Results 51 to 60 of about 2,368,406 (271)

No Fuss Distance Metric Learning using Proxies

open access: yes, 2017
We address the problem of distance metric learning (DML), defined as learning a distance consistent with a notion of semantic similarity. Traditionally, for this problem supervision is expressed in the form of sets of points that follow an ordinal ...
Ioffe, Sergey   +4 more
core   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

open access: yesAdvanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt   +8 more
wiley   +1 more source

Dispositional Styles in Original Tales of Adolescents with Cancer and Rheumatic Diseases [PDF]

open access: yesКлиническая и специальная психология, 2019
The article presents the results of a study of dispositional styles, which are reflected in the content of the original fairy tales of adolescents with oncological (n=40) and rheumatic (n=50) diseases.
Odintsova M.A.   +3 more
doaj   +1 more source

Harnessing the creativity of digital multimedia tools in distance learning [PDF]

open access: yes, 2012
Over the past few decades, advances in information and communication technologies, and particularly the digitisation of information, have brought about radical changes in the way media can be produced, distributed and shared. The exchange of information,
Kouadri Mostéfaoui, Soraya   +1 more
core  

What Do Large Language Models Know About Materials?

open access: yesAdvanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer   +2 more
wiley   +1 more source

FEATURES OF EXPERIENCING A SPIRITUAL CRISIS AND ATTITUDES TO SELF IN PERSONS WITH SPINAL INJURY

open access: yesКонсультативная психология и психотерапия, 2020
The article presents the results of the study of the specifics of spiritual crisis experience and attitudes to Self in persons with spinal injury (N=65) and conventionally healthy respondents (N=63).
Igor V. Vachkov   +2 more
doaj   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

open access: yesAdvanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice   +2 more
wiley   +1 more source

Distance Learning

open access: yes
The article discusses innovative approaches to education on the example of the introduction of distance learning in Russia, the main forms of its organization, the necessary means, areas of application, advantages, and disadvantages. The authors note that distance learning is becoming more in demand, has many advantages, and therefore, will develop ...
Bogdan Anatolievich Ershov   +1 more
  +4 more sources

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

open access: yesAdvanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky   +5 more
wiley   +1 more source

Tree Edit Distance Learning via Adaptive Symbol Embeddings

open access: yes, 2018
Metric learning has the aim to improve classification accuracy by learning a distance measure which brings data points from the same class closer together and pushes data points from different classes further apart.
Gallicchio, Claudio   +3 more
core  

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