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Working paper distributed at 2nd Annual Next Generation Telecommunications Conference 2009, 13th – 14th October 2009, Brussels 14 pages Abstract Governments all over Europe are in the process of adopting new broadband strategies. The objective is to create modern telecommunications networks based on powerful broadband infrastructures". In doing so, they aim for innovative and investment-friendly concepts. For instance, in a recently published consultation paper on the subject the German regulator BNetzA declared that it will take “greater account of … reducing risks, securing the investment and innovation power, providing planning certainty and transparency – in order to support and advance broadband rollout in Germany”. It further states that when regulating wholesale rates it has to be ensured that “… adequate incentives for network rollout are provided on the one hand, while sustainable and fair competition is ensured on the other”. Also an EC draft recommendation on regulated network access is about to set new standards for the regulation of next generation access networks. According to the recommendation the prices of new assets shall be based on costs plus a projectspecific risk premium to be included in the costs of capital for the investment risk incurred by the operator. This approach has been criticised from various sides. In particular it has been questioned whether such an approach is adequate to meet the objectives of encouraging both competition and investment into next generation access networks. Against this background, the concept of “long term risk sharing contracts” has been proposed recently as an approach which does not only incorporate the various additional risks involved in the deployment of NGA infrastructure, but has several other advantages. This paper will demonstrate that the concept allows for competition to evolve at both the retail and wholesale level on fair, objective, non-discriminatory and transparent terms and conditions. Moreover, it ensures the highest possible investment incentive in line with socially desirable outcome. The paper is organised as follows: The next section will briefly outline the importance of encouraging competition and investment in an NGA-environment. The third section will specify the design of long term risk sharing contracts in view of achieving these objectives. The fourth section will examine potential problems associated with the concept. In doing so a way of how to deal with them will be elaborated. The last section will look at arguments against long term risk sharing contracts. It will be shown that these arguments are not strong enough to build a case against introducing such contracts.
Enterprise SOA Roadmap
(2008)
Purpose
In the determination of the measurement uncertainty, the GUM procedure requires the building of a measurement model that establishes a functional relationship between the measurand and all influencing quantities. Since the effort of modelling as well as quantifying the measurement uncertainties depend on the number of influencing quantities considered, the aim of this study is to determine relevant influencing quantities and to remove irrelevant ones from the dataset.
Design/methodology/approach
In this work, it was investigated whether the effort of modelling for the determination of measurement uncertainty can be reduced by the use of feature selection (FS) methods. For this purpose, 9 different FS methods were tested on 16 artificial test datasets, whose properties (number of data points, number of features, complexity, features with low influence and redundant features) were varied via a design of experiments.
Findings
Based on a success metric, the stability, universality and complexity of the method, two FS methods could be identified that reliably identify relevant and irrelevant influencing quantities for a measurement model.
Originality/value
For the first time, FS methods were applied to datasets with properties of classical measurement processes. The simulation-based results serve as a basis for further research in the field of FS for measurement models. The identified algorithms will be applied to real measurement processes in the future.