Results 261 to 270 of about 56,042 (290)

Evaluating students’ learning gains, strategies, and errors using OrgChem101's module: organic mechanisms—mastering the arrows

Chemistry Education Research and Practice, 2020
We developed an online learning module called “Organic Mechanisms: Mastering the Arrows” to help students learn part of organic chemistry's language—the electron-pushing formalism. The module guides students to learn and practice the electron-pushing formalism using a combination of interactive videos, questions with instant feedback, and metacognitive
Myriam S Carle, Alison B Flynn
exaly   +2 more sources

On the concrete hardness of Learning with Errors [PDF]

Journal of Mathematical Cryptology, 2015
The learning with errors (LWE) problem has become a central building block of modern cryptographic constructions. This work collects and presents hardness results for concrete instances of LWE.
Rachel PLAYER
exaly   +2 more sources

Online learning applied to error modulated state setting control

2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2012
For systems with variable gain, proportional plus integral controllers need to be tuned in the highest gain state of the system. This can lead to sluggish response when the system is in a low gain state. Previous research has shown that error modulated state setting control can be used to improve the transient response of variable gain systems ...
openaire   +1 more source

A Gaussian Sampler for Ring-Learning-With-Errors Scheme Reusing a Cryptographic Module

Advanced Science and Technology Letters, 2015
Since the different characteristics from the PRNG (Pseudo Random Number Generator) or various deterministic devices such as arithmetic processing units, new concepts and test methods should be suggested in order to test TRNG (Ture Random Number Generator).
openaire   +1 more source

Priors in perception: Top-down modulation, Bayesian perceptual learning rate, and prediction error minimization

Consciousness and Cognition, 2017
I discuss top-down modulation of perception in terms of a variable Bayesian learning rate, revealing a wide range of prior hierarchical expectations that can modulate perception. I then switch to the prediction error minimization framework and seek to conceive cognitive penetration specifically as prediction error minimization deviations from a ...
openaire   +2 more sources

Personalized Machine Learning Algorithm based on Shallow Network and Error Imputation Module for an Improved Blood Glucose Prediction. [PDF]

, 2020
Real-time forecasting of blood glucose (BG) levels has the potential to drastically improve management of Type 1 Diabetes, a widespread chronic disease affecting the metabolic system. Most notably, if hypo or hyperglycemia episodes (i.e. glycemic excursion below or above a safe range) could be accurately predicted, then the patient could be timely ...
Pavan J., Prendin F., Meneghetti L., Cappon G., Sparacino G., Facchinetti A., Del Favero S.   +6 more
openaire   +1 more source

DEC-aided SM-OFDM: A Spatial Modulation System with Deep Learning based Error Correction

Proceedings of the Second International Conference on AI-ML Systems, 2022
Harsh Verma, Vivek Ashok Bohara, Anubha Gupta   +2 more
openaire   +1 more source

On the Hardness of Module-LWE with Binary Secret

Lecture Notes in Computer Science, 2021
Katharina Boudgoust, Adeline Roux-Langlois, Boudgoust Katharina   +2 more
exaly  

Entropic Hardness of Module-LWE from Module-NTRU

Lecture Notes in Computer Science, 2023
Katharina Boudgoust, Adeline Roux-Langlois, Boudgoust Katharina   +2 more
exaly  

Cocaine Use Modulates Neural Prediction Error During Aversive Learning

2017
Master of ...
openaire   +1 more source