Bibliographic record
Abstract
It is our pleasure to welcome you to the 2019 4th International Conference on Mechatronics and Electrical Systems (ICMES 2019) in Prague, Czech Republic on October 11-13, 2019. ICMES 2019 is a conference dedicated to topics in advances in aerospace and automotive, applied sciences and biosciences, biomechanics and medical technology, dynamic, vibration, acoustic and control system, control, robotics and mechatronics, artificial intelligence and intelligent control, etc. The proceedings present a selection of 13 papers submitted to the conference from universities, research institutes and industries. All of the papers were subjected to peer-review by conference committee members and international reviewers. Papers included in the proceedings have been selected according to quality and relevance to the conference themes. The proceedings aim to present to the readers recent advances in the field of mechatronics and control engineering and in various related areas. We would like to express our genuine gratitude to everyone who has contributed to ICMES 2019. The opening remark including a warm welcome to all participants has been given by Assoc. Prof. Jan Faigl, Czech Technical University (CTU), Czech. Our especially thanks to the international advisory committee, Prof. Chun-Yi Su, Concordia University, Canada, the program chairs, Prof. Juan M. Corchado, University of Salamanca, Spain, Assoc. Prof. Ahmed Abdelgawad, Central Michigan University, USA, all the technical committee members. Let us wish ICMES the same success for next year.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".