Results 141 to 150 of about 3,042,897 (294)

A Review on Recent Trends of Bioinspired Soft Robotics: Actuators, Control Methods, Materials Selection, Sensors, Challenges, and Future Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker, Tamzid Ul Islam, Md. Robiul Islam   +2 more
wiley   +1 more source

Adversarial Learning in Accelerometer Based Transportation and Locomotion Mode Recognition

, 2022
This chapter demonstrates how adversarial learning can be used in the mobile computing domain. Specifically, we address the problem of improving the recognition of human activities from smartphone sensors, when limited training data is available ...
Wang, L, Günthermann, L, Philippides, A, Simpson, I, Roggen, D   +4 more
core   +1 more source

Generating Images Using Generative Adversarial Networks

, 2020
U ovom radu su objašnjene neuronske mreže, konvolucijske neuronske mreže i generativne suparničke mreže. Cilj je generiranje slika u boji korištenjem ACGAN-a.
Bartol, Mirko
core  

Large Language Model‐Based Chatbots in Higher Education

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci, Merve Eryilmaz, Ail K. Yetisen, Savas Tasoglu, Aydogan Ozcan   +4 more
wiley   +1 more source

Predicting Performance of Hall Effect Ion Source Using Machine Learning

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park, Guentae Doh, Dongho Lee, Youngho Kim, Changmin Shin, Su‐Jin Shin, Young‐Chul Ghim, Sanghoo Park, Wonho Choe   +8 more
wiley   +1 more source

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

Advanced Intelligent Systems, EarlyView.
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica, Kostya S. Novoselov, Seongmin Kim, Yousung Jung, Silvana Botti, Miguel A. L. Marques, Tigany Zarrouk, Miguel A. Caro, Sanggyu Chong, Michele Ceriotti, Marivi Fernandez‐Serra, Sara Navarro‐Rodriguez, Aakash Ashok Naik, Janine George, Ömer Hasan Omar, Victor Trinquet, Gian‐Marco Rignanese, Andrey Ustyuzhanin, Sonia Conesa‐Boj, Juan Rojo, Minh‐Tuan Dau, Simon M.‐M. Dubois, Jean‐Christophe Charlier, Jose H. Garcia, Romain Gautier, Rachid Laref, Junfeng Qiao, Giovanni Pizzi, Nicola Marzari, Camilla Coletti, Antonio Rossi, Jan‐Lucas Uslu, Chiara Zanardi, Vincenzo Palermo, Wide Hogenhout, Natalia Konchakova, Peter Klein, Tejs Vegge, Stephan Roche   +38 more
wiley   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

Transformative skeletal motion analysis: optimization of exercise training and injury prevention through graph neural networks

Frontiers in Neuroscience
IntroductionExercise is pivotal for maintaining physical health in contemporary society. However, improper postures and movements during exercise can result in sports injuries, underscoring the significance of skeletal motion analysis. This research aims
Jiaju Zhu, Zijun Ye, Meixue Ren, Guodong Ma, Guodong Ma   +4 more
doaj   +1 more source

Semi-supervised community detection method based on generative adversarial networks

Journal of King Saud University: Computer and Information Sciences
Community detection in complex networks often suffers from insufficient data and limited utilization of prior knowledge. In this paper we propose “Semi-supervised Generative Adversarial Network” (GANSE), a novel algorithm that integrates Generative ...
Xiaoyang Liu, Mengyao Zhang, Yanfei Liu, Chao Liu, Chaorong Li, Wei Wang, Xiaoqin Zhang, Asgarali Bouyer   +7 more
doaj   +1 more source

Resilient Multimodal Fusion for Robust Vulnerability Exploitability Prediction Under Data Degradation

Advanced Intelligent Systems, EarlyView.
Secure Fusion‐X harmonizes unstructured NVD descriptions with structured CVSS/CWE/CPE metadata via decision‐level fusion, overcoming the fragility of traditional unimodal models. Automated assessment of software vulnerability exploitability is essential for intelligent cyber defense, yet its effectiveness is often hindered by unstable, delayed, or ...
Mona Dolati, Seyedeh Leili Mirtaheri, Reza Shahbazian, Andrea Pugliese   +3 more
wiley   +1 more source