Results 121 to 130 of about 268,397 (277)

Stochastic optimization of Power‐to‐Methanol: Production cost sensitivity to process design vs. scheduling

AIChE Journal, EarlyView.
Abstract Under time‐varying electricity prices, the production costs of Power‐to‐X processes with intermediate storage can be reduced by simultaneously optimizing the process unit design and size with their scheduling and operation. However, the production cost sensitivity to optimal process design or scheduling is unclear, especially when several ...
Simone Mucci, Dominik Bongartz
wiley   +1 more source

Hardware acceleration of number theoretic transform for zk‐SNARK

Engineering Reports, EarlyView., 2023
An FPGA‐based hardware accelerator with a multi‐level pipeline is designed to support the large‐bitwidth and large‐scale NTT tasks in zk‐SNARK. It can be flexibly scaled to different scales of FPGAs and has been equipped in the heterogeneous acceleration system with the help of HLS and OpenCL.
Haixu Zhao, Dong Ding, Feng Wang, Pengcheng Hua, Ning Wang, Qin Wu, Zhilei Chai   +6 more
wiley   +1 more source

Efficient Minimum Flow Decomposition via Integer Linear Programming. [PDF]

J Comput Biol, 2022
Dias FHC, Williams L, Mumey B, Tomescu AI.   +3 more
europepmc   +1 more source

Graph‐based imitation and reinforcement learning for efficient Benders decomposition

AIChE Journal, EarlyView.
Abstract This work introduces an end‐to‐end graph‐based agent for accelerating the computational efficiency of Benders Decomposition. The agent's policy is parameterized by a graph neural network, which takes as input a bipartite graph representation of the master problem and proposes a candidate solution.
Bernard T. Agyeman, Zhe Li, Ilias Mitrai, Prodromos Daoutidis   +3 more
wiley   +1 more source

Research on outpatient capacity planning combining lean thinking and integer linear programming. [PDF]

BMC Med Inform Decis Mak, 2023
Hua L, Dongmei M, Xinyu Y, Xinyue Z, Shutong W, Dongxuan W, Hao P, Ying W.   +7 more
europepmc   +1 more source

Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution

Advanced Intelligent Discovery, EarlyView.
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren, Qian Jiang, Xin Jin, Puming Wang, Xing Chu, Shaowen Yao, Shengfa Miao   +6 more
wiley   +1 more source

Optimization of a Food List for Food Frequency Questionnaires Using Mixed Integer Linear Programming: A Proof of Concept Based on Data from the Second German National Nutrition Survey. [PDF]

Nutrients, 2023
Blaurock J, Heuer T, Gedrich K.
europepmc   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Clinically Informed Intelligent Classification of Ovarian Cancer Cells by Label‐Free Holographic Imaging Flow Cytometry

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quantitative phase maps of single cells recorded in flow cytometry modality feed a hierarchical architecture of machine learning models for the label‐free identification of subtypes of ovarian cancer. The employment of a priori clinical information improves the classification performance, thus emulating the clinical application of liquid biopsy during ...
Daniele Pirone, Beatrice Cavina, Daniele Gaetano Sirico, Martina Mugnano, Vittorio Bianco, Lisa Miccio, Anna Myriam Perrone, Anna Maria Porcelli, Giuseppe Gasparre, Ivana Kurelac, Pasquale Memmolo, Pietro Ferraro   +11 more
wiley   +1 more source

Maximum likelihood reconstruction of ancestral networks by integer linear programming. [PDF]

Bioinformatics, 2021
Rajan V, Zhang Z, Kingsford C, Zhang X.
europepmc   +1 more source