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Enregistrement W4207042095 · doi:10.1088/1742-6596/2174/1/011001

Preface

2022· article· en· W4207042095 sur OpenAlexaboutno aff

Notice bibliographique

RevueJournal of Physics Conference Series · 2022
Typearticle
Langueen
DomaineComputer Science
ThématiqueAdvanced Technology in Applications
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGlobeChinaCoronavirus disease 2019 (COVID-19)Political scienceLibrary scienceBeijingPandemicEvent (particle physics)Public relationsMedical educationEngineeringMedicineComputer scienceLaw

Résumé

récupéré en direct d'OpenAlex

The 9th International Conference on Advanced Manufacturing Technology and Materials Science (AMTMS 2021) was planned to be held on November 19-21, 2021 in Beijing, China. Considering the COVID-19 pandemic, the AMTMS 2021 conference was held virtually as agencies around the world are now issuing restrictions on travel, gatherings, and meetings to limit and slow the spread of this pandemic. The health and safety of our participants and members of our research community is of top priority to the Organizing Committee. Therefore, the AMTMS 2021 conference was held online through Zoom software. AMTMS 2021 is being organized by Beihang University to provide an opportunity to research scholars, delegates, and students to interact and share their experience and knowledge in Advanced Manufacturing Technology and Materials. We sincerely welcome all scientists, scholars, students, industrialists to attend and explore their knowledge in the field of Functional Materials and Applied Technologies. We strongly believe that AMTMS 2021 was a remarkable event which can bring together professors, researchers, and students in the field of functional materials and applied technologies making the conference a perfect platform to share experience, foster collaborations across industry and academia, and evaluate emerging technologies across the globe. More than 150 participants attended the online conference, they were from China, Canada, Malaysia and more. During the conference, the conference model was divided into three sessions, including oral presentations, keynote speeches, and online Q&A discussion. In the first part, some scholars, whose submissions were selected as the excellent papers, were given about 5-10 minutes to perform their oral presentations one by one. Then in the second and third part, keynote speakers were each allocated 30-45 minutes to hold their speeches. In the keynote speeches part, we invited four professors as our keynote speakers. Prof. Lu Li, National University of Singapore. Dr. Lu’s research interests include nanostructured materials, and functional thin films such as all-solid-state micro batteries and ferroelectric thin films. And then we had Prof. Sung-Hoon Ahn (CIRP Fellow), Seoul National University, South Korea. Dr. Ahn’s research interests include soft robotics, smart/composite materials, micro/nano fabrications, 3D/4D printing, smart factory, green manufacturing, renewable energy, smart grid, and appropriate technology. Prof. Lihui Lang, our third keynote speakers, from Beihang University, China. He mainly focuses on automotive, aircraft and aerospace fields. And then we invited Prof. Jiangfeng Ni, from Soochow University, China as our finale keynote speaker. At present Dr. Ni is leading a team working on various types of energy storage systems including rechargeable batteries, supercapacitors, with a focus on fundamental physics, chemistry, and materials in these devices. Their insightful speeches had triggered heated discussion in the third session of the conference. Every participant praised this conference for disseminating useful and insightful knowledge. The proceedings are a compilation of the accepted papers and represent an interesting outcome of the conference. Topics include but are not limited to the following areas: Materials Processing Technology and Materials Science, Manufacturing Technology and Systems and Other related topics. All the papers have been through rigorous review and process to meet the requirements of International publication standard. This year, we have all worked and lived with the daily threat of Covid-19, the need for social distancing and relative isolation has impacted upon the familiar and fundamental nature of conferences. Regardless, such interactions are the lifeblood of our respective communities, and so we made the decision to proceed with the Workshop, bring participants together from around the world through a digital platform. We would like to acknowledge all of those who supported AMTMS 2021. The help and contribution of each individual and institution was instrumental in the success of the conference. We would like to thank the organizing committee for its valuable inputs in shaping the conference program and reviewing the submitted papers. The Committee of AMTMS 2021 List of Committee member are available in this pdf.

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)0,002
score de la tête « metaresearch » (Gemma)0,011
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: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,487
Score d'incertitude au seuil0,000

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,011
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0030,002
Études des sciences et des technologies0,0040,001
Communication savante0,0040,004
Science ouverte0,0020,003
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,5130,347

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 Opus0,020
Tête enseignante GPT0,253
Écart entre enseignants0,233 · 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
GenreÉditorial

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
Publié2022
Routes d'admission1
Résumé présentoui

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