Results 291 to 300 of about 1,249,401 (374)

Transducer Materials Mediated Deep Brain Stimulation in Neurological Disorders

Advanced Functional Materials, EarlyView.
This review discusses advanced transducer materials for improving deep brain stimulation (DBS) in neurological disorders. These materials respond to light, ultrasound, or magnetic fields, enabling precise, less invasive neuromodulation. Their stimulus‐responsive properties enhance neural control and adaptive therapy, paving the way for next‐generation ...
Di Zhao, Zhengyang Cao, Guangjun Zhong, Limin Shi, Junxia Xie, Jianhua Hao   +5 more
wiley   +1 more source

Solving multi-scenario hybrid flow shop scheduling problem based on an improved probe machine model. [PDF]

PLoS One
Tian X, Kong Y, Liu X.
europepmc   +1 more source

Fluorinated Interphase Enabled by Lithium Salt‐Driven Electrical Double‐Layer Modulation for Advanced Zinc Metal Batteries

Advanced Functional Materials, EarlyView.
This study introduces a highly soluble, reduction‐active lithium salt into conventional zinc battery electrolytes, enhancing the solvation structure and electric double layer. These modifications significantly improve the reversibility of the zinc anode and mitigate cathode material dissolution, presenting a novel approach to enhancing the performance ...
Ziwei Zhao, Pengcheng Li, Yuxuan Wu, Ziwei Chai, Hao Zhang, Ge Li   +5 more
wiley   +1 more source

Impact of social rewarding in dynamic shop floor environments. [PDF]

Sci Rep
Sait U, Frego M, De Angeli A, Peer A.
europepmc   +1 more source

A novel dynamic scheduling model for application in multimode approach. [PDF]

Sci Rep
Elqabli Z, Kamach O, Khatab A, Chater Y.
europepmc   +1 more source

Constructive-destructive neighbor search drives artificial bee colony algorithm for variable speed green hybrid flowshop scheduling problem. [PDF]

Sci Rep
Hu D, Wu Y, Qiu L, Mi J, Yang Y.
europepmc   +1 more source

A hybrid evolution strategies algorithm for non-permutation flow shop scheduling problems. [PDF]

Sci Rep
Khurshid B, Maqsood S, Habib MS, Omair M, Hwang SJ.   +4 more
europepmc   +1 more source

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Deep reinforcement learning for dynamic scheduling of a flexible job shop

International Journal of Production Research, 2022
The ability to handle unpredictable dynamic events is becoming more important in pursuing agile and flexible production scheduling. At the same time, the cyber-physical convergence in production system creates massive amounts of industrial data that ...
Renke Liu, R. Piplani, C. Toro
semanticscholar   +1 more source

Real-Time Scheduling for Dynamic Partial-No-Wait Multiobjective Flexible Job Shop by Deep Reinforcement Learning

IEEE Transactions on Automation Science and Engineering, 2022
In modern discrete flexible manufacturing systems, dynamic disturbances frequently occur in real time and each job may contain several special operations in partial-no-wait constraint due to technological requirements.
Shu Luo, Linxuan Zhang, Yushun Fan
semanticscholar   +1 more source

Solving Multiobjective Fuzzy Job-Shop Scheduling Problem by a Hybrid Adaptive Differential Evolution Algorithm

IEEE Transactions on Industrial Informatics, 2022
The job-shop scheduling problem (JSP) is NP hard, which has very important practical significance. Because of many uncontrollable factors, such as machine delay or human factors, it is difficult to use a single real-number to express the processing and ...
Gai-ge Wang, D. Gao, W. Pedrycz
semanticscholar   +1 more source