6,970 research outputs found

    Exogenous underdevelopment pattern

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    The main dynamics of capitalism is the creation of overproduction in order to search for an internal and foreign market outlet. While increasing the overproduction, both the expansion process and the internationalization of consumption raise. The context just described leads to think about the existence of rich and emerging economies producing an excess of supply compared with their internal demand (net supply) that must be allocated to the poor economies showing an excess of demand compared with their internal supply (net demand). We are, after all, in the compensating structure of the world economy, where the poor countries are setting against the rich and emerging countries; these last two are in competition with each other. Besides, the poor countries absorb the surplus of the rich and emerging ones. The assertion of monetarism, in the last decades, encouraging the market outlets abroad to the detriment of the outlets towards the public sector, leads to stress the tensions between the advantaged and disadvantaged nations. This context makes more doubtful the future economical perspectives. The compensating structure of the world economy facilitates the exogenous nature of the underdevelopment of wide areas of the planet that are addressed to absorb the productive excesses of the advanced economies. The purpose of this current theoretical contribution is just to formalize, through an appropriate economical and mathematical pattern, the interdependence between the strong economical world and the weak economical world.Monetarism; Underdevelopment; Market outlet; Overproduction.

    Cognition-Based Networks: A New Perspective on Network Optimization Using Learning and Distributed Intelligence

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    IEEE Access Volume 3, 2015, Article number 7217798, Pages 1512-1530 Open Access Cognition-based networks: A new perspective on network optimization using learning and distributed intelligence (Article) Zorzi, M.a , Zanella, A.a, Testolin, A.b, De Filippo De Grazia, M.b, Zorzi, M.bc a Department of Information Engineering, University of Padua, Padua, Italy b Department of General Psychology, University of Padua, Padua, Italy c IRCCS San Camillo Foundation, Venice-Lido, Italy View additional affiliations View references (107) Abstract In response to the new challenges in the design and operation of communication networks, and taking inspiration from how living beings deal with complexity and scalability, in this paper we introduce an innovative system concept called COgnition-BAsed NETworkS (COBANETS). The proposed approach develops around the systematic application of advanced machine learning techniques and, in particular, unsupervised deep learning and probabilistic generative models for system-wide learning, modeling, optimization, and data representation. Moreover, in COBANETS, we propose to combine this learning architecture with the emerging network virtualization paradigms, which make it possible to actuate automatic optimization and reconfiguration strategies at the system level, thus fully unleashing the potential of the learning approach. Compared with the past and current research efforts in this area, the technical approach outlined in this paper is deeply interdisciplinary and more comprehensive, calling for the synergic combination of expertise of computer scientists, communications and networking engineers, and cognitive scientists, with the ultimate aim of breaking new ground through a profound rethinking of how the modern understanding of cognition can be used in the management and optimization of telecommunication network

    Uniform Labeled Transition Systems for Nondeterministic, Probabilistic, and Stochastic Process Calculi

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    Labeled transition systems are typically used to represent the behavior of nondeterministic processes, with labeled transitions defining a one-step state to-state reachability relation. This model has been recently made more general by modifying the transition relation in such a way that it associates with any source state and transition label a reachability distribution, i.e., a function mapping each possible target state to a value of some domain that expresses the degree of one-step reachability of that target state. In this extended abstract, we show how the resulting model, called ULTraS from Uniform Labeled Transition System, can be naturally used to give semantics to a fully nondeterministic, a fully probabilistic, and a fully stochastic variant of a CSP-like process language.Comment: In Proceedings PACO 2011, arXiv:1108.145

    The Spectrum of Strong Behavioral Equivalences for Nondeterministic and Probabilistic Processes

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    We present a spectrum of trace-based, testing, and bisimulation equivalences for nondeterministic and probabilistic processes whose activities are all observable. For every equivalence under study, we examine the discriminating power of three variants stemming from three approaches that differ for the way probabilities of events are compared when nondeterministic choices are resolved via deterministic schedulers. We show that the first approach - which compares two resolutions relatively to the probability distributions of all considered events - results in a fragment of the spectrum compatible with the spectrum of behavioral equivalences for fully probabilistic processes. In contrast, the second approach - which compares the probabilities of the events of a resolution with the probabilities of the same events in possibly different resolutions - gives rise to another fragment composed of coarser equivalences that exhibits several analogies with the spectrum of behavioral equivalences for fully nondeterministic processes. Finally, the third approach - which only compares the extremal probabilities of each event stemming from the different resolutions - yields even coarser equivalences that, however, give rise to a hierarchy similar to that stemming from the second approach.Comment: In Proceedings QAPL 2013, arXiv:1306.241

    A uniform framework for modelling nondeterministic, probabilistic, stochastic, or mixed processes and their behavioral equivalences

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    Labeled transition systems are typically used as behavioral models of concurrent processes, and the labeled transitions define the a one-step state-to-state reachability relation. This model can be made generalized by modifying the transition relation to associate a state reachability distribution, rather than a single target state, with any pair of source state and transition label. The state reachability distribution becomes a function mapping each possible target state to a value that expresses the degree of one-step reachability of that state. Values are taken from a preordered set equipped with a minimum that denotes unreachability. By selecting suitable preordered sets, the resulting model, called ULTraS from Uniform Labeled Transition System, can be specialized to capture well-known models of fully nondeterministic processes (LTS), fully probabilistic processes (ADTMC), fully stochastic processes (ACTMC), and of nondeterministic and probabilistic (MDP) or nondeterministic and stochastic (CTMDP) processes. This uniform treatment of different behavioral models extends to behavioral equivalences. These can be defined on ULTraS by relying on appropriate measure functions that expresses the degree of reachability of a set of states when performing single-step or multi-step computations. It is shown that the specializations of bisimulation, trace, and testing equivalences for the different classes of ULTraS coincide with the behavioral equivalences defined in the literature over traditional models

    Revisiting bisimilarity and its modal logic for nondeterministic and probabilistic processes

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    We consider PML, the probabilistic version of Hennessy-Milner logic introduced by Larsen and Skou to characterize bisimilarity over probabilistic processes without internal nondeterminism.We provide two different interpretations for PML by considering nondeterministic and probabilistic processes as models, and we exhibit two new bisimulation-based equivalences that are in full agreement with those interpretations. Our new equivalences include as coarsest congruences the two bisimilarities for nondeterministic and probabilistic processes proposed by Segala and Lynch. The latter equivalences are instead in agreement with two versions of Hennessy-Milner logic extended with an additional probabilistic operator interpreted over state distributions rather than over individual states. Thus, our new interpretations of PML and the corresponding new bisimilarities offer a uniform framework for reasoning on processes that are purely nondeterministic or reactive probabilistic or are mixing nondeterminism and probability in an alternating/non-alternating way

    Quantitative risk assessment on a hydrogen refuelling station

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    The Directive 2014/94/UE (DAFI, Alternative Fuel Initiative Directive) on the deployment of alternative fuels (i.e. hydrogen) infrastructures has been recently transposed into national law in Italy. Consequently, the technical regulation on fire prevention for H2fuelling stations has been updated, in order to consider the current maximum delivery pressure (700 bar) of gaseous hydrogen for road vehicles. This technical regulation establishes the prescriptive safety distance from a piece of equipment. In the case of a new station, an assessment of the frequency of the event and its potential consequences is necessary. This is to understand which risk can reasonably be mitigated by a safety distance or whether additional mitigation or prevention measures should be taken. This paper presents the quantitative risk assessment (QRA) study on a hydrogen station planned to be installed, study which aims at determining the safety distances. Such study utilizes the Sandia-developed QRA tool, Hydrogen Risk Analysis Model (HyRAM), to calculate risk values when developing risk-equivalent plans. HyRAM combines reduced order deterministic models that characterize hydrogen release and flame behavior with probabilistic risk models to quantify risk values. Thanks to HyRAM tool it is possible to estimate physical effects and consequences on people and structures and plants, related to risk scenarios, by means of a damage model library. Use of risk assessment may allow station owners and designers to flexibly define station-specific mitigations, with the purpose of achieving equal or better levels of safety with respect to prescriptive recommendation levels, as suggested by ISO19880-1 (2018)
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