This paper presents the second release of arrau, a multigenre corpus of anaphoric information created over 10 years to provide data for the next generation of coreference/anaphora resolution systems combining different types of linguistic and world knowledge with advanced discourse modeling supporting rich linguistic annotations. The distinguishing features of arrau include the following: treating all NPs as markables, including non-referring NPs, and annotating their (non-) referentiality status; distinguishing between several categories of non-referentiality and annotating non-anaphoric mentions; thorough annotation of markable boundaries (minimal/maximal spans, discontinuous markables); annotating a variety of mention attributes, ranging from morphosyntactic parameters to semantic category; annotating the genericity status of mentions; annotating a wide range of anaphoric relations, including bridging relations and discourse deixis; and, finally, annotating anaphoric ambiguity. The current version of the dataset contains 350K tokens and is publicly available from LDC. In this paper, we discuss in detail all the distinguishing features of the corpus, so far only partially presented in a number of conference and workshop papers, and we also discuss the development between the first release of arrau in 2008 and this second one.

A crisis is a complex situation, which actors have some difficulties to manage it. They are under stress to deal with problems that they cannot predict consequences. The human conditions (familial and life) and, the influence of the environment (politic, economic, media) pushes the actors to lose control of the crisis situation. The question we face in this paper is: “is it possible to predict the impact of the stress in this type of situation?” Our main hypothesis to answer is to represent experience feedback using knowledge management. To model the crisis management as systemic system emphasizing regulation loops, and the collaboration activity by showing the dimension of the communication, coordination, and cooperation. This modeling is illustrated in a terrorist attack situation in Algeria. To predict stress consequences, fuzzy set principle is adopted, based on experience feedback and situations modeling, as a generator of alternative states given a stress event.

During a crisis situation, the ability of emergency department to take reliable and quick decisions is the main feature that defines the success or failure of this organization in the course of its crisis management. Decision makers spend time on identifying the decisions that will be taken for the whole of the crisis management, and on anticipating the preparation of these decisions, ensuring that they have time to properly prepare all decisions to be taken and, be able to implement them as fast as possible. However, the context and the characteristics of the crisis make the decision process complicated because there is no specific methodology to anticipate these decisions and properly manage collaboration with the other protagonists. There is also the pressure of time, a significant stress and, the emotional impact on the decision maker that lead to losing objectivity in decision making. We understand so that the right decision will be greatly facilitated and enhanced by the development of an adequate tool and process for decision-making. This tool must respect methods of the emergency department considered, and highlight the importance of experience feedback referencing to past cases, especially success and failures. We propose in this paper, software in order to handle experience feedback as a support for decision-making in crisis management “Crisis Clever System”. Several dimensions are considered in this study, from one side: organization, communication and problem-solving activities and from the other side the presentation and finding of experience feedback thanks to an analogy technique.

Innovation and creativity are a mandatory for companies who wish to stay competitive. In order to promote an inventive dynamic, it implies to set up tools, habits, and an adapted environment to foster creativity. Creativity is the wealth of companies that should be valorized. To promote creativity, companies implement creativity workshops that gather people with various roles and expertise exchange and create knowledge to solve collectively open-ended engineering problems. However, group dynamics or facilitation can make the wrong decision and make the creative problem-solving unfruitful. The aim of our research project is to create a digital system to manage and valorize knowledge during creativity workshops. To design this system, we need to formalize the knowledge domain of creative workshops. The ontologies are used for decades to structure and manage information and knowledge in different domains. However, methodologies to design these ontologies are either hardly reproducible or not oriented to extract knowledge from organization. This article describes a methodology based on an organizational modeling to build ontologies. We will illustrate our approach by designing an ontology that models knowledge of creativity workshops.

This work aims to evaluate the energy savings that can be achieved in domestic hot water (DHW) production using consumption forecasting through statistical modeling. It uses our forecast algorithm and aims at investigating how it can improve energy efficiency depending on the system configuration. Especially, the influence of the DHW production type used is evaluated as well as the water tank insulation. To that end, real consumption measurements are used for model training. Then simulations are run on using TRNSYS software to compute the total energy consumption of DHW production systems over 1 year. Simulations are also based on real consumption measurements for realistic results. To appraise the energy savings, we compared simulations that consider either no forecast (reactive control), perfect forecast (to estimate the control ability to consider forecast), or the forecast provided by our algorithm. The measurements and simulations are run on 26 different but real dwellings to assess results variability. Several system configurations are also compared with varying thermal insulation indices for a complete benchmark of the approach so that an overall performance of the system and the anticipation strategy could be evaluated.

Recently, interest in integrated assembly sequence planning (ASP) and assembly line balancing (ALB) began to pick up because of its numerous benefits, such as the larger search space that leads to better solution quality, reduced error rate in planning, and expedited product time-to-market. However, existing research is limited to the simple assembly problem that only runs one homogenous product. This paper therefore models and optimizes the integrated mixed-model ASP and ALB using Multi-objective Discrete Particle Swarm Optimization (MODPSO) concurrently. This is a new variant of the integrated assembly problem. The integrated mixed-model ASP and ALB is modeled using task-based joint precedence graph. In order to test the performance of MODPSO to optimize the integrated mixed-model ASP and ALB, an experiment using a set of 51 test problems with different difficulty levels was conducted. Besides that, MODPSO coefficient tuning was also conducted to identify the best setting so as to optimize the problem. The results from this experiment indicated that the MODPSO algorithm presents a significant improvement in term of solution quality toward Pareto optimal and demonstrates the ability to explore the extreme solutions in the mixed-model assembly optimization search space. The originality of this research is on the new variant of integrated ASP and ALB problem. This paper is the first published research to model and optimize the integrated ASP and ALB research for mixed-model assembly problem.

The ability to successfully conduct radical innovations is mandatory for mature industrial companies that want to remain competitive in the global market. This ability relies on several ingredients, namely: (1) the structuring of the innovation process; (2) managerial principles; (3) methodological tools; (4) the presence of a culture of innovation. This paper reports about the impact of applying the User eXperience-Fuzzy Front End (UX-FFE) model, which brings together the systemic innovation process with the social, economical, and methodological aspects on the outcomes of the innovation process. Firstly, it appears that the operational performance of the upstream innovation process relies on the quality of the social context, intrinsic to the group of co-creators, corresponding to the reported perceived experience. Secondly, the UX-FFE model application, therefore, allows optimizing the upstream innovation process performance. Indeed, we argue that the evaluation of the co-creators perceived experience brings new opportunities to optimize the operational performance of the upstream innovation process. The first part of this paper presents deeper a theoretical model, named UX-FFE, which combines a UX approach with an upstream innovation process (FFE). The main interest of this UX-FFE model is that it allows evaluating the social aspect of the upstream innovation process, which may be detrimental to the success of radical innovation projects in mature companies. The second part presents the results of previous experiments that validated the model. The results allow the design of an instrument dedicated to the evaluation of the user experience of co-creators in the ideation stage. Finally, the third part reports about the experimentation of the UX-FFE in a mature company. Results present the impact of the co-creators' experience on the performance of radical innovation projects.

We provide a deterministic algorithm that finds, in ɛ-O(1)n2 time, an ɛ-regular Frieze–Kannan partition of a graph on n vertices. The algorithm outputs an approximation of a given graph as a weighted sum of ɛ-O(1) many complete bipartite graphs.

As a corollary, we give a deterministic algorithm for estimating the number of copies of H in an n-vertex graph G up to an additive error of at most ɛnv(H), in time ɛ-OH(1)n2.

Nowadays, the use of virtual reality/virtual acoustics (VR/VA) in archaeology for rendering lost buildings is an important topic in the cultural heritage field. Moreover, the addition of additional senses apart from the sight increases the feeling of immersion in virtual environments. The aim of this paper is to show the interaction work developed in a VA system, based on Unity and FMOD, the graphical and acoustical reconstruction of an ancient building and the development of a VR goggles with headphones to render 3D audio and video interactively. This system has been implemented to render auralizations in a binaural system and has been applied to the renderization of an old and lost theatre in València (Spain). The first building of theatre was built in the 16th century, and was rebuilt several times until the 18th century. The auralization of several theatrical excerpts of different Spanish authors of that time is also presented. The integrated system has been subjectively evaluated, obtaining very satisfactory results.

Support vector machine (SVM) methods are widely used for classification and regression analysis. In many engineering applications, only one class of data is available, and then one-class SVM methods are employed. In reliability applications, the one-class data may be failure data since the data are recorded during reliability experiments when only failures occur. Different from the problems handled by existing one-class SVM methods, there is a bias constraint in the SVM model in this work and the constraint comes from the probability of failure estimated from the failure data. In this study, a new one-class SVM regression method is proposed to accommodate the bias constraint. The one class of failure data is maximally separated from a hypersphere whose radius is determined by the known probability of failure. The proposed SVM method generates regression models that directly link the states of failure modes with design variables, and this makes it possible to obtain the joint probability density of all the component states of an engineering system, resulting in a more accurate prediction of system reliability during the design stage. Three examples are given to demonstrate the effectiveness of the new one-class SVM method.

This paper addresses the construction of digital twins (exact mirror images of real-world in cyberspace) using hidden Markov models for the futuristic manufacturing systems known as Industry 4.0. The proposed digital twin consists of two components namely model component and simulation component. The model component forms a Markov chain that encapsulates the dynamics underlying the phenomenon by using some discrete states and their transition probabilities. The simulation component recreates the phenomenon using a Monte Carlo simulation process. The efficacy of the proposed digital twin construction methodology is shown by a case study, where the digital twin of the surface roughness of a surface created by successive grinding operations is described. The developers of the cyber-physical systems will be benefitted from the outcomes of this study because these systems need the computable virtual abstractions of the manufacturing phenomena to address the issues related to the maturity index of futuristic manufacturing systems (i.e., understand, predict, decide, and adopt).

This paper documents autonomous multi-floor stairwell ascent by a legged robot. This is made possible through empirically deployed sequential composition of several reactive controllers, with perceptually triggered transitions. This composition relies on simplified assumptions regarding the robot’s sensory capabilities, its level of mobility, and the environment it operates in. The discrepancies between these assumptions and the physical reality are capably handled by the intrinsic motor competence of the robot. This behavior is implemented on the legged RHex platform and experiments spanning 10 different stairwells with various challenges are conducted.