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1,719 results for “Making”
Development of a Mobile Robot Test Platform and Methods for Validation of Prognostics-Enabled Decision Making Algorithms
As fault diagnosis and prognosis systems in aerospace applications become more capable, the ability to utilize information supplied by them becomes increasingly important. While certain types of vehicle health data can be effectively processed and acted upon by crew or support personnel, others, due to their complexity or time constraints, require either automated or semi-automated reasoning. Prognostics-enabled Decision Making (PDM) is an emerging research area that aims to integrate prognostic health information and knowledge about the future operating conditions into the process of selecting subsequent actions for the system. The newly developed PDM algorithms require suitable software and hardware platforms for testing under realistic fault scenarios. The paper describes the development of such a platform, based on the K11 planetary rover prototype. A variety of injectable fault modes are being investigated for electrical, mechanical, and power subsystems of the testbed, along with methods for data collection and processing. In addition to the hardware platform, a software simulator with matching capabilities has been developed. The simulator allows for prototyping and initial validation of the algorithms prior to their deployment on the K11. The simulator is also available to the PDM algorithms to assist with the reasoning process. A reference set of diagnostic, prognostic, and decision making algorithms is also described, followed by an overview of the current test scenarios and the results of their execution on the simulator.
An Approach to Prognostic Decision Making in the Aerospace Domain
The field of Prognostic Health Management (PHM) has been undergoing rapid growth in recent years, with development of increasingly sophisticated techniques for diagnosing faults in system components and estimating fault progression tra- jectories. Research efforts on how to utilize prognostic health information (e.g. for extending the remaining useful life of the system, increasing safety, or maximizing operational ef- fectiveness) are mostly in their early stages, however. This process of using prognostic information to determine a sys- tem’s actions or its configuration is beginning to be referred to as Prognostic Decision Making (PDM). In this paper we, first, propose a formulation of the PDM problem with the at- tributes of the aerospace domain in mind, outline some of the key requirements on PDM methods, and explore techniques that can be used as a foundation of PDM development. The problem of Pareto set viability, i.e. satisfaction of perfor- mance goals set for objective functions, is discussed next, followed by ideas for possible solutions. The ideas, termed Dynamic Constraint Redesign (DCR), have roots in the fields of Multidisciplinary Design Optimization and Game Theory. Prototype PDM and DCR algorithms are also described and results of their testing are presented.
How to Make an Elephant: Functional Genomic Divergence and the Evolution of Cancer Suppression
GEO Series GSE148098. Loxodonta africana. 4 samples. Type: Expression profiling by high throughput sequencing.
Does a hypersensitive immune response to helminth infection at duodenum make Merino sheep susceptible to diarrhoea?
GEO Series GSE176569. Ovis aries. 8 samples. Type: Expression profiling by high throughput sequencing.
microRNA signature to support clinical-decision making in patients with suspected Obstructive Sleep Apnea
GEO Series GSE229362. Homo sapiens. 53 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Effect of Presentation Format on Decision-Making in the Sharing Economy
<p>The coding rules and interpretations for each variable are provided in the comments attached to their respective column names. </p>
LabSCoC Moral Decision-Making - data
<p>This repository contains the raw data, preprocessed data, script and jamovi files of the <a href="https://zenodo.org/records/14070419"><em>LabSCoC Moral Decision-Making - project (https://zenodo.org/records/14070419)</em></a></p>
Figure 1 in Making shelter for enemies: parasitoid-induced shelter-building behaviour in Paraponyx stagnalis
Figure 1. Study sites in Northern Kerala.
Exploring the Influence of GenAI-based Tools on Student's Planning and Decision Making in Software Modeling
<p>The file describes our sample modelling problem used for the controlled experiment with students. Also, the file contains two sets of initial questions for students to use to interact with their respective product owners and domain experts. </p>
Deciphering the transcriptional changes in Escherichia coli strains C41(DE3) and C43(DE3) that makes them a superior choice for membrane protein production.
GEO Series GSE153028. Escherichia coli. 18 samples. Type: Expression profiling by high throughput sequencing.
Suppressor mutations that make the essential transcription factor Spn1/Iws1 dispensable in Saccharomyces cerevisiae
GEO Series GSE202590. Saccharomyces cerevisiae. 36 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Supporting students in making informed data sharing decisions: from comprehension to consenting
<p>Whether deciding to participate in research or gain access to online applications, studies on consent suggest that individuals often do not read or fail to understand the text outlining the conditions they agree to when giving their consent. Limited comprehension related to the risks of big data and habituation may contribute to consent being given in a manner that counters the best interests of individuals (i.e. a privacy paradox). Are those asking students to use new technologies and share their data ethically responsible for helping students learn to make informed decisions regarding the sharing of their data? As educational technology researchers, we conducted a quasi-experimental study involving 127 undergraduate students in which we explored the effects on study enrollment of supporting students in making informed data sharing decisions. Prior to reading the consent form for a study involving the evaluation of a collaborative learning application, one group of participants was primed to consider data sharing risks whereas the other group was not. The primed group scored lower on a consent form comprehension quiz yet had higher enrollment rates and were more likely to cite trust as reasoning for enrolling in the study.</p> <p>The data set is composed by:</p> <ul> <li>‘Classes’ spreadsheet: including the relation of flows, group of students, number of students, instructor id, day and time</li> <li>‘Participants’ spreadsheet: including the relation of ID (of each participant), if s/he consented, group class, flow and language</li> <li>‘Prior knowledge Survey’ spreadsheet: participant’s ID and ID, relevant prior knowledge questionnaire data (questions included).</li> <li>‘Quiz data’ spreadsheet: participant’s ID, quiz data and survey data (questions included)</li> <li>PDF including: <ul> <li>Table S1. Summary of participating classes </li> <li>Table S2. Consent form subsections and summaries </li> <li>Table S3. Consent form quiz questions, question types, and assigned points </li> <li>Table S4. Guiding questions in the prior knowledge questionnaire </li> <li>Table S5. Comparison of Flow A and Flow B quiz scores per question</li> </ul> </li> </ul>
Coded interviews - dataset - project: From dialog to deliberation. Non-public actors as (non)present participants in local decision-making
<p>Coded interviews - dataset. The interviews were conducted as part of the project <em>From dialog to deliberation. Non-public actors as (non)present participants in local decision-making, </em>financed within the framework of the Programme DIALOG by the Ministry of Science and Higher Education of the Republic of Poland, in the years 2018-2020 (project no. DIALOG 0163/2017). </p>
Decision-making, interactions and complexity across three cancer multidisciplinary teams
<p>Observational data on team decision-making, interactions, size and disciplinary composition, and case complexity. </p>
ESI_Electrifying Freight-Modeling the Decision Making Process for Battery Electric Truck Procurement
Open the record for dataset details and reuse information.
Fieldnotes for the UKRI-funded PhD project "Interiorising the borders of the nation: Civic education in Europe and the making of the Muslim citizen"
<p>The bulk of the data supporting this study is non-digital. It comprises 14 notebooks of handwritten ethnographic fieldnotes taken over a 24-month period of fieldwork in Germany between 2020 and 2022. The aim of this fieldwork was to understand the workings Germany's far-flung sector of 'civic education' (<em>politische Bildung</em>), and to conceptualise the normative agendas of citizenship and belonging operative in the contemporary Federal Republic in particular in relation to citizen-subjects interpellated as Muslim.</p> <p>These notes comprise participant observation at five different sets of sites:</p> <ul> <li>Dedicated state-funded training seminars for civic educators and social workers</li> <li>Projects of interreligious and intercultural dialogue</li> <li>Six neighbourhood youth centres</li> <li>A series of photography exhibitions commemorating the 'guest worker' labour migration agreement between Bonn and Ankara.</li> </ul> <p>The non-digital data supporting this study are stored by the author in a secure locker at the London School of Economics and Political Science.</p>
ESI_Electrifying Freight-Modeling the Decision Making Process for BET Procurement
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The Transformative Impact of Digital Technologies on Entrepreneurial Decision-Making and Strategic Adaptation
Open the record for dataset details and reuse information.
What Makes a Good Commit Message?
<p><strong>What-Makes-a-Good-Commit-Message?</strong></p> <p>This repository contains the main data and scripts used in "What Makes a Good Commit Message"</p> <p><strong>Dataset:</strong></p> <p>The folder dataset contains the following files.</p> <ul> <li> <p>literature survery.xlsx</p> <ul> <li>It contains the data of 46 relevant literature reviewed in this study (Section 3.2).</li> </ul> </li> <li> <p>Questionnaire.pdf</p> <ul> <li>It is the questionnaire sent to experienced contributors.</li> <li>It contains three questions.</li> <li>It also contains an example of the initialized questionnaire.</li> </ul> </li> <li>Frequency.pdf <ul> <li>It describes the number and proportion of occurrences of a category/subcategory.</li> </ul> </li> <li> <p>posts list.xlsx</p> <ul> <li>It contains all posts we studied in Sec. 3.2.</li> </ul> </li> <li> <p>sampled messages.csv</p> <ul> <li>It contains meta-information of 1649 labeled commit messages.</li> <li>label = 0 means a commit message contains "Why and What".</li> <li>label = 1 means a commit message contains "Neither Why nor What".</li> <li>label = 2 means a commit message contains "No What".</li> <li>label = 3 means a commit message contains "No Why".</li> <li>if_mulit_commit = 1 means a commit is non-atomic.</li> <li>new_message1 means a message after preprocessing.</li> </ul> </li> <li> <p>maintenance type and expression way.xlsx</p> <ul> <li>It contains the results of our RQ2: the expression ways of Why and What, as well as links to maintenance types.</li> </ul> </li> </ul> <p><strong>CommitMessage (Scripts):</strong></p> <p>The folder contains the following scripts files.</p> <ul> <li> <p>Preprocessor</p> <ul> <li>It contains the preprocessing of commit messages, including the replacement of token in the message, etc.</li> </ul> </li> <li> <p>ModelTraining</p> <ul> <li>It contains the code for our model training, that is, the implementation of different classification techniques.</li> </ul> </li> </ul>
Dataset related to article: "Comparative Accuracy of Bowel Ultrasound Versus Magnetic Resonance Enterography in Combination With Colonoscopy in Assessing Crohn's Disease and Guiding Clinical Decision-making"
<p>This record contains raw data related to article: "This record contains raw data related to article "Comparative Accuracy of Bowel Ultrasound Versus Magnetic Resonance Enterography in Combination With Colonoscopy in Assessing Crohn's Disease and Guiding Clinical Decision-making"</p> <p>The comparative accuracy of bowel ultrasound [US] versus magnetic resonance enterography [MRE] in combination with colonoscopy [CS] in assessing Crohn's disease [CD] and influencing the decision-making process is unknown.</p> <p>Methods:</p> <p>Consecutive ileo-colonic CD patients seen in a tertiary referral centre were prospectively assessed by MRE, CS, and bowel US, within 1 week. Sensitivity, specificity, accuracy, positive predictive value [PPV], and negative predictive value [NPV] of bowel US in assessing localisation, enhancement [presence of vascularisation at Power Doppler], active disease [presence of ulcers at colonoscopy], strictures, fistulas, and abscesses were calculated using CS + MRE findings together as a reference standard. Two blinded inflammatory bowel disease [IBD] specialists reviewed MRE and bowel US findings and were asked to decide the therapeutic strategy [continue versus change therapy]. Kappa agreement with clinical decision was calculated.</p> <p>Results:</p> <p>Sixty CD patients [36 with endoscopic disease activity, 28 with complications] were enrolled. For localisation, sensitivity, specificity, accuracy, PPV, and NPV of bowel US were 88%, 96%, 91%, 96%, and 85%, respectively; for enhancement, 87%, 92%, 89%, 93%, and 86%; for activity, 92%, 100%, 96%, 100%, and 94%; for strictures, 75%, 86%, 81%, 78%, and 83%; for fistulas, 100%, 98%, 98%, 66%, and 100%; for abscesses, 100%, 96%, 96%, 33%, and 100%. The concordance of management of CD patients based on bowel US or MRE findings, alone, compared with clinical decision, was 0.768 and 0.767, respectively [p <0.001]. The concordance between bowel US and MRE on management of CD patients was 0.800 [p <0.001].</p> <p>Conclusions:</p> <p>Bowel US is very accurate in assessing CD and is a non-invasive, easy-to-use tool to manage CD patients in clinical practice.</p>
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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.