Results 161 to 170 of about 577,814 (285)

A Data‐Centric Approach to Quantifying the Forward and Inverse Relationship Between Laser Powder Bed Fusion Process Parameters and as‐Built Surface Roughness of IN718 Parts

Advanced Intelligent Systems, EarlyView.
This study introduces the first inverse machine learning model to predict laser powder bed fusion process parameters for targeted surface roughness of Inconel 718 parts. Unlike prior approaches, it incorporates spatial surface characteristics for improved accuracy.
Samsul Mahmood, Bart Raeymaekers
wiley   +1 more source

CH₄ Adsorption Behavior on Coals with Different Ranks by Grand Canonical Monte Carlo Simulations. [PDF]

ACS Omega
Chen Z, Ge H, Zhang J, Wang Y, Yan Z, Zhang Y, Liang X.   +6 more
europepmc   +1 more source

Machine Learning‐Based Standard Compact Model Binning Parameter Extraction Methodology for Integrated Circuit Design of Next‐Generation Semiconductor Devices

Advanced Intelligent Systems, EarlyView.
This study presents a neural network‐based methodology for Berkeley Short‐Channel IGFET Model–Common Multi‐Gate parameter extraction of gate‐all‐around field effect transistors, integrating binning adaptive sampling and transformer neural networks to efficiently capture current–voltage and capacitance–voltage characteristics.
Jaeweon Kang, Johyeon Kim, Sueyeon Kim, Hyunbo Cho, Jongwook Jeon   +4 more
wiley   +1 more source

Exploring the role of sample thickness for hyperspectral microscopy tissue discrimination through Monte Carlo simulations. [PDF]

Biomed Opt Express
Quintana-Quintana L, Witteveen M, Dashtbozorg B, Ortega S, Ruers TJM, Sterenborg HJCM, Callico GM.   +6 more
europepmc   +1 more source

Ternary Content‐Addressable Memory Using One Capacitor and One Nanoelectromechanical Memory Switch for Data‐Intensive Applications

Advanced Intelligent Systems, EarlyView.
A charge‐domain ternary content‐addressable memory using one capacitor one nanoelectromechanical memory switch (1C‐1N TCAM) is proposed for energy‐efficient, high‐reliability computations. Integrated with the back‐end‐of‐line process, the 1C‐1N TCAM leverages the air gap capacitance to achieve a high capacitance ratio and ternary functionality.
Jin Wook Lee, Changha Kim, Geun Tae Park, Seung Hun Baek, Myeong Su Shin, Woo Young Choi   +5 more
wiley   +1 more source

Advancing X-ray quantum imaging through Monte-Carlo simulations. [PDF]

Sci Rep
Espoukeh P, Biener G, Baxter J, Aquila A, Schwander P.   +4 more
europepmc   +1 more source

Polymerase Chain Reaction. Perturbation Theory and Machine Learning Artificial Intelligence‐Experimental Microbiome Analysis: Applications to Ancient DNA and Tree Soil Metagenomics Cases of Study

Advanced Intelligent Systems, EarlyView.
The polymerase chain reaction (PCR).Perturbation Theory and Machine Learning framework integrates perturbation theory and machine learning to classify genetic sequences, distinguishing ancient DNA from modern controls and predicting tree health from soil metagenomic data.
Jose L. Rodriguez, Estefania Ascencio, Jose M. Ageitos, Lucia Feijoo, Shan He, Amirreza Daghighi, Gerardo M. Casanola‐Martin, Cristian R. Munteanu, Santiago Rodriguez Yañez, Alejandro Pazos, Harbil Bediaga, Brenda Durand Ordiales, Raquel Esteban, Ana‐Maria Heres, Jorge Curiel Yuste, Lur Epelde, Bakhtiyor Rasulev, Tomas Gonzalez, Sonia Arrasate, Humberto González‐Diaz   +19 more
wiley   +1 more source

Accelerated Free Energy Estimation in <i>Ab Initio</i> Path Integral Monte Carlo Simulations. [PDF]

J Phys Chem Lett
Svensson P, Kalkavouras F, Hernandez Acosta U, Moldabekov ZA, Tolias P, Vorberger J, Dornheim T.   +6 more
europepmc   +1 more source

Real‐Time Sampling‐Based Model Predictive Control Based on Reverse Kullback–Leibler Divergence and Its Adaptive Acceleration

Advanced Intelligent Systems, EarlyView.
This study presents a new sampling‐based model predictive control minimizing reverse Kullback‐Leibler divergence to quickly find a local optimum. In addition, a modified Nesterov's acceleration method is introduced for faster convergence. The method is effective for real‐time simulations and real‐world operability improvement on a force‐driven mobile ...
Taisuke Kobayashi, Kota Fukumoto
wiley   +1 more source

A Novel Contact‐Implicit Trajectory Optimization Framework for Quadruped Locomotion without Fixed Contact Sequences

Advanced Intelligent Systems, EarlyView.
Legged robots have advanced in environmental interaction through contact, but most works rely on fixed contact sequences. This work presents a new method based on an indirect optimization method for legged robots to automatically generate contact sequences for complex movements.
Yaowei Chen, Jie Zhang, Ming Lyu
wiley   +1 more source