Results 101 to 110 of about 31,999 (310)

Triple‐Mode Ferroelectric Thin‐Film Transistor for Hybrid Electrical–Optical Reservoir Computing

Advanced Science, EarlyView.
A triple‐mode ferroelectric thin‐film transistor is developed by integrating Si3N4/HZO/IGZO layers to realize three independent memory modes: electric long‐term, electric short‐term, and optical short‐term. This single‐device architecture functions as both a reservoir and readout layer, achieving 92.43% MNIST accuracy. It offers a fully hardware‐based,
Hyeonho Lee, Seungjun Lee, Tae‐Hyeon Kim, Yonghee Jeong, Gwangmin An, Minsu Ko, Junsu Yu, Heung Soo Kim, Yang Chai, Sungjun Kim   +9 more
wiley   +1 more source

Stochastic model of business process decomposition

CoRR, 2019
Published in two languages (English and Russian)
openaire   +2 more sources

Processing second-order stochastic dominance models using cutting-plane representations [PDF]

, 2011
This is the post-print version of the Article. The official published version can be accessed from the links below. Copyright @ 2011 Springer-VerlagSecond-order stochastic dominance (SSD) is widely recognised as an important decision criterion in ...
Mitra, G, Fabian, CI, Roman, D
core   +1 more source

Combining Spatial Multi‐Omics Data to Decipher Spatial Domains and Elucidate Cell Heterogeneity Based on Self‐Supervised Graph Learning

Advanced Science, EarlyView.
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu, Rui Qiao, Ying Li, Junhong Li, Nuoya Yue, Jing Ge, Jiao Wang, Luonan Chen, Peiluan Li   +8 more
wiley   +1 more source

Decomposition Algorithms for Stochastic Programming on a Computational Grid

Computational Optimization and Applications, 2003
We describe algorithms for two-stage stochastic linear programming with recourse and their implementation on a grid computing platform. In particular, we examine serial and asynchronous versions of the L-shaped method and a trust-region method. The parallel platform of choice is the dynamic, heterogeneous, opportunistic platform provided by the Condor ...
Jeff T. Linderoth, Stephen J. Wright 0001   +1 more
openaire   +2 more sources

Shear‐Induced Emergence of Aromatic Superlow‐Friction Interfaces in Amorphous Carbon: Triggering Chemical Impurities and Atomic‐Scale Mechanisms

Advanced Science, EarlyView.
High‐throughput quantum‐mechanical simulations reveal that amorphous carbon undergoes shear‐driven structural transformation into aromatic, graphene‐like interfaces. This mechanochemical process is governed by dopant chemistry: dopants with valency less than four promote the emergence of superlow‐friction amorphous graphene, whereas tetra‐valent ...
Takuya Kuwahara, Koki Horiguchi, Leonhard Mayrhofer, Gianpietro Moras, Michael Moseler   +4 more
wiley   +1 more source

Parallel decomposition of multistage stochastic programming problems [PDF]

Mathematical Programming, 1993
The author deals with a multistage stochastic linear programming problem. In detail, he considers a nonanticipative case and a finite underlying probability space. Consequently, the considered multistage stochastic programming problem can be represented in a tree like form and moreover, with each note of the decision tree a certain linear or quadratic ...
openaire   +2 more sources

Unraveling the Power of Disorder: A Bioinspired Cuttlebone Structure With Superior Strength, Energy Absorption and Isotropy

Advanced Science, EarlyView.
Cuttlebone‐inspired architected metamaterials introduce controlled structural disorder to simultaneously enhance strength, energy absorption, and compressive stability. Tunable disorder suppresses shear anisotropy, outperforms periodic lattices, and establishes discrete randomness as a robust route to high‐performance lightweight mechanical ...
Zengqin Shi, Peng Jiang, Xiaoyan Zhu, Suyun Li, Wenqing Wang, Tian Zhao, Rujie He, Ying Li   +7 more
wiley   +1 more source

Disentangling dynamic and stochastic modes in multivariate time series

Frontiers in Applied Mathematics and Statistics
A signal decomposition is presented that disentangles the deterministic and stochastic components of a multivariate time series. The dynamical component analysis (DyCA) algorithm is based on the assumption that an unknown set of ordinary differential ...
Christian Uhl, Annika Stiehl, Nicolas Weeger, Markus Schlarb, Markus Schlarb, Knut Hüper   +5 more
doaj   +1 more source

A Stochastic Multiobjective Optimization Framework for Wireless Sensor Networks

EURASIP Journal on Wireless Communications and Networking, 2010
In wireless sensor networks (WSNs), there generally exist many different objective functions to be optimized. In this paper, we propose a stochastic multiobjective optimization approach to solve such kind of problem.
Shibo He, Jiming Chen, Weiqiang Xu, Youxian Sun, Preetha Thulasiraman, Xuemin (Sherman) Shen   +5 more
doaj   +1 more source