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35 results for “State-of-the-Art”
State-of-the-art review of near-term freshwater forecasting literature published between 2017 and 2022
This data publication includes code and results from a systematic literature review on the current state of near-term forecasting of freshwater quality. The review aimed to address the following questions: (1) Freshwater variables, scales, models, and skill: Which freshwater variables and temporal scales are most commonly targeted for near-term forecasts, and what modeling methods are most commonly employed to develop these forecasts? How is the accuracy of freshwater quality forecasts assessed, and how accurate are they? How is uncertainty typically incorporated into water quality forecast output? (2) Forecast infrastructure and workflows: Are iterative, automated workflows commonly employed in near-term freshwater quality forecasting? How are forecasts validated and archived? (3) Human dimensions: What is the stated motivation for development of most near-term freshwater quality forecasts, and who are the most common end users (if any)? How are end users engaged in forecast development? An initial search was conducted for published papers presenting freshwater quality forecasts from 1 January 2017 to 17 February 2022 in the Web of Science Core Collection. Results were subsequently analyzed in three stages. First, paper titles were screened for relevance. Second, an initial screen was conducted to assess whether each paper presented a near-term freshwater quality forecast. Third, papers that passed the initial screen were analyzed using a standardized matrix to assess the state of near-term freshwater quality forecasting and identify areas of recent progress and ongoing challenges. Additional details regarding the systematic literature search and review are presented in the Methods section of the metadata.
Datenaufbereitung zum State-of-the-Art und Fortschritt europäischer Gaia-X sowie Datenraum Initiativen mit einem Schwerpunkt auf Industrie 4.0 Anwendungsfälle
<p><span>In seiner Gesamtheit umfasst der Datensatz eine Sammlung von Initiativen und Projekten, die mit </span><span>Gaia-X sowie Data Spaces im Allgemeinen in Verbindung stehen</span><span>.</span> Ziel der Datensammlung war es, eine detaillierte Übersicht über bestehende Projekte zu erhalten und diese systematisch zu kategorisieren, um anschließend spezifische industrielle Anwendungsfälle herauszuarbeiten und diese zu analysieren. Der Zeitraum dieser Sammlung erstreckte sich von April 2023 bis März 2024. Anzumerken ist, dass sämtliche zur Verfügung stehenden Informationen innerhalb dieses Zeitraums in den Datensatz aufgenommen wurden. Ab März 2024 wurden keine weiteren Daten erfasst, wodurch der Datensatz den aktuellen Stand bis zu diesem Zeitpunkt widerspiegelt.</p> <p>Insgesamt wurden 211 Initiativen aus 281 Quellen zusammengetragen und ausgewertet. Diese unterteilen sich (über alle Domänen hinweg) in 102 Data Spaces und 93 Anwendungsfälle. Die 93 Anwendungsfälle beinhalten 47 Industrie 4.0 relevante Anwendungsfälle.</p>
A recent overview of the state-of-the-art elements of text classification - dataset
<p>The two available datasets were used to conduct the quantitative analysis of the text classification area. The set, such as:</p> <ol> <li>biblio.bib contains all articles that are grouped in categories</li> <li>biblio.csv contains processed records from biblio.bib, based on it were built the statistics presented in the article</li> </ol>
Desk research of 107 case studies on state-of-the-art of cultural tourism interventions
<p>The aim of Work Package 3 of the SmartCulTour project (<a href="http://www.smartcultour.eu">www.smartcultour.eu</a>) is to provide a state-of-the-art overview of cultural tourism interventions implemented in European cities and regions, thereby identifying best practices and the impacts and success conditions of cultural tourism interventions. To this end, the consortium identified 107 interesting cultural tourism interventions throughout Europe, with a <strong>geographical coverage</strong> of: Belgium (9), Italy (8), The Netherlands (8), Serbia (7), Romania (6), Croatia (5), Hungary (4), Portugal (4), Spain (4), United Kingdom (4), Finland (3), France (3), Sweden (3), Other countries (24), Multiple countries (15). The "Overview and taxonomy of 107 interventions" lists every intervention that was studied, as well as their respective classification given, based on the description and objective of the intervention. Within this table, a value of "1" is its primary categorization, with a value of "2" assigned to a secondary taxonomy. Each intervention can have multiple purposes and therefore belong to different categories.The taxonomy of cultural tourism interventions is further described in "State of the art of cultural tourism interventions" (DOI: 10.5281/zenodo.5270321).</p> <p>The 107 cultural tourism interventions were analyzed via desk research only during the period September 2020-January 2021, based on available secondary data and following a standardized <strong>data collection form</strong>. This form is included here as "Internal data collection form used for analysis". The forms collect data on:</p> <ul> <li>Context and background information;</li> <li>The 'reason why' of the intervention;</li> <li>The intervention;</li> <li>Resources and tools necessary to design and implement the interventions;</li> <li>Impacts (expected, perceived and measured);</li> <li>(Perceived) success conditions and limiting factors.</li> </ul> <p>The zip-file "Internal forms of 107 interventions" contains all 107 completed data collection forms.</p> <p> </p>
A "short blanket" dilemma for a state-of-the-art neural network potential for water: Reproducing experimental properties or the underlying many-body physics?
<p>Deep neural network (DNN) potentials have recently gained popularity in computer simulations of a wide range of molecular systems, from liquids to materials.<br> In this study, we explore the possibility of combining the computational efficiency of the DeePMD framework and the demonstrated accuracy of the MB-pol data-driven many-body potential to train a DNN potential for large-scale simulations of water across its phase diagram.<br> We find that the DNN potential is able to reliably reproduce the MB-pol results for liquid water but provides a less accurate description of the vapor-liquid equilibrium properties.<br> This shortcoming is traced back to the inability of the DNN potential to correctly represent many-body interactions.<br> An attempt to explicitly include information about many-body effects results in a new DNN potential that exhibits the opposite performance, being able to correctly reproduce the MB-pol vapor-liquid equilibrium properties but losing accuracy in the description of the liquid properties.<br> These results suggest that DeePMD-based DNN potentials are not able to correctly "learn" and, consequently, represent many-body interactions, which implies that DNN potentials may have limited ability to predict properties for state points that are not explicitly included in the training process.<br> The computational efficiency of the DeePMD framework can still be exploited to train DNN potentials on data-driven many-body potentials, which can thus enable large-scale, "chemically accurate" simulations of various molecular systems, with the caveat that the target state points must have been adequately sampled by the reference data-driven many-body potential in order to guarantee a faithful representation of the associated properties.</p>
Asymmetry of AMOC Hysteresis in a State-of-the-Art Global Climate Model
<p>These directories contain Python (v3) scripts for plotting/analysing model output.</p> <p>Python scripts can be found in the directory 'Program'. Model output can be found in the directory 'Data'.</p> <p>The processed model output are stored as NETCDF files and using the relevant scripts one can regenerate all the figures. We provided the original model output (native grid) and is only converted to yearly-averaged data (due to storage limitations). Some scripts (e.g., FOV_index.py and AMOC_transport.py) use the original model output and running these script generates in the time series, which are presented in the manuscript.</p>
3D printed biomedical devices and their applications: A review on state-of-the-art technologies, existing challenges, and future perspectives
<p>This repository consists of the data that have been utilized to imagine and subsequently construct Fig. 1, Fig. 3 , Fig. 5 , Fig. 6 and Fig. 7 of the article " H. B. Mamo, M. Adamiak and A. Kunwar. 3D printed biomedical devices and their applications: A review on state-of-the-art technologies, existing challenges, and future perspectives, Journal of the Mechanical Behavior of Biomedical Materials, 143 (2023) 105930. doi: 10.1016/j.jmbbm.2023.105930 ".</p> <p> Brief introduction of the files contained in this repository</p> <ol> <li> acronyms.csv: This file consists of the list of acronyms associated with materials and techniques used in 3D printing of biomedical devices.</li> <li>fig1a-data.csv: The csv file provides a relative ranking of different types of 3D printing techniques for biomedical applications based upon merits and limitations (wherever applicable). The technique listed as Rank 1 is considered as the most commonly used 3D printing procedure.</li> <li> fig1b-data.csv: The csv file enlists the benfits of the 3D printing techniques in biomedical applications as compared to subtractive manufacturing methods.</li> <li> fig3-data.csv: The file contains a comparison between conventional and customized tablet printing methods. The illustration is made through the manufacturing or printing of pharmaceutical tablets or pills. This illustation also applies to the production of pharmaceutical capsules. It thus illustrates that customized medicine is enabled using 3D printing technology.</li> <li> fig5-data.csv: This file enumerates the major challenges associated with 3D printing of biomedical devices.</li> <li> fig6-data.csv: The file enlists the roles of wearable smarts, cloud-based platforms and physicians in context of the hospitals implementing IoMT.</li> <li> fig7-data.csv: The aspects of IoMT Sensors,IoMT Platforms,3D Printers,Design and Prototypes within the integrated 3D printing-IoMT ecosystem are listed in the file.</li> </ol>
In-depth analysis of 18 case studies on state-of-the-art of cultural tourism interventions
<p>The aim of Work Package 3 of the SmartCulTour project (<a href="http://www.smartcultour.eu">www.smartcultour.eu</a>) is to provide a state-of-the-art overview of cultural tourism interventions implemented in European cities and regions, thereby identifying best practices and the impacts and success conditions of cultural tourism interventions. Based on the previous, desk-researched 107 interesting cultural tourism interventions see "Desk research of 107 case studies on state-of-the-art of cultural tourism interventions", DOI: 10.5281/zenodo.5213017 ), a further 18 interventions were selected for in-depth analysis.</p> <p>These 18 cultural tourism interventions were analyzed via a series of expert interviews, combined with document and literature analysis, performed in the period January 2021-March 2021. Description of the case studies follows a standardized <strong>case study data collection form</strong>. This form is included here as "Case study data collection form". The form collect data on:</p> <ul> <li>Context and background information;</li> <li>The 'reason why' of the intervention;</li> <li>The intervention;</li> <li>Resources and tools necessary to design and implement the interventions;</li> <li>Impacts (expected, perceived and measured);</li> <li>(Perceived) success conditions and limiting factors.</li> </ul> <p>The semi-structured interviews left some room for adaptability depending on the case studies. A <strong>general guide on potential interview questions</strong> is included here as "Potential questions list for case study interviews".</p> <p>All case studies are included as individual odt-files, starting with "detailed case study + name of the intervention".</p>
Literature Search from SECURE Deliverable 1.1: STATE-OF-THE-ART on Research Career Frameworks
<p>SECURE Deliverable 1.1: STATE-OF-THE-ART on Research Career Frameworks (<a title="SECURE Deliverable 1.1: STATE-OF-THE-ART on Research Career Frameworks" href="../doi/10.5281/zenodo.10066374">https://zenodo.org/doi/10.5281/zenodo.10066374</a>) included a State-of-the-Art on existing literature and recommendations related to research career frameworks (RCFs) and focusing on recruitment and working conditions for researchers, career development and progression for researchers, and interinstitutional (between academic institutions), intersectoral (across sectors), and international (across countries) mobility.</p> <p>The literature review data for is available as:</p> <ul> <li>an online library on Zotero - <a href="https://www.zotero.org/groups/5436703/secure_project_library/library">https://www.zotero.org/groups/5436703/secure_project_library/library</a></li> <li>Microsoft Excel files (xlsx) and</li> <li>CSV (comma-separated values) files.</li> </ul> <p>The selected literature is separated into the following headings:</p> <ul> <li>Career Development and Progression for Researchers</li> <li>Interinstitutional, Intersectoral, and International Mobility</li> <li>Recruitment and Employment Conditions for Researchers</li> <li>Research Career Frameworks</li> </ul>
Literature Search from SECURE Deliverable 1.2: STATE-OF-THE-ART on Tenure Track-Like Models
<p>SECURE Deliverable 1.2: STATE-OF-THE-ART on Tenure Track-Like Models (<a title="SECURE Deliverable 1.2: STATE-OF-THE-ART on Tenure Track-Like Models" href="https://doi.org/10.5281/zenodo.10066388">https://doi.org/10.5281/zenodo.10066388</a>) included a State-of-the-Art on Tenure Track-Like Models.</p> <p>The literature review data is available as:</p> <ul> <li>an online library on Zotero - <a href="https://www.zotero.org/groups/5436703/secure_project_library/library">https://www.zotero.org/groups/5436703/secure_project_library/library</a></li> <li>Microsoft Excel files (xlsx) and</li> <li>CSV (comma-separated values) files.</li> </ul> <p>The selected literature is separated into the following headings:</p> <ul> <li>Career development and assessment for tenure track-like models</li> <li>Overall Literature for Tenure Track-Like Model</li> <li>Review of Funding Schemes for Tenure Track-Like Models</li> <li>Review of recruitment and employment conditions for tenure track-like models</li> </ul>
The state-of-the-art machine learning model for Plasma Protein Binding Prediction: computational modeling with OCHEM and experimental validation
<p><span>Institute of Materia Medica, Chinese Academy of Medical Sciences purchased 10,000 ChemDiv databases.</span></p>
Requirements Quality Theory: State-of-the-Art
<p>This repository contains the replication package for evaluating state-of-the-art requirements quality research. Grounded in a harmonized theory of activity-based requirements quality, we assessed 57 primary studies from the research domain of requirements quality to determine which theory elements are neglected.</p>
State-of-the-Art Review on the Aspects of Martensitic Alloys Studied via Machine Learning
<p>Description</p> <p>The dataset for the review paper titled "State-of-the-Art Review on the Aspects of Martensitic Alloys Studied via Machine Learning" consists of the four files with the names (i) alloy_names.csv, (ii) machine_learning_methods.csv, (iii) nomenclature.csv, and (iv) ptmc_terminologies.csv.</p> <p><strong>(i) alloy_names.csv </strong>: This file presents the summarized list of alloys' names which have been discussed in the review paper. The list thus provides the names of the alloys for which data-driven studies have been attempted to explore one of the effects - martensitic transformation, phase transformation or shape memory effect. </p> <p><strong>(ii) machine_learning_methods.csv</strong> : The machine learning methods that have been discussed in the review paper in relation to the simulation, modeling or prediction tasks in martensitic alloys are listed in this file. This csv file conssits of three columns. The first column "Methods" lists the names of the machine learning methods whereas the second column "Purpose" briefly reveals the objective of the use of the named machine learning method. The final column "Reference" provides the information about the original work (source) from which the data is obtained. </p> <p><strong>(iii) nomenclature.csv </strong>: This file lists all of the acronyms utilized in the review paper, and provides their corresponding full forms. </p> <p><strong> (iv) ptmc_terminologies.csv</strong> : One of the major theories considered significant in the study of martensitic alloys and shape memory effects is phenomenological theory of martensite crystallography (PTMC). The review paper discusses this theory. The different concepts that might be helpful in understanding PTMC , have been assembled in the form of terminologies. </p>
Visual and visual-inertial SLAM: State-of-the-Art, Classification and Experimental Benchmarking
<p>IRSTV dataset used in the publication "Visual and visual-inertial SLAM: State-of-the-Art, Classification and Experimental Benchmarking", Myriam Servières, Valérie Renaudin, Alexis Dupuis<sup> </sup>and Nicolas Antigny<sup>,</sup> Hidawi Journal of Sensors, To be published</p>
Preprocessed Data and Pretrained Models for Zero-Shot Multi-Speaker Text-To-Speech with State-of-the-art Neural Speaker Embeddings
<p>This is preprocessed data and pretrained models from two of our papers:</p> <p>"Zero-Shot Multi-Speaker Text-To-Speech with State-of-the-art Neural Speaker Embeddings," by Erica Cooper, Cheng-I Lai, Yusuke Yasuda, Fuming Fang, Xin Wang, Nanxin Chen, and Junichi Yamagishi. (ICASSP 2020)<br> <a href="https://arxiv.org/abs/1910.10838">https://arxiv.org/abs/1910.10838</a></p> <p> "Pretraining Strategies, Waveform Model Choice, and Acoustic Configurations for Multi-Speaker End-to-End Speech Synthesis," by Erica Cooper, Xin Wang, Yi Zhao, Yusuke Yasuda, and Junichi Yamagishi. (arXiv) <a href="https://arxiv.org/abs/2011.04839">https://arxiv.org/abs/2011.04839</a></p> <p>This data is meant to be used with our open-source implementation, which can be found here: https://github.com/nii-yamagishilab/multi-speaker-tacotron</p> <p>More information about the directory structure and how to use the data can be found in the READMEs on GitHub.</p>
Comparison of State-of-the-Art Reactive Auto-Scaler in 3 Different Environments
<p>We investigate the hypothesis "The scaling behavior of a standard, reactive, CPU utilization-rule-based auto-scaler depends on the environment". Hence, we implement such an auto-scaler for scaling a CPU-intensive application as a benchmark in three different environments: (i) a private Cloud, (ii) AWS EC2 and (iii) IaaS cloud of the Distributed ASCI Supercomputer 4 (DAS-4).</p>
State-of-the-art evolution models for single, binary and magnetic massive stars
<p>The Universe is threaded by magnetic fields on all scales, from planetary systems to galaxy clusters. In massive stars, they play a pivotal and multifaceted role. They are thought to be crucial in transporting angular momentum throughout the stellar interior and maintaining the overall angular-momentum budget. They may also contribute to chemical mixing, can interact with convective fluid motions and may give rise to distinct seismic signatures. For example, the spin rates of white dwarfs, neutron stars and black holes are strongly determined by the coupling of a star’s core to its envelope. In this talk, I will discuss recent progress in our understanding of how magnetic fields affect single and binary stars, and what are possible origins of the different types of magnetic fields in massive stars. In particular, I will highlight connections to observations and how these can be used to further our understanding of how magnetic fields influence the evolution and final fates of stars.</p>
DMP: Illustration of State-of-the-Art Embedding Methods for Social Networks
<p>This project aims to explore state-of-the-art network embedding methods for social network analysis, with a specific focus on link prediction. Using data from the Austrian online newspaper derStandard.at, a follow-network is constructed to represent user interactions. By applying selected network embedding algorithms to this dataset, the goal is to identify the most effective method for predicting links between users. Through this investigation, the aim is to enhance understanding of graph embedding techniques and their applicability in social network analysis tasks.</p>
Datafiles for: Benchmarking State-of-the-art DIRECT-type Methods on the BBOB Noiseless Testbed
<p>Datafiles for the paper "Benchmarking State-of-the-art DIRECT-type Methods on the BBOB Noiseless Testbed" submitted for the GECCO 2023 BBOB workshop.</p>
Dataset of Flow Velocity Prediction in Vegetated Alluvial Channels Comparing Empirical and State-of-the-art Hybrid Machine Learning Models
<p>We compiled 447 datasets from different sources and lab- and field-based measurements. These datasets included Einstein and Banks (1950), Fenzl (1962), Kouwen et al. (1969), Ree and Crow (1977), Murota (1984), Tsujimoto and Kitamura (1990), Tsujimoto (1991), Tsujimoto (1993), Shimizu (1994), Dunn et al. (1996), Ikeda and Kanazawa (1996), Meijer (1998), Jarvela (2002), Rowinski and Kubrak (2002), Stone and Shen (2002), Poggi et al. (2004), Carollo et al. (2005), and Murphy et al. (2007).</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.