cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/d3bgrrfz7k.2
title: Evapotranspiration and crop coefficients of potato in a semi-arid climate (South Africa)

description: Correct estimation of crop coefficients is essential to accurately assess water requirements of crops and thereby optimize irrigation management. The objectives of this study were (i) to quantify evapotranspiration and water use efficiency of potato crops grown in different locations and seasons in a semi-arid climate under irrigation, (ii) to estimate Kc values for these crops at different growth stages, and (iii) to assess the usefulness of the Penman-Monteith equation to estimate evapotranspiration and irrigation requirements. An eddy covariance system (ECV) was used in potato fields in three production regions of South Africa: the western Free State (summer crop), North West (spring crop) and Limpopo (winter crop). An IRGASON integrated open-path CO2/H2O gas analyzer - the ECV system (Campbell Scientific) was used to measure the H2O vapour fluxes above the crop canopy. It was integrated with a sonic anemometer, which measures the three-dimensional wind speed. Additional supporting sensors (fine wire thermocouple, NR-Lite net radiometer, silicon pyranometer, krypton hygrometer, CS616 reflectometer, Hukseflux heat flux plates) and a tipping bucket rain gauge were added to the system. Data were sampled at a frequency of 10 Hz, processed using EasyFlux DL software (Campbell Scientific), and recorded using a CR3000 datalogger. Seasonal mean crop evapotranspiration (ETc) was 4.6, 4.4 and 2.8 mm/day, respectively, for the summer, spring and winter crops. The reference evapotranspiration (ETo) correlated well with the daily patterns in ETc (r = 0.89, 0.56 and 0.76 for winter, spring and summer potato crops, respectively) and can be used for irrigation scheduling of potato. Seasonal mean Kc values varied considerably between the winter (1.00) and the spring (0.69) / summer (0.79) crops. This range is within the range reported from other parts of the world. The winter crop had the highest WUE of 3.2 kg dry potato tuber m3 of water evapotranspired, whilst WUE for the spring and summer crops was 2.9 and 2.2 kg/m3. The corresponding dry matter tuber yields were 12.0 t/ha (winter crop), 14.1 t/ha (spring crop) and 9.1 t ha/1 (summer crop). Our results suggest that ETo, which can be relatively easily estimated based on data from a weather station, can be used for irrigation scheduling of potato, but Kc values used to estimate crop evapotranspiration and irrigation requirements may need to be adjusted depending on the cropping season. Water use efficiency of potato was higher for the crop growing in the cooler winter compared to the crops growing in spring / summer. To optimize water use efficiency of potato in water-scarce areas that rely mostly on irrigation water for potato production, it is advisable to grow potato crops in the cooler season, outside the frost-prone period if possible.
DOI: 10.17632/d3bgrrfz7k.3
title: Evapotranspiration and crop coefficients of potato in a semi-arid climate (South Africa)

description: Correct estimation of crop coefficients is essential to accurately assess water requirements of crops and thereby optimize irrigation management. The objectives of this study were (i) to quantify evapotranspiration and water use efficiency of potato crops grown in different locations and seasons in a semi-arid climate under irrigation, (ii) to estimate Kc values for these crops at different growth stages, and (iii) to assess the usefulness of the Penman-Monteith equation to estimate evapotranspiration and irrigation requirements. An eddy covariance system (ECV) was used in potato fields in three production regions of South Africa: the western Free State (summer crop), North West (spring crop) and Limpopo (winter crop). An IRGASON integrated open-path CO2/H2O gas analyzer - the ECV system (Campbell Scientific) was used to measure the H2O vapour fluxes above the crop canopy. It was integrated with a sonic anemometer, which measures the three-dimensional wind speed. Additional supporting sensors (fine wire thermocouple, NR-Lite net radiometer, silicon pyranometer, krypton hygrometer, CS616 reflectometer, Hukseflux heat flux plates) and a tipping bucket rain gauge were added to the system. Data were sampled at a frequency of 10 Hz, processed using EasyFlux DL software (Campbell Scientific), and recorded using a CR3000 datalogger. Seasonal mean crop evapotranspiration (ETc) was 4.6, 4.4 and 2.8 mm/day, respectively, for the summer, spring and winter crops. The reference evapotranspiration (ETo) correlated well with the daily patterns in ETc (r = 0.89, 0.56 and 0.76 for winter, spring and summer potato crops, respectively) and can be used for irrigation scheduling of potato. Seasonal mean Kc values varied considerably between the winter (1.00) and the spring (0.69) / summer (0.79) crops. This range is within the range reported from other parts of the world. The winter crop had the highest WUE of 3.2 kg dry potato tuber m3 of water evapotranspired, whilst WUE for the spring and summer crops was 2.9 and 2.2 kg/m3. The corresponding dry matter tuber yields were 12.0 t/ha (winter crop), 14.1 t/ha (spring crop) and 9.1 t ha/1 (summer crop). Our results suggest that ETo, which can be relatively easily estimated based on data from a weather station, can be used for irrigation scheduling of potato, but Kc values used to estimate crop evapotranspiration and irrigation requirements may need to be adjusted depending on the cropping season. Water use efficiency of potato was higher for the crop growing in the cooler winter compared to the crops growing in spring / summer. To optimize water use efficiency of potato in water-scarce areas that rely mostly on irrigation water for potato production, it is advisable to grow potato crops in the cooler season, outside the frost-prone period if possible.
DOI: 10.17632/prk6fsn56y.1
title: Breit–Pauli R-Matrix approach for the time-dependent investigation of ultrafast processes

description: We have refactored the Breit–Pauli R-Matrix integral package within the RMatrxI package to employ a B-Spline basis to allow for level-resolved time-dependent R-Matrix calculations involving a laser pulse. The B-Spline approach independently verifies the accuracy of the current integral package pstg1r.f, but requires greater flexibility at the R-Matrix boundary when describing the continuum wavefunctions. This adaptation can be integrated with either the subsequent serial or parallel Breit–Pauli suite of codes.
DOI: 10.7281/t1/1ecvb0/4edgpw
title: DustOff-monthly-average_wrfout_d01_2010-03_06_mean.nc
DOI: 10.7281/t1/1ecvb0/b76ymt
title: DustOff-monthly-average_wrfout_d01_2014-05_00_mean.nc
DOI: 10.7281/t1/1ecvb0/b8hsea
title: DustOff-monthly-average_wrfout_d01_2010-08_00_mean.nc
DOI: 10.7281/t1/1ecvb0/bspbjb
title: DustOff-monthly-average_wrfout_d01_2010-07_18_mean.nc
DOI: 10.7281/t1/1ecvb0/bu2ozw
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-09_06_std.nc
DOI: 10.7281/t1/1ecvb0/eoeayg
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-04_18_std.nc
DOI: 10.7281/t1/1ecvb0/ezobub
title: DustOff-monthly-average_wrfout_d01_2010-06_06_mean.nc
DOI: 10.7281/t1/1ecvb0/gsc7pn
title: DustOff-monthly-average_wrfout_d01_2010-05_00_mean.nc
DOI: 10.7281/t1/1ecvb0/han9xb
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-09_18_std.nc
DOI: 10.7281/t1/1ecvb0/kgwtcp
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-05_00_std.nc
DOI: 10.7281/t1/1ecvb0/lh2bmj
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-03_18_std.nc
DOI: 10.7281/t1/1ecvb0/nlkutt
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-05_12_std.nc
DOI: 10.7281/t1/1ecvb0/ovv7xv
title: DustOff-monthly-average_wrfout_d01_2010-09_06_mean.nc
DOI: 10.7281/t1/1ecvb0/qgjxjp
title: DustOff-monthly-average_wrfout_d01_2014-07_18_mean.nc
DOI: 10.7281/t1/1ecvb0/rch9vk
title: DustOff-monthly-average_wrfout_d01_2014-04_06_mean.nc
DOI: 10.7281/t1/1ecvb0/rglb0g
title: DustOff-monthly-average_wrfout_d01_2010-08_12_mean.nc
DOI: 10.7281/t1/1ecvb0/sqf4td
title: DustOff-monthly-average_wrfout_d01_2014-08_00_mean.nc
DOI: 10.7281/t1/1ecvb0/szbpx9
title: DustOff-monthly-average_wrfout_d01_2014-08_18_mean.nc
DOI: 10.7281/t1/1ecvb0/tqbsfp
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-04_06_std.nc
DOI: 10.7281/t1/1ecvb0/ytf2bx
title: DustOff-monthly-average_wrfout_d01_2010-07_00_mean.nc
DOI: 10.7281/t1/1ecvb0/yuzoyd
title: DustOff-monthly-average_wrfout_d01_2014-09_06_mean.nc
DOI: 10.7281/t1/1ecvb0/ywvhr0
title: DustOff-monthly-average_wrfout_d01_2010-05_12_mean.nc
DOI: 10.7281/t1/1ecvb0/zzmrob
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-03_06_std.nc
DOI: 10.13140/rg.2.2.17400.60161
title: Data Analysis and Application (DAA) Two-Way Factorial ANOVA
DOI: 10.13140/rg.2.2.30822.37443
title: Data Analysis and Application (DAA) Two-Way Factorial ANOVA
DOI: 10.17632/932kxghmmg.1
title: Evapotranspiration of potato in a semi-arid climate

description: Correct estimation of crop coefficients is essential to accurately assess water requirements of crops and thereby optimize irrigation management. The objectives of this study were (i) to quantify evapotranspiration and water use efficiency of potato crops grown in different locations and seasons in a semi-arid climate under irrigation, (ii) to estimate Kc values for these crops at different growth stages, and (iii) to assess the usefulness of the Penman-Monteith equation to estimate evapotranspiration and irrigation requirements. An eddy covariance system (ECV) was used in potato fields in three production regions of South Africa: the western Free State (summer crop), North West (spring crop) and Limpopo (winter crop). An IRGASON integrated open-path CO2/H2O gas analyzer - the ECV system (Campbell Scientific) was used to measure the H2O vapour fluxes above the crop canopy. It was integrated with a sonic anemometer, which measures the three-dimensional wind speed. Additional supporting sensors (fine wire thermocouple, NR-Lite net radiometer, silicon pyranometer, krypton hygrometer, CS616 reflectometer, Hukseflux heat flux plates) and a tipping bucket rain gauge were added to the system. Data were sampled at a frequency of 10 Hz, processed using EasyFlux DL software (Campbell Scientific), and recorded using a CR3000 datalogger. Seasonal mean crop evapotranspiration (ETc) was 4.6, 4.4 and 2.8 mm/day, respectively, for the summer, spring and winter crops. The reference evapotranspiration (ETo) correlated well with the daily patterns in ETc (r = 0.89, 0.56 and 0.76 for winter, spring and summer potato crops, respectively) and can be used for irrigation scheduling of potato. Seasonal mean Kc values varied considerably between the winter (1.00) and the spring (0.69) / summer (0.79) crops. This range is within the range reported from other parts of the world. The winter crop had the highest WUE of 3.2 kg dry potato tuber m3 of water evapotranspired, whilst WUE for the spring and summer crops was 2.9 and 2.2 kg/m3. The corresponding dry matter tuber yields were 12.0 t/ha (winter crop), 14.1 t/ha (spring crop) and 9.1 t ha/1 (summer crop). Our results suggest that ETo, which can be relatively easily estimated based on data from a weather station, can be used for irrigation scheduling of potato, but Kc values used to estimate crop evapotranspiration and irrigation requirements may need to be adjusted depending on the cropping season. Water use efficiency of potato was higher for the crop growing in the cooler winter compared to the crops growing in spring / summer. To optimize water use efficiency of potato in water-scarce areas that rely mostly on irrigation water for potato production, it is advisable to grow potato crops in the cooler season, outside the frost-prone period if possible.
DOI: 10.17632/rybgtbbhs9.2
title: MEdit4CEP-SP dataset

description: In this dataset we collect the Event Processing Language (EPL) patterns used in this work, as well as some screenshots of the proposed system, MEdit4CEP-SP. EPL &gt; pattern.epl contains all the patterns for the situations described on the paper (AnomalyReadingErrors, AnomalyWaterLeaks and AnomalyUnusualConsumption). Screenshots &gt; reading-errors-pattern.png shows the graphical model, in the editor, of the pattern AnomalyReadingErrors described on the paper. Screenshots &gt; water-leaks-pattern.png shows the graphical model, in the editor, of the pattern AnomalyWaterLeaks described on the paper. Screenshots &gt; unusual-consumption-pattern.png shows the graphical model, in the editor, of the pattern AnomalyUnusualConsumption described on the paper. Screenshots &gt; pattern-changes-alert.png shows the alert that the editor triggers when an existing pattern has been updated. Screenshots &gt; pattern-remove-backup.png shows the dialog to select the folder where the removed existing pattern is going to be exported.
DOI: 10.18430/m36vww
title: X-ray diffraction data for the crystal Structure of NSP15 Endoribonuclease from SARS CoV-2. (6VWW)
DOI: 10.18430/m36vxs
title: X-ray diffraction data for the crystal Structure of ADP ribose phosphatase of NSP3 from SARS CoV-2 (6VXS)
DOI: 10.18430/m36w01
title: X-ray diffraction data for the the 1.9 A Crystal Structure of NSP15 Endoribonuclease from SARS CoV-2 in the Complex with a Citrate (6W01)
DOI: 10.7281/t1/1ecvb0/4laqjs
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-09_12_std.nc
DOI: 10.7281/t1/1ecvb0/8slmqb
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-05_18_std.nc
DOI: 10.7281/t1/1ecvb0/9efwpq
title: DustOff-monthly-average_wrfout_d01_2014-05_06_mean.nc
DOI: 10.7281/t1/1ecvb0/af6yhx
title: DustOff-monthly-average_wrfout_d01_2014-04_00_mean.nc
DOI: 10.7281/t1/1ecvb0/bsw3sg
title: DustOff-monthly-average_wrfout_d01_2010-09_00_mean.nc
DOI: 10.7281/t1/1ecvb0/cypkme
title: DustOff-monthly-average_wrfout_d01_2010-05_06_mean.nc
DOI: 10.7281/t1/1ecvb0/eqd9fe
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-10_00_std.nc
DOI: 10.7281/t1/1ecvb0/fhbxya
title: DustOff-monthly-average_wrfout_d01_2010-04_00_mean.nc
DOI: 10.7281/t1/1ecvb0/flrlah
title: DustOff-monthly-average_wrfout_d01_2014-10_18_mean.nc
DOI: 10.7281/t1/1ecvb0/fwkjqq
title: DustOff-monthly-average_wrfout_d01_2014-07_00_mean.nc
DOI: 10.7281/t1/1ecvb0/jzph0d
title: DustOff-monthly-average_wrfout_d01_2010-03_12_mean.nc
DOI: 10.7281/t1/1ecvb0/kkguwu
title: DustOff-monthly-average_wrfout_d01_2010-10_18_mean.nc
DOI: 10.7281/t1/1ecvb0/ksylts
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-10_12_std.nc
DOI: 10.7281/t1/1ecvb0/m9klew
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-09_00_std.nc
DOI: 10.7281/t1/1ecvb0/nxvju5
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-04_00_std.nc
DOI: 10.7281/t1/1ecvb0/ohcxnd
title: DustOff-monthly-average_wrfout_d01_2014-05_12_mean.nc
DOI: 10.7281/t1/1ecvb0/pv89va
title: DustOff-monthly-average_wrfout_d01_2014-06_06_mean.nc
DOI: 10.7281/t1/1ecvb0/rilexp
title: DustOff-monthly-average_wrfout_d01_2010-08_06_mean.nc
DOI: 10.7281/t1/1ecvb0/u2i7nl
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-04_12_std.nc
DOI: 10.7281/t1/1ecvb0/vcrjs9
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-05_06_std.nc
DOI: 10.7281/t1/1ecvb0/wxkpqc
title: DustOff-monthly-average_wrfout_d01_2014-03_06_mean.nc
DOI: 10.7281/t1/1ecvb0/xvx469
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-08_06_std.nc
DOI: 10.7281/t1/1ecvb0/zik9w0
title: DustOff-monthly-average_wrfout_d01_2014-08_12_mean.nc
DOI: 10.17632/kbtfyrhtxv.1
title: Topographic data_xj PE

description: The topographic data were used in the paper about paleoearthqakes of the Xiaojiang fault zone.
DOI: 10.17632/r53wxcvt5g.1
title: Data for the paper titled: Application of change-point analysis to the selection of representative data in creep experiments

description: These files include the representative creep data of experimentally investigated alloy VF80 which is a single crystalline (SX) γ′-strengthened Co-base superalloy. The creep test was performed in compression at 950 C and at a constant stress of 400 MPa. The representative data have been selected with different methods. Each file includes three columns: time, plastic strain and strain rate. manual.txt: The result of the manual selection of representative data by the practitioner mean.txt, sbs.txt, and var.txt: The results of the automated selection of representative data by statistical methods
DOI: 10.17632/szhw6k2bsv.1
title: Zonguldak, Turkey: Mining-induced Land Deformation in 2018-2019 - Sentinel 1 SBAS results

description: This is a dataset consisting of the SBAS LOS land deformation and the differences between TanDEM-X and SRTM DEMs over a mining area located in Zonguldak district, Turkey. The land deformation was calculated based on the Copernicus Sentinel 1A/B SAR data collected between Jan 2018 and Nov 2019. The dataset allows for the study of the relationship between the deformations and differences between DEMs captured some 11 years apart. The data are in ESRI's shop format. The raster is in tiff format.
DOI: 10.18430/m36w02
title: X-ray diffraction data for the crystal Structure of ADP ribose phosphatase of NSP3 from SARS CoV-2 in the complex with ADP ribose (6W02)
DOI: 10.18430/m36w4b
title: X-ray diffraction data for the the crystal structure of Nsp9 RNA binding protein of SARS CoV-2 (6W4B)
DOI: 10.7281/t1/1ecvb0/34dnbe
title: DustOff-monthly-average_wrfout_d01_2010-07_06_mean.nc
DOI: 10.7281/t1/1ecvb0/3ecjop
title: DustOff-monthly-average_wrfout_d01_2014-03_12_mean.nc
DOI: 10.7281/t1/1ecvb0/6xklp9
title: DustOff-monthly-average_wrfout_d01_2014-06_12_mean.nc
DOI: 10.7281/t1/1ecvb0/8d3l2s
title: DustOff-monthly-average_wrfout_d01_2010-10_00_mean.nc
DOI: 10.7281/t1/1ecvb0/9jyhuc
title: DustOff-monthly-average_wrfout_d01_2010-06_12_mean.nc
DOI: 10.7281/t1/1ecvb0/ainj9h
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-06_18_std.nc
DOI: 10.7281/t1/1ecvb0/b0cvqr
title: DustOff-monthly-average_wrfout_d01_2014-08_06_mean.nc
DOI: 10.7281/t1/1ecvb0/bra3ji
title: DustOff-monthly-average_wrfout_d01_2010-04_18_mean.nc
DOI: 10.7281/t1/1ecvb0/dt4bfh
title: DustOff-monthly-average_wrfout_d01_2014-10_00_mean.nc
DOI: 10.7281/t1/1ecvb0/ms3flo
title: DustOff-monthly-average_wrfout_d01_2010-09_18_mean.nc
DOI: 10.7281/t1/1ecvb0/nrbzt9
title: DustOff-monthly-average_wrfout_d01_2014-09_00_mean.nc
DOI: 10.7281/t1/1ecvb0/pbbr92
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-07_00_std.nc
DOI: 10.7281/t1/1ecvb0/rblb3h
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-06_06_std.nc
DOI: 10.7281/t1/1ecvb0/td6n7w
title: DustOff-monthly-average_wrfout_d01_2014-04_18_mean.nc
DOI: 10.7281/t1/1ecvb0/tmn9nu
title: DustOff-monthly-average_wrfout_d01_2010-06_00_mean.nc
DOI: 10.7281/t1/1ecvb0/x86gpm
title: DustOff-monthly-standard-deviation_wrfout_d01_2008-08_18_std.nc
DOI: 10.7281/t1/1ecvb0/yry0jn
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-07_12_std.nc
DOI: 10.18430/m36w61
title: X-ray diffraction data for the crystal Structure of the methyltransferase-stimulatory factor complex of NSP16 and NSP10 from SARS CoV-2. (6W61)
DOI: 10.7281/t1/1ecvb0/273b1q
title: DustOff-monthly-average_wrfout_d01_2014-07_06_mean.nc
DOI: 10.7281/t1/1ecvb0/6qres0
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-10_06_std.nc
DOI: 10.7281/t1/1ecvb0/9ls89k
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-06_12_std.nc
DOI: 10.7281/t1/1ecvb0/9ptsi9
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-04_06_std.nc
DOI: 10.7281/t1/1ecvb0/al84yb
title: DustOff-monthly-average_wrfout_d01_2010-03_00_mean.nc
DOI: 10.7281/t1/1ecvb0/av921a
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-06_00_std.nc
DOI: 10.7281/t1/1ecvb0/avjbqa
title: DustOff-monthly-average_wrfout_d01_2014-09_18_mean.nc
DOI: 10.7281/t1/1ecvb0/bgzzvz
title: DustOff-monthly-average_wrfout_d01_2010-04_12_mean.nc
DOI: 10.7281/t1/1ecvb0/crtlod
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-07_18_std.nc
DOI: 10.7281/t1/1ecvb0/dmx77s
title: DustOff-monthly-average_wrfout_d01_2010-03_18_mean.nc
DOI: 10.7281/t1/1ecvb0/fdwkt9
title: DustOff-monthly-average_wrfout_d01_2010-09_12_mean.nc
DOI: 10.7281/t1/1ecvb0/fqlfae
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-07_06_std.nc
DOI: 10.7281/t1/1ecvb0/knkrqr
title: DustOff-monthly-average_wrfout_d01_2014-04_12_mean.nc
DOI: 10.7281/t1/1ecvb0/kugkfd
title: DustOff-monthly-average_wrfout_d01_2014-10_12_mean.nc
DOI: 10.7281/t1/1ecvb0/le4bg5
title: DustOff-monthly-average_wrfout_d01_2014-06_18_mean.nc
DOI: 10.7281/t1/1ecvb0/qntvcm
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-04_18_std.nc
DOI: 10.7281/t1/1ecvb0/ry5aoa
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-10_18_std.nc
DOI: 10.7281/t1/1ecvb0/swlqty
title: DustOff-monthly-average_wrfout_d01_2014-03_18_mean.nc
DOI: 10.7281/t1/1ecvb0/tgjjuu
title: DustOff-monthly-average_wrfout_d01_2014-06_00_mean.nc
DOI: 10.7281/t1/1ecvb0/xnnwwe
title: DustOff-monthly-average_wrfout_d01_2010-10_12_mean.nc
DOI: 10.6084/m9.figshare.12095196.v3
title: HOSVD-ALS

description: <b>Introduction</b><b><br></b>The truncated Tucker decomposition, also known as the truncated higher-order singular value decomposition (HOSVD), has been extensively utilized as an efficient tool in many applications. Popular direct methods for truncated HOSVD often suffer from the notorious intermediate data explosion issue and are not easy to parallelize. To handle these issues, we proposed a class of alternating least squares (ALS) based algorithms for HOSVD. The proposed methods are able to eliminate the redundant computations of the singular vectors of intermediate matrices and are therefore free of data explosion. Also, the new methods are more flexible with adjustable convergence tolerance and are intrinsically parallelizable on high-performance computers. The link of our paper is https://arxiv.org/abs/2004.02583.<b><br></b><b>Data sets</b><b><br></b>We provide three groups of test tensors and the corresponding numerical results.1. Randomly generated low rank dense tensors with Gaussian noise.2. Randomly generated sparse tensors.3. Tensors generated from the simulation results of a lid-driven cavity flow.You can view all of these from 'data_sets.rar' and 'results.rar'.
DOI: 10.7281/t1/1ecvb0/1jluoy
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-03_00_std.nc
DOI: 10.7281/t1/1ecvb0/7hniti
title: DustOff-monthly-average_wrfout_d01_2015-06_18_mean.nc
DOI: 10.7281/t1/1ecvb0/bgti2m
title: DustOff-monthly-average_wrfout_d01_2015-09_12_mean.nc
DOI: 10.7281/t1/1ecvb0/bx72bk
title: DustOff-monthly-average_wrfout_d01_2011-06_18_mean.nc
DOI: 10.7281/t1/1ecvb0/ckqnhf
title: DustOff-monthly-average_wrfout_d01_2011-09_12_mean.nc
DOI: 10.7281/t1/1ecvb0/cldadi
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-05_12_std.nc
DOI: 10.7281/t1/1ecvb0/cztt67
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-09_18_std.nc
DOI: 10.7281/t1/1ecvb0/g61eao
title: DustOff-monthly-average_wrfout_d01_2011-04_12_mean.nc
DOI: 10.7281/t1/1ecvb0/gno4ko
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-03_12_std.nc
DOI: 10.7281/t1/1ecvb0/h7o35x
title: DustOff-monthly-average_wrfout_d01_2014-09_12_mean.nc
DOI: 10.7281/t1/1ecvb0/j6qpqy
title: DustOff-monthly-average_wrfout_d01_2011-03_18_mean.nc
DOI: 10.7281/t1/1ecvb0/jdszba
title: DustOff-monthly-average_wrfout_d01_2015-04_12_mean.nc
DOI: 10.7281/t1/1ecvb0/mkogn9
title: DustOff-monthly-average_wrfout_d01_2011-03_00_mean.nc
DOI: 10.7281/t1/1ecvb0/mxxxdn
title: DustOff-monthly-average_wrfout_d01_2015-03_00_mean.nc
DOI: 10.7281/t1/1ecvb0/o7b8nz
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-08_12_std.nc
DOI: 10.7281/t1/1ecvb0/opq1mr
title: DustOff-monthly-average_wrfout_d01_2014-03_00_mean.nc
DOI: 10.7281/t1/1ecvb0/pzpgd8
title: DustOff-monthly-average_wrfout_d01_2011-07_06_mean.nc
DOI: 10.7281/t1/1ecvb0/qak60r
title: DustOff-monthly-average_wrfout_d01_2011-10_12_mean.nc
DOI: 10.7281/t1/1ecvb0/sexfjj
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-09_06_std.nc
DOI: 10.7281/t1/1ecvb0/t7i5d4
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-08_00_std.nc
DOI: 10.7281/t1/1ecvb0/tjjkdn
title: DustOff-monthly-standard-deviation_wrfout_d01_2009-05_00_std.nc