pinecone/core-2020-05-10-deduplication huggingface dataset:
Graphene Nanoribbons: from chemistry to circuits

The Y-chart is a powerful tool for understanding the relationship between
various views (behavioral, structural, physical) of a system, at different
levels of abstraction, from high-level, architecture and circuits, to
low-level, devices and materials. We thus use the Y-chart adapted for graphene
to guide the chapter and explore the relationship among the various views and
levels of abstraction. We start with the innermost level, namely, the
structural and chemical view. The edge chemistry of patterned graphene
nanoribbons (GNR) lies intermediate between graphene and benzene, and the
corresponding strain lifts the degeneracy that otherwise promotes metallicity
in bulk graphene. At the same time, roughness at the edges washes out chiral
signatures, making the nanoribbon width the principal arbiter of metallicity.
The width-dependent conductivity allows the design of a monolithically
patterned wide-narrow-wide all graphene interconnect-channel heterostructure.
In a three-terminal incarnation, this geometry exhibits superior
electrostatics, a correspondingly benign short-channel effect and a reduction
in the contact Schottky barrier through covalent bonding. However, the small
bandgaps make the devices transparent to band-to-band tunneling. Increasing the
gap with width confinement (or other ways to break the sublattice symmetry) is
projected to reduce the mobility even for very pure samples, through a
fundamental asymptotic constraint on the bandstructure. An analogous trade-off,
ultimately between error rate (reliability) and delay (switching speed) can be
projected to persist for all graphitic derivatives. Proceeding thus to a higher
level, a compact model is presented to capture the complex nanoribbon circuits,
culminating in inverter characteristics, design metrics and layout diagrams.Comment: Chapter to be published by Springer Series in Material Science.
  Title: Graphene Nanoelectronics: Metrology, Synthesis, Properties and
  Applications. Editor: Hassan Raz
On the Use of Guards for Logics with Data

International audienceThe notion of orbit finite data monoid was recently introduced by Bojanczyk as an algebraic object for defining recognizable languages of data words. Following Buchi's approach, we introduce the new logic 'rigidly guarded MSO' and show that the data languages definable in this logic are exactly those recognizable by orbit finite data monoids. We also establish, following this time the approach of Schutzenberger, McNaughton and Papert, that the first-order variant of this logic defines exactly the languages recognizable by aperiodic orbit finite data monoids. Finally, we give a variant of the logic that captures the larger class of languages recognized by non-deterministic finite memory automata
Argumentation with Advice

This paper is concerned with rhetorical argumentation that aims to alter the beliefs of the listener, and so to influence his future actions, as opposed to classical argumentation that is concerned with the generation of arguments, usually as logical proofs, for and against a given course of action. Rhetorical argumentation includes rhetoric moves such as Threat, Reward and Appeal. Rhetorical argumentative utterances generated by an agent contribute to the strength of its relationship with the listener. This paper examines advice and the rhetoric particle “I advise you …” that may be used to strengthen such relationships.Peer Reviewe
Semantic contextualisation of social tag-based profiles and item recommendations

Proceedigns of 12th International Conference, EC-Web 2011, Toulouse, France, August 30 - September 1, 2011.The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-23014-1_9We present an approach that efficiently identifies the semantic meanings and contexts of social tags within a particular folksonomy, and exploits them to build contextualised tag-based user and item profiles. We apply our approach to a dataset obtained from Delicious social bookmarking system, and evaluate it through two experiments: a user study consisting of manual judgements of tag disambiguation and contextualisation cases, and an offline study measuring the performance of several tag-powered item recommendation algorithms by using contextualised profiles. The results obtained show that our approach is able to accurately determine the actual semantic meanings and contexts of tag annotations, and allow item recommenders to achieve better precision and recall on their predictions.This work was supported by the Spanish Ministry of Science
and Innovation (TIN2008-06566-C04-02), and the Community of Madrid (CCG10-
UAM/TIC-5877
Interoperability for the design and construction industry through semantic web technology

The domain of architecture, engineering and construction (AEC) has experienced significant improvements with the advent of building information modelling (BIM) applications, which allow AEC specialists to model all information concerning a building design into one three-dimensional building model. Much of these improvements are however generated by the mere availability of such an environment, whereas many more improvements were expected by achieving an appropriate interoperability of information. We are investigating why such an interoperability is not reached fully and consider the semantic web as an alternative approach to reach the targeted interoperability. In this paper, an AEC description framework based on semantic web technology is presented and compared to the BIM approach, after which we indicate how it might solve the issue of interoperability more appropriately. Our evaluation of this investigation indicates the semantic web approach as a valid alternative approach, although considerably more research is needed to show it capable of providing the targeted interoperability of information in the AEC domain
Application and evaluation of inductive reasoning methods for the semantic web and software analysis

Exploiting the complex structure of relational data enables to build better models by taking into account the additional information provided by the links between objects. We extend this idea to the Semantic Web by introducing our novel SPARQL-ML approach to perform data mining for Semantic Web data. Our approach is based on traditional SPARQL and statistical relational learning methods, such as Relational Probability Trees and Relational Bayesian Classifiers. We analyze our approach thoroughly conducting four sets of experiments on synthetic as well as real-world data sets. Our analytical results show that our ap- proach can be used for almost any Semantic Web data set to perform instance-based learning and classification. A comparison to kernel methods used in Support Vector Machines even shows that our approach is superior in terms of classification accuracy
Indexing Finite Language Representation of Population Genotypes

With the recent advances in DNA sequencing, it is now possible to have
complete genomes of individuals sequenced and assembled. This rich and focused
genotype information can be used to do different population-wide studies, now
first time directly on whole genome level. We propose a way to index population
genotype information together with the complete genome sequence, so that one
can use the index to efficiently align a given sequence to the genome with all
plausible genotype recombinations taken into account. This is achieved through
converting a multiple alignment of individual genomes into a finite automaton
recognizing all strings that can be read from the alignment by switching the
sequence at any time. The finite automaton is indexed with an extension of
Burrows-Wheeler transform to allow pattern search inside the plausible
recombinant sequences. The size of the index stays limited, because of the high
similarity of individual genomes. The index finds applications in variation
calling and in primer design. On a variation calling experiment, we found about
1.0% of matches to novel recombinants just with exact matching, and up to 2.4%
with approximate matching.Comment: This is the full version of the paper that was presented at WABI
  2011. The implementation is available at
  http://www.cs.helsinki.fi/group/suds/gcsa
When Both Transmitting and Receiving Energies Matter: An Application of Network Coding in Wireless Body Area Networks

A network coding scheme for practical implementations of wireless body area networks is presented, with the objective of providing reliability under low-energy constraints. We propose a simple network layer protocol for star networks, adapting redundancy based on both transmission and reception energies for data and control packets, as well as channel conditions. Our numerical results show that even for small networks, the amount of energy reduction achievable can range from 29% to 87%, as the receiving energy per control packet increases from equal to much larger than the transmitting energy per data packet. The achievable gains increase as a) more nodes are added to the network, and/or b) the channels seen by different sensor nodes become more asymmetric.February 25, 2011Georgia Institute of Technology (Subcontract RA306-S1)European Commission (N-Crave Project) (Grant FP7-INFSO-ICT-215252
Energy-Aware Hardware Implementation of Network Coding

In the last few years, Network Coding (NC) has been shown to provide several advantages, both in theory and in practice. However, its applicability to battery-operated systems under strict power constraints has not been proven yet, since most implementations are based on high-end CPUs and GPUs. This work represents the first effort to bridge NC theory with real-world, low-power applications. In this paper, we provide a detailed analysis on the energy consumption of NC, based on VLSI design measurements, and an approach for specifying optimal algorithmic parameters, such as field size, minimizing the required energy for both transmission and coding of data. Our custom, energy-aware NC accelerator proves the feasibility of incorporating NC into modern, low-power systems; the proposed architecture achieves a coding throughput of 80MB/s (60MB/s), while consuming 22uW (12.5mW) for the encoding (decoding) process.Georgia Institute of Technology (Award 017894-010
Greedy versus Dynamic Channel Aggregation Strategy in CRNs: Markov Models and Performance Evaluation

Publishes version of a paper from the book: Networking 2011 Workshops. Also available f rom the publisher on SpringLink:http://dx.doi.org/10.1007/978-3-642-23041-7_3In cognitive radio networks, channel aggregation techniques which aggregate several channels together as one channel have been proposed in many MAC protocols. In this paper, we consider elastic data traffic and spectrum adaptation for channel aggregation, and propose two new strategies named as Greedy and Dynamic respectively. The performance of channel aggregation represented by these strategies is evaluated using continuous time Markov chain models. Moreover, simulation results based on various traffic distributions are utilized in order to evaluate the validity and preciseness of the mathematical models
Techno-economic evaluation of cognitive radio in a factory scenario

Wireless applications gradually enter every aspect of our life. Unfortunately, these applications must reuse the same scarce spectrum, resulting in increased interference and limited usability. Cognitive Radio proposes to mitigate this problem by adapting the operational parameters of wireless devices to varying interference conditions. However, it involves an increase in cost. In this paper we examine the economic balance between the added cost and the increased usability in one particular real-life scenario. We focus on the production floor of an industrial installation where wireless sensors monitor production machinery, and a wireless LAN is used as the data backbone. We examine the effects of implementing dynamic spectrum access by means of ideal RE sensing, and model the benefit in terms of increased reliability and battery lifetime. We estimate the financial cost of interference and the potential gain, and conclude that cognitive radio can bring business gains in real-life applications
A new multicast opportunistic routing protocol for wireless mesh networks

Opportunistic Routing (OR) has been proposed to improve the efficiency of unicast protocols in wireless networks. In contrast to traditional routing, instead of preselecting a single specific node to be the next-hop forwarder, an ordered set of nodes (referred to as candidates) is selected as the next-hop potential forwarders. In this paper, we propose a new multicast routing protocol based on OR for wireless mesh networks, named Multicast OR Protocol (MORP). We compare our proposal with the well known ODMRP Multicast protocol. Our results show that Multicast-OR outperforms ODMRP, reducing the number of transmissions and increasing the packet delivery ratio.Peer ReviewedPostprint (author's final draft
Heparin and Heparan Sulfate: Analyzing Structure and Microheterogeneity [chapter]

The structural microheterogeneity of heparin and heparan sulfate is one of the major reasons for the multifunctionality exhibited by this class of molecules. In a physiological context, these molecules primarily exert their effects extracellularly by mediating key processes of cellular cross-talk and signaling leading to the modulation of a number of different biological activities including development, cell proliferation, and inflammation. This structural diversity is biosynthetically imprinted in a nontemplate-driven manner and may also be dynamically remodeled as cellular function changes. Understanding the structural information encoded in these molecules forms the basis for attempting to understand the complex biology they mediate. This chapter provides an overview of the origin of the structural microheterogeneity observed in heparin and heparan sulfate, and the orthogonal analytical methodologies that are required to help decipher this information.available in PMC 2013 August 2
Clone detection in repositories of business process models

As organizations reach to higher levels of business process management maturity, they often find themselves maintaining repositories of hundreds or even thousands of process models, representing valuable knowledge about their\ud
operations. Over time, process model repositories tend to accumulate duplicate fragments (also called clones) as new process models are created or extended by copying and merging fragments from other models. This calls for methods to detect clones in process models, so that these clones can be refactored as separate subprocesses in order to improve maintainability. This paper presents an indexing\ud
structure to support the fast detection of clones in large process model repositories. The proposed index is based on a novel combination of a method for process model decomposition (specifically the Refined Process Structure Tree), with established graph canonization and string matching techniques. Experiments show that the algorithm scales to repositories with hundreds of models. The experimental results also show that a significant number of non-trivial clones can be found in process model repositories taken from industrial practice
On the Beneﬁts of Transparent Compression for Cost-Effective Cloud Data Storage

International audienceInfrastructure-as-a-Service (IaaS) cloud computing has revolutionized the way we think of acquiring computational resources: it allows users to deploy virtual machines (VMs) at large scale and pay only for the resources that were actually used throughout the runtime of the VMs. This new model raises new challenges in the design and development of IaaS middleware: excessive storage costs associated with both user data and VM images might make the cloud less attractive, especially for users that need to manipulate huge data sets and a large number of VM images. Storage costs result not only from storage space utilization, but also from bandwidth consumption: in typical deployments, a large number of data transfers between the VMs and the persistent storage are performed, all under high performance requirements. This paper evaluates the trade-oﬀ resulting from transparently applying data compression to conserve storage space and bandwidth at the cost of slight computational overhead. We aim at reducing the storage space and bandwidth needs with minimal impact on data access performance. Our solution builds on BlobSeer, a distributed data management service speciﬁcally designed to sustain a high throughput for concurrent accesses to huge data sequences that are distributed at large scale. Extensive experiments demonstrate that our approach achieves large reductions (at least 40%) of bandwidth and storage space utilization, while still attaining high performance levels that even surpass the original (no compression) performance levels in several data-intensive scenarios
Replication in DHTs using Dynamic Groups

International audienceDistributed Hash Tables (DHTs) provide an efficient solution for data location and lookup in large-scale P2P systems. However, it is up to the applications to deal with the availability of the data they store in the DHT, e.g. via replication. To improve data availability, most DHT applications rely on data replication. However, efficient replication management is quite challenging, in particular because of concurrent and missed updates. In this paper, we propose a complete solution to data replication in DHTs. We propose a new service, called Continuous Timestamp based Replication Management (CTRM), which deals with the efficient storage, retrieval and updating of replicas in DHTs. In CTRM, the replicas are maintained by groups of peers which are determined dynamically using a hash function. To perform updates on replicas, we propose a new protocol that stamps the updates with timestamps that are generated in a distributed fashion using the dynamic groups. Timestamps are not only monotonically increasing but also continuous, i.e. without gap. The property of monotonically increasing allows applications to determine a total order on updates. The other property, i.e. continuity, enables applications to deal with missed updates. We evaluated the performance of our solution through simulation and experimentation. The results show its effectiveness for replication management in DHTs
Quantitative Information Flow and Applications to Differential Privacy

International audienceSecure information flow is the problem of ensuring that the information made publicly available by a computational system does not leak information that should be kept secret. Since it is practically impossible to avoid leakage entirely, in recent years there has been a growing interest in considering the quantitative aspects of information flow, in order to measure and compare the amount of leakage. Information theory is widely regarded as a natural framework to provide firm foundations to quantitative information flow. In this notes we review the two main information-theoretic approaches that have been investigated: the one based on Shannon entropy, and the one based on Rényi min-entropy. Furthermore, we discuss some applications in the area of privacy. In particular, we consider statistical databases and the recently-proposed notion of differential privacy. Using the information-theoretic view, we discuss the bound that differential privacy induces on leakage, and the trade-off between utility and privac
Data Integration over NoSQL Stores Using Access Path Based Mappings

International audienceDue to the large amount of data generated by user interactions on the Web, some companies are currently innovating in the domain of data management by designing their own systems. Many of them are referred to as NoSQL databases, standing for 'Not only SQL'. With their wide adoption will emerge new needs and data integration will certainly be one of them. In this paper, we adapt a framework encountered for the integration of relational data to a broader context where both NoSQL and relational databases can be integrated. One important extension consists in the efficient answering of queries expressed over these data sources. The highly denormalized aspect of NoSQL databases results in varying performance costs for several possible query translations. Thus a data integration targeting NoSQL databases needs to generate an optimized translation for a given query. Our contributions are to propose (i) an access path based mapping solution that takes benefit of the design choices of each data source, (ii) integrate preferences to handle conflicts between sources and (iii) a query language that bridges the gap between the SQL query expressed by the user and the query language of the data sources. We also present a prototype implementation, where the target schema is represented as a set of relations and which enables the integration of two of the most popular NoSQL database models, namely document and a column family stores
Towards an On-Line Analysis of Tweets Processing

International audienceTweets exchanged over the Internet represent an important source of information, even if their characteristics make them dicult to analyze (a maximum of 140 characters, etc.). In this paper, we define a data warehouse model to analyze large volumes of tweets by proposing measures relevant in the context of knowledge discovery. The use of data warehouses as a tool for the storage and analysis of textual documents is not new but current measures are not well-suited to the specificities of the manipulated data. We also propose a new way for extracting the context of a concept in a hierarchy. Experiments carried out on real data underline the relevance of our proposal
Twig Pattern Matching: A Revisit

Twig pattern matching plays a crucial role in xml query processing.  In order to reduce the processing time, some existing holistic one phase  twig pattern matching algorithms (e.g., HolisticTwigStack [3],  TwigFast [5], etc) use the core function getNext of TwigStack [2] to effectively  and efficiently filter out the useless elements. However, using  getNext as a filter may incur other redundant computation. We propose  two approaches, namely re-test checking and forward-to-end, which can  avoid the redundant computation and can be easily applied to both holistic  one-phase and two-phase algorithms. The experiments show that our  approach can significantly improve the efficiency by avoiding the redundant  computation.Griffith Sciences, School of Information and Communication TechnologyFull Tex
Efficient and Robust Alignment of Unsynchronized Video Sequences

International audienceThis paper addresses the problem of aligning two unsynchronized video sequences. We present a novel approach that allows for temporal and spa- tial alignment of similar videos captured from independently moving cameras. The goal is to synchronize two videos of a scene such that changes between the videos can be detected automatically. This aims at applications in driver assis- tance or surveillance systems but we also envision applications in map building. Our approach is novel in that it adapts an efficient information retrieval frame- work to a computer vision problem. In addition, we extend the recent ECC image- alignment algorithm to the temporal dimension in order to improve spatial regis- tration and enable synchro refinement. Experiments with traffic videos recorded by in-vehicle cameras demonstrate the efficiency of the proposed method and verify its effectiveness with respect to spatio-temporal alignment accuracy