pinecone/core-2020-05-10-deduplication huggingface dataset:
A New Analytics Model for Large Scale Multidimensional Data Visualization

With the rise of Big Data, the challenge for modern multidimensional data analysis and visualization is how it grows very quickly in size and complexity. In this paper, we first present a classification method called the 5Ws Dimensions which classifies multidimensional data into the 5Ws definitions. The 5Ws Dimensions can be applied to multiple datasets such as text datasets, audio datasets and video datasets. Second, we establish a Pair-Density model to analyze the data patterns to compare the multidimensional data on the 5Ws patterns. Third, we created two additional parallel axes by using pair-density for visualization. The attributes has been shrunk to reduce data over-crowding in pair-density parallel coordinates. This has achieved more than 80 % clutter reduction without the loss of information. The experiment shows that our model can be efficiently used for Big Data analysis and visualization
Argument mining: A machine learning perspective

Argument mining has recently become a hot topic, attracting the interests of several and diverse research communities, ranging from artificial intelligence, to computational linguistics, natural language processing, social and philosophical sciences. In this paper, we attempt to describe the problems and challenges of argument mining from a machine learning angle. In particular, we advocate that machine learning techniques so far have been under-exploited, and that a more proper standardization of the problem, also with regards to the underlying argument model, could provide a crucial element to develop better systems
The Matrix Approach for Abstract Argumentation Framework

Matrices and the operation of dual interchange are introduced into the study of Dung’s argumentation frameworks. It is showed that every argumentation framework can be represented by a matrix, and the basic extensions (such as admissible, stable, complete) can be determined by sub-blocks of its matrix. In particular, an efficient approach for determining the basic extensions has been developed using two types of standard matrix. Furthermore, we develop the topic of matrix reduction along two different lines. The first one enables to reduce the matrix into a less order matrix playing the same role for the determination of extensions. The second one enables to decompose an extension into several extensions of different sub-argumentation frameworks. It makes us not only solve the problem of determining grounded and preferred extensions, but also obtain results about dynamics of argumentation frameworks
An Axiomatic Approach to Support in Argumentation

In the context of bipolar argumentation (argumentation with two kinds of interaction, attacks and supports), we present an axiomatic approach for taking into account a special interpretation of the support relation, the necessary support. We propose constraints that should be imposed to a bipolar argumentation system using this interpretation. Some of these constraints concern the new attack relations, others concern acceptability. We extend basic Dung’s framework in different ways in order to propose frameworks suitable for encoding these constraints. By the way, we propose a formal study of properties of necessary support
Maximizing Throughput in Energy-Harvesting Sensor Nodes

We consider an online throughput maximization problem in sensor nodes that can harvest energy. The sensor nodes generate and forward packets, which cost energy; they can also harvest energy from the environment, but the amount of energy that can be harvested is not known in advance. We give a number of algorithms and lower bounds for the case of a single node. We consider both the general case and some types of ‘non-idling’ adversaries where we can get better bounds. We also consider the case of networks with multiple nodes and demonstrate that some very simple scenarios already admit no competitive algorithms.Peer-reviewedPost-print11th International Symposium on Algorithms and Experiments for Wireless Sensor Networks (ALGOSENSORS 2015), Patras, Greece 17-18 Septembe
Media Transatlantic: Developments in Media and Communication Studies Between North American and German-Speaking Europe

This book reflects recent scholarly and theoretical developments in media studies, or Medienwissenschaft. It focuses on linkages between North America and German-speaking Europe, and brings together and contextualizes contributions from a range of leading scholars. In addition to introducing English-language readers to some of the most prominent contemporary German media theorists and philosophers, including Claus Pias, Sybille Krämer and Rainer Leschke, the book shows how foundational North American contributions are themselves inspired and informed by continental sources. This book takes Harold Innis or Marshall McLuhan (and other members of the \u22Toronto School\u22) as central points of reference, and traces prospective and retrospective lines of influence in a cultural geography that is increasingly global in its scope. In so doing, the book also represents a new episode in the international reception and reinterpretation of the work of Innis and McLuhan, the two founders of the theory and study of media.http://scholarworks.boisestate.edu/fac_books/1454/thumbnail.jp
Theoretical and applied aspects of the self-organizing maps

International audienceThe Self-Organizing Map (SOM) is widely used, easy to implement , has nice properties for data mining by providing both clustering and visual representation. It acts as an extension of the k-means algorithm that preserves as much as possible the topological structure of the data. However, since its conception, the mathematical study of the SOM remains difficult and has be done only in very special cases. In WSOM 2005, Jean-Claude Fort presented the state of the art, the main remaining difficulties and the mathematical tools that can be used to obtain theoretical results on the SOM outcomes. These tools are mainly Markov chains, the theory of Ordinary Differential Equations, the theory of stability , etc. This article presents theoretical advances made since then. In addition, it reviews some of the many SOM algorithm variants which were defined to overcome the theoretical difficulties and/or adapt the algorithm to the processing of complex data such as time series, missing values in the data, nominal data, textual data, etc
Sparse online self-organizing maps for large relational data

International audienceDuring the last decades, self-organizing maps were proven to be useful tools for exploring data. While the original algorithm was designed for numerical vectors, the data became more and more complex, being frequently too rich to be described by a fixed set of numerical attributes. Several extensions of the original SOM were proposed in the literature for handling kernel or dissimilarity data. Most of them use the entire kernel/dissimilarity matrix, which requires at least quadratic complexity and becomes rapidly unfeasible for 100 000 inputs, for instance. In the present manuscript, we propose a sparse version of the online relational SOM, which sequentially increases the composition of the prototypes
Image informatics strategies for deciphering neuronal network connectivity

Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies
Integrated high-content quantification of intracellular ROS levels and mitochondrial morphofunction

Oxidative stress arises from an imbalance between the production of reactive oxygen species (ROS) and their removal by cellular antioxidant systems. Especially under pathological conditions, mitochondria constitute a relevant source of cellular ROS. These organelles harbor the electron transport chain, bringing electrons in close vicinity to molecular oxygen. Although a full understanding is still lacking, intracellular ROS generation and mitochondrial function are also linked to changes in mitochondrial morphology. To study the intricate relationships between the different factors that govern cellular redox balance in living cells, we have developed a high-contentmicroscopy-based strategy for simultaneous quantification of intracellular ROS levels and mitochondrial morphofunction. Here, we summarize the principles of intracellular ROS generation and removal, and we explain the major considerations for performing quantitative microscopy analyses of ROS and mitochondrial morphofunction in living cells. Next, we describe our workflow, and finally, we illustrate that a multiparametric readout enables the unambiguous classification of chemically perturbed cells as well as laminopathy patient cells
A framework for creating population specific multimodal brain atlas using clinical T1 and diffusion tensor images

International audienceSpatial normalization is one of the most important steps in population based statistical analysis of brain images. This involves normalizing all the brain images to a pre-defined template or a population specific template. With multiple emerging imaging modalities, it is quintessential to develop a method for building a joint template that is a statistical representation of the given population across different modalities. It is possible to create different population specific templates in different modalities using existing methods. However, they do not give an opportunity for voxelwise comparison of different modalities. A multimodal brain template with probabilistic region of interest (ROI) definitions will give opportunity for multivariate statistical frameworks for better understanding of brain diseases. In this paper, we propose a methodology for developing such a multimodal brain atlas using the anatomical T1 images and the diffusion tensor images (DTI), along with an automated workflow to probabilistically define the different white matter regions on the population specific multimodal template. The method will be useful to carry out ROI based statistics across different modalities even in the absence of expert segmentation. We show the effectiveness of such a template using voxelwise multivariate statistical analysis on population based group studies on HIV/AIDS patients. 1 The need for a probabilistic multimodal atlas The growth in brain imaging data across different modalities gives an opportunity to understand the disease progression and make correlations across them. Statistical analysis across different modalities and across population require spatial normalization. All the brain images are often normalized to a pre-defined template, for example the ICBM-152 or MNI template. However in [1] and [2], the authors have shown that choosing a generic template biases the statistical presently at Imaging Genetics Center, University of Southern California presently at MORPHENE team, INRIA Sophia-Antipoli
On temporally connected graphs of small cost.

We study the design of small cost temporally connected graphs, under various constraints. We mainly consider undirected graphs of n vertices, where each edge has an associated set of discrete availability instances (labels). A journey from vertex u to vertex v is a path from u to v where successive path edges have strictly increasing labels. A graph is temporally connected iff there is a (u, v)-journey for any pair of vertices u,v, u≠v. We first give a simple polynomial-time algorithm to check whether a given temporal graph is temporally connected. We then consider the case in which a designer of temporal graphs can freely choose availability instances for all edges and aims for temporal connectivity with very small cost; the cost is the total number of availability instances used. We achieve this via a simple polynomial-time procedure which derives designs of cost linear in n, and at most the optimal cost plus 2. To show this, we prove a lower bound on the cost for any undirected graph. However, there are pragmatic cases where one is not free to design a temporally connected graph anew, but is instead given a temporal graph design with the claim that it is temporally connected, and wishes to make it more cost-efficient by removing labels without destroying temporal connectivity (redundant labels). Our main technical result is that computing the maximum number of redundant labels is APX-hard, i.e., there is no PTAS unless P=NP. On the positive side, we show that in dense graphs with random edge availabilities, all but Θ(n) labels are redundant whp. A temporal design may, however, be minimal, i.e., no redundant labels exist. We show the existence of minimal temporal designs with at least nlogn labels
Traversed Graph Representation for Sparse Encoding of Macro-Reentrant Tachycardia

© Springer International Publishing Switzerland 2016.Macro-reentrant atrial and ventricular tachycardias originate from additional circuits in which the activation of the cardiac chambers follows a high-frequency rotating pattern. The macro-reentrant circuit can be interrupted by targeted radiofrequency energy delivery with a linear lesion transecting the pathway. The choice of the optimal ablation site is determined by the operator’s experience, thus limiting the procedure success, increasing its duration and also unnecessarily extending the ablated tissue area in the case of incorrect ablation target estimation. In this paper, an algorithm for automatic intraoperative detection of the tachycardia reentry path is proposed by modelling the propagation as a graph traverse problem. Moreover, the optimal ablation point where the path should be transected is computed. Finally, the proposed method is applied to sparse electroanatomical data to demonstrate its use when undersampled mapping occurs. Thirteen electroanatomical maps of right ventricle and right and left atrium tachycardias from patients treated for congenital heart disease were analysed retrospectively in this study, with prediction accuracy tested against the recorded ablation sites and arrhythmia termination points
ICWE 2015 rapid mashup challenge: Introduction

The ICWE 2015 Rapid Mashup Challenge is the first installment of a series of challenges that aim to engage researchers and practitioners in a competition for the best mashup approach. This paper introduces the reader to the general context of the Challenge, its objectives and motivation. It summarizes its structure into phases and the requirements contributions were asked to satisfy, so as to be eligible for participation. A brief summary of the contributions that were selected for presentation provides an overview of the content of the remainder of this volume
Interactive, live mashup development through UI-oriented computing

This paper proposes to approach the problem of developing mashups by exclusively focusing on the SurfaceWeb, that is, the data and functionality accessible through common Web pages. Typically, mashups focus on the integration of resources accessible through the Deep Web, such as data feeds, Web services and Web APIs, that do not have own UIs – next to data extracted from Web pages. Yet, these resources can be wrapped with ad-doc UIs, suitably instrumented, and made accessible through the Surface Web. Doing so enables a UI-oriented computing paradigm that allows developers to implement mashups interactively and in a live fashion inside theirWeb browser, without having to program any line of code. The goal of this paper is to showcase UI-oriented computing in practice and to demonstrate its feasibility and potential
Web mashups with webmakeup

Modding refers to the act of modifying hardware, software, or virtually anything else, to perform a function not originally conceived or intended by the designer. The rationales for modding should be sought in the aspiration of users to contextualize to their own situation the artefact at hand. Websites are not exception. WebMakeup targets mod scenarios where web pages are turned into canvases users can tune to account for their situational, idiosyncratic, and potentially, short-lived needs. By clicking, users turn DOM nodes into widgets. Widgets can next be rearranged, deleted, updated or stored for later reuse in other pages. In addition, widgets can be involved in ?blink? patterns where interactions with a widget might affect the related widgets. This empowers users to tune not only what but also when content is to show up in an AJAX-like way. WebMakeup is publicly available as a Chrome extension.Fil: Díaz, Oscar. Universidad del País Vasco; EspañaFil: Aldalur, Iñigo. Universidad del País Vasco; EspañaFil: Arellano, Cristóbal. Universidad del País Vasco; EspañaFil: Medina, Haritz. Universidad del País Vasco; EspañaFil: Firmenich, Sergio Damian. Universidad Nacional de la Patagonia; Argentina. Universidad Nacional de la Plata. Facultad de Informática. Laboratorio de Investigación y Formación en Informática Avanzada; Argentin
Nonlocal diffusion and applications

We consider the fractional Laplace framework and provide models and theorems
related to nonlocal diffusion phenomena. Some applications are presented,
including: a simple probabilistic interpretation, water waves, crystal
dislocations, nonlocal phase transitions, nonlocal minimal surfaces and
Schr\"{o}dinger equations. Furthermore, an example of an $s$-harmonic function,
the harmonic extension and some insight on a fractional version of a classical
conjecture formulated by De Giorgi are presented. Although this book aims at
gathering some introductory material on the applications of the fractional
Laplacian, some proofs and results are original. Also, the work is self
contained, and the reader is invited to consult the rich bibliography for
further details, whenever a subject is of interest.Comment: 132 pages, 26 figure
On some conjectures about free and nearly free divisors

In this paper infinite families of examples of irreducible free and nearly
free curves in the complex projective plane which are not rational curves and
whose local singularites can have an arbitrary number of branches are given.
All these examples answer negatively to some conjectures proposed by A. Dimca
and G. Sticlaru. Our examples say nothing about the most remarkable conjecture
by A. Dimca and G. Sticlaru, i.e. every rational cuspidal plane curve is either
free or nearly free.Comment: 20 page
Generation of Transmission Control Rules Compliant with Existing Access Control Policies

International audienceAccess Control (AC) is a well known mechanism that allows access restriction to resources. Nevertheless, it does not provide notification when a resource is retransmitted to an unauthorized third party. To overcome this issue, one can use mechanisms such as Data Loss/Leak Prevention (DLP) or Transmission Control (TC). These mechanisms are based on policies that are defined by security experts. Unfortunately, these policies can contradict existing AC rules, leading to security leakage (i.e. a legitimate user is allowed to send a resource to someone who has no access rights in the AC). In this article, we aim at creating TC policies that are compliant with existing AC policies. To do so, we use a mapping mechanism that generates TC rules directly from existing AC policies. Thanks to the generated rules, our solution can make inferences to improve existing AC and enhance security knowledge between infrastructures
RatSLAM : using models of rodent hippocampus for robot navigation and beyond

We describe recent biologically-inspired mapping research incorporating brain-based multi-sensor fusion and calibration processes and a new multi-scale, homogeneous mapping framework. We also review the interdisciplinary approach to the development of the RatSLAM robot mapping and navigation system over the past decade and discuss the insights gained from combining pragmatic modelling of biological processes with attempts to close the loop back to biology. Our aim is to encourage the pursuit of truly interdisciplinary approaches to robotics research by providing successful case studies
Towards modular verification of threaded concurrent executable code generated from DSL models

An important problem in Model Driven Engineering is maintaining the correctness of a specification under model transformations. We consider this issue for a framework that implements the transformation chain from the modeling language SLCO to Java. In particular, we verify the generic part of the last transformation step to Java code, involving change in granularity, focusing on the implementation of SLCO communication channels. To this end we use a parameterized modular approach; we apply a novel proof schema that supports fine grained concurrency and procedure-modularity, and use the separation logic based tool VeriFast. Our results show that such tool-assisted formal verification can be a viable addition to traditional techniques, supporting object orientation, concurrency via threads, and parameterized verification.status: publishe
Access Time Tradeoffs in Archive Compression

Web archives, query and proxy logs, and so on, can all be very large and
highly repetitive; and are accessed only sporadically and partially, rather
than continually and holistically. This type of data is ideal for
compression-based archiving, provided that random-access to small fragments of
the original data can be achieved without needing to decompress everything. The
recent RLZ (relative Lempel Ziv) compression approach uses a semi-static model
extracted from the text to be compressed, together with a greedy factorization
of the whole text encoded using static integer codes. Here we demonstrate more
precisely than before the scenarios in which RLZ excels. We contrast RLZ with
alternatives based on block-based adaptive methods, including approaches that
"prime" the encoding for each block, and measure a range of implementation
options using both hard-disk (HDD) and solid-state disk (SSD) drives. For HDD,
the dominant factor affecting access speed is the compression rate achieved,
even when this involves larger dictionaries and larger blocks. When the data is
on SSD the same effects are present, but not as markedly, and more complex
trade-offs apply.Comment: Note that the final published version of this paper prepared by
  Springer/LNCS introduced errors in the publication process in Figures 1, 2,
  and 3 that are not present in this preprint. In all other regards the
  preprint and the published version are identical in their conten