Notice bibliographique
Résumé
These Proceedings present the written contributions of the participants of the 2023 2nd International Conference on Electrical, Control and Information Technology (ECITech 2023) which was held in the form of virtual conference from 24th to 26th February 2023, at the Changsha city, China, supported by Concordia University, Canada. This was the second version of the annual meeting that began in 2022, with about 50 participants. The Proceedings consist the contributions that were presented as speeches or presentations at the Conference. All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Proceedings Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. The topics of papers collected in this volume cover but are not limited to: Electromagnetic Compatibility, High Voltage Insulation Technologies, System Engineering Theory and Method, Intelligent Manufacturing and Industrial Intelligence, Intelligent Robots and Autonomous Agents, Information Technology Management, etc.. The three-day scientific program of the ECITech 2023 consisted of Keynote Speeches, Oral Presentations, Poster Presentations and Academic Investigation with the participation of graduate students, professors, researchers and entrepreneurs from China, Canada, Italy, UK, Kuwait, Spain, Turkey, Iran, Malaysia, India, among others. Moreover, the objective of ECITech was to bring together national and international researchers in order to establish a network of scientific cooperation with a global impact in the area of the electrical, control and information technology; to promote the exchange of creative ideas and the effective transfer of scientific knowledge, from fundamental research to innovation applied to electrical solutions and to advance in the development of new research by means of efficient transference of the knowledge between sectors academia and industry. At the keynote speech part of the Conference, Prof. Marco C. Campi (University of Brescia, Italy) provided a general and easy-to-access overview of the VRFT method in his report Virtual Reference Feedback Tuning (VRFT): Handy Tuning of Industrial Controllers. And Prof. Chun-Yi Su (Concordia University, Canada) discussed a newly proposed modeling and parameters learning of dielectric elastomer enabled soft robots via data-in-loop approach, showing the status of the art of the current research for modeling of the smart-material based soft robots. The speakers’ brilliant speeches made the attendees feel like bathing in a feast of knowledge. We would like to thank the members of reviewers for their kind assistance in reviewing the papers. We would also extend our best gratitude to keynote speakers for their invaluable contribution and worthwhile ideas shared in the Conference. Special acknowledgements go to the Editors and staff of the Journal of Physics: Conference Series for their hard work in making this volume published. We hope that the series conference of ECITech will be even greater than ever before in the future! The Committee of ECITech 2023 List of Committee Member is 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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,006 | 0,004 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,544 | 0,398 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».