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Presentations for the Canadian Hydrographic Conference

2020· article· en· W7005357395 sur OpenAlexaboutno aff

Notice bibliographique

RevueUniversity of New Hampshire Scholars Repository (University of New Hampshire at Manchester) · 2020
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueLepidoptera: Biology and Taxonomy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLeverPhotogrammetryBathymetryLidarCalibrationAerial surveyInertial navigation systemGlobal Positioning System
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Casey O'Heran Title: Horizontal Calibration of Vessel Lever Arms Using Unmanned Aircraft Systems (UASs) Knowledge of lever arm distances from sonars, mounted on vessels, to systems such as Inertial Measurement Units (IMUs) and Global Navigation Satellite Systems (GNSS) is crucial for accurate ocean mapping applications. Traditional methods, such as laser scanners or total stations, are used to determine professional survey vessel lever arm distances reliably. However, for vessels of opportunity that are collecting volunteer bathymetric data, it is beneficial to consider survey methods that are less time consuming, less expensive, and which do not involve bringing the vessel into a dry dock. With the development of Unmanned Aircraft Systems (UASs) in the field of mapping, more cost-effective and quicker surveys can be conducted. To investigate the feasibility of conducting accurate horizontal lever arm surveys of vessels, while maximizing time efficiency in data collection, UAS surveys of a vessel with calibrated lever arm distances were conducted using both Structure for Motion (SfM) photogrammetry and aerial LiDAR while the vessel was docked at the pier. Estimates of the horizontal uncertainties, for both methods, were obtained by comparing the horizontal distances between targets acquired by the UAS methods to ground-truth measurements of lever distances from survey-grade laser scanning of the vessel. With the use of Ground Control Points (GCPs), horizontal uncertainties of both the photogrammetry and LiDAR models are on the order of centimeters, with the LiDAR model being slightly higher in horizontal uncertainty than most of the photogrammetry models. Ivan Guimaraes Title: Calibrating Broadband Multibeam Seabed Backscatter Standard calibration procedures for multibeam sonars currently only address the fidelity of the bathymetric data. Equivalent effort is needed to ensure that the acquired seabed backscatter strength measurements are referenced to a similarly precise level. This project presents an operational method utilizing multiple pre-calibrated split beam echo sounders covering a wide range (50-400 kHz) of frequencies. This is needed to cover the full range of frequencies utilized by multi-sector multibeams operating in continental shelf depths. Roland Arsenault Title: A mapping focused open-sourced software framework for Autonomous Surface Vehicles A software framework, dubbed “Project 11”, was developed as a backseat driver for Autonomous Surface Vehicles (ASVs). Key design features include the ability to quickly and easily specify survey plans; monitoring of mission progress, even over unreliable wireless networks; and to provide an environment to develop advanced autonomous technologies. Presenter Bio Casey O’Heran earned his B.S. in Surveying Engineering from Ferris State University in Big Rapids, Michigan. During his time there, he participated in projects that exposed him to geospatial data acquisition using land surveying methods and data fusion. His studies also exposed him to the theory of multispectral LIDAR, echo sounders, and their ability to collect bathymetric data. This exposure sparked his interest in bathymetric data acquisition and ocean mapping. Casey is now pursuing a master’s degree in Ocean Engineering with a focus on Ocean Mapping. This experience positions Casey to utilize developed skill sets in both terrestrial land surveying and hydrographic sciences in the open market. Ivan Bodra Guimaraes graduated with a degree in Naval Sciences–Major Electronics from the Brazilian Naval Academy in 2008, and specialized in Hydrography (Cat. "A") in the Directory of Hydrography and Navigation of the Brazilian Navy in 2011. He worked on Brazilian hydrographic researcher ships from 2009 to 2018, operating with singlebeam and multibeam echosounders and sidescan sonar in offshore, coastal, and shallow waters, and rivers. Ivan will be working mainly with tides, as that is an important aspect to be considered in hydrographic surveys on shallow and coastal waters and on rivers, at some point. Roland Arsenult joined CCOM/JHC in 2000. He received his Bachelor's degree in Computer Science and worked as a research assistant with the Human Computer Interaction Lab at the Department of Computer Science, University of New Brunswick. As a member of the Data Visualisation Research Lab, he combines his expertise with interactive 3D graphics with his experience working with various mapping related technologies to help provide a unique perspective on some of the challenges undertaken at CCOM/JHC.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,741
Score d'incertitude au seuil0,711

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,003
Études des sciences et des technologies0,0040,001
Communication savante0,0040,002
Science ouverte0,0010,003
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,5020,136

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,033
Tête enseignante GPT0,211
Écart entre enseignants0,178 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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Même revueUniversity of New Hampshire Scholars Repository (University of New Hampshire at Manchester)Même sujetLepidoptera: Biology and TaxonomyTravaux en français237 207