Results 81 to 90 of about 96,235 (264)

OPTIMIZATIONS OF DEEP LEARNING OBJECTS DETECTION MODELS FOR INFERENCE ACCELERATION ON GENERAL-PURPOSE AND HARDWARE-ACCELERATED SINGLE-BOARD PLATFORMS

Електроніка та інформаційні технології
Background. Description and preparation of modern approaches for deep learning object detection models are provided. Deep learning frameworks for model training and inference, such as TensorFlow and TensorFlow Lite, are used as bases.
Dmytro Myroniuk, Bohdan Blahitko
doaj   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

A Dataset and Experimental Evaluation of a Parallel Conflict Detection Solution for Model-Based Diagnosis

Data
This article presents a dataset and experimental evaluation of a parallelized variant of Junker’s QuickXPlain algorithm, designed to efficiently compute minimal conflict sets in constraint-based diagnosis tasks.
Jessica Janina Cabezas-Quinto, Cristian Vidal-Silva, Jorge Serrano-Malebrán, Nicolás Márquez   +3 more
doaj   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

Benchmarking the performance of Python web frameworks

Journal of Computer Sciences Institute
This article presents a comparative performance analysis of three the most popular Python web frameworks - Django (with Django Rest Framework), Flask, and FastAPI - in the context of developing Web APIs. The evaluation focused on key performance metrics
Bartłomiej Bednarz, Marek Miłosz
doaj   +1 more source

The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty

Journal of Advances in Modeling Earth Systems, 2019
The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems.
David M. Lawrence, Rosie A. Fisher, Charles D. Koven, Keith W. Oleson, Sean C. Swenson, Gordon Bonan, Nathan Collier, Bardan Ghimire, Leo vanKampenhout, Daniel Kennedy, Erik Kluzek, Peter J. Lawrence, Fang Li, Hongyi Li, Danica Lombardozzi, William J. Riley, William J. Sacks, Mingjie Shi, Mariana Vertenstein, William R. Wieder, Chonggang Xu, Ashehad A. Ali, Andrew M. Badger, Gautam Bisht, Michiel van denBroeke, Michael A. Brunke, Sean P. Burns, Jonathan Buzan, Martyn Clark, Anthony Craig, Kyla Dahlin, Beth Drewniak, Joshua B. Fisher, Mark Flanner, Andrew M. Fox, Pierre Gentine, Forrest Hoffman, Gretchen Keppel‐Aleks, Ryan Knox, Sanjiv Kumar, Jan Lenaerts, L. Ruby Leung, William H. Lipscomb, Yaqiong Lu, Ashutosh Pandey, Jon D. Pelletier, Justin Perket, James T. Randerson, Daniel M. Ricciuto, Benjamin M. Sanderson, Andrew Slater, Zachary M. Subin, Jinyun Tang, R. Quinn Thomas, Maria Val Martin, Xubin Zeng   +55 more
doaj   +1 more source

A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science

Advanced Engineering Materials, EarlyView.
We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann, Sarath Menon, Raphael Röske, Johannes Steinhülb, Michael Selzer, Jan Janssen, Tilmann Hickel, Ruth Schwaiger, Jörg Neugebauer   +8 more
wiley   +1 more source

Benchmarking [PDF]

Proceedings., International Test Conference, 2002
openaire   +2 more sources

High‐Temperature Nanoindentation of Metals: Assessing Thermal Drift, Frame Compliance, and Chemical Composition Effects on the Reported Mechanical Properties

Advanced Engineering Materials, EarlyView.
Do not let thermal drift and instrument artifacts deceive high‐temperature nanoindentation results. We compare classical Oliver–Pharr and automatic image recognition analyses across steels and a Ni alloy to quantify these effects. Accounting for artifacts reveals systematic softening with temperature, while Cr and Ni additions boost resistance ...
Velislava Yonkova, Steffen Brinckmann, Ruth Schwaiger   +2 more
wiley   +1 more source

Machine Learning Methods as a Cost-Effective Alternative to Physics-Based Binding Free Energy Calculations

Molecules
The rank ordering of ligands remains one of the most attractive challenges in drug discovery. While physics-based in silico binding affinity methods dominate the field, they still have problems, which largely revolve around forcefield accuracy and ...
Nupur Bansal, Ye Wang, Simone Sciabola
doaj   +1 more source