pinecone/core-2020-05-10-deduplication huggingface dataset:
Seeded Segmentation Methods for Medical Image Analysis

Chapter 3International audienceSegmentation is one of the key tools in medical image analysis. The objective of segmentation is to provide reliable, fast, and effective organ delineation. While traditionally, particularly in computer vision, segmentation is seen as an early vision tool used for subsequent recognition, in medical imaging the opposite is often true. Recognition can be performed interactively by clinicians or automatically using robust techniques, while the objective of segmentation is to precisely delineate contours and surfaces. This can lead to effective techniques known as "intelligent scissors" in 2D and their equivalent in 3D
Mechanical characterization and AE of translucent self-compacting concrete plates in bending

An experimental and numerical study on the mechanical behaviour of an innovative composite material based on the combination of a self-compacting concrete (SCC) matrix with transparent glass inclusions is proposed. The experimental tests have been monitored by an acoustic emission (AE) device. The results are interpreted by a FEM model accounting for the fracture of the two different materials and the interface between them. The AE monitoring is used for the definition of the crack pattern, and to determine the fracture energy dissipation domai
A pedagogical image processing tool to understand structural dynamics

This paper presents a framework and one pedagogical application of motion tracking algorithms applied to\ud
structural dynamics. The aim of this work is to show the ability of high speed camera to study the dynamic\ud
characteristics of simple mechanical systems using a marker less and simultaneous Single Input Multiple Output (SIMO) broadband analysis. KLT (Kanade-Lucas-Tomasi) trackers are used as virtual sensors on mechanical systems video. First we introduce the paradigm of virtual sensors in the field of modal analysis using video processing. Then we present a pedagogical example of flexible beam (Fishing rod) video. From KLT tracking we extracted displacements data (virtual sensors) which are then enhanced using filtering and smoothing and then we can identify natural frequency and damping ratio from classical modal analysis. The experimental results (mode shapes) are compared to an analytical flexible beam model showing high correlation but also showing the limitation of linear analysis. The main interest of this paper is that displacements are simply measured using only video at FPS (Frame Per Second) that respects the Nyquist frequency. There is no target needed on the structure only few critical pixels that are good features to track and which become virtual sensors
The systematic construction of information systems

Process modelling is a vital issue for communicating with experts of the application domain. Depending on the roles and responsibilities of the application domain experts involved, process models are discussed on different levels of abstraction. These may range from detailed regulation for process execution to the interrelation of basic core processes on a strategic level. To ensure consistency and to allow for a flexible integration of process information on different levels of abstraction, we introduce a transformational calculus that allows the incremental addition to and refinement of the information in a process model, while maintaining the validity of more abstract high level processes. A complete formal treatment of model and the calculus is given and is illustrated on a small banking example.Funding received from the UK Engineering and Physical Sciences Research Council (EPSRC) through the Research Grant GR/M/0258
A comparison of semi-deterministic and stochastic search techniques

This paper presents an investigation of two search techniques, tabu search (TS) and simulated annealing (SA), to assess their relative merits when applied to engineering design optimisation. Design optimisation problems are generally characterised as having multi-modal search spaces and discontinuities making global optimisation techniques beneficial. Both techniques claim to be capable of locating globally optimum solutions on a range of problems but this capability is derived from different underlying philosophies. While tabu search uses a semi-deterministic approach to escape local optima, simulated annealing uses a complete stochastic approach. The performance of each technique is investigated using a structural optimisation problem. These performances are then compared to each other as well as a steepest descent (SD) method
Acceptance Criteria for Critical Software Based on Testability Estimates and Test Results

Testability is defined as the probability that a program will fail a test, conditional on the program containing some fault. In this paper, we show that statements about the testability of a program can be more simply described in terms of assumptions on the probability distribution of the failure intensity of the program. We can thus state general acceptance conditions in clear mathematical terms using Bayesian inference. We develop two scenarios, one for software for which the reliability requirements are that the software must be completely fault-free, and another for requirements stated as an upper bound on the acceptable failure probability
Automatic neural generalized font identification

The final publication is available at Springer via http://dx.doi.org/10.1007/978-1-4471-1599-1_116Proceedings of the 8th International Conference on Artificial Neural Networks, Skövde, Sweden, 2–4 September 1998Neural methods are gaining a steady acceptance as powerful tools in a variety of pattern detection problems, OCR certainly being one of them. The concrete implementation of these neural OCR systems is of course a well guarded corporate secret, but in broad terms it can be said that in most of the cases, multilayer perceptrons (MLPs) are used. There are several reasons for the MLPs’ success. To begin with, they are based in well understood mathematical and statistical principles and there are efficient tools and methodologies for their training and evaluation. Furthermore they have good generalization properties.With partial support of grant TIC 95-965 of Spain's CICy
Analysing Persistent Language Applications

Most research into persistent programming has been directed towards the design and implementation of languages and object stores. There are few reports on the characteristics of systems exploiting such technology. This paper reports on a study of the source code of 20 applications consisting of more than 108,000 lines of persistent language code. The authors of the applications range from students to experienced programmers. The programs have been categorised and examined with respect to a persistent application model and the extent of inconsistencies relative to this model is presented. The results confirm the need for and give input to the design of programming methodologies and tools for persistent software engineering. Measurements also include the use of names, types, (polymorphic) procedures and persistent bindings. It is hoped that analysis of the measurements will be used as input to the next generation of languages and programming environments. As part of this new generation, a measurements system is outlined operating entirely within the persistent environment, thus simplifying access to and measurement of both static and dynamic information.

The definitive version is available at springerlink.co
A distributed scheme to detect wormhole attacks in mobile wireless sensor networks

Due to mostly being unattended, sensor nodes become open to physical attacks such as wormhole attack, which is our focus in this paper. Various solutions are proposed for wormhole attacks in sensor networks, but only a few of them take mobility of sensor nodes into account. We propose a distributed wormhole detection scheme for mobile wireless sensor networks in which mobility of sensor nodes is utilized to estimate two network features (i.e. network node density, standard deviation in network node density) through using neighboring information in a local manner. Wormhole attack is detected via observing anomalies in the neighbor nodes’ behaviors based on the estimated network features and the neighboring information. We analyze the performance of proposed scheme via simulations. The results show that our scheme achieves a detection rate up to 100% with very small false positive rate (at most 1.5%) if the system parameters are chosen accordingly. Moreover, our solution requires neither additional hardware nor tight clock synchronization which are both costly for sensor networks
Client-based CardSpace-OpenID Interoperation

We propose a novel scheme to provide interoperability between two  of the most widely discussed identity management systems, namely  CardSpace and OpenID. In this scheme, CardSpace users are  able to obtain an assertion token from an OpenID-enabled identity  provider, the contents of which can be processed by a CardSpace-enabled  relying party. The scheme, based on a browser extension, is   transparent to OpenID providers and to the CardSpace identity selector,  and only requires minor changes to the operation of the CardSpace  relying party
Contextually learnt detection of unusual motion-based behaviour in
  crowded public spaces

In this paper we are interested in analyzing behaviour in crowded public
places at the level of holistic motion. Our aim is to learn, without user
input, strong scene priors or labelled data, the scope of "normal behaviour"
for a particular scene and thus alert to novelty in unseen footage. The first
contribution is a low-level motion model based on what we term tracklet
primitives, which are scene-specific elementary motions. We propose a
clustering-based algorithm for tracklet estimation from local approximations to
tracks of appearance features. This is followed by two methods for motion
novelty inference from tracklet primitives: (a) we describe an approach based
on a non-hierarchial ensemble of Markov chains as a means of capturing
behavioural characteristics at different scales, and (b) a more flexible
alternative which exhibits a higher generalizing power by accounting for
constraints introduced by intentionality and goal-oriented planning of human
motion in a particular scene. Evaluated on a 2h long video of a busy city
marketplace, both algorithms are shown to be successful at inferring unusual
behaviour, the latter model achieving better performance for novelties at a
larger spatial scale
Multiobjective Reliability Allocation in Multi-State Systems: Decision Making by Visualization and Analysis of Pareto Fronts and Sets

ISBN 978-1-4471-2206-7Reliability-based design, operation and maintenance of multi-state systems lead to multiobjective (multicriteria) optimization problems whose solutions are represented in terms of Pareto Fronts and Sets. Among these solutions, the decision maker must choose the ones which best satisfy his\her preferences on the objectives of the problem. Visualization and analysis of the Pareto Fronts and Sets can help decision makers in this task. In this view, a recently introduced graphical representation, called Level Diagrams, is here used in support of the analysis of Pareto Fronts and Sets aimed at reducing the number of non-dominated solutions to be considered by the decision maker. Each objective and design parameter is represented on separate "synchronized" diagrams which position the Pareto front points according to their proximity to ideal preference points and on the basis of this representation a two-step front reduction procedure is proposed. An application to a redundancy allocation problem of literature concerning a multi-state system is used to illustrate the analysis
Distributed Interactive Surfaces: A step towards the distribution of tangible and virtual objects

International audienceAfter having outlined the uses of new technologies such as smartphones, touchscreen tablets and laptops, in this paper we present the TangiSense interactive table, equipped with RFID technology tagged on tangible objects, as new paradigm of interaction for ambient intelligence. We propose a problem space and some scenarios illustrating the distribution of user interfaces within the framework of collective work. A case study centered on crisis management units, i.e. a collaborative situation, with multiple actors who are geographically separate, makes it possible to illustrate possible distributed uses and the TangiSense's capacities. To finish, the chapter presents the directions under consideration for our future research
Cross organisational compatible plans generation framework

This is a conference paper. The original publication is available at www.springerlink.comIn this modern era, organisations have to work in coordination with\ud
many other organisations in order to succeed in business. Interacting organisations\ud
can only proceed in business if they have compatible workflows. This paper proposes\ud
a framework to automatically generate compatible workflows for multiple\ud
interacting organisations from their process definitions and service descriptions.\ud
Existing systems can reconcile existing workflows only, and cannot generate\ud
compatible workflows for multiple organisations automatically. The proposed\ud
system is different from existing systems since it targets workflow collaboration\ud
by generating workflows automatically. This allows the organisations to save the\ud
time that would otherwise be spent in modelling workflows and making them\ud
compatible with the workflows of interacting organisations
Linking behavioral patterns to personal attributes through data re-mining

A fundamental challenge in behavioral informatics is the development of methodologies and systems that can achieve its goals and tasks, including behavior pattern analysis. This study presents such a methodology, that can be converted into a decision support system, by the appropriate integration of existing tools for association mining and graph visualization. The methodology enables the linking of behavioral patterns to personal attributes, through the re-mining of colored association graphs that represent item associations. The methodology is described and mathematically formalized, and is demonstrated in a case study related with retail industry
Scoring and predicting risk preferences

This study presents a methodology to determine risk scores of individuals, for a given financial risk preference survey. To this end, we use a regression-based\ud
iterative algorithm to determine the weights for survey questions in the scoring process. Next, we generate classification models to classify individuals\ud
into risk-averse and risk-seeking categories, using a subset of survey questions. We illustrate the methodology through a sample survey with 656 respondents. We find that the demographic (indirect) questions can be almost as successful as risk-related (direct) questions in predicting risk preference classes of respondents. Using a decision-tree based classification model, we discuss how one can generate actionable business rules based on the findings
RMCASE: COMPUTER-AIDED SUPPORT FOR HYPERMEDIA DESIGN AND DEVELOPMENT

We present the design of a computer-aided environment, RMCase, to support the
design and construction of hypermedia applications. The environment is based upon
the Relationship Management methodology. MCase supports hypermedia design
and development activities. Support for cognitive design processes is achieved
through three fundamental premises that form the foundation of RMCase: (1) fluid
feedback loops between the various methodological stages, (2) manipulation of objects
at the instance level, and (3) lightweight prototyping . To achieve this, RMCase itself
is designed as a hypermedia application, where hypertextual navigation implements
feedback loops. Instance objects can be cloned and abstraction/instantiation
mechanisms are envisioned to facilitate designers back and forth movements between
the abstract and the concrete layers of an application. As a result, RMCase will
support bottom-up, top-down and middle-out software development styles.Information Systems Working Papers Serie
A Generic Knowledge Model for SME Supply Chain Based on Multiagent Paradigm

23 pagesInternational audienceThis chapter is dedicated to the generation of an agentified knowledge model for modeling and simulation of the supply chain in Small and Medium Enterprises (SME) context. For this purpose, the organization of this work is directed by the ArchMDE development process which is founded on Model Driving Engineering (MDE). The fundamental contributions concern two research areas. The first one concerning the industrial engineering scope, proposes a generic domain meta-model (i.e. supply chain integrating SME) identifying the functional concepts and their properties. The second one considering the computer engineering scope, highlights all steps necessary to integrate the dynamic behaviour into the domain meta-model built according to the multi-agent technology. In this perspective, this chapter describes the outcome of these artefacts from the study of the domain through the agentification process, to the implementation of the knowledge model
Reliable online social network data collection

Large quantities of information are shared through online social networks, making them attractive sources of data for social network research. When studying the usage of online social networks, these data may not describe properly users’ behaviours. For instance, the data collected often include content shared by the users only, or content accessible to the researchers, hence obfuscating a large amount of data that would help understanding users’ behaviours and privacy concerns. Moreover, the data collection methods employed in experiments may also have an effect on data reliability when participants self-report inacurrate information or are observed while using a simulated application. Understanding the effects of these collection methods on data reliability is paramount for the study of social networks; for understanding user behaviour; for designing socially-aware applications and services; and for mining data collected from such social networks and applications. This chapter reviews previous research which has looked at social network data collection and user behaviour in these networks. We highlight shortcomings in the methods used in these studies, and introduce our own methodology and user study based on the Experience Sampling Method; we claim our methodology leads to the collection of more reliable data by capturing both those data which are shared and not shared. We conclude with suggestions for collecting and mining data from online social networks.Postprin
Exploring the virtual space of academia

The aim of this chapter is to provide a view on how researchers present themselves in a social network specifically developed for supporting academic practices, how they share information and engage in dialogues with colleagues worldwide. We analysed data from 30,428 users who have registered on a publicly available website to study the effect of academic position, university ranking and country on people's behaviour. Results suggest that the virtual network closely mirrors physical reality, reproducing the same hierarchical structure imposed by position, ranking, and country on user behaviour. Despite the potential for bridging and bonding social capital the networks have not achieved substantial changes in structures and practices of the academic context. Furthermore, our analysis highlights the need of finding new strategies to motivate the users to contribute to the community and support equal participation, as so far the community is mainly exploited as a static website
Stroke Based Painterly Rendering

International audienceMany traditional art forms are produced by an artist sequentially placing a set of marks, such as brush strokes, on a canvas.  Stroke based Rendering (SBR) is inspired by this process, and underpins many early and contemporary Artistic Stylization algorithms.  This Chapter outlines the origins of SBR, and describes key algorithms for placement of brush strokes to create painterly renderings from source images.  The chapter explores both local greedy, and global optimization based approaches to stroke placement. The issue of creative control in SBR is also briefly discussed
Performance evaluation of different CRL distribution schemes embedded in WMN authentication

Wireless Mesh Networks (WMNs) have emerged as a promising technology to provide low cost and scalable solutions for high speed Internet access and additional services. In hybrid WMNs, where mesh clients also act as relaying agents and form a mesh client network, it is important to provide users with an efficient anonymous and accountable authentication scheme. Accountability is required for the malicious users that are to be identified and revoked from the network access and related services. Promising revocation schemes are based on Certification Revocation Lists (CRLs). Since in hybrid WMNs mesh clients also authenticate other clients, distribution of these CRLs is an important task. In this paper, we propose and examine the performance of different distribution schemes of CRLs and analyze authentication performance in two scenarios: in one scenario all mesh routers and mesh clients obtain CRLs and in the second one, CRLs are held only by the mesh routers and mesh clients acting as relaying agents require CRL checking to be performed from the router in authenticating another client
Learning Equilibria in Games by Stochastic Distributed Algorithms

International audienceWe consider a family of stochastic distributed dynamics to learn equilibria in games, that we prove to correspond to an Ordinary Differential Equation (ODE). We focus then on a class of stochastic dynamics where this ODE turns out to be related to multipopulation replicator dynamics.Using facts known about convergence of this ODE, we discuss the convergence of the initial stochastic dynamics. For general games, there might be non-convergence, but when the convergence of the ODE holds, considered stochastic algorithms converge towards Nash equilibria. For games admitting a multiaffine Lyapunov function, we prove that this Lyapunov function is a super-martingale over the stochastic dynamics and that the stochastic dynamics converge. This leads a way to provide bounds on their time of convergence by martingale arguments. This applies in particular for many classes of games considered in literature, including several load balancing games and congestion games
Cost and Benefits of Denser Topologies for the Smart Grid

The Smart Grid promises to reshape how electricity is generated, distributed, and used. More delocalized generation based on renewable sources will transform end-users into prosumers (producers and consumers) of energy. These will require electric and supporting ICT infrastructures to be able to openly access the energy market. In this paper, we focus on the electric infrastructure issue related to the Smart Grid topic. We consider network models from the literature of Complex Network Analysis and evaluate their ability to be used for the Distribution Grid to reduce the cost of electricity distribution based on topological property. Our initial conclusion is that denser topologies are helpful to reach the goal. However, the cost of realizing such topologies in terms of cabling is not negligible, as we show.