pinecone/core-2020-05-10-deduplication huggingface dataset:
DeShaTo: Describing the Shape of Cumulative Topic Distributions to Rank Retrieval Systems without Relevance Judgments

This paper investigates an approach for estimating the effectiveness of any IR system. The approach is based on the idea that a set of documents retrieved for a specific query is highly relevant if there are only a small number of predominant topics in the retrieved documents. The proposed approach is to determine the topic probability distribution of each document offline, using Latent Dirichlet Allocation. Then, for a retrieved set of documents, a set of probability distribution shape descriptors, namely the skewness and the kurtosis, are used to compute a score based on the shape of the cumulative topic distribution of the respective set of documents. The proposed model is termed DeShaTo, which is short for Describing the Shape of cumulative Topic distributions. In this work, DeShaTo is used to rank retrieval systems without relevance judgments. In most cases, the empirical results are better than the state of the art approach. Compared to other approaches, DeShaTo works independently for each system. Therefore, it remains reliable even when there are less systems to be ranked by relevance
Infrastructures to Engineer Open Agent Environments by Means of Electronic Institutions

Electronic institutions provide a computational analogue of human institutions to engineer open environments in which agents can interact in an autonomous way while complying with the norms of an institution. The purpose of this paper is twofold. On the one hand, we lightly survey our research on coordination infrastructures for electronic institutions in the last ten years. On the other hand, we highlight the research challenges in environment engineering that we have tackled during this journey as well as promising research paths for future research on the engineering of open environments for multi-agent systems.This paper has been partially funded by the following projects: TIN2012-38876-C02-01,  PRAISE  (FP7-318770),  CollectiveMind  (TEC2013-49430-EXP),  ACE (Autonomic software engineering for online Cultural Experiences), and the Generalitat of Catalunya (2014 SGR 118)Peer reviewe
Control Issues of MEMS Nanopositioning Devices

In this chapter, the control issues of microelectromechanical system (MEMS) nanopositioning devices are introduced and discussed. The real-time feedback control of a novel micro-machined 1-degree-of-freedom (1-DoF) thermal nanopositioner with on-chip electrothermal position sensors is presented. The actuation works based on the thermal expansion of V-shaped silicon beams. The sensing mechanism works based on measuring the resistance difference between two electrically biased identical silicon beams. The resistance difference varies with displacement. The heat conductance of the sensor beams varies oppositely with the position of the movable stage, resulting in different beam temperatures and resistances. A pair of position sensors are operated in differential mode to reduce low-frequency drift. The micro-machined nanopositioner has a nonlinear static input–output characteristic. The electrothermal actuator has a dynamic range of 14.4 μm and the electrothermal sensor has a low drift of 8.9 nm over 2000 s. An open-loop controller is first designed and implemented. It is experimentally shown that uncertainties result in unacceptable positioning performance. Hence, feedback control is required for accurate positioning. The on-chip displacement sensor is able to provide high-resolution displacement control. Therefore, a real-time closed-loop feedback control system is designed using a proportional-integral (PI) controller together with the nonlinear compensator used for the open-loop control system. The closed-loop system provides acceptable and robust tracking resolution for a wide range of set point values. The step response results show a positioning resolution of 7.9 nm and a time constant of 1.6 ms in a 10 μm stroke. For triangular reference tracking, which is required in raster-scanned scanning probe microscopy (SPM), the steady-state tracking error has a standard deviation of 20 nm within a wide range of 10 μm.Griffith Sciences, Griffith School of EngineeringFull Tex
Bayesian optimization for materials design

We introduce Bayesian optimization, a technique developed for optimizing
time-consuming engineering simulations and for fitting machine learning models
on large datasets. Bayesian optimization guides the choice of experiments
during materials design and discovery to find good material designs in as few
experiments as possible. We focus on the case when materials designs are
parameterized by a low-dimensional vector. Bayesian optimization is built on a
statistical technique called Gaussian process regression, which allows
predicting the performance of a new design based on previously tested designs.
After providing a detailed introduction to Gaussian process regression, we
introduce two Bayesian optimization methods: expected improvement, for design
problems with noise-free evaluations; and the knowledge-gradient method, which
generalizes expected improvement and may be used in design problems with noisy
evaluations. Both methods are derived using a value-of-information analysis,
and enjoy one-step Bayes-optimality
Inference of hidden structures in complex physical systems by
  multi-scale clustering

We survey the application of a relatively new branch of statistical
physics--"community detection"-- to data mining. In particular, we focus on the
diagnosis of materials and automated image segmentation. Community detection
describes the quest of partitioning a complex system involving many elements
into optimally decoupled subsets or communities of such elements. We review a
multiresolution variant which is used to ascertain structures at different
spatial and temporal scales. Significant patterns are obtained by examining the
correlations between different independent solvers. Similar to other
combinatorial optimization problems in the NP complexity class, community
detection exhibits several phases. Typically, illuminating orders are revealed
by choosing parameters that lead to extremal information theory correlations.Comment: 25 pages, 16 Figures; a review of earlier work
Experimental Economies and Tax Evasion: The Order Beyond the Market

Research on tax evasion will probably never get old. As long as there are taxes, there will also be policy-makers all over the world eager to tackle deviant conduct in the most efficient and efficacious way. To fill this purpose a number of theoretical and empirical frameworks have been developed in economics over the last decades, starting from the classical models of Allingham and Sandmo (1972) where individuals were assumed to be perfectly rational following a pure cost-benefit logic. Today, however, we look at a body of literature which has opened up to new and interdisciplinary findings, also thanks to the inclusion of behavioral aspects that do not necessarily follow the paradigms of the homo oeconomicus. To this end, the discipline of Experimental Economics has developed numerous ways to overcome the distance between economic theory and human behavior. The aim of this survey is to take the reader on a tour through some of these methodologies applied to the analysis of tax evasion, arguing that further research should focus on integrating multi-agent simulation models with outcomes from human subject experiments in order to create useful and necessary tools to administer, consolidate and represent the complex theoretical, empirical and experimental panorama of tax evasion research
Several Multiplexes in the same City: The role of wealth differences in
  urban mobility

In this work we analyze the architecture of real urban mobility networks from
the multiplex perspective. In particular, based on empirical data about the
mobility patterns in the cities of Bogot\'a and Medell\'{\i}n, each city is
represented by six multiplex networks, each one representing the
origin-destination trips performed by a subset of the population corresponding
to a particular socioeconomic status. The nodes of each multiplex are the
different urban locations whereas links represent the existence of a trip from
one node (origin) to another (destination). On the other hand, the different
layers of each multiplex correspond to the different existing transportation
modes. By exploiting the characterization of multiplex transportation networks
combining different transportation modes, we aim at characterizing the mobility
patterns of each subset of the population. Our results show that the
socioeconomic characteristics of the population have an extraordinary impact in
the layer organization of these multiplex systems.Comment: 15 pages, 7 figures, 1 table. Updated main text, Submitted for
  publicatio
An ensemble perspective on multi-layer networks

We study properties of multi-layered, interconnected networks from an
ensemble perspective, i.e. we analyze ensembles of multi-layer networks that
share similar aggregate characteristics. Using a diffusive process that evolves
on a multi-layer network, we analyze how the speed of diffusion depends on the
aggregate characteristics of both intra- and inter-layer connectivity. Through
a block-matrix model representing the distinct layers, we construct transition
matrices of random walkers on multi-layer networks, and estimate expected
properties of multi-layer networks using a mean-field approach. In addition, we
quantify and explore conditions on the link topology that allow to estimate the
ensemble average by only considering aggregate statistics of the layers. Our
approach can be used when only partial information is available, like it is
usually the case for real-world multi-layer complex systems
A unified approach to percolation processes on multiplex networks

Many real complex systems cannot be represented by a single network, but due
to multiple sub-systems and types of interactions, must be represented as a
multiplex network. This is a set of nodes which exist in several layers, with
each layer having its own kind of edges, represented by different colours. An
important fundamental structural feature of networks is their resilience to
damage, the percolation transition. Generalisation of these concepts to
multiplex networks requires careful definition of what we mean by connected
clusters. We consider two different definitions. One, a rigorous generalisation
of the single-layer definition leads to a strong non-local rule, and results in
a dramatic change in the response of the system to damage. The giant component
collapses discontinuously in a hybrid transition characterised by avalanches of
diverging mean size. We also consider another definition, which imposes weaker
conditions on percolation and allows local calculation, and also leads to
different sized giant components depending on whether we consider an activation
or pruning process. This 'weak' process exhibits both continuous and
discontinuous transitions.Comment: arXiv admin note: text overlap with arXiv:1312.381
Policies and regulations in Mexico with regard to genetic technology and food security

In 1988 the first application for field trials of a GMO was formally received in Mexico. Since then a Biosafety law, few bylaws and national official standards were enacted in order to regulate the safe use of GMOs and to evaluate, control and avoid adverse effects to human health and the environment. The Law on Biosafety of Genetically Modified Organisms was enacted in 2005 in order to comply with international obligations derived from the Cartagena Protocol on Biosafety signed by Mexico in 2000. This law established a biosafety legal framework to regulate the use of GMOs, protect biodiversity, and promote the conservation of organisms which Mexico is center of origin and center of genetic diversity. Since then, 561 permits for the release of GMOs into the environment have been granted between 2005 and 2014. This report gives and overview of the country’s approach to the use of GMOs, the current status of the biosafety legislation in Mexico and the development of policies and regulations since the first introduction of GM crops in the country
On the Partial Analytical Solution of the Kirchhoff Equation

We derive a combined analytical and numerical scheme to solve the
(1+1)-dimensional differential Kirchhoff system. Here the object is to obtain
an accurate as well as an efficient solution process. Purely numerical
algorithms typically have the disadvantage that the quality of solutions
decreases enormously with increasing temporal step sizes, which results from
the numerical stiffness of the underlying partial differential equations. To
prevent that, we apply a differential Thomas decomposition and a Lie symmetry
analysis to derive explicit analytical solutions to specific parts of the
Kirchhoff system. These solutions are general and depend on arbitrary
functions, which we set up according to the numerical solution of the remaining
parts. In contrast to a purely numerical handling, this reduces the numerical
solution space and prevents the system from becoming unstable. The differential
Kirchhoff equation describes the dynamic equilibrium of one-dimensional
continua, i.e. slender structures like fibers. We evaluate the advantage of our
method by simulating a cilia carpet.Comment: 13 Pages, 1 Figur
Random Surfing Without Teleportation

In the standard Random Surfer Model, the teleportation matrix is necessary to
ensure that the final PageRank vector is well-defined. The introduction of this
matrix, however, results in serious problems and imposes fundamental
limitations to the quality of the ranking vectors. In this work, building on
the recently proposed NCDawareRank framework, we exploit the decomposition of
the underlying space into blocks, and we derive easy to check necessary and
sufficient conditions for random surfing without teleportation.Comment: 13 pages. Published in the Volume: "Algorithms, Probability, Networks
  and Games, Springer-Verlag, 2015". (The updated version corrects small
  typos/errors
A Method for Short Message Contextualization: Experiments at CLEF/INEX

This paper presents the approach we developed for automatic multi-document summarization applied to short message contextualization, in particular to tweet contextualization. The proposed method is based on named entity recognition, part-of-speech weighting and sentence quality measuring. In contrast to previous research, we introduced an algorithm from smoothing from the local context. Our approach exploits topic-comment structure of a text. Moreover, we developed a graph-based algorithm for sentence reordering. The method has been evaluated at INEX/CLEF tweet contextualization track. We provide the evaluation results over the 4 years of the track. The method was also adapted to snippet retrieval and query expansion. The evaluation results indicate good performance of the approach
Overview of the CLEF eHealth Evaluation Lab 2015

This paper reports on the 3rd CLEFeHealth evaluation lab, which continues our evaluation resource building activities for the medical domain. In this edition of the lab, we focus on easing patients and nurses in authoring, understanding, and accessing eHealth information. The 2015 CLEFeHealth evaluation lab was structured into two tasks, focusing on evaluating methods for information extraction (IE) and information retrieval (IR). The IE task introduced two new challenges. Task 1a focused on clinical speech recognition of nursing handover notes; Task 1b focused on clinical named entity recognition in languages other than English, specifically French. Task 2 focused on the retrieval of health information to answer queries issued by general consumers seeking information to understand their health symptoms or conditions.\ud
\ud
The number of teams registering their interest was 47 in Tasks 1 (2 teams in Task 1a and 7 teams in Task 1b) and 53 in Task 2 (12 teams) for a total of 20 unique teams. The best system recognized 4, 984 out of 6, 818 test words correctly and generated 2, 626 incorrect words (i.e., 38.5%\ud
error) in Task 1a; had the F-measure of 0.756 for plain entity recognition, 0.711 for normalized entity recognition, and 0.872 for entity normalization in Task 1b; and resulted in P@10 of 0.5394 and nDCG@10 of 0.5086 in Task 2. These results demonstrate the substantial community interest and capabilities of these systems in addressing challenges faced by patients and nurses. As in previous years, the organizers have made data and tools available for future research and development
Knowledge-based and data-driven approaches for georeferencing of informal documents

This paper describes Knowledge-Based and Data-Driven approaches we have followed for generic Textual Georeferencing of Informal Documents. Textual georeferencing consists in assigning a set of geographical coordinates to formal (news, reports,..) or informal (blogs, social networks, chats, tagsets,...) texts and documents. The system presented in this paper has been designed to deal with informal documents from social sites. The paper describes four Georeferencing approaches, experiments, and results at the MediaEval 2014 Placing Task (ME2014PT) evaluation, and posterior experiments. The task consisted of predicting the most probable geographical coordinates of Flickr images and videos using its visual, audio and metadata associated features. Our approaches used only Flickr users textual metadata annotations and tagsets. The four approaches used for this task were: 1) a Geographical Knowledge-Based (GeoKB) approach that uses Toponym Disambiguation heuristics, 2) the Hiemstra Language Model (HLM), TFIDF and BM25 Information Retrieval (IR) approaches with Re-Ranking, 3) a combination of the GeoKB and the IR models with Re-Ranking (GeoFusion). 4) a combination of the GeoFusion with a HLM model derived from the English Wikipedia georeferenced pages. The HLM approach with Re-Ranking showed the best performance in accuracy within a margin of distance errors ranging from 10m to 1km. The GeoFusion approaches achieved the best results in accuracies from 10km to 5,000km. Both approaches achieved state-of-the-art results at ME2014PT evaluation and posterior experiments, including the best results for distance accuracies of 1000km and 5,000km in the task where only the official training dataset can be used to predict the coordinates.Peer ReviewedPostprint (published version
A Mobile Context-Aware Proactive Recommendation Approach

The Proactive Context Aware Recommender Systems aim at combining a set of technologies and knowledge about the user context not only in order to deliver the most appropriate information to the user need at the right time but also to recommend it without a user query. In this paper, we propose a contextualized proactive multi-domain recommendation approach for mobile devices. Its objective is to efficiently recommend relevant items that match users’ personal interests at the right time without waiting for users to initiate any interaction. Our contribution is divided into two main areas: The modeling of a situational user profile and the definition of an aggregation frame for contextual dimensions combination
Formal verification of Virtual Network Function graphs in an SP-DevOps context

The role of software and its flexibility is becoming more and more important in todays networks. New emerging paradigms, such as Software Defined Networking (SDN) and Network Function Virtualization (NFV), are changing the rules of the game, shifting the focus on dynamicity and programmability. Perfectly aligned with this new spirit, the FP7 UNIFY European project aims at realizing this appealing vision by applying DevOps concepts to telecom operator networks and supporting the idea of fast network reconfiguration. However, the increased range of possibilities offered by the DevOps approach comes at the cost of designing new processes and toolkits to make SDN and NFV a concrete opportunity. In this paper we specifically focus on the verification process as part of the challenging tasks that must be addressed in this scenario and its fundamental role of automatically checking some desired network properties before deploying a particular configuration. Our preliminary results confirm the feasibility of the approach and encourage future efforts in this directio
Quantum Acoustics with Surface Acoustic Waves

It has recently been demonstrated that surface acoustic waves (SAWs) can
interact with superconducting qubits at the quantum level. SAW resonators in
the GHz frequency range have also been found to have low loss at temperatures
compatible with superconducting quantum circuits. These advances open up new
possibilities to use the phonon degree of freedom to carry quantum information.
In this paper, we give a description of the basic SAW components needed to
develop quantum circuits, where propagating or localized SAW-phonons are used
both to study basic physics and to manipulate quantum information. Using
phonons instead of photons offers new possibilities which make these quantum
acoustic circuits very interesting. We discuss general considerations for SAW
experiments at the quantum level and describe experiments both with SAW
resonators and with interaction between SAWs and a qubit. We also discuss
several potential future developments.Comment: 14 pages, 12 figure
Ontology Evolution for Experimental Data in Food

International audienceThroughout its life cycle, an ontology may change in order to adapt to domain changes or to new usages. This paper presents an ontology evolution activity [1] applied to an ontology dedicated to the annotation of experimental data in food [2], and a plug-in, DynarOnto, which assists ontology engineers for carrying out the ontology changes. Our evolution method is an a priori method which takes as input an ontology in a consistent state, implements the changes selected to be applied and manages all the consequences of those changes by producing an ontology in a consistent state
A Collaborative Requirement Mining Framework to Support OEMs

12th International Conference, CDVE 2015, Mallorca, Spain, September 20-23, 2015. ProceedingsInternational audienceWith the fastidiously ever-increasing complexity of systems, the relentless, massive customisation of products and the mushrooming accumulation of legal documents (standards, policies and laws), we can observe a significant increase in requirements. We consider the tremendous volume of requirements as big data with which companies struggle to make strategic decisions early on. This paper proposes a collaborative requirement mining framework to enable the decision-makers of an Original Equipment Manufacturer (OEM) to gain insight and discover opportunities in a massive set of requirements so as to make early effective strategic decisions. The framework supports OEMs willing to uncover a subset of key requirements by distilling large unstructured and semi-structured specifications