Chronicle of a Pandemic Foretold. CEPS Policy Insights No 2020-05 / March 2020

In just a few weeks, COVID-19 appeared in China and quickly spread to the rest of the world, including Europe and the United States. Many have rushed to describe the outbreak as a ‘black swan’ – an unpredictable event with extremely severe consequences. However, COVID-19 was not only predictable ex post: it was amply predicted ex ante. This allows us to draw some preliminary lessons: • First, economic policy will need to shift from its current focus on efficiency, towards a greater emphasis on resilience and sustainability. • Second, a more centralised governance to address health emergencies is needed. • Third, Europe should create a centre for the prevention of large-scale risks. • Fourth, digital technologies, if handled with care, can be an important part of both a mitigation and a response strategy. • Fifth, Europe should improve its science advice and communication functions. Finally, there are many ways to pursue enhanced resilience and responsiveness, but not all of them are compatible with sustainability and democratic values. The challenge is to find an adequate policy mix, which safeguards individual rights and liberties, protects the economy, and at the same time strengthens government preparedness for cases of epidemics and pandemics

Handwritten digit classification

Pattern recognition is one of the major challenges in statistics framework. Its goal is the feature extraction to classify the patterns into categories. A well-known example in this field is the handwritten digit recognition where digits have to be assigned into one of the 10 classes using some classification method. Our purpose is to present alternative classification methods based on statistical techniques. We show a comparison between a multivariate and a probabilistic approach, concluding that both methods provide similar results in terms of test-error rate. Experiments are performed on the known MNIST and USPS databases in binary-level image. Then, as an additional contribution we introduce a novel method to binarize images, based on statistical concepts associated to the written trace of the digitDigit, Classification, Images

On the lower semicontinuous envelope of functionals defined on polyhedral chains

In this note we prove an explicit formula for the lower semicontinuous envelope of some functionals defined on real polyhedral chains. More precisely, denoting by $H \colon \mathbb{R} \to \left[ 0,\infty \right)$ an even, subadditive, and lower semicontinuous function with $H(0)=0$, and by $\Phi_H$ the functional induced by $H$ on polyhedral $m$-chains, namely \Phi_{H}(P) := \sum_{i=1}^{N} H(\theta_{i}) \mathcal{H}^{m}(\sigma_{i}), \quad\mbox{for every }P=\sum_{i=1}^{N} \theta_{i} [[ \sigma_{i} ]] \in\mathbf{P}_m(\mathbb{R}^n), we prove that the lower semicontinuous envelope of $\Phi_H$ coincides on rectifiable $m$-currents with the $H$-mass \mathbb{M}_{H}(R) := \int_E H(\theta(x)) \, d\mathcal{H}^m(x) \quad \mbox{ for every } R= [[ E,\tau,\theta ]] \in \mathbf{R}_{m}(\mathbb{R}^{n}). Comment: 14 page

The balanced scorecard logic in the management control and reporting of small business company networks: a case study

The purpose of this paper is to assess and integrate the application of the balance scorecard (BSC) logic into business networks identifying functions and use that such performance measuring tool may undertake for SME’s collaborative development. Thus, the paper analyses a successful case study regarding an Italian network of small companies, evaluating how the multidimensional perspective of BSC can support strategic and operational network management as well as communication of financial and extra financial performance to stakeholders. The study consists of a qualitative method, proposing the application of BSC model for business networks from international literature. Several meetings and interviews as well as triangulation with primary and secondary documents have been conducted. The case study allows to recognize how BSC network logic can play a fundamental role on defining network mission, supporting management control as well as measuring and reporting the intangible assets formation along the network development lifecycle. This is the first time application of a BSC integrated framework for business networks composed of SMEs. The case study demonstrates operational value of BSC for SME’s collaborative development and success

Clustering and classifying images with local and global variability

A procedure for clustering and classifying images determined by three classification variables is presented. A measure of global variability based on the singular value decomposition of the image matrices, and two average measures of local variability based on spatial correlation and spatial changes. The performance of the procedure is compared using three different databases.Images, Cluster, Classification

An ultra-fast method for gain and noise prediction of Raman amplifiers

A machine learning method for prediction of Raman gain and noise spectra is presented: it guarantees high-accuracy (RMSE < 0.4 dB) and low computational complexity making it suitable for real-time implementation in future optical networks controllers

Parallel waveform extraction algorithms for the Cherenkov Telescope Array Real-Time Analysis

The Cherenkov Telescope Array (CTA) is the next generation observatory for the study of very high-energy gamma rays from about 20 GeV up to 300 TeV. Thanks to the large effective area and field of view, the CTA observatory will be characterized by an unprecedented sensitivity to transient flaring gamma-ray phenomena compared to both current ground (e.g. MAGIC, VERITAS, H.E.S.S.) and space (e.g. Fermi) gamma-ray telescopes. In order to trigger the astrophysics community for follow-up observations, or being able to quickly respond to external science alerts, a fast analysis pipeline is crucial. This will be accomplished by means of a Real-Time Analysis (RTA) pipeline, a fast and automated science alert trigger system, becoming a key system of the CTA observatory. Among the CTA design key requirements to the RTA system, the most challenging is the generation of alerts within 30 seconds from the last acquired event, while obtaining a flux sensitivity not worse than the one of the final analysis by more than a factor of 3. A dedicated software and hardware architecture for the RTA pipeline must be designed and tested. We present comparison of OpenCL solutions using different kind of devices like CPUs, Graphical Processing Unit (GPU) and Field Programmable Array (FPGA) cards for the Real-Time data reduction of the Cherenkov Telescope Array (CTA) triggered data.Comment: In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.0589