pinecone/core-2020-05-10-deduplication huggingface dataset:
DEEP: a provenance-aware executable document system

This is a book chapter from Provenance and Annotation of Data and Processes, Lecture Notes in Computer Science 7525 [© Springer-Verlag]. The definitive version is available at: http://dx.doi.org/10.1007/978-3-642-34222-6_3The concept of executable documents is attracting growing interest from both academics and publishers since it is a promising technology for the the dissemination of scientific results. Provenance is a kind of metadata that provides a rich description of the derivation history of data products starting from their original sources. It has been used in many different e-Science domains and has shown great potential in enabling reproducibility of scientific results. However, while both executable documents and provenance are aimed at enhancing the dissemination of scientific results, little has been done to explore the integration of both techniques. In this paper, we introduce the design and development of Deep, an executable document environment that generates scientific results dynamically and interactively, and also records the provenance for these results in the document. In this system, provenance is exposed to users via an interface that provides them with an alternative way of navigating the executable document. In addition, we make use of the provenance to offer a document rollback facility to users and help to manage the system’s dynamic resources
Automatic discovery of high-level provenance using semantic similarity

As interest in provenance grows among the Semantic Web community, it is recognized as a useful tool across many domains. However, existing automatic provenance collection techniques are not universally applicable. Most existing methods either rely on (low-level) observed provenance, or require that the user discloses formal workflows. In this paper, we propose a new approach for automatic discovery of provenance, at multiple levels of granularity. To accomplish this, we detect entity derivations, relying on clustering algorithms, linked data and semantic similarity. The resulting derivations are structured in compliance with the Provenance Data Model (PROV-DM). While the proposed approach is purposely kept general, allowing adaptation in many use cases, we provide an implementation for one of these use cases, namely discovering the sources of news articles. With this implementation, we were able to detect 73% of the original sources of 410 news stories, at 68% precision. Lastly, we discuss possible improvements and future work
Flame Detection for Video-Based Early Fire Warning for the Protection of Cultural Heritage

Cultural heritage and archaeological sites are exposed to the risk of fire and early warning is the only way to avoid losses and damages. The use of terrestrial systems, typically based on video cameras, is currently the most promising solution for advanced automatic wildfire surveillance and monitoring. Video cameras are sensitive in visible spectra and can be used either for flame or smoke detection. This paper presents and compares three video-based flame detection techniques, which were developed within the FIRESENSE EU research project
Reconstrucción virtual del estado previo de una iglesia en ruinas

Contributed to: 4th International Conference, EuroMed 2012, Limassol, Cyprus, October 29 – November 3, 2012.[EN] This document is related with the master thesis "Geometric documentation and reconstruction of the church of the Monastery of San Prudencio (La Rioja, Spain)", http://hdl.handle.net/10810/7096[ES] Este artículo está relacionado con el proyecto fin de carrera titulado This document is related with the master thesis "Documentación geométrica y reconstrucción de la iglesia del Monasterio de San Prudencio (La Rioja, España)", http://hdl.handle.net/10810/7096[EN] Three dimensional virtual models can represent both the existing and the already destroyed architectural heritage. This project deals with the 3D reconstruction and representation of the church of San Prudencio's Monastery in La Rioja (Spain) as it is supposed to be during the 15th century. Today the monument is totally in ruins; hence severe reconstruction was needed. This is an exemplary project of close collaboration of different scientific fields. Surveying data of the monument itself and of the wider area around it, but also architectural and archaeological data were collected in situ. It was not possible from the current situation to conclude about the exact form, style and representation of the monument; hence a large part of the project is based on assumptions which have a sound scientific base. Because of the multisource data there was need to define specific criteria by which every data source was evaluated.[ES] Los modelos tridimensionales pueden representar tanto los elementos patrimoniales existentes como los ya han dejado de existir. En este proyecto se trata la reconstrucción tridimensional de la iglesia del Monasterio de San Prudencio de Monte Laturce (Clavijo, La Rioja, España) tal como se supone que fue durante el siglo XV.
En la actualidad el edificio está arruinado por lo que ha sido necesario realizar una importante reconstrucción virtual basad en hipótesis que han requerido la colaboración de técnicos de diferentes áreas de conocimiento, por ejemplo,
se ha contado con un levantamiento topográfico de los restos y del área circundante, datos sobre los materiales e hipótesis arqueológicas y arquitectónicas.
Dado que existe información de múltiples fuentes, ha sido necesario incorporar un conjunto de criterios de selección y evaluación de las mismas.This project is an outcome of the ERASMUS IP activity “TOPCART Geometric documentation of Heritage: European integration of technologies” undertaken during the summer 2010 2009-1-ES1-ERAIP-0013) and 2011 (2010-1-ES1-ERA10-0024)
Defending against the Unknown Enemy: Applying FlipIt to System Security

Most cryptographic systems carry the basic assumption that entities are able to preserve the secrecy of their keys. With attacks today showing ever increasing sophistication, however, this tenet is eroding. “Advanced Persistent Threats” (APTs), for instance, leverage zero-day exploits and extensive system knowledge to achieve full compromise of cryptographic keys and other secrets. Such compromise is often silent, with defenders failing to detect the loss of private keys critical to protection of their systems. The growing virulence of today’s threats clearly calls for new models of defenders’ goals and abilities.

In this paper, we explore applications of FlipIt, a novel game-theoretic model of system defense introduced in [14]. In FlipIt, an attacker periodically gains complete control of a system, with the unique feature that system compromises are stealthy, i.e., not immediately detected by the system owner, called the defender. We distill out several lessons from our study of FlipIt and demonstrate their application to several real-world problems, including password reset policies, key rotation, VM refresh and cloud auditing
Why Neurons Are Not the Right Level of Abstraction for Implementing Cognition

International audienceThe cortex accounts for 70% of the brain volume. The human cortex is made of micro-columns, arrangements of 110 cortical neurons (Mountcastle), grouped in by the thousand in so-called macro-colums (or columns) which belong to the same functional unit as exemplified by Nobel laureates Hubel and Wiesel with the orientation columns of the primary visual cortex. The cortical column activity does not exhibit the limitations of single neurons: activation can be sustained for very long periods (sec.) instead of been transient and subject to fatigue. Therefore, the cortical column has been proposed as the building block of cognition by several researchers, but to not effect – since explanations about how the cognition works at the column level were missing. Thanks to the Theory of neuronal Cognition, it is no more the case. The cortex functionality is cut into small areas: the cortical maps. Today, about 80 cortical maps are known in the primary and secondary cortex [1]. These maps form a hierarchical organization. A cortical map is a functional structure encompassing several thousands of cortical columns. The function of such maps (also known as Kohonen maps) is to build topographic (i.e., organized and localized) representations of the input stimulii (events). This organization is such that similar inputs activate either the same cortical column or neighboring columns. Also, the more frequent the stimulus, the greater the number of cortical columns involved. Each map acts as a novelty detector and a filter. Events are reported as patterns of activations on various maps, each map specialized in a specific " dimension ". Spatial and temporal coordinates of events are linked to activations within the hippo-campus and define de facto the episodic memory. Learning is achieved at neuronal level using the famous Hebb's law: " Neurons active in the same time frame window reinforce their connections ". This rule does not respect " causality ". This, plus the fact that there is at least as much feedback connections as there are feed-forward ones, explain why a high level cortical activation generates a low level cortical pattern of activations – the same one that would trigger this high level activity. Therefore, our opinion is that the true building block of the cognition is a set of feed-forward and feedback connections between at least two maps, each map a novelty detector
More anti-chain based refinement checking

Refinement checking plays an important role in system verification. It establishes properties of an implementation by showing a refinement relationship between the implementation and a specification. Recently, it has been shown that anti-chain based approaches increase the efficiency of trace refinement checking significantly. In this work, we study the problem of adopting anti-chain for stable failures refinement checking, failures-divergence refinement checking and probabilistic refine checking (i.e., a probabilistic implementation against a non-probabilistic specification). We show that the first two problems can be significantly improved, because the state space of the product model may be reduced dramatically. Though applying anti-chain for probabilistic refinement checking is more complicated, we manage to show improvements in some cases. We have integrated these techniques into the PAT model checking framework. Experiments are conducted to demonstrate the efficiency of our approach.Full Tex
An analytical and experimental comparison of CSP extensions and tools

Communicating Sequential Processes (CSP) has been widely applied to modeling and analyzing concurrent systems. There have been considerable efforts on enhancing CSP by taking data and other system aspects into account. For instance, CSPM combines CSP with a functional programming language whereas CSP# integrates high-level CSP-like process operators with low-level procedure code. Little work has been done to systematically compare these CSP extensions, which may have subtle and substantial differences. In this paper, we compare CSPM and CSP# not only on their syntax, but also operational semantics as well as their supporting tools such as FDR, ProB, and PAT. We conduct extensive experiments to compare the performance of these tools in different settings. Our comparison can be used to guide users to choose the appropriate CSP extension and verification tool based on the system characteristics.Full Tex
Symbolic model-checking of stateful timed CSP using BDD and digitization

Stateful Timed CSP has been recently proposed to model (and verify) hierarchical real-time systems. It is an expressive modeling language which combines data structure/operations, complicated control flows (modeled using compositional process operators adopted from Timed CSP), and real-time requirements like deadline and within. It has been shown that Stateful Timed CSP is equivalent to closed timed automata with silent transitions, which implies that the timing constraints of Stateful Timed CSP can be captured using explicit tick events, through digitization. In order to tackle the state space explosion problem, we develop a BDD-based symbolic model checking approach to verify Stateful Timed CSP models. Due to the rich language features, BDD-based system encoding and verification is highly nontrivial. In this work, we show how to systematically encode Stateful Timed CSP models in BDD. Our approach consists of two steps. The first step is to identify maximum primitive components of a given system and then generate finite state machines (FSMs) from them, applying a set of symbolic firing rules. These FSMs are then encoded in the standard way. The second step is to compose the encoded components using a set of BDD-based compositional functions. The proposed method has been implemented in the PAT model checker. It supports properties like reachability, linear temporal logic, etc. The effectiveness of our technique is evaluated with benchmark systems.Full Tex
State space c-reductions for concurrent systems in rewriting logic

We present c-reductions, a simple, flexible and very general state space reduction technique that exploits an equivalence relation on states that is a bisimulation. Reduction is achieved by a canonizer function, which maps each state into a not necessarily unique canonical representative of its equivalence class. The approach contains symmetry reduction and name reuse and name abstraction as special cases, and exploits the expressiveness of rewriting logic and its realization in Maude\ud
to automate c-reductions and to seamlessly integrate model checking and the discharging of correctness proof obligations. The performance of the approach has been validated over a set of representative case studies
t-words: playing with sounds and creating narratives

We present t-words an interface for children to playful explore
sounds, words and sentences while developing pre-literate skills. The interface
consists of rectangular blocks in which children can record and then play the
recorded audio. Additionally children can personalize the blocks by drawing on
their surface. Children can engage in different literacy related activities such as
building rhymes, playing with sounds and words as well as trying out different
combinations of sentences while engaging in storytelling. Since the interface
targets audio skills it may foster the development of phonological awareness
and sensitiveness, helping to promote children’s early literacy.Fundação para a Ciência e a Tecnologia (FCT) - PTDC/CPE-CED /110417/2009 ; SFRH/BD/62531/200
Producing while consuming: Social interaction around photos shared within private group

User-generated content plays a pivotal role in the current social media. The main focus, however, has been on the explicitly generated user content such as photos, videos and status updates on different social networking sites. In this paper, we explore the potential of implicitly generated user content, based on users’ online consumption behaviors. It is technically feasible to record users’ consumption behaviors on mobile devices and share that with relevant people. Mobile devices with such capabilities could enrich social interactions around the consumed content, but it may also threaten users’ privacy. To understand the potentials of this design direction we created and evaluated a low-fidelity prototype intended for photo sharing within private groups. Our prototype incorporates two design concepts, namely, FingerPrint and MoodPhotos that leverage users’ consumption history and emotional responses. In this paper, we report user values and user acceptance of this prototype from three participatory design workshops
RobotML, a Domain-Specific Language to Design, Simulate and Deploy Robotic Applications

International audienceA large number of robotic software have been developed but cannot or can hardly interoperate with each other because of their dependencies on specific hardware or software platform is hard-wired into the code. Consequently, robotic software is hard and expensive to develop because there is little opportunity of reuse and because low-level details must be taken into account in early phases. Moreover, robotic experts can hardly develop their application without programming knowledge or the help of programming experts and robotic software is difficult to adapt to hardware or target-platform changes. In this paper we report on the development of RobotML, a Robotic Modeling Language that eases the design of robotic applications, their simulation and their deployment to multiple target execution platforms
Visual-Trace Simulation of Concurrent Finite-State Machines for Validation and Model-Checking of Complex Behaviour

Simulation of models that specify behaviour of software in robots, embedded systems, and safety critical systems is crucial to ensure correctness. This is particularly important in conjunction with model- driven development, which is highly prevalent due to its numerous ben- efits. We use vectors of finite-state machines (FSMs) as our modelling tool. Our FSMs can have their transitions labeled by expressions of a common sense logic, and they are more expressive than other modelling approaches (such as Behavior Trees, Petri nets, or plain FSMs). We inter- pret the models using the same round-robin scheduler which is integrated into the simulator. Execution on a platform is exactly the same as in the simulator (where sensors and actuators are masqueraded by proxies) and coincides with the generator of the Kripke structure for formal model- checking. In three ubiquitous case studies we show that our simulation discovers issues where those models were incomplete, ambiguous, or in- correct. This further illustrates that simulation and monitoring need to complement formal verification.Griffith Sciences, School of Information and Communication TechnologyFull Tex
Penalized additive regression for space-time data: a Bayesian perspective

We propose extensions of penalized spline generalized additive models for analysing space-time regression data and study them from a Bayesian perspective. Non-linear effects of continuous covariates and time trends are modelled through Bayesian versions of penalized splines, while correlated spatial effects follow a Markov random field prior. This allows to treat all functions and effects within a unified general framework by assigning appropriate priors with different forms and degrees of smoothness. Inference can be performed either with full (FB) or  empirical Bayes (EB) posterior analysis. FB inference using MCMC techniques is a slight extension of own previous work. For EB inference, a computationally efficient solution is developed on the basis of a generalized linear mixed model representation. The second approach can be viewed as posterior mode estimation and is closely related to penalized likelihood estimation in a frequentist setting. Variance components, corresponding to smoothing parameters, are then estimated by using marginal likelihood. We carefully compare both inferential procedures in simulation studies and illustrate them through real data applications. The methodology is available in the open domain statistical package BayesX and as an S-plus/R function.
A Design Process for Exhibiting Design Choices and Trade-offs in (potentially) Conflicting User Interface Guidelines

In the last decades a huge amount of knowledge about user interface
design has been gathered in the form of guidelines. Quite often, guidelines are
compiled according to user interface properties (e.g. usability, accessibility)
and/or application domains (e.g. Web, mobile). In many situations designers
have to combine several guideline sets in order to address the specific
application domain and the desired set of properties corresponding to the
application under consideration. Despite the fact that the problems related to the
selection of guidelines from different sources are not new, the occurrence and
management of conflicting guidelines are poorly documented leaving designers
with little help in order to handle conflicts in a rationale and consistent way. In
this paper we revise the questions related to selection and management of
conflicting guidelines and we propose a systematic approach based on design
rationale tools and techniques for exhibiting choices and trade-offs when
combining different guidelines sets. This paper illustrates how such as an
approach can also be used to deepen the knowledge on the use of user interface
guidelines recording decisions across projects in an iterative way.The work has been supported by Universitat de Lleida for pre-doctoral fellowship to Llúcia Masip and the EU project FEDER Ubiloop
Can GUI implementation markup languages be used for modelling?

The current diversity of available devices and form factors 
increases the need for model-based techniques to support adapting applications
from one device to another.Most work on user interface modelling
is built around declarative markup languages. Markup languages play a
relevant role, not only in the modelling of user interfaces, but also in their
implementation. However, the languages used by each community (modellers/
developers) have, to a great extent evolved separately. This means
that the step from concrete model to final interface becomes needlessly
complicated, requiring either compilers or interpreters to bridge this gap.
In this paper we compare a modelling language (UsiXML) with several
markup implementation languages. We analyse if it is feasible to use the
implementation languages as modelling languages
Many to many mobile maps

© Springer-Verlag Berlin Heidelberg 2013. The rapid development of mobile computing devices along with a variety of Web 2.0 social networking tools has led to a dramatic change in the way maps and other spatial displays are utilized. The evolution from stand-alone desktop GIS to the interactive, mobile devices, in which information from one or more sources and is sent to one or more sinks, is discussed. The result is access to real-time information, which is generated from both traditional sources, social networks, and other specialized geowikis. Both the benefits of many to many mobile maps and the emergence of new problems, such as understanding the needs of the user and providing appropriate context, are discussed
Bayesian optimization using sequential Monte Carlo

International audienceWe consider the problem of optimizing a real-valued continuous function $f$ using a Bayesian approach, where the evaluations of $f$ are chosen sequentially by combining prior information about $f$, which is described by a random process model, and past evaluation results. The main difficulty with this approach is to be able to compute the posterior distributions of quantities of interest which are used to choose evaluation points. In this article, we decide to use a Sequential Monte Carlo (SMC) approach
A hyper-heuristic inspired by pearl hunting

Pearl hunting is a traditional way of diving to retrieve pearl from pearl oysters or to hunt some other sea creatures. In some areas, hunters need to dive and search seafloor repeatedly at several meters depth for pearl oysters. In a search perspective, pearl hunting consists of repeated diversification (to surface and change target area) and intensification (to dive and find pearl oysters). A Pearl Hunter (PHunter) hyper-heuristic is inspired by the pearl hunting, as shown in Fig. 1. Given a problem domain and some low-level heuristics (LLHs), PHunter can group, test, select and organize LLHs for the domain by imitating a rational diver.Department of Industrial and Systems Engineeringpreprint_postprin