Scientific Research Publishing

Predicting Stock Price Movements Using Deep Learning Techniques ()

Stock Price Prediction, Deep Learning, LSTM, GRU, Attention Mechanism, Financial Time Series Share and Cite: Kirui, D. (2026) ...
IEEE

Temporal-Spatial Feature Extraction in IoT-Based SCADA System Security: Hybrid CNN-LSTM and Attention-Based Architectures for Malware Classification and Attack Detection

Abstract: This research presents a Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) model developed for malware classification from IoT devices in the SCADA system and for ...
IEEE

Spatiotemporal Feature Extraction from Integrated Multivariate Time Series via MCNN-LSTM for Wind Turbine Fault Diagnosis

Abstract: Wind turbine (WT) fault diagnosis faces challenges from imbalanced SCADA data, which degrades detection accuracy for minority classes. To address this issue, a fault diagnosis method based ...
The New York Times

More Than Half of Teens Use Chatbots for Schoolwork, Survey Finds

A new study from the Pew Research Center finds teenagers think chatbot-assisted cheating has become “a regular feature of student life.” A new study from the Pew Research Center finds teenagers think ...
Frontiers

HairSentinel: a time-aware anomaly detection framework for forecasting hairfall trends using temporal fusion transformers

Hairfall is a primary concern for many individuals worldwide today. Hair strands may fall due to various conditions such as hereditary factors, scalp health issues, nutritional deficiencies, hormonal ...