Results 41 to 50 of about 1,612,060 (336)
Management Policy for Greater Computer Benefits: Friendly Software, Computer Literacy, or Formal Training [PDF]
, 1994 Using data from over 3,000 public employees in 46 U.S. cities in 1988, this article in vestigates three classes of factors commonly thought to affect computer use: training, friendliness of software, and user computer background. Computer use is analyzed
Dunkle, Debora E +3 more
core +2 more sources
, 2015 —Mental-Imagery based Brain-Computer Interfaces (MI-BCIs) allow their users to send commands to a computer using their brain activity alone (typically measured by ElectroEn-cephaloGraphy-EEG), which is processed while they perform specific mental tasks.
Camille Jeunet
openaire +5 more sources
Warta Pengabdian Andalas, 2021 Training of Computer network using Miktrotik at the Integrated Modern Islamic Boarding School of Dr. Muhammad Natsir at Alahan Panjang is one of the solutions to overcome the problem of the effectiveness and efficiency computer user.
Heru Dibyo Laksono +3 more
doaj +1 more source
Journal of Innovation in Health Informatics, 2002 Introduction Little is known about the confidence and competence of community nurses in using information and communications technology. This survey set out to explore this issue.
Kate Pritchard +2 more
doaj +1 more source
Analyzing P300 Distractors for Target Reconstruction
, 2018 P300-based brain-computer interfaces (BCIs) are often trained per-user and per-application space. Training such models requires ground truth knowledge of target and non-target stimulus categories during model training, which imparts bias into the model ...
Gordon, Stephen M. +3 more
core +1 more source
Human-Computer Interaction for BCI Games: Usability and User Experience [PDF]
, 2010 Brain-computer interfaces (BCI) come with a lot of issues, such as delays, bad recognition, long training times, and cumbersome hardware. Gamers are a large potential target group for this new interaction modality, but why would healthy subjects want to ...
Gürkök, Hayrettin +8 more
core +3 more sources
User Factor Adaptation for User Embedding via Multitask Learning [PDF]
arXiv, 2021 Language varies across users and their interested fields in social media data: words authored by a user across his/her interests may have different meanings (e.g., cool) or sentiments (e.g., fast). However, most of the existing methods to train user embeddings ignore the variations across user interests, such as product and movie categories (e.g ...
arxiv
GUIDER: a GUI for semiautomatic, physiologically driven EEG feature selection for a rehabilitation BCI [PDF]
, 2017 GUIDER is a graphical user interface developed in MATLAB software environment to identify electroencephalography (EEG)-based brain computer interface (BCI) control features for a rehabilitation application (i.e. post-stroke motor imagery training).
Cincotti, Febo +5 more
core +1 more source
Pre-training for low resource speech-to-intent applications [PDF]
arXiv, 2021 Designing a speech-to-intent (S2I) agent which maps the users' spoken commands to the agents' desired task actions can be challenging due to the diverse grammatical and lexical preference of different users. As a remedy, we discuss a user-taught S2I system in this paper.
arxiv
PrivFL: Practical Privacy-preserving Federated Regressions on High-dimensional Data over Mobile Networks [PDF]
, 2020 Federated Learning (FL) enables a large number of users to jointly learn a shared machine learning (ML) model, coordinated by a centralized server, where the data is distributed across multiple devices. This approach enables the server or users to train and learn an ML model using gradient descent, while keeping all the training data on users' devices.
arxiv +1 more source