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324 results for “test cases”
FIGURE 1 in Testing hypothesis of skeletal unity using bone histology: The case of the sauropod remains from the Howe-Stephens and Howe Scott quarries (Morrison Formation, Wyoming, USA)
FIGURE 1. Detailed quarry map of the Howe-Stephens Quarry with finds from excavation seasons 1992-2001. The color coding reflects the hypothesis of skeletal unity based on field observations (Ayer, 2000). Sauropods are indicated in red text in the legend. Note that the 2002 season, which was the last season for the Howe-Stephens Quarry, only uncovered another silicified tree trunk, which was found below the partial skeletons of SMA 0002 "E.T." and SMA no # "Brösmeli". The arrows indicate the sampled bones used in this study. This quarry map was made by E. Premru, and provided by the Sauriermuseum Aathal, Aathal, Switzerland.
FIGURE 15 in Testing hypothesis of skeletal unity using bone histology: The case of the sauropod remains from the Howe-Stephens and Howe Scott quarries (Morrison Formation, Wyoming, USA)
FIGURE 15. Images of both samples taken from SMA 0084 "Rich". A, tibia (l). B, fibula (l). For all samples, the bone tissue types are indicated to the left, and the number and patterns of the visible growth cycles are indicated to the right. Abbreviations; EFS: External fundamental system, MC: Medullary cavity, RA: Remodeled area.
FIGURE 3 in Testing hypothesis of skeletal unity using bone histology: The case of the sauropod remains from the Howe-Stephens and Howe Scott quarries (Morrison Formation, Wyoming, USA)
FIGURE 3. The innermost cortex of fibula SMA 0084 "Rich" with the three visible generations of secondary osteons. The numbers indicate the three overlapping secondary osteons. Image taken under plane-polarized light.
FIGURE 12 in Testing hypothesis of skeletal unity using bone histology: The case of the sauropod remains from the Howe-Stephens and Howe Scott quarries (Morrison Formation, Wyoming, USA)
FIGURE 12. Several histological structures observed in the anterior section of the femur of SMA 0014 "Jacques". A, Large circular structure, which possesses clear circumferentially orientated vascular canals. B, Close-up of the circular structure and the vascular canals. C, D, F, Cycles which show unorganized bone tissue, and varying vascular canal orientations. E, Close-up of unorganized bone tissue cycle. Images taken under plane-polarized light.
FIGURE 11 in Testing hypothesis of skeletal unity using bone histology: The case of the sauropod remains from the Howe-Stephens and Howe Scott quarries (Morrison Formation, Wyoming, USA)
FIGURE 11. Images of all samples taken from SMA 0014 "Jacques". A, femur (r), drilled on the anterior side. B, femur (r), drilled on the posterior side. C, tibia (r). For all samples, the bone tissue types are indicated to the left, and the number and patterns of the visible growth cycles are indicated to the right. Abbreviations; D: Bone tissue type D, E: Bone tissue type E, F: Bone tissue type F, MC: Medullary cavity, RA: Remodeled area.
FIGURE 14 in Testing hypothesis of skeletal unity using bone histology: The case of the sauropod remains from the Howe-Stephens and Howe Scott quarries (Morrison Formation, Wyoming, USA)
FIGURE 14. Images of all hindlimb samples taken from SMA 0011 "Max". A, femur (l), drilled on the anterior side. B, femur (l), drilled on the posterior side. C, tibia (l). D, fibula (l). E, SMA M16/12-3 femur (l). For all samples, the bone tissue types are indicated to the left, and the number and patterns of the visible growth cycles are indicated to the right. Abbreviations; D: Bone tissue type D, E: Bone tissue type E, EFS: External fundamental system, F: Bone tissue type F, MC: Medullary cavity, RA: Remodeled area.
FIGURE 9 in Testing hypothesis of skeletal unity using bone histology: The case of the sauropod remains from the Howe-Stephens and Howe Scott quarries (Morrison Formation, Wyoming, USA)
FIGURE 9. Images of all samples taken from the isolated bones SMA G47/87-1, G47/87-1 and G50/91-1. A, SMA G46/87-1 humerus (l). B, SMA G50/91-1 humerus (r). C, SMA G47/87-1 femur (l). For all samples, the bone tissue types are indicated to the left, and the number and patterns of the visible growth cycles are indicated to the right. Abbreviations; D: Bone tissue type D, E: Bone tissue type E, MC: Medullary cavity, RA: Remodeled area.
Figure 4.1. Distribution of scores for the Nelson test-The Effects of CALL on Vocabulary Learning: A Case of Iranian Intermediate EFL Learners
<p>In the past, vocabulary teaching and learning were often given little priority in second<br> language programs but recently there has been a renewed interest in the nature of vocabulary and its<br> role in learning and teaching. Although most teachers might be aware of the importance of<br> technology, say, computer, rarely teachers use it for teaching vocabulary. Thus, the current study<br> aims at exploring the effects of CALL on vocabulary learning of Iranian EFL Learners. In this<br> study, 40 intermediate EFL learners, both male and female aged from 16 to 18 studying New<br> Interchange, book III, were chosen randomly from a language institute in Tehran. They were divided<br> into two twenty-member groups. The experimental group was given the VTS.S (a computer<br> program for teaching vocabularies), a computerized dictionary and provided with teacher efeedback.<br> The control group received no special software and vocabularies were taught using the<br> conventional ways with the help of a paper dictionary. A vocabulary pre-test based on the tests<br> available in their teacher's guide was given to both groups. The aim of this test was to make sure<br> that the students were not familiar with the words in advance. By pre-test/post-test comparison<br> researchers found learners exposed to VTS.S teacher e-feedback plus the computerized dictionary<br> scored higher than the control group. Both high-stake and low-stake holders can avail from the<br> findings of the study.</p>
Execution and data log: on the effectiveness of random and adaptive random test case prioritization
<p>Execution and data logs automatically generated by the test driver during experimentation. These results are similar (but not identical) to the results summarized in Table 1 of the following paper:</p> <p>Z. Q. Zhou, A. Sinaga, and W. Susilo, "On the fault-detection capabilities of adaptive random test case prioritization: case studies with large test suites," in Proceedings of the 45th Annual Hawaii International Conference on System Sciences (HICSS-45). IEEE, 2012, pp. 5584-5593.<br> https://doi.org/10.1109/HICSS.2012.454</p> <p>Compared with the above paper, the current dataset was collected from a different but similar set of experiments and included faulty versions 13, 23, and 26 of the Replace program---although these three versions were excluded from the experiments reported in the above paper due to their instability.</p> <p>If you find these data useful, please cite the above paper.</p>
Data Set Used in Combinatorial Modeling and Test Case Generation for Industrial Control Software using ACTS
<p>This document contains the data set used for the study Combinatorial Modeling and Test Case Generation for Industrial Control Software using ACTS that is currently in submission.</p>
Bioexcel building blocks test cases
<p>Bioexcel building blocks test cases for Lysozyme and Pyruvate Kinase executed in Workstations, OpenNebula VMs and MareNostrum4 HPC.</p> <p> </p> <p> </p> <p> </p> <p> </p>
Learning How to Search: Generating Effective Test Cases Through Adaptive Fitness Function Selection
<p>Data Package for "Learning How to Search: Generating Effective Test Cases Through Adaptive Fitness Function Selection"</p> <p>This package contains data generated as part of our experiments on adaptive fitness function selection as part of unit test generation for Java systems.</p> <p>This paper is currently under submission. A draft of the paper is included in the data package.</p> <p>This package contains experimental data (in folder "experiment_data"), including goal attainment, fault detection, time per generation, and choices made by the reinforcement learning algorithm. In the folder "test_suites", the suites generated by each technique are included for each project. </p> <p>If you have questions, please contact Gregory Gay at greg@greggay.com.</p> <p>NOTE: A small number of items are currently missing from this data package and will be added shortly. Please make sure you have the latest version of this package.</p>
INSYDE model - Testing empirical and synthetic flood damage models: the case of Italy
<p>This repository contains the R code for <a href="http://www.nat-hazards-earth-syst-sci.net/16/2577/2016/">INSYDE, a synthetic, probabilistic flood damage model based on explicit cost analysis</a>.</p> <p>Correspondence to: Rui Figueiredo (<a href="mailto:rui.figueiredo@iusspavia.it">rui.figueiredo@iusspavia.it</a>)</p>
Improving triaging from primary care into secondary care using heterogeneous data-driven hybrid machine learning: A real-world case study of decision support system using blood test & GP referral letters - Bing Wang and Prof Weizi (Vicky) Li (University of Reading)
<p>This video is the sixth talk from our two day Future Blood Testing: Challenges & Opportunities Event that took place on the 13/09/2022.</p> <p>Improving triaging from primary care into secondary care using heterogeneous data-driven hybrid machine learning: A real-world case study of decision support system using blood test & GP referral letters - Bing Wang and Prof Weizi (Vicky) Li (University of Reading)</p> <p>Bio: Dr Weizi (Vicky) Li is the PI of the Future Blood Testing Network, an Associate Professor of Informatics and Digital Health, Deputy Director in Informatics Research Centre, Henley Business School, University of Reading. She is an interdisciplinary researcher focusing on using informatics, data science, machine learning, and digital information systems to solve real-world healthcare challenges. She is the academic lead of a large collaborative project of Improving the Quality of Healthcare through an Integrated Clinical Pathway Management Approach and Cloud based Digital Data Integration Platform, which was awarded ESRC O2RB Excellence in Impact Award in 2018 for her research impact on healthcare quality improvement. She is the academic lead of machine learning based decision support system for outpatient management which has successfully been implemented in Royal Berkshire NHS Foundation Trust and has received Research Engagement and Impact award in 2020. She has been PI on projects funded by ESRC, EPSRC, The Health Foundation, NHS and companies, working on data-driven decision support systems that use real-world data (under privacy preserving framework) from multiple sources including Electronic Patient Record in acute, community hospital and primary care settings, remote health monitoring and patient reported outcomes to develop novel technologies (including AI based methods) to support clinical and operational decision makings in patient pathway. Bing Wang is currently a PhD candidate in informatics and system science at the Informatics Research Center, Henley Business School, University of Reading. Bing’s research interests are Natural Language Processing, Machine Learning and Graph Machine Learning. Bing been working as a data scientist at Royal Berkshire NHS Foundation Trust since December 2019 during his PhD.</p> <p>Further details on this event can be found at: https://futurebloodtesting.org/event/13-14-09-2022/</p> <p>This video is an output from the Future Blood Testing Network which is funded by EPSRC under Grant Number EP/W000652/1</p> <p>YouTube Link: https://youtu.be/W6EH5l80NmU</p>
RML Tabular Views Test Cases
<p>Test cases for <a href="https://ceur-ws.org/Vol-1184/ldow2014_paper_01.pdf">RML</a> tabular views based on the <a href="https://www.w3.org/2001/sw/rdb2rdf/test-cases/">R2RML test cases</a>. The test cases use the CSV data format similarly to the <a href="https://doi.org/10.1007/978-3-030-21395-4_12">RML test cases</a>.</p>
Replication Data for "How Do Different Types of Testing Goals Affect Test Case Design?"
<p># Replication Data for "How Do Different Types of Testing Goals Affect Test Case Design?"</p> <p>## Overview</p> <p>Background: Test cases are designed in service of one or more goals, e.g., assessing functional correctness or performance. We lack a clear understanding of how specific goal types influence test design.</p> <p>Aims: We explore the relationship between types of testing goals and test design, including identification and importance of goal types, quantitative relations between goal types and test cases, and personal, organizational, methodological, and technological factors that may influence this relationship.</p> <p>Method: We have conducted both qualitative and quantitative analysis of interviews and a survey with software developers in various domains and of varying experience.</p> <p>Results: We identify nine goal types, and focus on correctness, reliability, and quality. We observe that test design for correctness forms a "default" design process that is modified when pursuing other goals. For the examined goal types, test cases tend to be simple, with many tests targeting a single goal and each test focusing on 1-2 goals at a time. Testers often start by using past tests as templates. Testing practices, tools, and system types of interest vary between goal types. Test design can be influenced by organization, process, and team makeup.</p> <p>Conclusions: This study provides a foundation for future research on test case design and testing goals.</p> <p>The paper can be found at http://greg4cr.github.io/pdf/23goals.pdf </p> <p>## Data Contained in This Package</p> <p>- thematic_coding.pdf</p> <p>This is the theme map created from the interview data. We extracted important statements from the interviews (codes) and clustered them into themes and sub-themes.</p> <p>- survey_responses.pdf</p> <p>This file contains all survey responses.</p> <p>Both interview and survey data has been anonymized to protect the privacy of the participants.</p>
Implementation of ATP and Microbial Indicator Testing for Hygiene Monitoring in a Tofu Production Facility Improves Product Quality and Hygienic Conditions of Food Contact Surfaces: A Case Study
<p>This is the code and associated data that was used to generate conclusions for the following manuscript published in Applied and Environmental Microbiology:</p> <p>DOI: 10.1128/AEM.02278-20</p> <p>Implementation of ATP and Microbial Indicator Testing for Hygiene Monitoring in a Tofu Production Facility Improves Product Quality and Hygienic Conditions of Food Contact Surfaces: A Case Study</p> <p>Authors: Jonathan H. Sogin(a), Gabriela Lopez Velasco(b), Burcu Yordem(b), Cari K. Lingle(b), John M. David(b), Mario Cobo(a), Randy W. Worobo(a)</p> <p>(a)Department of Food Science, Cornell University, Ithaca, NY, USA</p> <p>(b)3M Company, St. Paul, MN, USA</p> <p>Address correspondence to Jonathan H. Sogin, jhs397@cornell.edu</p>
Identifying diagnostic genetic markers for a cryptic invasive agricultural pest: a test case using the apple maggot fly, Rhagoletis pomonella (Diptera: Tephritidae)
Insect pests destroy ~15% of all USA crops, resulting in losses of $15 billion annually. Thus, developing cheap, quick and reliable methods for detecting harmful species is critical to curtail insect damage and lessen economic impact. The apple maggot fly, Rhagoletis pomonella (Diptera: Tephritidae), is a major invasive pest threatening the multibillion-dollar apple industry in the Pacific Northwest USA. The fly is also sympatric with a benign but morphologically similar and genetically closely related species, R. zephyria, which attacks non-commercial snowberry. Unambiguous species identification is essential due to a zero-infestation policy of apple maggot for fruit export. Mistaking R. zephyria for R. pomonella triggers unnecessary and costly quarantines, diverting valuable control resources. Here we develop and apply a relatively simple and cost-effective diagnostic approach using Illumina sequencing of double digest restriction-site associated DNA markers. We identified five informative single nucleotide polymorphisms (SNPs) and designed a diagnostic test based on agarose gel electrophoresis of restriction enzyme digested polymerase chain reaction amplification products (RFLPs) to distinguish fly species. We demonstrated the utility of this approach for immediate, one day species identification by scoring apple- and snowberry-infesting flies of known host plant identity, reared directly from 11 sites throughout Washington. However, if immediate diagnosis is not required, or hundreds to thousands of specimens must be assessed, then a direct Illumina-based sequencing strategy, similar to that used here for diagnostic SNP identification can be powerful and cost-effective. The genomic strategy we present is effective for R. pomonella and also transferable to many cryptic pests.
SBML Test Suite Syntactic Test Cases 3.2.0
<p>The SBML Test Suite is a conformance testing system. It allows developers and users to test the degree and correctness of the SBML support provided in a software package. A core part of the SBML Test Suite is the collection of test cases. There are 3 sets of tests: <strong>semantic</strong> (for deterministic simulation behavior), <strong>stochastic</strong>(for stochastic simulation behavior), and <strong>syntactic</strong> (for basic parsing).</p> <p>This is the version 3.2.0 release of the s<strong>yntactic</strong> test cases archive.</p> <p>For more information about SBML and the SBML Test Suite, please visit http://sbml.org.</p>
SBML Test Suite Semantic Test Cases 3.2.0
<p>The SBML Test Suite is a conformance testing system. It allows developers and users to test the degree and correctness of the SBML support provided in a software package. A core part of the SBML Test Suite is the collection of test cases. There are 3 sets of tests: <strong>semantic</strong> (for deterministic simulation behavior), <strong>stochastic</strong>(for stochastic simulation behavior), and <strong>syntactic</strong> (for basic parsing).</p> <p>This is the version 3.2.0 release of the <strong>semantic</strong> test cases archive.</p> <p>For more information about SBML and the SBML Test Suite, please visit http://sbml.org.</p>
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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.