pinecone/core-2020-05-10-deduplication huggingface dataset:
On the Zarankiewicz Problem for Intersection Hypergraphs

Let d and t be fixed positive integers, and let Kdt,…,t denote the complete d-partite hypergraph with t vertices in each of its parts, whose hyperedges are the d-tuples of the vertex set with precisely one element from each part. According to a fundamental theorem of extremal hypergraph theory, due to Erd\H os~\cite{E64}, the number of hyperedges of a d-uniform hypergraph on n vertices that does not contain Kdt,…,t as a subhypergraph, is nd−1td−1. This bound is not far from being optimal. We address the same problem restricted to {\em intersection hypergraphs} of (d−1)-dimensional {\em simplices} in Rd. Given an n-element set § of such simplices, let \HHd(§) denote the d-uniform hypergraph whose vertices are the elements of §, and a d-tuple is a hyperedge if and only if the corresponding simplices have a point in common. We prove that if \HHd(§) does not contain Kdt,…,t as a subhypergraph, then its number of edges is O(n) if d=2, and O(nd−1+ϵ) for any ϵ>0 if d≥3. This is almost a factor of n better than Erd\H os's above bound. Our result is tight, apart from the error term ϵ in the exponent. In particular, for d=2, we obtain a theorem of Fox and Pach~\cite{FP08}, which states that every Kt,t-free intersection graph of n {\em segments} in the plane has O(n) edges. The original proof was based on a separator theorem that does not generalize to higher dimensions. The new proof works in any dimension and is simpler: it uses {\em size-sensitive cuttings}, a variant of random sampling. We demonstrate the flexibility of this technique by extending the proof of the planar version of the theorem to intersection graphs of x-monotone curves
2-Layer Fan-Planarity: From Caterpillar to Stegosaurus

In a fan-planar drawing of a graph there is no edge that crosses two other independent edges. We study 2-layer fan-planar drawings, i.e., fan-planar drawings such that the vertices are assigned to two distinct horizontal layers and edges are straight-line segments that connect vertices of different layers. We characterize 2-layer fan-planar drawable graphs and describe a linear-time testing and embedding algorithm for biconnected graphs. We also study the relationship between 2-layer fan-planar graphs and 2-layer right-angle crossing graphs
Methods for the Study of Marine Biodiversity

Recognition of the threats to biodiversity and its importance to society has led to calls for globally coordinated sampling of trends in marine ecosystems. As a step to defining such efforts, we review current methods of collecting and managing marine biodiversity data. A fundamental component of marine biodiversity is knowing what, where, and when species are present. However, monitoring methods are invariably biased in what taxa, ecological guilds, and body sizes they collect. In addition, the data need to be placed, and/or mapped, into an environmental context. Thus a suite of methods will be needed to encompass representative components of biodiversity in an ecosystem. Some sampling methods can damage habitat and kill species, including unnecessary bycatch. Less destructive alternatives are preferable, especially in conservation areas, such as photography, hydrophones, tagging, acoustics, artificial substrata, light-traps, hook and line, and live-traps. Here we highlight examples of operational international sampling programmes and data management infrastructures, notably the Continuous Plankton Recorder, Reef Life Survey, and detection of Harmful Algal Blooms and MarineGEO. Data management infrastructures include the World Register of Marine Species for species nomenclature and attributes, the Ocean Biogeographic Information System for distribution data, Marine Regions for maps, and Global Marine Environmental Datasets for global environmental data. Existing national sampling programmes, such as fishery trawl surveys and intertidal surveys, may provide a global perspective if their data can be integrated to provide useful information. Less utilised and emerging sampling methods, such as artificial substrata, light-traps, microfossils and eDNA also hold promise for sampling the less studied components of biodiversity. All of these initiatives need to develop international standards and protocols, and long-term plans for their governance and support.published_or_final_versio
Involving Citizen Scientists in Biodiversity Observation

The involvement of non-professionals in scientific research and environmental monitoring, termed Citizen Science (CS), has now become a mainstream approach for collecting data on earth processes, ecosystems and biodiversity. This chapter examines how CS might contribute to ongoing efforts in biodiversity monitoring, enhancing observation and recording of key species and systems in a standardised manner, thereby supporting data relevant to the Essential Biodiversity Variables (EBVs), as well as reaching key constituencies who would benefit Biodiversity Observation Networks (BONs). The design of successful monitoring or observation networks that rely on citizen observers requires a careful balancing of the two primary user groups, namely data users and data contributors (i.e., citizen scientists). To this end, this chapter identifies examples of successful CS programs as well as considering practical issues such as the reliability of the data, participant recruitment and motivation, and the use of emerging technologies
Vehicle Cardinality Estimation in VANETs by Using RFID Tag Estimator

Nowadays, many vehicles equipped with RFID-enabled chipsets traverse the Electronic Toll Collection (ETC) systems. Here, we present a scheme to estimate the vehicle cardinality with high accuracy and efficiency. A unique RFID tag is attached to a vehicle, so we can identify vehicles through RFID tags. With RFID signal, the location of vehicles can be detected remotely. Our scheme makes vehicle cardinality estimation based on the location distance between the first vehicle and second vehicle. Specifically, it derives the relationship between the distance and number of vehicles. Then, it deduces the optimal parameter settings used in the estimation model under certain requirement. According to the actual estimated traffic flow, we put forward a mechanism to improve the estimation efficiency. Conducting extensive experiments, the presented scheme is proven to be outstanding in two aspects. One is the deviation rate of our model is 50 % of FNEB algorithm, which is the classical scheme. The other is our efficiency is 1.5 times higher than that of FNEB algorithm.Second International Conference, IOV 2015Chengdu, ChinaDecember 19-21, 201
Communication models insights meet simulations

International audienceIt is well-known that taking into account communications while scheduling jobs in large scale parallel computing platforms is a crucial issue. In modern hierarchical platforms, communication times are highly different when occurring inside a cluster or between clusters. Thus, allocating the jobs taking into account locality constraints is a key factor for reaching good performances. However, several theoretical results prove that imposing such constraints reduces the solution space and thus, possibly degrades the performances. In practice, such constraints simplify implementations and most often lead to better results. Our aim in this work is to bridge theoretical and practical intuitions, and check the differences between constrained and unconstrained schedules (namely with respect to locality and node contiguity) through simulations. We have developped a generic tool, using SimGrid as the base simulator, enabling interactions with external batch schedulers to evaluate their scheduling policies. The results confirm that insights gained through theoretical models are ill-suited to current architectures and should be reevaluated
Behavioral Spherical Harmonics for Long-Range Agents’ Interaction

We introduce behavioral spherical harmonic (BSH), a novel approach to efficiently and compactly represent the directional-dependent behavior of agent. BSH is based on spherical harmonics to project the directional information of a group of multiple agents to a vector of few coefficients; thus, BSH drastically reduces the complexity of the directional evaluation, as it requires only few agent-group interactions instead of multiple agent-agent ones. We show how the BSH model can efficiently model intricate behaviors such as long-range collision avoidance, reaching interactive performance and avoiding agent congestion on challenging multi-groups scenarios.
Furthermore, we demonstrate how both the innate parallelism and the compact coefficient representation of the BSH model are well suited for GPU architectures, showing performance analysis of our OpenCL implementation
RAMSES: Reversibility-based Aget Modeling and Simulation Environment with Speculation support

This paper presents RAMSES, a framework for easily specifying agent-based discrete event models entailing both environment and agent entities. RAMSES offers parallel execution capabilities based on speculative event processing and an innovative software reversibility technique that copes with state restore in case the run slides along a non-consistent speculative path. Reversibility in RAMSES relies on transparent static software instrumentation, thus allowing the model developer to concentrate on the actual forward-execution logic of the simulation events occurring in the system. An experimental assessment of RAMSES is also presented, which is aimed at determining its run-time effectiveness and its potential for simplifying the development of agent-based models when compared to other (general purpose) speculative frameworks for parallel discrete event simulation
Marshall-Olkin extended Zipf distribution

Being able to generate large synthetic graphs resembling those found in the real world, is of high importance for the design of new graph algorithms and benchmarks. In this paper, we first compare several probability models in terms of goodness-of-fit, when used to model the degree distribution of real graphs. Second, after confirming that the MOEZipf model is the one that gives better fits, we present a method to generate MOEZipf distributions. The method is shown to work well in practice when implemented in a scalable synthetic graph generator.Peer ReviewedPostprint (author's final draft
Fluid Structure Interaction of Multiple Flapping Filaments Using Lattice Boltzmann and Immersed Boundary Methods

The problem of flapping filaments in an uniform incoming flow is tackled using a Lattice Boltzmann—Immersed Boundary method. The fluid momentum equations are solved on a Cartesian uniform lattice while the beating filaments are tracked through a series of markers, whose dynamics are functions of the forces exerted by the fluid, the filament flexural rigidity and the tension. The instantaneous wall conditions on the filament are imposed via a system of singular body forces, consistently discretised on the lattice of the Boltzmann equation. We first consider the case of a single beating filament, and then the case of multiple beating filaments in a side-by-side configuration, focussing on the modal behaviour of the whole dynamical systems
Digital Stylometry: Linking Profiles Across Social Networks

There is an ever growing number of users with accounts on multiple social media and networking sites. Consequently, there is increasing interest in matching user accounts and profiles across different social networks in order to create aggregate profiles of users. In this paper, we present models for Digital Stylometry, which is a method for matching users through stylometry inspired techniques. We experimented with linguistic, temporal, and combined temporal-linguistic models for matching user accounts, using standard and novel techniques. Using publicly available data, our best model, a combined temporal-linguistic one, was able to correctly match the accounts of 31% of 5,612 distinct users across Twitter and Facebook
Applying Sorting Networks to Synthesize Optimized Sorting Libraries

This paper shows an application of the theory of sorting networks to
facilitate the synthesis of optimized general purpose sorting libraries.
Standard sorting libraries are often based on combinations of the classic
Quicksort algorithm with insertion sort applied as the base case for small
fixed numbers of inputs. Unrolling the code for the base case by ignoring loop
conditions eliminates branching and results in code which is equivalent to a
sorting network. This enables the application of further program
transformations based on sorting network optimizations, and eventually the
synthesis of code from sorting networks. We show that if considering the number
of comparisons and swaps then theory predicts no real advantage of this
approach. However, significant speed-ups are obtained when taking advantage of
instruction level parallelism and non-branching conditional assignment
instructions, both of which are common in modern CPU architectures. We provide
empirical evidence that using code synthesized from efficient sorting networks
as the base case for Quicksort libraries results in significant real-world
speed-ups.Comment: IMADA-preprint-c
The ultimate tactics of self-referential systems

Mathematics is usually regarded as a kind of language. The essential behavior
of physical phenomena can be expressed by mathematical laws, providing
descriptions and predictions. In the present essay I argue that, although
mathematics can be seen, in a first approach, as a language, it goes beyond
this concept. I conjecture that mathematics presents two extreme features,
denoted here by {\sl irreducibility} and {\sl insaturation}, representing
delimiters for self-referentiality. These features are then related to physical
laws by realizing that nature is a self-referential system obeying bounds
similar to those respected by mathematics. Self-referential systems can only be
autonomous entities by a kind of metabolism that provides and sustains such an
autonomy. A rational mind, able of consciousness, is a manifestation of the
self-referentiality of the Universe. Hence mathematics is here proposed to go
beyond language by actually representing the most fundamental existence
condition for self-referentiality. This idea is synthesized in the form of a
principle, namely, that {\sl mathematics is the ultimate tactics of
self-referential systems to mimic themselves}. That is, well beyond an
effective language to express the physical world, mathematics uncovers a deep
manifestation of the autonomous nature of the Universe, wherein the human brain
is but an instance.Comment: 9 pages. This essay received the 4th. Prize in the 2015 FQXi essay
  contest: "Trick or Truth: the Mysterious Connection Between Physics and
  Mathematics
Children of the Cosmos. Presenting a Toy Model of Science with a Supporting Cast of Infinitesimals

Mathematics may seem unreasonably effective in the natural sciences, in particular in physics. In this essay, I argue that this judgment can be attributed, at least in part, to selection effects. In support of this central claim, I offer four elements. The first element is that we are creatures that evolved within this Universe, and that our pattern finding abilities are selected by this very environment. The second element is that our mathematics—although not fully constrained by the natural world—is strongly inspired by our perception of it. Related to this, the third element finds fault with the usual assessment of the efficiency of mathematics: our focus on the rare successes leaves us blind to the ubiquitous failures (selection bias). The fourth element is that the act of applying mathematics provides many more degrees of freedom than those internal to mathematics. This final element will be illustrated by the usage of ‘infinitesimals’ in the context of mathematics and that of physics. In 1960, Wigner wrote an article on this topic [4] and many (but not all) later authors have echoed his assessment that the success of mathematics in physics is a mystery. At the end of this essay, I will revisit Wigner and three earlier replies that harmonize with my own view. I will also explore some of Einstein’s ideas that are connected to this. But first, I briefly expose my views of science and mathematics, since these form the canvass of my central claim.status: publishe
Mathematics Is Physics

In this essay, I argue that mathematics is a natural science---just like
physics, chemistry, or biology---and that this can explain the alleged
"unreasonable" effectiveness of mathematics in the physical sciences. The main
challenge for this view is to explain how mathematical theories can become
increasingly abstract and develop their own internal structure, whilst still
maintaining an appropriate empirical tether that can explain their later use in
physics. In order to address this, I offer a theory of mathematical
theory-building based on the idea that human knowledge has the structure of a
scale-free network and that abstract mathematical theories arise from a
repeated process of replacing strong analogies with new hubs in this network.
This allows mathematics to be seen as the study of regularities, within
regularities, within ..., within regularities of the natural world. Since
mathematical theories are derived from the natural world, albeit at a much
higher level of abstraction than most other scientific theories, it should come
as no surprise that they so often show up in physics.
  This version of the essay contains an addendum responding to Slyvia
Wenmackers' essay and comments that were made on the FQXi website.Comment: 15 pages, LaTeX. Second prize winner in 2015 FQXi Essay Contest (see
  http://fqxi.org/community/forum/topic/2364
A question of balance: The benefits of pattern-recognition when solving problems in a complex domain

This is the accepted manuscript version of the following article: M. Lloyd-Kelly, F. Gobet, and Peter C. R. Lane, ???A Question of Balance The Benefits of Pattern-Recognition when Solving Problems in a Complex Domain???, LNCS Transactions on Computational Collective Intelligence, Vol. XX, 2015. The final published version is available at: http://www.springer.com/gb/book/9783319275420 ?? 2015 Springer International Publishing.The dual-process theory of human cognition proposes the existence of two systems for decision-making: a slower, deliberative,problem-solving system and a quicker, reactive, pattern-recognition system. We alter the balance of these systems in a number of computational simulations using three types of agent equipped with a novel, hybrid, human-like cognitive architecture. These agents are situated in the stochastic, multi-agent Tileworld domain, whose complexity can be precisely controlled and widely varied. We explore how agent performance is affected by different balances of problem-solving and pattern-recognition, and conduct a sensitivity analysis upon key pattern-recognition system variables. Results indicate that pattern-recognition improves agent performance by as much as 36.5 % and, if a balance is struck with particular pattern-recognition components to promote pattern-recognition use, performance can be further improved by up to 3.6 %. This research is of interest for studies of expert behaviour in particular, and AI in general
SAJaS: enabling JADE-based simulations

Multi-agent systems (MAS) are widely acknowledged as an appropriate modelling paradigm for distributed and decentralized systems, where a (potentially large) number of agents interact in non-trivial ways. Such interactions are often modelled defining high-level interaction protocols. Open MAS typically benefit from a number of infrastructural components that enable agents to discover their peers at run-time. On the other hand, multi-agent-based simulations (MABS) focus on applying MAS to model complex social systems, typically involving a large agent population. Several MAS development frameworks exist, but they are often not appropriate for MABS; and several MABS frameworks exist, albeit sharing little with the former. While open agent-based applications benefit from adopting development and interaction standards, such as those proposed by FIPA, MABS frameworks typically do not support them. In this paper, a proposal to bridge the gap between MAS simulation and development is presented, including two components. The Simple API for JADE-based Simulations (SAJaS) enhances MABS frameworks with JADE-based features. While empowering MABS modellers with modelling concepts offered by JADE, SAJaS also promotes a quicker development of simulation models for JADE programmers. In fact, the same implementation can, with minor changes, be used as a large scale simulation or as a distributed JADE system. In its current version, SAJaS is used in tandem with the Repast simulation framework. The second component of our proposal consists of a MAS Simulation to Development (MASSim2Dev) tool, which allows the automatic conversion of a SAJaS-based simulation into a JADE MAS, and vice-versa. SAJaS provides, for certain kinds of applications, increased simulation performance. Validation tests demonstrate significant performance gains in using SAJaS with Repast when compared with JADE, and show that the usage of MASSim2Dev preserves the original functionality of the system. Â© Springer-Verlag Berlin Heidelberg 2015
Strategic negotiation and trust in diplomacy - the DipBlue approach

The study of games in Artificial Intelligence has a long tradition. Game playing has been a fertile environment for the development of novel approaches to build intelligent programs. Multi-agent systems (MAS), in particular, are a very useful paradigm in this regard, not only because multi-player games can be addressed using this technology, but most importantly because social aspects of agenthood that have been studied for years by MAS researchers can be applied in the attractive and controlled scenarios that games convey. Diplomacy is a multi-player strategic zero-sum board game, including as main research challenges an enormous search tree, the difficulty of determining the real strength of a position, and the accommodation of negotiation among players. Negotiation abilities bring along other social aspects, such as the need to perform trust reasoning in order to win the game. The majority of existing artificial players (bots) for Diplomacy do not exploit the strategic opportunities enabled by negotiation, focusing instead on search and heuristic approaches. This paper describes the development of DipBlue, an artificial player that uses negotiation in order to gain advantage over its opponents, through the use of peace treaties, formation of alliances and suggestion of actions to allies. A simple trust assessment approach is used as a means to detect and react to potential betrayals by allied players. DipBlue was built to work with DipGame, a MAS testbed for Diplomacy, and has been tested with other players of the same platform and variations of itself. Experimental results show that the use of negotiation increases the performance of bots involved in alliances, when full trust is assumed. In the presence of betrayals, being able to perform trust reasoning is an effective approach to reduce their impact. Â© Springer-Verlag Berlin Heidelberg 2015