Supervised machine learning improves predictions of compressive strength in industrial waste-modified concrete, supporting ...

Abstract: Smart grid (SG) engages bidirectional energy and data flow with advanced metering infrastructure (AMI) and lures attackers to exploit vulnerabilities in the critical infrastructure. Of the ...

The deep learning revolution has a curious blind spot: the spreadsheet. While Large Language Models (LLMs) have mastered the nuances of human prose and image generators have conquered the digital ...

Reviews of notable new fiction, nonfiction, and poetry.

Python and Jupyter offer a simple, powerful setup for beginner-friendly data science learning. Real-world datasets make each project practical and industry-relevant. Skills gained cover analysis, ...

The Random Survival Forest package provides a python implementation of the survival prediction method originally published by Ishwaran et al. (2008). Reference ...

For the C++ library itself, you need no additional libaries, only a C++11 capable compiler. Technically, you need Boost if you want to compile the unit tests. The development is done using GCC 7.2.

With the accelerating pace of urbanization, the issue of air pollution has become increasingly severe. Notably, carbon monoxide (CO), as a prevalent harmful gas, poses potential threats to both human ...

The operation of the power grid is closely related to meteorological disasters. Changes in meteorological conditions may have an impact on the operation and stability of the power system, leading to ...

Effective pavement maintenance and rehabilitation decisions rely on both pavement functional and structural condition data. Traditionally, state transportation agencies prioritize pavement segments ...