Notice bibliographique
Résumé
With the continuous progress of science and technology, the innovation and development in the fields of advanced manufacturing and materials engineering has become an important force to promote global industrial upgrading. It is against this backdrop that the 2024 10th International Conference on Applied Materials and Manufacturing Technology (ICAMMT 2024) gathered scholars, researchers, and industry experts in Guangzhou, China from May 22nd to 23rd, 2024 via hybrid form to share their insights and advancements in the domains of applied materials and manufacturing technology. ICAMMT is a premier interdisciplinary platform for the presentation of new advances and research results in applied materials and manufacturing technology. ICAMMT 2024 brought together leading scientists, researchers, practitioners, and other personnel to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the domains of interest from around the world to share their experiences and research results in advanced manufacturing and materials engineering, and exchange views. Themed around advanced manufacturing and materials engineering, the Conference set up a number of topics, including but not limited to: Research and Development of New Materials, Mechanical Behavior & Fracture, Advanced Forming Manufacturing and Equipment, Manufacturing Systems and Automation, Measure Control Technologies and Intelligent Systems, etc. Through in-depth discussion of these topics, the Conference gathered global wisdom and strength, and jointly promoted the innovative development of applied materials and manufacturing technology. The Conference agenda was designed to cater to a wide range of interests and expertise levels, including one main forum and two sub-forums. One of the highlights of the event was keynote speeches delivered by eight renowned experts in their respective fields at home and abroad. They discussed about the latest research results and experiences of advanced manufacturing technology and materials engineering, and shared their unique views on the development trend and research and development direction of the industry. Topics cover Discussion on Low-Carbon Development Approach of China’s Iron and Steel Industry (Prof. Liejun Li, South China University of Technology, China), High Performance Organic-Inorganichybrid Cement-Based Materials (Prof. Jiangxiong Wei, South China University of Technology, China), Applications of Light Alloys in Battery-Powered Electric Vehicles (Prof. Henry Hu, University of Windsor, Canada), Machine Vision and Human-Computer Interaction (Prof. Wei Xie, South China University of Technology, China), etc. These speeches not only provided a comprehensive overview of the latest trends and developments but also offered insights into the potential challenges and opportunities that lie ahead. Last but not the least is our gratitude. We would like to express our sincere thanks to all the authors, speakers, committee members, supporters, and all those involved for the complete success of the Conference, which has then given rise to this Proceedings of selected papers. Special thanks to the members of Journal of Physics: Conference Series for their efforts in making this volume published. The Committee of ICAMMT 2024 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 | 0,002 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,005 | 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) | 0,591 | 0,434 |
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 ».