Results 151 to 160 of about 16,838,211 (334)

Energy-Efficient Blockchain-Enabled IoT Networks:A Deep Reinforcement Learning Approach

Energy-Efficient Blockchain-Enabled IoT Networks:A Deep Reinforcement Learning Approach ZERIHUN HURUY NEGASH Supervised By: Professor Sungoh Kwon Submitted in Partial Fulfillment of the Requirements for the degree of Master of Science The growing ...
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Energy-Efficient Prediction in Textile Manufacturing: Enhancing Accuracy and Data Efficiency With Ensemble Deep Transfer Learning

IEEE Access
Traditional textile factories consume substantial energy, making energy-efficient production optimization crucial for sustainability and cost reduction.
Yan-Chen Chen, Wei-Yu Chiu, Qun-Yu Wang, Jing-Wei Chen, Hao-Ting Zhao   +4 more
doaj   +1 more source

Self‐Adaptive Gradient Interphase Enables Durable Solid‐State Lithium Metal Batteries

Advanced Functional Materials, EarlyView.
This work presents a machine learning‐guided interfacial design that forms a self‐adaptive graded interphase on lithium metal anode. A B105M40 composite interlayer evolves into lithiophilic, porous, and fast‐ion‐conducting phases, enabling intimate contact, dendrite suppression, and uniform lithium deposition.
Hongmin Liu, Rui Li, Yitao Lou, Xinran Gao, Min Xu, Shijian Wang, Nana Wang, Huakun Liu, Guoxiu Wang, Zhongchao Bai   +9 more
wiley   +1 more source

Energy-efficient adaptive sampling for IIoT via deep perception and reinforcement learning

Journal of King Saud University: Computer and Information Sciences
To mitigate resource waste and information loss in fixed-frequency sampling for the Industrial Internet of Things (IIoT), this paper proposes a collaborative framework integrating dynamic perception with adaptive sampling.
Shuangying Li, Peishun Liu, Jintao Chen, Xinyue Li, Ruixin Hua   +4 more
doaj   +1 more source

On-Device Deep Learning: Survey on Techniques Improving Energy Efficiency of DNNs

IEEE Transactions on Neural Networks and Learning Systems
Providing high-quality predictions is no longer the sole goal for neural networks. As we live in an increasingly interconnected world, these models need to match the constraints of resource-limited devices powering the Internet of Things (IoT) and embedded systems. Moreover, in the era of climate change, reducing the carbon footprint of neural networks
Anais Boumendil, Walid Bechkit, Karima Benatchba   +2 more
openaire   +3 more sources

Biodegradable Conductors for Implantable and Wearable Transient Bioelectronics

Advanced Functional Materials, EarlyView.
Biodegradable conductors are essential building blocks for transient bioelectronics, enabling temporary sensing, stimulation, and energy transfer while eliminating the need for device retrieval. This review summarizes biodegradable metals, conducting polymers, ionic conductors, and conductive composites, highlighting degradation mechanisms, material ...
Yicheng Zhu, Yijun Liu, Naoji Matsuhisa
wiley   +1 more source

Energy Scheduling of Hydrogen Hybrid UAV Based on Model Predictive Control and Deep Deterministic Policy Gradient Algorithm

Algorithms
Energy scheduling for hybrid unmanned aerial vehicles (UAVs) is of critical importance to their safe and stable operation. However, traditional approaches, predominantly rule-based, often lack the dynamic adaptability and stability necessary to address ...
Haitao Li, Chenyu Wang, Shufu Yuan, Hui Zhu, Bo Li, Yuexin Liu, Li Sun   +6 more
doaj   +1 more source

A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems

Scientific Reports
The rapid evolution of smart grids, driven by rising global energy demand and renewable energy integration, calls for intelligent, adaptive, and energy-efficient resource allocation strategies.
Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, H. Addis, K. Sarada   +5 more
semanticscholar   +1 more source

NeuroVisio SyncPatch: A Skin‐Conformal Multimodal EMG–Motion Sensing Platform for Quantitative Neuromuscular Rehabilitation and Performance Monitoring

Advanced Healthcare Materials, EarlyView.
NeuroVisio SyncPatch integrates skin‐conformal electromyography (EMG) electrodes with camera‐tracked markers to jointly assess muscle activity and three‐dimensional knee kinematics during rehabilitation. Parallel feedback pathways provide real‐time kinematic guidance during movement and post‐trial neuromuscular feedback.
Bohyung Choi, Yoo‐Jin Jun, Heewon Choee, Kun‐Do Lee, Heesoo Kim, Yu Seok Hwang, Choong Yeon Kim, Seongok Chae, Juhyun Lee, Minkyu Je, Jae‐Woong Jeong, Hyung‐Soon Park   +11 more
wiley   +1 more source

Energy-Smart Building Choices: How School Facilities Managers and Business Officials Are Reducing Operating Costs and Saving Money

, 2001
Most K-12 schools could save 25% of their energy costs by being smart about energy. Nationwide, the savings potential is $6 billion. While improving energy use in buildings and busses, schools are likely to create better places for teaching and learning,
Team, Energy Smart Schools
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