Results 81 to 90 of about 3,160,703 (293)

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

open access: yesAdvanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer   +4 more
wiley   +1 more source

Efficient and Provable Security Searchable Asymmetric Encryption in the Cloud

open access: yesIEEE Access, 2018
Cloud and remote storage, which has become the preferred method for reducing the security risk and safeguarding our data, is widely used for backups or outsourcing.
Jianyi Zhang   +4 more
doaj   +1 more source

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani   +7 more
wiley   +1 more source

Registered Keyword Searchable Encryption Based on SM9

open access: yes, 2023
The SM9 algorithm is an Identity-Based Encryption (IBE) algorithm independently made by China. The existing SM9 searchable encryption scheme cannot be effective against insider keyword guessing attacks and violates users’ data privacy. This article
Baodong Qin, Dong Zheng, Haoyu Zhang
core   +1 more source

Toward Full Interoperability in Materials Science: Integrating Workflows With Knowledge Graphs

open access: yesAdvanced Engineering Materials, EarlyView.
The connection of conceptual workflow design, portable execution, and ontology‐based semantics leading to provenance‐rich knowledge graphs are main contributors to interoperability in materials science and a prerequisite to AI‐assisted orchestration and for interoperable Materials Acceleration Platforms.
Jan Janssen   +14 more
wiley   +1 more source

Achieving Semantic Secure Search in Cloud Supported Information-Centric Internet of Things

open access: yesIEEE Access, 2019
With the support of cloud computing, the scalability of the information-centric Internet of Things (IC-IoT) can be increased greatly. In the cloud-supported IC-IoT, how to make search more secure and efficient is a key issue to deal with.
Zhitao Guan   +5 more
doaj   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

open access: yesAdvanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin   +14 more
wiley   +1 more source

Bioinspired Co‐Assembly Enables Multiscale Architected Hydrogels for 3D Printing With Integrated Antibacterial and Bioactive Functions

open access: yesAdvanced Functional Materials, EarlyView.
A multicomponent supramolecular hydrogel integrating cell‐adhesive and antibacterial peptides within an alginate‐cellulose nanofibril matrix is developed. Peptide co‐assembly simultaneously strengthens the hydrogel network, improves extrusion printability, and imparts cell‐adhesive and antibacterial functions, offering a versatile platform for ...
Mor Tsuriano‐Zernichov   +4 more
wiley   +1 more source

Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery

open access: yesAdvanced Functional Materials, EarlyView.
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang   +3 more
wiley   +1 more source

Verifiable multi-keyword search scheme based on improved Merkle-Tree authentication method

open access: yesTongxin xuebao, 2020
Aiming at the problem that the result verification method in the searchable encryption scheme was complicated,the search cost was high and the efficiency was low,it was difficult to meet the requirements of efficient verification and security of multi ...
Youliang TIAN, Qin LUO
doaj   +2 more sources

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