V. I. Antonov, G. F. Malykhina, V. B. Semenyutin
Development of personalized medicine is determined by the synergy of scientists from several fields of medicine, mathematics, computer science and instrumentation. Approaches based on modern methods of measuring, signal processing and machine learning complement the main methods for studying biological processes, make it possible to identify the mechanisms of the disease and personalize the treatment strategy. The article is devoted to the study of models and methods that characterize the processes of cerebral blood flow autoregulation for methodological support of measuring systems in the...
M4Dconf2022
· TC6
· 2022
· 10.21014/tc6-2022.008
· Download
Maryam Alsenaidi, Samia Mohamed, Abdulla AlBlooshi, Munish Narang, Jon Bartholomew
The government of the United Arab Emirates (UAE) is actively introducing digital technology to improve the efficiency and availability of the services it provides to its customers. As government entities the UAE national metrology institute, Emirates Metrology Institute (EMI) and Designated Institute for ionizing radiation, Federal Authority for Nuclear Regulation Secondary Standards Dosimetry Laboratory (FANR SSDL) have developed customer service portals which have now been in use for some years. This paper presents the customer service portals, highlights the portals results in 2019-2021,...
M4Dconf2022
· TC6
· 2022
· 10.21014/tc6-2022.007
· Download
Blair D Hall
A simple model for data obtained by measurement is described. The data model satisfies requirements for evaluation and reporting of measurement uncertainty given in the Guide to the expression of uncertainty in measurement (GUM). The model supports what is called internally consistent and transferable calculations, which are qualities favoured by the GUM. In this way, more rigorous GUM-compliant digital data processing can be supported than the common reporting format of a single value for measurement uncertainty presently allows.
M4Dconf2022
· TC6
· 2022
· 10.21014/tc6-2022.006
· Download
Blair D Hall, Shan Cui, Kazuaki Yamazawa
The Asia Pacific Metrology Programme created a special focus group to address the emerging trends of digitalisation and digital transformation in metrology at the end of 2021. The group will serve as a regional forum for coordination of activities and collaborations. It is tasked with: acquiring the latest information about international trends; identifying common challenges and prioritising tasks; and developing a work programme to address awareness, knowledge transfer and stakeholder liaison. This paper reports on the group’s composition and structure, some initial activities, and some of...
M4Dconf2022
· TC6
· 2022
· 10.21014/tc6-2022.005
· Download
Jonathan Pearce, Radka Veltcheva, Declan Tucker, Graham Machin
Autonomous control systems rely on input from sensors, so it is crucial that the sensor input is validated to ensure that it is ‘right’ and that the measurements are traceable to the International System of Units. The measurement and control of temperature is widespread, and its reliable measurement is key to maximising product quality, optimising efficiency, reducing waste and minimizing emissions such as CO2 and other harmful pollutants. Degradation of temperature sensors in harsh environments such as high temperature, contamination, vibration and ionising radiation causes a progressive...
M4Dconf2022
· TC6
· 2022
· 10.21014/tc6-2022.004
· Download
Tanja Dorst, Maximilian Gruber, Anupam P. Vedurmudi, Daniel Hutzschenreuter, Sascha Eichstädt, Andreas Schütze
In recent years, data science and engineering have faced many challenges concerning the increasing amount of data. In order to ensure findability, accessability, interoperability and reusability (FAIRness) of digital resources, digital objects as a synthesis of data and metadata with persistent and unique identifiers should be used. In this context, the FAIR data principles formulate requirements that research data and, ideally, also industrial data should fulfill to make full use of them, particularly when Machine Learning or other data-driven methods are under consideration. In this...
M4Dconf2022
· TC6
· 2022
· 10.21014/tc6-2022.003
· Download
Frederic Brochu, Michael Chrubasik, Spencer A. Thomas
We present a framework for easy annotating, archiving, retrieving and searching measurement data from a large-scale data archival system. Our tool extends and simplifies the interaction with the database and is implemented in popular scientific applications used for data analysis, namely MATLAB and python. This allows scientists to execute complex interactions with the database for data curation and retrieval tasks in a few simple lines of accessible templated code. Scientists can now ensure their measurement data is well curated and FAIR (findable, accessible, interoperable and reusable)...
M4Dconf2022
· TC6
· 2022
· 10.21014/tc6-2022.002
· Download
Jianqianga Mou, Liuyangb Feng, Xiudongb Qian , Shan Cui
A measurement system using strain gauges for structural health monitoring (SHM) was built up. The measurement uncertainty and sensor fault models were studied under a cyclic loading condition emulating the ocean waves. A methodology for sensor fault diagnosis and classification using the Convolutional Neural Network (CNN) deep learning with the images converted from time domain measurement data as the input was investigated.
M4Dconf2022
· TC6
· 2022
· 10.21014/tc6-2022.001
· Download
Emanuele Alcars, Claudio Parente, Andrea Vallario
Bathymetric data acquired by a single beam echo sounder, as well as those derived by a navigational chart, require interpolation procedure to pass from cloud point dataset to continuous tridimensional representation. Among different algorithms available in GIS software, Kriging interpolators are very powerful tools to process bathymetric data. This paper aims to analyze the accuracy levels that can be reached using Kriging. Bathymetric information included in two Electronic Navigational Charts (ENCs) of the Bay of Pozzuoli (nominal scale 1:30.000) is used for digital 3D model of this area....
Paolo Russo, Fabiana Di Ciaccio, Salvatore Troisi
One of the main issues for underwater robots navigation is their accurate positioning, which heavily depends on the orientation estimation phase. The systems employed to this scope are affected by different noise typologies, mainly related to the sensors and to the irregular noise of the underwater environment. Filtering algorithms can reduce their effect if opportunely configured, but this process usually requires fine techniques and time. In this paper we propose DANAE, a deep Denoising AutoeNcoder for Attitude Estimation which works on Kalman filter IMU/AHRS data integration with the aim...