Results 101 to 110 of about 1,838 (257)

MANC: A masked autoencoder neural cryptography based encryption scheme for CT scan images

MethodsX
Sharing medical images securely is very important towards keeping patients’ data confidential. In this paper we propose MANC: a Masked Autoencoder Neural Cryptography based encryption scheme for sharing medical images. The proposed technique builds upon
Kishore Kumar, Sarvesh Tanwar, Shishir Kumar   +2 more
doaj   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Image encryption and distribution method based on LFSR and counters

Ìнформаційні технології та компʼютерна інженерія
In the conditions of processing large amounts of graphic data, the task arises of developing a reliable image encryption scheme with reduced computing costs.
V. Luzhetsky, M. Tsikhotskyi
doaj   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Small Stretch Problem of the DCT Scheme and How to Fix It

IACR Transactions on Symmetric Cryptology
DCT is a beyond-birthday-bound (BBB) deterministic authenticated encryption (DAE) mode proposed by Forler et al. in ACISP 2016, ensuring integrity by redundancy. The instantiation of DCT employs the BRW polynomial, which is more efficient than the usual
Yuchao Chen, Tingting Guo, Lei Hu, Lina Shang, Shuping Mao, Peng Wang   +5 more
doaj   +1 more source

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

Crater Observing Bioinspired Rolling Articulator (COBRA)

Advanced Intelligent Systems, EarlyView.
Crater Observing Bio‐inspired Rolling Articulator (COBRA) is a modular, snake‐inspired robot that addresses the mobility challenges of extraterrestrial exploration sites such as Shackleton Crater. Incorporating snake‐like gaits and tumbling locomotion, COBRA navigates both uneven surfaces and steep crater walls.
Adarsh Salagame, Henry Noyes, Eric Sihite, Arash Kalantari, Alireza Ramezani   +4 more
wiley   +1 more source

Safe Compilation for Hidden Deterministic Hardware Aliasing and Encrypted Computing

, 2019
16 pages, early version of submission prepared for Ada-Europe ...
openaire   +2 more sources