Results 51 to 60 of about 14,997,530 (270)

Human‐Guided Bayesian Optimization Enables High‐Throughput Laser Annealing of Mesoporous SiOx Anodes for Lithium‐Ion Batteries

Advanced Science, EarlyView.
An empirical‐aided active learning framework is developed to optimize high‐throughput laser‐induced photothermal annealing of silicon suboxide anodes. By integrating probabilistic machine learning with empirical domain knowledge, this approach achieves optimal electrochemical performance using limited experiments.
Chaeyoung Park, Yeongje Lee, Sunho Jeong, Eungkyu Lee   +3 more
wiley   +1 more source

A Private Quantum Bit String Commitment

Entropy, 2020
We propose an entanglement-based quantum bit string commitment protocol whose composability is proven in the random oracle model. This protocol has the additional property of preserving the privacy of the committed message.
Mariana Gama, Paulo Mateus, André Souto
doaj   +1 more source

Short Signatures in the Random Oracle Model [PDF]

, 2002
We study how digital signature schemes can generate signatures as short as possible, in particular in the case where partial message recovery is allowed. We give a concrete proposition named OPSSR that achieves the lower bound for message expansion, and give an exact security proof of the scheme in the ideal cipher model.
openaire   +2 more sources

Weakened Random Oracle Models with Target Prefix [PDF]

, 2019
Weakened random oracle models (WROMs) are variants of the random oracle model (ROM). The WROMs have the random oracle and the additional oracle which breaks some property of a hash function. Analyzing the security of cryptographic schemes in WROMs, we can specify the property of a hash function on which the security of cryptographic schemes depends ...
Masayuki Tezuka, Yusuke Yoshida, Keisuke Tanaka   +2 more
openaire   +4 more sources

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Universally Composable Oblivious Transfer with Low Communication

Applied Sciences, 2023
In this paper, a universally composable 1-out-of-N oblivious transfer protocol with low communication is built. This protocol obtained full simulation security based on the modulo learning with rounding (Mod-LWR) assumption.
Jiashuo Song, Dongfei Wang, Zhenzhen Zhang, Zhenzhen Li, Haiyang Ding, Zichen Li   +5 more
doaj   +1 more source

Value of Information of Improved Traceability in Fresh Produce Markets

Agribusiness, EarlyView.
ABSTRACT Traceability plays an important role in promoting a safe food supply by fostering transparent information exchange along the food supply chain. New technological innovations have the potential to improve traceability outcomes, as greater transparency along the food supply chain can aid in pinpointing precise origins of the contamination ...
Kelsey Vourazeris, Mark R. Manfredo, Michael N. Kozicki   +2 more
wiley   +1 more source

Security of signed ELGamal encryption [PDF]

, 2005
Assuming a cryptographically strong cyclic group G of prime order q and a random hash function H, we show that ElGamal encryption with an added Schnorr signature is secure against the adaptive chosen ciphertext attack, in which an attacker can freely use
Jakobsson, Markus, Schnorr, Claus Peter
core  

MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design

Advanced Intelligent Discovery, EarlyView.
MolMiner is a fragment‐based, geometry‐aware, and order‐agnostic generative model for molecular design with strong inductive biases. Using symmetry‐aware fragment assembly, dynamic three‐dimensional geometry, and multi‐property conditioning, MolMiner enables interpretable and controllable molecular generation.
Raul Ortega‐Ochoa, Tejs Vegge, Jes Frellsen   +2 more
wiley   +1 more source

Interpretable Short‐Term Electric Load Forecasting

Advanced Intelligent Systems, EarlyView.
A temporal fusion transformer is implemented to generate day‐ahead forecasts of the hourly electrical load of a departmentbuilding at an Italian university. A forecasting performance improvement of more than 25% compared with established benchmark models and a provision of inherent robust interpretability insights reveal the potential of this model for
Alessandro Nicola, Giorgia Ghione, Vincenzo Randazzo, Vincenzo Franzitta, Marco Badami, Eros Pasero, Giansalvo Cirrincione   +6 more
wiley   +1 more source