Results 91 to 100 of about 3,318,937 (295)

Graph-based pattern identification from architecture change logs [PDF]

, 2012
Service-based architectures have become commonplace, creating the need to address their systematic maintenance and evolution. We investigate architecture change representation, primarily focusing on the identification of change patterns that support the ...
Pooyan Jamshidi (5276344), Pooyan Jamshidi, Ahmad, Aakash, Aakash Ahmad, Claus Pahl, Claus Pahl (12588787), Pahl, Claus, Jamshidi, Pooyan, Aakash Ahmad (5022314)   +8 more
core   +2 more sources

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Service Solution Planning Considering Priori Knowledge and Fast Retrieval

IEEE Access, 2018
Service composition is widely used to build complex value-added composite services to meet various coarse-grained requirements of customers. Discovering relevant services as the constituents of composite services is a crucial task, which needs to be ...
Ruilin Liu, Xiaofei Xu, Zhongjie Wang, Quan Z. Sheng   +3 more
doaj   +1 more source

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

Advanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam, William S. Rogers, Chen‐Yu Hu, Ming‐Yuan Song, Xinyu Bao, Shehrin Sayed, Jean Anne C. Incorvia   +6 more
wiley   +1 more source

Generalized Net of the Process of Sequential Pattern Mining by Generalized Sequential Pattern Algorithm (GSP)

, 2014
In the present paper is constructed a Generalized net model of a process of sequential pattern mining by a generalized sequential pattern algorithm. Sequence pattern mining is a technique used for predictive data mining.
Bureva, V., Evdokia Sotirova, Veselina Bureva, Panagiotis Chountas, Sotirova, E., Chountas, P.   +5 more
core   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Data‐Driven Materials Science for Energy‐Sustainable Applications

Advanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley   +1 more source

arules - A Computational Environment for Mining Association Rules and Frequent Item Sets [PDF]

Mining frequent itemsets and association rules is a popular and well researched approach for discovering interesting relationships between variables in large databases.
Bettina Grün, Kurt Hornik, Michael Hahsler   +2 more
core  

Towards fast and memory efficient discovery of periodic frequent patterns

Journal of Information and Telecommunication, 2019
Periodic frequent pattern (PFP) mining, the process of discovering frequent patterns that occur at regular periods in databases, is an important data mining task for various decision-making.
Vincent Mwintieru Nofong, John Wondoh
doaj   +1 more source

Frequent Pattern Mining on Time and Location Aware Air Quality Data

IEEE Access, 2019
With the advent of big data era, enormous volumes of data are generated every second. Varied data processing algorithms and architectures have been proposed in the past to achieve better execution of data mining algorithms.
Apeksha Aggarwal, Durga Toshniwal
doaj   +1 more source