cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21078136.v3
title: Real-time measurement of debris-flow impact force at Jiangjia Ravine, China

description: This is Metadata for real-time impact-force measurements and field observations of debris flows recorded by a sensor network in Jiangjia Ravine, China. We observed 49 debris flows during and after a storm on August 25, 2004, including 42 debris-flow surges and seven continuous debris flows.
DOI: 10.18434/mds2-2635
title: Computer Forensic Reference Data Set Portal
DOI: 10.5281/zenodo.7075028
title: Science through ML: Post-storm Cooling Data and Programs

description: These programs and data are associated with the AGU Space Weather Journal article "Science through Machine Learning: Quantification of Post-storm Thermospheric Cooling".
DOI: 10.5281/zenodo.7075027
title: Science through ML: Post-storm Cooling Data and Programs

description: These programs and data are associated with the AGU Space Weather Journal article "Science through Machine Learning: Quantification of Post-storm Thermospheric Cooling".
DOI: 10.5281/zenodo.7075179
title: An SEM Approach to Validating the Psychological Model of Musical Groove (Data Set)

description: Data set for the study "An SEM Approach to Validating the Psychological Model of Musical Groove"
DOI: 10.5281/zenodo.7075178
title: An SEM Approach to Validating the Psychological Model of Musical Groove (Data Set)

description: Data set for the study "An SEM Approach to Validating the Psychological Model of Musical Groove"
DOI: 10.5281/zenodo.7075074
title: HTR - Araucania - XIX manuscript

description: <strong>General</strong> Ground Truth dataset for Spanish 19th typewritten OCR (XML-ALTO) The archives come from the events of the Occupation of Araucania (1850-1881) in Chile. They are archived in the 'Colección manuscritos' of the Archivo Central Andres Bello - Universidad de Chile. Thereby, it is not possible to publicly distribute the images (.jpg) To use them for segmentation/recognition model training, please contact me : archivo.central@uchile.cl <strong>Methodology</strong> Transcription rules : - xxx for blurred or unreadable characters<br> - ^+letters for superscript letters<br> - ⁋ for new paragraph Using the Kraken OCR engine in finetuning with the Menu_MacFrench template. A template uses the NFKD method. Segmonto ontology <strong>Evaluation</strong> <strong>Name</strong> <strong>Quantity (GT)</strong> <strong>Val_acc</strong> <strong>Test_acc</strong> <strong>CER</strong> <strong>WER</strong> <strong>HTR-Araucania_XIX</strong> 180 0,90354 0,8673 0,05598 0.21423 <strong>HTR-Araucania_XIX_NFKD</strong> 180 0,89872 0,8563 0,06646 0.24963 <strong>Others</strong> JSONL file for NER annotation in <code>ner/</code> (MISC, LOC, PERS, ORG, DATE)
DOI: 10.5281/zenodo.7075075
title: HTR - Araucania - XIX manuscript

description: <strong>General</strong> Ground Truth dataset for Spanish 19th typewritten OCR (XML-ALTO) The archives come from the events of the Occupation of Araucania (1850-1881) in Chile. They are archived in the 'Colección manuscritos' of the Archivo Central Andres Bello - Universidad de Chile. Thereby, it is not possible to publicly distribute the images (.jpg) To use them for segmentation/recognition model training, please contact me : archivo.central@uchile.cl <strong>Methodology</strong> Transcription rules : - xxx for blurred or unreadable characters<br> - ^+letters for superscript letters<br> - ⁋ for new paragraph Using the Kraken OCR engine in finetuning with the Menu_MacFrench template. A template uses the NFKD method. Segmonto ontology <strong>Evaluation</strong> <strong>Name</strong> <strong>Quantity (GT)</strong> <strong>Val_acc</strong> <strong>Test_acc</strong> <strong>CER</strong> <strong>WER</strong> <strong>HTR-Araucania_XIX</strong> 180 0,90354 0,8673 0,05598 0.21423 <strong>HTR-Araucania_XIX_NFKD</strong> 180 0,89872 0,8563 0,06646 0.24963 <strong>Others</strong> JSONL file for NER annotation in <code>ner/</code> (MISC, LOC, PERS, ORG, DATE)
DOI: 10.5281/zenodo.7075149
title: HTR - Araucania - XIX manuscript

description: <strong>General</strong> Ground Truth dataset for Spanish 19th typewritten OCR (XML-ALTO) The archives come from the events of the Occupation of Araucania (1850-1881) in Chile. They are archived in the 'Colección manuscritos' of the Archivo Central Andres Bello - Universidad de Chile. Thereby, it is not possible to publicly distribute the images (.jpg) To use them for segmentation/recognition model training, please contact me : archivo.central@uchile.cl <strong>Methodology</strong> Transcription rules : - xxx for blurred or unreadable characters<br> - ^+letters for superscript letters<br> - ⁋ for new paragraph Using the Kraken OCR engine in finetuning with the Menu_MacFrench template. A template uses the NFKD method. Segmonto ontology <strong>Evaluation</strong> <strong>Name</strong> <strong>Quantity (GT)</strong> <strong>Val_acc</strong> <strong>Test_acc</strong> <strong>CER</strong> <strong>WER</strong> <strong>HTR-Araucania_XIX</strong> 180 0,90354 0,8673 0,05598 0.21423 <strong>HTR-Araucania_XIX_NFKD</strong> 180 0,89872 0,8563 0,06646 0.24963 <strong>Others</strong> JSONL file for NER annotation in <code>ner/</code> (MISC, LOC, PERS, ORG, DATE)
DOI: 10.5281/zenodo.7075186
title: HTR - Araucania - XIX manuscript

description: <strong>General</strong> Ground Truth dataset for Spanish 19th typewritten OCR (XML-ALTO) The archives come from the events of the Occupation of Araucania (1850-1881) in Chile. They are archived in the 'Colección manuscritos' of the Archivo Central Andres Bello - Universidad de Chile. Thereby, it is not possible to publicly distribute the images (.jpg) To use them for segmentation/recognition model training, please contact me : archivo.central@uchile.cl <strong>Methodology</strong> Transcription rules : - xxx for blurred or unreadable characters<br> - ^+letters for superscript letters<br> - ⁋ for new paragraph Using the Kraken OCR engine in finetuning with the Menu_MacFrench template. A template uses the NFKD method. Segmonto ontology <strong>Evaluation</strong> <strong>Name</strong> <strong>Quantity (GT)</strong> <strong>Val_acc</strong> <strong>Test_acc</strong> <strong>CER</strong> <strong>WER</strong> <strong>HTR-Araucania_XIX</strong> 180 0,90354 0,8673 0,05598 0.21423 <strong>HTR-Araucania_XIX_NFKD</strong> 180 0,89872 0,8563 0,06646 0.24963 <strong>Others</strong> JSONL file for NER annotation in <code>ner/</code> (MISC, LOC, PERS, ORG, DATE)
DOI: 10.5281/zenodo.7075214
title: CCS database for steroids

description: Database containing High Resolution Mass spectrometric information as well as chromatographic retention time and Collision Cross Section values for steroids.
DOI: 10.5281/zenodo.7075213
title: CCS database for steroids

description: Database containing High Resolution Mass spectrometric information as well as chromatographic retention time and Collision Cross Section values for steroids.
DOI: 10.5281/zenodo.7075173
title: The Role of Actors in Platform Ecosystems: Selected Studies and Coding Results

description: 13th International Conference on Software Business (ICSOB 2022). Paper: The Role of Actors in Platform Ecosystems: A Systematic Literature Review and Comparison Across Platform Types File: Selected Studies and Coding Results.
DOI: 10.5281/zenodo.7075172
title: The Role of Actors in Platform Ecosystems: Selected Studies and Coding Results

description: 13th International Conference on Software Business (ICSOB 2022). Paper: The Role of Actors in Platform Ecosystems: A Systematic Literature Review and Comparison Across Platform Types File: Selected Studies and Coding Results.
DOI: 10.6084/m9.figshare.21089953
title: model results

description: model results for fig7
DOI: 10.6084/m9.figshare.21089953.v1
title: model results

description: model results for fig7
DOI: 10.6084/m9.figshare.20101949.v4
title: Analysis of 3'UTRs in B. nonstop

description: To identify the 3'UTRs, we assembled the transcripts de novo using Trinity (https://doi.org/10.1038/nprot.2013.084) with both standard and 3'enriched transcriptomic reads. Then we mapped transcripts back to the genome using BLAST and chose those transcripts that were identical to the genome but had one or more of A at the 3' end of the transcript and analysed them using custom Python scripts.
DOI: 10.48420/21076921
title: Research data for "An analytic linear vibronic coupling method for first-principles spin-dynamics calculations in single-molecule magnets"

description: All research data for the paper "An analytic linear vibronic coupling method for first-principles spin-dynamics calculations in single-molecule magnets". <br> Contains: atomic coordinates, spin-phonon coupling parameters, input/output files for calculations.
DOI: 10.48420/21076921.v1
title: Research data for "An analytic linear vibronic coupling method for first-principles spin-dynamics calculations in single-molecule magnets"

description: All research data for the paper "An analytic linear vibronic coupling method for first-principles spin-dynamics calculations in single-molecule magnets". <br> Contains: atomic coordinates, spin-phonon coupling parameters, input/output files for calculations.
DOI: 10.34740/kaggle/dsv/4198703
title: COVID Vaccination in World (updated daily)
DOI: 10.5281/zenodo.6616542
title: Data to publication "The performance of deep generative models for learning joint embeddings of single-cell multi-omics data"

description: Joint embedding data to publication "The performance of deep generative models for learning joint embeddings of single-cell multi-omics data" Code available at https://github.com/MTreppner/multiomics_dgms
DOI: 10.5281/zenodo.6616543
title: Data to publication "The performance of deep generative models for learning joint embeddings of single-cell multi-omics data"

description: Joint embedding data to publication "The performance of deep generative models for learning joint embeddings of single-cell multi-omics data" Code available at https://github.com/MTreppner/multiomics_dgms
DOI: 10.5281/zenodo.7075287
title: Data to publication "The performance of deep generative models for learning joint embeddings of single-cell multi-omics data"

description: Joint embedding data to publication "The performance of deep generative models for learning joint embeddings of single-cell multi-omics data" Code available at https://github.com/MTreppner/multiomics_dgms
DOI: 10.6084/m9.figshare.20101949.v5
title: Analysis of 3'UTRs in B. nonstop

description: To identify the 3'UTRs, we assembled the transcripts de novo using Trinity (https://doi.org/10.1038/nprot.2013.084) with both standard and 3'enriched transcriptomic reads. Then we mapped transcripts back to the genome using BLAST and chose those transcripts that were identical to the genome but had one or more of A at the 3' end of the transcript and analysed them using custom Python scripts.
DOI: 10.5281/zenodo.7075305
title: Proteomic analysis

description: Proteomic analysis of lyophilized extracellular vesicles and skeletal muscles.
DOI: 10.5281/zenodo.7075304
title: Proteomic analysis

description: Proteomic analysis of lyophilized extracellular vesicles and skeletal muscles.
DOI: 10.5517/ccdc.csd.cc28xykq
title: CCDC 2113194: Experimental Crystal Structure Determination

description: Related Article: Arpine Vardanyan, Sebastian Boldt, Alexander Villinger, Peter Ehlers, Peter Langer|2022|J.Org.Chem.|87|11296|doi:10.1021/acs.joc.1c02394
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b057s
title: CCDC 2145114: Experimental Crystal Structure Determination

description: Related Article: Ruizhi Lai|2022|CSD Communication|||
description: Related Article: Yuerong Wang, Qingyao Zhang, Yingdi Hao, Cankun Luo, Xin Huang, Li Guo, Yong Wu|2022|Organometallics|41|2494|doi:10.1021/acs.organomet.2c00325
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bdzmc
title: CCDC 2157433: Experimental Crystal Structure Determination

description: Related Article: Min Zeng, Ze-Yang Zhou, Xue-Ru Wu, Cai-Ming Liu, Hui-Zhong Kou|2022|Inorg.Chem.|61|14275|doi:10.1021/acs.inorgchem.2c01822
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.21227/dn9v-3278
title: SCVIC-CIDS-2022: Bridging Networks and Hosts via Machine Learning-Based Intrusion Detection

description: SCVIC-CIDS-2021 was created using the raw data in CIC-IDS-2018*, while SCVIC-CIDS-2022 is formed from NDSec-1** meta-data by following the similar procedure in Section *Sharafaldin, I.; Habibi Lashkari, A. and Ghorbani, A. (2018). Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization. In Proceedings of the 4th International Conference on Information Systems Security and Privacy - ICISSP, ISBN 978-989-758-282-0; ISSN 2184-4356, pages 108-116. DOI: 10.5220/0006639801080116**Beer, F., Hofer, T., Karimi, D. & Bühler, U., (2017). A new Attack Composition for Network Security. In: Müller, P., Neumair, B., Raiser, H. & Dreo Rodosek, G. (Hrsg.), 10. DFN-Forum Kommunikationstechnologien. Bonn: Gesellschaft für Informatik e.V.. (S. 11-20).
DOI: 10.6084/m9.figshare.21090223
title: palythoa_grandiflora_zanfona_1.fasta.gz

description: .......
DOI: 10.6084/m9.figshare.21090223.v1
title: palythoa_grandiflora_zanfona_1.fasta.gz

description: .......
DOI: 10.5281/zenodo.7003068
title: Research data for "Indirect learning and physically guided validation of interatomic potential models"

description: This dataset contains structural data, potential parameter files, and data shown in the plots for the publication "Indirect learning and physically guided validation of interatomic potential models". Details of the contents can be found in README.txt.
DOI: 10.5281/zenodo.7003067
title: Research data for "Indirect learning and physically guided validation of interatomic potential models"

description: This dataset contains structural data, potential parameter files, and data shown in the plots for the publication "Indirect learning and physically guided validation of interatomic potential models". Details of the contents can be found in README.txt.
DOI: 10.25387/g3.19326374
title: Supplemental Material for Vranic et al., 2022

description: DE_dataset_Vranic_et_al.xlsx contains expression profiles of wheat transcripts during an infection with five fungal diseases (Fusarium head blight, Fusarium crown rot, Septoria tritici blotch, stripe rust, powdery mildew. Only the data of high confidence wheat genes were retained (FDR &lt; 0.05; -1 ≥ Log2 Fold Change ≥1). The source of the raw counts and a methodology of the differential expression analysis are described in Benbow et al. (2019) https://doi.org/10.1534/g3.119.400444.
DOI: 10.25387/g3.19326374.v1
title: Supplemental Material for Vranic et al., 2022

description: DE_dataset_Vranic_et_al.xlsx contains expression profiles of wheat transcripts during an infection with five fungal diseases (Fusarium head blight, Fusarium crown rot, Septoria tritici blotch, stripe rust, powdery mildew. Only the data of high confidence wheat genes were retained (FDR &lt; 0.05; -1 ≥ Log2 Fold Change ≥1). The source of the raw counts and a methodology of the differential expression analysis are described in Benbow et al. (2019) https://doi.org/10.1534/g3.119.400444.
DOI: 10.17172/nomad/2022.09.09-5
title: NOMAD dataset: NaxMn0.75Ni0.25-yMgyO2
DOI: 10.25824/redu/72q3t6
title: File 7 – Release Profile.docx
DOI: 10.25824/redu/a1pt6x
title: File 9 – Static in vitro digestibility.docx
DOI: 10.25824/redu/dtjhph
title: File 3B – pH values stability – Mass.docx
DOI: 10.25824/redu/etqbg6
title: File 6 – Fourier transform infrared spectroscopy (FTIR).docx
DOI: 10.25824/redu/evqmjw
title: File 2 – Mechanical Properties.docx
DOI: 10.25824/redu/ijjqwi
title: File 5 – Scanning electron microscopy (SEM).docx
DOI: 10.25824/redu/grott1
title: File 3A – pH values stability – Diameter.docx
DOI: 10.25824/redu/8tlxz2
title: File 8 – Adjustment profile.docx
DOI: 10.25824/redu/ozvzzc
title: File 1 – Zeta potential.docx
DOI: 10.25824/redu/1nttkc
title: File 4 – Encapsulation efficiency.docx
DOI: 10.25824/redu/1kovbw
title: Effect of ionotropic gelation and electrostatic complexation on the modulation of the properties of sodium alginate-chitosan hydrogels

description: Zeta potential metadata, mechanical properties, pH values ​​stability, encapsulation efficiency, scanning electron microscopy, fourier transform infrared spectra, release profile, adjustment profile and static in vitro digestibility of alginate hydrogels produced by ionotropic gelation and electrostatic complexation.
DOI: 10.21227/njyt-t438
title: Mobile Sensor Dataset for Human Activity Classification used in Forensics

description: Roughly 16 million mobile devices are available with the majority of the population worldwide and this number going to increase exponentially. Many mobile devices do include sensors and hence can be used for other applications rather than mobile gaming. In the present work, we have collected mobile sensor data for 11 classes. Each class of data is gathered with a child or adult person performing different activities during the day or recreating the scenario of different crimes.
DOI: 10.14457/tu.the.2021.561
title: Understanding determinants and behavioral influences of carpooling adoption for educational trips in Thailand

description: Carpooling is emerging as a more appealing “sharing economy” form with promising benefits in reducing carbon emissions, traveling costs, and traffic congestion. However, a thorough understanding of carpooling adoption for commuting trips is lacking for policymakers and transport planners in developing countries due to limited scientific research, specifically in Southeast Asia. Therefore, the present study aimed to understand the determinants and behavioral influence of carpool adoption for tertiary educational trips in Thailand by conducting a multivariate analysis on a dataset of 307 observations gathered at Thammasat University, Pathum Thani, Thailand. A conceptual model was developed primarily based on the Consumer Acceptance and Use of Information Technology (UTAUT2) model with modifications of replacing habit construct with perceived safety and adding two additional constructs related to COVID-19 and time credits. The sample data were analyzed using Structural Equation Modelling (SEM). It was found that hedonic motivation, social influence, and time credit factors play statistically significant roles in the intention to use carpool for tertiary educational trips, while effort expectancy, perceived safety, and perception towards COVID-19 and carpool do not. Further, hedonic motivation mediates the effect of social influence and effort expectancy. Through multigroup analysis, it was identified that hedonic motivation and time credits factors are highly significant for motorized mode users compared to active mode users. Furthermore, SEM with interaction terms revealed that social influence and time credits factors could be used to attract people who drive cars towards carpooling even though they are less inclined to carpool. Also, hedonic motivation and social influence factors can be used to attract people who live closer to their school. Upon analysis of the findings, policy implications are presented that can be used to improve carpooling adoption for educational trips in Thailand.
DOI: 10.14457/tu.the.2021.562
title: A comparative study of fuzzy multi-objective investment project portfolio selection and optimization based on financial return and different risk measurements

description: Competitiveness in global market is getting more intense. Due to resource and budget constraints, firms need to achieve their expected goals and satisfy all investment constraints under uncertainty within these limitations. Selecting the set of projects among other candidates to get the most efficient portfolio requires a lot of attention from the Decision Makers (DMs) as this consideration no longer relies purely on the financial term. This problem becomes a multi-objective problem under uncertainty where the financial return and risk from uncertainty are required into the trading off consideration. Due to the financial uncertainty, the chance-constrained programming has been employed in this study for defuzzifying and solving uncertain optimization problems at a specified confidence level that is defined by the DMs. This multi-objective project portfolio selection is to optimize the return maximization and risk minimization simultaneously. Various kinds of risk measures, Lower-Semi Variance Index (LSVI), the absolute deviation with the expected Fuzzy Net Present Value (FNPV), and the absolute mean-Conditional Value at Risk (CVaR) gap are provided in the selection of risk measures to show their differences in characteristics and performances in the obtained results. Since, such problems can consist of many project candidates and complex constraints, which may grow beyond the application of the exact optimization approach, a meta-heuristic method, Genetic Algorithm (GA), is introduced to optimize this problem through designing and constructing a decision support tool for the investment portfolio selection and optimization. The applicability of the proposed comparative approach and the constructed tool are illustrated through examples.
DOI: 10.14457/tu.the.2021.563
title: Smart shoe for predicting knee abduction moment

description: This research aims to develop a smart shoe to measure a knee abduction moment (KAM) while walking. Previous research shows that activities with the high KAM are re- lated to create the future knee pain in elders. Various kinds of floors propose to reduce the risk of osteoarthritis and injury of falls in elderly persons. KAM is a factor in determining a supporting property of the floor, and it is usually measured from the optical tracking sys- tem and force plate in the laboratory that can not be moved. To overcome above issue, our research proposes a smart shoe with a portable sensor to estimate KAM in an open environ- ment. The smart shoe consists of an inertial measurement unit (IMU) sensor and six force sensors connected to the microcontroller to collect forces and kinematic data while walking. Then, a multi-layer perceptron regressor (MLP Regressor) model issue for predicting KAM. The two steps are used for this purpose. The first step is to predict the maximum KAM from the stance phase. The second step is to predict the KAM in a full human gait cycle. Finally, The proposed shoe can estimate the peak KAM with an accuracy of 86.95 percent at the stance phase and 94.3336 percent of the full human gait cycle compared to the actual KAM measured in the laboratory.