Results 101 to 110 of about 462 (258)
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
A Practical View on Dynamic Symmetric Searchable Encryption
Die symmetrische Suche auf verschlüsselten Daten ermöglicht eine entfernte Suche auf verschlüsselten Dokumenten in der Cloud, wobei der Server keinen Zugriff auf den Klartext der Daten hat.
Kramer, Ines
core
A Critical Assessment of Bonding Descriptors for Predicting Materials Properties
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik +6 more
wiley +1 more source
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang +9 more
wiley +1 more source
Forward and Backward-Secure Range-Searchable Symmetric Encryption [PDF]
Dynamic searchable symmetric encryption (DSSE) allows a client to search or update over an outsourced encrypted database. Range query is commonly needed (AsiaCrypt\u2718) but order-preserving encryption approach is vulnerable to reconstruction attacks ...
Sherman S. M. Chow, Jiafan Wang
core
Optimizing 3D Bin Packing of Heterogeneous Objects Using Continuous Transformations in SE(3)
This article presents a method for solving the three‐dimensional bin packing problem for heterogeneous objects using continuous rigid‐body transformations in SE(3). A heuristic optimization framework combines signed‐distance functions, neural network approximations, point‐cloud bin modeling, and physics simulation to ensure feasibility and stability ...
Michele Angelini, Marco Carricato
wiley +1 more source
Oblivious Dynamic Searchable Encryption on Distributed Cloud Systems
Dynamic Searchable Symmetric Encryption (DSSE) allows search/update operations over encrypted data via an encrypted index. However, DSSE has been shown to be vulnerable to statistical inference attacks, which can extract a significant amount of ...
Durak, F. Betul +9 more
core +1 more source
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison +4 more
wiley +1 more source
Ising Solver Using Vertical NAND Flash Memory
Commercial V‐NAND flash memory is repurposed as a discrete‐time Ising solver by exploiting in‐memory current summation and read‐voltage‐controlled intrinsic noise. The system implements Hopfield neural‐network updates with simulated‐annealing‐like behavior, solving max‐cut problems with high accuracy and energy efficiency while using mass‐produced ...
Sung‐Ho Park +7 more
wiley +1 more source

