899 resultados para Traffic courts.
Resumo:
This study provides a comparative analysis of the national legal regimes and practices governing the use of intelligence information as evidence in the United Kingdom, France, Germany, Spain, Italy, the Netherlands and Sweden. It explores notably how national security can be invoked to determine the classification of information and evidence as 'state secrets' in court proceedings and whether such laws and practices are fundamental rights- and rule of law-compliant. The study finds that, in the majority of Member States under investigation, the judiciary is significantly hindered in effectively adjudicating justice and guaranteeing the rights of the defence in ‘national security’ cases. The research also illustrates that the very term ‘national security’ is nebulously defined across the Member States analysed, with no national definition meeting legal certainty and “in accordance with the law” standards and a clear risk that the executive and secret services may act arbitrarily. The study argues that national and transnational intelligence community practices and cooperation need to be subject to more independent and effective judicial accountability and be brought into line with EU 'rule of law' standards.
Resumo:
The German Constitutional Court (BVG) recently referred different questions to the European Court of Justice for a preliminary ruling. They concern the legality of the European Central Bank’s Outright Monetary Transaction mechanism created in 2012. Simultaneously, the German Court has threatened to disrupt the implementation of OTM in Germany if its very restrictive analysis is not validated by the European Court of Justice. This raises fundamental questions about the future efficiency of the ECB’s monetary policy, the damage to the independence of the ECB, the balance of power between judges and political organs in charge of economic policy, in Germany and in Europe, and finally the relationship between the BVG and other national or European courts.
Resumo:
The 2011 proposal of the European Court of Justice aiming to increase the number of judges of the General Court has mutated after four years into a complete change of the EU judicial system. This long legislative debate was the first implementation of the Lisbon Treaty in the judicial domain. It has revealed different problems – formal and substantial – of the approach of public service reform in the European institutions.
Resumo:
Internet traffic classification is a relevant and mature research field, anyway of growing importance and with still open technical challenges, also due to the pervasive presence of Internet-connected devices into everyday life. We claim the need for innovative traffic classification solutions capable of being lightweight, of adopting a domain-based approach, of not only concentrating on application-level protocol categorization but also classifying Internet traffic by subject. To this purpose, this paper originally proposes a classification solution that leverages domain name information extracted from IPFIX summaries, DNS logs, and DHCP leases, with the possibility to be applied to any kind of traffic. Our proposed solution is based on an extension of Word2vec unsupervised learning techniques running on a specialized Apache Spark cluster. In particular, learning techniques are leveraged to generate word-embeddings from a mixed dataset composed by domain names and natural language corpuses in a lightweight way and with general applicability. The paper also reports lessons learnt from our implementation and deployment experience that demonstrates that our solution can process 5500 IPFIX summaries per second on an Apache Spark cluster with 1 slave instance in Amazon EC2 at a cost of $ 3860 year. Reported experimental results about Precision, Recall, F-Measure, Accuracy, and Cohen's Kappa show the feasibility and effectiveness of the proposal. The experiments prove that words contained in domain names do have a relation with the kind of traffic directed towards them, therefore using specifically trained word embeddings we are able to classify them in customizable categories. We also show that training word embeddings on larger natural language corpuses leads improvements in terms of precision up to 180%.
Resumo:
Modeling of self-similar traffic is performed for the queuing system of G/M/1/K type using Weibull distribution. To study the self-similar traffic the simulation model is developed by using SIMULINK software package in MATLAB environment. Approximation of self-similar traffic on the basis of spline functions. Modeling self-similar traffic is carried outfor QS of W/M/1/K type using the Weibull distribution. Initial data are: the value of Hurst parameter H=0,65, the shape parameter of the distribution curve α≈0,7 and distribution parameter β≈0,0099. Considering that the self-similar traffic is characterized by the presence of "splashes" and long-termdependence between the moments of requests arrival in this study under given initial data it is reasonable to use linear interpolation splines.
Resumo:
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