cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3859594
title: When and How to Transfer Knowledge in Dynamic Multi-objective Optimization

description: This file is the output data obtained when running the experiments of the paper below: Ruan, G., Minku, L.L., Menzel, S., Sendhoff, B., Yao, X., "When and How to Transfer Knowledge in Dynamic Multi-objective Optimization," 2019 IEEE Symposium Series on Computational Intelligence (SSCI), Xiamen, China, 2019, pp. 2034-2041. Transfer learning has been used for solving multiple optimization and dynamic multi-objective optimization problems, since transfer learning is able to transfer useful information from one problem to help solving another related problem. This paper aims to investigate when and how transfer learning works or fails in dynamic multi-objective optimization. Through computational analyses on a number of dynamic bi- and tri-objective benchmark problems, we show that transfer learning fails on problems with fixed Pareto optimal solution sets and under small environmental changes. We also show that the Gaussian kernel function used in the existing transfer learning-based method is not always adequate. Therefore, transfer learning should be avoided when dealing with problems for which transfer learning fails and other kernel functions should be used when the Gaussian kernel is inadequate. This paper proposes novel strategies and kernel functions that can be used in such cases. Experimental studies have demonstrated the superiority of our proposed techniques to state-of-the-art methods, on a number of dynamic bi- and tri-objective test problems.
DOI: 10.5281/zenodo.3859497
title: Data supplement for "Bifurcations of front motion in passive and active Allen-Cahn-type equations"

description: This dataset contains the data and source files for figures 5 and 7-10 in the following publication: F. Stegemerten, S.V. Gurevich, U. Thiele <em>'Bifurcations of front motion in passive and active Allen–Cahn-type equations' </em> published in 2020 in CHAOS. Please follow the instructions given in 'Readme.txt'.
DOI: 10.5281/zenodo.3859700
title: Computational Study on Effectiveness of Knowledge Transfer in Dynamic Multi-objective Optimization

description: This file is the output data obtained when running the experiments from the paper below: Ruan, G., Minku, L., Menzel, S., Sendhoff, B., Yao., “Computational Study on Effectiveness of Knowledge Transfer in Dynamic Multi-objective Optimization” <em>2020 IEEE Congress on Evolutionary Computation</em> Transfer learning has been used for solving multiple optimization and dynamic multi-objective optimization problems, since transfer learning is believed to be able to transfer useful information from one problem instance to help solving another related problem instance. This paper aims to study how effective transfer learning is in dynamic multi-objective optimization (DMO). Through computation time analysis of transfer learning, we show that the ‘inner’ optimization problem introduced by transfer learning is very time-consuming. In order to enhance the efficiency, two alternatives are computationally investigated on a number of dynamic bi- and tri-objective test problems. Experimental results have shown that the greatly enhanced efficiency does not result in much degeneration on the performance of transfer learning. Considering the high computational cost of transfer learning, it is likely that the original purpose of using transfer learning in DMO might be negated. In other words, the computation time saved in optimization is eaten up by computationally expensive transfer learning. As a result, there is less gain than expected in the overall computational efficiency. To verify this, experiments have been conducted, regarding using computational cost of transfer learning to optimize randomly generated solutions. The results have demonstrated that the convergence and diversity of final solutions generated from the random solutions are significantly better than those generated from transferred solutions under the same total computational budget.
DOI: 10.5281/zenodo.3859701
title: Computational Study on Effectiveness of Knowledge Transfer in Dynamic Multi-objective Optimization

description: This file is the output data obtained when running the experiments from the paper below: Ruan, G., Minku, L., Menzel, S., Sendhoff, B., Yao., “Computational Study on Effectiveness of Knowledge Transfer in Dynamic Multi-objective Optimization” <em>2020 IEEE Congress on Evolutionary Computation</em> Transfer learning has been used for solving multiple optimization and dynamic multi-objective optimization problems, since transfer learning is believed to be able to transfer useful information from one problem instance to help solving another related problem instance. This paper aims to study how effective transfer learning is in dynamic multi-objective optimization (DMO). Through computation time analysis of transfer learning, we show that the ‘inner’ optimization problem introduced by transfer learning is very time-consuming. In order to enhance the efficiency, two alternatives are computationally investigated on a number of dynamic bi- and tri-objective test problems. Experimental results have shown that the greatly enhanced efficiency does not result in much degeneration on the performance of transfer learning. Considering the high computational cost of transfer learning, it is likely that the original purpose of using transfer learning in DMO might be negated. In other words, the computation time saved in optimization is eaten up by computationally expensive transfer learning. As a result, there is less gain than expected in the overall computational efficiency. To verify this, experiments have been conducted, regarding using computational cost of transfer learning to optimize randomly generated solutions. The results have demonstrated that the convergence and diversity of final solutions generated from the random solutions are significantly better than those generated from transferred solutions under the same total computational budget.
DOI: 10.5281/zenodo.3860528
title: Elevation effects on air temperature in a topographically complex mountain valley in the Spanish Pyrenees

description: Data for Atmosphere Journal.
DOI: 10.5281/zenodo.3860529
title: Elevation effects on air temperature in a topographically complex mountain valley in the Spanish Pyrenees

description: Data for Atmosphere Journal.
DOI: 10.17632/4p3hpncttg.1
title: Developing&Validating Scale for context-based learning

description: Data were gathered to find out the students` learning in the context in an example of organic chemical materials that have been taught in secondary chemistry. Data shows students` wives about contextualizing learning or teaching methods during the teaching process of organic subjects in the last grade of secondary school. Two main contexts, industry and lives as contexts, were investigated and traditional instruction in besides. So, three factors were hypothesized to predict the teaching methods in which contextualizing to industry and daily life, traditional teaching. Data were described as the type like strongly agree- strongly disagree that was labelled in five choices for two academic years, between 2018-2020. Data were analyzed by using item analysis, factor analysis, reliability, and validation analysis. Item and Factor analysis were carried out by using SPSS software program. Items were retained with students` responses by analyzing some criteria such as t-value from two independent sample t-test. Six items were removed and the final version scale, including 11 items, was exploratory and confirmatory analyzed. For exploratory and confirmatory factor analysis, data were divided into two samples independently. To identify factors exploratory factor analysis was carried out. Three factors were identified and they were related to the students` learning methods of organic materials. These three factors were described as learning methods, contextualizing learning with industry, lives, and traditional learning. The three factors were confirmatory analyzed to identify the construct validity which was indicated by considering the fit indexes by using AMOS software which was supported by SPSS statistical program. All fit indexes were achieved without NFI that was the sensitive sample size. To determine the composite reliability, loadings of items and loading factors were used to calculate to find out composite reliability value. This value was acceptable. The internal reliability, Cronbach`s Alpha, was also determined for factors. Two factors related to contextualizing learning were greater than acceptable value, but the third factor that was related to traditional learning, was smaller than the acceptable value. Validation analysis was performed to predict the convergent and discriminate validity. Convergent validity was determined as applicable as a result of an appropriate method of calculation. Discriminate validity was found out as acceptable by considering correlations of factors. All fit indexes and validity values were good to fit the hypothesized model with data. According to all results, the hypothesized model was confirmed but some limitations, such as less NFI value and less reliability value of the third factor were considered. To minimize limitations, the analysis will be repeated with different and great sample size. NFI value was sensitive to the sample size so that greater 300 applicants will be questioned in the future study.
DOI: 10.25345/c53d90
title: MassIVE MSV000085471 - Comparative proteomic study of Ghiorsea bivora TAG-1.
title: Comparative proteomic study of the chemolithoautotroph Ghiorsea bivora strain TAG-1. This strain was grown under two different conditions: hydrogen-oxidizing (H2 as electron donor) and iron-oxidizing (ferrous iron as electron donor). TAG-1 was grown in microaerobic conditions.
DOI: 10.25345/c57402
title: MassIVE MSV000085469 - Proteomic Analysis of the Air-way Fluid in Lung Cancer. Detection of Periostin in Bronchoalveolar Lavage (BAL).
title: Bronchoalveolar lavage specimens collected from lung cancer patients, and analyzed using mass spectrometry-based quantitative N-glycoproteomic technique.
DOI: 10.25345/c5bx32
title: MassIVE MSV000085472 - P93 PDX Global Proteomics workflow
title: Breast cancer xenograft tissue P93 PDX global proteomics workflow
DOI: 10.5281/zenodo.3842039
title: Video classification using deep learning

description: Material accompanying the paper "Frame-by-frame annotation of video recordings using deep neural networks". Contains a selection of videos used in the paper, manual annotations, and results. Code is contained in the associated GitHub repository. See the readme for details.
DOI: 10.5281/zenodo.3842040
title: Video classification using deep learning

description: Material accompanying the paper "Frame-by-frame annotation of video recordings using deep neural networks". Contains a selection of videos used in the paper, manual annotations, and results. Code is contained in the associated GitHub repository. See the readme for details.
DOI: 10.5281/zenodo.3859936
title: Data Review Handphone Toko Online XYZ Market Place XYZ

description: Data set review Handphone di toko online di market place yang dipergunakan untuk natural language processing.
DOI: 10.5281/zenodo.3859937
title: Data Review Handphone Toko Online XYZ Market Place XYZ

description: Data set review Handphone di toko online di market place yang dipergunakan untuk natural language processing.
DOI: 10.17632/4c7x83hd64.1
title: COVID-19 related knowledge and mental health: Case of Croatia

description: This dataset refers to the data of 1244 people, aged from 18 to 72 years. Data concerns socio-demographic and epidemiological information and results to 3 questionnaires, as follows. The authors of the study used the information available on WHO website to examine knowledge about COVID-19. Eight questions were used to examine the participants knowledge about coronavirus, 5 of them were multiple choice questions and 3 questions were true/false type questions. Various types of factor and reliability analyzes were performed to see whether a linear combination of the results could be used, but the results did not support this. It was then decided to consider each question as separate, examining their relationship to the research variables. Participants were divided in two groups for each of the 8 questions according to their answers. More specifically, if a participant scored correctly on question 2, but incorrectly on question 3 he was put in the ‘informed’ group for question 2 and the ‘uninformed’ group for question 3. The The Hospital Anxiety and Depression scale (HADS) (Zigmond and Snaith, 1983:Pokrajac-Bulian et al. 2015) is divided in the Anxiety subscale and the Depression subscale. Both subscales contain 7 items. Participants were divided into three categories according to the authors. The Optimism-Pessimism scale (OPS) (Penezić,2000) was to measure positive and negative expectations of future activities outcome. This scale consists of the Optimism subscale which has 6 items and the Pessimism subscale which has 8 items.
DOI: 10.17632/4zy92xgf45.1
title: Photoelectrons as a tracer of planetary atmospheric composition: Application to CO on Mars

description: IDL procedures and data files used for doing AYS calculations and generating figures in the paper.
DOI: 10.18739/a2t14tp9q
title: Atmospheric tracers for Arctic wildfires, air pollution, atmospheric chemistry, and climate change at GEOSummit, Greenland, since 2018

description: There has been an unprecedented increase in Arctic wildfire occurrences in recent years. This Arctic Observing Network (AON) project focuses on the study of Arctic tundra wildfires through continuous observations of atmospheric fire tracers, including carbon monoxide, methane, and a series of volatile organic compounds (VOCs) monitored at the Greenland Environmental Observatory at Summit (GEOSummit). Observations will be applied in modeling research to simulate Arctic wildfires, and to assess climate-change induced increase in Arctic wildfires and their feedbacks on the Arctic environment. This dataset is an archive of methane, carbon monoxide, carbon dioxide, and VOCs (ethane, ethyne, methyl-chloride, acetonitrile, propane, iso-butane, n-butane, iso-pentane, n-pentane, benzene, toluene) ambient air mixing ratios collected at GEOSummit since 2018. We aim to update this dataset regularly.
DOI: 10.3886/e119042v1-24630
title: Predictors of adjustment in men with prostate cancer

description: This research aims to help us understand men's experience with prostate cancer. Participants were invited to complete a battery of web-based questionnaires via online prostate cancer forums (Cancer Support Network, The New Prostate Cancer InfoLink). Clinical Gatekeepers were sent a brief description of the study and then disseminated the survey link to forum users. Prospective participants read a Participant Information sheet and provided written informed consent. The enrolment period was January 2018 to September 2018. The sample consisted of men who had been diagnosed with prostate cancer in the last 5 years. The study protocol was approved by the Research Ethics Committee of the National University of Ireland, Galway and was conducted in accordance with the principles of the Declaration of Helsinki.
DOI: 10.5519/qd.7yeqmdfl
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4559068 records)
DOI: 10.6073/pasta/f95e6a0ff7cf8114df407e2dc785f949
title: Madison community science field campaign to assess abundance and distribution of invasive jumping worms.

description: Asian pheretimoid earthworms of the genera Amynthas and Metaphire (jumping worms) are leading a new wave of co-invasion into Northeastern and Midwestern states, with potential consequences for native organisms and ecosystem processes. However, little is known about their distribution, abundance, and habitat preferences in urban landscapes – areas which likely influence range expansion via human-driven spread. We led a participatory field campaign to assess jumping worm distribution and abundance in Madison, Wisconsin in September of 2017. By compressing 250 person-hours of sampling effort into a single day, we quantified presence and abundance of three jumping worm species across different land-cover types (forest, grassland, open space, residential lawns and gardens), finding that urban green spaces differed in invasibility. We show that community science can be powerful for researching invasive species while engaging the public in conservation. This approach was particularly effective here, where broad spatial sampling was required within a short temporal window.
DOI: 10.25592/uhhfdm.990
title: 3D Model of a leg with Myxoedema circumscriptum symmetricum

description: 3D Model of a leg with Myxoedema circumscriptum symmetricum
DOI: 10.17632/vptywz7dpr.5
title: Data for: Effect of dexmedetomidine sedation on the swallowing reflex: A pilot study

description: Effect of dexmedetomidine sedation on the swallowing reflex
DOI: 10.18112/openneuro.ds002837.v1.0.5
title: Naturalistic Neuroimaging Database
DOI: 10.5519/qd.ju62ygn2
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (6758 records)
DOI: 10.25386/genetics.12014943
title: Supplemental Material for Jasani, Hyunh, and Kellogg, 2020

description: Video 1 and 2, Figures S1 - S6. <br>
DOI: 10.25592/uhhfdm.992
title: 3D Model of Palmea Raphia-spec

description: 3D Model of Palmea Raphia-spec
DOI: 10.25919/5ececba8ef0ef
title: Parkes observations for project PX600 semester 2020APRS_04

description: The Galactic Center (GC) is a key target for the radio component of Breakthrough Listen (BL) program. Offering the largest amount of stars in any given direction in the sky, the GC is widely cited as a location believed to harbour advanced civilizations, and it is also the most energetic region in the Milky Way. We aim to conduct BL-GC Survey with Parkes radio telescope for around 350 hours. We will cover the frequency range from 700 MHz to 4 GHz, utilizing the newly installed ultra-wideband receiver. Our team has already leveraged both standard and bespoke tools to construct a flexible software stack to search data for signals of interest. We will look for signals from extraterrestrial intelligence (ETI) by searching for both simple narrow-band signals and complex modulated signals. Along with that, as an ancillary science, we will also search for accelerated pulsars — likely orbiting a supermassive black hole at the centre of the Milky Way Galaxy. Data products produced during this program will also be publically available to engage larger pulsar community
DOI: 10.5281/zenodo.3858844
title: Data: Size-dependent patterns of cell proliferation and migration in freely-expanding epithelia

description: Raw images ('*.tif" file extensions) and core measurement files ('*.mat file extension). For small and large circles, we include images of phase, GFP, RFP, and nuclei. We also include two ellipses in phase. 't0SummaryStats.mat' gives information for the starting conditions of tissues represented by the 'PIVunsmoothed.mat' and 'Kymographs.mat' datasets. 'ContinuityEqn_FVM.m' includes the solution to the continuity equation via the finite volume method as detailed in the materials and methods, and relies on data in 'Kymographs.mat' and 't0SummaryStats_continuityEqn.mat'.
DOI: 10.5281/zenodo.3858845
title: Data: Size-dependent patterns of cell proliferation and migration in freely-expanding epithelia

description: Raw images ('*.tif" file extensions) and core measurement files ('*.mat file extension). For small and large circles, we include images of phase, GFP, RFP, and nuclei. We also include two ellipses in phase. 't0SummaryStats.mat' gives information for the starting conditions of tissues represented by the 'PIVunsmoothed.mat' and 'Kymographs.mat' datasets. 'ContinuityEqn_FVM.m' includes the solution to the continuity equation via the finite volume method as detailed in the materials and methods, and relies on data in 'Kymographs.mat' and 't0SummaryStats_continuityEqn.mat'.
DOI: 10.5281/zenodo.3860447
title: Interdependency of port clusters during regional disasters

description: Ports play a vital role in the economy of nations and provide a critical link in the supply chain. Ports form the gateway by which essential goods are received within large geographic regions. Because of their function, ports are exposed to a substantial risk of flooding, storm events, sea-level rise, and climate change. The resiliency of ports is essential for the economy, the people, and national readiness. The contribution of this research work is in providing a methodology to quantify port resiliency that is applicable at the individual port level and regionally. The research approach first defines a quantifiable measure of systematic resiliency. Then applies this measure to quantify the resiliency of six ports located in the Southeast US impacted by Hurricane Matthew (2016). The details are presented in the final report. Also, the data set used for the report is included.
DOI: 10.25386/genetics.12014943.v1
title: Supplemental Material for Jasani, Hyunh, and Kellogg, 2020

description: Video 1 and 2, Figures S1 - S6. <br>
DOI: 10.25345/c5zm6p
title: MassIVE MSV000085473 - Label-free quantification of laser capture glomerular and tubular tissue from renal biopsies to differentiating Staphylococcus infection-associated glomerulonephritis and primary IgA nephropathy
title: Identification of glomerular and tubular proteins in laser capture micro-dissected tissue from five biopsy specimen groups including Staphylococcus aureus infection-associated glomerulonephritis (SAGN), primary IgA nephropathy (IgAN), vancomycin-associated acute tubular necrosis (vancATN), ATN-other causes, and normal kidney tissue. Laser capture tissue was solubilized using heat and acid labile detergent, reduced with DTT, alkylated with iodoacetamide, and digested with trypsin. Tissue digests (1.5ug) were analyzed with nano-LCMS using a 3hr 1D (C18) RP gradient and a LTQ-Orbitrap ELITE mass spectrometer collecting MS2 data by ETD/CID decision tree analysis. ProteomeDiscoverer 1.4 using Mascot (v2.4) and Sequest HT algorithms with a merged human and Staphylococcus aureus protein databases. Results were loaded into Scaffold 4 for comparative proteomics. Protein and peptide FDR were minimized using Peptide/Protein Prophet to less than 1% and final protein lists were constructed after elimination of all decoy hits and employing the 2-peptide hit rule.
DOI: 10.17632/s3tn2v2bzh.1
title: Supplementary Data: Cloud-based multi-dimensional parallel dynamic programming algorithm for a hydropower station system

description: The files in this record contain data for cloud-based multi-dimensional parallel dynamic programming algorithm for a hydropower station system The files consist of: cascade reservoir system data; Source code and results of the parallel dynamic programming algorithm program on the physical machine; Source code and results of the parallel dynamic programming algorithm program on the cloud virtual machine;
DOI: 10.21227/azgy-5e29
title: water quality

description: need data for time series
DOI: 10.5281/zenodo.3857793
title: Numerical code and data for: Suppressed Charge Dispersion via Resonant Tunneling in a Single-Channel Transmon

description: The numerical code and data accompanying the analysis of Figs. 4 and 5 of Suppressed Charge Dispersion via Resonant Tunneling in a Single-Channel Transmon, Phys. Rev. Lett. (2020)
DOI: 10.5281/zenodo.3857794
title: Numerical code and data for: Suppressed Charge Dispersion via Resonant Tunneling in a Single-Channel Transmon

description: The numerical code and data accompanying the analysis of Figs. 4 and 5 of Suppressed Charge Dispersion via Resonant Tunneling in a Single-Channel Transmon, Phys. Rev. Lett. (2020)
DOI: 10.21227/xqpb-4141
title: Twitter dataset

description: The dataset is for twitter spam detection.
DOI: 10.5281/zenodo.3860564
title: Elevation effects on air temperature in a topographically complex mountain valley in the Spanish Pyrenees

description: Data for Atmosphere Journal.