pinecone/core-2020-05-10-deduplication huggingface dataset:
Influence of Mother Tongue on Dynamic Handwriting Features in Primary School

Handwriting is an essential fine motor skill in school-aged children and plays a crucial role for educational development and autonomy of everyday life. To analyze hand-writing movement an objective quantitative kinematic analysis can be performed by using digital tablets. Through this tech-nology it was possible to identify a lot of parameters useful to characterize the handwriting process.\ud
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In order to study the influence of mother tongue on the dy-namic of handwriting in primary school, we examined the writing response of 42 non-native speakers and compared their characteristics with those of 131 Italian mother tongue chil-dren. All children undertook one repetitive sequence of le and an Italian sentence written in two different ways: as accurately as and as fast as possible.\ud
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The results showed that the differences between native and non-native speakers were not significant in the repetitive se-quence while a clear influence of mother tongue was present only in the third grade for the sentence tasks
p-leader based classification of first stage intrapartum fetal HRV

Interpretation and analysis of intrapartum fetal heart rate, enabling early detection of fetal acidosis, remains a challenging signal processing task. Recently, a variant of the wavelet-based multifractal analysis, based on p-exponents and p-leaders, which provides a rich framework for data regularity analysis, has been proposed. The present contribution aims at studying the benefits of using the p-leader multifractal formalism for discrimination of intrapartum fetal heart rate. First, a dependence on p of the multifractal properties of data is evidenced and interpreted. Second, classification between healthy subjects and fetuses suffering from acidosis is shown to have satisfactory performance that increases when p is decreased
Deceived bilateral filter for improving the automatic cell segmentation and tracking in the NF-kB pathway without nuclear staining

artículo -- Universidad de Costa Rica, Escuela de Ingeniería Eléctrica. 2014In this work we implement an automatic videobased online cell tracking system for TNFa treated cells in the
transcription factor NF-kB pathway, with the aim to provide
p65 measurement approximation with time and individual cell
resolution. The video used to test our proposed tracking system
consists on cells transfected with fluorescent p65 protein. Such
protein switches its location within the cell, among the nucleus
and cytoplasm over time, causing important changes on its apparent morphology. This represents a major challenge for an automatic cell tracking system. Additionally, images in the tested
microscopy footage present noise and contrast variations. For
noise reduction, we modified the deceived bilateral filter (DBF),
a denoising and edge sharpening non linear filter. The proposed
modification of the DBF consists in an adaptive border enhancement. We tested the cell tracking algorithm with different preprocessing configurations achieving a maximum tracking accuracy improvement of 28%, with the use of the modified DBFUniversidad de Costa Rica, Sistema de Estudios de Posgrado (SEP)UCR::Docencia::Ingeniería::Facultad de Ingeniería::Escuela de Ingeniería Eléctric
Modelling of trends in Twitter using retweet graph dynamics

In this paper we model user behaviour in Twitter to capture the emergence of
trending topics. For this purpose, we first extensively analyse tweet datasets
of several different events. In particular, for these datasets, we construct
and investigate the retweet graphs. We find that the retweet graph for a
trending topic has a relatively dense largest connected component (LCC). Next,
based on the insights obtained from the analyses of the datasets, we design a
mathematical model that describes the evolution of a retweet graph by three
main parameters. We then quantify, analytically and by simulation, the
influence of the model parameters on the basic characteristics of the retweet
graph, such as the density of edges and the size and density of the LCC.
Finally, we put the model in practice, estimate its parameters and compare the
resulting behavior of the model to our datasets.Comment: 16 pages, 5 figures, presented at WAW 201
LiveRank: How to Refresh Old Crawls

International audienceThis paper considers the problem of refreshing a crawl. More precisely, given a collection of Web pages (with hyperlinks) gathered at some time, we want to identify a significant fraction of these pages that still exist at present time. The liveness of an old page can be tested through an online query at present time. We call LiveRank a ranking of the old pages so that active nodes are more likely to appear first. The quality of a LiveRank is measured by the number of queries necessary to identify a given fraction of the alive pages when using the LiveRank order. We study different scenarios from a static setting where the LiveRank is computed before any query is made, to dynamic settings where the LiveRank can be updated as queries are processed. Our results show that building on the PageRank can lead to efficient LiveRanks for Web graphs
Firefighting as a game

The Firefighter Problem was proposed in 1995 [16] as a deterministic discrete-time model for the spread (and containment) of a fire. Its applications reach from real fires to the spreading of diseases and the containment of floods. Furthermore, it can be used to model the spread of computer viruses or viral marketing in communication networks.\ud
In this work, we study the problem from a game-theoretical perspective. Such a context seems very appropriate when applied to large networks, where entities may act and make decisions based on their own interests, without global coordination.\ud
We model the Firefighter Problem as a strategic game where there is one player for each time step who decides where to place the firefighters. We show that the Price of Anarchy is linear in the general case, but at most 2 for trees. We prove that the quality of the equilibria improves when allowing coalitional cooperation among players. In general, we have that the Price of Anarchy is in T(n/k) where k is the coalition size. Furthermore, we show that there are topologies which have a constant Price of Anarchy even when constant sized coalitions are considered.Peer ReviewedPostprint (author’s final draft
The effect of a finite time horizon in the durable good monopoly problem
  with atomic consumers

A durable good is a long-lasting good that can be consumed repeatedly over
time, and a duropolist is a monopolist in the market of a durable good. In
1972, Ronald Coase conjectured that a duropolist who lacks commitment power
cannot sell the good above the competitive price if the time between periods
approaches zero. Coase's counterintuitive conjecture was later proven by Gul et
al. (1986) under an infinite time horizon model with non-atomic consumers.
Remarkably, the situation changes dramatically for atomic consumers and an
infinite time horizon. Bagnoli et al. (1989) showed the existence of a
subgame-perfect Nash equilibrium where the duropolist extracts all the consumer
surplus. Observe that, in these cases, duropoly profits are either arbitrarily
smaller or arbitrarily larger than the corresponding static monopoly profits --
the profit a monopolist for an equivalent consumable good could generate. In
this paper we show that the result of Bagnoli et al. (1989) is in fact driven
by the infinite time horizon. Indeed, we prove that for finite time horizons
and atomic agents, in any equilibrium satisfying the standard skimming
property, duropoly profits are at most an additive factor more than static
monopoly profits. In particular, duropoly profits are always at least static
monopoly profits but never exceed twice the static monopoly profits.
  Finally we show that, for atomic consumers, equilibria may exist that do not
satisfy the skimming property. For two time periods, we prove that amongst all
equilibria that maximize duropoly profits, at least one of them satisfies the
skimming property. We conjecture that this is true for any number of time
period.Comment: A 2-page abstract of an earlier version of this paper was published
  in the proceeding of the 10th conference on Web and Internet Economics
  (WINE), pages 292-29
PTAS for Minimax Approval Voting

We consider Approval Voting systems where each voter decides on a subset to
candidates he/she approves. We focus on the optimization problem of finding the
committee of fixed size k minimizing the maximal Hamming distance from a vote.
In this paper we give a PTAS for this problem and hence resolve the open
question raised by Carragianis et al. [AAAI'10]. The result is obtained by
adapting the techniques developed by Li et al. [JACM'02] originally used for
the less constrained Closest String problem. The technique relies on extracting
information and structural properties of constant size subsets of votes.Comment: 15 pages, 1 figur
Institutional Mergers in Chinese Higher Education

Open access articleChina is an old civilization with extraordinarily rich traditions in higher learning. Chinese higher education institutions are now trying to assert themselves into the international system just as China is emerging as a major player in world affairs. Well integrated with the international community, the Chinese system has become one of the most influential in the world, in terms of its population size of students and teachers, the ever-growing academic publications it produces annually, and the large numbers of students it sends to and attracts from other countries.published_or_final_versio
NextServe Framework: Supporting Services Over Content-Centric Networking

The future Internet architecture aims to reformulate the way the content/service is requested to make it location-independent. Information-Centric Networking is a new network paradigm, which tries to achieve this goal by making content objects identified and requested by name instead of address.\ud
In this paper, we extend Information-Centric Networking architecture to support services in order to be requested and invoked by names. We present NextServe framework, which is a service framework with a human-readable self-explanatory naming scheme. NextServe is inspired by the object-oriented programming paradigm and is applicable with real-world scenarios
Judgment Aggregation with Abstentions under Voters' Hierarchy

Similar to Arrow’s impossibility theorem for preference aggregation, judgment aggregation has also an intrinsic impossibility for generating consistent group judgment from individual judgments. Removing some of the pre-assumed conditions would mitigate the problem but may still lead to too restrictive solutions. It was proved that if completeness is removed but other plausible conditions are kept, the only possible aggregation functions are oligarchic, which means that the group judgment is purely determined by a certain subset of participating judges. Instead of further challenging the other conditions, this paper investigates how the judgment from each individual judge affects the group judgment in an oligarchic environment. We explore a set of intuitively demanded conditions under abstentions and design a feasible judgment aggregation rule based on the agents’ hierarchy. We show this proposed aggregation rule satisfies the desirable conditions. More importantly, this rule is oligarchic with respect to a subset of agenda instead of the whole agenda due to its literal-based characteristics
Strong-field-enhanced forward scattering of high-order harmonics

This is a copy of the author 's final draft version of an article published in the journal Ultrafast phenomena XIX: proceedings of the 19th international conference, Okinawa Convention Center, Okinawa, Japan, July 7-11, 2014.\ud
The final publication is available at Springer via\ud
http://dx.doi.org/10.1007/978-3-319-13242-6_24We show that scattering of ultrashort XUV pulses from strong-field driven electron wave packets is enhanced as compared with normal weak scattering from bound or free electrons. We predict large XUV amplification in high-order harmonic generation. Recent measurements have corroborated the main effect that we report. Parametric amplification of attosecond pulse trains at 11 nm has been observed to occur only if the seed pulse-train is perfectly synchronized to the driving laser pulse in the amplifier as predicted here theoretically: J. Seres et al. Scientific Reports 4:4254 (2014).Postprint (author's final draft
Integral Difference Ratio Functions on Integers

number theoryInternational audienceTo Jozef, on his 80th birthday, with our gratitude for sharing with us his prophetic vision of Informatique Abstract. Various problems lead to the same class of functions from integers to integers: functions having integral difference ratio, i.e. verifying f (a) − f (b) ≡ 0 (mod (a − b)) for all a > b. In this paper we characterize this class of functions from Z to Z via their a la Newton series expansions on a suitably chosen basis of polynomials (with rational coefficients). We also exhibit an example of such a function which is not polynomial but Bessel like
Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"Hand gesture recognition is a natural way of human computer interaction and an area of very
active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research applied to Human-Computer Interaction (HCI) is to create systems, which can identify specific human gestures and use them to convey information or controlling devices. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. This paper presents a solution, generic enough, with the help of machine learning algorithms, allowing its application in a wide range of human-computer interfaces, for real-time gesture recognition. Experiments carried out showed that the system was able to achieve an accuracy of 99.4% in terms of hand posture recognition and an average accuracy of 93.72% in terms of dynamic gesture recognition. To validate the proposed framework, two applications were implemented. The first one is a real-time system able to help a robotic soccer referee judge a game in real time. The prototype combines a vision-based hand gesture recognition system with a formal language definition, the Referee CommLang, into what is called the Referee Command Language Interface System (ReCLIS). The second one is a real-time system able to interpret the Portuguese Sign Language. Sign languages are not standard and universal and the grammars differ from country to country. Although the implemented prototype was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.(undefined
A 3D computed tomography based tool for orthopedic surgery planning

Series : Lecture notes in computational vision and biomechanics, vol. 19The preparation of a plan is essential for a surgery to take place in the
best way possible and also for shortening patient’s recovery times. In the orthopedic
case, planning has an accentuated significance due to the close relation between the
degree of success of the surgery and the patient recovering time. It is important that
surgeons are provided with tools that help them in the planning task, in order to
make it more reliable and less time consuming. In this paper, we present a 3D Computed
Tomography based solution and its implementation as an OsiriX plugin for
orthopedic surgery planning. With the developed plugin, the surgeon is able to manipulate
a three-dimensional isosurface rendered from the selected imaging study (a
CT scan). It is possible to add digital representations of physical implants (surgical
templates), in order to evaluate the feasibility of a plan. These templates are STL
files generated from CAD models. There is also the feature to extract new isosurfaces
of different voxel values and slice the final 3D model according to a predefined
plane, enabling a 2D analysis of the planned solution. Finally, we discuss how the
proposed application assists the surgeon in the planning process in an alternative
way, where it is possible to three-dimensionally analyze the impact of a surgical
intervention on the patient.(undefined
Ethical issues in ubiquitous computing—three technology assessment studies revisited

This paper discusses ethical issues in ubiquitous (or pervasive) computing from the perspective of the general discourse on ethics in computing, which started in the 1970s, two decades before the “ubicomp” vision emerged. The IFIP “Human Choice and Computers” conferences are used as points of reference for the general computing ethics discourse, and three technology as-sessment projects related to the ubicomp vision serve as a (nonrepresentative) sample of documents from the discussion of ethical issues in a ubicomp world. Revisiting these studies from the general computing ethics point of view shows that the basic issues have persisted, but ubicomp has added new aspects that were not anticipated in the earlier discourse
SLA-Driven Simulation of Multi-Tenant Scalable Cloud-Distributed Enterprise Information Systems

Cloud Computing is an enabler for delivering large-scale, distributed enterprise applications with strict requirements in terms of performance. It is often the case that such applications have complex scaling and Service Level Agreement (SLA) management requirements. In this paper we present a simulation approach for validating and comparing SLA-aware scaling policies using the CloudSim simulator, using data from an actual Distributed Enterprise Information System (dEIS). We extend CloudSim with concurrent and multi-tenant task simulation capabilities. We then show how different scaling policies can be used for simulating multiple dEIS applications. We present multiple experiments depicting the impact of VM scaling on both datacenter energy consumption and dEIS performance indicators
Shortest paths in nearly conservative digraphs

We introduce the following notion: a digraph D = (V, A) with arc weights c: A → R is called nearly conservative if every negative cycle consists of two arcs. Computing shortest paths in nearly conservative digraphs is NP-hard, and even deciding whether a digraph is nearly conservative is coNP-complete. We show that the “All Pairs Shortest Path” problem is fixed parameter tractable with various parameters for nearly conservative digraphs. The results also apply for the special case of conservative mixed graphs
Hierarchical meta-rules for scalable meta-learning

The Pairwise Meta-Rules (PMR) method proposed in [18] has been shown to improve the predictive performances of several metalearning algorithms for the algorithm ranking problem. Given m target objects (e.g., algorithms), the training complexity of the PMR method with respect to m is quadratic: (formula presented). This is usually not a problem when m is moderate, such as when ranking 20 different learning algorithms. However, for problems with a much larger m, such as the meta-learning-based parameter ranking problem, where m can be 100+, the PMR method is less efficient. In this paper, we propose a novel method named Hierarchical Meta-Rules (HMR), which is based on the theory of orthogonal contrasts. The proposed HMR method has a linear training complexity with respect to m, providing a way of dealing with a large number of objects that the PMR method cannot handle efficiently. Our experimental results demonstrate the benefit of the new method in the context of meta-learning
A HMM POS Tagger for Micro-blogging Type Texts

The high volume of communication via micro-blogging type messages has created an increased demand for text processing tools customised the unstructured text genre. The available text processing tools developed on structured texts has been shown to deteriorate significantly when used on unstructured, micro-blogging type texts. In this paper, we present the results of testing a HMM based POS (Part-Of-Speech) tagging model customized for unstructured texts. We also evaluated the tagger against published CRF based state-of-the-art POS tagging models customized for Tweet messages using three publicly available Tweet corpora. Finally, we did cross-validation tests with both the taggers by training them on one Tweet corpus and testing them on another one
A more expressive behavioral logic for decision-theoretic planning

We examine the problem of compactly expressing models of non-Markovian reward decision processes (NMRDP). In the field of decision-theoretic planning NMRDPs are used whenever the agent's reward is determined by the history of visited states. Two different propositional linear temporal logics can be used to describe execution histories that are rewarding. Called PLTL and $FLTL, they are backward and forward looking logics respectively. In this paper we find both to be expressively weak and propose a change to $FLTL resulting in a much more expressive logic that we have called $* FLTL. The time complexities of $* FLTL and $FLTL related model checking operations performed in planning are the same.Griffith Sciences, School of Information and Communication TechnologyFull Tex
BEST : an efficient algorithm for mining frequent unordered embedded subtrees

This paper presents an algorithm for mining unordered embedded subtrees using the balanced-optimal-search canonical form (BOCF). A tree structure guided scheme based enumeration approach is defined using BOCF for systematically enumerating the valid subtrees only. Based on this canonical form and enumeration technique, the balanced optimal search embedded subtree mining algorithm (BEST) is introduced for mining embedded subtrees from a database of labelled rooted unordered trees. The extensive experiments on both synthetic and real datasets demonstrate the efficiency of BEST over the two state-of-the-art algorithms for mining embedded unordered subtrees, SLEUTH and U3
GDL Meets ATL: A Logic for Game Description and Strategic Reasoning

This paper presents a logical framework that extends the Game Description Language with coalition operators from Alternating-time Temporal Logic and prioritised strategy connectives. Our semantics is built upon the standard state transition model. The new framework allows us to formalise van Benthem’s game-oriented principles in multi-player games, and formally derive Weak Determinacy and Zermelo’s Theorem for two-player games. We demonstrate with a real-world game how to use our language to specify a game and design a strategy, and how to use our framework to verify a winning/no-losing strategy. Finally, we show that the model-checking problem of our logic is in 2EXPTIME with respect to the size of game structure and the length of formula, which is no worse than the model-checking problem in ATL