Results 231 to 240 of about 1,407,468 (324)

Monte Carlo and Quasi-Monte Carlo Methods [PDF]

, 2016
openaire   +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

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

Enhancing Monte Carlo Tree Search for Retrosynthesis. [PDF]

J Chem Inf Model
Blackshaw TM, Davies JC, Spoerer KT, Hirst JD.   +3 more
europepmc   +1 more source

Comparative study of plasmons in half-filled graphene via Quantum Monte Carlo and Random Phase Approximation [PDF]

Maksim Ulybyshev, Adrien Reingruber, Kitinan Pongsangangan   +2 more
openalex  

RPSLearner: A Novel Approach Based on Random Projection and Deep Stacking Learning for Categorizing Non‐Small Cell Lung Cancer

Advanced Intelligent Systems, EarlyView.
Identifying non‐small cell lung cancer (NSCLC) subtypes is essential for precision cancer treatment. Conventional methods are laborious, or time‐consuming. To address these concerns, RPSLearner is proposed, which combines random projection and stacking ensemble learning for accurate NSCLC subtyping. RPSLearner outperforms state‐of‐the‐art approaches in
Xinchao Wu, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

Mechanisms of Barium Sulfate Dissolution through the Lens of Kinetic Monte Carlo Simulations. [PDF]

ACS Omega
Trofimov N, Luttge A, Kurganskaya I.
europepmc   +1 more source

Monte Carlo Simulation of Proton-induced Cosimc Ray Cascades in the Atmosphere

, 2007
C. Hagmann, D. J. Lange, Doug Wright
openalex   +2 more sources

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