Apple's research explains how AI can identify bugs in code and generate QE tests

New papers on Apple's machine learning blog detail how AI can be used for faster, cheaper, and more effective QE testing, as ...

Building Reliable Data Systems Through Privacy, Automation, and Observability: The Research Journey of Chiranjeevi Devi

Chiranjeevi Devi's research focuses on building reliable data systems through anomaly detection, DevSecOps automation, and policy-as-code for compliance.

AI Expands the Search for New Battery Materials

When Microsoft researchers in 2023 identified a new kind of material that could dramatically reduce the amount of lithium ...
IEEE

Hybrid Deep Learning-Based Autoencoder-DNN Model for Intelligent Intrusion Detection System in IoT Networks

Abstract: The internet of things (IoT) has revolutionized contemporary life by seamlessly integrating devices and applications across various fields, including precision agriculture, digital ...
C&EN

Explainable Deep Learning Framework for SERS Bioquantification

Melville Laboratory for Polymer Synthesis, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Rd, Cambridge CB2 1EW, U.K. Melville Laboratory for Polymer Synthesis, Yusuf Hamied ...
ABC News

Mile-deep underwater volcano off West Coast could erupt soon, scientists say

More than 2,000 earthquakes were recorded in one day. An underwater volcano off the coast of Oregon is gearing up for an eruption, according to volcanologists who are monitoring for activity. The ...
Scientific Research Publishing

Traffic Speed Prediction Based on Autoencoder and Deep Learning ()

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...
GitHub

Enhancing EV Cost Prediction Using AutoEncoder-Based Feature Learning

Electric Vehicle (EV) cost prediction involves analyzing complex, high-dimensional data that often contains noise, multicollinearity, and irrelevant features. Traditional regression models struggle to ...
GitHub

Fault Detection in Turbofan Engines Using LSTM AutoEncoder and Fine-Tuned LLM

This project focuses on fault detection in turbofan engines using the NASA C-MAPSS (Commercial Modular Aero-Propulsion System Simulation) dataset, specifically the DS02 subset. The system combines ...