Papers.

Virtual Private Overlays: Secure Group Commounication in NAT-Constrained Environments

Structured P2P overlays provide a framework for building distributed applications that are self-configuring, scalable, and resilient to node failures. Such systems have been successfully adopted in large-scale Internet services such as content delivery networks and file sharing; however, widespread adoption in small/medium scales has been limited due in part to security concerns and difficulty bootstrapping in NAT-constrained environments. Nonetheless, P2P systems can be designed to provide guaranteed lookup times, NAT traversal, point-to-point overlay security, and distributed data stores. In this paper we propose a novel way of creating overlays that are both secure and private and a method to bootstrap them using a public overlay. Private overlay nodes use the public overlay's distributed data store to discover each other, and the public overlay's connections to assist with NAT hole punching and as relays providing STUN and TURN NAT traversal techniques. The security framework utilizes groups, which are created and managed by users through a web based user interface. Each group acts as a Public Key Infrastructure (PKI) relying on the use of a centrally-managed web site providing

WCL2R: A Benchmark Collection for Learning to Rank Research with Clickthrough Data

Visual web mining for website evaluation

TYPO3 4.3 Multimedia Cookbook

Trainable automated forces.

The Pragmatist's Guide to Comparative Effectiveness Research

The New Frontier of Web Search Technology: Seven Challenges.

The Distribution and Evolution of the Capital Structure of Entrepreneurial Firms: Evidence on the Financial Crisis

The CALBC Silver Standard Corpus for Biomedical Named Entities - A Study in Harmonizing the Contributions from Four Independent Named Entity Taggers.

SystemT: An Algebraic Approach to Declarative Information Extraction

Subword Variation in Text Message Classification

Spark: Cluster Computing with Working Sets

MapReduce and its variants have been highly successful in implementing large-scale data-intensive applications on commodity clusters. However, most of these systems are built around an acyclic data flow model that is not suitable for other popular applications. This paper focuses on one such class of applications: those that reuse a working set of data across multiple parallel operations. This includes many iterative machine learning algorithms, as well as interactive data analysis tools. We propose a new framework called Spark that supports these applications while retaining the scalability and fault tolerance of MapReduce. To achieve these goals, Spark introduces an abstraction called resilient distributed datasets (RDDs). An RDD is a read-only collection of objects partitioned across a set of machines that can be rebuilt if a partition is lost. Spark can outperform Hadoop by 10x in iterative machine learning jobs, and can be used to interactively query a 39 GB dataset with sub-second response time. 1

Smarter Analytics: Taking the Journey to IBM Cognitive Systems

Single-Photon Detection, Kinetic Inductance, and Non-Equilibrium Dynamics in Niobium and Niobium Nitride Superconducting Nanowires

Serendipitous Encounters along Dynamically Personalized Museum Tours.

Today Recommender Systems (RSs) are commonly used with various purposes, especially dealing with e-commerce and information filtering tools. Content-based RSs rely on the concept of similarity between items. It is a common belief that the user is interested in what is similar to what she has already bought/searched/visited. We believe that there are some contexts in which this assumption is wrong: it is the case of acquiring unsearched but still useful items or pieces of information. This is called serendipity. Our purpose is to stimulate users and facilitate these serendipitous encounters to happen. The paper presents a hybrid recommender system that joins a content-based approach and serendipitous heuristics in order to provide also surprising suggestions. The reference scenario concerns with personalized tours in a museum and serendipitous items are introduced by slight diversions on the context-aware tours. 1. BACKGROUND AND MOTIVATION RSs allow a customized information access for targeted domains. They provide the users with personalized advices based on their needs, preferences and usage patterns. Sometimes RSs can only recommend items that score highly against the user’s profile and, consequently, the user is limited to obtain advices only about items too similar to those she already knows. This drawback is referred as over-specialization and it prevents surprising finding from taking place. Indeed, the RSs are required to provide novel and even serendipitous ∗The full version will appear in A. Lazinica (editor), E-Commerce, ISBN 978-953-7619-X-X, electronic version freely available at http://intechweb.org. Appears in the Proceedings of the 1st Italian Information Retrieval Workshop (IIR’10), January 27–28, 2010, Padova, Italy....

SemEval-2010 Task 5 : Automatic Keyphrase Extraction from Scientific Articles

Secondary use of clinical data

Resource-aware annotation through active learning.

Real Options in Information Systems - a Revised Framework

Quantifying the Trustworthiness of Social Media Content: Content Analysis for the Social Web

Public and private BitTorrent communities: a measurement study

Programming in Scala: A Comprehensive Step-by-Step Guide, 2nd Edition

Piloted search and recommendation with social tag cloud-based navigation

PHP Acceleration in the Cloud: Caching PHP Virtual Machine Opcodes for Reuse in a Secure, Multi-User, Enterprise Programming Environment

Performance Assessment to Enhance Training Effectiveness

Training simulators have become increasingly popular tools for instructing humans on performance in complex environments. However, the question of how to provide individualized and scenario-specific assessment and feedback to students remains largely an open question. To maximize training efficiency, new technologies are required that assist instructors in providing individually relevant instruction. Sandia National Laboratories has shown the feasibility of automated performance assessment tools, such as the Sandia-developed Automated Expert Modeling and Student Evaluation (AEMASE) software, through proof-of-concept demonstrations, a pilot study, and an experiment. In the pilot study, the AEMASE system, which automatically assesses student performance based on observed examples of good and bad performance in a given domain, achieved a high degree of agreement with a human grader (89%) in assessing tactical air engagement scenarios. In more recent work, we found that AEMASE achieved a high degree of agreement with human graders (83-99%) for three Navy E-2 domain-relevant performance metrics. The current study provides a rigorous empirical evaluation of the enhanced training effectiveness achievable with this technology. In particular, we assessed whether giving students feedback based on automated metrics would enhance training effectiveness and improve student performance. We trained two groups of employees (differentiated by type of feedback) on a Navy E-2 simulator and assessed their performance on three domain-specific performance metrics. We found that students given feedback via the AEMASE-based debrief tool performed significantly better than students given only instructor feedback on two out of three metrics. Future work will focus on extending these developments for automated assessment of teamwork.

On-Demand Language Model Interpolation for Mobile Speech Input

Numerical Validation of the CLIC/SwissFEL/FERMI Multi Purpose X Band Structure

Currently an X-band traveling wave accelerator structure is fabricated in a collaboration between CERN, PSI and Sincrotrone Trieste (ST). PSI and ST will use it in their FEL projects, CERN will test break down limits and rates for high gradients. A special feature of this structure is two integrated wake field monitors monitoring the beam to structure alignment. The design used the classical approach to model individual components and to assume the overall behavior to be the simple superposition of the results. This technique is known to produce valid structure designs. To get a full view of the structure's properties, we followed that by a numerical electromagnetic simulation validation of the full structure to see effects such as internal reflections inside the structure or higher order dispersive terms. Using SLAC's high-performance electromagnetic code suite ACE3P, first results were obtained for the fundamental mode and the lower transverse modes.

Modeling and Validation of ARINC653 architectures

International audience

Model based code generation for distributed embedded systems

Embedded systems are becoming increasingly complex and more distributed. Cost and quality requirements necessitate reuse of the functional software components for multiple deployment architectures. An important step is the allocation of software components to hardware. During this process the differences between the hardware and application software architectures must be reconciled. In this paper we discuss an architecture driven approach involving model-based techniques to resolve these differences and integrate hardware and software components. The system architecture serves as the underpinning based on which distributed real-time components can be generated. Generation of various embedded system architectures using the same functional architecture is discussed. The approach leverages the following technologies – IME (Integrated Modeling Environment), the SAE AADL (Architecture Analysis and Design Language), and Ocarina. The approach is illustrated using the electronic throttle control system as a case study.

Mixed reference frame representations underlie the use of multimodal sensory signals for reaching

Mining the Web 2.0 for Better Search.

Making Privacy a Fundamental Component of Web Resources

LLNL's Precision Compton Scattering Light Source

Abstract not provided

Learning Tree Conditional Random Fields

We examine maximum spanning tree-based methods for learning the structure of tree Conditional Random Fields (CRFs) P (Y|X). We use edge weights which take advantage of local inputs X and thus scale to large problems. For a general class of edge weights, we give a negative learnability result. However, we demonstrate that two members of the class–local Conditional Mutual Information and Decomposable Conditional Influence– have reasonable theoretical bases and perform very well in practice. On synthetic data and a large-scale fMRI application, our methods outperform existing techniques. 1.

Le Web sémantique : un enjeu majeur pour le partage et la réutilisation des données sur le Web

Javna uprava i evropske integracije Srbije

Is Bill Gates the Exception or the Norm - Role of Human Capital in Occupation Choice in IT Industries

Interim report : interoperability of registries

Intégration de la sécurité et de la sûreté de fonctionnement dans la construction d'intergiciels critiques

Safety-critical software (used in avionics, military or aerospace domains) must preserve their integrity, ensure a continuous operational state and enforce security of their data. There requirements are met through a dedicated development process that analyses and detects errors before system release. However, these methods are not sufficient and safety or security still occurs in such systems (e.g. explosion of Ariane 5, mission failure of Mars Climate Orbiter, etc). In addition, meeting safety and security becomes more and more difficult due to an increasing number of functionalities. This thesis introduces a new method to build safety-critical systems and ensure their safety and security requirements. The approach proposes patterns for the specification of safe and secure systems. Then, a dedicated development process relies on them to (i) validate, (ii) automatically implement and (iii) certify the system, enforcing its requirements from the specifications to the code. System validation (i) detects specification errors, ensuring its correctness and feasibility prior any development effort. The automatic implementation process (ii) translates system specification into code and ensures their requirements enforcement. The certification (iii) aspect verifies that specification requirements are met in the implementation by analyzing the system during its execution. It also evaluates its compliance against certification standards (such as DO178B).

Incremental Decoding for Phrase-Based Statistical Machine Translation

Holistic language processing : joint models of linguistic structure

Hierarchical Joint Learning: Improving Joint Parsing and Named Entity Recognition with Non-Jointly Labeled Data

GreenHDFS: towards an energy-conserving, storage-efficient, hybrid Hadoop compute cluster

Forced Alignment Under Adverse Conditions

Finding Cognate Groups Using Phylogenies

Ensuring quality in crowdsourced search relevance evaluation: The effects of training question distribution

Domain Adaptation of Rule-Based Annotators for Named-Entity Recognition Tasks

Do You Want to Take Notes? Identifying Research Missions in Yahoo! Search Pad

Design, Verification and Implementation of MILS systems

International audience

Crowdsourcing and language studies: the new generation of linguistic data