms (AES, RSA, ECC, SHA-2/3, ChaCha20) are secure, efficient, and widely trusted. Bad algorithms (DES, MD5, SHA-1, ...
IEEE

Level Test-Inspired SNR Estimation-Based Dataset Clustering Algorithms for Learnability Maximization in Neural Network Design

Abstract: Neural networks (NNs) are pivotal in enhancing data processing tasks such as classification, generation, and restoration. A crucial consideration in these applications is the signal-to-noise ...
SciELO

Structural damage detection utilizing probabilistic divergence of FFT coefficient ratios and DBSCAN cluster algorithm

In structural health monitoring (SHM), uncertainties from environmental noise and modeling errors affect damage detection accuracy. This paper introduces a new concept: the Fast Fourier Transform ...
GitHub

[ENH] Adding KModes and KPrototypes clustering algorithms

The workflow I want to enable is a seamless and native experience for clustering categorical and mixed data: This integrates categorical clustering directly into the robust and familiar scikit-learn ...