Results 41 to 50 of about 686,580 (270)
Advanced Engineering Materials, EarlyView.A multimaterial approach is introduced to improve upon auxetic structures by combining two different polymers into the same reentrant honeycomb structure via additive manufacturing. The deformation behavior as well as the resulting Poisson's ratio are thereby improved significantly.
Alexander Engel +2 more
wiley +1 more source
GENESIM : genetic extraction of a single, interpretable model [PDF]
, 2016 Models obtained by decision tree induction techniques excel in being interpretable.However, they can be prone to overfitting, which results in a low predictive performance. Ensemble techniques are able to achieve a higher accuracy. However, this comes at
De Turck, Filip +4 more
core +2 more sources
Active Learning Embedded in Incremental Decision Trees
, 2020 As technology evolves and electronic devices become widespread, the amount of data produced in the form of stream increases in enormous proportions. Data streams are an online source of data, meaning that it keeps producing data continuously. This creates the need for fast and reliable methods to analyse and extract information from these sources ...
Vinicius Eiji Martins +2 more
openaire +2 more sources
Advanced Engineering Materials, EarlyView.The utilization of direct energy deposition (DED)‐arc additive manufacturing processes in industrial applications is increasing, and these processes have the potential for multi‐material applications. This work provides a overview of the state of research in DED‐arc made functional graded structures, to establish a link to potential industrial ...
Kai Treutler, Volker Wesling
wiley +1 more source
A Bayesian Approach to Optimizing Stem Cell Cryopreservation protocols
, 2014 Cryopreservation is beset with the challenge of protocol alignment across a wide range of cell types and process variables. By taking a cross-sectional assessment of previously published cryopreservation data (sample means and standard errors) as ...
Sambu, S
core +1 more source
Learning Binary Decision Trees by Argmin Differentiation
, 2020 We address the problem of learning binary decision trees that partition data for some downstream task. We propose to learn discrete parameters (i.e., for tree traversals and node pruning) and continuous parameters (i.e., for tree split functions and prediction functions) simultaneously using argmin differentiation. We do so by sparsely relaxing a mixed-
Zantedeschi, Valentina +2 more
openaire +2 more sources
Carbon Nanotube 3D Integrated Circuits: From Design to Applications
Advanced Functional Materials, EarlyView.As Moore's law approaches its physical limits, carbon nanotube (CNT) 3D integrated circuits (ICs) emerge as a promising alternative due to the miniaturization, high mobility, and low power consumption. CNT 3D ICs in optoelectronics, memory, and monolithic ICs are reviewed while addressing challenges in fabrication, design, and integration.
Han‐Yang Liu +3 more
wiley +1 more source
Advanced Functional Materials, EarlyView.Geometric multi‐bit patterning based on dynamic wetting and dewetting phenomena creates roulette‐like Physical Unclonable Function (PUF) labels with stochastic yet deterministic properties. This method leverages the solutal‐Marangoni effect for high randomness while achieving deterministic multinary patterns through polygonal confinement of binary ...
Yeongin Cho +8 more
wiley +1 more source
Advanced Functional Materials, EarlyView.Symmetry‐broken plasmonic nanoantenna arrays achieve broadband multiresonant enhancement of second harmonic generation (SHG), third harmonic generation (THG), and upconversion photoluminescence (UCPL), under femtosecond laser excitation across the near‐infrared range (1000–1600 nm).
Elieser Mejia +9 more
wiley +1 more source
Learning Decision Trees for Unbalanced Data [PDF]
, 2008 Learning from unbalanced datasets presents a convoluted problem in which traditional learning algorithms may perform poorly. The objective functions used for learning the classifiers typically tend to favor the larger, less important classes in such problems.
David A. Cieslak, Nitesh V. Chawla
openaire +2 more sources