pinecone/core-2020-05-10-deduplication huggingface dataset:
Table-based division by small integer constants

International audienceComputing cores to be implemented on FPGAs may involve divisions by small integer constants in fixed or floating point. This article presents a family of architectures addressing this need. They are derived from a simple recurrence whose body can be implemented very efficiently as a look-up table that matches the hardware resources of the target FPGA. For instance, division of a 32-bit integer by the constant 3 may be implemented by a combinatorial circuit of 48 LUT6 on a Virtex-5. Other options are studied, including iterative implementations, and architectures based on embedded memory blocks. This technique also computes the remainder. An efficient implementation of the correctly rounded division of a floating-point constant by such a small integer is also presented
Simulating research behaviour

This paper presents a simulation of research behaviour, focusing on the process of writing papers, submitting them to journals and conferences, reviewing them, and accepting/rejecting them. The simulation is currently used to evaluate the OpinioNet reputation model, which calculates the reputation of researchers and research work based on the propagation of opinions amongst related entities. The goal is to verify whether the reputation model succeeds in encouraging ‘good' research behaviour or not, although the simulator is elaborate enough to be used for the analysis of other aspects of paper writing, submission, and review processes.This work has been supported by the LiquidPublications project (funded by the European Commission's FET programme) and the Agreement Technologies project (funded by CONSOLIDER CSD 2007-0022, INGENIO 2010).Peer Reviewe
Seaweeds and their communities in polar regions

Polar seaweeds typically begin to grow in late winter-spring, around the time of sea-ice break up. They can grow under very low light enabling distributions to depths of ≥40 m. Moreover, they are physiologically adapted to low temperatures. Intertidal species exhibit a remarkable stress tolerance against freezing, desiccation and salinity changes. Endemism is much greater in the Antarctic compared to the Arctic species. On rocky shores of the Antarctic Peninsula and of Spitsbergen >80% of the bottom can be covered by seaweeds with standing biomass levels ≥20 kg wet wt m-2.  Species richness and biomass declines, however, towards higher latitudes. Seaweeds are the dominant organisms in coastal waters and thus play important roles in benthic food webs and are likely to be of particular importance to benthic detrital food chains. Chemical defenses against herbivores are common in Antarctic, but not in Arctic seaweeds. More research is needed especially to study the effects of global climate changes
Encoding databases satisfying a given set of dependencies

Consider a relation schema with a set of dependency constraints. A fundamental question is what is the minimum space where the possible instances of the schema can be "stored". We study the following model. Encode the instances by giving a function which maps the set of possible instances into the set of words of a given length over the binary alphabet in a decodable way. The problem is to find the minimum length needed. This minimum is called the information content of the database. We investigate several cases where the set of dependency constraints consist of relatively simple sets of functional or multivalued dependencies. We also consider the following natural extension. Is it possible to encode the instances such a way that small changes in the instance cause a small change in the code. © 2012 Springer-Verlag
Group law computations on Jacobians of hyperelliptic Curves

We derive an explicit method of computing the composition step in Cantor’s algorithm for group operations on Jacobians of hyperelliptic curves. Our technique is inspired by the geometric description of the group law and applies to hyperelliptic curves of arbitrary genus. While Cantor’s general composition involves arithmetic in the polynomial ring F_q[x], the algorithm we propose solves a linear system over the base field which can be written down directly from the Mumford coordinates of the group elements. We apply this method to give more efficient formulas for group operations in both affine and projective coordinates for cryptographic systems based on Jacobians of genus 2 hyperelliptic curves in general form
Semantic disambiguation and contextualisation of social tags

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-28509-7_18This manuscript is an extended version of the paper ‘cTag: Semantic Contextualisation of Social Tags’, presented at the 6th International Workshop on Semantic Adaptive Social Web (SASWeb 2011).We present an algorithmic framework to accurately and efficiently identify the semantic meanings and contexts of social tags within a particular folksonomy. The framework is used for building contextualised tag-based user and item profiles. We also present its implementation in a system called cTag, with which we preliminary analyse semantic meanings and contexts of tags belonging to Delicious and MovieLens folksonomies. The analysis includes a comparison between semantic similarities obtained for pairs of tags in Delicious folksonomy, and their semantic distances in the whole Web, according to co-occurrence based metrics computed with results of a Web search engine.This work was supported by the Spanish Ministry of Science
and Innovation (TIN2008-06566-C04-02), and Universidad Autónoma de Madrid
(CCG10-UAM/TIC-5877
Uncovering the big players of the web

In this paper we aim at observing how today the Internet large organizations deliver web content to end users. Using one-week long data sets collected at three vantage points aggregating more than 30,000 Internet customers, we characterize the offered services precisely quantifying and comparing the performance of different players. Results show that today 65% of the web traffic is handled by the top 10 organiza- tions. We observe that, while all of them serve the same type of content, different server architectures have been adopted considering load bal- ancing schemes, servers number and location: some organizations handle thousands of servers with the closest being few milliseconds far away from the end user, while others manage few data centers. Despite this, the performance of bulk transfer rate offered to end users are typically good, but impairment can arise when content is not readily available at the server and has to be retrieved from the CDN back-en
A formal definition and a new security mechanism of physical unclonable
  functions

The characteristic novelty of what is generally meant by a "physical
unclonable function" (PUF) is precisely defined, in order to supply a firm
basis for security evaluations and the proposal of new security mechanisms. A
PUF is defined as a hardware device which implements a physical function with
an output value that changes with its argument. A PUF can be clonable, but a
secure PUF must be unclonable. This proposed meaning of a PUF is cleanly
delineated from the closely related concepts of "conventional unclonable
function", "physically obfuscated key", "random-number generator", "controlled
PUF" and "strong PUF". The structure of a systematic security evaluation of a
PUF enabled by the proposed formal definition is outlined. Practically all
current and novel physical (but not conventional) unclonable physical functions
are PUFs by our definition. Thereby the proposed definition captures the
existing intuition about what is a PUF and remains flexible enough to encompass
further research. In a second part we quantitatively characterize two classes
of PUF security mechanisms, the standard one, based on a minimum secret
read-out time, and a novel one, based on challenge-dependent erasure of stored
information. The new mechanism is shown to allow in principle the construction
of a "quantum-PUF", that is absolutely secure while not requiring the storage
of an exponentially large secret. The construction of a PUF that is
mathematically and physically unclonable in principle does not contradict the
laws of physics.Comment: 13 pages, 1 figure, Conference Proceedings MMB & DFT 2012,
  Kaiserslautern, German
Temporally-constrained convolutive probabilistic latent component analysis for multi-pitch detection

In this paper, a method for multi-pitch detection which exploits the temporal evolution of musical sounds is presented. The proposed method extends the shift-invariant probabilistic latent component analysis algorithm by introducing temporal constraints using multiple Hidden Markov Models, while supporting multiple-instrument spectral templates. Thus, this model can support the representation of sound states such as attack, sustain, and decay, while the shift-invariance across log-frequency can be utilized for multi-pitch detection in music signals that contain frequency modulations or tuning changes. For note tracking, pitch-specific Hidden Markov Models are also employed in a postprocessing step. The proposed system was tested on recordings from the RWC database, the MIREX multi-F0 dataset, and on recordings from a Disklavier piano. Experimental results using a variety of error metrics, show that the proposed system outperforms a non-temporally constrained model. The proposed system also outperforms state-of-the art transcription algorithms for the RWC and Disklavier datasets
Inter-organizational Interoperability through integration of Multiagent, Web Service, and Semantic Web Technologies

This paper presents a software architecture for inter-organizational multiagent systems. The architecture integrates Web service technology into multiagent systems to overcome the technical interoperability problem of current multiagent systems in the fast growing service-oriented environments. We integrate Semantic Web technology to make multiagent systems semantically interoperable. We address the problem of interoperability regarding interfaces, messaging protocols, data exchanged, and security whilst considering a dynamic e-business environment. The proposed architecture enables service virtualization, secure service access across organizational boundaries, service-to-agent communication, and OWL reasoning within agents
Grounding Verbs of Motion in Natural Language Commands to Robots

To be useful teammates to human partners, robots must be able to follow spoken instructions given in natural language. An important class of instructions involve interacting with people, such as “Follow the person to the kitchen” or “Meet the person at the elevators.” These instructions require that the robot fluidly react to changes in the environment, not simply follow a pre-computed plan. We present an algorithm for understanding natural language commands with three components. First, we create a cost function that scores the language according to how well it matches a candidate plan in the environment, defined as the log-likelihood of the plan given the command. Components of the cost function include novel models for the meanings of motion verbs such as “follow,” “meet,” and “avoid,” as well as spatial relations such as “to” and landmark phrases such as “the kitchen.” Second, an inference method uses this cost function to perform forward search, finding a plan that matches the natural language command. Third, a high-level controller repeatedly calls the inference method at each timestep to compute a new plan in response to changes in the environment such as the movement of the human partner or other people in the scene. When a command consists of more than a single task, the controller switches to the next task when an earlier one is satisfied. We evaluate our approach on a set of example tasks that require the ability to follow both simple and complex natural language commands. Keywords: Cost Function; Spatial Relation; State Sequence; Edit Distance; Statistical Machine TranslationUnited States. Office of Naval Research (Grant  MURI N00014-07-1-0749
Triadic motifs and dyadic self-organization in the World Trade Network

In self-organizing networks, topology and dynamics coevolve in a continuous
feedback, without exogenous driving. The World Trade Network (WTN) is one of
the few empirically well documented examples of self-organizing networks: its
topology strongly depends on the GDP of world countries, which in turn depends
on the structure of trade. Therefore, understanding which are the key
topological properties of the WTN that deviate from randomness provides direct
empirical information about the structural effects of self-organization. Here,
using an analytical pattern-detection method that we have recently proposed, we
study the occurrence of triadic "motifs" (subgraphs of three vertices) in the
WTN between 1950 and 2000. We find that, unlike other properties, motifs are
not explained by only the in- and out-degree sequences. By contrast, they are
completely explained if also the numbers of reciprocal edges are taken into
account. This implies that the self-organization process underlying the
evolution of the WTN is almost completely encoded into the dyadic structure,
which strongly depends on reciprocity.Comment: 12 pages, 3 figures; Best Paper Award at the 6th International
  Conference on Self-Organizing Systems, Delft, The Netherlands, 15-16/03/201
System Orchestration Support for a Collaborative Blended Learning Flow

Portable and interactive technologies are changing the nature of collaborative learning practices and open up new possibilities for Computer Supported Collaborative Learning (CSCL). Now, activities occurring in and beyond the classroom can be combined and integrated leading to a new type of complex collaborative blended learning scenarios. However, to organize and structure these scenarios is challenging and represent a workload for practitioners, which hinder the adoption of these technology-enhanced practices. As an approach to alleviate this workload, this paper proposes a proof of concept of a technological solution to overcome the limitations detected in an analysis of an actual collaborative blended learning experiment carried out in a previous study. The solution consists on a Unit of Learning suitable to be instantiated with IMS Learning Design and complemented by a GenericService Integration system. This chapter also discusses to which extent the proposed solution covers the limitations detected in the previous study and how useful could be for reducing the orchestration effort in future experiences.This work has been partially funded by the Project Learn3 (TIN2008-
05163/TSI) from the Plan Nacional I+D+I and "Investigación y Desarrollo de Tecnologías
para el e-Learning en la Comunidad de Madrid” funded by the Madrid Regional
Government under grant No. S2009/TIC-1650
Scene invariant crowd counting and crowd occupancy analysis

In public places, crowd size may be an indicator of congestion, delay, instability, or of abnormal events, such as a fight, riot or emergency. Crowd related information can also provide important business intelligence such as the distribution of people throughout spaces, throughput rates, and local densities.\ud
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A major drawback of many crowd counting approaches is their reliance on large numbers of holistic features, training data requirements of hundreds or thousands of frames per camera, and that each camera must be trained separately. This makes deployment in large multi-camera environments such as shopping centres very costly and difficult.\ud
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In this chapter, we present a novel scene-invariant crowd counting algorithm that uses local features to monitor crowd size. The use of local features allows the proposed algorithm to calculate local occupancy statistics, scale to conditions which are unseen in the training data, and be trained on significantly less data.\ud
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Scene invariance is achieved through the use of camera calibration, allowing the system to be trained on one or more viewpoints and then deployed on any number of new cameras for testing without further training. A pre-trained system could then be used as a ‘turn-key’ solution for crowd counting across a wide range of environments, eliminating many of the costly barriers to deployment which currently exist
Identifying customer behaviour and dwell time using soft biometrics

In a commercial environment, it is advantageous to know how long it takes customers to move between different regions, how long they spend in each region, and where they are likely to go as they move from one location to another. Presently, these measures can only be determined manually, or through the use of hardware tags (i.e. RFID). Soft biometrics are characteristics that can be used to describe, but not uniquely identify an individual. They include traits such as height, weight, gender, hair, skin and clothing colour. Unlike traditional biometrics, soft biometrics can be acquired by surveillance cameras at range without any user cooperation. While these traits cannot provide robust authentication, they can be used to provide identification at long range, and aid in object tracking and detection in disjoint camera networks. In this chapter we propose using colour, height and luggage soft biometrics to determine operational statistics relating to how people move through a space. A novel average soft biometric is used to locate people who look distinct, and these people are then detected at various locations within a disjoint camera network to gradually obtain operational statistic
Question answering and multi-search engines in geo-temporal information retrieval

In this paper we present a complete system for the treatment of both geographical and temporal dimensions in text and its application to information retrieval. This system has been evaluated in both the GeoTime task of the 8th and 9th NTCIR workshop in the years 2010 and 2011 respectively, making it possible to compare the system to contemporary approaches to the topic. In order to participate in this task we have added the temporal dimension to our GIR system. The system proposed here has a modular architecture in order to add or modify features. In the development of this system, we have followed a QA-based approach as well as multi-search engines to improve the system performance.This research has been partially funded by the Spanish Government under project TEXTMESS 2.0 (TIN2009-13391-C04-01), and by the University of Alicante under project GRE10-33
Are firms exporting to China and India different from other exporters?

This chapter asks if and why advanced countries differ in their ability to export to China and India. To this end we exploit a newly collected, comparable cross-country dataset (EFIGE) obtained from a survey of 15,000 manufacturing firms in Austria, France, Germany, Hungary, Italy, Spain and the United Kingdom. The EFIGE dataset contains detailed information on firms’ international activities as well as firm characteristics such as size and productivity, governance and management structure, workforce, innovation and research activity. We study both the extensive and intensive margins of exports and identify firm characteristics that are positively or negatively correlated wiThexporting activity tout court and wiThexporting to China and India conditional on being an exporter. We confirm previous rich evidence and show that larger, more productive, and more innovative firms are more likely to become exporters and export more. We also provide some new evidence on the role of governance and management: while there does not seem to be a strong negative effect of family ownership, we find that a higher percentage of family management reduces a firm’s export propensity and export volumes. When we turn to exports to China and India, we find that firms exporting there must be on average larger, more productive, and more innovative than firms exporting elsewhere
Bayesian Painting by Numbers: Flexible Priors for Colour-Invariant Object Recognition

Generative models of images should take into account transformations of geometry and reflectance. Then, they can provide explanations of images that are factorized into intrinsic properties that are useful for subsequent tasks, such as object classification. It was previously shown how images and objects within images could be described as compositions of regions called structural elements or ‘stels’. In this way, transformations of the reflectance and illumination of object parts could be accounted for using a hidden variable that is used to ‘paint’ the same stel differently in different images. For example, the stel corresponding to the petals of a flower can be red in one image and yellow in another. Previous stel models have used a fixed number of stels per image and per image class. Here, we introduce a Bayesian stel model, the colour − invariant admixture (CIA) model, which can infer different numbers of stels for different object types, as appropriate. Results on Caltech101 images show that this method is capable of automatically selecting a number of stels that reflects the complexity of the object class and that these stels are useful for object recognition.Engineering and Applied Science
Distributed Intelligent MEMS: Progresses and Perspectives

International audienceMEMS research has until recently focused mainly on the engineering process, resulting in interesting products and a growing market. To fully realize the promise of MEMS, the next step is to add embedded intelligence. With embedded intelligence, the scalability of manufacturing will enable distributed MEMS systems consisting of thousands or millions of units which can work together to achieve a common goal. However, before such systems can become a reallity, we must come to grips with the challenge of scalability which will require paradigm-shifts both in hardware and software. Furthermore, the need for coordinated actuation, programming, communication and mobility management raises new challenges in both control and programming. The objective of this article is to report the progresses made by taking the example of two research projects and by giving the remaining challenges and the perspectives of distributed intelligent MEMS
Client classification policies for SLA negotiation and allocation in shared cloud datacenters

In Utility Computing business model, the owners of the computing resources negotiate with their potential clients to sell computing power. The terms of the Quality of Service (QoS) to be provided as well as the economic conditions are established in a Service-Level Agreement (SLA). There are situations in which providers must differentiate the SLAs in function of the type of Client that is willing to access the resources or the agreed QoS e.g. when the hardware resources are shared between users of the company that own the resources and external users. This paper proposes to consider the information of potential users when the SLA is under negotiation to allow providers to prioritize users (e.g. internal users over external users, or preferential users over common users). Two policies for negotiation are introduced: price discrimination and client-aware overselling of resources. The validity of the policies is\ud
demonstrated through exhaustive experiments.Postprint (author’s final draft
Developing a cost-effective virtual cluster on the cloud.

The Cloud provides highly democratic access to computer services on a pay-per-use basis. A fact that has encouraged many researchers to adopt the Cloud for the processing of large computational tasks and data storage. This has been used in the past for single research endeavours or as mechanism for coping with excessive load on conventional computational resources (clusters). In this paper we investigate, through the use of simulation, the applicability of running an entire computer cluster on the Cloud. We investigate a number of policy decisions which can be made over such a virtual cluster to reduce the running cost and the effect these policies have on the users of the cluster