18,718 research outputs found
Augmented reality usage for prototyping speed up
The first part of the article describes our approach for solution of this
problem by means of Augmented Reality. The merging of the real world model and
digital objects allows streamline the work with the model and speed up the
whole production phase significantly. The main advantage of augmented reality
is the possibility of direct manipulation with the scene using a portable
digital camera. Also adding digital objects into the scene could be done using
identification markers placed on the surface of the model. Therefore it is not
necessary to work with special input devices and lose the contact with the real
world model. Adjustments are done directly on the model. The key problem of
outlined solution is the ability of identification of an object within the
camera picture and its replacement with the digital object. The second part of
the article is focused especially on the identification of exact position and
orientation of the marker within the picture. The identification marker is
generalized into the triple of points which represents a general plane in
space. There is discussed the space identification of these points and the
description of representation of their position and orientation be means of
transformation matrix. This matrix is used for rendering of the graphical
objects (e. g. in OpenGL and Direct3D).Comment: Keywords: augmented reality, prototyping, pose estimation,
transformation matri
A schema for generic process tomography sensors
A schema is introduced that aims to facilitate the widespread exploitation of the science of process tomography (PT) that promises a unique multidimensional sensing opportunity. Although PT has been developed to an advanced state, applications have been laboratory or pilot-plant based, configured on an end-to-end basis, and limited typically to the formation of images that attempt to represent process contents. The schema facilitates the fusion of multidimensional internal process state data in terms of a model that yields directly usable process information, either for design model confirmation or for effective plant monitoring or control, here termed a reality visualization model (RVM). A generic view leads to a taxonomy of process types and their respective RVM. An illustrative example is included and a review of typical sensor system components is given
Applying advanced machine learning models to classify electro-physiological activity of human brain for use in biometric identification
In this article we present the results of our research related to the study
of correlations between specific visual stimulation and the elicited brain's
electro-physiological response collected by EEG sensors from a group of
participants. We will look at how the various characteristics of visual
stimulation affect the measured electro-physiological response of the brain and
describe the optimal parameters found that elicit a steady-state visually
evoked potential (SSVEP) in certain parts of the cerebral cortex where it can
be reliably perceived by the electrode of the EEG device. After that, we
continue with a description of the advanced machine learning pipeline model
that can perform confident classification of the collected EEG data in order to
(a) reliably distinguish signal from noise (about 85% validation score) and (b)
reliably distinguish between EEG records collected from different human
participants (about 80% validation score). Finally, we demonstrate that the
proposed method works reliably even with an inexpensive (less than $100)
consumer-grade EEG sensing device and with participants who do not have
previous experience with EEG technology (EEG illiterate). All this in
combination opens up broad prospects for the development of new types of
consumer devices, [e.g.] based on virtual reality helmets or augmented reality
glasses where EEG sensor can be easily integrated. The proposed method can be
used to improve an online user experience by providing [e.g.] password-less
user identification for VR / AR applications. It can also find a more advanced
application in intensive care units where collected EEG data can be used to
classify the level of conscious awareness of patients during anesthesia or to
automatically detect hardware failures by classifying the input signal as
noise
Exploration of Reaction Pathways and Chemical Transformation Networks
For the investigation of chemical reaction networks, the identification of
all relevant intermediates and elementary reactions is mandatory. Many
algorithmic approaches exist that perform explorations efficiently and
automatedly. These approaches differ in their application range, the level of
completeness of the exploration, as well as the amount of heuristics and human
intervention required. Here, we describe and compare the different approaches
based on these criteria. Future directions leveraging the strengths of chemical
heuristics, human interaction, and physical rigor are discussed.Comment: 48 pages, 4 figure
- …