<strong>Problem description</strong> A DistoX calibration device has been developed, ... more <strong>Problem description</strong> A DistoX calibration device has been developed, encouraging me to test DistoX calibration with and without it. A report on findings is published in Glas podzemlja 2020 (in Slovene, also available here). An English-language report may be published in the Journal of Cave and Karst Studies. <strong>File description</strong> The data is organised in this way: The folder "Raw" contains files exported from TopoDroid; The folder "Converted" contains manually converted data from the folder "Raw" in a file format more suitable for further processing. The column "Name" that names the instrument and the target locations is added manually. In the cases where TopoDroid joined similar measurements into a survey shot due to unsuitable settings and did not export them, they are read from the phone screen and entered manually. The folder "Organised" contains all the data that gets automatically processed by the program DistoX.R. It is the data from the folder "Converted" with possible manual corrections (measurement order in case of mistakes, measurement length in case of the beam bouncing from an obstacle before the target, etc.), the file data_list.txt containing the list of the files to be processed with short descriptions (emphasising the manual corrections), and the file manual.txt containing Suunto measurements for comparison. The folder "Rest" contains notes that are neither automatically processed nor exported from TopoDroid but may be of interest. DistoX.R is the data processing program. Program DistoX.py draws a graph. The file is available at 10.5281/zenodo.3887485.
Similarity between occupations is a crucial piece of information when making career decisions. Ho... more Similarity between occupations is a crucial piece of information when making career decisions. However, the notion of a single and unified occupation similarity measure is more of a limitation than an asset. The goal of the study is to assess multiple explainable occupation similarity measures that can provide different insights into inter-occupation relations. Several such measures are derived using the framework of bipartite graphs. Their viability is assessed on more than 450,000 job transitions occurring in Slovenia in the period between 2012 and 2021. The results support the hypothesis that several similarity measures are plausible and that they present different feasible career paths. The complete implementation and part of the datasets are available at https://repo.ijs.si/pboskoski/bipartite_job_similarity_code.
s................................................................................................... more s........................................................................................................49 CD with short papers 17 International Karstological School “Classical Karst”, Postojna, Slovenia, 2009 4 Financed by the European Union Marie Curie Conferences and Training Courses (http://cordis.europa.eu/mariecurie-actions/scf) Project SMART-KARST (MSCF-2005-029674) Within the frame of the 6 FP Action Marie Curie Conferences & Training Courses the Karst Research Institute SRC SASA is leading the project SMART-KARST: International Karstological school “Sustainable management of natural resources on karst”. The project supports five events organized in the period of 2006 to 2009. Four of them are our regular International Karstological Schools “Classical Karst” held each year in June, and the fifth one is the Symposium on Time in Karst organized in March 2007. An important objective of the project is to bring together researchers of karst from different disciplines, and especi...
... Author: Matija Perne ... A good model should explain the basic features of rillenkarren: the ... more ... Author: Matija Perne ... A good model should explain the basic features of rillenkarren: the peri-odicity of the structure, the cross profile of a rill, the formation at a crest and extinguishing downstream [8]. Rillenkarren formation appears to be complex and it seems that several ...
Abstract In case of a major accident involving airborne emissions of harmful gases, a temporary p... more Abstract In case of a major accident involving airborne emissions of harmful gases, a temporary portable meteorological station may be used to improve atmospheric dispersion modelling (ADM) for protection of people and the environment. While the meteorological station provides signal values in real time, ADM results for the future are of particular interest for planning purposes. It is possible to use the current measured value as a future input to the ADM but it is suboptimal. It is also possible to use model output statistics (MOS) to predict the future local weather information from numerical weather prediction (NWP) models, while available operational NWP models are in general too coarse to be used directly in fine-resolution ADM. MOS models are obtained through machine learning and the training data sets in most traditional uses of MOS are big, which is beneficial for modelling. We envision using MOS in an emergency and for a location of a temporary meteorological station. We use windowing for online data selection to explore its accuracy when the amount of available training data is very limited, which is expected in an emergency situation. We show that MOS for wind vector with 1 day of training data greatly improves on the numerical weather predictions and the persistence model, so its use in such an emergency would be advantageous.
A long-term measured wind speed time series from the location is typically used when deciding on ... more A long-term measured wind speed time series from the location is typically used when deciding on placing a small wind turbine at a particular location. These data take a long time to collect. The presented novel method of measuring for a shorter time, using the measurement data for training an experimental model, and predicting the wind in a longer time period enables one to avoid most of the wait for the data collection. As the model inputs, the available long-term signals that consist of measurements from the meteorological stations in the vicinity and numerical weather predictions are used. Various possible experimental modelling methods that are based on linear or nonlinear regression models are tested in the field sites. The study area is continental with complex terrain, hilly topography, diverse land use, and no prevailing wind. It is shown that the method gives good results, showing linear regression is most advantageous, and that it is easy enough to use to be practically a...
We observe the effects of training data sample selection in modelling of a physical system with G... more We observe the effects of training data sample selection in modelling of a physical system with Gaussian process nonlinear autoregressive models with exogenous input. Gaussian process modelling limits the number of training data points and we use a big nonlinear benchmark data set. The combination calls for training data sample selection. We compare a &#39;smart&#39; method based on Euclidean distance between training data points with decimation. We use the training data samples obtained by both methods to train the models, test model predictions on a test data set, and calculate two figures of merit, e RMSt and mean standardised log loss (MSLL). The model trained on the &#39;smartly&#39; selected training data points is better in e RMSt while the one with the decimated data is superior in MSLL. The direct conclusion is that the purpose of the model determines which training data sample selection method is better, as the relevant figure of merit depends on the model purpose. We notice that the predicted variance is more sensitive to the training data sample than the predicted mean. We warn that training data sample selection may have unexpected consequences.
CAAI Transactions on Intelligence Technology, 2019
This study describes an application of hybrid modelling for an atmospheric variable in the Krsko ... more This study describes an application of hybrid modelling for an atmospheric variable in the Krsko basin. The hybrid model is a combination of a physics-based and data-driven model and has some properties of both modelling approaches. In the authors’ case, it is used for the modelling of an atmospheric variable, namely relative humidity in a particular location for the purpose of using the predictions of the model as an input to the air-pollution-dispersion model for radiation exposure. The presented hybrid model is a combination of a physics-based atmospherical model and a Gaussian-process (GP) regression model. The GP model is a probabilistic kernel method that also enables evaluation of prediction confidence. The problem of poor scalability of GP modelling was solved using sparse GP modelling; in particular, the fully independent training conditional method was used. Two different approaches to dataset selection for empirical model training were used and multiple-step-ahead predictions for different horizons were assessed. It is shown in this study that the accuracy of the predicted relative humidity in the Krsko basin improved when using hybrid models over using the physics-based model alone and that predictions for a considerable length of horizon can be used.
<strong>Opis problema</strong> Pojavila se je naprava za umerjanje DistoX, ki me je s... more <strong>Opis problema</strong> Pojavila se je naprava za umerjanje DistoX, ki me je spodbudila k temu, da sem preizkusil umerjanje DistoX z njo in brez nje. Poročilo o ugotovitvah je objavljeno v članku v Glasu podzemlja 2020 (na voljo tudi tu). <strong>Opis datotek</strong> Podatki so razvrščeni takole: Podmapa "Izvorni" vsebuje datoteke, ki jih je neposredno izvozil TopoDroid; Podmapa "Pretvorjeni" vsebuje ročno pretvorjene podatke iz mape "Izvorni" v nadaljnji obdelavi prijaznejšo obliko datoteke. Ročno sem jim dodal stolpec "Ime", ki pove, s katerega na katero oglišče trikotnika je merjeno. Kjer je TopoDroid zaradi neustreznih nastavitev podobne meritve samodejno združeval v vizure in meritev ni izvozil, sem te meritve ročno pretipkal z zaslona telefona. Podmapa "Urejeni" vsebuje vse podatke, ki vstopajo v samodejno obdelavo s programom DistoX.R. To so podatki iz mape "Pretvorjeni" z morebitnimi ročnimi popravki (vrstnega reda vizur ob pomotah, dolžine vizur če se je žarek kje prekmalu ustavil, ...) in datoteka seznam_podatkov.txt, ki vsebuje seznam datotek, ki jih obdela program, s kratkimi opisi (predvsem opisi ročnih popravkov). Podmapa "Ostali" vsebuje zapiske, ki niti ne vstopajo v program niti niso izvoženi iz TopoDroid-a, a bi bili lahko zanimivi. DistoX.R je program za obdelavo podatkov. Program DistoX.py služi samo risanju grafa. K preizkušanju so bistveno pripomogli Marjan Baričič, Matic Di Batista, Gregor Pintar, Peter Prevec, Janez Strojan starejši in Rafko Urankar-Cile.
UDC 53.089.6:551.44 Matija Perne: DistoX calibration tools and the need for calibration checking ... more UDC 53.089.6:551.44 Matija Perne: DistoX calibration tools and the need for calibration checking For proper cave surveying using DistoX, the device needs to be calibrated with adequate accuracy. Calibrating does not require any tools; but, tools to make calibration easier have been developed. Theoretical consideration shows that the use of certain tools enables one to introduce a type of calibration error that goes undetected by the calibration software. In this study, the existence of such errors is experimentally confirmed and their magnitude is estimated. It is demonstrated to be crucial that the DistoX is calibrated and that the calibration is valid, that is, that the device has not changed since it was last calibrated. No part of the DistoX must have moved or changed its magnetization since calibration, not even the battery. The calibration method used and the quality of the resulting calibration are important too. It is highly recommended that the DistoX be checked immediately...
Quadratic programs resulting from a model predictive control problem in real-time control context... more Quadratic programs resulting from a model predictive control problem in real-time control context are solved using a dual gradient method. The projection operator of the method is modified so as to implement soft state constraints with linear and quadratic cost on constraint violation without directly calculating values of slack variables. Evolution of iterates and residuals throughout iterations of the modified method is studied. We notice that in most iterations, the set of the constraints that are active and the ones that are violated does not change. Observing the residuals through multiple iterations in which the active and violated sets do not change leads to interesting results. When the dual residual is transformed into a certain base, its components are decaying independently of each other and at exactly predictable rates. The transformation only depends on the system matrices and on the active and violated sets. Since the matrices are independent of the system state, so is...
A faster implementation of the Quadratic Programming (QP) solver used in the Model Predictive Con... more A faster implementation of the Quadratic Programming (QP) solver used in the Model Predictive Control scheme for Iter Plasma current and shape control was developed for Xilinx Field-Programmable Gate Array (FPGA) platforms using a high-level synthesis approach. The QP solver is based on the dual Fast Gradient Method (dFGM). The dFGM is essentially an iterative algorithm, where matrix-vector arithmetic operations within the main iteration loop may be parallelized. This type of parallelism is not well-suited to standard multi-core processors because the number of operations to be spread among processing threads is relatively small considering the time-scale of thread scheduling. The FPGA implementation avoids this issue, but it requires specific techniques of code optimization in order to achieve faster solver execution.
<strong>Problem description</strong> A DistoX calibration device has been developed, ... more <strong>Problem description</strong> A DistoX calibration device has been developed, encouraging me to test DistoX calibration with and without it. A report on findings is published in Glas podzemlja 2020 (in Slovene, also available here). An English-language report may be published in the Journal of Cave and Karst Studies. <strong>File description</strong> The data is organised in this way: The folder "Raw" contains files exported from TopoDroid; The folder "Converted" contains manually converted data from the folder "Raw" in a file format more suitable for further processing. The column "Name" that names the instrument and the target locations is added manually. In the cases where TopoDroid joined similar measurements into a survey shot due to unsuitable settings and did not export them, they are read from the phone screen and entered manually. The folder "Organised" contains all the data that gets automatically processed by the program DistoX.R. It is the data from the folder "Converted" with possible manual corrections (measurement order in case of mistakes, measurement length in case of the beam bouncing from an obstacle before the target, etc.), the file data_list.txt containing the list of the files to be processed with short descriptions (emphasising the manual corrections), and the file manual.txt containing Suunto measurements for comparison. The folder "Rest" contains notes that are neither automatically processed nor exported from TopoDroid but may be of interest. DistoX.R is the data processing program. Program DistoX.py draws a graph. The file is available at 10.5281/zenodo.3887485.
Similarity between occupations is a crucial piece of information when making career decisions. Ho... more Similarity between occupations is a crucial piece of information when making career decisions. However, the notion of a single and unified occupation similarity measure is more of a limitation than an asset. The goal of the study is to assess multiple explainable occupation similarity measures that can provide different insights into inter-occupation relations. Several such measures are derived using the framework of bipartite graphs. Their viability is assessed on more than 450,000 job transitions occurring in Slovenia in the period between 2012 and 2021. The results support the hypothesis that several similarity measures are plausible and that they present different feasible career paths. The complete implementation and part of the datasets are available at https://repo.ijs.si/pboskoski/bipartite_job_similarity_code.
s................................................................................................... more s........................................................................................................49 CD with short papers 17 International Karstological School “Classical Karst”, Postojna, Slovenia, 2009 4 Financed by the European Union Marie Curie Conferences and Training Courses (http://cordis.europa.eu/mariecurie-actions/scf) Project SMART-KARST (MSCF-2005-029674) Within the frame of the 6 FP Action Marie Curie Conferences & Training Courses the Karst Research Institute SRC SASA is leading the project SMART-KARST: International Karstological school “Sustainable management of natural resources on karst”. The project supports five events organized in the period of 2006 to 2009. Four of them are our regular International Karstological Schools “Classical Karst” held each year in June, and the fifth one is the Symposium on Time in Karst organized in March 2007. An important objective of the project is to bring together researchers of karst from different disciplines, and especi...
... Author: Matija Perne ... A good model should explain the basic features of rillenkarren: the ... more ... Author: Matija Perne ... A good model should explain the basic features of rillenkarren: the peri-odicity of the structure, the cross profile of a rill, the formation at a crest and extinguishing downstream [8]. Rillenkarren formation appears to be complex and it seems that several ...
Abstract In case of a major accident involving airborne emissions of harmful gases, a temporary p... more Abstract In case of a major accident involving airborne emissions of harmful gases, a temporary portable meteorological station may be used to improve atmospheric dispersion modelling (ADM) for protection of people and the environment. While the meteorological station provides signal values in real time, ADM results for the future are of particular interest for planning purposes. It is possible to use the current measured value as a future input to the ADM but it is suboptimal. It is also possible to use model output statistics (MOS) to predict the future local weather information from numerical weather prediction (NWP) models, while available operational NWP models are in general too coarse to be used directly in fine-resolution ADM. MOS models are obtained through machine learning and the training data sets in most traditional uses of MOS are big, which is beneficial for modelling. We envision using MOS in an emergency and for a location of a temporary meteorological station. We use windowing for online data selection to explore its accuracy when the amount of available training data is very limited, which is expected in an emergency situation. We show that MOS for wind vector with 1 day of training data greatly improves on the numerical weather predictions and the persistence model, so its use in such an emergency would be advantageous.
A long-term measured wind speed time series from the location is typically used when deciding on ... more A long-term measured wind speed time series from the location is typically used when deciding on placing a small wind turbine at a particular location. These data take a long time to collect. The presented novel method of measuring for a shorter time, using the measurement data for training an experimental model, and predicting the wind in a longer time period enables one to avoid most of the wait for the data collection. As the model inputs, the available long-term signals that consist of measurements from the meteorological stations in the vicinity and numerical weather predictions are used. Various possible experimental modelling methods that are based on linear or nonlinear regression models are tested in the field sites. The study area is continental with complex terrain, hilly topography, diverse land use, and no prevailing wind. It is shown that the method gives good results, showing linear regression is most advantageous, and that it is easy enough to use to be practically a...
We observe the effects of training data sample selection in modelling of a physical system with G... more We observe the effects of training data sample selection in modelling of a physical system with Gaussian process nonlinear autoregressive models with exogenous input. Gaussian process modelling limits the number of training data points and we use a big nonlinear benchmark data set. The combination calls for training data sample selection. We compare a &#39;smart&#39; method based on Euclidean distance between training data points with decimation. We use the training data samples obtained by both methods to train the models, test model predictions on a test data set, and calculate two figures of merit, e RMSt and mean standardised log loss (MSLL). The model trained on the &#39;smartly&#39; selected training data points is better in e RMSt while the one with the decimated data is superior in MSLL. The direct conclusion is that the purpose of the model determines which training data sample selection method is better, as the relevant figure of merit depends on the model purpose. We notice that the predicted variance is more sensitive to the training data sample than the predicted mean. We warn that training data sample selection may have unexpected consequences.
CAAI Transactions on Intelligence Technology, 2019
This study describes an application of hybrid modelling for an atmospheric variable in the Krsko ... more This study describes an application of hybrid modelling for an atmospheric variable in the Krsko basin. The hybrid model is a combination of a physics-based and data-driven model and has some properties of both modelling approaches. In the authors’ case, it is used for the modelling of an atmospheric variable, namely relative humidity in a particular location for the purpose of using the predictions of the model as an input to the air-pollution-dispersion model for radiation exposure. The presented hybrid model is a combination of a physics-based atmospherical model and a Gaussian-process (GP) regression model. The GP model is a probabilistic kernel method that also enables evaluation of prediction confidence. The problem of poor scalability of GP modelling was solved using sparse GP modelling; in particular, the fully independent training conditional method was used. Two different approaches to dataset selection for empirical model training were used and multiple-step-ahead predictions for different horizons were assessed. It is shown in this study that the accuracy of the predicted relative humidity in the Krsko basin improved when using hybrid models over using the physics-based model alone and that predictions for a considerable length of horizon can be used.
<strong>Opis problema</strong> Pojavila se je naprava za umerjanje DistoX, ki me je s... more <strong>Opis problema</strong> Pojavila se je naprava za umerjanje DistoX, ki me je spodbudila k temu, da sem preizkusil umerjanje DistoX z njo in brez nje. Poročilo o ugotovitvah je objavljeno v članku v Glasu podzemlja 2020 (na voljo tudi tu). <strong>Opis datotek</strong> Podatki so razvrščeni takole: Podmapa "Izvorni" vsebuje datoteke, ki jih je neposredno izvozil TopoDroid; Podmapa "Pretvorjeni" vsebuje ročno pretvorjene podatke iz mape "Izvorni" v nadaljnji obdelavi prijaznejšo obliko datoteke. Ročno sem jim dodal stolpec "Ime", ki pove, s katerega na katero oglišče trikotnika je merjeno. Kjer je TopoDroid zaradi neustreznih nastavitev podobne meritve samodejno združeval v vizure in meritev ni izvozil, sem te meritve ročno pretipkal z zaslona telefona. Podmapa "Urejeni" vsebuje vse podatke, ki vstopajo v samodejno obdelavo s programom DistoX.R. To so podatki iz mape "Pretvorjeni" z morebitnimi ročnimi popravki (vrstnega reda vizur ob pomotah, dolžine vizur če se je žarek kje prekmalu ustavil, ...) in datoteka seznam_podatkov.txt, ki vsebuje seznam datotek, ki jih obdela program, s kratkimi opisi (predvsem opisi ročnih popravkov). Podmapa "Ostali" vsebuje zapiske, ki niti ne vstopajo v program niti niso izvoženi iz TopoDroid-a, a bi bili lahko zanimivi. DistoX.R je program za obdelavo podatkov. Program DistoX.py služi samo risanju grafa. K preizkušanju so bistveno pripomogli Marjan Baričič, Matic Di Batista, Gregor Pintar, Peter Prevec, Janez Strojan starejši in Rafko Urankar-Cile.
UDC 53.089.6:551.44 Matija Perne: DistoX calibration tools and the need for calibration checking ... more UDC 53.089.6:551.44 Matija Perne: DistoX calibration tools and the need for calibration checking For proper cave surveying using DistoX, the device needs to be calibrated with adequate accuracy. Calibrating does not require any tools; but, tools to make calibration easier have been developed. Theoretical consideration shows that the use of certain tools enables one to introduce a type of calibration error that goes undetected by the calibration software. In this study, the existence of such errors is experimentally confirmed and their magnitude is estimated. It is demonstrated to be crucial that the DistoX is calibrated and that the calibration is valid, that is, that the device has not changed since it was last calibrated. No part of the DistoX must have moved or changed its magnetization since calibration, not even the battery. The calibration method used and the quality of the resulting calibration are important too. It is highly recommended that the DistoX be checked immediately...
Quadratic programs resulting from a model predictive control problem in real-time control context... more Quadratic programs resulting from a model predictive control problem in real-time control context are solved using a dual gradient method. The projection operator of the method is modified so as to implement soft state constraints with linear and quadratic cost on constraint violation without directly calculating values of slack variables. Evolution of iterates and residuals throughout iterations of the modified method is studied. We notice that in most iterations, the set of the constraints that are active and the ones that are violated does not change. Observing the residuals through multiple iterations in which the active and violated sets do not change leads to interesting results. When the dual residual is transformed into a certain base, its components are decaying independently of each other and at exactly predictable rates. The transformation only depends on the system matrices and on the active and violated sets. Since the matrices are independent of the system state, so is...
A faster implementation of the Quadratic Programming (QP) solver used in the Model Predictive Con... more A faster implementation of the Quadratic Programming (QP) solver used in the Model Predictive Control scheme for Iter Plasma current and shape control was developed for Xilinx Field-Programmable Gate Array (FPGA) platforms using a high-level synthesis approach. The QP solver is based on the dual Fast Gradient Method (dFGM). The dFGM is essentially an iterative algorithm, where matrix-vector arithmetic operations within the main iteration loop may be parallelized. This type of parallelism is not well-suited to standard multi-core processors because the number of operations to be spread among processing threads is relatively small considering the time-scale of thread scheduling. The FPGA implementation avoids this issue, but it requires specific techniques of code optimization in order to achieve faster solver execution.
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