Results 51 to 60 of about 20,971 (250)

A Comparative Study of Neural Network Performance on the NVIDIA Jetson Orin Nano

IEEE Access
This paper presents a comparative evaluation of the runtime characteristics of three deep learning model architectures for both image classification and object detection, executed across three programming languages and three inference frameworks.
Richard Szegedi, Yannick Bukschat, Marcus Vetter   +2 more
doaj   +1 more source

Multi-Tasking and Choice of Training Data Influencing Parietal ERP Expression and Single-Trial Detection—Relevance for Neuroscience and Clinical Applications

Frontiers in Neuroscience, 2018
Event-related potentials (ERPs) are often used in brain-computer interfaces (BCIs) for communication or system control for enhancing or regaining control for motor-disabled persons.
Elsa A. Kirchner, Elsa A. Kirchner, Su Kyoung Kim   +2 more
doaj   +1 more source

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

Robotics And Artificial Intelligence

, 2018
Recent Advancement on Deep Learning in Ocular Image ...
  +7 more sources

Thin and Flexible Breeze-Sense Generators for Non-Contact Haptic Feedback in Virtual Reality

Nano-Micro Letters
Highlights The breeze-sense generators generate significant air flow pressure output of ~ 163 Pa that can easily be sensed by human skin and have an overall thickness around 1 mm. Volunteers successfully identify multiple programming patterns transmitted
Kaijun Zhang, Zhe Liu, Yexi Zhou, Zhaoyang Li, Dazhe Zhao, Xiao Guan, Tianjun Lan, Yanting Gong, Bingpu Zhou, Junwen Zhong   +9 more
doaj   +1 more source

Toward Knowledge‐Based Workflows: A Semantic Approach to Atomistic Simulations for Mechanical and Thermodynamic Properties

Advanced Engineering Materials, EarlyView.
Knowledge‐based atomistic workflows are presented for mechanical and thermodynamic properties. By coupling modular simulations with ontology‐aligned metadata and provenance, Fe case studies on elastic behavior, defects, thermal properties, and Hall–Petch strengthening reveal how FAIR, queryable, and reusable simulation data can be generated. Mechanical
Abril Azócar Guzmán, Hoang‐Thien Luu, Sarath Menon, Tilmann Hickel, Nina Merkert, Stefan Sandfeld   +5 more
wiley   +1 more source

Exploration of Design Alternatives for Reducing Idle Time in Shor's Algorithm: A Study on Monolithic and Distributed Quantum Systems

IEEE Transactions on Quantum Engineering
Shor's algorithm is one of the most prominent quantum algorithms, yet finding efficient implementations remains an active research challenge. While many approaches focus on low-level modular arithmetic optimizations, a broader perspective can ...
Moritz Schmidt, Abhoy Kole, Leon Wichette, Rolf Drechsler, Frank Kirchner, Elie Mounzer   +5 more
doaj   +1 more source

Influence of Geometric Design on Mechanical Performance of Auxetic Metastructure

Advanced Engineering Materials, EarlyView.
Strategic geometric reinforcement transforms auxetic performance. This study evaluates 3D‐printed arrowhead metastructures, revealing that a modified design with local ring reinforcement suppresses premature failure to achieve superior energy absorption and structural efficiency.
Muhammad Gulzari, Supharoek Sornsomrit, Muhammad Ayaz Akbar, Stephan Rudykh   +3 more
wiley   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Human-centered AI and robotics

AI Perspectives, 2022
Robotics has a special place in AI as robots are connected to the real world and robots increasingly appear in humans everyday environment, from home to industry.
Stephane Doncieux, Raja Chatila, Sirko Straube, Frank Kirchner   +3 more
doaj   +1 more source