Search results for "DOM"
showing 10 items of 12668 documents
Model-based Engineering for the Integration of Manufacturing Systems with Advanced Analytics
2016
To employ data analytics effectively and efficiently on manufacturing systems, engineers and data scientists need to collaborate closely to bring their domain knowledge together. In this paper, we introduce a domain-specific modeling approach to integrate a manufacturing system model with advanced analytics, in particular neural networks, to model predictions. Our approach combines a set of meta-models and transformation rules based on the domain knowledge of manufacturing engineers and data scientists. Our approach uses a model of a manufacturing process and its associated data as inputs, and generates a trained neural network model as an output to predict a quantity of interest. This pape…
A Comprehensive Survey of Indoor Localization Methods Based on Computer Vision
2020
Computer vision based indoor localization methods use either an infrastructure of static cameras to track mobile entities (e.g., people, robots) or cameras attached to the mobile entities. Methods in the first category employ object tracking, while the others map images from mobile cameras with images acquired during a configuration stage or extracted from 3D reconstructed models of the space. This paper offers an overview of the computer vision based indoor localization domain, presenting application areas, commercial tools, existing benchmarks, and other reviews. It provides a survey of indoor localization research solutions, proposing a new classification based on the configuration stage…
Design of a robust controller for DC/DC converter–electrolyzer systems supplied by μWECSs subject to highly fluctuating wind speed
2020
Abstract A buck-based, isolated, high-voltage-ratio DC/DC converter that allows supplying a proton exchange membrane (PEM) electrolyzer from a micro-wind energy conversion system ( μ WECS) has been recently presented. It exhibits low ripple at the switching frequency on the output voltage and current and represents an attractive solution for low-cost hydrogen production. In this paper, a more accurate mathematical model of such a converter is derived and discussed. Then, a model-based robust controller is designed in the frequency domain using the Internal Model Control structure and in the context of H 2 ∕ H ∞ optimal control. The controller satisfies the condition of robust stability and …
Interoperable real-time symbolic programming for smart environments
2019
Smart environments demand novel paradigms offering easy configuration, programming and deployment of pervasive applications. To this purpose, different solutions have been proposed ranging from visual paradigms based on mashups to formal languages. However, most of the paradigms proposed in the literature require further external tools to turn application description code into an executable program before the deployment on target devices. Source code generation, runtime upgrades and recovery, and online debugging and inspection are often cumbersome in these programming environments. In this work we describe a methodology for real-time and on-line programming in smart environments that is co…
Graph-theoretical derivation of brain structural connectivity
2020
Brain connectivity at the single neuron level can provide fundamental insights into how information is integrated and propagated within and between brain regions. However, it is almost impossible to adequately study this problem experimentally and, despite intense efforts in the field, no mathematical description has been obtained so far. Here, we present a mathematical framework based on a graph-theoretical approach that, starting from experimental data obtained from a few small subsets of neurons, can quantitatively explain and predict the corresponding full network properties. This model also changes the paradigm with which large-scale model networks can be built, from using probabilisti…
Identification of Objects Based on Generalized Amplitude-Phase Images Statistical Models
2017
The article presents the dynamical objects identification technology based on statistical models of amplitude-phase images (APIm) – multidimensional data arrays (semantic models) and statistical correlation analysis methods using the generalized discrete Hilbert transforms (DHT) – 2D Hilbert (Foucault) isotropic (HTI), anisotropic (HTA) and total transforms – AP-analysis (APA) to calculate the APIm. The identified objects are modeled with 3D airplanes templates rotated in space around the center of Cartesian coordinate system. The DHT domain system of coordinates displaying the plane projections (2D flat images) remains to be space-invariant. That causes the anisotropic properties of APIm a…
Abnormal Textures Identification Based on Digital Hilbert Optics Methods: Fundamental Transforms and Models
2017
The article presents the abnormal textures identification technology based on structural and statistical models of amplitude-phase images (APIm) – multidimensional data arrays (semantic models) and statistical correlation analysis methods using the generalized discrete Hilbert transforms (DHT) – 2D Hilbert (Foucault) isotropic (HTI), anisotropic (HTA) and total transforms – AP-analysis (APA) to calculate the APIm. The identified fragments of textures are obtained as examples of experimental observation of real mammograms contains areas of pathological tissues. The DHT based information technology as conceptual chart description is discussed and illustrated with DHO domain images. As additio…
Types of Mimetics for the Design of Intelligent Technologies
2019
Mimetic design means using a source in the natural or artificial worlds as an inspiration for technological solutions. It is based around the abstraction of the relevant operating principles in a source domain. This means that one must be able to identify the correct level of analysis and extract the relevant patterns. How this should be done is based on the type of source. From a mimetic perspective, if the design goal is intelligent technology, an obvious source of inspiration is human information processing, which we have called cognitive mimetics. This article offers some conceptual clarification on the nature of cognitive mimetics by contrasting it with biomimetics in the context of in…
Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?
2020
Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…
Using Inverse Reinforcement Learning with Real Trajectories to Get More Trustworthy Pedestrian Simulations
2020
Reinforcement learning is one of the most promising machine learning techniques to get intelligent behaviors for embodied agents in simulations. The output of the classic Temporal Difference family of Reinforcement Learning algorithms adopts the form of a value function expressed as a numeric table or a function approximator. The learned behavior is then derived using a greedy policy with respect to this value function. Nevertheless, sometimes the learned policy does not meet expectations, and the task of authoring is difficult and unsafe because the modification of one value or parameter in the learned value function has unpredictable consequences in the space of the policies it represents…