pinecone/core-2020-05-10-deduplication huggingface dataset:
Stochastic excitation of acoustic modes in stars

For more than ten years, solar-like oscillations have been detected and
frequencies measured for a growing number of stars with various characteristics
(e.g. different evolutionary stages, effective temperatures, gravities, metal
abundances ...).
  Excitation of such oscillations is attributed to turbulent convection and
takes place in the uppermost part of the convective envelope. Since the
pioneering work of Goldreich & Keely (1977), more sophisticated theoretical
models of stochastic excitation were developed, which differ from each other
both by the way turbulent convection is modeled and by the assumed sources of
excitation. We review here these different models and their underlying
approximations and assumptions.
  We emphasize how the computed mode excitation rates crucially depend on the
way turbulent convection is described but also on the stratification and the
metal abundance of the upper layers of the star. In turn we will show how the
seismic measurements collected so far allow us to infer properties of turbulent
convection in stars.Comment: Notes associated with a lecture given during the fall school
  organized by the CNRS and held in St-Flour (France) 20-24 October 2008 ; 39
  pages ; 11 figure
Boosting bitext compression

Bilingual parallel corpora, also know as bitexts, convey the same information in two different languages. This implies that when modelling bitexts one can take advantage of the fact that there exists a relation between both texts; the text alignment task allow to establish such relationship. In this paper we propose different approaches that use words and biwords (pairs made of two words, each one from a different text) as representation symbolic units. The properties of these approaches are analysed from a statistical point of view and tested as a preprocessing step to general purpose compressors. The results obtained suggest interesting conclusions concerning the use of both words and biwords. When encoded models are used as compression boosters we achieve compression ratios improving state-of-the-art compressors up to 6.5 percentage points, being up to 40% faster.Work supported by the Spanish Government through projects TIN2009-14009-C02-01 and TIN2009-14009-C02-02; and by the Millennium Institute for Cell Dynamics and Biotechnology (ICDB) (Grant ICM P05-001-F)
Bringing Statistical Methodologies for Enterprise Integration of Conversational Agents

Proceedings of: 9th International Conference on Practical Applications of Agents and Multiagent Systems (PAAMS 11). Salamanca, 6-8 April, 2011In this paper we present a methodology to develop commercial conversational agents that avoids the effort of manually defining the dialog strategy for the dialog management module. Our corpus-based methodology is based on selecting the next system answer by means of a classification process in which the complete dialog history is considered. This way, system developers can employ standards like VoiceXML to simply define system prompts and the associated grammars to recognize the users responses to the prompt, and the statistical dialog model automatically selects the next system prompt.We have applied this methodology for the development of an academic conversational agent.Funded by projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC 2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485), and DPS2008-07029-
C02-02.Publicad
Using mobile systems to monitor an ambulatory patient

Medical diagnostics and vital signs monitoring demands more technological solutions to cope with new methods of treatment. Continuous monitoring and
information processing tools are vital to a physician with several patients under his care. In this work, a system that relies on agents and mobile and wireless devices is presented. Its use with small scale sensors allows to collect and analyse vital data in real-time, triggering appropriate reactions in case of eminent danger. This includes real-time notifications to practitioners. In cases in which the physician is unable to divide his attention among all his patients, the system is able to drive his attention to one patient only and, when it is necessary, to another one, according to their medical
state. This concept represents a breakthrough in terms of the physician’s time and task management, being possible to apply it two major scenarios: patient recovery in a hospital environment or elderly living alone in a domestic environment. In that sense, we present a brief contextualiation of the problem as well as the architecture and technologies used to implement the proposed work
Agent Simulation to Develop Interactive and User-Centered Conversational Agents

Proceedings of: International Symposium on Distributed Computing and Artificial Intelligence (DCAI 2011). Salamanca, 06-08 April 2011.In this paper, we present a technique for developing user simulators which are able to interact and evaluate conversational agents. Our technique is based on a statistical model that is automatically learned from a dialog corpus. This model is used by the user simulator to provide the following answer taking into account the complete history of the interaction. The main objective of our proposal is not only to evaluate the conversational agent, but also to improve this agent by employing the simulated dialogs to learn a better dialog model. We have applied this technique to design and evaluate a conversational agent which provides academic information in a multi-agent system. The results of the evaluation show that the conversational agent reduces the time needed to fulfill to complete the the dialogs, thereby allowing the conversational agent to tackle new situations and generate new coherent answers for the situations already present in an initial model.Funded by projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-
02/TEC, CAM CONTEXTS (S2009/TIC-1485), and DPS2008-07029-C02-02.Publicad
The EducAgent Platform: Intelligent Conversational Agents for E-Learning Applications

Proceedings of: 2nd International Symposium on Ambient Intelligence (ISAmI 2011). Salamanca, 06-08 April 2011.In this paper, we describe a multi-agent system developed for teaching support and student's self-learning. The main objective of the EducAgent platform is the creation of an innovative virtual space following the principles of the European Higher Education Area to make subjects and e-learning initiatives to become a more flexible, participatory and attractive space. One of the most important characteristics of the developed platform is to facilitate a more natural interaction between the system and students by means of conversational agents. We describe the main features of the EducAgent platform and its application in the new European Computer Science Degree at the Carlos III University of Madrid.Funded by projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAMCONTEXTS (S2009/TIC-1485), and DPS2008-07029-C02-02.Publicad
Recommendation and planning through mobile devices in tourism context

In this paper we present a mobile recommendation and planning system, named PSiS Mobile. It is designed to provide effective support during a tourist visit
through context-aware information and recommendations about points of interest, exploiting tourist preferences and context. Designing a tool like this brings several challenges that must be addressed. We discuss how these challenges have been overcame, present the overall system architecture, since this mobile application extends the PSiS project website, and the mobile application architecture.The authors would like to acknowledge FCT, FEDER, POCTI, POSI, POCI and POSC for their support to GECAD unit, and the project PSIS (PTDC/TRA/ 72152/2006)
Toward seamless environments for dispute prevention and resolution

Given the evolution of the Information Technology society, it is now rather simple to acquire products or services in a foreign country. This practice may conduct to the event of conflicts whenever a consumer detects some fault or malfunction in services or products he/she had bought. A situation that may worsen if at the time of the uncovering of the defect, the shopper is already in a different geographical arena. There is thus the need to develop computational tools that may prevent these disputes from even happening. In this work it is proposed the development of seamless intelligent environments for dispute resolution that will surround the user, independently of his/her location. It is described the implementation of a prototype that may provide contextualized real-time information and legal support to consumers. The objective is to decrease the number of disputes due to a poor understanding in relation to the The Law and make justice more personalized and closer to people.The work described in this paper was developed under the TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution Project (PTDC/JUR/71354/2006), which is a research project supported by FCT (Science & Technology Foundation), Portuga
A DSL for context quality modeling in context-aware applications

Developing reliable context-aware applications remains a big
challenge, even after a decade of research in this area. Usually a lot of code is required to handle an application's correct behavior in a variety of different situations. Along with a growing amount of code, also increases the risk of programming errors that may lead to an undesired behavior in particular situations. In this paper we present a domain specific language (DSL) for developing context-aware applications. It allows creating  context quality models which are transformed into software artifacts of the final application. This code generation saves time and effort, and helps to ensure an appropriate autonomic behavior at runtime in inherently uncertain situations.status: publishe
High Dimensional Sparse Econometric Models: An Introduction

In this chapter we discuss conceptually high dimensional sparse econometric
models as well as estimation of these models using ℓ1-penalization and post-
ℓ1-penalization methods. Focusing on linear and nonparametric regression frameworks,
we discuss various econometric examples, present basic theoretical results,
and illustrate the concepts and methods withMonte Carlo simulations and an empirical
application. In the application, we examine and confirm the empirical validity
of the Solow-Swan model for international economic growth.arXiv: (Submitted on 26 Jun 2011 (v1), last revised 2 Sep 2011 (this version, v2)
Using a genetic algorithm to solve a bi-objective WWTP process optimization

When modeling an activated sludge system of a wastewater treatment
plant (WWTP), several conflicting objectives may arise. The proposed formulation
is a highly constrained bi-objective problem where the minimization of the
investment and operation costs and the maximization of the quality of the effluent
are simultaneously optimized. These two conflicting objectives give rise to a set of
Pareto optimal solutions, reflecting different compromises between the objectives.
Population based algorithms are particularly suitable to tackle multi-objective problems
since they can, in principle, find multiple widely different approximations to
the Pareto-optimal solutions in a single run. In this work, the formulated problem
is solved through an elitist multi-objective genetic algorithm coupled with a constrained
tournament technique. Several trade-offs between objectives are obtained
through the optimization process. The direct visualization of the trade-offs through
a Pareto curve assists the decision maker in the selection of crucial design and operation
variables. The experimental results are promising, with physical meaning and
highlight the advantages of using a multi-objective approach
Metabolic Network Analysis Demystified

Metabolic networks are a representation of current knowledge about the metabolic reactions available to a given organism. These networks can be placed into various mathematical frameworks, of which the constraintbased framework [1] has received the most attention over the past 15 years. This results in a predictive model of metabolism. Metabolic models can yield predictions of two types: quantitative, such as the growth rate of an organism under given experimental conditions [2], and qualitative, such as the viability of a mutant [3] or minimal media required for growth [4]. Qualitative predictions, on which we focus, tend to be more robust and reliable than quantitative ones, while remaining experimentally testable and biologically relevant.15th Annual International Conference, RECOMB 2011, Vancouver, BC, Canada, March 28-31, 2011. Proceeding
T-IDBA: A de novo Iterative de Bruijn Graph Assembler for Transcriptome

LNCS v. 6577 entitled: Research in computational molecular biology: 15th annual international conference, RECOMB 2011 ... : proceedingsRNA-seq data produced by next-generation sequencing technology is a useful tool for analyzing transcriptomes. However, existing de novo transcriptome assemblers do not fully utilize the properties of transcriptomes and may result in short contigs because of the splicing nature (shared exons) of the genes. We propose the T-IDBA algorithm to reconstruct expressed isoforms without reference genome. By using pair-end information to solve the problem of long repeats in different genes and branching in the same gene due to alternative splicing, the graph can be decomposed into small components, each corresponds to a gene. The most possible isoforms with sufficient support from the pair-end reads will be found heuristically. In practice, our de novo transcriptome assembler, T-IDBA, outperforms Abyss substantially in terms of sensitivity and precision for both simulated and real data. T-IDBA is available at http://www.cs.hku.hk/~alse/ tidba/. © 2011 Springer-Verlag.postprin
An unbiased adaptive sampling algorithm for the exploration of RNA mutational landscapes under evolutionary pressure

International audienceThe analysis of the relationship between sequences and structures (i.e. how mutations aect structures and reciprocally how structures in uence mutations) is essential to decipher the principles driving molecular evolution, to infer the origins of genetic diseases or to develop bioengineering applications such as the design of articial molecules. Because their structures can be predicted from the sequence data only, RNA molecules provide a good framework to study this sequence-structure relationship. We recently introduced a suite of algorithms called RNAmutants which allows, for the rst time, a complete exploration of RNA sequence-structure maps in polynomial time and space. Formally, RNAmutants takes an input sequence (or seed) to compute the Boltzmann weighted ensembles of mutants with exactly k mutations, and sample mutations from these ensembles. However, this approach suers from major limitations. Indeed, since the Boltzmann probabilities of the mutations depend of the free energy of the structures, RNAmutants has diculties to sample mutant sequences with low G+C-contents. In this paper we introduce a novel unbiased adaptive sampling algorithm that enables RNAmutants to sample regions of the mutational landscape poorly covered by classical algorithms. We applied these methods to sample mutations with low G+C-contents. These adaptive sampling techniques can be easily adapted to explore other regions of the sequence and structural landscapes which are dif- cult to sample. Importantly, these algorithms come at a minimal computational cost. We demonstrate the insights oered by these techniques on studies of complete RNA sequence structures maps of sizes up to 40 nucleotides. Our results indicate that the G+C-content has a strong in uence on the size and shape of the evolutionary accessible sequence and structural spaces. In particular, we show that low G+C-contents favor the apparition of internal loops and thus possibly the synthesis of tertiary structure motifs. On the other hand, high G+C-contents signicantly reduce the size of the evolutionary accessible mutational landscapes
A new frontier in novelty detection: Pattern recognition of stochastically episodic events

Published version of an article from the book: Intelligent Information and Database Systems, Lecture Notes in Computer Science. Also available from the publisher on SpringerLink:http://dx.doi.org/10.1007/978-3-642-20039-7_44A particularly challenging class of PR problems in which the, generally required, representative set of data drawn from the second class is unavailable, has recently received much consideration under the guise of One-Class (OC) classification. In this paper, we extend the frontiers of OC classification by the introduction of a new field of problems open for analysis. In particular, we note that this new realm deviates from the standard set of OC problems based on the following characteristics: The data contains a temporal nature, the instances of the classes are “interwoven”, and the labelling procedure is not merely impractical - it is almost, by definition, impossible, which results in a poorly defined training set. As a first attempt to tackle these problems, we present two specialized classification strategies denoted by Scenarios S 1 and S 2 respectively. In Scenarios S 1, the data is such that standard binary and one-class classifiers can be applied. Alternatively, in Scenarios S 2, the labelling challenge prevents the application of binary classifiers, and instead, dictates a novel application of OC classifiers. The validity of these scenarios has been demonstrated for the exemplary domain involving the Comprehensive Nuclear Test-Ban-Treaty (CTBT), for which our research endeavour has also developed a simulation model. As far as we know, our research in this field is of a pioneering sort, and the results presented here are novel
Improving Query Processing Performance in Large Distributed Database Management Systems

<p>The dream of computing power as readily available as the electricity in a wall socket is coming closer to reality with the arrival of grid and cloud computing. At the sametime, databases grow to sizes beyond what can be efficiently managed by single server systems. There is a need for efficient distributed database management systems (DBMSs). Current distributed DBMSs are not built to scale to more than tensor hundreds of sites (i.e., nodes or computers). Users of grid and cloud computingexpect not only almost innite scalability, i.e., at least to thousands of sites, but alsothat the scale is adapted automatically to meet the demand, whether it increases or decreases. This is a challenge to current distributed DBMSs.</p><p>In this thesis, the focus is on how to improve performance of query processingin large distributed DBMSs where coordination between sites has been reduced inorder to increase scalability. The challenge is for the sites to make decisions thatare globally benecial when their view of the complete system is limited. The main contributions of this thesis are methods to increase failure resilience of aggregation queries, adaptively place data on dierent sites and locate these sites afterwards,and cache intermediate results of query processing.</p><p>The study of failure resilience in aggregation queries presented in this thesisshows that dierent aggregation functions react dierently to failures and that countermeasures must be adapted to each function. A low-cost method to increase accuracyis proposed.</p><p>The dynamic data placement method presented in this thesis allows data to befragmented, allocated, and replicated to adapt to the current system conguration and workload. Fragments are split, coalesced, reallocated, and replicated during query processing to improve query processing performance by allowing more data to be accessed locally. The proposed look up method uses range indexing to make it possible to efficiently identify the sites that store relevant data for a query with low overhead when data is updated.</p><p>During query execution, a number of intermediate results are produced, and this thesis proposes a method to cache these results and use them to answer other,similar queries. In particular, a caching method to improve execution times of top-kqueries is presented.</p><p>Results of experiments in simulators and on an implementation in the DASCOSADB distributed DBMS prototype show that these methods lead to signicant savings in query execution time.</p>PhD i informasjonsteknologiPhD in Information Technolog
Extracting and Visualizing Quotations from News Wires

International audienceWe introduce SAPIENS, a platform for extracting quotations from news wires, associated with their author and context. The originality of SAPIENS is that it relies on a deep linguistic processing chain, which allows for extracting quotations with a wide coverage and an extended definition, including quotations which are only partially quotes-delimited verbatim transcripts. We describe the architecture of SAPIENS and how it was applied to process a corpus of French news wires from the AFP news agency
Educational resource scheduling based on socio-inspired agents

Revised Selected Papers of 4th International Conference, ICSOFT 2009, Sofia, Bulgaria, July 26-29, 2009.The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-20116-5_17Scheduling a set of constrained resources is a difficult task, specially when there is no clear definition of ‘optimal’. When the constraints depend not only on physical or temporal issues but also in human desires or preferences the task gets harder. This is the case of educational resources, for example when a set of students must be distributed into a limited set of laboratories to attend to periodical practical sessions, in this case weekly. The preferences of the students may vary during the process for reasons such as the number of people already in that group. This paper presents a socio–inspired solution implemented as a multiagent system. The agents enroll themselves in the lab sessions based on their preferences and negotiate with other agents, using the resources they already have, to obtain desired groups that were already full.This work has been partially supported by the Spanish Ministry of Science and Innovation under grants TIN 2007-65989, TIN 2007-64718, and TIN2010-19872
Social based layouts for the increase of locality in graph operations

Graphs provide a natural data representation for analyzing the relationships among entities in many application areas. Since the\ud
analysis algorithms perform memory intensive operations, it is important that the graph layout is adapted to take advantage of the memory hierarchy.\ud
Here, we propose layout strategies based on community detection to improve the in-memory data locality of generic graph algorithms. We\ud
conclude that the detection of communities in a graph provides a layout strategy that improves the performance of graph algorithms consistently over other state of the art strategies.Postprint (published version