eess papers | Gist.Science

Short-Term Hourly Hydropower Prediction: Evaluating Long Short-Term Memory (LSTM) and Mixed-Integer Linear Programming (MILP)-Based Methods

This paper presents a novel autoregressive Long Short-Term Memory (LSTM) model for short-term hourly hydropower prediction on the Péribonka River, demonstrating its effectiveness in capturing discharge patterns while highlighting its potential and limitations compared to traditional Mixed-Integer Linear Programming (MILP) optimization methods.

Yoan Villeneuve, Sara Séguin, Abdellah Chehri, Kenjy Demeester2026-07-06

⚡ electrical engineering

User Evaluation of Telepresence Through a Virtual Environment Enhanced VR Framework with Real World Constraints

This study demonstrates that an immersive telepresence experience can be achieved using less-than-ideal, accessible hardware by integrating standard VR equipment with a robot to create a virtual environment that mimics real-world constraints, as validated by a user study categorizing the solution's effectiveness across five key areas.

Brendan Geary, Bradford Towle2026-07-06

⚡ electrical engineering

Shear Strength Enhancement and Optimum Dosage Prediction of Fly Ash–Stabilized Cohesive and Cohesionless Soils

This study demonstrates that incorporating 12% fly ash optimally enhances the shear strength of both cohesive and cohesionless soils through distinct mechanisms of densification and pozzolanic cementation, while a proposed quadratic regression model effectively predicts this optimum dosage for sustainable geotechnical applications.

MD. MOIN Akon, Khan MD Mohaiminul Islam Sho, Asif Alam Chowdhury, Swarnali Ahmed2026-07-06

⚡ electrical engineering

Improving Reanalysis Hub-Height Wind Speeds and Wind Shear Across Large Spatial Domains Using Near-Surface Observational Networks

This study presents a machine learning framework that leverages near-surface observational networks to simultaneously correct ERA5 hub-height wind speeds and predict wind shear exponents, significantly improving accuracy and temporal variability across large spatial domains without requiring direct hub-height measurements.

Freddy Houndekindo, Taha B.M.J. Ouarda2026-07-06

⚡ electrical engineering

A Systematic Review of Security Privacy and Provenance in EEG-Based Brain-Computer Interfaces with a Blockchain-Based Reference Architecture

This PRISMA 2020-compliant systematic review of 729 records identifies critical security and privacy gaps in EEG-based BCI systems, particularly the near-total absence of blockchain-based provenance, and proposes a "NeuroChain" reference architecture to address these vulnerabilities through hash-anchored data integrity, differential privacy, and patient-controlled consent.

Jonathas Tavares Neves, Carlos Augusto de Moraes Cruz2026-07-06

⚡ electrical engineering

A fully coupled transient wellbore–fracture model for analyzing fracture stability during tripping out deep gas reservoirs

This study presents a fully coupled transient wellbore–fracture model validated by field data that reveals tripping speed as the dominant factor driving pressure drops and fracture closure in deep gas reservoirs, thereby providing a quantitative framework for optimizing drilling protocols to mitigate lost circulation risks.

Shigui Zhao, Xiangwei Kong, Hengda Che, Sen Zhong2026-07-06

⚡ electrical engineering

Development of a Multi-robot System for Illuminance Measurement

This paper presents a fully automated multi-robot system that utilizes up to six robots and a graphical user interface to significantly improve the efficiency and speed of illuminance measurements in construction sites compared to traditional manual methods.

Yuki Hyodo, Yuki Nishiura, Kohei Matsumoto, Kazuyuki Sakemi, Junji Furuno, Yoshiaki Ikeda, Ryo Kurazume2026-07-06

⚡ electrical engineering

Improved Conditional Generative Network for Rapid Flow Field Prediction

This paper proposes an improved conditional Generative Adversarial Network (cGAN) that leverages high-fidelity CFD data to rapidly and accurately predict complex flow fields around unseen geometries, achieving a 79.14% accuracy improvement over baseline models while significantly reducing computational costs.

yan zhao, cheng xiaomei2026-07-06

⚡ electrical engineering

Natural visibility graph-based multiscale dispersion entropy for chatter identification in thin-walled parts finishing milling

This paper proposes an intelligent chatter identification method for thin-walled parts finishing milling that combines second-order generalized synchrosqueezing transform for signal reconstruction with natural visibility graph-based multiscale dispersion entropy for feature extraction, achieving high recognition accuracy through a crayfish optimization algorithm-optimized support vector machine.

ZeRui Bai, Junxue Ren, Weijun Tian, Yizhuo Wang2026-07-06

⚡ electrical engineering

Investigation into the material removal mechanism and surface integrity of Zr-based bulk metallic glass via rotary ultrasonic vibration grinding

This study demonstrates that rotary ultrasonic vibration-assisted grinding (RUVAG) significantly improves the surface integrity and reduces material removal defects of Zr-based bulk metallic glasses compared to conventional grinding by introducing intermittent contact that mitigates stress concentration and lowers surface roughness by approximately 21%.

Guijiu Xie, Yunfeng Liao, Xufeng Tang, Junsheng Gao, Xinyi Li, Wenqing Ding, Yan Wang, Zhongpeng Zheng2026-07-06

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