Knowledge Flows through Informal Contacts in Industrial Clusters Myths or Realities?

The role of informal networks in the development of regional clusters has received a lot of attention in the literature recently. Informal contact between employees in different firms is argued to be one of the main carriers of knowledge between firms in a cluster. This paper empirically examines the role of informal contacts in a specific cluster. In a recent questionnaire, we ask a sample of engineers in a regional cluster of wireless communication firms in Northern Denmark, a series of questions on informal networks. We analyze whether the engineers actually acquire valuable knowledge through these networks. We find that the engineers do share even valuable knowledge with informal contacts. This shows that informal contacts are important channels of knowledge diffusion.Informal contacts, regional clusters, communication technology

Scalable Model-Based Management of Correlated Dimensional Time Series in ModelarDB+

To monitor critical infrastructure, high quality sensors sampled at a high frequency are increasingly used. However, as they produce huge amounts of data, only simple aggregates are stored. This removes outliers and fluctuations that could indicate problems. As a remedy, we present a model-based approach for managing time series with dimensions that exploits correlation in and among time series. Specifically, we propose compressing groups of correlated time series using an extensible set of model types within a user-defined error bound (possibly zero). We name this new category of model-based compression methods for time series Multi-Model Group Compression (MMGC). We present the first MMGC method GOLEMM and extend model types to compress time series groups. We propose primitives for users to effectively define groups for differently sized data sets, and based on these, an automated grouping method using only the time series dimensions. We propose algorithms for executing simple and multi-dimensional aggregate queries on models. Last, we implement our methods in the Time Series Management System (TSMS) ModelarDB (ModelarDB+). Our evaluation shows that compared to widely used formats, ModelarDB+ provides up to 13.7 times faster ingestion due to high compression, 113 times better compression due to the adaptivity of GOLEMM, 630 times faster aggregates by using models, and close to linear scalability. It is also extensible and supports online query processing.Comment: 12 Pages, 28 Figures, and 1 Tabl

Reflecting Back on the Ebola Outbreak and the Future of Bioterrorism

In the wake of the 2014 Ebola outbreak, policy makers have focused on the public health components which led to the outbreak, the efforts to control it, and mitigate the impact of the outbreak. Some of the most enlightening aspects of the outbreak, pertain to National Security. The crisis demonstrated some crucial challenges the United States would have to plan for to effectively respond to a bioterrorist attack