pinecone/core-2020-05-10-deduplication huggingface dataset:
Verifying cryptographic software correctness with respect to reference implementations

This paper presents techniques developed to check program equivalences in the context of cryptographic software development, where specifications are typically reference implementations. The techniques allow for the integration of interactive proof techniques (required given the difficulty and generality of the results sought) in a verification infrastructure that is capable of discharging many verification conditions automatically. To this end, the difficult results in the verification process (to be proved interactively) are isolated as a set of lemmas. The fundamental notion of natural invariant is used to link the specification level and the interactive proof construction process.Fundação para a Ciência e a Tecnologia (FCT
Controlled English for Reasoning on the Semantic Web

The existing Semantic Web languages have a very technical focus and fail to provide good usability for users with no background in formal methods. We argue that controlled natural languages like Attempto Controlled English (ACE) can solve this problem. ACE is a subset of English that can be translated into various logic based languages, among them the Semantic Web standards OWL and SWRL. ACE is accompanied by a set of tools, namely the parser APE, the Attempto Reasoner RACE, the ACE View ontology and rule editor, the semantic wiki AceWiki, and the Protune policy framework. The applications cover a wide range of Semantic Web scenarios, which shows how broadly ACE can be applied. We conclude that controlled natural languages can make the Semantic Web better understandable and more usable
P300 Detection Based on Feature Extraction in On-line Brain-Computer Interface

We propose a new EEG-based wireless brain computer interface (BCI) with which subjects can “mind-type” text on a computer screen. The application is based on detecting P300 event-related potentials in EEG signals recorded on the scalp of the subject. The BCI uses a simple classifier which relies on a linear feature extraction approach. The accuracy of the presented system is comparable to the state-of-the-art for on-line P300 detection, but with the additional benefit that its much simpler design supports a power-efficient on-chip implementation.status: publishe
Case retrieval in ontology-based CBR systems

International audienceThis paper presents our knowledge-intensive Case-Based Reasoning platform for diagnosis, COBRA. It integrates domain knowledge along with cases in an ontological structure. COBRA allows users to describe cases using any concept or instance of a domain ontology, which leads to a heterogeneous case base. Cases heterogeneity complicates their retrieval since correspondences must be identified between query and case attributes. We present in this paper our system architecture and the case retrieval phase. Then, we introduce the notions of similarity regions and attributes' roles used to overcome cases heterogeneity problems
Analyzing the EGEE production grid workload: application to jobs submission optimization

International audienceGrids reliability remains an order of magnitude below clusters on production infrastructures. This work is aims at improving grid application performances by improving the job submission system. A stochastic model, capturing the behavior of a complex grid workload management system is proposed. To instantiate the model, detailed statistics are extracted from dense grid activity traces. The model is exploited in a simple job resubmission strategy. It provides quantitative inputs to improve job submission performance and it enables quantifying the impact of faults and outliers on grid operations
A methodology and framework for the semi-automatic assembly of learning objects

One of the major obstacles in developing high quality content for learning is the substantial development cost and effort. In addition, the return on investment is often low, as developed learning materials are difficult to reuse and adapt to new and different educational contexts. In this paper, we present a semi-automatic content assembly methodology to automate, at least partially, the reuse of existing learning content in high quality and effective learning sequences. In addition, we present a case study that integrates the approach into the LAMS learning design environment.status: publishe
A framework to author educational interactions for geographical web applications

International audienceThis paper focuses on the production of authoring tools that teachers may use to prototype interactive geographical web applications. We present some computational models and a toolset that we designed to address some needs of teachers trying to make use of particular localized documents called "travel stories". Our research challenge is to enable teachers to design interaction scenarios for such a domain, avoiding any programmer intervention. In the design process, the teacher typically faces three activities: (a) Identification of candidate documents, (b) Evaluation of the adequacy of the document and (c) Production of the learning application making use of the selected document. In this paper, we mainly focus on the (c) Production activity. We highlight the necessary use of an "agile" approach to shorten as much as possible the delay between the design and the evaluation step of a prototype. To address the technological challenges raised by such an aim, we present WIND framework and we discuss its capabilities while considering some examples of interactive scenarios generated with WIND framework
The Cost of Stability in Coalitional Games

A key question in cooperative game theory is that of coalitional stability,
usually captured by the notion of the \emph{core}--the set of outcomes such
that no subgroup of players has an incentive to deviate. However, some
coalitional games have empty cores, and any outcome in such a game is unstable.
  In this paper, we investigate the possibility of stabilizing a coalitional
game by using external payments. We consider a scenario where an external
party, which is interested in having the players work together, offers a
supplemental payment to the grand coalition (or, more generally, a particular
coalition structure). This payment is conditional on players not deviating from
their coalition(s). The sum of this payment plus the actual gains of the
coalition(s) may then be divided among the agents so as to promote stability.
We define the \emph{cost of stability (CoS)} as the minimal external payment
that stabilizes the game.
  We provide general bounds on the cost of stability in several classes of
games, and explore its algorithmic properties. To develop a better intuition
for the concepts we introduce, we provide a detailed algorithmic study of the
cost of stability in weighted voting games, a simple but expressive class of
games which can model decision-making in political bodies, and cooperation in
multiagent settings. Finally, we extend our model and results to games with
coalition structures.Comment: 20 pages; will be presented at SAGT'0
Visual Registration Method for a Low Cost Robot

The original publication is available at www.springerlink.comAn autonomous mobile robot must face the correspondence\ud
or data association problem in order to carry out\ud
tasks like place recognition or unknown environment mapping. In\ud
order to put into correspondence two maps, most correspondence\ud
methods first extract early features from robot sensor data,\ud
then matches between features are searched and finally the\ud
transformation that relates the maps is estimated from such\ud
matches. However, finding explicit matches between features is a\ud
challenging and computationally expensive task. In this paper, we\ud
propose a new method to align obstacle maps without searching\ud
explicit matches between features. The maps are obtained from a\ud
stereo pair. Then, we use a vocabulary tree approach to identify\ud
putative corresponding maps followed by a Newton minimization\ud
algorithm to find the transformation that relates both maps. The\ud
proposed method is evaluated on a typical office dataset showing\ud
good performance.This work has been partially funded by TIN 2006-15308-\ud
C02-02 project grant of the Ministry of Education of Spain,\ud
the CSD2007-00018 Consolider Ingenio 2010, the FI grant and\ud
the BE grant from the AGAUR, the European Social Fund,\ud
the 2005/SGR/00093 project, supported by the Generalitat de\ud
Catalunya, the MIDCBR project grant TIN 200615140C0301,\ud
TIN 200615308C0202 and FEDER funds.Peer reviewe
An intelligent alarm management system for large-scale telecommunication companies

This paper introduces an intelligent system that performs alarm correlation and root cause analysis. The system is designed to operate in large- scale heterogeneous networks from telecommunications operators. The pro- posed architecture includes a rules management module that is based in data mining (to generate the rules) and reinforcement learning (to improve rule se- lection) algorithms. In this work, we focus on the design and development of the rule generation part and test it using a large real-world dataset containing alarms from a Portuguese telecommunications company. The correlation engine achieved promising results, measured by a compression rate of 70% and as- sessed in real-time by experienced network administrator staff
Instability in spatial evolutionary games

We investigate the aspects that influence the instability of
spatial evolutionary games, namely the Prisoner's Dilemma and the
Snowdrift games. In this paper instability is defined as the proportion of
strategy changes in the asymptotic period of the evolutionary process.
The results show that with the Prisoner's Dilemma, when the level of
noise present in the decision process is very low, the instability decreases
as the synchrony rate decreases. With the Snowdrift this pattern of behavior
depends strongly on the interaction topology and arises only for
random and scale-free networks. However, for large noise values, the instability
in both games depends only on the proportion of cooperators
present in the population: it increases as the proportion of cooperators
approaches 0.5. We advance an explanation for this behavior
Computing confidence Values: does trust dynamics matter?

Computing Confidence Values: Does Trust Dynamics Matter?Em um Sistema Multi-agente, a selecção de outros agentes para trabalho conjunto depende da eventual confiança que é esperada existir no desempenho desses outros.Propomos uma forma de agregar indícios para computar correctamente uma função cujo resultado seja um valor de confiançaComputational Trust and Reputation (CTR) systems are platforms capable of collecting trust information about candidate partners and of computing confidence scores for each one of these partners. These systems start to be viewed as vital elements in environments of electronic institutions, as they support fundamental decision making processes, such as the selection of business partners and the automatic and adaptive creation of contractual terms and associated enforcement methodologies. In this article, we propose a model for the aggregation of trust evidences that computes confidence scores taking into account dynamic properties of trust. We compare our model with a traditional statistical model that uses weighted means to compute trust, and show experimental results that show that in certain scenarios the consideration of the trust dynamics allows for a better estimation of confidence scores
Using data mining for wine quality assessment

Certiﬁcation and quality assessment are crucial issues within 
the wine industry. Currently, wine quality is mostly assessed by physico- 
chemical (e.g alcohol levels) and sensory (e.g. human expert evaluation) 
tests. In this paper, we propose a data mining approach to predict wine 
preferences that is based on easily available analytical tests at the certiﬁ- 
cation step. A large dataset is considered with white vinho verde samples 
from the Minho region of Portugal. Wine quality is modeled under a re- 
gression approach, which preserves the order of the grades. Explanatory 
knowledge is given in terms of a sensitivity analysis, which measures the 
response changes when a given input variable is varied through its do- 
main. Three regression techniques were applied, under a computationally 
efficient procedure that performs simultaneous variable and model selec- 
tion and that is guided by the sensitivity analysis. The support vector 
machine achieved promising results, outperforming the multiple regres- 
sion and neural network methods. Such model is useful for understand- 
ing how physicochemical tests affect the sensory preferences. Moreover, 
it can support the wine expert evaluations and ultimately improve the 
production
It's not only about technology, it's about people: interpersonal skills as a part of the IT education.

Proceedings of: Second World Summit on the Knowledge Society (WSKS 2009), Chania, Crete, Greece, September 16-18, 2009.The importance of what have been termed the "soft skills" for the professional development of IT professionals is beyond any doubt. Taking account of this circumstance, the objective of the current research may be phrased as two separate questions. In the first place, determining the importance which IT related degree students place on these types of competencies for their professional future. In the second place, the importance which the development of the mentioned competencies has been given during their studies. The realization of an empirical study has fulfilled the two objectives described. The results demonstrate, on the one side, the moderate relevance which students assign to interpersonal competencies, especially emotional competencies, in contrast to the international curricular recommendations and studies concerning labor markets. On the other hand, the results indicate the scarce emphasis which lecturers have placed on the development of such competencies.Publicad
ERP and four dimensions of absorptive capacity: lessons from a developing country

Enterprise resource planning systems can grant crucial strategic, operational
and information-based benefits to adopting firms when implemented successfully. However, a failed implementation can often result in financial losses rather than profits. Until now, the research on the failures and successes were focused on implementations in large manufacturing and service organizations firms located in western countries, particularly in USA. Nevertheless, IT has gained intense diffusion to developing countries through declining hardware costs and increasing benefits that merits attention as much as developed countries.
The aim of this study is to examine the implications of knowledge transfer
in a developing country, Turkey, as a paradigm in the knowledge society with a
focus on the implementation activities that foster successful installations.
We suggest that absorptive capacity is an important characteristic of a firm that
explains the success level of such a knowledge transfer.Publicad
Memory usage verification using Hip/Sleek.

Embedded systems often come with constrained memory footprints. It is therefore essential to ensure that software running on such platforms fulfils memory usage specifications at compile-time, to prevent memory-related software failure after deployment. Previous proposals on memory usage verification are not satisfactory as they usually can only handle restricted subsets of programs, especially when shared mutable data structures are involved. In this paper, we propose a simple but novel solution. We instrument programs with explicit memory operations so that memory usage verification can be done along with the verification of other properties, using an automated verification system Hip/Sleek developed recently by Chin et al.[10,19]. The instrumentation can be done automatically and is proven sound with respect to an underlying semantics. One immediate benefit is that we do not need to develop from scratch a specific system for memory usage verification. Another benefit is that we can verify more programs, especially those involving shared mutable data structures, which previous systems failed to handle, as evidenced by our experimental results
Dynamic Observers for the Synthesis of Opaque Systems

International audienceIn this paper, we address the problem of synthesizing opaque systems. A secret predicate S over the runs of a system G is opaque to an external user having partial observability over G, if s/he can never infer from the observation of a run of G that the run belongs to S. We first investigate the case of static partial observability where the set of events the user can observe is fixed a priori. In this context, we show that checking whether a system is opaque is PSPACE-complete, which implies that computing an optimal static observer ensuring opacity is also a PSPACE-complete problem. Next, we introduce dynamic partial observability where the set of events the user can observe changes over time. We show how to check that a system is opaque w.r.t. to a dynamic observer and also address the corresponding synthesis problem: given a system G and secret states S, compute the set of dynamic observers under which S is opaque. Our main result is that the set of such observers can be finitely represented and can be computed in EXPTIME
CLAN : a tool for contract analysis and conflict discovery

As Service-Oriented Architectures are more widely adopted, it becomes more important to adopt measures for ensuring that the services satisfy functional and non-functional requirements. One approach is the use of contracts based on deontic logics, expressing obligations, permissions and prohibitions of the different actors. A challenging aspect is that of service composition, in which the contracts composed together may result in conflicting situations, so there is a need to analyse contracts and ensure their soundness. In this paper, we present CLAN, a tool for automatic analysis of conflicting clauses of contracts written in the contract language . We present a small case study of an airline check-in desk illustrating the use of the tool.peer-reviewe
Characterising anomalous events using change point correlation on unsolicited network traffic

Monitoring unused or dark IP addresses offers opportunities to extract useful information about both on-going and new attack patterns. In recent years, different techniques have been used to analyze such traffic including sequential analysis where a change in traffic behavior, for example change in mean, is used as an indication of malicious activity. Change points themselves say little about detected change; further data processing is necessary for the extraction of useful information and to identify the exact cause of the detected change which is limited due to the size and nature of observed traffic. In this paper, we address the problem of analyzing a large volume of such traffic by correlating change points identiﬁed in different traffic parameters. The signiﬁcance of the proposed technique is two-fold. Firstly, automatic extraction of information related to change points by correlating change points detected across multiple traffic parameters. Secondly, validation of the detected change point by the simultaneous presence of another change point in a diﬀerent parameter. Using a real network trace collected from unused IP addresses, we demonstrate that the proposed technique enables us to not only validate the change point but also extract useful information about the causes of change points
On the Success Rate of Crossover Operators for Genetic Programming with
  Offspring Selection

Genetic programming is a powerful heuristic search technique that is used for
a number of real world applications to solve among others regression,
classification, and time-series forecasting problems. A lot of progress towards
a theoretic description of genetic programming in form of schema theorems has
been made, but the internal dynamics and success factors of genetic programming
are still not fully understood. In particular, the effects of different
crossover operators in combination with offspring selection are largely
unknown.
  This contribution sheds light on the ability of well-known GP crossover
operators to create better offspring when applied to benchmark problems. We
conclude that standard (sub-tree swapping) crossover is a good default choice
in combination with offspring selection, and that GP with offspring selection
and random selection of crossover operators can improve the performance of the
algorithm in terms of best solution quality when no solution size constraints
are applied.Comment: The final publication is available at
  http://link.springer.com/chapter/10.1007/978-3-642-04772-5_10
Partial symbol ordering distance

Nowadays sequences of symbols are becoming more important, as they are the standard format for representing information in a large variety of domains such as ontologies, sequential patterns or non numerical attributes in databases. Therefore, the development of new distances for this kind of data is a crucial need. Recently, many similarity functions have been proposed for managing sequences of symbols; however, such functions do not always hold the triangular\ud
inequality. This property is a mandatory requirement in many data mining algorithms like clustering or k-nearest neighbors algorithms, where the presence of a metric space is a must. In this paper, we propose a new distance for sequences of (non-repeated) symbols based on the partial distances between the positions of the common symbols. We prove that this Partial Symbol Ordering distance satisfies the triangular inequality property, and we finally describe a set of experiments supporting that the new distance outperforms the Edit distance in those  ecenarios where sequence similarity is related to the positions occupied by the symbols.Postprint (published version
Inducing metaassociations and induced relationships

In the last years, UML has been tailored to be used as a domainspecific modelling notation in several contexts. Extending UML with this purpose entails several advantages: the integration of the domain in a standard framework; its potential usage by the software engineering community; and the\ud
existence of supporting tools. In previous work, we explored one particular issue of heavyweight extensions, namely, the definition of inducing metaassociations\ud
in metamodels as a way to induce the presence of specific relationships in their instances. Those relationships were intended by the metamodel specifier but not forced by the metamodel itself. However, our work was\ud
restricted to the case of induced associations. This paper proposes an extension to the general case in which inducing metaassociations may force the existence of arbitrary relationships at M1. To attain this goal, we provide a general definition of inducing metaassociation that covers all the possible cases. After revisiting induced associations, we show the inducement of the other relationship\ud
types defined in UML: association classes, generalization and dependencies.Peer ReviewedPostprint (author’s final draft