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Extracting useful information from astronomical observations represents one of the most challenging tasks of data exploration. This is largely due to the volume of the data acquired using advanced observational tools. While other challenges typical for the class of big data problems (like data variety) are also present, the size of datasets represents the most significant obstacle in visualization and subsequent analysis. This paper studies an efficient data condensation algorithm aimed at providing its compact representation. It is based on fast nearest neighbor calculation using tree structures and parallel processing. In addition to that, the possibility of using approximate identification of neighbors, to even further improve the algorithm time performance, is also evaluated. The properties of the proposed approach, both in terms of performance and condensation quality, are experimentally assessed on astronomical datasets related to the GAIA mission. It is concluded that the introduced technique might serve as a scalable method of alleviating the problem of the dataset size.

In the era of miniaturization of electronic equipment and the need to connect sensors with textile materials, including clothing, the processing of signals received from the implemented sensors becomes an important issue. Information obtained by measuring the electrical properties of the sensors must be sent, processed, and visualized. For this purpose, the authors of this article have developed a prototype of a data collector obtained from textronic sensors created on composite textile substrates. The device operates in a system consisting of an electronic module based on the nRF52 platform, which supports wireless communication with sensors using Bluetooth technology and transmits the obtained data to a database hosted on the Microsoft Azure platform. A mobile application based on React Native technology was created to control the data stream. The application enables automatic connection to the selected collector, data download and their presentation in the form of selected charts. Initial verification tests of the system showed the correctness and reliability of its operation, and the presented graphs created from the obtained data indicate the usefulness of the device in applications where measurements and recording of impedance, resistance, and temperature are necessary. The presented prototype of a data collector can be used for resistance, impedance, and temperature measurements in the case of textronic structures but also in other wearable electronic systems. [ABSTRACT FROM AUTHOR]

One of the key issues in wearable electronics is data transmission over wireless networks. Among the most commonly used solutions are Bluetooth Low Energy (BLE), as well as the ZigBee protocol, which are characterized by low power consumption and low implementation cost. The functionality of such solutions also depends on the energy consumption of the proposed solutions, as well as their size and weight. The purpose of this paper is to analyze selected communication techniques, which were compared in terms of their range and energy efficiency. The paper presents results on wireless communication tests. A comparison is presented of Bluetooth communication range carried out under different conditions, such as in a building where there were no obstacles and in a public facility. In order to compare Bluetooth communication parameters, different phone models were used. [ABSTRACT FROM AUTHOR]

ATLAS is embarking on a project to multithread its reconstruction software in time for use in Run 3 of the LHC. One component that must be migrated is the histogramming infrastructure used for data quality monitoring of the reconstructed data. This poses unique challenges due to its large memory footprint which forms a bottleneck for parallelization and the need to accommodate relatively inexperienced developers. We discuss plans for the upgraded framework.

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