Results 81 to 90 of about 748,201 (294)
Advanced Functional Materials, EarlyView.A sequence‐encoded supramolecular construct containing two accessible toeholds is developed herein for enabling multiple editing operations. By introducing specific input strands, it is possible to selectively erase or rewrite digital content through parallel or series toehold‐mediated strand displacement (PTMSD or STMSD).
Jakub Ossowski +3 more
wiley +1 more source
Semi-supervised feature selection via fuzzy C-means clustering and simulated annealing optimization
Journal of King Saud University: Computer and Information SciencesFeature selection is a critical step in machine learning, as it helps minimize redundant features, thereby enhancing model performance and interpretability. In practice, partially labeled datasets are common.
Hongwu Qin +3 more
doaj +1 more source
Connecting Theater and Virtual Reality with Cognitive Sciences: Positioning from computer science and artist meeting [PDF]
, 2010 International audienceThis positioning paper presents arguments in favor of collaboration between artists and computer scientists in touch with cognitive science.
Cabioch, Vincent +3 more
core +2 more sources
Photoswitching Conduction in Framework Materials
Advanced Functional Materials, EarlyView.This mini‐review summarizes recent advances in state‐of‐the‐art proton and electron conduction in framework materials that can be remotely and reversibly switched on and off by light. It discusses the various photoswitching conduction mechanisms and the strategies employed to enhance photoswitched conductivity.
Helmy Pacheco Hernandez +4 more
wiley +1 more source
Super Virus Machines: Faster Virus Transmission, More Efficiency Using Superchannels
Intelligent ComputingSurpassing the classical computing architecture is one of the great challenges of computer science today. The branch that approaches it from a theoretical point of view, inspired by nature, is called natural computation.
Antonio Ramírez-de-Arellano-Marrero +3 more
doaj +1 more source
What is Computational Intelligence and where is it going? [PDF]
, 2007 What is Computational Intelligence (CI) and what are its relations with Artificial Intelligence (AI)? A brief survey of the scope of CI journals and books with ``computational intelligence'' in their title shows that at present it is an umbrella for ...
Duch, Wlodzislaw
core
Advanced Functional Materials, EarlyView.Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz +3 more
wiley +1 more source
Usage costs, interconnection, and regulation: remarks from Bill Lehr [PDF]
, 2013 William Lehr, Research Associate in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the MIT provides a summary of points made during his participation in the Interconnection Workshop hosted by the LSE Network Economy Forum on 11 ...
Lehr, William
core
MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance
Advanced Functional Materials, EarlyView.Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source