Beijing Institute Of Technology Research Articles

Cluster Preface: Synthesis of Energetic Molecules

Haifeng Huang is a professor at Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, P.R. China. He received his Ph.D. in 2012 from Beijing Institute of Technology (BIT) under the guidance of Prof. Zhiming Zhou. Then, he joined Shanghai Institute of Organic Chemistry to start his academic career. His research interests mainly focus on the design and synthesis of new energetic materials. Jun Yang received his Ph.D. at Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences in 2005 under the supervision of Prof. Minzhi Deng. He is now a professor of the Shanghai Institute of Organic Chemistry, CAS. His research interests primarily include the synthesis of energetic materials and energy regulation materials for solid and liquid propellants.

Preface

10 - 13 December 2023 Ho Chi Minh City, Vietnam Conference Website: https://www.isegt.org SEGT 2023 The International Conference on Sustainable Energy and Green Technology 2023 is being held in Ho Chi Minh City, Vietnam, from 9-13 December 2023. The conference is co-organized by Universiti Malaya, Vietnam National University Ho Chi Minh City-University of Science, Universiti Tenaga Nasional (UNITEN), and Universiti Tunku Abdul Rahman (UTAR). Additionally, there are other supporting institutions such as 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, and the International Association for Hydrogen Energy. SEGT 2023 welcomed more than 350 participants, representing institutions from 25 economies worldwide, including Malaysia, Thailand, Canada, Taiwan, Singapore, the Philippines, Indonesia, Hong Kong, China, India, Vietnam, South Korea, New Zealand, Australia, Poland, the UK, the Netherlands, Turkey, Saudi Arabia, the US, etc. There are two plenary speakers: Prof. Ibrahim Dincer from Ontario Tech University and Prof. Niu JianLei from The Hong Kong Polytechnic University. Additionally, six keynote speakers include Mr. Tien Q. Duong, Dr. Luan Quoc Huan, Prof. Wei-Hsin Chen, Prof. Fariborz Haghighat, Prof. Dennis Leung, and Prof. Michael K.H. Leung. Furthermore, there are five special sessions organized by Prof. Qihong Deng, Prof. Talal Yusaf, Dr. Xiao-Qing Yang, Dr. Hiang Kwee Lee, Prof. Hyung-Ho Park, Dr. Viyak G. Parale, and Prof. Chang Jo-Shu. List of Committee of SEGT 2023 and Group photo are available in this pdf.

Итоги работы российско-китайского экспертного семинара «Развитие научной дипломатии в Арктике в условиях глобальных вызовов»

The review summarizes the results of the Russian-Chinese expert seminar “Development of Science Diplomacy in the Arctic under the Global Challenges”, which was organized in December 2023 in Arkhangelsk, Russia. The aim of the seminar is described: accumulation of intellectual resources of universities and scientific institutes of Russia and China. The need to unite the scientific potential of the two countries is determined by the current geopolitical context, in which the development of relevant functional solutions to international humanitarian issues becomes extremely important. The seminar was organized by the Northern (Arctic) Federal University named after M.V. Lomonosov together with the project partners — Beijing Institute of Technology (PRC) and the Association “National Arctic Scientific and Educational Consortium” within the framework of the project of the Alexander Gorchakov Public Diplomacy Fund. The event resulted in a final document (recommendations) on further development of Russian-Chinese cooperation in the Arctic.

Non-Intrusive Speech Quality Assessment Based on Deep Neural Networks for Speech Communication.

Traditionally, speech quality evaluation relies on subjective assessments or intrusive methods that require reference signals or additional equipment. However, over recent years, non-intrusive speech quality assessment has emerged as a promising alternative, capturing much attention from researchers and industry professionals. This article presents a deep learning-based method that exploits large-scale intrusive simulated data to improve the accuracy and generalization of non-intrusive methods. The major contributions of this article are as follows. First, it presents a data simulation method, which generates degraded speech signals and labels their speech quality with the perceptual objective listening quality assessment (POLQA). The generated data is proven to be useful for pretraining the deep learning models. Second, it proposes to apply an adversarial speaker classifier to reduce the impact of speaker-dependent information on speech quality evaluation. Third, an autoencoder-based deep learning scheme is proposed following the principle of representation learning and adversarial training (AT) methods, which is able to transfer the knowledge learned from a large amount of simulated speech data labeled by POLQA. With the help of discriminative representations extracted from the autoencoder, the prediction model can be trained well on a relatively small amount of speech data labeled through subjective listening tests. Fourth, an end-to-end speech quality evaluation neural network is developed, which takes magnitude and phase spectral features as its inputs. This phase-aware model is more accurate than the model using only the magnitude spectral features. A large number of experiments are carried out with three datasets: one simulated with labels obtained using POLQA and two recorded with labels obtained using subjective listening tests. The results show that the presented phase-aware method improves the performance of the baseline model and the proposed model with latent representations extracted from the adversarial autoencoder (AAE) outperforms the state-of-the-art objective quality assessment methods, reducing the root mean square error (RMSE) by 10.5% and 12.2% on the Beijing Institute of Technology (BIT) dataset and Tencent Corpus, respectively. The code and supplementary materials are available at https://github.com/liushenme/AAE-SQA.

The Influence of AI ChatGPT on Improving Teachers' Creative Thinking

The latest technologies, such as Artificial Intelligence (AI), have emerged as pivotal tools for fostering creativity, aiding in the development of novel and interactive pedagogical methods, and catalysing innovation within the educational process. The integration of technology into education opens avenues for creative expression and the cultivation of creative skills among students. Investigating the cognitive styles of educators is imperative for adapting instructional strategies, as divergent modes of thinking can impact the efficacy of teaching and facilitate the customization of approaches in pedagogy. In this article, the predominant type of thinking among student teachers is investigated, the average level of creativity is determined, and the potential influence of employing an innovative method - ChatGPT - on the creative abilities of future educators is explored. The study sample consisted of (450) university teachers at three universities, Udmurt State University (Izhevsk, Russia), Peoples' Friendship University of Russia (Moscow, Russia), and Beijing Institute of Technology (Beijing, China). Participants were invited to participate in two assessments: J. Bruner's test on thinking styles, and a proprietary questionnaire designed to gather additional insights into the perception and influence of ChatGPT on creative potential. This research employed a quantitative approach. The study revealed that 70% of the surveyed student teachers exhibited a sign-oriented type of thinking. The experimental findings indicated a moderate level of creativity among these students. Only 28% of the participants demonstrated a high degree of creativity. In contrast, educators who utilized the developed programme exhibited a higher level of creative ability and better performance compared to teachers in the control group. This suggests that the incorporation of ChatGPT in education exerts a positive influence on enhancing educators' outcomes when compared to conventional teaching methods. The practical significance of this study lies in its contribution to expanding knowledge about the impact of ChatGPT on the development of creative potential. It underscores the importance of employing contemporary information and communication technologies in the preparation of future teachers.

Digital Finance & Green Innovation Review Paper with special reference to Oman and Bibliometric Analysis for the Duration of 2017-2023

This bibliometric analysis highlighted the transformative role of blockchain technology in reshaping the banking sector and amplifying its value for stakeholders. Using data extracted from the Dimension AI database, the study centers on English-language articles from 2017 to 2023, which were processed and visualized using Excel and Vos-viewer. The annual publication growth rate in Digital Finance and Green Innovation stood at 33.74%. A peak of 1,197 citations in 2022 marks heightened scholarly engagement. Diverse citation counts across articles underscore the varied academic impact. Journals like 'Technological Forecasting and Social Change' are pivotal, with "Energy Policy" distinguishing itself in volume and impact. The Beijing Institute of Technology and North China Electric Power University emerge as influential contributors, with China, the US, and the UK leading globally in publications. Thematically, the synthesis of fintech, sustainability, innovation policy, and green finance signals the domain's depth and interdisciplinarity. Exploring economic, environmental, societal, and policy facets of Digital Finance and Green Innovation is imperative.

Preface

ICPMS (International Conference on Physics, Mathematics and Statistics) is an annually held conference for all researchers at home and abroad since 2018, aiming to provide a good platform for scholars and researchers in the field of physics, mathematics and statistics to discuss the latest developments and achievements, work out good solutions, and make contributions.The 6th International Conference on Physics, Mathematics, and Statistics (ICPMS 2023) was held online from May 20 to 21, 2023 for academic exchanges and discussions.There were over 30 participants from 4 different countries and regions, including China, Brazil, and Malaysia, attending ICPMS2023. The conference program was divided into 3 sessions: keynote speeches, oral presentations, and poster presentations. We greatly appreciate Prof. Wanyang Dai from Nanjing University, who presided over the conference, and all participants for attending and sharing!We are honored to invite 6 experts to give impressive keynote speeches: Professor Rongming Wang from Beijing University of Science and Technology, China; Prof. Le Fang from Beihang University, China; Prof. Fujun Zhang from Beijing Jiaotong University, China; Prof. Jianhua Zeng from University of Chinese Academy of Sciences, China; Asso. Prof. Jingya Sun from Beijing Institute of Technology, China, and Asso. Prof. Elammaran Jayamani from the Swinburne University of Technology Sarawak Campus, Malaysia.Following the keynote speakers, 3 scholars made oral presentations respectively in the afternoon. And 9 poster presentations came after it. Reporters shared their latest research findings and audiences were actively involved in discussions.We would like to express our gratitude to the reviewers of these manuscripts, who provided their time and expertise to review papers and facilitate the smooth running of ICPMS. We are extremely grateful to the organizers, technical program committee, and editors and extend our most sincere thanks to all the authors for their excellent contribution and work and to participants for their active attendance. Our sincere thanks also go to the IOP Publishing editors and managers for their helpful cooperation during the preparation of the proceedings.On behalf of the Organizing Committee of ICPMS 2023.List of Technical Program Committee are available in this pdf.

Voice Series: Interview with Professor Dr. Kun Qian, School of Medical Technology, Beijing Institute of Technology, China

Voice Series: Interview with Professor Dr. Kun Qian, School of Medical Technology, Beijing Institute of Technology, China

Analysis on research trends with dust explosions by bibliometric approach

Highly destructive combustible dust explosions, which is prone to cause secondary explosion, has been a concern in industrial processes. To understand the current development and status of research on dust explosions, 1276 publications related to dust explosions from 1998 to 2021 were indexed through the Web of Science Core Collection database. CiteSpace and VOSviewer were used to visualize and analyze the collected literature information. The number of articles related to dust explosions has increased from 12 in 1998 to 191 in 2021. China, the United States, and Canada are the major contributors in this field. Dalhousie University, Beijing Institute of Technology, and Dalian University of Technology are at the core of dust explosion research. Wei Gao, Paul Amyotte, and Chi-Min Shu are the most prolific researchers. Journal of Loss Prevention in the Process Industries, Powder Technology, and Process Safety and Environmental Protection are the major sources of publications related to dust explosions. The research topic of dust explosions mainly evolves into four aspects: explosion characteristics and influencing factors, research media, explosion suppression, and numerical simulation. New research hotspots have appeared related to gas–dust hybrid mixtures, nanomaterials, and powder suppressants. The results can help researchers in the dust explosion field to quickly determine the research frontier and the overall situation.

Guest Editorial: Learning, optimisation and control of cyber‐physical systems

Guest Editorial: Learning, optimisation and control of cyber‐physical systems

Letter to the Editor: Cost Utility of Schlemm Canal Microstent Injection With Cataract Surgery for Open Angle Glaucoma in the US Medicare System.

†Beijing Institute of Ophthalmology, Beijing, China *Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing, China ‡School of Information and Electronics, Beijing Institute of Technology, Beijing, China Disclosure: The authors declare no conflict of interest.

A Scientometric Analysis of Energy Management in the Past Five Years (2018–2022)

Energy management is an essential part of the integration of renewable energy in energy systems, electric vehicles, energy-saving strategies, waste-heat recovery, and building energy. Although many publications considered energy management, no study addressed the connection between scientists, organizations, and countries. The present study provides a scientometric analysis that addresses the trend of publications and worldwide dynamic maps of connectivity and scientists, organizations, and countries and their contribution to energy management. The results showed that Javaid Nadeem published the most papers in the field of energy management (90) while Xiao Hu received the most citations (1394). The university with the highest number of publications in energy management is the Islamic Azad University (144 papers), while the Beijing Institute of Technology has received the most citations (2061 citations) and the largest h-index (28). China and the United States are in the first and second rank in terms of total publications, citations, and h-index. Pakistan has the most publications relative to the country’s research and development investment level. The maps of co-authorship show islands of isolated groups of authors. This implies that the researchers in energy management are not well-connected. Bibliographic coupling of countries revealed China and USA are influential contributors in the field, and other countries were coupled mostly through these two countries.

The first International Conference on Mechanical System Dynamics grandly convened in Nanjing, China

The first International Conference on Mechanical System Dynamics grandly convened in Nanjing, China

Bibliometric analysis of finance and natural resources: past trend, current development, and future prospects.

The finance and natural resources revenue nexus play a critical role in an economy. The recent development and significant increase in academic literature regarding the resource-finance nexus are the primary motivations for conducting this study. This study aims to conduct a bibliometric analysis of 363 documents published between 1976 and 2021 collected from the Scopus database. The results have been demonstrated via graphs, tables, knowledge maps about the past trends, growth, and prospects using co-occurrence, co-authorship, and co-citation analysis via the VOSviewer tool. This study has identified prolific authors, journals, countries, academic institutions, and future pathways. The findings indicate that China has the highest share of publications (88, 24.2%), followed by Pakistan (58, 15.9%) and Turkey (37, 10.2%). The most productive academic institution is the Beijing Institute of Technology in China (13, 3.6%). This study proposes new avenues for further research concerning the resource-finance nexus, such as ecological footprint, sustainability, fiscal decentralization, green investment, energy prices, environmental quality, technological innovation, financial resource curse (especially the stock market resource curse), human capital, and renewable energy in policy development and sustainability towards the achievement of the SDGs.

Analysis of Electric Vehicle Battery State Estimation Using Scopus and Web of Science Databases from 2000 to 2021: A Bibliometric Study

This paper presents a bibliometric analysis of battery state estimation in electric vehicles. In this paper, a quick study is performed on the top global research contributors, funding agencies, and affiliate universities or institutes performing research on this topic while also finding the top keyword searches and top authors based on the most citations in the field of electric vehicles. Trend analysis is done by using the SCOPUS and Web of Science (WOS) databases (DB) from the period of 2000 to 2021. Battery state estimation plays a major role in the battery present state based on past experience. Battery available charge and health knowledge is a must for range estimation and helps us acknowledge if a battery is in useful condition or needs maintenance or replacement. A total of 136 documents in SCOPUS and 1311 documents in Web of Science were analyzed. Through this bibliometric analysis, we learn the top authors, country, publication journal, citation, funding agency, leading documents, research gap, and future trends in this research direction. The author Xiong Rui has the most publications, and he is working at the Beijing Institute of Technology, China. The most common institution is the Beijing Institute of Technology, and China is the most highly contributing country in this research. Most of the publications are conference types in SCOPUS DB and article types in WOS DB. The National Natural Science Foundation of China provides the most funding. The journal Energies has the most publications related to this field. The most cited works are by the authors M.A. Hannan and L.G. Lu in SCOPUS and WOS DB, respectively. A statistical analysis of the top ten countries’ productivity results is also discussed.

GTOC 11: Results found at Beijing Institute of Technology and China Academy of Space Technology

This paper presents the crucial method for the results found at Beijing Institute of Technology and China Academy of Space Technology in the 11th Global Trajectory Optimization Competition (GTOC-11). To build 12 solar-power stations placed in the “Dyson Ring” orbit around the Sun, GTOC-11 focuses on the flyby trajectory design, low-thrust trajectory optimization, and target assignment problem. The mission with time and state constraints causes many difficulties in the design and optimization, which is performed in the following four steps. The first step is to design the orbital elements of the “Dyson Ring” by the grid search method. An approximate model is utilized to evaluate the minimum transfer time for each candidate at first, and the accurate solutions are obtained by the indirect method. The second step involves the Mother Ship trajectories design. A large quantity of earth-to-asteroid and asteroid-to-asteroid subsequences are generated by parallel beam search. The complete trajectories of Mother Ship are designed by connecting the subsequences using beam search. The third step involves the station assignment problem, which is required to design the asteroid transfer device activation epoch and the target station assignment. Based on the results above, the last step involves the rendezvous trajectories optimization to obtain the accurate thrust direction profile. Finally, the submitted and post-competition results are reported.

Investigating the Use of C/SiC Ceramic Composites in an Innovative Light-Water Reactor Core Grouping Catcher

China Nuclear Power Engineering, Northwestern Polytechnical University, and Beijing Institute of Technology have undertaken a joint research work with the goal of developing corium retention containers for use in an innovative light-water reactor core grouping catcher (CGC). In Serious Accidents (SAs), the corium will be retained in the C/SiC ceramic composite spherical shell container and thrown into the pool for passive cooling. In order to investigate the capability of the C/SiC ceramic composites to withstand the high temperature of 1800°C and the huge thermal shock at the initial stage of cooling, in this work, the high-temperature performance of these composites is studied. Furthermore, the compatibility of these composites with corium is investigated, and a retention container design prototype is proposed. The thermal conductivity, thermal expansion coefficient, high-temperature tensile strength, and thermal shock resistance of the candidate C/SiC specimens to be used in the manufacturing of the detention container are measured. The FactSage software package is used for the chemical compatibility study and product composition analysis of the composite SiC deposition layer and corium. The corrosion process of the SiC deposition layer of the composite material caused by corium is investigated through high-temperature corrosion tests and the electron microscopy analysis of the SiC specimen with the incorporation of CeO2. The results show that the C/SiC ceramic composite can meet the design criteria of the CGC corium retention container, and it is impossible to cause a carbon reaction disaster through the failure of the composite SiC deposition layer.

Preface

International Conference on Computer, Big Data And Artificial IntelligenceData has always existed in the changes of human society, constantly changing how humans learn about the world. It is also on the basis of data and information that human beings have made many efforts to explore the planet we live in. Not until modern information technology represented by electronic computer emerges did mankind make a qualitative leap in its ability to master and process data. In recent years, big data and artificial intelligence almost domain human activity, which provides a complex ecosystem of information and services on a global scale. Big data is essentially embodied as a digital virtual image for building the real world. Based on the premise of sufficient computing power and efficient data analysis methods, the in-depth study of this digital virtual image will make it possible to understand and discover the operation, state and laws of real complex systems.The 2nd International Conference on Computer, Big Data and Artificial Intelligence(ICCBDAI 2021) was co-organized by Central South University, Hunan University and Beijing Institute of Technology. Approximately 40 universities had participated the event, and there was over 2000 views for the live broadcast of this conference. Originally the conference was planned to be held in Beihai, China, however, considering the COVID-19 pandemic situation, it was decided to be held virtually online. As the conference organizer, the safety and well-being of our participants are our top priority.The conference aims to provide an international forum where engineers, researchers, practitioners and industrial partners in the field of Computer, Big Data and Artificial Intelligence can discuss/exchange/share recent advances/developments and future perspectives in the use of these technologies in various applications. In line with the aims of the ICCBDAI 2021 conference, and as maybe seen from the table of contents, the papers cover a wide range of topics under a variety of themes: Big Data Analysis and Measurement, Recent Advances in Artificial Intelligence with Applications, Intelligent Image Processing and Recognition, Challenges and Opportunities in Cloud Computing and Edge Computing, Big Data Analytics for Intelligent Transportation, etc.ICCBDAI 2021 was sponsored and supported by the followings:Central South UniversityHunan UniversityDalarna UniversityGuangxi UniversityChengdu University of Information TechnologyChangchun University of TechnologySilesian University of TechnologyList of Committee are available in this pdf.

JACIII Distinguished Editor & Outstanding Reviewer Awards 2021

The JACIII Distinguished Editor and Outstanding Reviewer Awards were established for the purpose to honor and editors who have made a significant contribution to the growth of the JACIII in 2018 and to acknowledge reviewers who have made a significant contribution to reviewing in 2019. We express our deepest gratitude for their professional work, which we believe conductive to development of not only the JACIII but also scientific research. JACIII DISTINGUISHED EDITOR AWARD 2021 Tomomi Hashimoto (Saitama Institute of Technology, Japan) Zhen-Tao Liu (China University of Geosciences, China) Bin Xin (Beijing Institute of Technology, China) Jianqiang Yi (Institute of Automation, Chinese Academy of Sciences, China) Junzo Watada (Waseda University, Japan) Yaping Dai (Beijing Institute of Technology, China) Zhiyang Jia (Beijing Institute of Technology, China) Wentao Gu (Zhejiang Gongshang University, China)

Teaching Industrial Ecology to Undergraduate Students: Lessons Learned

Industrial ecology (IE) education is a topic that has received attention in institutions of higher education throughout the world. Some universities have been teaching and researching IE for the past 20 years but its scope is still being defined. There is a need to catalog and exchange experiences of IE teaching and their results. Based on a literature review, this paper aims to provide a framework composed of content and strategies for IE teaching. This framework is tested in teaching IE as a general education course for undergraduate students at Beijing Institute of Technology (BIT). The methodology applied in this paper is of a descriptive and empirical nature and thus this paper focuses on a practice-oriented perspective in describing the experience of BIT. A range of different strategies, including lectures, group discussions, case studies, role playing games, oral presentations, evaluation, and student feedback have been incorporated in the course. The results show that the course received a highly positive evaluation by the participating students. Students were impressed by IE’s characteristics of interdisciplinarity, ways of thinking, and practical value. Additionally, the course appears to influence students’ values, attitudes, and behavioral intentions. The paper concludes with some thoughts on ways of improving IE education in the future.