Miracle-dz/UniFAR-FTUs huggingface dataset:
Blocking Negative Cycles in Mean Payoff Games is Strongly Polynomial Time Solvable To the memory of Peter L . Hammer ( 1936 – 2006 )

Trying to improve the algorithm [10], Leonid Khachiyan raised the following natural combinatorial game-theoretic problem, one of the few remaining natural problems in NP ∩ coNP unknown to be in P, and generalizing Minimum Cost Average Cycles. Blocking Negative Cycles. Given a finite edge-weighted digraph without sinks (every vertex has an outgoing edge) and a subset C of its vertices, can we choose one otgoing edge from each vertex in C (and throw away all other outgoing edges from C) in such a way that the remaining digraph has no negative-weight cycles reachable from a distingushed starting vertex? 2 (I.e., one player forbids edges so as the other cannot construct negative cycles.) This problem appears as a subproblem in computing values and constructing ergodic partitions in the celebrated Mean Payoff Games [5, 6, 10]. Until now a strongly polynomial solution for the above problems appeared elusive. All existing algorithms were superpolynomial : [10, 14, 16, 2, 15] suggested pseudopolynomial algorithms, with the number of iterations proportional to the maximum absolute edge weight, whereas [4] described a subexponential, in the number of vertices, algorithm. This paper settles the problem by showing, for the first time, that Blocking Negative Cycles in cyclic Mean Payoff Games, as well as p-Mean Partition (partition vertices into subsets with mean values < p and ≥ p), are strongly polynomial time solvable, independently of the edge weight.
Generalized entropies and the similarity of texts

We show how generalized Gibbs–Shannon entropies can provide new insights on the statistical properties of texts. The universal distribution of word frequencies (Zipf’s law) implies that the generalized entropies, computed at the word level, are dominated by words in a specific range of frequencies. Here we show that this is the case not only for the generalized entropies but also for the generalized (Jensen–Shannon) divergences, used to compute the similarity between different texts. This finding allows us to identify the contribution of specific words (and word frequencies) for the different generalized entropies and also to estimate the size of the databases needed to obtain a reliable estimation of the divergences. We test our results in large databases of books (from the google n-gram database) and scientific papers (indexed by Web of Science).
Comparison-based search in the presence of errors

The classic problem of searching an ordered list becomes more complicated when the answers to queries are not reliable. In the prefix-bounded error model, the number of incorrect responses at no point exceeds r times the number of questions, where r is a fixed positive fraction strictly less than ~. We present efficient algorithms for searching in this error model, and we also establish nontrivial lower bounds for sorting, maxima finding, and related problems.
New methods for computing visibility graphs

Let <italic>S</italic> be a set of <italic>n</italic> non-intersecting line segments in the plane. The visibility graph <italic>G<subscrpt>S</subscrpt></italic> of <italic>S</italic> is the graph that has the endpoints of the segments in <italic>S</italic> as nodes and in which two nodes are adjacent whenever they can “see” each other (i.e., the open line segment joining them is disjoint from all segments or is contained in a segment). Two new methods are presented to construct <italic>G<subscrpt>S</subscrpt></italic>. Both methods are very simple to implement. The first method is based on a new solution to the following problem: given a set of points, for each point sort the other points around it by angle. It runs in time &Ogr;(<italic>n</italic><supscrpt>2</supscrpt>). The second method uses the fact that visibility graphs often are sparse and runs in time &Ogr;(<italic>m</italic> log <italic>n</italic>) where <italic>m</italic> is the number of edges in <italic>G<subscrpt>S</subscrpt></italic>. Both methods use only Ogr;(<italic>n</italic>) storage.
End-to-End Transport Security in the IP-Based Internet of Things

The IP-based Internet of Things refers to the interconnection of smart devices in a Low-power and Lossy Network (LLN) with the Internet by means of protocols such as 6LoWPAN or CoAP. The mechanisms to protect the LLN from attacks from the Internet and provisioning of an end-to-end (E2E) secure connection are key requirements for functionalities ranging from network access to software updates. Interconnecting such resource constrained devices with high-performance machines requires new security mechanisms that cannot be covered by already known solutions. This paper describes attacks at transport layer against the LLN launched from the Internet. It also introduces approaches to ensure E2E security between two devices located in homogeneous networks using either HTTP/TLS or CoAP/DTLS by proposing a mapping between TLS and DTLS.
Model Checking for Successor-Invariant First-Order Logic on Minor-Closed Graph Classes

Model checking problems for first- and monadic second-order logic on graphs have received considerable attention in the past, not the least due to their connections to problems in algorithmic graph structure theory. While the model checking problem for these logics on general graphs is computationally intractable, it becomes tractable on important classes of graphs such as those of bounded tree-width, planar graphs or more generally, classes of graphs excluding a fixed minor. It is well known that allowing an order relation or successor function can greatly increase the expressive power of the respective logics. This remains true even in cases where we require the formulas to be order- or successor-invariant, that is, while they can use an order relation, their truth in a given graph must not depend on the particular ordering or successor function chosen. Naturally, the question arises whether this increase in expressive power comes at a cost in terms of tractability on specific classes of graphs. In LICS 2012, Engelmann et al. studied this problem and showed that order-invariant monadic second-order logic (MSO) remains tractable on the same classes of graphs than MSO without an ordering. That is, adding order-invariance to MSO essentially comes at no extra cost in terms of model checking complexity. For successor-invariant first-order logic something similar should be true. However, they only managed to show that successor-invariant first-order logic is tractable on the class of planar graphs which is very far from the best tractability results currently known for first-order logic. In this paper we significantly improve the latter result and show that successor-invariant first-order logic is tractable on any class of graphs excluding a fixed minor. This is much closer to the best results known for FO without an ordering. The proof relies on the construction of k-walks in suitable supergraphs of the input graphs, i.e., walks which visit every vertex at least once and at most k times, for some k depending on the excluded minor H. The supergraphs may in general contain H minors, but they still exclude some possible larger minor H', so by results of Flum and Grohe [20] model checking on these graphs is still fixed-parameter tractable.
Efficiency transfer for regression models with responses missing at random

We consider independent observations on a random pair (X,Y ), where the response Y is allowed to be missing at random but the covariate vector X is always observed. We demonstrate that characteristics of the conditional distribution of Y given X can be estimated efficiently using complete case analysis, i.e., one can simply omit incomplete cases and work with an appropriate efficient estimator which remains efficient. This means in particular that we do not have to use imputation or work with inverse probability weights. Those approaches will never be better (asymptotically) than the above complete case method. This efficiency transfer is a general result and holds true for all regression models for which the distribution of Y given X and the marginal distribution of X do not share common parameters. We apply it to the general homoscedastic semiparametric regression model. This includes models where the conditional expectation is modeled by a complex semiparametric regression function, as well as all basic models such as linear regression and nonparametric regression. We discuss estimation of various functionals of the conditional distribution, e.g., of regression parameters and of the error distribution.
Ensemble Optical Character Recognition Systems via Machine Learning

Optical Character Recognition (OCR) Systems are widely used to process scanned text into text usable by computers. We observe that current OCR systems have bad performance on domain-specific papers, even generating lots of incorrect words; besides, different OCR systems make relatively independent mistakes. Based on these observations, we train an ensemble system from multiple open-source OCR systems, which chooses outputs from candidates generated by each OCR, and train the system with machine learning techniques. We implement Softmax Regression and multi-class SVM. Our system achieve over 80% accuracy selecting between different outputs on our training set of 1,011 words. We further explore ways to improve the performance by suggesting new options, and use domain knowledge to improve its performance. Our contribution lies in following aspects: (1) We show the great potential of treating OCR systems as black-boxes and correct their outputs from each other. (2) Our system build on best open-source OCRs and achieve significant improvement on their accuracy. (3) Moreover, our work explore the possibility to make use of rich semantic knowledge to craft a better OCR system, and cast insight to a general approach to ensemble systems as black-boxes.
A MULTIMEDIA INFORMATION RETRIEVAL MODEL BASED ON SEMANTIC AND VISUAL CONTENT

Unlike text-based information retrieval model, information retrieval based on multimedia lacks a good IR model. In this paper, the goal is to present a retrieval model based on both semantic and visual content about the multimedia object. First, we survey the four basic IR models: boolean model, cluster-based model, vector-based model and probabilistic model. Considering the fact that a user's query will always contain both the textual information as well as the visual information, we work out an algorithm for the distance measurement.
A sequential test for autonomous localisation of map errors for driving assistance systems

Driving assistance systems are progressively introduced to enhance safety and comfort in passenger vehicles. They increasingly rely on information stored in digital navigation maps. However maps can be obsolete or contain errors, resulting in malfunctions of context based driving assistance systems and possibly generating hazardous situations. This paper aims at making the vehicle able to detect and localise map errors in an autonomous manner using its embedded sensors. The proposed approach relies on the sequential generation and monitoring of residuals. The vehicle estimated trajectory is compared statistically with the geometric data in the map. The approach allows driving assistance functions to know if they can rely on the map in real-time and to store this information for future journeys. The method is very efficient in terms of computational load which makes embedded applications possible. Performance is assessed using vehicle data acquired in real traffic conditions, which is then compared with an outdated navigation map.
Teaching Girls to Be Assertive: Using Conflict Resolution Strategies to Teach Elementary Age Girls the Importance of Empowering One Another

Research shows that girls between the ages of four and fourteen years old are experiencing bullying by other girls in schools at an alarming rate. Bullying between girls is typically shown indirectly, which is also known as relational aggression (e.g. exclusion, gossiping). As Radliff and Joseph (2011) state “researchers are consistently reporting that girls involved in relational aggression are at an increased risk for internalizing and externalizing difficulties as well as other health related concerns” (p. 177). The purpose of this study is to examine the conflict resolution strategies teachers use to help their female students maintain empowering relationships with other female students. The study delves into the social constructions of femininity and how that plays a major role in the ways in which girls show aggression towards each other. The main question guiding this research is: How are teachers using conflict resolution strategies to help elementary-age girls maintain supportive and empowering friendships with other girls? Some subsidiary questions include: What are teachers’ experiences with conflicts between girls in their classrooms? What are the benefits and challenges of using conflict resolution strategies to help female students cope with bullying among their gendered friendship groups? This research is a qualitative study where two educators were chosen to take part in a forty-five minute semi-structured interview. The findings from this study suggest that when teachers engage girls in conflict resolution strategies that allow them to share their stories and be collaborative, they see the importance of working together and empowering one another.
Expressing TNF in Endothelial Cells Acute Hepatitis in Transgenic Mice Chronic Inflammation and Protection from

Eisel, Gisa Tiegs and Matthias ClaussAntje Willuweit, Gabriele Sass, Annette Schoneberg, Ulrichhttp://www.jimmunol.org/content/167/7/3944J Immunol€2001; 167:3944-3952; ;Referenceshttp://www.jimmunol.org/content/167/7/3944.full#ref-list-1This article cites 55 articles, 26 of which you can access for free at: Subscriptionshttp://jimmunol.org/subscriptionsInformation about subscribing to The Journal of Immunology is online at: Permissionshttp://www.aai. org/ji/copyright.htmlSubmit copyright permission requests at: Email Alertshttp://jimmunol.org/cgi/alerts/etocReceive free email-alerts when new articles cite this article. Sign up at:
Synthesizing Hardware from Object-Oriented Descriptions1

Hardware synthesis from programming languages, including object-oriented ones such as C++ and Java, has recently attracted a lot of interest from researchers and users. Increasingly, the object-oriented aspect is being stressed. In this paper, several approaches to describing hardware by means of object-orientation are investigated with respect to their support for synthesis. We have formulated a more general, languageindependent conceptual framework for the system-level synthesis of not only objects, but also their communication in a concurrent context. An example demonstrates that the concepts can be made practical by generating VHDL code which can be further processed with high-level and RTL synthesis tools.
Spatio-temporal segmentation of mesoscale ocean surface dynamics using satellite data

Multi-satellite measurements of altimeter-derived Sea Surface Height (SSH) and Sea Surface Temperature (SST) provide a wealth of information about ocean circulation, especially mesoscale ocean dynamics which may involve strong spatio-temporal relationships between SSH and SST fields. Within an observation-driven framework, we investigate the extent to which mesoscale ocean dynamics may be decomposed into a superimposition of dynamical modes, characterized by different local regressions between SSH and SST fields. Formally, we develop a novel latent class regression model to identify dynamical modes from joint SSH and SST observation series. Applied to the highly dynamical Agulhas region off South Africa, we demonstrate and discuss the geophysical relevance of the proposed mixture model to achieve a spatio-temporal segmentation of the upper ocean dynamics.
Parallelizing OPTICS for Commodity Clusters

In this paper, we propose an algorithm, DOPTICS, a parallelized version of a popular density based cluster-ordering algorithm OPTICS. Parallelizing OPTICS is challenging because of its strong sequential data access behavior. To achieve high parallelism, a data parallel approach that exploits the underlying indexing structure is proposed. We implement the proposed algorithm for processor nodes in a commodity cluster as well as across cores in a processor. Moreover, the clusters obtained by our algorithm are exactly same as that of classical OPTICS unlike the only existing implementation of the parallel OPTICS. We demonstrate the performance of the proposed algorithm on a commodity cluster which is typically a combination of distributed and shared memory systems. Experimental results on several large real and synthetic data sets with varying dimensions are presented to show speed up and scalability achieved. The speed up obtained is remarkable and is found to scale well with increasing number of processing elements. Performance improvements of the proposed DOPTICS algorithm are due to algorithmic optimizations and parallelization strategy.
Linguistics and some aspects of its underlying dynamics

In recent years, central components of a new approach to linguistics, the Minimalist Program, have come closer to physics. In this paper, an interesting and productive isomorphism is established between minimalist structure, algebraic structures, and many-body field theory opening new avenues of inquiry on the dynamics underlying some central aspects of linguistics. Features such as the unconstrained nature of recursive Merge, the difference between pronounced and un-pronounced copies of elements in a sentence, and the Fibonacci sequence in the syntactic derivation of sentence structures, are shown to be accessible to representation in terms of algebraic formalism.
Seasonal movements of satellite-collared caribou from the Bathurst herd

SUMMARY We tracked the movements of between six and 19 caribou cows from the Bathurst herd from April 1996 to December 2000 using collars that transmit to a satellite. Spring migration routes partially depended where the caribou wintered which changed from northwest of Great Slave Lake to southeast of Great Slave Lake in winter 1997/98 and 2000/01. In winters of 1998/99 and1999/2000, distribution was split with caribou northwest and southeast of Great Slave Lake. The use of the satellite collars confirmed that the Bathurst herd moved into northern Saskatchewan early in the winters when the caribou were southeast of Great Slave Lake. Caribou movements were most synchronized during pre and postcalving migrations when daily rates average 20 km/day. During spring migration in 1996 and 1997, caribou traveled slightly faster as they neared the calving grounds but in 1999 and 2000, they slowed down as they were closer. We only found a weak suggestion that mosquito and warble activity may increase summer movements due to limitations within the data. The calving grounds were the smallest and most predictable part of the annual range and the area used during the rut varied most in size. The information on the distribution and migration of the caribou cows is relatively detailed baseline information geographically but limited in time to four years which is why the study is complimentary to the WKSS traditional knowledge studies 2 ACKNOWLEDGEMENTS
Stereo Motion Transparency Processing Implements an Ecological Smoothness Constraint

Transparent motion stimuli allow us to investigate how visual motion is processed in the presence of multiple sources of information. We used stereo random-dot kinematograms to determine how motion processing is affected by the difference in direction and depth of two overlapping motion components. Observers judged whether a noise dot display contained one or two directions of motion. For all disparity differences, performance did not change among angles greater than 60°, but the ability to detect transparent motion fell dramatically as the direction difference decreased below 60°. When a disparity difference was added between the two motion components, detection became easier. We compared these results to an ideal-observer model limited by stimulus uncertainty and low-level sources of internal noise. The resulting measure of efficiency—the ratio of human to model performance—reflects changes in how motion stimuli are being processed. A decrease of both the direction and disparity differences had the effect of decreasing efficiency. These results suggest that the mechanism processing transparent motion may implement a smoothness constraint that tends to combine similar motions into a single percept.
The effects of "phubbing" on social interaction

This research experimentally investigated the social consequences of “phubbing” – the act of snubbing someone in a social setting by concentrating on one’s mobile phone. Participants viewed a three-minute animation in which they imagined themselves as part of a dyadic conversation. Their communication partner either phubbed them extensively, partially, or not at all. Results revealed that increased phubbing significantly and negatively affected perceived communication quality and relationship satisfaction. These effects were mediated by reduced feelings of belongingness and both positive and negative affect. This research underlines the importance of phubbing as a modern social phenomenon to be further investigated.
Implementation of an oracle on top of a peer sampling service

Peer to peer systems are large scale distributed systems in which each node has the same role as any other node. Due to their size, these systems distribute the global knowledge of the whole list of peers onto the system such that no one node has the list of all the other nodes. A peer sampling service links the nodes together, forming a connected topology. To write distributed algorithms for peer to peer systems, one can rely on an oracle, which abstracts out the peer sampling service. We introduce a method to implement this oracle on top of a peer sampling service using a random walk.
Eta invariants with spectral boundary conditions

We study the asymptotics of the heat trace where P is an operator of Dirac type, where f is an auxiliary smooth smearing function which is used to localize the problem, and where we impose spectral boundary conditions. Using functorial techniques and special case calculations, the boundary part of the leading coefficients in the asymptotic expansion is found.
ReoptSMART : A Learning Query Plan Cache Columbia University Computer Science Technical Report cucs-023-08

The task of query optimization in modern relational database systems is important but can be computationally expensive. Parametric query optimization(PQO) has as its goal the prediction of optimal query execution plans based on historical results, without consulting the query optimizer. We develop machine learning techniques that can accurately model the output of a query optimizer. Our algorithms handle non-linear boundaries in plan space and achieve high prediction accuracy even when a limited amount of data is available for training. We use both predicted and actual query execution times for learning, and are the first to demonstrate a total net win of a PQO method over a state-of-the-art query optimizer for some workloads. ReoptSMART realizes savings not only in optimization time, but also in query execution time, for an over-all improvement by more than an order of magnitude in some cases.