Bibliographic record
Abstract
11-14 December 2019 Bangkok, Thailand Conference Website: https://www.isegt.org SEGT 2019 Conference The International Conference on Sustainable Energy and Green Technology 2019 was held at Millenium Hilton Bangkok, Bangkok from 11-14 December 2019. The conference was co-organized by 6 research centres across the Asian region, i.e. Centre for Energy Sciences (UM), The Joint Graduate School of Energy and Environment (KMUTT), Centre for Vehicular Technology (UTAR), Center of Excellence on Energy Technology & Environment (KMUTT), Center of Inter-Integration (NIU), Research Center of Energy Conservation (Taipei Tech) and United Nations Environment Programme (UNEP). Besides, there were others supporting institution such as National I-Lan University, University of Malaya, UTAR, King Mongkut’s University of Technology Thonburi, National Cheng Kung University, Xi’an Jiatong University, Huazhong University of Science and Technology, Beijing Institute of Technology, De La Salle University, National Dong Hwa University, The University of Hong Kong, City University of Hong Kong, Universiti Teknologi Malaysia, ASHRAE Thailand Chapter and International Association for Hydrogen Energy. SEGT 2019 Conference welcomed more than 500 participants. These participants representing institutions from 35 countries over the world such as Malaysia, Thailand, Canada, Taiwan, Singapore, Philippines, Indonesia, Hong Kong, China, India, Iran, South Africa, France, Nigeria, Vietnam, Japan, Pakistan, South Korea, New Zealand, Australia, Nepal, Norway, Myanmar, UK, Bangladesh, Czech Republic, Netherlands, Turkey, Saudi Arabia, Pakistan, Sri Lanka, Spain, Namibia, US, Mexico, etc. There are 2 Plenary Speakers (Prof. Ibrahim Dincer from University of Ontario Institute of Technology and Prof. Jiri Jaromir Klemes from Brno University of Technology), 5 Keynote Speakers (Prof. Somchai Wongwises, Prof. Wei-Hsin Chen, Prof. Jo-Shu Chang, Prof. Meng Ni, and Prof. Jamal Chaouki) and 2 Invited Speakers (Mr. Wallop Lamlertpongpana and Mr. Warot Lamlertpongpana) from ASHRAE attended the conference. The conference topics are: • New and Renewable Energy • Sustainable Technologies for Energy Conversion • Environment and Climate Change • Energy Management, Policy, Economics and Sustainability • Energy Sciences • Energy Storage and Power Engineering • Sustainable Cities, Architecture and Green Buildings • Green Design, Products and Manufacturing Processes • Green Materials • Waste Management and Waste Water Treatment • Heating, Ventilation and Air Conditioning (HVAC) • Smart Grid / Smart City / Smart Mobility • Bioresource and Bioenergy Editors (SEGT 2019 IOP-EES Conference Proceedings) Chong Wen Tong Wang Chin-Tsan Bernard Saw Lip Huat XianBo Xiang
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.727 | 0.569 |
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 source (direct Gemma or distilled Codex), 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".