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58 results for “computer program”
A computer program to calculate discrete wavelet transform for one-dimensional signals
<p>This is the most recent version of the True Basic program 'NDHAAR.TRU', which was part of the supplementary materials for the following publication: X. Dong, P. Nyren, B. Patton, A. Nyren, J. Richardson and T. Maresca, 2008. Wavelets for agriculture and biology: A tutorial with applications and outlook. BioScience 58: 445-453.</p> <p>The original version (1.0, April 8, 2008) accepts a one-dimensional signal with 1024 data points. It was previously posted at http://www.ag.ndsu.edu/CentralGrasslandsREC/wavelets-for-agriculture-and-biology</p> <p>Version 1.1 (June 1, 2010) accepts signals with a length of 64, 128, 256, 512, 1024, 2048, 4096, 8192, 16384,<br> 32768, or 65536. This version with documentation was initially posted at www.infoclearinghouse.com. Later the website was closed. Now the documentation can still be accessed at https://www.scss.tcd.ie/Khurshid.Ahmad/Research/Wavelets/wva.pdf.</p> <p>Version 1.2 is posted in this current upload. A major change in this version is the correction of a few typos existing in Version 1.1, so that the program can correctly process signals longer than 4096 (that is, with signal length as either of 8192, 16384, 32768, or 65536). Note that Version 1.1 is fine in correctly processing signals with a length at or shorter than 4096.</p> <p>Two sample input data files are included. Also included is the original supplemental material Suppl_dong_2008.pdf. The first input data file 'pdsi.txt' has a length of 1024, and the related output files are OO1.txt, OO2.txt, OO3.txt, OO4.txt and OO5.txt. These data files are discussed in the original BioScience paper as well as in Suppl_dong_2008.pdf. </p> <p>The second sample input file 'warm.txt' has a length of 65536 and the related output files are OUT_1.txt, OUT_2.txt, OUT_3.txt, OUT_4.txt, and OUT_5.txt. The sample input file warm.txt contains NDVI values of winter wheat measured at Uvalde, TX, USA, from about 8 am to 10 am on April 12, 2018. The measurement was made using an ACS-430 Crop Circle sensor mounted to a push-wheel cart. This file and the associated output files are part of the intermediate results for Supplementary Figure S2 to the article entitled "Leaf water potential of field crops estimated using NDVI in ground-based remote sensing - opportunities to increase prediction precision" (<em>PeerJ</em>. 9:e12005 DOI 10.7717/peerj.12005), which can be accessed at https://zenodo.org/record/4574674#.YD7kI2hKiUk</p>
Fig. 3 in SNAIL - an interactive computer program for the determination of Central European freshwater gastropods
Fig. 3: The commputer programm SNAIL (version 1.0) with its eentrance menu (aa) as well as thee main menu (b).
Fig. 5 in SNAIL - an interactive computer program for the determination of Central European freshwater gastropods
Fig. 5: Key ooffered by the computer progrram SNAIL forr determining tthe species Lymmnaea stagnalis.
Trapalyzer: A computer program for quantitative analyses in fluorescent live-imaging studies of Neutrophil Extracellular Trap formation.
<p>This data set contains a set of fluorescent microscopy images of a co-culture of neutrophil cells and E. coli bacteria used to study the Neutrophil Extracellular Trap (NET) formation stimulated by bacteria. </p> <p>NETs and live cells were visualized with a double fluorescent staining of DNA using Hoechst 33342 and SYTOX Green. </p> <p><strong>Reagents.</strong></p> <p>Roswell Park Memorial Institute (RPMI) 1640 medium, HEPES, SYTOX<sup>TM</sup> Green, and Hoechst 33342 were purchased from Thermo Fisher Scientific (Waltham, USA). LB broth was purchased from Sigma Aldrich (St Louis, MO, USA).</p> <p><strong>Preparation of blood neutrophils.</strong></p> <p>Neutrophils were obtained from peripheral blood of one healthy blood donor. Blood sample was purchased at Local Blood Donation Centre and according to local regulations, the blood donor enabled blood donation center to sell their blood samples for scientific purposes and the consent of bioethical committee was not required. Blood was collected into a citrate tube and processed within 2 hours from collection. Neutrophils were isolated using density gradient centrifugation followed by polyvinyl alcohol sedimentation, exactly as described in [1]. Isolated neutrophils were suspended in RPMI 1640 medium with 10 mM HEPES (RH). </p> <p><strong>Preparation of bacteria.</strong></p> <p><em>Escherichia coli</em> (American Type Culture Collection(ATCC) 25922 strain) were grown overnight in LB broth with shaking. In the morning, an aliquot of bacterial culture was taken, diluted 100 x in a fresh LB medium and grown for subsequent 2-3 hours. Subsequently, bacterial cultures were washed and resuspended in RH medium.</p> <p><strong>Co-culture of neutrophils with bacteria</strong><br> Neutrophils were seeded into the wells of 48-well plates at the density of 2 ⨉ 10<sup>4</sup> cells/well and allowed to settle for 30 minutes at 37°C, 5% CO2. Subsequently, <em>E. coli</em> was added into the appropriate wells at the multiplicity of infection of 4 or 1 (<em>E.coli</em>: neutrophil). Neutrophils incubated without bacteria were used as a control group. A technical duplicate for each condition was prepared. <br> For each intended timepoint (t=0, 60, 90, 120, 180 minutes), a separate 48 well plate was prepared. The plates were centrifuged for 5 minutes at 250 g to allow the contact of bacteria with neutrophils. The plates were incubated at 37°C, 5\% CO2 for a specified time and then the samples were stained with SYTOX<sup>TM</sup> Green (100 nM) and Hoechst 33342 (1.25 μM) for 10 minutes. Four images of each well were taken with Leica DMi8 fluorescent microscope equipped with a 10× magnification objective (Leica, Wetzlar, Germany). Overall, 120 images have been obtained.</p> <p> </p> <p><strong>2019_04_24--ecoli_neu_tiff_channel_merged.zip:</strong> Images in .tif format, each containing 5 channels: channel 1 for SYTOX Green fluorescent stain (green fluorescence), channel 2 for Hoechst 33342 fluorescent stain (blue fluorescence), and three channels for transmission light encoded in RGB values. </p> <p> </p> <p><strong>2019_04_24--ecoli_neu_tiff_raw_exported.zip:</strong> Images split by different light sources: transmission light (_ch00.tif), SYTOX Green fluorescence (_ch01.tif), Hoechst 33342 fluorescence (_ch02.tif).</p> <p> </p> <p>[1] Bystrzycka W, Moskalik A, Sieczkowska S, Manda-Handzlik A, Demkow U, Ciepiela O. The effect of clindamycin and amoxicillin on neutrophil extracellular trap (NET) release. <em>Cent Eur J Immunol</em>. 2016;41(1):1-5. doi:10.5114/ceji.2016.58811</p>
Dataset for the article: Evaluating the Predictive Performance of Quick Methods for Estimating Task Difficulty and Student Ability in Automated Computer Programming Assessment
<p>This open access repository houses the dataset utilized in the research article:</p><p>Pankiewicz, M. (2023). Evaluating the Predictive Performance of Quick Methods for Estimating Task Difficulty and Student Ability in Automated Computer Programming Assessment. In T. Bastiaens (Ed.), Proceedings of EdMedia + Innovate Learning (pp. 1413-1418). Vienna, Austria: Association for the Advancement of Computing in Education (AACE). Retrieved from https://www.learntechlib.org/primary/p/222666</p><p>The repository includes these files:</p><p>"submissions.csv": This data file captures the evaluation results of programming assignments. It is organized by the following columns:</p><p> </p><ul><li>"user_id": The unique identifier for each student who submitted the assignment.</li><li>"task_id": The unique identifier for each task that received submissions.</li><li>"submission_seconds": The number of seconds since the first user accessed the initial task's description within the system.</li><li>"correct": The outcome of the evaluation (1 denotes correct; 0 denotes incorrect).</li><li>"subject": The specific subject matter that the task addresses.</li></ul><p> </p><p>"subjects.csv": This data file comprises the roster of subjects for which tasks have been assigned within the system. It includes these columns:</p><p> </p><ul><li>"subject_id": The unique identifier for each subject.</li><li>"subject": The actual name of the subject.</li></ul><p> </p>
Computing integrated activities scored for programming concepts
<p>Educators across disciplines are implementing lessons and activities that integrate computing concepts into their curriculum to broaden participation in computing. Out of myriad important introductory computing skills, it is unknown which—and to what extent—these concepts are included in these integrated experiences, especially when compared to concepts commonly taught in introductory computer science courses. Thus, it is unclear how integrated computing activities serve the goal of broadening participation in computing. To address this deficit, we compiled a database of 81 integrated computing activities, constructed a framework of fundamental programming concepts, and scored each activity in the database for the presence of each concept. The dataset also includes different activity features, including discipline, programming language, student age, and duration of activity. </p>
qplib-web: Mathematical Programming Computations
<p>Release to go along with the publication of the QPLIB paper on MPC.</p>
Fig. 4 in SNAIL - an interactive computer program for the determination of Central European freshwater gastropods
Fig. 4: Key offered by thee computer proogram SNAIL for determiningg the family oof the Lymnaeidae.
Feasibility of a Touch Screen Computer Based Breast-feeding Educational Support Program
ClinicalTrials.gov study NCT03308058. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Interactive Computer-adaptive Chronic Kidney Disease Education Program
ClinicalTrials.gov study NCT06364358. IPD Sharing: YES. Countries: 1. Publications: 1.
Computing integrated activities scored for programming concepts
Open the record for dataset details and reuse information.
Programming and computational thinking concepts and contextual factors in integrated computing activities in U.S. Schools
Open the record for dataset details and reuse information.
Programs for chemoinformatics and computational medicinal chemistry
<p>Programs provided herein are a part of a freely available database of annotated compound data sets and software tools developed in our laboratory for chemoinformatics and computational medicinal chemistry. The original release is described in the following article:<br /> <br /> Hu Y, Bajorath J: Freely available compound data sets and software tools for chemoinformatics and computational medicinal chemistry applications [v1; ref status: indexed, http://f1000r.es/Mu9krs] <em>F1000Research</em> 2012; 1:11 (doi: 10.12688/f1000research.1-11.v1).<br /> <br /> The updated version containing the data provided herein will be described in a forthcoming data note in <em>F1000Research</em>.</p>
SelfCode 2.0: Annotated Corpus of Student Self-Explanations to Introductory JAVA Programs in Computer Science
<p><strong>Dataset Description:</strong> This dataset was collected during a lab study conducted in Spring 2022 for introductory JAVA programming. Students had to provide line by explanations to four JAVA programs in the experimental condition of the study. The JAVA Programs were selected from the examples made available in the <a title="PCEX" href="https://dl.acm.org/doi/abs/10.1145/3279720.3279726" target="_blank" rel="noopener">PCEX Worked Examples interface</a>. The explanations collected were then split by the number of attempts. Students could attempt twice based on the feedback provided using the the PCEX interface and in their third attempt they filled in the blanks to complete an explanation to the particular line of code. In this dataset, we only have the annotated examples of explanations provided by students. The explanations were annotated on their correctness (binary rating 0 or 1), completeness (binary rating 0 or 1) and similarity (rating scale 1 to 5).</p> <p><strong>Correctness:</strong> Given the line of code and context of the line in the program, if the student explanation covers **only** the topics relevant to the line of code</p> <p><strong>Completeness:</strong> Given the line of code and context of the line in the program, if the student explanation covers **all** the topics relevant to the line of code</p> <p><strong>Similarity:</strong> Given the line of code, the context of the line in the program and an expert explanation to the line of code, the metric compares the similarity on a rating scale from 1 to 5, defined in the following manner:</p> <p>1 - expert and student explanations are very different,</p> <p>2 -- expert and student explanations are somewhat alike, but there are major differences in the concepts / topics explained</p> <p>3 -- expert and student explanations are similar but there are differences in the concepts / topics explained</p> <p>4 -- expert and student explanations are similar and have few differences in the concepts / topics explained</p> <p>5 -- expert and student explanations are very similar.</p> <p> </p> <p>Overall 3000 single attempts (corresponding to 40 student explanation submission) were annotated against different various expert explanation pairs.</p> <p> </p> <p><strong>Dataset Summary:</strong></p> <p><strong>Explanation Type N Definition<br></strong>Experts 2 Source Code Line-by-Line Explanations by Experts<strong><br></strong>Students 60 (annotated 40) Source Code Line-by-Line Explanations by Students</p> <table> <tbody> <tr> <td>COUNT of std_sent_count</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>std_sent_count</td> <td>1</td> <td>2</td> <td>3</td> <td>4</td> <td>5</td> <td>6</td> <td>Grand Total</td> </tr> <tr> <td>1</td> <td>1854</td> <td>367</td> <td>245</td> <td>107</td> <td>34</td> <td>33</td> <td>2640</td> </tr> <tr> <td>2</td> <td>222</td> <td>46</td> <td>40</td> <td>12</td> <td>6</td> <td>6</td> <td>332</td> </tr> <tr> <td>3</td> <td>21</td> <td>5</td> <td>5</td> <td>5</td> <td>1</td> <td>2</td> <td>39</td> </tr> <tr> <td>4</td> <td>2</td> <td>1</td> <td>2</td> <td>3</td> <td> </td> <td> </td> <td>8</td> </tr> <tr> <td>Grand Total</td> <td>2099</td> <td>419</td> <td>292</td> <td>127</td> <td>41</td> <td>41</td> <td>3019</td> </tr> </tbody> </table> <p> </p> <p><strong>Sample Data:</strong></p> <p><strong>Program:</strong> PointTester; Line number: 12; Line code: private int y;<br><strong>Expert1: </strong>Every object of the Point class will have its own y-coordinate. Therefore, we<br>need to declare an instance variable for the class to store the y-coordinate of the point.<br>We declare it as int because we want to have integer coordinates for the point. Note<br>that an instance variable is a variable defined in a class, for which each instantiated<br>object of the class has a separate copy, or instance.<br><strong>Expert2:</strong> The instance variables are declared as private to prevent direct access to<br>them from outside the class. In this way, no unexpected modifications to a Point<br>object’s data are possible.<br><strong>Student1: </strong>initialize a private value inside the point class with no value yet<br><strong>Student2:</strong> Declares the private int variable y.<br><strong>Student3: </strong>Creates a private int that can only be accessed by class Point called int y<br>...<br><strong>Student59:</strong> private variable used to store the value entered into the value of the y<br>coordinate</p> <p> </p> <p><strong>Kappa Scores:</strong></p> <div> <table> <tbody> <tr> <td> <p>Round</p> </td> <td> <p>Row Numbers</p> </td> <td> <p>Correctness Rating Agreement %age</p> </td> <td> <p>Correctness Rating Kappa</p> </td> <td> <p>Sufficiency Rating Agreement %age</p> </td> <td> <p>Sufficiency Rating Kappa</p> </td> </tr> <tr> <td> <p>1</p> </td> <td> <p>1000 - 1432 </p> </td> <td> <p>92.9</p> </td> <td> <p>0.365</p> </td> <td> <p>0.708</p> </td> <td> <p>-0.0123</p> </td> </tr> <tr> <td> <p>2</p> </td> <td> <p>1432 - 1864</p> </td> <td> <p>94.2</p> </td> <td> <p>0.263</p> </td> <td> <p>77.6</p> </td> <td> <p>0.329</p> </td> </tr> <tr> <td> <p>3</p> </td> <td> <p>1864 – 1964 </p> </td> <td> <p>75.3</p> </td> <td> <p>0</p> </td> <td> <p>70.3</p> </td> <td> <p>0.299</p> </td> </tr> <tr> <td> <p>4</p> </td> <td> <p>1964 -- 2064 </p> </td> <td> <p>86</p> </td> <td> <p>0.108</p> </td> <td> <p>74.7</p> </td> <td> <p>0.275</p> </td> </tr> <tr> <td> <p>5</p> </td> <td> <p>2064 – 2264</p> </td> <td> <p>95.5</p> </td> <td> <p>-0.0158</p> </td> <td> <p>81.5</p> </td> <td> <p>0.312</p> </td> </tr> <tr> <td> <p>6</p> </td> <td> <p>2264 – 2464</p> </td> <td> <p>83.5</p> </td> <td> <p>0.039</p> </td> <td> <p>86.5</p> </td> <td> <p>0.648</p> </td> </tr> <tr> <td> <p>7</p> </td> <td> <p>2464 – 2864</p> </td> <td> <p>92</p> </td> <td> <p>0.103</p> </td> <td> <p>74.5</p> </td> <td> <p>0.188</p> </td> </tr> <tr> <td> <p>8</p> </td> <td> <p>2864 -- 3005</p> </td> <td> <p>86.5</p> </td> <td> <p>-0.026</p> </td> <td> <p>72.3</p> </td> <td> <p>0.117</p> </td> </tr> </tbody> </table> </div> <p> </p> <p> </p> <p><strong>Citation Format:</strong><br>If using this dataset in your project please cite:</p> <p>Lekshmi-Narayanan, A.-B., Chapagain, J., Brusilovsky, P., & Rus, V. (2023). SelfCode 2.0: Annotated Corpus of Student Self-Explanations to Introductory JAVA Programs in Computer Science [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10912669</p> <p><strong>Acknowledgements:</strong><br>This project was funded as a part of the NSF AWARD # 1822752</p> <p> </p> <p> </p>
Computation Tree Logic guided Reactive Program Repair
<p>This is the supporting data for OOPSLA24 submission: Computation Tree Logic guided Reactive Program Repair. </p> <p>It includes the source code and benchmarks presented in the paper. </p>
Computer Assisted Cognitive Remediation Program in Schizophrenia
ClinicalTrials.gov study NCT01598220. IPD Sharing: Not stated. Countries: 1. Publications: 2.
The Effect of Self-Efficacy Promoting Program Using Computer Game on Proteinuria in Thai Children With Nephrotic Syndrome
ClinicalTrials.gov study NCT06524986. IPD Sharing: NO. Countries: 1. Publications: 6.
Infant Nutrition: Evaluation of an Educational Touchscreen Computer Program
ClinicalTrials.gov study NCT01272492. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Novel Computer-Based Functional Skills Assessment and Training Program
ClinicalTrials.gov study NCT04679441. IPD Sharing: NO. Countries: 1. Publications: 2.
Computer-based Cognitive Rehabilitation Program for Healthy Older Adults, Older People With Mild Cognitive Impairment and Mild Dementia
ClinicalTrials.gov study NCT03430401. IPD Sharing: NO. Countries: 1. Publications: 1.
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.