pinecone/core-2020-05-10-deduplication huggingface dataset:
Verified global optimization for estimating the parameters of nonlinear models

Nonlinear parameter estimation is usually achieved via the minimization of some possibly non-convex cost function. Interval analysis allows one to derive algorithms for the guaranteed characterization of the set of all global minimizers of such a cost function when an explicit expression for the output of the model is available or when this output is obtained via the numerical solution of a set of ordinary differential equations. However, cost functions involved in parameter estimation are usually challenging for interval techniques, if only because of multi-occurrences of the parameters in the formal expression of the cost. This paper addresses parameter estimation via the verified global optimization of quadratic cost functions. It introduces tools for the minimization of generic cost functions. When an explicit expression of the output of the parametric model is available, significant improvements may be obtained by a new box exclusion test and by careful manipulations of the quadratic cost function. When the model is described by ODEs, some of the techniques available in the previous case may still be employed, provided that sensitivity functions of the model output with respect to the parameters are available
Methodology for Carbon Footprint in Forestry Findings and Ways of Improvement

International audienceClassic methodologies for carbon footprint are made for conventional companies or territories. None is well adapted for entire sectors or parts of sectors, which usually contain numerous and very different companies, such in the forestry. In this work, we proposed a methodology to count GHG emissions for forestry in a region, from harvest preparation to the entrance of industries. We divided forestry in three steps: harvesting, forwarding and transport, for which we listed each GHG emitting process. Then, we applied this methodology in the Auvergne region (FR) and estimated GHG emissions to bring one cubic meter of wood to the industry to an average of 4.7 kgCe; with each step (harvesting, forwarding and transport) causing around a third of it. We also estimated related emissions for different types of wood (timber, industrial wood and fuelwood) and finally, we proposed 32 recommendations to reduce GHG emissions in forestry
A Multi-layer Framework for Virtual Organizations Creation in Breeding Environment

International audienceNowadays collaboration among organizations in the so called Virtual Organizations (VOs) is the most advanced form to make business. Their emergence and growing are closely related to integrated information and communication technology (ICT). One of the promising approaches to carry out the agility and flexibility in VO creation is defined under the assumption of a VO Breeding Environment (VBE). To support such agile organizations, an efficient IT system and methodologies should be set in order to facilitate their daily management activities. Service-oriented software technologies provide promising means to regulate and enforce coordination of cross-organisational business services interactions but lack organizational abstractions and methodology. This paper proposes a framework for collaborative network coordination in the VBEs's context. The proposed framework satisfies flexibility and agility requirements of virtual organization using a multi layer approach combining VBE management systems layer that assist flexible VO creation, a semantic interoperability layer essential for promoting integration on the basis of common language that describe VO concepts and inherent dependencies, and a service oriented layer that introduces the concept of service domain that encapsulates business processes fitting VO requirements
Integration of the Supplier Capacity for Choosing the Less Risky Schedule within an Uncertain Environment

International audienceThis communication addresses the integration of the supplier capacity in the procurement planning process of a customer within a supply chain. Since this supply chain evolves within an uncertain environment, uncertainties may be due to an ill-known demand (prevision) and to the customer production system (scraps, imprecise processing time...). Thus, we propose a collaborative process where the customer aims at taking the less risked decision.The integration of the supplier capacity in the gross requirement enables to assess the risk of back order so that the feasibility of the requirement plan. It then enables the customer to make the decisions which limit this risk
Towards Controlling the Acceptance Factors for a Collaborative Platform in Engineering Design

International audienceThis paper might serve as a guide to take step towards a better acceptance of computer-based Knowledge management (KM) tools in institutional setting. At first time, it investigates a set of factors with different origins which are proved to have an effect on usage decision. Secondly, we set a list of candidate factor which are supposed to influence future users of a collaborative KM platform (Dimocode). At the end, we develop a methodology to take into account the selected factors and master their positive or negative impacts. The contents of this paper would be an appropriate framework in the way of Knowledge management systems (KMS) deployment
Application of PLM processes to respond to mechanical SMEs needs

International audiencePLM is today a reality for mechanical SMEs. Some companies implement PLM systems very well but others have more difficulties. This paper aims to explain why some SMEs do not success to integrated PLM systems analyzing the needs of mechanical SMEs, the processes to implement to respond to those needs and the actual PLM software functionalities. The proposition of a typology of those companies and the responses of those needs by PLM processes will be explain through the applications of a demonstrator applying appropriate generic data model and modelling framework
Integrated New Product Introduction Challenges in Aerospace Manufacturing

The key dynamic in supporting an efficient and effective new product
introduction is the nature of the exchange of information between the functions
of manufacturing engineering and design engineering. This paper describes a
study of this dynamic with particular regard to the role of manufacturing
engineering in developing robust production process for the design intent. This
study reports related work in this area and establishes the views of
participants concerning product introduction process at a major aerospace
manufacturer. It is found that integration between the manufacturing and design
function driven by communication of qualitative data has brought benefit to the
process in terms of quality cost and time. However, a stronger definition
regarding the quality and usability of manufacturing process knowledge
communicated to the design function is required for more effective and efficient
new product introduction in the shortening timescales of the changing industrial
environment
Design for wire and arc additive layer manufacture

Additive Layer Manufacture (ALM) is a technique whereby freeform structures are
produced by building up material in layers. RUAM (Ready-to-Use Additive Layer
Manufacturing) is an innovative concept for building large scale metal ready-to-
use parts. The design for RUAM has several process steps: the geometric design
of the parts taking the complex process behaviour of the arc welding process
into account; FEM to predict temperature and stress distributions to minimise
part distortions; and efficient robot tool path design. This paper covers these
essential design steps from a technical as well as practical point of view
Semantic Knowledge Based Approach for Product Maintenance Support

The purpose of this paper is to use semantic technology to represent the
knowledge for product maintenance . Companies are begining to understand the
importance of utilising an effective approach to manage existing knowledge in
order to increase their intellectual capital. However, one of the main
constraints that have hindered the solution in resolving technical problems has
been the efficient access to knowledge and expertise. Therefore, there is need
for enhancing the management and maintenance of knowledge through a semantic
based approach. This research project adopts a qualitative research approach and
a five-phase research programme methodology. This research project has
highlighted that semantic technology enhances the reusability, flexibility and
maintainability of knowledge and its management
Tracking uncertainty in a spatially explicit susceptible-infected epidemic model

In this paper we conceive an interval-valued continuous cellular automaton for describing the spatio-temporal dynamics of an epidemic, in which the magnitude of the initial outbreak and/or the epidemic properties are only imprecisely known. In contrast to well-established approaches that rely on probability distributions for keeping track of the uncertainty in spatio-temporal models, we resort to an interval representation of uncertainty. Such an approach lowers the amount of computing power that is needed to run model simulations, and reduces the need for data that are indispensable for constructing the probability distributions upon which other paradigms are based
Towards generalized measures grasping CA dynamics

In this paper we conceive Lyapunov exponents, measuring the rate of separation between two initially close configurations, and Jacobians, expressing the sensitivity of a CA's transition function to its inputs, for cellular automata (CA) based upon irregular tessellations of the n-dimensional Euclidean space. Further, we establish a relationship between both that enables us to derive a mean-field approximation of the upper bound of an irregular CA's maximum Lyapunov exponent. The soundness and usability of these measures is illustrated for a family of 2-state irregular totalistic CA
A stochastic evaluation of the contour strength

International audienceIf one considers only local neighborhoods for segmenting an image, one gets contours whose strength is often poorly estimated. A method for reevaluating the contour strength by taking into account non local features is presented: one generates a fixed number of random germs which serve as markers for the watershed segmentation. For each new population of markers, another set of contours is generated. "Important" contours are selected more often. The present paper shows that the probability that a contour is selected can be estimated without performing the effective simulations. Copyright Springer-Verlag 2010. The original publication is available at www.springerlink.com/content/y057x103475301r2
Under-Determined Reverberant Audio Source Separation Using Local Observed Covariance and Auditory-Motivated Time-Frequency Representation

International audienceWe consider the local Gaussian modeling framework for under-determined convolutive audio source separation, where the spatial image of each source is modeled as a zero-mean Gaussian variable with full-rank time- and frequency- dependent covariance. We investigate two methods to improve the accuracy of parameter estimation, based on the use of local observed covariance and auditory-motivated time-frequency representation. We derive an iterative expectation-maximization (EM) algorithm with a suitable initialization scheme. Experimental results over stereo synthetic reverberant mixtures of speech show the effectiveness of the proposed methods
Use of Bimodal Coherence to Resolve Spectral Indeterminacy in Convolutive BSS

Recent studies show that visual information contained in visual speech can be helpful for the performance enhancement of audio-only blind source separation (BSS) algorithms. Such information is exploited through the statistical characterisation of the coherence between the audio and visual speech using, e.g. a Gaussian mixture model (GMM). In this paper, we present two new contributions. An adapted expectation maximization (AEM) algorithm is proposed in the training process to model the audio-visual coherence upon the extracted features. The coherence is exploited to solve the permutation problem in the frequency domain using a new sorting scheme. We test our algorithm on the XM2VTS multimodal database. The experimental results show that our proposed algorithm outperforms traditional audio-only BSS
Management of Assessment Resources in a Federated Repository of Educational Resources

Proocedings of: Fifth European Conference  on Technology Enhanced Learning Sustaining TEL: From Innovation to Learning and Practice (EC-TEL 2010). Barcelona, 28 September-1 October, 2010.This article tries to shed some light over the management of assessment resources in a repository of educational resources from an outcome-based perspective. The approximation to this problem is based on the ICOPER Reference Model, as a model to capture e-learning data, services and processes, addressing an interoperability approach. To demonstrate this proposal, a prototype has been implemented. This article also describes the design and development of this prototype that accesses a repository of educational resources (the Open ICOPER Content Space - OICS), the main features of the prototype, the development environment and the evaluation that is being performed.This work was partially funded by the Best Practice Network ICOPER (Grant No. ECP-2007-EDU-417007), the Learn3 project, “Plan Nacional de I+D+I” TIN2008-05163/TSI, and the eMadrid network, S2009/TIC-1650, “Investigación y Desarrollo de tecnologías para el e-learning en la Comunidad de Madrid”.Publicad
How to share and reuse learning resources: the Ariadne experience

ARIADNE is a European foundation that aims to foster  Share and Reuse  of learning resources. To support this goal, ARIADNE has created an infrastructure for managing learning objects in an open and scalable way. This paper describes the technical approach behind our open, standards based infrastructure, how content providers can connect to it, and the value they can derive from doing so. As such, the abundance that we help to unlock will act as a platform for innovation by tool developers, trainers and teachers and learners themselves.status: publishe
A simple E-learning system based on classroom competition

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-16020-2_42Proceedings of 5th European Conference on Technology Enhanced Learning, EC-TEL 2010, Barcelona, Spain, September 28 - October 1, 2010.We present an e-learning system based on online forms that allows teachers to easily organise competitions in a classroom. This system is used in a preliminary study to evaluate whether cooperative competition is positive or not in education, and to identify which are the characteristics this kind of activity should have to be no harmful for students, motivating and helping them in their learning process.This work was supported by the Spanish Ministry of Science
and Innovation (TIN2008-06566-C04-02), and the Community of Madrid (S2009TIC-
1542)
End-User Visual Design of Web-Based Interactive Applications Making Use of Geographical Information: the WINDMash Approach

International audienceVisual instructional design languages currently provide notations for representing the intermediate and final results of a knowledge engineering process. This paper reports on a visual framework (called WIND - Web INteraction Design) that focuses on both designers' creativity and model executability. It only addresses Active Reading Learning Scenarios making use of localized documents (travel stories, travel guides). Our research challenge is to enable the teachers to design by themselves interaction scenarios for such a domain, avoiding any programmer intervention. The WIND framework provides a conceptual model and its associated Application Programming Interface (API). The WIND interaction scenarios are encoded as XML documents which are automatically transformed into code thanks to the provided API, thus providing designers with a real application that they can immediately assess and modify (prototyping techniques). The WIND conceptual model only provides designers with an abstract syntax and a semantics. Users of such a Domain Specific Language (DSL) need a concrete syntax. Our choice is to produce a Web-Based Mashup Environment providing designers with visual functionality
Components of a research 2.0 infrastructure

In this paper, we investigate the components of a Research 2.0 infrastructure. We propose building blocks and their concrete implementation to leverage Research 2.0 practice and technologies in our field, including a publication feed format for exchanging publication data, a RESTful API to retrieve publication and Web 2.0 data, and a publisher suit for refining and aggregating data. We illustrate the use of this infrastructure with Research 2.0 application examples ranging from a Mash-Up environment, a mobile and multitouch application, thereby demonstrating the strength of this infrastructure.status: publishe
Computing in Social Networks

International audienceThis paper defines the problem of Scalable Secure Computing in a Social network: we call it the S3 problem. In short, nodes, directly reflecting on associated users, need to compute a function f: V->U of their inputs in a set of constant size, in a scalable and secure way. Scalability means that the message and computational complexity of the distributed computation is at most O(sqrt(n) polylog(n)). Security encompasses (1) accuracy and (2) privacy: accuracy holds when the distance from the output to the ideal result is negligible with respect to the maximum distance between any two possible results; privacy is characterized by how the information disclosed by the computation helps faulty nodes infer inputs of non-faulty nodes. We present AG-S3, a protocol that S3-computes a class of aggregation functions, that is that can be expressed as a commutative monoid operation on U: f(x1,...,xn) = x1+...+xn, assuming the number of faulty participants is at most sqrt(n)/log(n). Key to our protocol is a dedicated overlay structure that enables secret sharing and distributed verifications which leverage the social aspect of the network: nodes care about their reputation and do not want to be tagged as misbehaving
Contribution of Turkish Scholars to Earthquake Literature: The Impact of the Marmara Earthquake

This paper addresses the question of whether the Marmara Earthquake of August 17, 1999, has had an impact on the contribution of Turkish scholars to the earthquake literature. We identified a total of 1,098 papers published between 1990 and 2009 by Turkish earthquake scientists. These papers were cited 7,691 times. Both the number of papers and the citations they generated increased considerably after the Marmara Earthquake. This may be explained, in part, by the increase in the number of projects being carried out since then to study the Marmara Sea basin
Hybrid algorithms for the variable sized bin packing problem

This paper deals with the so-called variable sized bin packing problem, which is a generalization of the one-dimensional bin packing problem in which a set of items with given weights have to be packed into a minimum-cost set of bins of variable sizes and costs. First we propose a heuristic and a beam search approach. Both algorithms are\ud
strongly based on dynamic programming procedures and lower bounding techniques. Second, we propose a variable neighborhood search approach where some neighborhoods are also based on dynamic programming. The best results are obtained by using the solutions provided by the proposed heuristic as starting solutions for variable neighborhood search. The results show that this algorithm is very competitive with current\ud
state-of-the-art approaches.Peer ReviewedPostprint (published version
Taking the customer into account in collaborative design

This article describes the improvement of a model of collaborative design for the ceramic industry. A new stakeholder playing a crucial role is now included in the design process, i.e. the customer. Specifically, we present a pilot validation study for the framework that aims to analyse how the environment, experiences and reference criteria of different types of the customers (commercial dealers, final users, architects and interior designers, etc.) can affect their preferences. Information about these customer preferences could be very useful for designers during the early stages of product development. A multidisciplinary approach to the problem can introduce substantial improvements in defining a truly collaborative design chain
A lower bound for learning distributions generated by probabilistic automata

Known algorithms for learning PDFA can only be shown to  run in time polynomial in the so-called distinguishability  μ of the target machine, besides the number of states and the usual accuracy and confidence parameters. We show that the dependence on μ is necessary for every algorithm whose structure resembles existing ones. As a technical tool, a new variant of Statistical Queries termed L ∞-queries is defined. We show how these queries can be simulated from samples and observe that known PAC algorithms for learning PDFA can be rewritten to access its target using L∞-queries and standard  Statistical Queries. Finally, we show a lower bound: every algorithm to learn PDFA using queries with a resonable tolerance needs a number of queries larger than (1=μ )c  for every c < 1.Peer ReviewedPostprint (author’s final draft
Consistency of Feature Markov Processes

We are studying long term sequence prediction (forecasting).
We approach this by investigating criteria for choosing a compact
useful state representation. The state is supposed to summarize useful
information from the history. We want a method that is asymptotically
consistent in the sense it will provably eventually only choose between
alternatives that satisfy an optimality property related to the used criterion.
We extend our work to the case where there is side information that
one can take advantage of and, furthermore, we briefly discuss the active
setting where an agent takes actions to achieve desirable outcomes
Dynamic Bayesian Networks for Learning Interactions between Assistive Robotic Walker and Human Users

Detection of individuals intentions and actions from a stream of human behaviour is an open problem. Yet for robotic agents to be truly perceived as human-friendly entities they need to respond naturally to the physical interactions with the surrounding environment, most notably with the user. This paper proposes a generative probabilistic approach in the form of Dynamic Bayesian Networks (DBN) to seamlessly account for users attitudes. A model is presented which can learn to recognize a subset of possible actions by the user of a gait stability support power rollator walker, such as standing up, sitting down or assistive strolling, and adapt the behaviour of the device accordingly. The communication between the user and the device is implicit, without any explicit intention such as a keypad or voice.The end result is a decision making mechanism that best matches the users cognitive attitude towards a set of assistive tasks, effectively incorporating the evolving activity model of the user in the process. The proposed framework is evaluated in real-life condition