The widespread use of new technologies such as the Internet of things (IoT) and machine type communication (MTC) forces an increase on the number of user equipments (UEs) and MTC devices that are connecting to mobile ...
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Referring to objects in a natural and unambiguous manner is crucial for effective human-robot interaction. Previous research on learning-based referring expressions has focused primarily on comprehension tasks, while ...
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The ability to attend to salient regions of a visual scene is an innate and necessary preprocessing step for both biological and engineered systems performing high-level visual tasks (e.g. object detection, tracking, ...
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For creation of digital textual corpora of preserved historical sources, automatic or semi-automatic extraction of specific types of information is becoming a requested tool for many researchers active in the field of...
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For creation of digital textual corpora of preserved historical sources, automatic or semi-automatic extraction of specific types of information is becoming a requested tool for many researchers active in the field of digital humanities. With such tools, the efforts in digitization and semantic annotation will be greatly aided. For this reason, we propose a rule-based named-entity recognition system that can be used for location extraction from Latin text (so-call LOCALE). It is based on a set of computational linguistics rules for Latin language. Experimental results obtained on a set of 100 documents, which were further manually evaluated by human experts, showed that very promising results are achieved. Copyright 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
This paper presents a novel Distributed Stochastic Model Predictive Control algorithm for networks of linear systems with multiplicative uncertainties and local chance constraints on the control inputs and states. The...
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On the recent advancements in current sensor field, single chip contactless current sensors enable the end users to efficiently monitor the switching current in modern power electronics systems. This work further inve...
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ISBN:
(纸本)9781728116129
On the recent advancements in current sensor field, single chip contactless current sensors enable the end users to efficiently monitor the switching current in modern power electronics systems. This work further investigates a novel low-cost measurement technique based on Magnetoresistive (MR) sensors. The process uses a single current sensing unit, measuring the current mismatch between the two parallel Gallium Nitride (GaN) MOSFETs, which would be used for prognostic and protection purposes. The magnetic field distribution analysis of GaN devices in switching converter is investigated using FEA simulations, in order to optimize the MR sensor location. The experimental results verify the sensitivity and linearity of the sensing unit up to 20 A of current mismatch.
Mixture models are a popular unsupervised learning technique useful for discovering homogeneous clusters in unlabeled data. A key research problem lies in the accurate and efficient determination of their associated p...
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ISBN:
(数字)9781728124858
ISBN:
(纸本)9781728124865
Mixture models are a popular unsupervised learning technique useful for discovering homogeneous clusters in unlabeled data. A key research problem lies in the accurate and efficient determination of their associated parameters. Variational inference has recently risen as a prominent parameter learning approach. Hence, in this research, we propose a variational Bayes learning framework for asymmetric Gaussian mixture model. Unlike Gaussian mixture models, these models incorporate the asymmetric shape of data and are adaptive to different conditions in real-word image processing domains. Experimental results show the merit of the proposed approach.
A simple and effective colored Petri net (CPN) model is proposed in this paper for a special type of electrical networks that describe local transformer areas, in order to detect and localize illegal loads that may be...
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This paper presents graph theoretic conditions for the controllability and accessibility of bilinear systems over the special orthogonal group, the special linear group and the general linear group, respectively, in t...
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This paper proposes a layered networked SIWS (Susceptible-Infected-Water-Susceptible) model, for an SIS-type waterborne disease spreading over a human contact network connected to a water distribution network that has...
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ISBN:
(数字)9781728113982
ISBN:
(纸本)9781728113999
This paper proposes a layered networked SIWS (Susceptible-Infected-Water-Susceptible) model, for an SIS-type waterborne disease spreading over a human contact network connected to a water distribution network that has a pathogen spreading in it. Conditions for local and global stability of the healthy state, where no one is sick and the water network is not contaminated, are provided. We also pose an observability problem, and show under certain conditions if you observe some of the human contact network you can recover the pathogen levels in the water network.
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