Delocalisation patterns in University-Industry interaction: Evidence from the 6th R&D Framework Programme

Increasing university-industry interaction (UII) and university contribution to the local economy are compatibleconventional wisdom would say. However, similar to other university activities, interaction with industry may be limited due to a lack of absorptive capacity in local firms. The data of those participating in the European Union's (EU's) Sixth R&D Framework Programme (FP6) were used to obtain values for the number and, notably, the budgets of UII projects at the regional level for the EU27. Two types of interactions were considered: inside and outside the region. Our analysis indicates that universities from regions whose firms have low absorptive capacity participate more often in FP6 projects with firms outside the region. Our results highlight the value of policies that facilitate firm R&D to enhance collaboration with regional universities.Azagra Caro, JM.; Pontikakis, D.; Varga, A. (2013). Delocalisation patterns in University-Industry interaction: Evidence from the 6th R&D Framework Programme. European Planning Studies. 21(10):1676-1701. doi:10.1080/09654313.2012.722949S16761701211

Enabling the Discovery of Recurring Anomalies in Aerospace System Problem Reports using High-Dimensional Clustering Techniques

This paper describes the results of a significant research and development effort conducted at NASA Ames Research Center to develop new text mining techniques to discover anomalies in free-text reports regarding system health and safety of two aerospace systems. We discuss two problems of significant importance in the aviation industry. The first problem is that of automatic anomaly discovery about an aerospace system through the analysis of tens of thousands of free-text problem reports that are written about the system. The second problem that we address is that of automatic discovery of recurring anomalies, i.e., anomalies that may be described m different ways by different authors, at varying times and under varying conditions, but that are truly about the same part of the system. The intent of recurring anomaly identification is to determine project or system weakness or high-risk issues. The discovery of recurring anomalies is a key goal in building safe, reliable, and cost-effective aerospace systems. We address the anomaly discovery problem on thousands of free-text reports using two strategies: (1) as an unsupervised learning problem where an algorithm takes free-text reports as input and automatically groups them into different bins, where each bin corresponds to a different unknown anomaly category; and (2) as a supervised learning problem where the algorithm classifies the free-text reports into one of a number of known anomaly categories. We then discuss the application of these methods to the problem of discovering recurring anomalies. In fact the special nature of recurring anomalies (very small cluster sizes) requires incorporating new methods and measures to enhance the original approach for anomaly detection. ?& pant 0

Academic research groups: evaluation of their quality and quality of their evaluation

In recent years, evaluation of the quality of academic research has become an increasingly important and influential business. It determines, often to a large extent, the amount of research funding flowing into universities and similar institutes from governmental agencies and it impacts upon academic careers. Policy makers are becoming increasingly reliant upon, and influenced by, the outcomes of such evaluations. In response, university managers are increasingly attracted to simple indicators as guides to the dynamics of the positions of their various institutions in league tables. However, these league tables are frequently drawn up by inexpert bodies such as newspapers and magazines, using rather arbitrary measures and criteria. Terms such as "critical mass' and "metrics" are often bandied about without proper understanding of what they actually mean. Rather than accepting the rise and fall of universities, departments and individuals on a turbulent sea of arbitrary measures, we suggest it is incumbent upon the scientific community itself to clarify their nature. Here we report on recent attempts to do that by properly defining critical mass and showing how group size influences research quality. We also examine currently predominant metrics and show that these fail as reliable indicators of group research quality.Comment: Presented at the International Conference on Computer Simulation in Physics and Beyond in Moscow, 2015. The Proceedings will appear in Journal of Physics: Conference Series (JPCS

History matters in Greece: The adoption of Internet-enabled computers by small and medium sized enterprises

In recent years the idea that historical trajectories condition the pace of technical change has been gaining ground but has so far received little empirical backing. Using an original survey, we analyse the adoption of Internet-enabled personal computers (IEPCs) by small- and medium-sized enterprises (SMEs) in Greece. Results indicate that, among other factors, previous experiences with earlier forms of the technology explain current trends. Having shown the dramatic effect of past adoption events in future decisions, the authors call for a policy that specifically targets and caters for historical non-adopters. (c) 2006 Elsevier B.V. All rights reserved

POINT Review of Industrial Transition of Greece: Renewables, batteries and their applications in mobility, agriculture, shipping and defence

Countries and regions around the world are gearing up to make the industrial transitions that will be necessary to move towards sustainable production and consumption patterns. This report documents the findings of a review of industrial transition of Greece launched in 2019 in partnership with the Greek Ministry of Development and Investments, which follows the POINT (Projecting Opportunities for INdustrial Transitions) methodology of the JRC. The review explores some of the policy pathways that Greece might take as it moves from a dependence on fossil fuels to an economy that makes greater use of renewable sources of energy and exploits many of the opportunities that are arising in the production and use of batteries in the realms of transport and mobility, agriculture, shipping and defence

POINT Review of Industrial Transition of Greece: Renewables, batteries and their applications in mobility, agriculture, shipping and defence

Countries and regions around the world are gearing up to make the industrial transitions that will be necessary to move towards sustainable production and consumption patterns. This report documents the findings of a review of industrial transition of Greece launched in 2019 in partnership with the Greek Ministry of Development and Investments, which follows the POINT (Projecting Opportunities for INdustrial Transitions) methodology of the JRC. The review explores some of the policy pathways that Greece might take as it moves from a dependence on fossil fuels to an economy that makes greater use of renewable sources of energy and exploits many of the opportunities that are arising in the production and use of batteries in the realms of transport and mobility, agriculture, shipping and defence

Efficient algorithms for distortion and blocking techniques in association rule hiding

Data mining provides the opportunity to extract useful information from large databases. Various techniques have been proposed in this context in order to extract this information in the most efficient way. However, efficiency is not our only concern in this study. The security and privacy issues over the extracted knowledge must be seriously considered as well. By taking this into consideration, we study the procedure of hiding sensitive association rules in binary data sets by blocking some data values and we present an algorithm for solving this problem. We also provide a fuzzification of the support and the confidence of an association rule in order to accommodate for the existence of blocked/unknown values. In addition, we quantitatively compare the proposed algorithm with other already published algorithms by running experiments on binary data sets, and we also qualitatively compare the efficiency of the proposed algorithm in hiding association rules. We utilize the notion of border rules, by putting weights in each rule, and we use effective data structures for the representation of the rules so as (a) to minimize the side effects created by the hiding process and (b) to speed up the selection of the victim transactions. Finally, we study the overall security of the modified database, using the C4.5 decision tree algorithm of the WEKA data mining tool, and we discuss the advantages and the limitations of blocking