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An open dataset of electrospinning parameter configurations and resultant nanofiber morphologies
No full text<p><strong>The dataset consists of two tables, Table 1 is an annotated collection of 318 papers on electrospinning, and Table 2 is a</strong><strong>n open dataset of nanofiber input and output parameters based on published 146 technical reports on electrospinning. </strong></p>
<p><strong>About Table 1: </strong></p>
<ul>
<li>A largely unfiltered collection of papers (both reviews and technical reports) </li>
<li>Annotations on materials, solvents, and availability of parameters</li>
<li>The dataset can be used as a paper index for future literature reviews.</li>
</ul>
<p><strong>About Table 2: </strong></p>
<ul>
<li>The dataset is a collection of electrospinning process parameters (e.g. applied voltage, tip distance, polymer composition) and corresponding nanofiber diameter and morphology.</li>
<li>The collection contains records from 146 technical reports on electrospinning.</li>
<li>The dataset can be used as a parameter reference for stable electrospinning configurations, as well as for machine learning modeling. </li>
</ul>
<p><strong>Kindly cite our works if you use the dataset, check out our other works and contact us via <a href="https://droplets.taltech.ee">https://droplets.taltech.ee</a></strong><strong> :)</strong></p>
<p> </p>
<p><strong>Changelog: </strong></p>
<ul>
<li>v2: Added list of papers (Table 1), renamed list of parameter records to Table2, made minor corrections to Table2</li>
<li>v3: Added new data records to both Table 1 and Table 2, expanding the dataset coverage and improving its comprehensiveness.</li>
</ul>
Electronic structure and defect states in bismuth and antimony sulphides identified by energy-resolved electrochemical impedance spectroscopy
No full text<p>One of the reasons chalcogenide-based photovoltaic solar cells (SC) do not yet meet the expected high-power conversion efficiencies is a lack of understanding of their electronic structure, and particularly the nature of the point defects in the absorber materials. We show that the density of states of the characteristic features of the electronic structure, such as band edges and energy distribution of defects, can be obtained experimentally by energy-resolved electrochemical impedance spectroscopy (ER-EIS) in a technically simple and quick way. The ER-EIS data correlate well with theoretical density functional theory calculations. The ER-EIS reveals that Bi<sub>2</sub>S<sub>3,</sub> has only shallow defects near the conduction band minimum (CBM). In Sb<sub>2</sub>S<sub>3</sub>, ER-EIS also shows deep defect states, which can be the cause of the low electrical conductivity of Sb<sub>2</sub>S<sub>3</sub> and lower than theoretically possible power conversion efficiency of Sb<sub>2</sub>S<sub>3</sub>-based SC. A dominant sulphur vacancy defect was identified in Bi- and Sb-chalcogenides. In the (Sb<em><sub>x</sub></em>Bi<sub>(1−<em>x</em>)</sub>)<sub>2</sub>S<sub>3</sub> ternary alloy series, a gradual transformation of CBM and defect states in the band gap was observed. Notably, a 1:9 ratio of Bi:Sb cations already transforms the deep sulphur defects into shallow ones while keeping the band edges similar to those of the pristine Sb<sub>2</sub>S<sub>3</sub>. It can provide a novel strategy for healing the deep defect states in Sb<sub>2</sub>S<sub>3</sub>, a crucial step for boosting solar cell performance.</p>
video_preclassification_models
No full text<p>models for video pre-classification models training script (feature extraction)</p>
Kaugteenuste näidisprojektide protsessi analüüs: Lõppraport
No full text<p>This report was prepared within the framework of the procurement contract concluded between Tallinn University of Technology and the Health Insurance Fund. The purpose of the analysis is to describe and analyse the innovation contest organised by the Health Insurance Fund and the related activities, and to assess the effectiveness of the competition in meeting the objectives of developing remote healthcare services. This report summarises all three phases of the contest. <span> </span></p>
Kaugteenuste näidisprojektide protsessi analüüs: II vaheraport
No full text<p>This report was prepared within the framework of the procurement contract concluded between Tallinn University of Technology and the Health Insurance Fund. The purpose of the analysis is to describe and analyse the innovation contest organised by the Health Insurance Fund and the related activities, and to assess the effectiveness of the competition in meeting the objectives of developing remote healthcare services. This report summarises the second phase of the contest. <span> </span></p>
Heat potential sea surface temperature (SST) reanalysis in the Baltic Sea
Full text link<p>My reanalysis focuses on the Gulf in Finland with coordinates 58°34′00′′N, 60°45′00′′N, 21°56′00′′E, 30°20′00′′E on years 1993-2003. Extracted variables are coordinate variables, time and thetao at a depth of 1.5013654m. Mean yearday time series and average days when (SST > 0) are ploted</p>
Baltic Sea Biogeochemical reanalysis (2007-2022)
Full text link<p>This dataset contains biochemical variables for the Baltic Sea (2007-2022). Raw data was from the Copernicus Marine Environment Monitoring Service (CMEMS) and includes indicators of water quality, biological productivity, and carbon dynamics. Each dataset was downsized and transformed into monthly climatological statistical summaries to aid in further analysis and visualization of marine biogeochemical processes.</p>
Baltic Sea Ice Analysis (1989-2019)
No full text<p>This study examines the dynamics of sea ice by utilizing daily sea ice fraction data obtained from satellites between 1989 and 2019 for the Baltic Sea area (21–30°E, 57–61°N). The raw data is transformed into various outputs, including annual and multi-year datasets, climatological overviews, and statistics on ice extent for specific regions such as the Gulf of Riga and Finland. Through this processing, the analysis offers valuable insights into the patterns of ice coverage both spatially and temporally.</p>
Deliverable 14: Health Professional Digital Competence Profiles for Estonia
No full text<p>This report outlines the outcome of Deliverable 14 of the project "Improving digital competences of the health workforce in Spain and Estonia". </p>
Dataset of Forklift-Deployed Multi-Sensor Setup for Indirect Tracking of Markerless Industrial Products
No full text<p>Dataset of the time-synchronized multisensor data, collected by a total of four sensors, deployed on the full-scale forklift, operating in the industrial environment. The dataset contains the experimentally collected data for the Indirect Tracking project, as well as its selective processing results. The following initial data is provided: Positioning data of the forklift, collected by using <i><strong>Eliko UWB RTLS system</strong></i>; Selective inertial data of the forklift heading (Z-axis angular velocity), collected by the gyroscope of the <i><strong>IMU unit Bosh bno055</strong></i>; Fork elevation data, collected by <i><strong>Miran MPS series draw wire encoder</strong></i>; Distance to the object in front of the forklift data, collected by <i><strong>ultrasonic distance sensor SEN0208</strong></i>.</p><p>The dataset also contains certain results of the initial data processing, used in the context of the Indirect Tracking project. The dataset is provided in the Indirect_Tracking_Dataset.csv file, and contains the following data sections: </p><p><strong>FORKLIFT POSITIONING DATA </strong>includes the initial forklift positioning data, including real-time 2D coordinates of the forklift: <strong>X</strong> [m] and <strong>Y</strong> [m], collected by the UWB RTLS system at the update rate of 5Hz, along with the corresponding time within the experimental campaign <strong>TIME.xy</strong> [s] and delta time of the <strong>dt.xy </strong>[s] between positioning data samples.</p><p><strong>FORKLIFT IMU INPUT </strong>includes the angular velocity of the forklift heading <strong>GYR_Z</strong> [deg/s], collected by the onboard gyroscope at 100Hz update rate, along with the corresponding time within the test campaign <strong>TIME.xy</strong> [s] and delta time of the <strong>dt.xy </strong>[s] between the data samples.</p><p><strong>FORKLIFT HEADING DATA</strong> includes the calculated forklift heading data <strong>ATKF.YAW</strong> [deg], based on the above-mentioned inertial and positioning data, by using the ATKF (Adaptive Tandem Kalman Filter) heading estimation algorithm. This section also includes the estimation of the expected true forklift heading <strong>TRU.YAW</strong> [deg].</p><p><strong>ESTIMATED FORKLIFT FORK COORDINATES & FORK SENSORS' DATA </strong>includes the collected and calculated data, related to the fork (tynes) of the used forklift. The provided 2D coordinates of the fork area <strong>FORK.X</strong> [m] and <strong>FORK.Y</strong> [m] are calculated by using the above-mentioned forklift positioning and (ATKF estimated) heading data. This section also provides the initial measurement data of the fork <strong>elevation sensor </strong>(<strong>FORK.Z</strong> [m]), reflecting the Z coordinate of the fork, and the distance data collected by the ultrasonic <strong>Distance sensor</strong> [m], reflecting the occupancy of the fork area. Fork elevation and distance sensors' data were simultaneously collected by the onboard MCU with the appropriate update rate of 12Hz).</p><p><strong>INTERACTION EVENT </strong>reflects the sequential number and the exact period of the forklift interaction with the payload (pick-up or drop-down event).</p><p>As in the tested indirect tracking method, the location of the payload pick-up or drop-down is formed over time from 2D (X&Y) and elevation (Z) coordinates, the <strong>INDIR.COORD.SAVED</strong> reflects the particular event coordinates part (X&Y, or Z), saved at the exact moment. The exact moment of the event coordinates saving is calculated by using the A-PDD (Automatic Pick-up & Drop-down Detection) algorithm, based on the initial data of the aforementioned fork elevation and distance sensors.</p><p>The collected data reflects the experimental positioning of two industrial payloads. Sections <strong>STATUS & POSITION OF INDIRECTLY TRACKED PAYLOAD 1</strong> and <strong>STATUS & POSITION OF INDIRECTLY TRACKED PAYLOAD 2 </strong>separately provide the momentary status information <strong>PYLD1.STATUS</strong> & <strong>PYLD2.STATUS </strong>of each tracked payload. Each payload has one of four status values: <i>Stored</i> - payload is stored at the known coordinates; <i>Transported</i> - payload is being transported by the forklift and indirectly tracked in real-time; <i>Pick-up</i> - payload pick-up process (event) is ongoing and its coordinates are being defined; Drop-down - payload drop-down process (event) is ongoing and its coordinates are being defined. These sections also provide the corresponding indirectly tracked 3D coordinates of each payload (<strong>INDIR.PYLD1.X</strong> [m], <strong>INDIR.PYLD1.Y</strong> [m], <strong>INDIR.PYLD1.Z</strong> [m]) and (<strong>INDIR.PYLD2.X</strong> [m], <strong>INDIR.PYLD2.Y</strong> [m], <strong>INDIR.PYLD2.Z</strong> [m])</p><p><strong>UWB INITIAL PERFORMANCE in INDIRECT METHOD </strong>section reflects the momentary positioning quality of the used UWB RTLS system in the initial forklift tracking, and therefore, in the indirect payload localization. The section provides the momentary number of UWB anchor units in the line of sight with the forklift onboard UWB tag <strong>INDIR.ANCH_in_LOS </strong>(min. required 3), and the momentary status <strong>INDIR.POS.SUCCESS </strong>of successful coordinates calculation by the UWB system (<i>yes</i> or <i>no</i>)<strong>.</strong></p><p><strong>POSITION OF DIRECTLY TRACKED PAYLOAD 2 </strong>includes the real-time coordinates of payload 2 (<strong>DIR.PYLD2.X</strong> [m], <strong>DIR.PYLD2.Y </strong>[m], <strong>DIR.PYLD2.Z</strong> [m]), independently tracked by the directly attached UWB tag. </p><p><strong>UWB INITIAL PERFORMANCE in DIRECT METHOD </strong>section reflects the positioning quality of the used UWB RTLS system regarding the UWB tag, directly attached to the payload 2. The momentary number of UWB anchor units in the line of sight with the payload attached UWB tag <strong>DIR.ANCH_in_LOS </strong>(min. required 4 for 3D positioning) is provided in this section along with the momentary status <strong>DIR.POS.SUCCESS </strong>of successful coordinates calculation (<i>yes</i> or <i>no</i>).</p><p>Section <strong>TRUE COORDINATES OF INTERACTED PAYLOADS</strong> provides the manually measured true coordinates (<strong>PYLD.TRU.X</strong> [m], <strong>PYLD.TRU.Y</strong> [m], <strong>PYLD.TRU.Z</strong> [m]) of the interacted payload at the moment of the corresponding event.</p>