Results 61 to 70 of about 8,467,026 (293)

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Trigonometric words ranking model for spam message classification

IET Networks, EarlyView., 2022
Abstract The significant increase in the volume of fake (spam) messages has led to an urgent need to develop and implement a robust anti‐spam method. Several of the current anti‐spam systems depend mainly on the word order of the message in determining the spam message, which results in the system's inability to predict the correct type of message when
Suha Mohammed Hadi, Ali Hakem Alsaeedi, Dhiah Al‐Shammary, Zaid Abdi Alkareem Alyasseri, Mazin Abed Mohammed, Karrar Hameed Abdulkareem, Riyadh Rahef Nuiaa, Mustafa Musa Jaber   +7 more
wiley   +1 more source

Hidden Semi Markov Models for Multiple Observation Sequences: The mhsmm Package for R

Journal of Statistical Software, 2011
This paper describes the R package mhsmm which implements estimation and prediction methods for hidden Markov and semi-Markov models for multiple observation sequences. Such techniques are of interest when observed data is thought to be dependent on some
Jared O'Connell, Søren Højsgaard
doaj  

Dynamic Bayesian Networks for Audio-Visual Speech Recognition

EURASIP Journal on Advances in Signal Processing, 2002
The use of visual features in audio-visual speech recognition (AVSR) is justified by both the speech generation mechanism, which is essentially bimodal in audio and visual representation, and by the need for features that are invariant to acoustic noise
Liang Luhong, Pi Xiaobo, Liu Xiaoxing, Murphy Kevin, Nefian Ara V   +4 more
doaj   +1 more source

Multiple-regression hidden Markov model [PDF]

2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002
Proposes a class of hidden Markov model (HMM) called multiple-regression HMM (MR-HMM) that utilizes auxiliary features such as fundamental frequency (F/sub 0/) and speaking styles that affect spectral parameters to better model the acoustic features of phonemes.
Fujinaga, Katsuhisa, Nakai, Mitsuru, Shimodaira, Hiroshi, Sagayama, Shigeki   +3 more
openaire   +2 more sources

Large Language Model‐Based Chatbots in Higher Education

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci, Merve Eryilmaz, Ail K. Yetisen, Savas Tasoglu, Aydogan Ozcan   +4 more
wiley   +1 more source

Features requirement elicitation process for designing a chatbot application

IET Networks, EarlyView., 2022
This article seeks to assist the chatbot community by outlining the characteristics that a chatbot needs to possess and explaining how to create a chatbot for a bank. In order to determine which capabilities are most crucial to ending users, a study of a small sample of chatbot users was conducted.
Nurul Muizzah Johari, Puteri N. E. Nohuddin, Ahmad Hanif Ahmad Baharin, Noor Azuddin Yakob, Mohammad Javad Ebadi   +4 more
wiley   +1 more source

Accommodating availability bias on line transect surveys using hidden Markov models. [PDF]

, 2009
Previously in the University eprints HAIRST pilot service at http://eprints.st-andrews.ac.uk/archive/00000458/Maximum likelihood methods are developed which accommodate intermittent animal availability of animals on line transect surveys.
Samara, Filipa I. P., Borchers, David L.
core   +2 more sources

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

Sequential Bayesian inference for implicit hidden Markov models and current limitations

ESAIM: Proceedings and Surveys, 2015
Hidden Markov models can describe time series arising in various fields of science, by treating the data as noisy measurements of an arbitrarily complex Markov process.
Jacob Pierre E.
doaj   +1 more source