Results 51 to 60 of about 170,367 (287)
Advanced Optical Materials, EarlyView.Combining high‐order cluster‐correlation expansion with experiment, it is revealed that P1‐driven NV decoherence under dynamical decoupling deviates from semi‐classical scaling laws. The coherence‐time exponent depends on pulse number and bath conditions, demonstrating the necessity of a full quantum bath description.
Huijin Park +8 more
wiley +1 more source
Asymmetric Deep Supervised Hashing
, 2017 Hashing has been widely used for large-scale approximate nearest neighbor search because of its storage and search efficiency. Recent work has found that deep supervised hashing can significantly outperform non-deep supervised hashing in many ...
Jiang, Qing-Yuan, Li, Wu-Jun
core +1 more source
Advanced Science, EarlyView.Time‐restricted feeding (TRF) exerts protein‐dependent neuroprotective effects in an MPTP‐induced Parkinson's disease model. In casein‐fed mice, TRF improves gut barrier integrity and reduces neuroinflammation, possibly via modulation of Allobaculum and BCAAs.
Ting Li +12 more
wiley +1 more source
One-way hash function with chaotic dynamic parameters
Tongxin xuebao, 2008 A novel keyed one-way hash function based on chaotic dynamic parameters was presented which combines the advantage of both chaotic system and conventional one-way hash function.In the proposed approach the fixed parameters of conventional hash function ...
GUO Wei1 +3 more
doaj +2 more sources
Merkle-Damgård Construction Method and Alternatives: A Review
Journal of Information and Organizational Sciences, 2017 Cryptographic hash function is an important cryptographic tool in the field of information security. Design of most widely used hash functions such as MD5 and SHA-1 is based on the iterations of compression function by Merkle-Damgård construction method ...
Harshvardhan Tiwari
doaj +1 more source
Unsupervised Triplet Hashing for Fast Image Retrieval
, 2017 Hashing has played a pivotal role in large-scale image retrieval. With the development of Convolutional Neural Network (CNN), hashing learning has shown great promise.
Huang, Shanshan +3 more
core +1 more source
Machine Learning for Green Solvents: Assessment, Selection and Substitution
Advanced Science, EarlyView.Environmental regulations have intensified demand for green solvents, but discovery is limited by Solvent Selection Guides (SSGs) that quantify solvent sustainability. Training a machine learning model on GlaxoSmithKline SSG, a database of sustainability metrics for 10,189 solvents, GreenSolventDB is developed. Integrated with Hansen solubility metrics,
Rohan Datta +4 more
wiley +1 more source
An Adaptive and Asymmetric Residual Hash for Fast Image Retrieval
IEEE Access, 2019 Hashing algorithm has attracted great attention in recent years. In order to improve the query speed and retrieval accuracy, this paper proposes an adaptive and asymmetric residual hash (AASH) algorithm based on residual hash, integrated learning, and ...
Shuli Cheng, Liejun Wang, Anyu Du
doaj +1 more source
Design and Application of Deep Hash Embedding Algorithm with Fusion Entity Attribute Information
Entropy, 2023 Hash is one of the most widely used methods for computing efficiency and storage efficiency. With the development of deep learning, the deep hash method shows more advantages than traditional methods. This paper proposes a method to convert entities with
Xiaoli Huang, Haibo Chen, Zheng Zhang
doaj +1 more source
Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI
Advanced Science, EarlyView.ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia +7 more
wiley +1 more source