Results 141 to 150 of about 2,251,103 (302)

Corn Leaf Disease Classification Optimization Using Resnet50 Architecture Utilizing Bayesian Optimization

Journal of Electrical Engineering and Computer
This research aims to optimize the classification of diseases on corn leaves using Convolutional Neural Network (CNN) architecture, ResNet50, combined with hyperparameter optimization techniques using Bayesian Optimization.
Yahya Auliya Abdillah, Kusrini Kusrini
doaj   +1 more source

Muscle Control of an Extra Robotic Digit

Advanced Robotics Research, EarlyView.
This study compares muscle‐ and movement‐based control for operating a supernumerary robotic thumb. While movement control performs better in the proposed tasks, muscle‐based (EMG) control promotes broader motor learning. The results highlight the promise and challenges of using biosignals for human augmentation, offering new insights into intuitive ...
Julien Russ, Lucy Dowdall, Francesco Cenciarelli, Kitty Goodridge, Mabel Ziman, Hristo Dimitrov, Danielle Clode, Tamar R. Makin   +7 more
wiley   +1 more source

Single‐Cell Dissection of Therapy‐Induced Remodeling Uncovers a Fibroblast‐Driven Immunosuppressive Niche and Targetable Vulnerabilities in Lethal Prostate Cancer

Advanced Science, EarlyView.
Single‐cell longitudinal profiling reveals that androgen‐deprivation therapy induces a DPT+ fibroblast‐complement axis that suppresses macrophage inflammation and drives CD8+ T cell exhaustion in prostate cancer. Concurrently, resistant epithelial subpopulations persist and engage TSPAN1‐ and NRXN1‐mediated programs promoting CRPC and neuroendocrine ...
Yang Chen, Dandan Dong, Jinling Liao, Naikai Liao, Mengqi Liu, Qin Zhang, Siting Chen, Qi Liu, Ying Lu, Tianyu Li, Chunlin Zou, Qiong Song, Qiuyan Wang, Jian Liang, Qiji Xie, Chengyang Li, Mengyun Wang, Jiwen Cheng, Zengnan Mo, Gong‐Hong Wei   +19 more
wiley   +1 more source

Traditional or adaptive design of experiments? A pilot-scale comparison on wood delignification

Heliyon
Traditional design of experiments and response surface methodology are widely used in engineering and process development. Bayesian optimization is an alternative machine learning approach that adaptively selects successive experimental conditions based ...
Hannu Rummukainen, Hanna Hörhammer, Pirkko Kuusela, Jorma Kilpi, Jari Sirviö, Mikko Mäkelä   +5 more
doaj   +1 more source

Categorical Inputs, Sensitivity Analysis, Optimization and Importance Tempering with tgp Version 2, an R Package for Treed Gaussian Process Models [PDF]

This document describes the new features in version 2.x of the tgp package for R, implementing treed Gaussian process (GP) models. The topics covered include methods for dealing with categorical inputs and excluding inputs from the tree or GP part of the
Robert B. Gramacy, Matthew Alan Taddy
core  

Iron‐Mediated Release of Aged Dissolved Organic Carbon From Waterlogged Peatland Under Warming

Advanced Science, EarlyView.
This study conducts a five‐year in situ warming experiment in high‐altitude peatlands to examine dissolved organic carbon (DOC) release. The study shows that warming promotes the release of plant‐derived modern DOC in drained peatlands, but amplifies aquatic export of century‐old DOC from waterlogged peatlands via Fe‐mediated DOC mobilization—a ...
Guohua Dai, Zhiying Yang, Zongguang Liu, Wanjia Hu, Lixiao Ma, Enze Kang, Wanqing Luo, Yunpeng Zhao, Chengzhu Liu, Juan Jia, Ting Liu, Chen He, Quan Shi, Jianliang Liu, Yongheng Gao, Huai Chen, Hailong Zhang, Meixun Zhao, Xiaojuan Feng   +18 more
wiley   +1 more source

Prompt Optimization in Large Language Models

Mathematics
Prompt optimization is a crucial task for improving the performance of large language models for downstream tasks. In this paper, a prompt is a sequence of n-grams selected from a vocabulary.
Antonio Sabbatella, Andrea Ponti, Ilaria Giordani, Antonio Candelieri, Francesco Archetti   +4 more
doaj   +1 more source

Bilevel Optimization by Conditional Bayesian Optimization

Bilevel optimization problems have two decision-makers: a leader and a follower (sometimes more than one of either, or both). The leader must solve a constrained optimization problem in which some decisions are made by the follower. These problems are much harder to solve than those with a single decision-maker, and efficient optimal algorithms are ...
Vedat Dogan, Steven D. Prestwich
openaire   +2 more sources

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

PMCBO: A Distributed Multi-Task Collaborative Bayesian Optimization Algorithm via Expert Beliefs over Networks

Mathematics
To optimize expensive black-box functions over networks, one of the most dominant frameworks is distributed Bayesian optimization (DBO), where local information can be exchanged among agents.
Youming Ge, Haishen Jiang, Zhihang Ji
doaj   +1 more source