Results 31 to 40 of about 536,285 (268)

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

A Short term Electricity Load Forecasting for Community Residents Based on Federated Learning and Considering Privacy Protection

EAI Endorsed Transactions on Energy Web
INTRODUCTION: As the penetration rate of renewable energy increases and patterns of energy demand evolve, fluctuations on both the supply and demand sides of electricity are becoming more pronounced.
Bo Peng, Jing Zuo, Xianfu Gong, Yaodong Li, Weijie Wu, Yixin Li   +5 more
doaj   +1 more source

Incremental power grid verification [PDF]

Proceedings of the 49th Annual Design Automation Conference, 2012
Verification of the on-die power grid is a key step in the design of complex high-performance integrated circuits. For the very large grids in modern designs, incremental verification is highly desirable, because it allows one to skip the verification of a certain section of the grid (internal nodes) and instead, verify only the rest of the grid ...
Abhishek, Farid N. Najm
openaire   +2 more sources

Data‐Driven SuStaIn Model of Disability Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To determine whether ordinal Subtype and Stage Inference (SuStaIn) applied to routine ALSFRS‐R item scores can identify reproducible disability progression patterns in amyotrophic lateral sclerosis (ALS) and provide clinically meaningful staging.
Giammarco Milella, Veria Vacchiano, Vittorio Velucci, Stefano Zoccolella, Rocco Liguori, Giovanni Defazio   +5 more
wiley   +1 more source

Federated asynchronous graph attention network with structural semantic embedding for multi-label graph classification

Scientific Reports
Federated Learning (FL) provides a privacy-preserving framework for training graph neural networks (GNNs) in privacy-sensitive scenarios. However, traditional FL-GNN approaches often focus on addressing data distribution inconsistencies across clients ...
Xinwu Ji, Yijing Zhang, Kaihong Zheng, Hao Yang, Yuan Ai, Jingxu Yang   +5 more
doaj   +1 more source

Design of Multi-Source Heterogeneous Data Fusion Algorithm for Distribution Networks Based on Improved Kalman Filter

IEEE Access
The complexity of multi-source heterogeneous data in distribution network is high and Significant deviations in multi-source heterogeneous data increase the complexity of fusion multi-source heterogeneous data in distribution network.
Min Li, Jing Tan, Juncheng Zhang, Xiaohong Tan, Tianlu Luo   +4 more
doaj   +1 more source

A Preventive Strategy of Voltage Stability based on Characteristic Analysis [PDF]

E3S Web of Conferences, 2019
The purpose of voltage stability prevention and control strategy is to minimize the impact of expected accidents on the whole power grid while ensuring safe power supply.
Hu Zhen, Wang Ding, Shen Yangwu, Chen Daojun, Liu Yongyan   +4 more
doaj   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga   +2 more
wiley   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Research on the linkage technology of electric power operation field video and Beidou high-precision positioning terminal [PDF]

E3S Web of Conferences
In order to adapt to the trend of intelligent development in power operation sites and solve practical problems such as inadequate supervision of traditional power operation sites, this article mainly studies the linkage technology between power ...
Liu Ying, Huang Jeihui, Yan Chengbo, Wei Yihao, Miao Hao, Lian Weibing, Zheng Linsheng   +6 more
doaj   +1 more source