Results 51 to 60 of about 15,984 (207)

An Improved Dynamic Time Warping Algorithm for Active Sonar Signal Matching

Archives of Acoustics
Active sonar signal matching is a critical technique for measuring inter-signal similarity and enhancing target detection and classification performance.
Tong-jing Sun, Hun-yuan Wang, Lei Chen, Hao-ran Xu   +3 more
doaj   +1 more source

A Multimodal Intelligent System for Human Digital Twin Simulation with Continuous Kinematic Data Tracking, Biometric Prognosis, and Cognitive State Feedback in Industrial Environments

Advanced Intelligent Discovery, EarlyView.
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury, Sebastian Gratz‐Kelly, Eric Wagner, Paul Motzki, Martina Lehser   +4 more
wiley   +1 more source

Dynamic Time Warping (DTW) as a Means of Assessing Solar Wind Time Series

, 2023
Over the last decades, international attempts have been made to develop realistic space weather prediction tools aiming to forecast the conditions on the Sun and in the interplanetary environment. These efforts have led to the development of appropriate metrics to assess the performance of those tools.
openaire   +1 more source

Decoding Emotional Signatures of Ethical Ads: An Analysis of Actor‐Viewer Synchrony

Journal of Consumer Behaviour, EarlyView.
ABSTRACT We examine whether ethical advertisements differ from conventional ads in their on‐screen emotional signatures and whether those signatures transfer to actor‐viewer synchrony. Study 1 analyses 138 professionally produced YouTube ads using Automated Facial Expression Recognition (AFER) and Convolutional Neural Networks (CNN) to quantify actor ...
Vik Naidoo, Nicolas Hamelin
wiley   +1 more source

Topology prediction for opportunistic network based on spatiotemporal convolution

Tongxin xuebao, 2023
The high dynamics of opportunistic network topology leads to the challenges of topology prediction.The existing research mainly focuses on the long-term spatiotemporal dependence of networks, ignoring the short-term spatiotemporal features.A topology ...
Jian SHU, Jiawei SHI, Linlan LIU, Al-Kali Manar   +3 more
doaj   +2 more sources

Enhancing Nearest Neighbor Classification Performance through Dynamic Time Warping with Progressive Constraint

Proceedings of the International Florida Artificial Intelligence Research Society Conference
Dynamic time warping (DTW) is a widely used metric for comparing time series data, offering elasticity in alignment. While the original DTW allows infinite elasticity without penalty, the wDTW imposes a constant penalty regardless of elastic length.
Sung-Hyuk Cha, Teryn Cha, Teja Vuppu
doaj   +1 more source

Stagewise crop yield prediction with multisource functional indices

Canadian Journal of Statistics, EarlyView.
Abstract Index insurance design involves integrating weather data, soil moisture, phenology information, and satellite imagery, which presents challenges in data fusion. This article addresses the modelling of multisource functional indices of varying lengths by constructing a stagewise ensemble of sequential models.
Jing Zou, Ostap Okhrin
wiley   +1 more source

A Data‐Driven Multidimensional Profiling Framework for Residential Electricity Users With Application to Load Forecasting

Energy Internet, EarlyView.
ABSTRACT With the advancement of smart grid and Internet of Things, alongside broad adoption of distributed energy resources, precise profiling of residential users has become vital to grid operational efficiency and load forecasting accuracy. However, existing profiling approaches mainly rely on single‐source load data and fail to capture the dynamic ...
Danlin Li, Yuchen Zhang, Rui Zhang, Ming Yang, Yu Li, Chuanqi Wang, Yateendra Mishra   +6 more
wiley   +1 more source

DTW-C++: Fast dynamic time warping and clustering of time series data

Journal of Open Source Software
Time-series data analysis is of interest in a huge number of different applications, from finding patterns of energy consumption to detecting brain activity or discovering stock price trends. Unsupervised learning methods can help analysts unlock patterns in data, and a key example of this is clustering.
Kumtepeli, V, Perriment, R, Howey, DA
openaire   +2 more sources

L‐VISP: LSTM Visualization for Interpretable Symptom Prediction in Patient Cohorts

Computer Graphics Forum, EarlyView.
L‐VISP is a human‐machine solution that uses visual analytics for LSTM modelling in clinical research. L‐VISP uses custom visual encodings to make multiple LSTM variants interpretable, supporting a full range of analysis, from understanding model operations and evaluating performance to interpreting results in a clinical context.
C. Floricel, Y. Wang, A. Wentzel, C. D. Fuller, G. E. Marai, M. E. Papka, G. Canahuate   +6 more
wiley   +1 more source