pinecone/core-2020-05-10-deduplication huggingface dataset:
Noisy mean field game model for malware propagation in opportunistic networks

978-3-642-30372-2International audienceIn this paper we present analytical mean eld techniques that can be used to better understand the behavior of malware propagation in opportunistic large networks. We develop a modeling methodology based on stochastic mean eld optimal control that is able to capture many aspects of the problem, especially the impact of the control and heterogeneity of the system on the spreading characteristics of malware. The stochastic large process characterizing the evolution of the total number of infected nodes is examined with a noisy mean eld limit and compared to a deterministic one. The stochastic nature of the wireless environment make stochastic approaches more realistic for such types of networks. By introducing control strategies, we show that the fraction of infected nodes can be maintained below some threshold. In contrast to most of the existing results on mean eld propagation models which focus on deterministic equations, we show that the mean eld limit is stochastic if the second moment of the number of object transitions per time slot is unbounded with the size of the system. This allows us to compare one path of the fraction of infected nodes with the stochastic trajectory of its mean eld limit. In order to take into account the heterogeneity of opportunistic networks, the analysis is extended to multiple types of nodes. Our numerical results show that the heterogeneity can help to stabilize the system. We verify the results through simulation showing how to obtain useful approximations in the case of very large systems
A comparative study of impairments aware optical networks planning tools

Transparent and translucent optical networks are widely considered as the prime candidates for the core network technology of the future. These networks provide ultra high speed end-to-end connectivity with high quality of service (QoS) and resilience to failures. This will be achieved through appropriate network planning techniques. A downside of transparency, however, is the accumulation of physical layer impairments\ud
over long distances, which are difficult to mitigate using purely physical-layer techniques. Considering the impact of physical layer impairments on network planning and operation has received considerable attention from research community. A novel physical layer impairment aware network planning tool is presented in this paper. Its performance is quantitatively\ud
compared with results obtained by a state-of-the-art tool under a common network scenario. The differences between the two\ud
planning approaches are illustrated and discussed.Postprint (author’s final draft
Telecommunication Economics. Selected results of the COST Action ISO605 Econ@Tel

This book constitutes a collaborative and selected documentation of the scientific outcome of the European COST Action IS0605 Econ@Tel "A Telecommunications Economics COST Network" which run from October 2007 to October 2011. Involving experts from around 20 European countries, the goal of Econ@Tel was to develop a strategic research and training network among key people and organizations in order to enhance Europe's competence in the field of telecommunications economics.\ud
Reflecting the organization of the COST Action IS0605 Econ@Tel in working groups the following four major research areas are addressed:\ud
 \ud
- evolution and regulation of communication ecosystems;\ud
- social and policy implications of communication technologies;\ud
- economics and governance of future networks;\ud
- future networks management architectures and mechanisms
Decision support in contract formation for commercial electronic services with international connection

This section addresses the automated and legally compliant determination of key contract parameters for commercially and internationally provided electronic services in the Internet. It designs and implements a decision support system that provides recommendations on suited contract parameters at the time of contract formation. Recommendations base on automated reasoning taking into consideration the relevant set of service- and contract-specific facts. The range of facts to be considered is imposed by the laws of these states that have sufficient connection with the international service contract to be concluded. Accordingly, this section develops and documents the solid basis for the decision support system, consisting of an information model that integrates perspectives of service and contract management as well as in a detailed method to formally model the legal basis for machine execution
Economic Traffic Management: Mechanisms and Applications

The paradigm shift from centralized services into hundreds of thousands of decentralized services changes traffic directions and patterns in the Internet. In that light, overlay providers form logical communication topologies, which effect the underlying telcos’ as well as Internet Service Providers’ (ISP) traffic and network management. Thus, Economic Traffic Management (ETM) principles deal with incentives, decentralized traffic generation, and modern applications, such as integrated Video-on-Demand and live streaming approaches. Therefore, this work overviews the very recent work on ETM mechanisms, especially driven by the SmoothIT project, and on LiveShift, combining efficiently architectural and system demands for an incentive-driven application management. Furthermore, this section describes in examples, provides evidences, and concludes that ETM and LiveShift can pave an efficient path to modern application support of distributed overlay traffic management, which benefits telcos, ISPs, overlay providers, and end users, if all or parts of them see the right incentives to cooperate, behave well, or interact
Mobile communications of the needy and poor: Affordability indicators, European data, social tariffs

This section summarizes the data and information collected across Europe and beyond, inside the COST 605 Action (2008-2011), and can be relevant for separate analysis, research and regulations about the mobile communications costs of poor and needy groups. Miscellaneous social and macro-economic data on the needy and their mobile communications usage in five European countries are presented. It also contains the specification of a new indicator whereby the affordability of mobile communications for poor and needy can be established, and the corresponding results for 7 countries in 2006 and 2010. The indicator is the "poor's purchasing power parity (PPP) in wireless minutes per month", based on reported data collected on the distribution amongst poor and needy groups in Georgia and France. An Appendix gives some data sources for the countries where data were collected
Handling Stateful Firewall Anomalies

Part 4: Access ControlInternational audienceA security policy consists of a set of rules designed to protect an information system. To ensure this protection, the rules must be deployed on security components in a consistent and non-redundant manner. Unfortunately, an empirical approach is often adopted by network administrators, to the detriment of theoretical validation. While the literature on the analysis of configurations of first generation (stateless) firewalls is now rich, this is not the case for second and third generation firewalls, also known as stateful firewalls. In this paper, we address this limitation, and provide solutions to analyze and handle stateful firewall anomalies and misconfiguration
Using Composition Trees to Validate an Entry Profile of Software Engineering Lifecycle Profiles for Very Small Entities (VSEs)

ISO/IEC TR 29110-5-1 provides a Software Engineering life cycle reference model for Very Small Entities on small software projects (less than 6 people month). This paper uses Composition Trees (CT) as a formal notation to model part of this process, and compares it with its counterpart process (which is also modeled in a CT) from ISO/IEC 12207. The outcome of the comparison is a Comparison Composition Tree (CCT). This CCT shows clearly the similarity and difference between the VSE Entry Profile and ISC12207. This information may help people to validate and understand the VSE Profile. This paper also proposes this approach can be used as a general approach for people to develop, study, and implement software processes.Griffith Sciences, School of Information and Communication TechnologyFull Tex
Modeling space plasma dynamics with anisotropic Kappa distributions

Space plasmas are collisionpoor and kinetic effects prevail leading to wave
fluctuations, which transfer the energy to small scales: wave-particle
interactions replace collisions and enhance dispersive effects heating
particles and producing suprathermal populations observed at any heliospheric
distance in the solar wind. At large distances collisions are not efficient,
and the selfgenerated instabilities constrain the solar wind anisotropy
including the thermal core and the suprathermal components. The generalized
power-laws of Kappa-type are the best fitting model for the observed
distributions of particles, and a convenient mathematical tool for modeling
their dynamics. But the anisotropic Kappa models are not correlated with the
observations leading, in general, to inconsistent effects. This review work
aims to reconcile some of the existing Kappa models with the observations.Comment: Paper accepted for publication in Astronomy and Space Science
  Proceedings - Springer (presented by M. Lazar at the International
  Astrophysics Forum 2011: Frontiers in Space Environment Research, at the
  Congress Centrum Alpbach (Austria) / June 20 - 24, 2011.
The statistical accuracy of surveys on business and economic perspectives: a case study

In this paper, we develop a new decision making model and apply it in political Surveys of economic climate collect opinions of managers about the short-term future evolution of their business. Interviews are carried out on a regular basis and responses measure optimistic, neutral or pessimistic views about the economic perspectives. We propose a method to evaluate the sampling error of the average opinion derived from a particular type of survey data. Our variance estimate is useful to interpret historical trends and to decide whether changes in the index from one period to another are due to a structural change or whether ups and downs can be attributed to sampling randomness. An illustration using real data from a survey of business managers opinions is discussed
Specification-driven test generation for model transformations

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-30476-7_3Proceedings of 5th International Conference, ICMT 2012, Prague, Czech Republic, May 28-29, 2012Testing model transformations poses several challenges, among them the automatic generation of appropriate input test models and the specification of oracle functions. Most approaches to the generation of input models ensure a certain level of source meta-model coverage, whereas the oracle functions are frequently defined using query or graph languages. Both tasks are usually performed independently regardless their common purpose, and sometimes there is a gap between the properties exhibited by the generated input models and those demanded to the transformations (as given by the oracles).
Recently, we proposed a formal specification language for the declarative formulation of transformation properties (invariants, pre- and postconditions) from which we generated partial oracle functions that facilitate testing of the transformations. Here we extend the usage of our specification language for the automated generation of input test models by constraint solving. The testing process becomes more intentional because the generated models ensure a certain coverage of the interesting properties of the transformation. Moreover, we use the same specification to consistently derive both the input test models and the oracle functions.Work funded by the Spanish Ministry of Economy and Competitivity (TIN2011-24139) and by the R&D programme of Madrid Region (S2009/TIC-1650
Multifocal: a strategic bidirectional transformation language for XML schemas

Lenses are one of the most popular approaches to define bidirectional transformations between data models. However, writing a lens transformation typically implies describing the concrete steps that convert values in a source schema to values in a target schema. In contrast, many XML-based languages allow writing structure-shy programs that manipulate only specific parts of XML documents without having to specify the behavior for the remaining structure. In this paper, we propose a structure-shy bidirectional two-level transformation language for XML Schemas, that describes generic type-level transformations over schema representations coupled with value-level bidirectional lenses for document migration. When applying these two-level programs to particular schemas, we employ an existing algebraic rewrite system to optimize the automatically-generated lens transformations, and compile them into Haskell bidirectional executables. We discuss particular examples involving the generic evolution of recursive XML Schemas, and compare their performance gains over non-optimized definitions.Fundação para a Ciência e a Tecnologi
Bidirectional transformation of model-driven spreadsheets

Lecture Notes in Computer Science Volume 7307, 2012Spreadsheets play an important role in software organizations. Indeed, in large software organizations, spreadsheets are not only used to define sheets containing data and formulas, but also to collect information from diferent systems, to adapt data coming from one system to the format required by another, to perform operations to enrich or simplify data, etc. In fact, over time many spreadsheets turn out to be used for storing and processing increasing amounts of data and supporting increasing numbers of users. Unfortunately, spreadsheet systems provide poor support for modularity, abstraction, and transformation, thus, making the maintenance, update and evolution of spreadsheets a very complex and error-prone task.
We present techniques for model-driven spreadsheet engineering where we employ bidirectional transformations to maintain spreadsheet models and instances synchronized. In our setting, the business logic of spreadsheets is defined by ClassSheet models to which the spreadsheet data conforms, and spreadsheet users may evolve both the model and the data instances. Our techniques are implemented as part of the MDSheet framework: an extension for a traditional spreadsheet system
On Challenging Techniques for Constrained Global Optimization

This chapter aims to address the challenging and demanding issue of solving a continuous nonlinear constrained global optimization problem. We propose four stochastic methods that rely on a population of points to diversify the search for a global solution: genetic algorithm, differential evolution, artificial fish swarm algorithm and electromagnetism-like mechanism. The performance of different variants of these algorithms is analyzed using a benchmark set of problems. Three different strategies to handle the equality and inequality constraints of the problem are addressed. An augmented Lagrangian-based technique, the tournament selection based on feasibility and dominance rules, and a strategy based on ranking objective and constraint violation are presented and tested. Numerical experiments are reported showing the effectiveness of our suggestions. Two well-known engineering design problems are successfully solved by the proposed methods. © Springer-Verlag Berlin Heidelberg 2013.Fundação para a
Ciência e a Tecnologia (Foundation for Science and Technology), Portugal for the financial support under fellowship grant: C2007-UMINHO-ALGORITMI-04. The other authors acknowledge FEDER COMPETE, Programa Operacional Fatores de Competitividade (Operational Programme
Thematic Factors of Competitiveness) and FCT for the financial support under project grant:
FCOMP-01-0124-FEDER-022674info:eu-repo/semantics/publishedVersio
Multilocal programming and applications

Preprint versionMultilocal programming aims to identify all local minimizers of unconstrained
or constrained nonlinear optimization problems. The multilocal programming
theory relies on global optimization strategies combined with simple ideas
that are inspired in deflection or stretching techniques to avoid convergence to the
already detected local minimizers. The most used methods to solve this type of problems
are based on stochastic procedures and a population of solutions. In general,
population-based methods are computationally expensive but rather reliable in identifying
all local solutions. In this chapter, a review on recent techniques for multilocal
programming is presented. Some real-world multilocal programming problems
based on chemical engineering process design applications are described.Fundação para a Ciência e a Tecnologia (FCT
Fake Run-Time Selection of Template Arguments in C++

C++ does not support run-time resolution of template type arguments. To
circumvent this restriction, we can instantiate a template for all possible
combinations of type arguments at compile time and then select the proper
instance at run time by evaluation of some provided conditions. However, for
templates with multiple type parameters such a solution may easily result in a
branching code bloat. We present a template metaprogramming algorithm called
for_id that allows the user to select the proper template instance at run time
with theoretical minimum sustained complexity of the branching code.Comment: Objects, Models, Components, Patterns (50th International Conference,
  TOOLS 2012
Information methods for predicting risk and outcome of stroke

Stroke is a major cause of disability and mortality in most economically developed countries. It is the second leading cause of death worldwide (after cancer and heart disease) [55.1, 2] and a major cause of disability in adults in developed countries [55.3]. Personalized modeling is an emerging effective computational approach, which has been applied to various disciplines, such as in personalized drug design, ecology, business, and crime prevention; it has recently become more prominent in biomedical applications. Biomedical data on stroke risk factors and prognostic data are available in a large volume, but the data are complex and often difﬁcult to apply to a speciﬁc person. Individualizing stroke risk prediction and prognosis will allow patients to focus on risk factors speciﬁc to them, thereby reducing their stroke risk and managing stroke outcomes more effectively. This chapter reviews various methods–conventional statistical methods and computational intelligent modeling methods for predicting risk and outcome of stroke
Personalised information modelling technologies for personalised medicine

Personalised modelling offers a new and effective approach for the study in pattern recognition and knowledge discovery, especially for biomedical applications. The created models are more useful and informative for analysing and evaluating an individual data object for a given problem. Such models are also expected to achieve a higher degree of accuracy of prediction of outcome or classification than conventional systems and methodologies. Motivated by the concept of personalised medicine and utilising transductive reasoning, personalised modelling was recently proposed as a new method for knowledge discovery in biomedical applications. Personalised modelling aims to create a unique computational diagnostic or prognostic model for an individual. Here we introduce an integrated method for personalised modelling that applies global optimisation of variables (features) and an appropriate size of neighbourhood to create an accurate personalised model for an individual. This method creates an integrated computational system that combines different information processing techniques, applied at different stages of data analysis, e.g. feature selection, classification, discovering the interaction of genes, outcome prediction, personalised profiling and visualisation, etc. It allows for adaptation, monitoring and improvement of an individual’s model and leads to improved accuracy and unique personalised profiling that could be used for personalised treatment and personalised drug design
Computational modeling with spiking neural networks

This chapter reviews recent developments in the area of spiking neural networks (SNN) and summarizes the main contributions to this research field. We give background information about the functioning of biological neurons, discuss the most important mathematical neural models along with neural encoding techniques, learning algorithms, and applications of spiking neurons. As a specific application, the functioning of the evolving spiking neural network (eSNN) classification method is presented in detail and the principles of numerous eSNN based applications are highlighted and discussed
Ontologies and machine learning systems

In this chapter we review the uses of ontologies within bioinformatics and neuroinformatics and the various attempts to combine machine learning (ML) and ontologies, and the uses of data mining ontologies. This is a diverse field and there is enormous potential for wider use of ontologies in bioinformatics and neuroinformatics research and system development. A systems biology approach comprising of experimental and computational research using biological, medical, and clinical data is needed to understand complex biological processes and help scientists draw meaningful inferences and to answer questions scientists have not even attempted so far
Brain, gene, and quantum inspired computational intelligence

This chapter discusses opportunities and challenges for the creation of methods of computational intelligence (CI) and more specifically – artificial neural networks (ANN), inspired by principles at different levels of information processing in the brain: cognitive, neuronal, genetic, and quantum, and mainly, the issues related to the integration of these principles into more powerful and accurate CI methods. It is demonstrated how some of these methods can be applied to model biological processes and to improve our understanding in the subject area; generic CI methods being applicable to challenging generic AI problems. The chapter first offers a brief presentation of some principles of information processing at different levels of the brain and then presents brain inspired, gene inspired, and quantum inspired CI. The main contribution of the chapter, however, is the introduction of methods inspired by the integration of principles from several levels of information processing, namely:
A computational neurogenetic model that in one model combines gene information related to spiking neuronal activities.
A general framework of a quantum spiking neural network (SNN) model.
A general framework of a quantum computational neurogenetic model (CNGM).
Many open questions and challenges are discussed, along with directions for further research