Results 91 to 100 of about 2,614 (275)

Energy‐Aware RF Fingerprinting for Device Identification in Ultra‐Low‐Power IoT Systems

Engineering Reports
The security of ultra‐low‐power Internet of Things (IoT) systems is critical yet challenging due to significant energy constraints. These networks are vulnerable to impersonation and data poisoning attacks, where malicious entities can mimic legitimate ...
Emmanuel Osei Owusu, Danlard Iddrisu, Griffith Selorm Klogo, Kwame Osei Boateng, Emmanuel Kofi Akowuah   +4 more
doaj   +1 more source

Helix Alignment, Chevrons, and Edge Dislocations in Twist‐Bend Ferroelectric Nematics

Advanced Science, EarlyView.
The recently discovered twist‐bend ferroelectric nematic (NTBF) is the new member of the multiferroic family, representing a fluid with an oblique helicoidal (heliconical) periodic structure of spontaneous electric polarization. The work presents a thorough exploration of the material properties of this phase, how the periodic modulation of ...
Bijaya Basnet, Priyanka Kumari, Sathyanarayana Paladugu, Damian Pociecha, Jakub Karcz, Przemysław Kula, Nataša Vaupotič, Ewa Górecka, Oleg D Lavrentovich   +8 more
wiley   +1 more source

Security of Wireless Devices using Biological-Inspired RF Fingerprinting Technique

, 2014
Radio Frequency (RF) fingerprinting is a security mechanism inspired by biological fingerprint identification systems. RF fingerprinting is proposed as a means of providing an additional layer of security for wireless devices.
Shafiq Alam, Saeed ur Rehman, Iman T. Ardekani, Rehman, Saeed, Ardekani, Iman, Alam, Shafiq   +5 more
core   +1 more source

Few‐shot cross‐receiver radio frequency fingerprinting identification based on feature separation

IET Communications
Radio frequency fingerprint identification (RFFI) is a widely used technique for authenticating equipment. It identifies transmitters by extracting hardware defects found in the RF front end.
Yuchen Hu, Yihang Du, Xiaoqiang Qiao, Chen Zhao, Tao Zhang, Jiang Zhang   +5 more
doaj   +1 more source

Machine Learning for Green Solvents: Assessment, Selection and Substitution

Advanced Science, EarlyView.
Environmental regulations have intensified demand for green solvents, but discovery is limited by Solvent Selection Guides (SSGs) that quantify solvent sustainability. Training a machine learning model on GlaxoSmithKline SSG, a database of sustainability metrics for 10,189 solvents, GreenSolventDB is developed. Integrated with Hansen solubility metrics,
Rohan Datta, Janhavi Nistane, Abhishek Sose, Harikrishna Sahu, Rampi Ramprasad   +4 more
wiley   +1 more source

Spatial and Temporal Agnostic Deep-learning Based Radio Fingerprinting

, 2023
Radio fingerprinting is a technique that validates wireless devices based on their unique radio frequency (RF) signals. This method is highly feasible because RF signals carry distinct hardware variations introduced during manufacturing. The security and
Afrin, Fahmida
core  

Machine‐Learning Microfluidic Minute‐Scale Microorganism Metrics Monitoring(M6)

Advanced Science, EarlyView.
ABSTRACT On‐site monitoring of microorganisms remains challenging because of low concentrations, strong background interference, and dynamic aerosol diffusion, particularly for aerosol‐transmitted pathogens. Here, we report a rapid detection platform that integrates a Puri‐focusing microfluidic chip, electrochemical impedance spectroscopy (EIS), and ...
Ning Yang, Jiahao Ding, Si Chen, Lijie Yan, Shichao Ding, Lavonda Li, Junyi Sun, Haodong Liu, Tongge Li, Ning Liu, Mingji Wei, Xiaoyong Zhu, Xiaobo Zou, Shouqi Yuan, Xingcai Zhang   +14 more
wiley   +1 more source

Generative AI‐Driven Accelerated Discovery of Passivation Molecules for Perovskite Solar Cells

Advanced Science, EarlyView.
A generative artificial intelligence (AI) framework combining a discriminative machine learning model (SMILES‐X) and a generative language model (GPT‐2) autonomously discovers new molecular passivators for perovskite solar cells (PSCs). Through an iterative design loop, over 100 000 candidates are generated and screened, and randomly selected molecules
Adroit T. N. Fajar, Guillaume Lambard, Jessie Manopo, Ruili Guo, Kevin Septioga, Rizfi F. Pari, Toshinori Matsushima, Zhanglin Guo   +7 more
wiley   +1 more source

Convolutional Neural Network and Ensemble Learning-Based Unmanned Aerial Vehicles Radio Frequency Fingerprinting Identification

Drones
With the rapid development of the unmanned aerial vehicles (UAVs) industry, there is increasing demand for UAV surveillance technology. Automatic Dependent Surveillance-Broadcast (ADS-B) provides accurate monitoring of UAVs.
Yunfei Zheng, Xuejun Zhang, Shenghan Wang, Weidong Zhang   +3 more
doaj   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source