TalTech Data Repository
Not a member yet
221 research outputs found
Sort by
UWB Active-Passive Two-Way Ranging Protocol Data Captured in an Industrial Environment
No full text<p>Dataset containing Ultra-Wideband (UWB) Active-Passive Two-Way-Ranging (AP-TWR) protocol range estimates, using the Qorvo DW1000 chip-based Eliko UWB RTLS system. Data was captured in an industrial environment, at the premises of a thermoplastic pipe manufacturer Krah Pipes OÜ, located near Tallinn, Estonia in December 2022.</p><p>Tests consisted of 1) 30 arbitrarily chosen stationary points on the factory floor 2) A movement track marked on the lines of the factory floor. The true coordinates of the stationary points and the critical points of the movements are measured with the Leica DISTO S910 laser distance meter. The data was used to validate the proposed AP-TWR-based Adaptive Extended Kalman Filter (A-EKF) position estimation method.</p><p><strong>Instructions:</strong> </p><p>The text file <i>anchor_coordinates.txt</i> contains the anchor coordinates (in meters) used in the tests in the form: <ANCHOR HEX ID>, <X-COORDINATE>, <Y-COORDINATE>, <Z-COORDINATE></p><p>The text file <i>stationary_truecoordinates.txt</i> contains the true coordinates (in meters) for each stationary test point in the form of: <FILENAME>, <X-COORDINATE>, <Y-COORDINATE>, <Z-COORDINATE></p><p>The text file <i>movement_truecoordinates.txt</i> contains the true coordinates (in meters) for the critical points of the movement tests in the form of: <CRITICAL POINT NUMBER>, <X-COORDINATE>, <Y-COORDINATE>, <Z-COORDINATE></p><p>Text files <i>movement.txt</i> and<i> stationaryX.txt</i> (X is the number on the stationary point) contain the AP-TWR ranging data (in centimeters) from which the AP-TWR measurement matrices are composed. The files contain 2 kinds of messages RR_L and LR_E, where the former contains the active SS-TWR range estimates and the internal clock counter of the tag (in milliseconds) and the latter consists of the passive range estimates (and the active SS-TWR range estimates of that specific anchor should be repeated after the <SELF> field). The <SEQUENCE NUMBER> (running from 0 to 255 is a cyclical number for the ranging sequence) and <TAG HEX ID> fields tie together the corresponding RR_L and LR_E messages. The movement tests also contain COORD_E messages, but these are not relevant from the standpoint of the tests - they are coordinates calculated by the Eliko UWB RTLS, and should be ignored.</p><p>Considering that the number of active anchors is m, the structure of RR_L messages is the following (irrelevant information, such as tag/anchor informational flags, etc. are not explained and left as <BLANK>):</p><p><PEKIO>, <MESSAGE TYPE: RR_L>, <SEQUENCE NUMBER>, <TAG HEX ID>, m times (<ANCHOR HEX ID>, <DISTANCE VALUE>), <TAG TIME COUNTER IN ms>, m times (<BLANK>), <BLANK></p><p>The same considerations are are taken for the LR_E messages, where the structure is (Note that <PASSIVE ESTIMATE CALCULATION> fields containing the asterisk *, denote that during this slot in the raniging sequence, the anchor was actively ranging):</p><p><PEKIO>, <MESSAGE TYPE: LR_E>, <SEQUENCE NUMBER>, <BLANK>, <PASSIVE ANCHOR HEX ID>, m times (<LISTENED ACTIVE ANCHOR HEX ID>, <PASSIVE RANGE ESTIMATE>, <PASSIVE ESTIMATE CALCULATION>), <SELF FIELD DESIGNATOR>, <ACTIVE SS-TWR RANGE ESTIMATE>, <NRI FIELD DESIGNATOR>, <NUMBER OF INTERCEPTED ACTIVE RANGINGS>, 8 times (<BLANK>)</p><p> </p><p>Based on the RR_L and LR_E messages, the AP-TWR measurement matrices for each ranging sequence is formed, the sampling times for the Extended Kalman Filter are extracted from the data of RR_L messages.</p><p><strong>Funding Agency: </strong></p><p>European Union's Horizon 2020 Research and Innovation programme</p><p><strong>Grant Number: </strong></p><p>951867, 668995, 101058505</p><p>This research has also been supported by the European Regional Development Fund and Estonian Research<br>Council under Grant PUT-PRG424.</p>
Dekonvolutsiooni algoritmide kasulikkus stuudioakustika lokaalseks parandamiseks madalatel sagedustel - Lisa 4
No full text
EARLY-STAGE CALCULATION MODEL FOR PLANNING HEATING AND VENTILATION SOLUTIONS FOR TYPICAL APARTAMENT BUILDINGS
No full textMachine learning models for predicting Estonian phosphorite dissolution in hydrochloric acid
No full text<p>This collection contains ML model trained to predict phosphorite concentration in hydrochloric acid and a Python notebook modelling.ipynb that creates models and gives an example of how to upload and use them.</p><p>Abbreviation: </p><p>Linear regression - lr </p><p>Linear polynomial regression of second order - lpr2 </p><p>Support vector regression - svr </p><p>Support vector regression with polynomial features - svr_pl2 </p><p>Random forest regression - rf </p><p>Random forest regression with polynomial features - rf_pl2 </p><p>CatBoost regression - catr </p><p>CatBoost regression with polynomial features - catr_pl2 </p><p>Neural net - NN </p>
Is the Estonian Alutaguse Section of Eastern Fennoscandia a continuation of the Southern Svecofennian Finnish Terranes, or is it akin to the Swedish Bergslagen region?
No full text<p>This research explores the geochemistry of Paleoproterozoic metasedimentary and metavolcanic units in the Alutaguse region of North Estonia and the South Svecofennian (SS) zones, including Ladoga, Saimaa, Häme Belt, and Uusimaa Belt, to better understand the tectonic evolution of the Svecofennian Orogeny in Eastern Fennoscandia. Metasedimentary units consist of micaceous gneisses (± Grt ± Crd ± Sil), while metavolcanics include amphibolites and pyroxenic gneisses. Historical and new data show that High-SiO₂ (>63 wt%) metasediments have felsic origins similar to the Upper Continental Crust (UCC), whereas Low-SiO₂ (≤63 wt%) metasediments, resembling graywackes and shales, indicate mafic to intermediate origins similar to Post-Archean Australian Shale (PAAS). Various weathering indices, including CIA, PIA, CIW, and ICV for metasediments, and AI, CCPI, WIP, and SI for metavolcanics, were applied to reveal these geochemical trends. The metavolcanics are classified as subalkaline, with geochemical signatures pointing to asthenospheric mantle origins for Alutaguse and subducted oceanic crust origins for SS. Tectonic affinity analyses indicate a predominant oceanic arc setting in both regions. High concentrations of CaO and MnO in Alutaguse and Uusimaa metasediments suggest a genetic link, positioning Alutaguse as a backarc of 1.90-1.89 Ga back-arc to the Uusimaa belt, followed by the accretion of the Uusimaa and Häme belts around 1.87 Ga, marking the closure of the Svecofennian ocean. The Alutaguse zone probably developed as a back-arc to the Tallinn-Uusimaa belt after the accretion of the Bergslagen microcontinent. This interpretation is supported by geophysical anomalies correlated with Zn-Pb-Fe mineralisation, which shows similarities to Bergslagen's VMS provinces and warrants further investigation. </p>
Port Dues calculations
No full text<p>Calculation of port dues of selected Estonian, Latvian, Finnish and Swedish ports. Year 2022. Excel file.</p>
Dataset for Performance Evaluation of UWB Active-Passive Two-Way Ranging Distance Estimation Matrix Weighting Methods
No full text<p>The dataset used for testing the proposed UWB AP-TWR distance estimation matrix weighting methods.</p><p>This project has received funding from the European Union's Horizon Europe research and innovation programme under the Grant Agreement 101058505.</p><p> </p>
Baltic Sea Ice Analysis (2002-2012)
No full text<p>This analysis focuses on sea ice dynamics using satellite-derived daily sea ice fraction data from 2002 to 2012 for the Baltic Sea region (21–30°E, 57–61°N). It processes raw data into multiple outputs, including yearly and multi-year datasets, climatological summaries, and ice extent statistics for specific subregions like the Gulf of Riga and Finland. The analysis provides insights into spatial and temporal ice coverage patterns.</p>
Dataset in support of the paper 'Experimental dataset on aluminium wedge slamming: measurements of acceleration, pressure, strain, and video data'
No full text<p>This dataset presents the measurements from three experimental campaigns conducted on a three-dimensional non-prismatic aluminium wedge, complementing the original research article "Slamming loads and responses on a non-prismatic stiffened aluminium wedge: Part I. Experimental study." The experiments were designed to investigate the effects of slamming loads on structural responses through a series of free-fall drop tests. These tests included both symmetric and asymmetric impacts on an aluminium wedge section, designed with two different bottom plates (stiffened and unstiffened) to examine the influence of flexural rigidity on hydroelastic slamming. Vertical acceleration during the free-fall impact was measured using three accelerometers. Sixteen pressure sensors were employed to capture slamming pressures during impact, and twenty strain gauges recorded structural responses in both longitudinal and transverse directions on the wedge surface. Detailed descriptions of the experimental conditions, including wedge geometry, material properties, and the test plan, are provided. The measurements are presented as time histories of sensor records. Symmetric impact tests were conducted at various drop heights ranging from 25 cm to 200 cm and involved two different wedge masses (denoted as m1 and m2) to assess the effect of structural mass on impact-induced loads and responses. Asymmetric impact tests were carried out at three drop heights with heel angles ranging from 5 to 25 degrees. Video footage from different runs is included in this dataset, providing illustrative samples of the experimental procedures.</p>