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291 results for “chaptering”
VALIDATION OF THE CHAPTER "ALLERGIES AND HYPERSENSITIVITY" OF THE INTERNATIONAL DISEASE CLASSIFICATION (CIM)
ClinicalTrials.gov study NCT03213808. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
CHAPTER: Clonal Haematopoiesis Assessment: Prevention, Treatment and Research
ClinicalTrials.gov study NCT07313059. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Datasets to chapter 5 (dissertation version)
<p>Contains data files on which analysis and results of chapter 5 of my dissertation were based. Upon acceptance of the article, data and metadata will become publicly available.</p>
Chapter 7. Methanotrophic flexibility of 'Ca. Methanoperedens' and its interactions with sulfate-reducing bacteria in the sediment of meromictic Lake Cadagno
<p>Supplementary Tables 2-21</p>
Chapter 3 Exploring cultivation strategies for mycelium-based materials
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Supplementary Material Chapter IV
<p>Supplementary Material Chapter IV.</p> <p>Figure S1 is shown.</p>
Valle Crucis Abbey, Chapter House LiDAR 01
heres my first try with ipad pro / polycam on a fairly complex space to capture. unwanted meshes were caused when the scan picked up areas at a distance, ill be learninh how to improve on this Created with Polycam Source: Objaverse 1.0 / Sketchfab
IPBES Transformative Change Assessment Chapter 5 - Interactive Figure 5.19
<p>To view the figure interactively, please download the html and view it locally in your browser.</p>
Chapter 2 Raw Data
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Chapter 3 Raw Data
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The Role of Safety in IVHM - Chapter 9
When we address safety in a book on the business case for IVHM, the question arises whether safety isn’t inherently in conflict with the need of operators to run their systems as efficiently (and as cost effectively) as possible. The answer may be that the system needs to be just as safe as needed, but not significantly more. That begs the next question: How safe is safe enough? Several regulatory bodies provide guidelines for operational safety, but irrespective of that, operators do not want their systems to be known as lacking safety. We illuminate the role of safety within the context of IVHM.
Algorithms and their Impact on Integrated Vehicle Health Management - Chapter 7
This chapter discussed some of the algorithmic choices one encounters when designing an IVHM system. While it would be generally desirable to be able to pick a particular set of algorithms for a particular problem, the reality is a bit more complex. Depending on the budget, the performance requirements, the computational constraints, sensor availability, access to historical data, operational and environmental conditions, robustness to changing system configurations, algorithm maintenance needs, etc., no one algorithm will perform best in all situations. Indeed, it is necessary to evaluate these constraints during the algorithm design process and determine the best choice on a case-by-case analysis. The trade-offs between different choices are very real, and sometimes no solution can be found, which means that some of the constraints have to be relaxed. The simplest solution is generally preferred over a more complex one, but it is also important to consider that there is no free lunch. Finally, any health management solution also has to undergo verification and validation (V&V) and, in some cases, certification. Some of these issues are topics of other chapters in this book.
Basic Principles - Chapter 6
This chapter described at a very high level some of the considerations that need to be made when designing algorithms for a vehicle health management application. The choices made here affect the quality of the diagnosis and prognosis (covered in Chapter 7). Therefore, the algorithmic design choices are made in conjunction with the design choices for diagnostics and prognostics to optimally support these tasks. Furthermore, additional considerations imposed by computational constraints, resource availability, algorithm maintenance, need for algorithm re-tuning, etc. will impact the solutions. It should also be noted that technological advances, both in hardware and software, impose the need for new solutions. For example, as new materials and new sensors are being developed, the algorithmic solutions will need to follow suit. In general, there seems to be a trend to have more sensor data available. While this is potentially a good thing, sensor data provides value only when it is being processed and interpreted properly, in part by the techniques described here. Testing of the methods, however, requires the “right” kind of data. Generally, there is a lack of seeded fault data which are required to train and validate algorithms. It is also important to migrate information from the component to the subsystem to the system levels so that health management technologies can be applied effectively and efficiently at the vehicle level. It may be required to perform elements described in this chapter between different levels of the vehicle architecture.
Diamond Throne image sequence [chapter 14] 29/04/2020
<p><em>Precious Treasures from the Diamond Throne</em> (London: British Museum Press, 2020), image sequence 29/04/2020.</p>
Sociological Books and Book Chapters indexed in Thomson Scientific's Book Citation Index by country and language
<p>Distribution of book chapters and books indexed in Thomson Scientific's Book Citation Index within the Web of Science subject category "Sociology" by language and country.</p>
Datasets to chapter 4 (dissertation version)
<p>Contains data files on which analysis and results of chapter 4 of my dissertation were based. Upon acceptance of the article, data and metadata will become publicly available.</p>
Thermal Chapter Data
<p>Data for chapter 3</p>
Transformative Change Assessment Chapter 1 Evidence Causes Data Package
<p>Data Package for <strong>Transformative Change Assessment Chapter 1 Evidence Cause</strong> technical report.</p>
Supplementary Tables S1-S3 from PhD thesis Evi Wubben, Chapter 5
<p>Supplementary Tables S1-S3 from PhD thesis Evi Wubben, Chapter 5</p> <p><strong>Table S1 </strong><em>Sites of which the (sub)surface temperature records are incorporated in the Early to Middle Miocene compilation for this study.</em></p> <p><strong>Table S2 </strong><em>100-kyr bins used for amplification factor calculations.</em></p> <p><strong>Table S3 </strong><em>400-kyr bins used for amplification factor calculations.</em></p>
Supplementary Information Chapter 1 PhD Thesis
<p>Video corresponding to Supplementary Information - Video from 1 to 8 of the Chapter 1 of the Phd Thesis</p>
ScienceDex guides
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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.