Results 31 to 40 of about 15,837 (289)

Finite-Time Asynchronous Fault Detection Filter Design for Conic-Type Nonlinear Semi-Markovian Jump Systems

IEEE Access, 2021
In this work, the problem of finite-time asynchronous fault detection filter design is investigated for conic-type nonlinear semi-Markovian jump systems with time delay, missing measurements and randomly jumping fault signal.
V. Nithya, V. T. Suveetha, R. Sakthivel, Yong-Ki Ma   +3 more
doaj   +1 more source

Identifying Cytokine Motif‐Containing, Immunomodulatory Bacterial Proteins in Human Gut Microbiome

Advanced Science, EarlyView.
By building and constructing HMM (Upper left, blue), the authors identify CMCPs in bacteria genomes and CRC related metagenomes and enriched CRC‐related CMCPs (Upper right, blue). They analyze sequence and structural similarity of hits (Lower left, green), test function with engineered EcN delivered to tumors in a mouse tumor model (Lower right, pink ...
Ziyu Wang, Siqi Guo, Jing Li, Qianqian Huang, Jing Ning, Binbin Xia, Xun Lv, Xiang Liu, Zeyu Gao, Jine Li, Longchao Liu, Moshi Song, Jun Wang   +12 more
wiley   +1 more source

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

Integrative Analyses Identify a cGAS‐STING Pathway‐Driven Signature With Context‐Dependent Roles in Systemic Lupus Erythematosus

Advanced Science, EarlyView.
Zhang et al. identify M7core, a critical cGAS‐STING pathway‐driven gene signature that is activated in most lupus patients’ blood and links to lupus disease severity, lymphopenia, and lupus nephritis. They further reveal the diagnostic and pathogenic characteristics of M7core and emphasize the importance of assessing pathway activity before initiating ...
Lele Zhang, Ming‐Ju Amy Lyu, Ze Hong, Jing Sun, Lan Guo, Jiameng Hu, Munire Maimaiti, Chenhui Li, Jinyi Song, Xiang Zhang, Huansha Yu, Chen Wang, Xuan Wang, Haiyang Hu   +13 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

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
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

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