pinecone/core-2020-05-10-deduplication huggingface dataset:
Digital control of a novel single-phase three-port bidirectional converter to interface renewables and electric vehicles with the power grid

This paper presents the digital control of a novel single-phase three-port bidirectional (STB) converter used to interface renewables from solar photovoltaic (PV) panels and electric vehicles (EVs) with the power grid. Using an appropriated power theory, the STB converter can be used to exchange ener-gy between the PVs, the EVs and the power grid in four distinct modes: (1) The EV receives energy from the power grid (G2V - grid-to-vehicle operation mode) or delivers energy to the power grid (V2G - vehicle-to-grid operation mode); (2) All the energy produced by the PV panels is delivery to the power grid; (3) All the energy produced by the PV panels is delivery to the EV; (4) The EV can receive energy simultaneously from the PV panels and from the power grid (G2V). The currents of the power grid, PV panels and EV are con-trolled through independent predictive current control strategies, which ensure good power quality levels. This paper presents the architecture of the proposed STB converter and the detailed explanation of the digital implementation of the control algorithms, namely, the power theory and the predictive current control strategies. The control algorithms were validated through computational simula-tions and experimental results.Fundação para a Ciência e Tecnologia (FCT); FEDER funds through the COMPETE 2020 – 
Programa Operacional Competitividade 
e Internacionalização (POCI) with the reference project POCI-01-0145-FEDER-
006941
Model predictive control of an on-board fast battery charger for electric mobility applications

Under the necessities of reducing emissions and air pollution, and also for increasing fuel economy, automotive companies have been developing electric and plug-in hybrid electric vehicles. Since these vehicles are parked when the batteries are being charged, it is possible to use the traction power converter as on-board charger, also allowing to reduce weight, volume and costs of components in the vehicle. In this context, this paper presents a model predictive control algorithm for an on-board fast battery charging that uses the traction power converter of an electric vehicle. Simulation results and system implementation are depicted, and finally, are presented some experimental results obtained with the proposed control system.(undefined)info:eu-repo/semantics/publishedVersio
Renewable energy system for an isolated sustainable social centre

This paper describes the development of the power converters and control algorithms to implement an isolated microgrid based in renewable energy sources used to feed a Sustainable Social Centre in a remote place. The microgrid is designed to work with photovoltaic panels, micro wind and micro-hydro turbines, or even with diesel generators. The control system of the power converters is totally digital and implemented by means of a TMS320f28335 Digital Signal Controller (DSC) from Texas Instruments. One of the most im-portant requirements imposed for the microgrid power system is the capability of providing a sinusoidal supply voltage with low harmonic distortion even in the presence of non linear electrical loads. The hardware topologies and the digital control systems of the power converters are evaluated through experimental results obtained with a developed laboratory prototype. This work is focused in the DC AC converter of the renewable energy system for the isolated Sustainable Centre.(undefined
Evaluation of the introduction of electric vehicles in the power grid – a study for the island of Maio in Cape Verde

Serie: Lecture notes in electrical engineering, vol. 402This paper presents an evaluation of the introduction of electric vehi-cles (EVs) in an electrical power grid. The main contribution is the control analysis of the power quality considering simultaneous battery charging pro-cesses. The methodology used can be applied to any known power grid; howev-er, it was considered the case of the island of Maio, in Cape Verde, in continua-tion of previous works concerning that power grid. Two commercial different types of battery chargers were considered: a traditional model with highly dis-torted current consumption (that causes distortion in the power grid voltage), and another with almost sinusoidal current consumption. Considering simulta-neous battery charging processes, it can be concluded that the power grid struc-ture (composed by three medium voltage branches) with the current power de-mands of the consumers of the island of Maio have a potential integration for 300 EVs if battery chargers with almost sinusoidal current consumption are used, i.e., 152 for the first medium voltage branch, 35 for the second branch, and 113 for the third branch. Moreover, the results show that the first medium voltage branch of the distribution system, which has the capability to support the integration of 152 EVs if the battery chargers have sinusoidal current con-sumption (presenting a maximum value of THDv% in the power grid voltage of 1.8%), only can support 27 EVs if are used traditional battery chargers, with highly distorted current consumption (considering a maximum THDv% of 5%).COMPETE: POCI-01-0145-FEDER-007043Fundação para a Ciência e Tecnologia (FCT) - UID/CEC/00319/2013Fundação para a Ciência e Tecnologia (FCT) - SFRH/BD/80155/201
OpenADR: intelligent electrical energy consumption towards Internet-of-Things

With the growing of intermittent renewable energy sources, like wind and solar, are required energy backup solutions to establish an advantageous compromise between the energy production and consumption. Typically, these renewable energy sources are not installed at the end-users level, which can cre-ate the problem of uncontrolled distributed energy sources. In this research work we propose a solution based on the standard OpenADR to handle this problem, creating a platform based on internet-of-things capable to turn-on or off electrical devices based on a central decision process that meets the requirements of energy producers and consumers. Producers can provide energy according to the con-sumer’s requirements and take part of energy production and costs fluctuations. Based on an OpenADR standard for energy data exchange and a central cloud server, a list of services are provided to handle this transactions, with georefer-enced information to minimize energy losses in the distribution process.(undefined
A low-cost ZigBee-based wireless industrial automation system

This paper describes the development of an industrial automation system based on a ZigBee wireless sensor network, designed for the monitoring and control of multiple refrigeration equipments in an industrial area, replacing the existing cabled network, which is based on the LonWorks platform. For this purpose, ZigBee routers were used to replace the local controllers at the refrigeration equipments, while the central management controller was re-placed by a ZigBee coordinator and a PC. The proposed system was devel-oped using a hardware platform based in the CC2530 integrated circuit and the Z-Stack software. Results from experimental field tests performed in an industrial environment are provided in order to assess the performance of the developed ZigBee network.This work is supported by FCT (Fundação para a Ciência e Tecnologia) with the reference project UID/EEA/04436/2013, and by FEDER funds through the COMPETE 2020 – Programa Operacional Competitividade e Internacionalização (POCI) with the reference project POCI-01-0145-FEDER-006941
Mobile sensing system for cycling power output control

This paper describes the development of a novel cycling effort control sys-tem that contributes to promote the users’ physical health and mobility. This system controls the motor assistance level of an electric bicycle in order to ensure that the cyclist’s power output remains inside the desired limits, regardless of changes in variables such as the speed of the bicycle or the slope of the terrain. The power output is monitored using a sensor device that provides raw torque and cadence data, whereas a smartphone application processes these data, implements the effort control algorithm and provides the user interface. Modules on the bicycle handle the data acquisition, wire-less communication with the smartphone and driving of the motor assis-tance level. Experimental results validate the effectiveness of the imple-mented power output control system.This work is supported by FCT (Fundação para a Ciência e Tecnologia) with the reference
project UID/EEA/04436/2013, and by FEDER funds through the COMPETE
2020 – Programa Operacional Competitividade e Internacionalização (POCI) with the
reference project POCI-01-0145-FEDER-006941
Adaptation Processes in Agriculture and Food Security: Insights from Evaluating Behavioral Changes in West Africa

This chapter focuses on the evaluation of adaptive capacities of community-level human systems related to agriculture and food security. It highlights findings regarding approaches and domains to monitor and evaluate behavioral changes from CGIAR’s research program on climate change, agriculture and food security (CCAFS). This program, implemented in five West African countries, is intended to enhance adaptive capacities in agriculture management of natural resources and food systems. In support of participatory action research on climate-smart agriculture, a monitoring and evaluation plan was designed with the participation of all stakeholders to track changes in behavior of the participating community members. Individuals’ and groups’ stories of changes were collected using most significant change tools. The collected stories of changes were substantiated through field visits and triangulation techniques. Frequencies of the occurrence of characteristics of behavioral changes in the stories were estimated. The results show that smallholder farmers in the intervention areas adopted various characteristics of behavior change grouped into five domains: knowledge, practices, access to assets, partnership and organization. These characteristics can help efforts to construct quantitative indicators of climate change adaptation at local level. Further, the results suggest that application of behavioral change theories can facilitate the development of climate change adaptation indicators that are complementary to indicators of development outcomes. We conclude that collecting stories on behavioral changes can contribute to biophysical adaptation monitoring and evaluation
Toward physical realizations of thermodynamic resource theories

Conventional statistical mechanics describes large systems and averages over
many particles or over many trials. But work, heat, and entropy impact the
small scales that experimentalists can increasingly control, e.g., in
single-molecule experiments. The statistical mechanics of small scales has been
quantified with two toolkits developed in quantum information theory: resource
theories and one-shot information theory. The field has boomed recently, but
the theorems amassed have hardly impacted experiments. Can thermodynamic
resource theories be realized experimentally? Via what steps can we shift the
theory toward physical realizations? Should we care? I present eleven
opportunities in physically realizing thermodynamic resource theories.Comment: Publication information added. Cosmetic change
Adaptive Mean Shift Based Hemodynamic Brain Parcellation in fMRI

One of the remaining challenges in event-related fMRI is to discriminate between the vascular response and the neural activity in the BOLD signal. This discrimination is done by identifying the hemodynamic territories which differ in their underlying dynamics. In the literature, many approaches have been proposed to estimate these underlying dynamics, which is also known as Hemodynamic Response Function (HRF). However, most of the proposed approaches depend on a prior information regarding the shape of the parcels (territories) and their number. In this paper, we propose a novel approach which relies on the adaptive mean shift algorithm for the parcellation of the brain. A variational inference is used to estimate the unknown variables while the mean shift is embedded within a variational expectation maximization (VEM) framework to allow for estimating the parcellation and the HRF profiles without having any prior information about the number of the parcels or their shape. Results on synthetic data confirms the ability of the proposed approach to estimate accurate HRF estimates and number of parcels. It also manages to discriminate between voxels in different parcels especially at the borders between these parcels. In real data experiment, the proposed approach manages to recover HRF estimates close to the canonical shape in the bilateral occipital cortex
Inference of Haemoglobin Concentration From Stereo RGB

Multispectral imaging (MSI) can provide information about tissue oxygenation,
perfusion and potentially function during surgery. In this paper we present a
novel, near real-time technique for intrinsic measurements of total haemoglobin
(THb) and blood oxygenation (SO2) in tissue using only RGB images from a stereo
laparoscope. The high degree of spectral overlap between channels makes
inference of haemoglobin concentration challenging, non-linear and under
constrained. We decompose the problem into two constrained linear sub-problems
and show that with Tikhonov regularisation the estimation significantly
improves, giving robust estimation of the Thb. We demonstrate by using the
co-registered stereo image data from two cameras it is possible to get robust
SO2 estimation as well. Our method is closed from, providing computational
efficiency even with multiple cameras. The method we present requires only
spectral response calibration of each camera, without modification of existing
laparoscopic imaging hardware. We validate our technique on synthetic data from
Monte Carlo simulation % of light transport through soft tissue containing
submerged blood vessels and further, in vivo, on a multispectral porcine data
set.Comment: To appear at the 6th International Conference on Medical Imaging and
  Augmented Reality, MIAR 2016, held in Bern, Switzerland during August 2016,
  and in the corresponding proceeding
A DTMC Model for Performance Evaluation of Irregular Interconnection Networks with Asymmetric Spatial Traffic Distributions

Several mathematical models have been proposed to evaluate the performance of interconnection networks used for high-speed connections for supercomputers, switches and routers for local and wide area networks, as well as networks on a chip. Often these models are based on state space reduction by exploiting symmetries of the network and requiring uniform traffic patterns. If an interconnection network is built for a specific application with non-uniform spatial traffic distribution, models that are more general are needed. This paper proposes a mathematical model for performance evaluation of application-specific interconnection networks based on inhomogeneous discrete time Markov chains (DTMC). It supports store and forward routing, irregular network topologies, and asymmetric spatial traffic distributions. The model is described in a generalized way so that it can support arbitrary switching element sizes within the network and its input buffers
System occupancy of a two-class batch-service queue with class-dependent variable server capacity

Due to their wide area of applications, queueing models with batch service, where the server can process several customers simultaneously, have been studied frequently. An important characteristic of such batch-service systems is the size of a batch, that is the number of customers that are processed simultaneously. In this paper, we analyse a two-class batch-service queueing model with variable server capacity, where all customers are accommodated in a common first-come-first served single-server queue. The server can only process customers that belong to the same class, so that the size of a batch is determined by the number of consecutive same-class customers. After establishing the system equations that govern the system behaviour, we deduce an expression for the steady-state probability generating function of the system occupancy at random slot boundaries. Also, some numerical examples are given that provide further insight in the impact of the different parameters on the system performance
Applying reversibility theory for the performance evaluation of reversible computations

Reversible computations have been widely studied from the functional point of view and energy consumption. In the literature, several authors have proposed various formalisms (mainly based on process algebras) for assessing the correctness or the equivalence among reversible computations. In this paper we propose the adoption of Markovian stochastic models to assess the quantitative properties of reversible computations. Under some conditions, we show that the notion of time-reversibility for Markov chains can be used to efficiently derive some performance measures of reversible computations. The importance of time-reversibly relies on the fact that, in general, the process’s stationary distribution can be derived efficiently by using numerically stable algorithms. This paper reviews the main results about time-reversible Markov processes and discusses how to apply them to tackle the problem of the quantitative evaluation of reversible computation
Semantic annotation of medical documents in CDA context

The goal of this work is to recover semantic and structural information from medical documents in electronic format. Despite the progressive diffusion of Electronic Health Record systems, a lot of medical information, also for legacy reasons, is available to patients and physicians in image-only or textual format. The difficulties of obtaining such information when needed result in high costs for health providers. In this work we develop the concept of a system designed to convert legacy medical documents into a standard and interoperable format compliant with the Clinical Document Architecture model by the means of semantic annotation
How to Search the Internet Archive Without Indexing It

Significant parts of cultural heritage are produced on the web during the
last decades. While easy accessibility to the current web is a good baseline,
optimal access to the past web faces several challenges. This includes dealing
with large-scale web archive collections and lacking of usage logs that contain
implicit human feedback most relevant for today's web search. In this paper, we
propose an entity-oriented search system to support retrieval and analytics on
the Internet Archive. We use Bing to retrieve a ranked list of results from the
current web. In addition, we link retrieved results to the WayBack Machine;
thus allowing keyword search on the Internet Archive without processing and
indexing its raw archived content. Our search system complements existing web
archive search tools through a user-friendly interface, which comes close to
the functionalities of modern web search engines (e.g., keyword search, query
auto-completion and related query suggestion), and provides a great benefit of
taking user feedback on the current web into account also for web archive
search. Through extensive experiments, we conduct quantitative and qualitative
analyses in order to provide insights that enable further research on and
practical applications of web archives
Archiving Software Surrogates on the Web for Future Reference

Software has long been established as an essential aspect of the scientific
process in mathematics and other disciplines. However, reliably referencing
software in scientific publications is still challenging for various reasons. A
crucial factor is that software dynamics with temporal versions or states are
difficult to capture over time. We propose to archive and reference surrogates
instead, which can be found on the Web and reflect the actual software to a
remarkable extent. Our study shows that about a half of the webpages of
software are already archived with almost all of them including some kind of
documentation.Comment: TPDL 2016, Hannover, German
Retrieving and Ranking Similar Questions from Question-Answer Archives
  Using Topic Modelling and Topic Distribution Regression

Presented herein is a novel model for similar question ranking within
collaborative question answer platforms. The presented approach integrates a
regression stage to relate topics derived from questions to those derived from
question-answer pairs. This helps to avoid problems caused by the differences
in vocabulary used within questions and answers, and the tendency for questions
to be shorter than answers. The performance of the model is shown to outperform
translation methods and topic modelling (without regression) on several
real-world datasets.Comment: International Conference on Theory and Practice of Digital Libraries
  2016 (accepted
Content-Based Video Retrieval in Historical Collections of the German
  Broadcasting Archive

The German Broadcasting Archive (DRA) maintains the cultural heritage of
radio and television broadcasts of the former German Democratic Republic (GDR).
The uniqueness and importance of the video material stimulates a large
scientific interest in the video content. In this paper, we present an
automatic video analysis and retrieval system for searching in historical
collections of GDR television recordings. It consists of video analysis
algorithms for shot boundary detection, concept classification, person
recognition, text recognition and similarity search. The performance of the
system is evaluated from a technical and an archival perspective on 2,500 hours
of GDR television recordings.Comment: TPDL 2016, Hannover, Germany. Final version is available at Springer
  via DO
Tracking and re-finding printed material using a personal digital library

Most web searches aim to re-find previously known information or documents. Keeping track of one’s digital and printed reading material is known to be a challenging and costly task. We describe the design, implementation and evaluation of our Human-centred workplace (HCW) – a system that supports the tracking of physical document printouts. HCW embeds QR codes in the document printout, stores the documents in a personal Digital Library, and uses cameras in the office to track changes in the document locations. We explored the HCW in three evaluations, using the system over several weeks in an office setting, a user study in a lab environment, and extensive functional tests
ArchiveWeb: Collaboratively Extending and Exploring Web Archive
  Collections

Curated web archive collections contain focused digital contents which are
collected by archiving organizations to provide a representative sample
covering specific topics and events to preserve them for future exploration and
analysis. In this paper, we discuss how to best support collaborative
construction and exploration of these collections through the ArchiveWeb
system. ArchiveWeb has been developed using an iterative evaluation-driven
design-based research approach, with considerable user feedback at all stages.
This paper describes the functionalities of our current prototype for
searching, constructing, exploring and discussing web archive collections, as
well as feedback on this prototype from seven archiving organizations, and our
plans for improving the next release of the system.Comment: Published via Springer in International Conference on Theory and
  Practice of Digital Libraries (TPDL 2016