pinecone/core-2020-05-10-deduplication huggingface dataset:
A Fuzzy Social Network Analysis Method and a Case Study on Tianya

Social networking service (SNS) has become online service platforms that focus on facilitating the building of social networks among people who share interests, activities, backgrounds, or real-life connections and has had a rapid development in China in the past few years. This paper aims to develop a fuzzy social network service analysis method, which combines graph theory with related fuzzy approach, to analyze the social network structural features and the distribution characteristics of interpersonal nodes in SNS community. A case study on a very famous Chinese tourism BBS-Tianya-is conducted to illustrate and validate the proposed approach. The research findings are as follows: (1) The attraction degrees of various areas in the forum are significantly different; (2) interpersonal nodes in the forum are concentrated relatively; (3) the fuzzy out-degrees and the fuzzy in-degrees of interpersonal nodes in the forum conflict each other; and (4) the distribution of interpersonal nodes is influenced by geographical relations. These findings can directly support social network service management and particularly tourism online service developments. © Springer-Verlag Berlin Heidelberg 2014
Combining word semantics within complex Hilbert space for information retrieval

Complex numbers are a fundamental aspect of the mathematical formalism of quantum physics. Quantum-like models developed outside physics often overlooked the role of complex numbers. Specifically, previous models in Information Retrieval (IR) ignored complex numbers. We argue that to advance the use of quantum models of IR, one has to lift the constraint of real-valued representations of the information space, and package more information within the representation by means of complex numbers. As a first attempt, we propose a complex-valued representation for IR, which explicitly uses complex valued Hilbert spaces, and thus where terms, documents and queries are represented as complex-valued vectors. The proposal consists of integrating distributional semantics evidence within the real component of a term vector; whereas, ontological information is encoded in the imaginary component. Our proposal has the merit of lifting the role of complex numbers from a computational byproduct of the model to the very mathematical texture that unifies different levels of semantic information. An empirical instantiation of our proposal is tested in the TREC Medical Record task of retrieving cohorts for clinical studies
Quantum Mechanics: Harbinger of a Non-Commutative Probability Theory?

In this paper we discuss the relevance of the algebraic approach to quantum
phenomena first introduced by von Neumann before he confessed to Birkoff that
he no longer believed in Hilbert space. This approach is more general and
allows us to see the structure of quantum processes in terms of non-commutative
probability theory, a non-Boolean structure of the implicate order which
contains Boolean sub-structures which accommodates the explicate classical
world. We move away from mechanical `waves' and `particles' and take as basic
what Bohm called a {\em structure process}. This enables us to learn new
lessons that can have a wider application in the way we think of structures in
language and thought itself.Comment: 20 pages, one figure. Invited pape
Aggregation of Statistical Data from Passive Probes: Techniques and Best Practices

Passive probes continuously generate statistics on large number of metrics, that are possibly represented as probability mass functions (pmf). The need for consolidation of several pmfs arises in two contexts, namely: (i) whenever a central point collects and aggregates measurement of multiple disjoint vantage points, and (ii) whenever a local measurement processed at a single vantage point needs to be distributed over multiple cores of the same physical probe, in order to cope with growing link capacity. In this work, we take an experimental approach and study both cases using, whenever possible, open source software and datasets. Considering different consolidation strategies, we assess their accuracy in estimating pmf deciles (from the 10th to the 90th) of diverse metrics, obtaining general design and tuning guidelines. In our dataset, we find that Monotonic Spline Interpolation over a larger set of percentiles (e.g., adding 5th, 10th, 15th, and so on) allow fairly accurate pmf consolidation in both the multiple vantage points (median error is about 1%, maximum 30%) and local processes (median 0.1%, maximum 1%) case
Gold Mining in a River of Internet Content Traffic

With the advent of Over-The-Top content providers (OTTs), Internet Service Providers (ISPs) saw their portfolio of services shrink to the low margin role of data transporters. In order to counter this effect, some ISPs started to follow big OTTs like Facebook and Google in trying to turn their data into a valuable asset. In this paper, we explore the questions of what meaningful information can be extracted from network data, and what interesting insights it can provide. To this end, we tackle the first challenge of detecting "user-URLs", i.e., those links that were clicked by users as opposed to those objects automatically downloaded by browsers and applications. We devise algorithms to pinpoint such URLs, and validate them on manually collected ground truth traces. We then apply them on a three-day long traffic trace spanning more than 19,000 residential users that generated around 190 million HTTP transactions. We find that only 1.6% of these observed URLs were actually clicked by users. As a first application for our methods, we answer the question of which platforms participate most in promoting the Internet content. Surprisingly, we find that, despite its notoriety, only 11% of the user URL visits are coming from Google Searc
On the Ideal Ratio Mask as the Goal of Computational Auditory Scene Analysis

The ideal binary mask (IBM) is widely considered to be the benchmark for time–frequency-based sound source separation techniques such as computational auditory scene analysis (CASA). However, it is well known that binary masking introduces objectionable distortion, especially musical noise. This can make binary masking unsuitable for sound source separation applications where the output is auditioned. It has been suggested that soft masking reduces musical noise and leads to a higher quality output. A previously defined soft mask, the ideal ratio mask (IRM), is found to have similar properties to the IBM, may correspond more closely to auditory processes, and offers additional computational advantages. Consequently, the IRM is proposed as the goal of CASA. To further support this position, a number of studies are reviewed that show soft masks to provide superior performance to the IBM in applications such as automatic speech recognition and speech intelligibility. A brief empirical study provides additional evidence demonstrating the objective and perceptual superiority of the IRM over the IBM
Understanding eParticipation services in indonesian local government

Published version of a chapter in the book: Information and Communication Technology. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-55032-4_32This study aims at understanding how local government from a developing country, in this case Indonesia, implement and manage eParticipation services. In doing so, we combine institutional theory and stakeholder theory to build a sharper analytical lens. From an interpretive case study in the city of Yogyakarta, we reveal the institutionalization process of the services since their inception and identify major stakeholders and their salience. Based on our findings, we propose implications for practice and suggest implications for further research. Future work, based on a multiple case strategy including several eParticipation cases from other parts of Indonesia, will further explore the findings reported here
ESSVCS: an enriched secret sharing visual cryptography

Visual Cryptography (VC) is a powerful technique that combines the notions of perfect ciphers and secret sharing in cryptography with that of raster graphics. A binary image can be divided into shares that are able to be stacked together so as to approximately recover the original image. VC is a unique technique in the sense that the encrypted message can be decrypted directly by the Human Visual System (HVS). The distinguishing characteristic of VC is the ability of secret restoration without the use of computation. However because of restrictions of the HVS, pixel expansion and alignment problems, a VC scheme perhaps can only be applied to share a small size of secret image. In this paper, we present an Enriched Secret Sharing Visual Cryptography Scheme (ESSVCS) to let the VC shares carry more secrets, the technique is to use cypher output of private-key systems as the input random numbers of VC scheme, meanwhile the encryption key could be shared, the shared keys could be associated with the VC shares. After this operation, VC scheme and secret sharing scheme are merged with the private-key system. Under this design, we implement a (k; t; n)-VC scheme. Compared to those existing schemes, our scheme could greatly enhance the ability of current VC schemes and could cope with pretty rich secrets
A layered approach to managing risks in OSS projects

In this paper, we propose a layered approach to managing risks in OSS projects. We define three layers: the first one for defining risk drivers by collecting and summarising available data from different data sources, including human-provided contextual information; the second layer, for converting these risk drivers into risk indicators; the third layer for assessing how these indicators impact the business of the adopting organisation. The contributions are: 1) the complexity of gathering data is isolated in one layer using appropriate techniques, 2) the context needed to interpret this data is provided by expert involvement evaluating risk scenarios and answering questionnaires in a second layer, 3) a pattern-based approach and risk reasoning techniques to link risks to business goals is proposed in the third layer.Peer ReviewedPostprint (author’s final draft
Reactive Statistical Mapping: Towards the Sketching of Performative Control with Data

Part 1: Fundamental IssuesInternational audienceThis paper presents the results of our participation to the ninth eNTERFACE workshop on multimodal user interfaces. Our target for this workshop was to bring some technologies currently used in speech recognition and synthesis to a new level, i.e. being the core of a new HMM-based mapping system. The idea of statistical mapping has been investigated, more precisely how to use Gaussian Mixture Models and Hidden Markov Models for realtime and reactive generation of new trajectories from inputted labels and for realtime regression in a continuous-to-continuous use case. As a result, we have developed several proofs of concept, including an incremental speech synthesiser, a software for exploring stylistic spaces for gait and facial motion in realtime, a reactive audiovisual laughter and a prototype demonstrating the realtime reconstruction of lower body gait motion strictly from upper body motion, with conservation of the stylistic properties. This project has been the opportunity to formalise HMM-based mapping, integrate various of these innovations into the Mage library and explore the development of a realtime gesture recognition tool
Laugh When You’re Winning

Part 1: Fundamental IssuesInternational audienceDeveloping virtual characters with naturalistic game playing capabilities is an increasingly researched topic in Human-Computer Interaction. Possible roles for such characters include virtual teachers, personal care assistants, and companions for children. Laughter is an under-investigated emotional expression both in Human-Human and Human-Computer Interaction. The EU Project ILHAIRE, aims to study this phenomena and endow machines with laughter detection and synthesis capabilities. The Laugh when you’re winning project, developed during the eNTERFACE 2013 Workshop in Lisbon, Portugal, aimed to set up and test a game scenario involving two human participants and one such virtual character. The game chosen, the yes/no game, induces natural verbal and non-verbal interaction between participants, including frequent hilarious events, e.g., one of the participants saying “yes” or “no” and so losing the game. The setup includes software platforms, developed by the ILHAIRE partners, allowing automatic analysis and fusion of human participants’ multimodal data (voice, facial expression, body movements, respiration) in real-time to detect laughter. Further, virtual characters endowed with multimodal skills were synthesised in order to interact with the participants by producing laughter in a natural way
Modeling Data Center Building Blocks for Energy-efficiency and Thermal Simulations

In this paper we present a concept and specification of Data Center Efficiency Building Blocks (DEBBs), which represent hardware components of a data center complemented by descriptions of their energy efficiency. Proposed building blocks contain hardware and thermodynamic models that can be applied to simulate a data center and to evaluate its energy efficiency. DEBBs are available in an open repository being built by the CoolEmAll project. In the paper we illustrate the concept by an example of DEBB defined for the RECS multi-server system including models of its power usage and thermodynamic properties. We also show how these models are affected by specific architecture of modeled hardware and differences between various classes of applications. Proposed models are verified by a comparison to measurements on a real infrastructure. Finally, we demonstrate how DEBBs are used in data center simulations
The macroeconomic and financial effects of oil price shocks

The oil price shock is considered as a major contributor to economic fluctuation. In this paper, we investigate whether the impulse responses of different macroeconomic variables and financial variables to the oil price shock and the effect of interest rates change. And we also use Granger Causality Test to evaluate the correlation between oil prices, stock markets and gold prices. Estimation results based on the U.S. data suggest that: (i) The oil price shock has a significant impact on inflation, stock markets and gold prices and it also has a short-term impact on interest rates. (ii) Co-movement of oil prices, stock markets and gold prices exist. (iii) Changing interest rates as monetary policy can induce price puzzle in order to reduce the inflation caused by the oil price shock.
Analysis of Partitioning Models and Metrics in Parallel Sparse Matrix-Vector Multiplication

International audienceGraph/hypergraph partitioning models and methods have been successfully used to minimize the communication among processors in several parallel computing applications. Parallel sparse matrix-vector multiplication (SpMxV) is one of the representative applications that renders these models and methods indispensable in many scientific com- puting contexts. We investigate the interplay of the partitioning metrics and execution times of SpMxV implementations in three libraries: Trilinos, PETSc, and an in-house one. We carry out experiments with up to 512 processors and investigate the results with regression analysis. Our experiments show that the partitioning metrics influence the perfor- mance greatly in a distributed memory setting. The regression analyses demonstrate which metric is the most influential for the execution time of the libraries
A parallel, distributed-memory framework for comparative motif discovery

The increasing number of sequenced organisms has opened new possibilities for the computational discovery of cis-regulatory elements ('motifs') based on phylogenetic footprinting. Word-based, exhaustive approaches are among the best performing algorithms, however, they pose significant computational challenges as the number of candidate motifs to evaluate is very high. In this contribution, we describe a parallel, distributed-memory framework for de novo comparative motif discovery. Within this framework, two approaches for phylogenetic footprinting are implemented: an alignment-based and an alignment-free method. The framework is able to statistically evaluate the conservation of motifs in a search space containing over 160 million candidate motifs using a distributed-memory cluster with 200 CPU cores in a few hours. Software available from http://bioinformatics.intec.ugent.be/blsspeller
Neighborhood Selection and Rules Identification for Cellular Automata: A
  Rough Sets Approach

In this paper a method is proposed which uses data mining techniques based on
rough sets theory to select neighborhood and determine update rule for cellular
automata (CA). According to the proposed approach, neighborhood is detected by
reducts calculations and a rule-learning algorithm is applied to induce a set
of decision rules that define the evolution of CA. Experiments were performed
with use of synthetic as well as real-world data sets. The results show that
the introduced method allows identification of both deterministic and
probabilistic CA-based models of real-world phenomena.Comment: 11 pages, 3 figure
Faster Compact Diffie-Hellman: Endomorphisms on the x-line

International audienceWe describe an implementation of fast elliptic curve scalar multiplication, optimized for Diffie--Hellman Key Exchange at the 128-bit security level. The algorithms are compact (using only x-coordinates), run in constant time with uniform execution patterns, and do not distinguish between the curve and its quadratic twist; they thus have a built-in measure of side-channel resistance. The core of our construction is a suite of two-dimensional differential addition chains driven by efficient endomorphism decompositions, built on curves selected from a family of Q-curve reductions over \(\FF_{p^2}\) with \(p = 2^{127}-1\). We include state-of-the-art experimental results for twist-secure, constant-time, x-coordinate-only scalar multiplication
Symmetrized summation polynomials: using small order torsion points to speed up elliptic curve index calculus

International audienceDecomposition-based index calculus methods are currently efficient only for elliptic curves E defined over non-prime finite fields of very small extension degree n. This corresponds to the fact that the Semaev summation polynomials, which encode the relation search (or “sieving”), grow over-exponentially with n. Actually, even their computation is a first stumbling block and the largest Semaev polynomial ever computed is the 6-th. Following ideas from Faugère, Gaudry, Huot and Renault, our goal is to use the existence of small order torsion points on E to define new summation polynomials whose symmetrized expressions are much more compact and easier to compute. This setting allows to consider smaller factor bases, and the high sparsity of the new summation polynomials provides a very efficient decomposition step. In this paper the focus is on 2-torsion points, as it is the most important case in practice. We obtain records of two kinds: we successfully compute up to the 8-th symmetrized summation polynomial and give new timings for the computation of relations with degree 5 extension fields
Fully Key-Homomorphic Encryption, Arithmetic Circuit ABE and Compact Garbled Circuits

We construct the first (key-policy) attribute-based encryption (ABE) system with short secret keys: the size of keys in our system depends only on the depth of the policy circuit, not its size. Our constructions extend naturally to arithmetic circuits with arbitrary fan-in gates thereby further reducing the circuit depth. Building on this ABE system we obtain the first reusable circuit garbling scheme that produces garbled circuits whose size is the same as the original circuit plus an additive poly(λ,d) bits, where λ is the security parameter and d is the circuit depth. All previous constructions incurred a multiplicative poly(λ) blowup.
We construct our ABE using a new mechanism we call fully key-homomorphic encryption, a public-key system that lets anyone translate a ciphertext encrypted under a public-key x into a ciphertext encrypted under the public-key (f(x),f) of the same plaintext, for any efficiently computable f. We show that this mechanism gives an ABE with short keys. Security of our construction relies on the subexponential hardness of the learning with errors problem.
We also present a second (key-policy) ABE, using multilinear maps, with short ciphertexts: an encryption to an attribute vector x is the size of x plus poly(λ,d) additional bits. This gives a reusable circuit garbling scheme where the garbled input is short.United States. Defense Advanced Research Projects Agency (Grant FA8750-11-2-0225)Alfred P. Sloan Foundation (Sloan Research Fellowship
Out-of-core solution of eigenproblems for\ud
macromolecular simulations

We consider the solution of large-scale eigenvalue problems that appear in the motion simulation of complex macromolecules on desktop platforms. To tackle the dimension of the matrices that are involved in these problems, we formulate out-of-core (OOC) variants of the two selected eigensolvers, that basically decouple the performance of the solver from the storage capacity. Furthermore, we contend with the high\ud
computational complexity of the solvers by off-loading the arithmetically-intensive parts of the algorithms to a hardware graphics accelerator
The Energy/Frequency Convexity Rule: Modeling and Experimental Validation on Mobile Devices

International audienceThis paper provides both theoretical and experimental evidence for the existence of an Energy/Frequency Convexity Rule, which relates energy consumption and CPU frequency on mobile devices. We monitored a typical smartphone running a speci c computing-intensive kernel of multiple nested loops written in C using a high-resolution power gauge. Data gathered during a week-long acquisition campaign suggest that energy consumed per input element is strongly correlated with CPU frequency, and, more interestingly, the curve exhibits a clear minimum over a 0.2 GHz to 1.6 GHz window. We provide and motivate an analytical model for this behavior, which ts well with the data. Our work should be of clear interest to researchers focusing on energy usage and minimization for mobile devices, and provide new insights for optimization opportunities
Hybrid Mechanical Systems

We discuss hybrid systems in which a mechanical oscillator is coupled to
another (microscopic) quantum system, such as trapped atoms or ions,
solid-state spin qubits, or superconducting devices. We summarize and compare
different coupling schemes and describe first experimental implementations.
Hybrid mechanical systems enable new approaches to quantum control of
mechanical objects, precision sensing, and quantum information processing.Comment: To cite this review, please refer to the published book chapter (see
  Journal-ref and DOI). This v2 corresponds to the published versio
Developments in statistical evaluation of clinical trials

This book describes various ways of approaching and interpreting the data produced by clinical trial studies, with a special emphasis on the essential role that biostatistics plays in clinical trials. Over the past few decades the role of statistics in the evaluation and interpretation of clinical data has become of paramount importance. As a result the standards of clinical study design, conduct and interpretation have undergone substantial improvement. The book includes 18 carefully reviewed chapters on recent developments in clinical trials and their statistical evaluation, with each chapter providing one or more examples involving typical data sets, enabling readers to apply the proposed procedures. The chapters employ a uniform style to enhance comparability between the approaches