Results 121 to 130 of about 173,300 (211)

The Consistency of Fairness Rules: An Experimental Study [PDF]

open access: yes
In the last two decades, experimental papers on distributive justice have abounded. Two main results have been replicated Firstly, there is a multiplicity of fairness rules. Secondly, fairness decisions differ depending on the context. This paper studies
Paloma Ubeda
core  

AS-672-08 Resolution on Revisions to Fairness Board Description and Procedures [PDF]

open access: yes, 2008
Changes made to the Fairness Board Description and Procedures noting reporting changes made in cases of cheating and ...
Fairness Board Committee,
core  

Solid Harmonic Wavelet Bispectrum for Image Analysis

open access: yesAdvanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown   +3 more
wiley   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

open access: yesAdvanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju   +5 more
wiley   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

open access: yesAdvanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan   +8 more
wiley   +1 more source

Fairness, Adverse Selection, and Employment Contracts [PDF]

open access: yes
This paper considers a firm whose potential employees have private information on both their productivity and the extent of their fairness concerns. Fairness is modelled as inequity aversion, where fair-minded workers suffer if their colleagues get more ...
Siemens, Ferdinand von
core   +2 more sources

Theories of Fairness and Reciprocity – Evidence and Economic Applications [PDF]

open access: yes
Most economic models are based on the self-interest hypothesis that assumes that all people are exclusively motivated by their material self-interest. In recent years experimental economists have gathered overwhelming evidence that systematically refutes
Klaus Schmidt, Ernst Fehr
core  

AS-684-09 Resolution on Revision to Fairness Board Description and Procedures [PDF]

open access: yes, 2009
Adds phrasing to Fairness Board Description and Procedures, A.9.E: In the event the student grievant fails to appear at the scheduled hearing, the Board may dismiss the case.
Fairness Board Committee,
core  

Overcoming Artificial Structures in Resolution‐Enhanced Hi‐C Data by Signal Decomposition and Multi‐Scale Attention

open access: yesAdvanced Science, EarlyView.
Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li   +6 more
wiley   +1 more source

Do Fairness Opinion Valuations Contain Useful Information? [PDF]

open access: yes
We analyze target firm valuations disclosed in the fairness opinions of negotiated mergers between 1998 and 2005. On average, acquirer advisors exhibit a greater degree of valuation optimism than do target advisors.
Matthew D. Cain, David J. Denis
core  

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