Results 51 to 60 of about 7,217 (228)

Adaptive Autonomy in Microrobot Motion Control via Deep Reinforcement Learning and Path Planning Synergy

Advanced Intelligent Systems, EarlyView.
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi, Bairong Zhu, Haoyu Liu, Tingting Yu   +3 more
wiley   +1 more source

Structured Inference for Recurrent Hidden Semi-markov Model [PDF]

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
Segmentation and labeling for high dimensional time series is an important yet challenging task in a number of applications, such as behavior understanding and medical diagnosis. Recent advances to model the nonlinear dynamics in such time series data, has suggested to involve recurrent neural networks into  Hidden Markov Models.
Hao Liu, Lirong He, Haoli Bai, Bo Dai, Kun Bai, Zenglin Xu   +5 more
openaire   +1 more source

Regional Shopping Objectives in British Grocery Retail Transactions Using Segmented Topic Models

Applied Stochastic Models in Business and Industry, EarlyView.
ABSTRACT Understanding the customer behaviours behind transactional data has high commercial value in the grocery retail industry. Customers generate millions of transactions every day, choosing and buying products to satisfy specific shopping needs.
Mariflor Vega Carrasco, Mirco Musolesi, Jason O'Sullivan, Rosie Prior, Ioanna Manolopoulou   +4 more
wiley   +1 more source

A Comparison of Realized Measures of Integrated Volatility: Price Duration‐ vs. Return‐Based Approaches

Journal of Forecasting, EarlyView.
ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann, Mawuli Segnon, Timo Wiedemann   +2 more
wiley   +1 more source

Lower Limb Locomotion Activity Recognition of Healthy Individuals Using Semi-Markov Model and Single Wearable Inertial Sensor

Sensors, 2019
Lower limb locomotion activity is of great interest in the field of human activity recognition. In this work, a triplet semi-Markov model-based method is proposed to recognize the locomotion activities of healthy individuals when lower limbs move ...
Haoyu Li, Stéphane Derrode, Wojciech Pieczynski   +2 more
doaj   +1 more source

Ophidiomycosis Prevalence and Disease Ecology in a Natrix tessellata (Laurenti, 1768) Population From Northern Italy

Journal of Experimental Zoology Part A: Ecological and Integrative Physiology, EarlyView.
ABSTRACT Fungal pathogens pose a growing threat to vertebrate biodiversity. In snakes, Ophidiomyces ophidiicola (Oo) has garnered particular concern, although its impact in Europe remains poorly understood. We conducted a season‐long, standardized survey of dice snakes (Natrix tessellata) along the northern shore of Lake Como (Italy) to quantify Oo and
Matteo Riccardo Di Nicola, Luca Colla, Kevin P Mulder, Federico Storniolo, Elin Verbrugghe, Giuseppe Esposito, Donato A. Grasso, Frank Pasmans, An Martel   +8 more
wiley   +1 more source

Temporal Convolutional Network Connected with an Anti-Arrhythmia Hidden Semi-Markov Model for Heart Sound Segmentation

Applied Sciences, 2020
Heart sound segmentation (HSS) is a critical step in heart sound processing, where it improves the interpretability of heart sound disease classification algorithms.
Yibo Yin, Kainan Ma, Ming Liu
doaj   +1 more source

Extending the hyper‐logistic model to the random setting: New theoretical results with real‐world applications

Mathematical Methods in the Applied Sciences, EarlyView.
We develop a full randomization of the classical hyper‐logistic growth model by obtaining closed‐form expressions for relevant quantities of interest, such as the first probability density function of its solution, the time until a given fixed population is reached, and the population at the inflection point.
Juan Carlos Cortés, Ana Navarro‐Quiles, Sorina Madalina Sferle   +2 more
wiley   +1 more source

Sequential Bayesian Learning for Hidden Semi-Markov Models

, 2023
In this paper, we explore the class of the Hidden Semi-Markov Model (HSMM), a flexible extension of the popular Hidden Markov Model (HMM) that allows the underlying stochastic process to be a semi-Markov chain. HSMMs are typically used less frequently than their basic HMM counterpart due to the increased computational challenges when evaluating the ...
Aschermayr, Patrick, Kalogeropoulos, Konstantinos   +1 more
openaire   +2 more sources

GraphReco: Probabilistic Structure Recognition for Chemical Molecules

ChemistryOpen, EarlyView.
Molecule structure images are unfriendly for machine understanding, blocking productivity improvements in chemical data mining, drug discovery, and many other fields. We present a rule‐based probabilistic Optical Chemical Structure Recognition model to explain and tackle the ambiguity challenges in graph assembly.
Haidong Wang, Yuncheng Yu, Jyh‐Charn Liu   +2 more
wiley   +1 more source