Results 101 to 110 of about 9,625,516 (256)

A hierarchical approach to multi-project planning under uncertainty. [PDF]

We survey several viewpoints on the management of the planning complexity of multi-project organisations under uncertainty. A positioning framework is proposed to distinguish between different types of project-driven organisations, which is meant to aid ...
Wullink, G, Hans, EW, Herroelen, Willy, Leus, Roel   +3 more
core  

Latent diffusion models for event history analysis [PDF]

, 2007
We consider Bayesian hierarchical models for event history analysis, where the event times are modeled through an underlying diffusion process, which determines the hazard rate. We show how these models can be e±ciently treated by means of Markov chain
Roberts, Gareth O., Sangalli, Laura M.
core  

Learning Hierarchical Multi-Category Text Classification Models

, 2005
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time.
Szedmak, S., Craig Saunders, Shawe-Taylor, J., Sandor Szedmak, Rousu, J., Saunders, C., Juho Rousu, John Shawe-Taylor   +7 more
core   +2 more sources

Analysis of event-related potential difference waves can benefit from linear mixed effects modeling: Recommendations for analyses and general model fitting

Developmental Cognitive Neuroscience
Linear mixed effects models (LMEs) have advantages for analyzing mean amplitude event-related potential (ERP) data. Compared to ANOVA and linear regression, LMEs retain more subjects and yield unbiased parameter estimates by accounting for trial-level ...
Megan J. Heise, Serena K. Mon, Lindsay C. Bowman   +2 more
doaj   +1 more source

Flexural Behavior of 3D‐Printed Porous Bouligand‐Structured Polymers: Influence of Pitch Angle and Porosity

Advanced Engineering Materials, EarlyView.
This study examines how helicoidal architectures with different porosities respond to bending. Adjusting layer angle and spacing in 3D‐printed polymers reveals clear tradeoffs between stiffness, strength, and energy absorption. Experiments and simulations highlight designs that distribute stress effectively, offering pathways for optimizing lightweight
Praveenkumar Subhash Patil, Edward D. McCarthy, Parvez Alam   +2 more
wiley   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Hierarchical and Non-Hierarchical Linear and Non-Linear Clustering Methods to aoShakespeare-De Vere Authorship Question [PDF]

, 2016
In my previous article entitled Hierarchical and Non- Hierarchical Linear and Non-Linear Clustering Methods to Shakespeare Authorship Question I used Mean Proximity as a linear hierarchical clustering method and Principal Components Analysis ...
Refat Aljumily
core  

Why Use Hierarchical Linear Models?

Sociologický Časopis, 2006
Petr Soukup
doaj   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source