SLOTT-AGAPE Data Processing

MEDEA Program (Microlensing Experiment Data-Analysis Software for Event with Amplification) is here presented. It is developed to the pixel lensing analysis used by SLOTT-AGAPE (Systematic Lensing Observation at Toppo Telescope - Andromeda Gravitational Amplification Pixel Experiment) Collaboration. All software components are fully automated and they can be used on-line and off-line.Comment: Short paper to be published in the Proceedings of the MG 9 Meeting. July 2000, Rom

Data processing and online reconstruction

In the upcoming upgrades for Run 3 and 4, the LHC will significantly increase Pb--Pb and pp interaction rates. This goes along with upgrades of all experiments, ALICE, ATLAS, CMS, and LHCb, related to both the detectors and the computing. The online processing farms must employ faster, more efficient reconstruction algorithms to cope with the increased data rates, and data compression factors must increase to fit the data in the affordable capacity for permanent storage. Due to different operating conditions and aims, the experiments follow different approaches, but there are several common trends like more extensive online computing and the adoption of hardware accelerators. This paper gives an overview and compares the data processing approaches and the online computing farms of the LHC experiments today in Run 2 and for the upcoming LHC Run 3 and 4.Comment: 6 pages, 0 figures, contribution to LHCP2018 conferenc

MicroED data collection and processing.

MicroED, a method at the intersection of X-ray crystallography and electron cryo-microscopy, has rapidly progressed by exploiting advances in both fields and has already been successfully employed to determine the atomic structures of several proteins from sub-micron-sized, three-dimensional crystals. A major limiting factor in X-ray crystallography is the requirement for large and well ordered crystals. By permitting electron diffraction patterns to be collected from much smaller crystals, or even single well ordered domains of large crystals composed of several small mosaic blocks, MicroED has the potential to overcome the limiting size requirement and enable structural studies on difficult-to-crystallize samples. This communication details the steps for sample preparation, data collection and reduction necessary to obtain refined, high-resolution, three-dimensional models by MicroED, and presents some of its unique challenges

Towards Big data processing in IoT: network management for online edge data processing

Heavy data load and wide cover range have always been crucial problems for internet of things (IoT). However, in mobile-edge computing (MEC) network, the huge data can be partly processed at the edge. In this paper, a MEC-based big data analysis network is discussed. The raw data generated by distributed network terminals are collected and processed by edge servers. The edge servers split out a large sum of redundant data and transmit extracted information to the center cloud for further analysis. However, for consideration of limited edge computation ability, part of the raw data in huge data sources may be directly transmitted to the cloud. To manage limited resources online, we propose an algorithm based on Lyapunov optimization to jointly optimize the policy of edge processor frequency, transmission power and bandwidth allocation. The algorithm aims at stabilizing data processing delay and saving energy without knowing probability distributions of data sources. The proposed network management algorithm may contribute to big data processing in future IoT

Biomedical bulk data processing program

Analog-to-digital computer accepts physiological flight data as three basic analog input signals - the ECG signal, the flowmeter signal which is a respiration monitor, and the accelerometer signal which measures the normal-g-load on the subject

Statistical load data processing

A recorder system has been installed on two operational fighter aircrafts. Signal values from a c.g.-acceleration transducer and a strain-gage installation at the wing root were sampled and recorded in digital format on the recorder system. To analyse such load-time histories for fatigue evaluation purposes, a number of counting methods are available in which level crossings, peaks, or ranges are counted. Ten different existing counting principles are defined. The load-time histories are analysed to evaluate these counting methods. For some of the described counting methods, the counting results might be affected by arbitrarily chosen parameters such as the magnitude of load ranges that will be neglected and other secondary counting restrictions. Such influences might invalidate the final counting results entirely. The evaluation shows that for the type of load-time histories associated with most counting methods, a sensible value of the parameters involved can be found

Data analysis techniques: Spectral processing

The individual steps in the data processing scheme applied to most radars used for wind sounding are analyzed. This processing method uses spectral analysis and assumes a pulse Doppler radar. Improvement in the signal to noise ratio of some radars is discussed

Quantum data processing and error correction

This paper investigates properties of noisy quantum information channels. We define a new quantity called {\em coherent information} which measures the amount of quantum information conveyed in the noisy channel. This quantity can never be increased by quantum information processing, and it yields a simple necessary and sufficient condition for the existence of perfect quantum error correction.Comment: LaTeX, 20 page