Les échelles de la cohésion spatiale en europe

Ce papier a été présenté en anglais sous le titre "Territorial Cohesion Scale in Europe: the Case of France"Après avoir rappelé l'importance de la cohésion territoriale et du polycentrisme pour l'Unioneuropéenne, on pointe les principaux enjeux liés à la multiplication des acteurs agissant sur sesterritoires. On montre ensuite que l'irruption de l'ambition de la compétitivité complique la recherchede la cohésion territoriale et place les responsables devant trois grands choix stratégiques possibles (I).Pour évaluer si l'un d'entre eux a été privilégié, on observe la ventilation des fonds structurels dans lesrégions françaises d'Objectif 2 (II). Les résultats montrent une répartition équilibrée entre lesdifférents types de régions et un souci de combiner la quête de la cohésion territoriale et dupolycentrisme avec la poursuite d'une meilleure compétitivité nationale. Ce résultat n'empêche pas lapersistance de débats théoriques assez vifs (III). Nous tentons d'en tirer des conclusions sur leséchelles et les modalités d'intervention optimales en faveur de la cohésion territoriale

PUBLIC EXPENDITURES FOR DEVELOPMENT - THEIR ROLE IN OVERCOMING THE ECONOMIC CRISIS AND ALIGNMENT OF ROMANIA TO EUROPEAN UNION REQUIREMENTS

This paper analyses the role of public capital expenditure in Romania. There were identified two important roles of public expenditures for development in Romania, currently: levers for overcoming the economic crisis, and a means to align Romania to European Union requirements stipulated in the revised Lisbon Strategy. The analysis concluded that these expenses, although with a relative value twice the EU average, experienced a strong downward trend with the economic crisis, so as they have not contributed to economic recovery. Regarding the second role, matching the EU requirements in development, has not been reached. This is demonstrated by the Lisbon index, according to which in 2008 Romania ranked 25th place, while in 2010 situated Romania only on position 26.public expenditure, public debt, economic crisis, capital expenditures

Vulnerability assessment of the karst aquifer feeding the Pertuso Spring (Central Italy): comparison between different applications of COP method

Karst aquifers vulnerability assessment and mapping are important tools for improved sustainable management and protection of karst groundwater resources. In this paper, in order to estimate the vulnerability degree of the karst aquifer feeding the Pertuso Spring in Central Italy, COP method has been applied starting from two different discretization approaches: using a polygonal layer and the Finite Square Elements (FSE). Therefore, the hydrogeological catchment basin has been divided into 72 polygons, related to the outcropping lithology and the karst features. COP method has been applied to a single layer composed by all these polygons. The results of this study highlight vulnerability degrees ranging from low to very high. The maximum vulnerability degree is due to karst features responsible of high recharge and high hydraulic conductivity. Comparing the vulnerability maps obtained by both methodologies it is possible to say that the traditional discretization approach seems to overestimate the vulnerability of the karst aquifer feeding the Pertuso Spring. Between the two different approaches of COP method, the proposed polygonal discretization of the hydrogeological basin seems to be more suitable to small areas, such as the Pertuso Spring hydrogeological basin, than the traditional grid mapping

The Importance of Accounting for Real-World Labelling When Predicting Software Vulnerabilities

Previous work on vulnerability prediction assume that predictive models are trained with respect to perfect labelling information (includes labels from future, as yet undiscovered vulnerabilities). In this paper we present results from a comprehensive empirical study of 1,898 real-world vulnerabilities reported in 74 releases of three security-critical open source systems (Linux Kernel, OpenSSL and Wiresark). Our study investigates the effectiveness of three previously proposed vulnerability prediction approaches, in two settings: with and without the unrealistic labelling assumption. The results reveal that the unrealistic labelling assumption can profoundly mis- lead the scientific conclusions drawn; suggesting highly effective and deployable prediction results vanish when we fully account for realistically available labelling in the experimental methodology. More precisely, MCC mean values of predictive effectiveness drop from 0.77, 0.65 and 0.43 to 0.08, 0.22, 0.10 for Linux Kernel, OpenSSL and Wiresark, respectively. Similar results are also obtained for precision, recall and other assessments of predictive efficacy. The community therefore needs to upgrade experimental and empirical methodology for vulnerability prediction evaluation and development to ensure robust and actionable scientific findings

Effective Removal of Operational Log Messages: an Application to Model Inference

Model inference aims to extract accurate models from the execution logs of software systems. However, in reality, logs may contain some "noise" that could deteriorate the performance of model inference. One form of noise can commonly be found in system logs that contain not only transactional messages---logging the functional behavior of the system---but also operational messages---recording the operational state of the system (e.g., a periodic heartbeat to keep track of the memory usage). In low-quality logs, transactional and operational messages are randomly interleaved, leading to the erroneous inclusion of operational behaviors into a system model, that ideally should only reflect the functional behavior of the system. It is therefore important to remove operational messages in the logs before inferring models. In this paper, we propose LogCleaner, a novel technique for removing operational logs messages. LogCleaner first performs a periodicity analysis to filter out periodic messages, and then it performs a dependency analysis to calculate the degree of dependency for all log messages and to remove operational messages based on their dependencies. The experimental results on two proprietary and 11 publicly available log datasets show that LogCleaner, on average, can accurately remove 98% of the operational messages and preserve 81% of the transactional messages. Furthermore, using logs pre-processed with LogCleaner decreases the execution time of model inference (with a speed-up ranging from 1.5 to 946.7 depending on the characteristics of the system) and significantly improves the accuracy of the inferred models, by increasing their ability to accept correct system behaviors (+43.8 pp on average, with pp=percentage points) and to reject incorrect system behaviors (+15.0 pp on average)