Results 101 to 110 of about 892 (280)

A Bloom filter-based dynamic symmetric searchable encryption scheme over cloud data

Cybersecurity
In this paper, a searchable encryption scheme for cloud data is proposed to address the limitations of existing schemes, which suffer from inefficient index construction and search process, as well as a lack of support for dynamic updates or the ...
Xing Zhang, Haozhe Wang, Junqing Lu, Tianning Li, Changda Wang   +4 more
doaj   +1 more source

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Advanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi, Yu Kumagai, Arata Takamatsu, Fumiyasu Oba   +3 more
wiley   +1 more source

Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates

Advanced Intelligent Discovery, EarlyView.
An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang, Abudukadi Tudi, Ran An, Zhihua Yang   +3 more
wiley   +1 more source

Exploiting Hidden Information Leakages in Backward Privacy for Dynamic Searchable Symmetric Encryption

Applied Sciences
Dynamic searchable symmetric encryption (DSSE) enables searches over encrypted data as well as data dynamics such as flexible data addition and deletion operations.
Hyundo Yoon, Muncheon Yu, Changhee Hahn, Dongyoung Koo, Junbeom Hur   +4 more
doaj   +1 more source

Searchable symmetric encryption

, 2020
The paper aims to study the various Searchable Symmetric Encryption (SSE) schemes available [1,2,3,4,5] to understand the feasibility and efficiency of the schemes in helping to keep our data secure, when a huge amount of data is stored in a third-party ...
Thio, Brian Yu Li
core  

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
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, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

Searchable Encryption Scheme for Large Data Sets in Cloud Storage Environment [PDF]

Radioengineering
Cloud storage has become essential in managing and retrieving extensive volumes of data, providing economical alternatives and adaptability for effective storage environment.
Y. Xiong, M. X. Luo
doaj  

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

Advanced Intelligent Discovery, EarlyView.
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, Nidal Dhamrait, Katharina Ueltzen, Christina Ertural, Philipp Benner, Gian‐Marco Rignanese, Janine George   +6 more
wiley   +1 more source

CSAKD: Determining Absolute Ligand Affinities From 19F NMR Chemical Shift Anisotropy

Angewandte Chemie, EarlyView.
Affinity determination is crucial in drug discovery, yet remains difficult for weakly binding fragments. We introduce chemical shift anisotropy KD$K_{\text{D}}$ (CSAKD) by 19F$^{19}{\rm F}$ NMR relaxation experiments, a titration‐free method that requires no isotopic labeling.
Simon H. Rüdisser, Gabriela Stadler, Alvar D. Gossert   +2 more
wiley   +2 more sources

Artificial Intelligence‐Driven Network Pharmacology: A Methodological Paradigm Shift Bridging Traditional Wisdom and Modern Science

Advanced Intelligent Discovery, EarlyView.
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, Sile Hu, Rigahai Ji, Riguna A, Siqige Hao, Ma Zhuo, Yi‐Hung Chen, Bisihalatu Hu, Ulana Bai, Xigui Hada   +9 more
wiley   +1 more source