Results 71 to 80 of about 550,497 (328)
Performance Impact of Optimization Methods on MySQL Document-Based and Relational Databases
Databases are an important part of today’s applications where large amounts of data need to be stored, processed, and accessed quickly. One of the important criteria when choosing to use a database technology is its data processing performance.
Cornelia A. Győrödi +5 more
doaj +1 more source
Towards an Efficient Evaluation of General Queries [PDF]
Database applications often require to evaluate queries containing quantifiers or disjunctions, e.g., for handling general integrity constraints. Existing efficient methods for processing quantifiers depart from the relational model as they rely on ...
Bry, François, Clifford, James
core +1 more source
This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley +1 more source
Graphical Notation for Document Database Modeling
Goals and objectives. Graphical models have proven to be a reliable, clear and convenient tool for creating sketch models of databases. Most of the existing notations are designed for the relational data model, the dominant data model for the last thirty
M. V. Smirnov, R. S. Tolmasov
doaj +1 more source
ABSTRACT Innovation is essential for competitiveness in agribusiness facing dynamic environments. This study examines how market orientation, marketing, relational, and social capabilities influence innovation performance. Using data from 751 Spanish firms and a multi‐method approach that integrates Structural Equation Modeling (PLS‐SEM), Necessary ...
Beatriz Corchuelo Martínez‐Azúa +1 more
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Preventing Additive Attacks to Relational Database Watermarking
False ownership claims are carried on through additive and invertibility attacks and, as far as we know, current relational watermarking techniques are not always able to solve the ownership doubts raising from the latter attacks. In this paper, we focus
M. L. P. Gort +3 more
semanticscholar +1 more source
The Interoperability Challenge in DFT Workflows Across Implementations
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen +13 more
wiley +1 more source
Toward building RDB to HBase conversion rules
Cloud data stores that can handle very large amounts of data, such as Apache HBase, have accelerated the use of non-relational databases (coined as NoSQL databases) as a way of addressing RDB database limitations with regards to scalability and ...
R. Ouanouki +4 more
doaj +1 more source
Design and Implementation of Relation Database and Non-Relation Database Unified Query Model
For scenarios that application data stored separately in relational database and non-relational database, an establishment of a unified query abstraction layer for SQL and NoSQL database is proposed, which can query data from different database as from a single data source.
Naizheng Bian, Xiaoyu Zheng
openaire +1 more source

