3rd ATTRACT TWD Symposium in Detection and Imaging (Tripolis)

Contribution List

84. Welcome Welcome (Professor Konstantinos Masselos, Rector of the University of Peloponnese)

31/05/2017, 14:00

1. Keynote Talk - implications of the advances in detector and imaging technology for generating scientific ‘Big Data’

Prof. Tony Hey (RAL)

31/05/2017, 14:20

85. Introduction - What is ATTRACT?

Sergio Bertolucci (Istituto Nazionale Fisica Nucleare Frascati (IT))

31/05/2017, 15:05

2. Presentation 1 - Node-X: A networked architecture for energy efficient high performance computing and data acquisition

Konstantinos Masselos (University of Peloponnese)

31/05/2017, 15:45

4. Presentation 2 - Modular data acquisition systems centred on commercial networks and compute nodes

Giovanna Lehmann Miotto (CERN)

31/05/2017, 16:00

75. Keynote talk - Bright future for Hybrid Pixel Detectors

Dr Christian Broennimann (Dectris)

31/05/2017, 16:45

14. Summary conclusions of Day 1

Michael Krisch (ESRF)

31/05/2017, 17:25

86. Keynote Talk - Where is the so-called “plenty of room at the bottom”?

Pablo Garcia Tello (CERN)

01/06/2017, 10:00

89. Presentation 3 - Integrated control and data acquisition systems

Enrico Gamberini (CERN)

01/06/2017, 10:40

87. Presentation 4 - Silicon Photonic Data Transmission for Detector Instrumentation

Marc Schneider (Karlsruhe Institute of Technology)

01/06/2017, 11:30

88. Presentation 5 - Intelligent Decision Support System for Environmental Risk Management

Dr Kostas Peppas (University of Peloponnese)

01/06/2017, 11:45

90. Presentation 6 - Crowd-Dx(TM): Using crowd-sourced data analytics to elucidate trends in healthcare, wellness and disease

David Sarphie (Bio Nano Consulting)

01/06/2017, 12:00

91. Presentation 7 - quAffirm-GPS™: Developing a network of smart sensors & data analytic strategies to address a global environmental issue: excessive arsenic in drinking water

David Sarphie (Bio Nano Consulting)

01/06/2017, 12:15

92. AquAffirm-GPS™: Developing a network of smart sensors & data analytic strategies to address a global environmental issue: excessive arsenic in drinking water

Dr David Sarphie (Bio Nano Consulting)

Software, imaging & computing

Problem Description:

With one in ten people worldwide lacking access to clean water, the World Economic Forum in 2015 named the water crisis as the #1 global risk based on impact to society “as a measure of devastation”. A key contributor to this overarching issue is the problem of chronic exposure to arsenic in drinking water, which affects over 140 million people in 70 countries, leading...

83. Crowd-Dx(TM): Using crowd-sourced data analytics to elucidate trends in healthcare, wellness and disease

Dr David Sarphie (Bio Nano Consulting)

Software, imaging & computing

Introduction:
Developments in Connectivity, Big Data and Structured Data Analytics promise significant advances in many important societal areas, including healthcare. Indeed, a number of predictions about future technological advances relate to "Smart Healthcare", wherein the connected world and Internet of Things (IoT) will impact our understanding of disease and offer material benefits to...

79. Integrated control and data acquisition systems

Enrico Gamberini (CERN)

TDAQ, signal processing

Traditionally there has always been a rigid separation between control and Data AcQuisition (DAQ) systems for detectors. This comes from the fact that historically very different technologies were applied to these types of systems and that the main system requirements, i.e. high reliability vs. high speed, were considered incompatible. The situation is different today, and this proposal aims...

81. Intelligent Decision Support System for Environmental Risk Management

Mr Panagiotis Nikolaou (University of Peloponnese), Dr Kostas Peppas (University of Peloponnese)

Software, imaging & computing

IDSERM: Intelligent Decision Support System for Environmental Risk Management

Wildfire activity is strongly affected by four factors: fuels, climate weather, ignition agents and people. Where fuel is available, weather is the most important factor in shaping fire regimes in many areas of the world.

In 2009, ISO published the international standard “Risk Management – Principles and...

78. Modular data acquisition systems centred on commercial networks and compute nodes

Giovanna Lehmann Miotto (CERN)

TDAQ, signal processing

With the increased need for scalable data acquisition systems, we see high potential in modular designs not only for software, but also for the hardware elements. Oftentimes, the on-detector electronics sends and receives data over point-to-point links which are connected to custom processing units. This proposal aims at minimizing the need for custom devices, by introducing an intermediate...

82. Node-X: A networked architecture for energy efficient high performance computing and data acquisition

Mr Evangelos Angelakos (Nanotronix Inc - University of Peloponnese)

Front/Back-End electronics

Introduction
Energy dissipation currently represents the major bottleneck towards exascale computing. High end instruction set processors including many/multi – core processors and graphics processing units (GPUs) adopt an instruction stream based/temporal model of computation which is energy inefficient. Field Programmable Gate Arrays (FPGAs) and Application Specific Integrated Circuits...

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80. Silicon Photonic Data Transmission for Detector Instrumentation

Dr Marc Schneider (KIT - Karlsruhe Institute of Technology (DE))

Front/Back-End electronics

In future detector systems for particle physics and photon science the ever-increasing number of electronic channels results in a keen demand for data read-out capacity. The data transmission from the detector front-end to the counting room relies more and more on optical links. In state-of-the art solutions, individual optical fibers connect directly modulated laser diodes to a corresponding...