cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7933206
title: SQAT v1_0: dataset of validation sounds

description: Dataset of test sounds used to verify the psychoacoustic metrics implemented in the first release of the sound quality analysis toolbox (SQAT), version 1.0. In order to reproduce the verification codes in the &lt;validation&gt; folder of SQAT, this repository of test sounds needs to be downloaded and the paste &lt;validation_SQAT_v1_0&gt; has to be included in the &lt;sound_files&gt; folder of the toolbox.
DOI: 10.5281/zenodo.7933205
title: SQAT v1_0: dataset of validation sounds

description: Dataset of test sounds used to verify the psychoacoustic metrics implemented in the first release of the sound quality analysis toolbox (SQAT), version 1.0. In order to reproduce the verification codes in the &lt;validation&gt; folder of SQAT, this repository of test sounds needs to be downloaded and the paste &lt;validation_SQAT_v1_0&gt; has to be included in the &lt;sound_files&gt; folder of the toolbox.
DOI: 10.5281/zenodo.7645529
title: FRGMRC - FIRST Radio Galaxy Morphology Reference Catalogue

description: FRGMRC - FIRST Radio Galaxy Morphology Reference Catalogue - Version 1.0 Brand et al. 2023 - https://ui.adsabs.harvard.edu/abs/2023MNRAS.522..292B/abstract
DOI: 10.5281/zenodo.7645530
title: FRGMRC - FIRST Radio Galaxy Morphology Reference Catalogue

description: FRGMRC - FIRST Radio Galaxy Morphology Reference Catalogue - Version 1.0 Brand et al. 2023 - https://ui.adsabs.harvard.edu/abs/2023MNRAS.522..292B/abstract
DOI: 10.34740/kaggle/dsv/5678079
title: Yahoo Finance - Industries - Dataset
DOI: 10.5281/zenodo.7933263
title: Permeable Curbs for Storm Water Pollution

description: One of the problems that increased urbanization poses is storm water pollution. Several control measures exist that are used to treat and reduce pollution in our waterways, one of those being permeable concretes; but these have not been widely adopted. The goal of this project was to develop a permeable curb apparatus that could be used in retrofitting conventional streets. The permeable curb is comprised of a permeable concrete mix with a perforated pipe running through its center, this allows for water to filter through the porous concrete and continue downstream through the perforated pipe which would eventually lead to our water ways. Project goals include determining permeable curbs pollutant removal efficiencies, and best cleaning options needed to be optimally utilized in urban environments. A test apparatus simulating a typical street profile is used in the laboratory environment to determine the percentage of solids that can be removed from the water treated for typical design rain events, the potential for clogging and fouling of the curb, and the ability to recover lost performance through cleaning the permeable curb. Results to date show that 95% solids removal is possible for up to 15 years of simulated solids loading to the curb. The diameter size range of the 5% of solids that do pass through the curb were measured to be in the range of 2 - 55 mm. Particle sizes larger than this tend to be caught within the curb and contributed eventually to curb clogging resulting in reduced hydraulic flow capacity. Cleaning cycles of the curb at a moderate backwash rate of 0.1 m<sup>3</sup> m<sup>-2­</sup> min<sup>-1</sup> did not recover solids trapped within the curb with only 7 % of the prior trapped solids removed from the curb in the cleaning process.
description: Tran-SET Project: 21PUTSA01
DOI: 10.5281/zenodo.7933262
title: Permeable Curbs for Storm Water Pollution

description: One of the problems that increased urbanization poses is storm water pollution. Several control measures exist that are used to treat and reduce pollution in our waterways, one of those being permeable concretes; but these have not been widely adopted. The goal of this project was to develop a permeable curb apparatus that could be used in retrofitting conventional streets. The permeable curb is comprised of a permeable concrete mix with a perforated pipe running through its center, this allows for water to filter through the porous concrete and continue downstream through the perforated pipe which would eventually lead to our water ways. Project goals include determining permeable curbs pollutant removal efficiencies, and best cleaning options needed to be optimally utilized in urban environments. A test apparatus simulating a typical street profile is used in the laboratory environment to determine the percentage of solids that can be removed from the water treated for typical design rain events, the potential for clogging and fouling of the curb, and the ability to recover lost performance through cleaning the permeable curb. Results to date show that 95% solids removal is possible for up to 15 years of simulated solids loading to the curb. The diameter size range of the 5% of solids that do pass through the curb were measured to be in the range of 2 - 55 mm. Particle sizes larger than this tend to be caught within the curb and contributed eventually to curb clogging resulting in reduced hydraulic flow capacity. Cleaning cycles of the curb at a moderate backwash rate of 0.1 m<sup>3</sup> m<sup>-2­</sup> min<sup>-1</sup> did not recover solids trapped within the curb with only 7 % of the prior trapped solids removed from the curb in the cleaning process.
description: Tran-SET Project: 21PUTSA01
DOI: 10.21227/85qd-gc45
title: Supplementary video for paper 22-TIE-4910 submitted to IEEE Transactions on Industrial Electronics

description: Legged robots have demonstrated high potential when dealing with rough terrain, for which an efficient motion planner becomes crucial. This paper presents a novel approach for quadrupedal robot motion planning on rough terrain, which is both conceptually straightforward and computationally efficient. Implementing the concept of workspace constitutes the cornerstone of this method: both body poses and swing-leg footholds are chosen within their corresponding workspace. A novel approach called "cross-diagonal method'' is developed to facilitate the search for new body poses. Based on the obtained body pose, the foothold for a swing leg selected within its foot workspace satisfies the reachability constraint automatically. The proposed motion planning scheme is integrated with an elevation mapping module and a state estimation module, enabling quadrupedal robots to travel through uneven terrains with high efficiency. The significance of this work is validated through simulation and physical experiments with a quadrupedal robot, which achieves high success rates in overcoming difficult terrains without prior knowledge of the environment. This approach offers advantages of high computational efficiency, simplicity, and adaptability to different types of terrains, making it a promising solution for real-world applications.
DOI: 10.5281/zenodo.7933287
title: Everest Model Output Statistics: improved wind speed forecasts

description: Data and pre-trained random forest models necessary to correct GFS forecast data and produce improved Everest Forecasts. Please find the associated code at: github.com/MaxVWDV/Everest_wind_forecast
DOI: 10.5281/zenodo.7933286
title: Everest Model Output Statistics: improved wind speed forecasts

description: Data and pre-trained random forest models necessary to correct GFS forecast data and produce improved Everest Forecasts. Please find the associated code at: github.com/MaxVWDV/Everest_wind_forecast
DOI: 10.6084/m9.figshare.22815794
title: Cyclists' exposure-network design-data-MATLAB file

description: These files includes the data and the coding that was used for this paper. The coding of the upper and lower level of the model was done in MATLAB. Before coding the algorithm and the model, a function was defined that contains the raw data that represent the numerical example (Mandl’s Network). Please note that not all the data that are presented in this file are based on the model’s network. Some of the essential data for this model was not available about the mentioned network. Hence, we assumed some of this data such as cyclists' free-flow travel time. The data is presented in the “CreatModel” function. This file consists of links’ demand, free flow travel time for each mode, the width of the link, etc. The data are specified by comments in the file. The rest of the files are as follows: “CreatSolution”: This is the INS algorithm to generate the initial network “MSA”: This file is the method of successive algorithm which is used to solve the lower-level of the model. “ObjectiveFunctions” This function consist of the formulation of the objective functions of the model “NSGA-II” This file is the main algorithm of the genetic algorithm. As can be observed from the algorithm the MSA algorithm runs then the objective function is calculated. “Mutation”: Is the coding for the mutation operator that was explained in the manuscript “Corssover_Intra_string”: As in the text the cross-over operator is presented in two parts: intra-string cross-over deals with the chromosomes at the node level. “Crosover_Inter_string”: This is the second type of cross-over which is used at the route level. “CalcCrowdingDistance”: crowding distance is a measure of how far apart solutions are in the feasible space. It is used to encourage diversity in the selected solutions, by selecting solutions that are well-spaced out and cover the feasible space. “Dominate”: A solution is dominant if it is better than other solutions in at least one objective, and not worse in any other objective. This function of the algorithm checks the solution in this term. “Non_DominateSorting”: Non-dominant solutions are solutions that are not worse than any other solution in any objective. These solutions in the Pareto front represent the trade of between objectives. To run the code one needs to run the NSGA-II function. all other functions are defined in order as a part of the NSGA-II algorithm in this coding file.
DOI: 10.6084/m9.figshare.22815794.v3
title: Cyclists' exposure-network design-data-MATLAB file

description: These files includes the data and the coding that was used for this paper. The coding of the upper and lower level of the model was done in MATLAB. Before coding the algorithm and the model, a function was defined that contains the raw data that represent the numerical example (Mandl’s Network). Please note that not all the data that are presented in this file are based on the model’s network. Some of the essential data for this model was not available about the mentioned network. Hence, we assumed some of this data such as cyclists' free-flow travel time. The data is presented in the “CreatModel” function. This file consists of links’ demand, free flow travel time for each mode, the width of the link, etc. The data are specified by comments in the file. The rest of the files are as follows: “CreatSolution”: This is the INS algorithm to generate the initial network “MSA”: This file is the method of successive algorithm which is used to solve the lower-level of the model. “ObjectiveFunctions” This function consist of the formulation of the objective functions of the model “NSGA-II” This file is the main algorithm of the genetic algorithm. As can be observed from the algorithm the MSA algorithm runs then the objective function is calculated. “Mutation”: Is the coding for the mutation operator that was explained in the manuscript “Corssover_Intra_string”: As in the text the cross-over operator is presented in two parts: intra-string cross-over deals with the chromosomes at the node level. “Crosover_Inter_string”: This is the second type of cross-over which is used at the route level. “CalcCrowdingDistance”: crowding distance is a measure of how far apart solutions are in the feasible space. It is used to encourage diversity in the selected solutions, by selecting solutions that are well-spaced out and cover the feasible space. “Dominate”: A solution is dominant if it is better than other solutions in at least one objective, and not worse in any other objective. This function of the algorithm checks the solution in this term. “Non_DominateSorting”: Non-dominant solutions are solutions that are not worse than any other solution in any objective. These solutions in the Pareto front represent the trade of between objectives. To run the code one needs to run the NSGA-II function. all other functions are defined in order as a part of the NSGA-II algorithm in this coding file.
DOI: 10.6084/m9.figshare.22815794.v2
title: Cyclists' exposure-network design-data-MATLAB file

description: This file includes the data that is used in study " Cyclists’ Exposure to Traffic-Generated Air Pollution in Multi-modal Transportation Network Design Problem" <br>
DOI: 10.5281/zenodo.7933299
title: Datasets Quantum Cybersecurity

description: Dataset files
DOI: 10.5281/zenodo.7933300
title: Datasets Quantum Cybersecurity

description: Dataset files
DOI: 10.5281/zenodo.7933338
title: Datasets Quantum Cybersecurity

description: Dataset files
DOI: 10.5281/zenodo.7933317
title: COVID-19 and Traffic Safety: Exploring Exposure, Crash Frequency and Severity, and Roadway and Network Design

description: Early COVID-19 lockdowns in the first half of 2020 largely kept people at home, thereby reducing motor vehicle traffic levels. Theoretically, reduced traffic exposure should have resulted in reduced motor vehicle crashes. However, a variety of factors may have complicated this relationship. In order to better understand the impact of COVID-19 lockdowns on traffic safety outcomes, we explore fatalities, injuries, and total crashes before and during the lockdowns on both the national and state levels. We provide descriptive statistics and create negative binomial regressions exploring the role of vehicle, user, and built environment factors on traffic safety outcomes. Findings suggest that crash counts in Region 6 were 35%-50% lower in 2020 during the COVID-19 lockdowns. Crashes that occurred during the COVID-19 lockdowns were more likely to be more severe. Fatal pedestrian crashes across the U.S. decreased during COVID-19 (although not as much as overall fatal crashes) and fatal bicyclist crash counts increased. Drunk drivers were less prevalent in nationwide fatalities but more prevalent in overall Region 6 crashes. Overall, crashes were more likely single-vehicle fixed-object or rollover crashes involving unsafe speeds. In Texas, suburban areas saw the most crashes before and during COVID-19, although they also saw the greatest decrease. Rural Texas crashes were most likely to result in a fatality or serious injury, and that likelihood got worse during the COVID-19 lockdowns. While Texas freeways and arterials saw the largest decreases in crash counts, these functional classifications still had the most crashes. Urban interstates and rural local roads in Texas were notable because these two functional classifications actually saw increases in the number of fatal and serious injury crashes during COVID-19 lockdowns.
description: Tran-SET Project: 21SAUNM02
DOI: 10.5281/zenodo.7933316
title: COVID-19 and Traffic Safety: Exploring Exposure, Crash Frequency and Severity, and Roadway and Network Design

description: Early COVID-19 lockdowns in the first half of 2020 largely kept people at home, thereby reducing motor vehicle traffic levels. Theoretically, reduced traffic exposure should have resulted in reduced motor vehicle crashes. However, a variety of factors may have complicated this relationship. In order to better understand the impact of COVID-19 lockdowns on traffic safety outcomes, we explore fatalities, injuries, and total crashes before and during the lockdowns on both the national and state levels. We provide descriptive statistics and create negative binomial regressions exploring the role of vehicle, user, and built environment factors on traffic safety outcomes. Findings suggest that crash counts in Region 6 were 35%-50% lower in 2020 during the COVID-19 lockdowns. Crashes that occurred during the COVID-19 lockdowns were more likely to be more severe. Fatal pedestrian crashes across the U.S. decreased during COVID-19 (although not as much as overall fatal crashes) and fatal bicyclist crash counts increased. Drunk drivers were less prevalent in nationwide fatalities but more prevalent in overall Region 6 crashes. Overall, crashes were more likely single-vehicle fixed-object or rollover crashes involving unsafe speeds. In Texas, suburban areas saw the most crashes before and during COVID-19, although they also saw the greatest decrease. Rural Texas crashes were most likely to result in a fatality or serious injury, and that likelihood got worse during the COVID-19 lockdowns. While Texas freeways and arterials saw the largest decreases in crash counts, these functional classifications still had the most crashes. Urban interstates and rural local roads in Texas were notable because these two functional classifications actually saw increases in the number of fatal and serious injury crashes during COVID-19 lockdowns.
description: Tran-SET Project: 21SAUNM02
DOI: 10.25345/c5cz32f7r
title: MassIVE MSV000091935 - Hyal-1 inhibitors from Phyllanthus muellerianus
title: Hyal-1 inhibition data from extracts of Phyllanthus
DOI: 10.5281/zenodo.7933034
title: narcissus_pseudonarcissus_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7933033
title: narcissus_pseudonarcissus_spades_01.fasta.gz

description: .
DOI: 10.34740/kaggle/dsv/5678374
title: Balochi Language to English Translation Dataset
DOI: 10.5281/zenodo.7794741
title: Dataset for Energy Resource Management Considering Participation in the Wholesale Day-Ahead Market

description: This release is associated with a paper entitled "A Novel Framework for the Day-Ahead Market Clearing Process Featuring the Participation of Distribution System Operators and a Hybrid Pricing Mechanism". In this document, we provide the mathematical manipulation employed to linearize an MPEC problem that models the market-clearing process considering the participation of generation companies and distribution operators in the day-ahead market. Additionally, we provide a numerical example of the pricing mechanism designed for solving the optimization problem. Finally, we include information regarding the transmission and distribution power systems adopted to present the results shown in the paper. These systems are modified versions of the IEEE 14-bus and the IEEE 34-bus, respectively. Three renewable non-dispatchable generators were added to the original 14-bus system, while 5 dispatchable generators and 3 non-dispatchable generators were added to the distribution system. 13 load shapes were considered as well as 5 scenarios for each uncertain variable (wind velocity, solar irradiance, distribution load oscillation, and transmission load oscillation). The data regarding the costs and physical parameters of each of the power system's elements are provided in this document.
DOI: 10.5281/zenodo.7794742
title: Dataset for Energy Resource Management Considering Participation in the Wholesale Day-Ahead Market

description: This release is associated with a paper entitled "A Novel Bilevel Programming Formulation for Optimizing the Interaction of Distribution System Operators and GENCOs in Day-Ahead Markets". In this document, we provide the mathematical manipulation employed to linearize an MPEC problem that models the market-clearing process considering the participation of generation companies and distribution operators in the day-ahead market. Additionally, we provide a numerical example of the pricing mechanism designed for solving the optimization problem. Finally, we include information regarding the transmission and distribution power systems adopted to present the results shown in the paper. These systems are modified versions of the IEEE 14-bus and the IEEE 34-bus, respectively. Three renewable non-dispatchable generators were added to the original 14-bus system, while 5 dispatchable generators and 3 non-dispatchable generators were added to the distribution system. 13 load shapes were considered as well as 5 scenarios for each uncertain variable (wind velocity, solar irradiance, distribution load oscillation, and transmission load oscillation). The data regarding the costs and physical parameters of each of the power system's elements are provided in this document.
DOI: 10.5281/zenodo.7933365
title: Dataset for Energy Resource Management Considering Participation in the Wholesale Day-Ahead Market

description: This release is associated with a paper entitled "A Novel Framework for the Day-Ahead Market Clearing Process Featuring the Participation of Distribution System Operators and a Hybrid Pricing Mechanism". In this document, we provide the mathematical manipulation employed to linearize an MPEC problem that models the market-clearing process considering the participation of generation companies and distribution operators in the day-ahead market. Additionally, we provide a numerical example of the pricing mechanism designed for solving the optimization problem. Finally, we include information regarding the transmission and distribution power systems adopted to present the results shown in the paper. These systems are modified versions of the IEEE 14-bus and the IEEE 34-bus, respectively. Three renewable non-dispatchable generators were added to the original 14-bus system, while 5 dispatchable generators and 3 non-dispatchable generators were added to the distribution system. 13 load shapes were considered as well as 5 scenarios for each uncertain variable (wind velocity, solar irradiance, distribution load oscillation, and transmission load oscillation). The data regarding the costs and physical parameters of each of the power system's elements are provided in this document.
DOI: 10.5281/zenodo.7933375
title: Coupled Situational Awareness System to Improve Transportation Infrastructure Performance during Extreme Events

description: The dense road networks and numerous low water crossings throughout Texas may be contributing to the higher recurrence rates of floods that pose a danger to vehicles. A timely issue that should be addressed by researchers is the compounding of disaster. Flooding can be combined with other life-threatening occurrences such as power loss and interruptions of health and emergency services. During these events, rescue requests from the stranded communities overwhelm the emergency response facilities; impassable roadways and the paucity of reliable information on the affected areas and their accessibility hamper emergency response operations, causing several detours and delays that put both the responders and evacuees at risk. This research presents a framework for improved situational awareness during extreme flooding events by combing a flood inundation model with transportation infrastructure performance assessment. The flood inundation model can be driven by real-time radar rainfall data in an efficient manner. The road network work model can use land use, census data, and locations of critical facilities in combination with spatial analysis. The proposed framework is demonstrated on a small catchment in San Antonio, Texas. The study includes the following tasks: literature review, vehicle-related flood fatality analysis, review of flood warning systems in Texas, and the proposed framework of a road flooding forecasting system that can predict land surface flooding in detail and the impacts on the road network and provide information on the spatial and temporal evolution of road network access during flooding events. It is recommended that the framework be used for identifying the transportation network-wide impacts of flood ‘hot-spots’ and assessment of transportation-related flood mitigation alternatives. The framework can also support disaster planning and emergency preparedness measures in preparation for major events. Examples may include contingency planning for deployment of barricades, mitigation of critical facilities, and large-scale evacuation planning. The methodology can provide useful outputs on system-wide costs of flooded roads that can be used to inform regional mitigation efforts.
description: Tran-SET Project: 21SATUTSA02