A new quantum-inspired algorithm has cracked a problem so massive that conventional supercomputers struggle to even approach it. Researchers used the method to simulate extraordinarily complex quantum ...

Abstract: The sparsity-regularized linear inverse problem has been widely used in many fields, such as remote sensing imaging, image processing and analysis, seismic deconvolution, compressed sensing, ...

Apple's HomePod and HomePod mini are incredible additions to your smart home. Here's how I've made use of Apple's smart speaker after abandoning Sonos and other speakers. We're approaching two months ...

Imaging is a critical technique in biology—from identifying cancerous cells in biopsies to observing how immune cells like macrophages hunt down and destroy pathogens. Traditionally, distinguishing ...

This project aims to detect and classify 16x16 pixel drawings into 10 categories (Sun, Moon, Tree, etc.) using linear and probabilistic models. The main focus was not just to use high-level libraries, ...

Among high school students and adults, girls and women are much more likely to use traditional, step-by-step algorithms to solve basic math problems – such as lining up numbers to add, starting with ...

To address the issues of strong subjectivity and difficulty in feature extraction that are inherent to traditional frequency response analysis methods used for diagnosing transformer winding ...

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...

Children as young as 4 years old are capable of finding efficient solutions to complex problems, such as independently inventing sorting algorithms developed by computer scientists. The scientists ...

Abstract: In this paper, a new Multilayer-Linear Forest Discriminant (M-LFD) algorithm is proposed to optimize the classification of mental health data based on multi-level perceptron (MLP). The ...