Results 61 to 70 of about 27,765 (261)

A Smart Machine Learning Model for the Detection of Brain Hemorrhage Diagnosis Based Internet of Things in Smart Cities

Complexity, 2020
Generally, the emergence of Internet of Things enabled applications inspired the world during the last few years, providing state-of-the-art and novel-based solutions for different problems.
Hang Chen, Sulaiman Khan, Bo Kou, Shah Nazir, Wei Liu, Anwar Hussain   +5 more
doaj   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

State-of-the-art in artificial neural network applications: A survey

Heliyon, 2018
This is a survey of neural network applications in the real-world scenario. It provides a taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of current and emerging trends in ANN applications research and area of focus ...
Oludare Isaac Abiodun, Aman Jantan, Abiodun Esther Omolara, Kemi Victoria Dada, Nachaat AbdElatif Mohamed, Humaira Arshad   +5 more
doaj   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

A Novel Approach of Optimal Signal Streaming Analysis Implicated Supervised Feedforward Neural Networks

IET Signal Processing
The analysis and interpretation of enormous amounts of data generated by 5G networks present several challenges related to noise, precision, and feasibility validation.
Farhan Ali, He Yigang
doaj   +1 more source

Extracting grid cell characteristics from place cell inputs using non-negative principal component analysis

eLife, 2016
Many recent models study the downstream projection from grid cells to place cells, while recent data have pointed out the importance of the feedback projection. We thus asked how grid cells are affected by the nature of the input from the place cells. We
Yedidyah Dordek, Daniel Soudry, Ron Meir, Dori Derdikman   +3 more
doaj   +1 more source

Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology

Advanced Intelligent Discovery, EarlyView.
Energy efficient computing has driven a shift toward brain‐inspired neuromorphic hardware. This study explores the design of three distinct silicon neuron topologies implemented in 16 nm fin field‐Effect transistor technology. While the Axon‐Hillock design achieves gigahertz throughput, its functional fragility persists. The Morris–Lecar model captures
Logan Larsh, Raiyan Siddique, Sarah S. Sharif, Yaser Mike Banad   +3 more
wiley   +1 more source

Data-Driven Feedforward Force Control of a Single-Acting Pneumatic Cylinder with a Nonlinear Hysteresis Characteristic

Actuators
Pneumatic force control has a broad application background in the automation field, such as in industrial polishing, robotic grasping, and humanoid robots.
Xiaofeng Wu, Hongliang Hua, Songquan Feng, Yanli Zhao, Yuhong Yang, Zhenqiang Liao   +5 more
doaj   +1 more source

Large‐Scale Machine Learning to Screen for Small‐Molecule Senolytics

Advanced Intelligent Discovery, EarlyView.
A consistent workflow underpins all experiments in this study. A dedicated model‐selection dataset first identifies optimal hyperparameters for each algorithm. Models are then trained and rigorously evaluated on independent sets of molecules using the senolytic ratio SR. Comprehensive hyperparameter exploration across SMILES representations, task types,
Alexis Dougha, Jesus Gil, Pedro J. Ballester   +2 more
wiley   +1 more source