Results 61 to 70 of about 667,394 (343)

A safe reinforcement learning approach for autonomous navigation of mobile robots in dynamic environments

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract When deploying mobile robots in real‐world scenarios, such as airports, train stations, hospitals, and schools, collisions with pedestrians are intolerable and catastrophic. Motion safety becomes one of the most fundamental requirements for mobile robots.
Zhiqian Zhou, Junkai Ren, Zhiwen Zeng, Junhao Xiao, Xinglong Zhang, Xian Guo, Zongtan Zhou, Huimin Lu   +7 more
wiley   +1 more source

Leveraging Semi-Markov Models to Identify Anomalies of Activities of Daily Living in Smart Homes Processes

Algorithms
Stochastic Process Mining, in particular, Markov processes, is used to represent uncertainty and variability in Activities of Daily Living (ADLs). However, the Markov models inherently assume that the time spent in each state must follow an exponential ...
Eman Shaikh, Sally McClean, Zeeshan Tariq, Bryan Scotney, Nazeeruddin Mohammad   +4 more
doaj   +1 more source

Optimality criteria for the process of technical operation of locomotives [PDF]

MATEC Web of Conferences
The efficiency of a locomotive fleet as a complex system depends significantly on the mode and conditions of its operation, which, in many cases, are determined both by its own condition and by the state of the maintenance system.
Kapica Mihajlo, Bobyr Dmytro, Kyslyi Dmytro, Bohomolov Andrii, Desiak Andrii   +4 more
doaj   +1 more source

AI‐Assisted Digital Single‐Molecule Activity Tracker for Decoupling Intrinsic Heterogeneity from Photo‐Oxidative Damage in High‐Photon‐Flux Enzymology

Advanced Science, EarlyView.
Employing a digital single‐molecule activity tracker (dSMAT), this research demonstrates that high‐photon‐flux irradiation drives progressive oxidative scarring in polymerases. Unlike simple thermal denaturation, real‐time kinetic tracking dynamically visualizes enzymes degrading into multiple impaired subpopulations.
Anran Zheng, Qi Yang, Jinze Li, Fuqiang Ma, Xuefeng Wang, Zhen Guo, Chuanyu Li, Dongshu Li, Jia Yao, Zhiqi Zhang, Wei Zhang, Lianqun Zhou   +11 more
wiley   +1 more source

Optimised Internet of Thing framework based hybrid meta‐heuristic algorithms for E‐healthcare monitoring

IET Networks, EarlyView., 2022
Abstract Everything can be connected in the Internet of Things (IoTs) technology that enables efficient communication between connected objects. IoTs industry‐based meta‐heuristic and mining algorithms, which are considered an important field of Artificial Intelligence will be used to construct a healthcare application in this study for lowering costs,
Muhaned Al‐Hashimi, Shymaa Mohammed Jameel, Firas Husham Almukhtar, Musaddak Maher Abdul Zahra, Refed Adnan Jaleel   +4 more
wiley   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

On a single-server queue with fixed accumulation level, state dependent service, and semi-Markov modulated input flow

International Journal of Mathematics and Mathematical Sciences, 1992
The authors study the queueing process in a single-server queueing system with state dependent service and with the input modulated by a semi-Markov process embedded in the queueing process. It is also assumed that the server capacity is r≥1 and that any
Jewgeni H. Dshalalow, Gary Russell
doaj   +1 more source

Markov chain Monte Carlo methods for state-space models with point process observations [PDF]

, 2012
This letter considers how a number of modern Markov chain Monte Carlo (MCMC) methods can be applied for parameter estimation and inference in state-space models with point process observations.
Niranjan, Mahesan, Girolami, Mark, Yuan, Ke   +2 more
core   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

MODELING STRENGTH PROPERTIES OF PRODUCTS OF ADDITIVE TECHNOLOGIES USING PARALLEL COMPUTING

Современная наука и инновации, 2022
In the modern world, the importance of scientific results is growing, ensuring the creation of fundamentally new technologies and products with new consumer properties.
A. N. Privalov, Y. I. Bogatyryova
doaj   +1 more source