pinecone/core-2020-05-10-deduplication huggingface dataset:
Professional Trajectories of Workers Using Disconnected Self-Organizing Maps

International audienceUsing the Panel Study of Income Dynamics (PSID) collected on the period 1984-2003, we study the situations of American workers with respect to employment. The data include all heads of household (men or women) as well as the partners who are on the labor market, working or not. They are extracted from the complete survey by computing a few relevant features which characterize the worker's situations. To perform this analysis, we suggest to use a Self-Organizing Map (Kohonen algorithm) with specific topology. In this paper we present a new topology for SOM based on a planar graph with disconnected components (called D-SOM) which is especially interesting for clustering. Each component takes the form of a string and corresponds to an organized cluster. From this clustering, we study the dynamics at the individual level, that is the trajectories of the individuals among the classes during the observed period. Then we estimate the transition probability matrices for each studied year and the corresponding stationary distributions. Finally, we try to give an answer to the question: is there a significant change in 1992 (new economic policies after the Reaganomics)
Paths and shortcuts in an event-oriented ontology

International audienceThe CIDOC CRM is an event-oriented ontology used in cultural heritage documentation. Events are temporal entities that are used as hooks for relating persistent entities. However end-users are relating persistent entities in a direct manner (e.g. J.R.R. Tolkien wrote Bilbo the Hobbit) and skip the path through a temporal entity. Fauconnier and Turner suggest that human conscious thinking tends to compress complex paths into simpler relationships, despite still knowing subconsciously about the complete paths. This paper presents two prototypical approaches yielding compression and decompression to the end-user, shortcuts implementation in Semantic Media Wiki and ontology path features in the WissKI system. Lessons learned yield research perspectives about identification, names, end-user usability, and event pattern heuristics
Hot topic detection in news blogs from the perspective of W2T

News blog hot topics are important for the information recommendation service and marketing. However, information overload and personalized management make the information arrangement more difficult. Moreover, what influences the formation and development of blog hot topics is seldom paid attention to. In order to correctly detect news blog hot topics, the paper first analyzes the development of topics in a new perspective based on W2T (Wisdom Web of Things) methodology. Namely, the characteristics of blog users, context of topic propagation and information granularity are unified to analyze the related problems. Some factors such as the user behavior pattern, network opinion and opinion leader are subsequently identified to be important for the development of topics. Then the topic model based on the view of event reports is constructed. At last, hot topics are identified by the duration, topic novelty, degree of topic growth and degree of user attention. The experimental results show that the proposed method is feasible and effective
Universal point subsets for planar graphs

A set S of k points in the plane is a universal point subset for a class G of planar graphs if every graph belonging to G admits a planar straight-line drawing such that k of its vertices are represented by the points of S . In this paper we study the following main problem: For a given class of graphs, what is the maximum k such that there exists a universal point subset of size k ? We provide a ⌈ √ n ⌉ lower bound on k for the class of planar graphs with n ver- tices. In addition, we consider the value F ( n; G ) such that every set of F ( n; G ) points in general position is a universal subset for all graphs with n vertices be- longing to the family G , and we establish upper and lower bounds for F ( n; G ) for different families of planar graphs, including 4-connected planar graphs and nested-triangles graphs.Peer ReviewedPostprint (author’s final draft
Algorithmic Aspects of the Intersection and Overlap Numbers of a Graph

International audienceThe intersection number of a graph G is the minimum size of a set S such that G is an intersection graph of some family of subsets F⊆2^S. The overlap number of G is defined similarly, except that G is required to be an overlap graph of F. Computing the overlap number of a graph has been stated as an open problem in [B. Rosgen and L. Stewart, 2010, arXiv:1008.2170v2] and [D.W. Cranston, et al., J. Graph Theory., 2011]. In this paper we show two algorithmic aspects concerning both these graph invariants. On the one hand, we show that the corresponding optimization problems associated with these numbers are both APX-hard, where for the intersection number our results hold even for biconnected graphs of maximum degree 7, strengthening the previously known hardness result. On the other hand, we show that the recognition problem for any specific intersection graph class (e.g. interval, unit disc, ...) is easy when restricted to graphs with fixed intersection number
Highly analysable, reusable, and realisable architectural designs with XCD

Connector-Centric Design (XcD) is a new approach to specifying software architectures. XcD views complex connectors as highly significant in architectural designs, as it is the complex connectors that non-functional quality properties in systems can emanate from. So, XcD promotes in designs a clean separation of connectors (interaction behaviours) from components (functional behaviours). Designers can then specify connectors in detail explicitly thus easing the analysis of system designs for quality properties. Furthermore, XcD separates control behaviour from connectors as control strategies. Architectural designs in XcD thus become highly modular with re-usable components, connectors, and control strategies (representing design solutions for quality properties). The end result is the eased architectural experimentation with different design solutions by re-using components/connectors and formal analysis of these solutions to find out the optimal ones
Augmented interface systems for the Darcy-Stokes problem

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-35275-1_48In this paper we study interface equations associated to the Darcy-Stokes problem\ud
using the classical Steklov-Poincaré approach and a new one called augmented. We compare\ud
these two families of methods and characterize at the discrete level suitable preconditioners\ud
with additive and multiplicative structures. Finally, we present some numerical results to assess\ud
their behavior in presence of small physical parameters
Learning Feature Hierarchies with Centered Deep Boltzmann Machines

Deep Boltzmann machines are in principle powerful models for extracting the
hierarchical structure of data. Unfortunately, attempts to train layers jointly
(without greedy layer-wise pretraining) have been largely unsuccessful. We
propose a modification of the learning algorithm that initially recenters the
output of the activation functions to zero. This modification leads to a better
conditioned Hessian and thus makes learning easier. We test the algorithm on
real data and demonstrate that our suggestion, the centered deep Boltzmann
machine, learns a hierarchy of increasingly abstract representations and a
better generative model of data
Speech Denoising Using Non-Negative Matrix Factorization with Kullback-Leibler Divergence and Sparseness Constraints

Proceedings of: IberSPEECH 2012 Conference, Madrid, Spain, November 21-23, 2012.A speech denoising method based on Non-Negative Matrix Factorization (NMF) is presented in this paper. With respect to previous related works, this paper makes two contributions. First, our method does not assume a priori knowledge about the nature of the noise. Second, it combines the use of the Kullback-Leibler divergence with sparseness constraints on the activation matrix, improving the performance of similar techniques that minimize the Euclidean distance and/or do not consider any sparsification. We evaluate the proposed method for both, speech enhancement and automatic speech recognitions tasks, and compare it to conventional spectral subtraction, showing improvements in speech quality and recognition accuracy, respectively, for different noisy conditions.This work has been partially supported by the Spanish Government grants TSI-020110-2009-103 and TEC2011-26807.Publicad
Cepstral trajectories in linguistic units for text-independent speaker recognition

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-35292-8_3Proceedings of IberSPEECH, held in Madrid (Spain) on 2012.In this paper, the contributions of different linguistic units to the speaker recognition task are explored by means of temporal trajectories of their MFCC features. Inspired by successful work in forensic speaker identification, we extend the approach based on temporal contours of formant frequencies in linguistic units to design a fully automatic system that puts together both forensic and automatic speaker recognition worlds. The combination of MFCC features and unit-dependent trajectories provides a powerful tool to extract individualizing information. At a fine-grained level, we provide a calibrated likelihood ratio per linguistic unit under analysis (extremely useful in applications such as forensics), and at a coarse-grained level, we combine the individual contributions of the different units to obtain a highly discriminative single system. This approach has been tested with NIST SRE 2006 datasets and protocols, consisting of 9,720 trials from 219 male speakers for the 1side-1side English-only task, and development data being extracted from 367 male speakers from 1,808 conversations from NIST SRE 2004 and 2005 datasetsSupported by MEC grant PR-2010-123, MICINN project TEC09-14179, ForBayes project CCG10-UAM/TIC-5792 and Cátedra UAM-Telefónica
Compact Proof Certificates for Linear Logic

International audienceLinear logic is increasingly being used as a tool for communicating reasoning agents in domains such as authorization, access control, electronic voting, etc., where proof certificates represent evidence that must be verified by proof consumers as part of higher protocols. Controlling the size of these certificates is critical. We assume that the proof consumer is allowed to do some search to reconstruct details of the full proof that are omitted from the certificates. Because the decision problem for linear logic is unsolvable, the certificate must contain at least enough information to bound the search: we show how to use the sequence of contractions in the sequent proof for this bound. The remaining content of the proof, in particular the information about resource divisions, can then be omitted from the certificate. We also describe a technique for giving a variable amount of additional search hints to the proof consumer to limit its non-determinism
Optimal Pricing Is Hard

We show that computing the revenue-optimal deterministic auction in unit-demand single-buyer Bayesian settings, i.e. the optimal item-pricing, is computationally hard even in single-item settings where the buyer’s value distribution is a sum of independently distributed attributes, or multi-item settings where the buyer’s values for the items are independent. We also show that it is intractable to optimally price the grand bundle of multiple items for an additive bidder whose values for the items are independent. These difficulties stem from implicit definitions of a value distribution. We provide three instances of how different properties of implicit distributions can lead to intractability: the first is a #P-hardness proof, while the remaining two are reductions from the SQRT-SUM problem of Garey, Graham, and Johnson [14]. While simple pricing schemes can oftentimes approximate the best scheme in revenue, they can have drastically different underlying structure. We argue therefore that either the specification of the input distribution must be highly restricted in format, or it is necessary for the goal to be mere approximation to the optimal scheme’s revenue instead of computing properties of the scheme itself.Microsoft Research (Fellowship)Alfred P. Sloan Foundation (Fellowship)National Science Foundation (U.S.) (CAREER Award CCF-0953960)National Science Foundation (U.S.) (Award CCF-1101491)Hertz Foundation (Daniel Stroock Fellowship
Forming Networks of Strategic Agents with Desired Topologies

Many networks such as social networks and organizational networks in global companies consist of self-interested agents. The topology of these networks often plays a crucial role in important tasks such as information diffusion and information extraction. Consequently, growing a stable network having a certain topology is of interest. Motivated by this, we study the following important problem: given a certain desired network topology, under what conditions would best response (link addition/deletion) strategies played by self-interested agents lead to formation of a stable network having that topology. We study this interesting reverse engineering problem by proposing a natural model of recursive network formation and a utility model that captures many key features. Based on this model, we analyze relevant network topologies and derive a set of sufficient conditions under which these topologies emerge as pairwise stable networks, wherein no node wants to delete any of its links and no two nodes would want to create a link between them
Lower Bounds on Revenue of Approximately Optimal Auctions

We obtain revenue guarantees for the simple pricing mechanism of a single
posted price, in terms of a natural parameter of the distribution of buyers'
valuations. Our revenue guarantee applies to the single item n buyers setting,
with values drawn from an arbitrary joint distribution. Specifically, we show
that a single price drawn from the distribution of the maximum valuation Vmax =
max {V_1, V_2, ...,V_n} achieves a revenue of at least a 1/e fraction of the
geometric expecation of Vmax. This generic bound is a measure of how revenue
improves/degrades as a function of the concentration/spread of Vmax.
  We further show that in absence of buyers' valuation distributions,
recruiting an additional set of identical bidders will yield a similar
guarantee on revenue. Finally, our bound also gives a measure of the extent to
which one can simultaneously approximate welfare and revenue in terms of the
concentration/spread of Vmax.Comment: The 8th Workshop on Internet and Network Economics (WINE
Exploiting Twitter for Spiking Query Classification

We propose a method for classifying queries whose frequency spikesin a search engine into their topical categories such as celebrities and sports. Unlikeprevious methods using Web search results and query logs that take a certainperiod of time to follow spiking queries, we exploit Twitter to timely classifyspiking queries by focusing on its massive amount of super-fresh content. Theproposed method leverages unique information in Twitter—not only tweets butalso users and hashtags. We integrate such heterogeneous information in a graphand classify queries using a graph-based semi-supervised classification method.We design an experiment to replicate a situation when queries spike. The resultsindicate that the proposed method functions effectively and also demonstrate thataccuracy improves by combining the heterogeneous information in Twitter.8th Asia Information Retrieval Societies Conference, AIRS 2012, Tianjin, China, December 17-19, 2012. Proceeding
Cross-Lingual knowledge discovery : Chinese-to-English article linking in Wikipedia

In this paper we examine automated Chinese to English link discovery in Wikipedia and the effects of Chinese segmentation and Chinese to English translation on the hyperlink recommendation. Our experimental results show that the implemented link discovery framework can effectively recommend Chinese-to-English cross-lingual links. The techniques described here can assist bi-lingual users where a particular topic is not covered in Chinese, is not equally covered in both languages, or is biased in one language; as well as for language learning
Physical access control administration using building information models

Physical access control systems play a central role in the protection of critical infrastructures, where both the provision of timely access and preserving the security of sensitive areas are paramount. In this paper we discuss the shortcomings of existing approaches to the administration of physical access control in complex environments. At the heart of the problem is the current dependency on human administrators to reason about the implications of the provision or the revocation of staff access to an area within these facilities. We demonstrate how utilising Building Information Models (BIMs) and the capabilities they provide, including 3D representation of a facility and path-finding can reduce possible intentional or accidental errors made by security administrators
Detecting control flow in Smarphones: Combining static and dynamic analyses

International audienceSecurity in embedded systems such as smartphones requires protection of confidential data and applications. Many of security mechanisms use dynamic taint analysis techniques for tracking information flow in software. But these techniques cannot detect control flows that use conditionals to implicitly transfer information from objects to other objects. In particular, malicious applications can bypass Android system and get privacy sensitive information through control flows. We propose an enhancement of dynamic taint analysis that propagates taint along control dependencies by using the static analysis in embedded system such as Google Android operating system. By using this new approach, it becomes possible to protect sensitive information and detect most types of software exploits without reporting too many false positives
Delay-tolerant positioning for location-based logging with mobile devices

In  this paper,  we  explore  the  viability  and  possible limitations  of  a 
delay-tolerant positioning process for location-based logging. Instead of esti-
mating the device position on the device, a delay-tolerant technique stores the 
radio  and  Wi-Fi  data  needed  to  calculate  that  position,  sends  it  to  a  server 
when appropriate, and it is the server that will calculate the position. This is 
very  suitable  for  location  logging  because  it  supports  the  generation  of  fre-
quent position registers without incurring in high communication and energy 
costs. We have conducted a controlled experiment to assess the accuracy of 
this technique and the results suggest that the accuracy of the positions calcu-
lated on the server using this technique is the same as those that can be ob-
tained by calculating the position directly on the device
Neglect Benevolence in Human-Swarm Interaction with Communication Latency

In practical applications of robot swarms with bio-inspired behaviors, a human operator will need to exert control over the swarm to fulfill the mission objectives. In many operational settings, human operators are remotely located and the communication environment is harsh. Hence, there exists some latency in information (or control command) transfer between the human and the swarm. In this paper, we conduct experiments of human-swarm interaction to investigate the effects of communication latency on the performance of a human-swarm system in a swarm foraging task. We develop and investigate the concept of neglect benevolence, where a human operator allows the swarm to evolve on its own and stabilize before giving new commands. Our experimental results indicate that operators exploited neglect benevolence in different ways to develop successful strategies in the foraging task. Furthermore, we show experimentally that the use of a predictive display can help mitigate the adverse effects of communication latency
Connectivity Differences between Human Operators of Swarms and Bandwidth Limitations

Human interaction with robot swarms (HSI) is a young field with very few user studies that explore operator behavior. All these studies assume perfect communication between the operator and the swarm. A key challenge in the use of swarm robotic systems in human supervised tasks is to understand human swarm interaction in the presence of limited communication bandwidth, which is a constraint arising in many practical scenarios. In this paper, we present results of human-subject experiments designed to study the effect of bandwidth limitations in human swarm interaction. We consider three levels of bandwidth availability in a swarm foraging task. The lowest bandwidth condition performs poorly, but the medium and high bandwidth condition both perform well. In the medium bandwidth condition, we display useful aggregated swarm information (like swarm centroid and spread) to compress the swarm state information. We also observe interesting operator behavior and adaptation of operators' swarm reaction
Human activity recognition on smartphones using a multiclass hardware-friendly support vector machine

Activity-Based Computing aims to capture the state of the user and its environment by exploiting heterogeneous sensors in order to provide adaptation to exogenous computing resources. When these sensors are attached to the subject’s body, they permit continuous monitoring of numerous physiological signals. This has appealing use in healthcare applications, e.g. the exploitation of Ambient Intelligence (AmI) in daily activity monitoring for elderly people. In this paper, we present a system for human physical Activity Recognition (AR) using smartphone inertial sensors. As these mobile phones are limited in terms of energy and computing power, we propose a novel hardware-friendly approach for multiclass classification. This method adapts the standard Support Vector Machine (SVM) and exploits fixed-point arithmetic for computational cost reduction. A comparison with the traditional SVM shows a significant improvement in terms of computational costs while maintaining similar accuracy, which can contribute to develop more sustainable systems for AmI.Peer ReviewedPostprint (author's final draft
Evaluation of emerging audio description systems for broadcast TV

Following EU directives on Media Access and Ambient Assisted Living, the broadcasting industry needs to introduce new services in order to guarantee access to all citizens. The article and its conclusions are part of the EU project DTV4ALL, which focuses on some possible broadcasting scenarios for achieving barrier - free television for those with visual impairments. Five enhanced Audiodescription (AD) scenarios were proposed and evaluated: 1) Live streaming Internet TV with AD, 2) AD reception in a group situation, 3) Video on demand over aset - top - box , 4) Video on PC and 5) Podcasts. User evaluation concerning usefulness, quality and usability of the services was assessed using questionnaires. Results of the user evaluation show that not only are AD emerging services technically viable but they are also positively rated by users. Implementation of these services will provide improved access to content, making TV accessible for all
The Impact of Introducing Therapeutic Robots in Hospital's Organization

The introduction of robots in health and wellbeing services could mean a great improvement in patients’ life, but also implies a huge change in hospital’s organization. This work introduces a empirical study that investigates the factors influencing the process of adoption of robots in hospitals. Interviews have been completed in a health organization leading this change. Learned lessons lead to define a balance of facilitators and barriers that should help to apply the innovation. This process has been completed from Kotter’s leading change approach, since it would\ud
be the roadmap for the whole procedure.Postprint (published version