scholarly journals Preface

2021 ◽  
Vol 2138 (1) ◽  
pp. 011001

Due to the COVID-19 pandemic, International Conference on Artificial Intelligence and Big Data Applications (ICAIBD2021) that were planned to be held in Huanggang, China were successfully held via an online platform during September 24, 2021. The events brought together researchers and scientists from big data and artificial intelligence, researchers from various application areas to discuss problems and solutions in the area, to identify new issues, and to shape future directions for research. The conference was composed of 2 sessions with 4 keynote speeches and 40 oral reports presented in this conference. Each keynote speech and oral report will take 30-40 minutes and 5-10 minutes, respectively. All papers included in the conference proceedings were peer reviewed according to IOP Publishing standards. We would like to deeply acknowledge all the parties involved in making this conference successfully held: the conference session chairs, organizing committee, authors, reviewers and IOP Publishing. Besides, we wish to thank all authors and participants for providing their valuable contributions for this proceeding as well as the reviewers for their constructive recommendations and criticism aiding to improve the presented articles. General Chair Yuntao Wu Wuhan Institute of Technology [email protected] Zhihua Hu Huanggang Normal University [email protected] List of Academy Committee are available in this pdf.

2020 ◽  
Vol 11 ◽  
Author(s):  
Hui Luan ◽  
Peter Geczy ◽  
Hollis Lai ◽  
Janice Gobert ◽  
Stephen J. H. Yang ◽  
...  

Author(s):  
Muhammed Can ◽  
Halid Kaplan

In recent years, artificial intelligence has become a new normal in the modern world. Even though there are still limitations and it remains to be premature both in terms of applications and theoretical approaches, AI has a huge potential to shift various systems from healthcare to transportation. Needless to say, smart cities are also significant for AI's development. IoT, big data applications, and power networks bring a new understanding of how we live and what the future will be like when AI is adapted to smart cities. However, it is highly misleading to focus on AI itself in this manner. Rather, it should be considered as a part of the ‘Large Technical System'. In this vein, the chapter will ask the following questions: To what extent might AI contribute the power networks of smart cities? How can LTS theory explain this evolution both in terms of technical aspects and technopolitics?


2021 ◽  
Vol 2082 (1) ◽  
pp. 011001

In order to accelerate the development of advanced manufacturing, promote in-depth integration of the Internet, big data, artificial intelligence and the real economy, and foster new growth areas and new drivers in such areas as high-end and medium consumption, innovation-driven development, green and low-carbon development, sharing economy, modern supply chain and human capital services. Computer Academy of Guangdong, Association of Computing Education in Chinese Universities, and Zhuhai Ton-Bridge Medical Technology together with AEIC Academic Exchange Information Center, hosted the 2021 Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2021) in Zhuhai, China during September 24 to 26, 2021. This conference focused on artificial intelligence, big data and medical and big health AI science, aimed to provide a platform for experts and scholars, engineers and researchers to share scientific research results and cutting-edge technologies, understand academic development trends, broaden research ideas, strengthen academic research and discussion, and promote cooperation in the industrialization of academic achievements. About 300 participants from academic, high-education institutes and other organizations took part in the conference. The conference model was divided into two sessions, including oral presentations and keynote speeches. In the first part, some scholars, whose submissions were selected as the excellent papers, were given 15 minutes to perform their oral presentations one by one. Then in the second part, keynote speakers were each allocated 30-45 minutes to hold their speeches. We were very honored to have Prof. Guoqiang Han, from South China University of Technology as our Conference Chairman. In the keynote presentation part, we invited 16 professors as our keynote speakers. The first keynote speaker, Prof. Junlong Chen, Distinguished Chair Professor, Doctoral Supervisor, Dean of School of Computer Science and Engineering, from South University of Technology. The others keynote speakers as follow: Prof. Guoliang Chen, Parallel algorithms, high performance computing experts; Prof. Anhui Liang, the director of the interdisciplinary research center of optical fiber communication and bio-optics, Shandong University of Science and Technology; Prof. Weijia Jia, from International College of Beijing Normal University-Hong Kong Baptist University; Prof. Zhengtian Fang, from La Trobe University in Australia; Prof. Yutong Lu, from Sun Yat-sen University; Prof. Young Liang, from Macau University of Science and Technology; Prof. Nong Xiao, from Sun Yat-sen University; Prof. Xiaofeng Zhu, from University of Electronic Science and Technology of China; Prof. Jianxin Wang, from Central South University; Prof. Xuan Wang, from Harbin Institute of Technology institute; Prof. Guoqiang Zhong, a member of ACM, IEEE, IAPR and China computer society; Prof. Bing Shi, a member of IEEE, ACM and CCF; Assoc. Prof. Chunjiang Duanmu, from Zhejiang Normal University; Prof. Yang Yue, from Nankai University; Prof. Na Li, from Xi’dian University. The proceedings present a selection of high-quality papers submitted to the conference by researchers from universities, research institutes, and industry. All papers were subjected to peer-review by conference committee members and international reviewers. The papers were selected based on their quality and their relevance to the conference. The proceedings present recent advances in the fields of Direction of Big data, Direction of Artificial Intelligence, Direction of Medical and health care and others related research. I would like to express special gratitude to members of the conference committee and organizers of the conference. I would also like to thank the reviewers for their valuable time and advice which helped in improving the quality of the papers selected for presentation at the conference and for publication in the proceedings. Finally, I want to thank the authors, the members of the organizing committee, the reviewers, the chairpersons, sponsors, and all other conference participants for their support of AIBDF 2021. The Committee of AIBDF 2021 List of Committee member are available in this pdf.


2021 ◽  
Vol 13 (22) ◽  
pp. 12656
Author(s):  
Yasheng Chen ◽  
Mohammad Islam Biswas

The COVID-19 pandemic has severe impacts on global health and social and economic safety. The present study discusses strategies for turning the COVID-19 crisis into opportunities to use artificial intelligence (AI) and big data in business operations. Based on the shared experience and theoretical ground, researchers identified five major business challenges during the COVID-19 pandemic: production and supply-chain disruption, appropriate business model selection, inventory management, budget planning, and workforce management. These five challenges were outlined with eight business cases as examples of companies that had already utilized AI and big data for their business operations during the COVID-19 pandemic. The outcomes of this study provide valuable insights into contemporary social science research and business management with AI and big data applications as a business response to any crisis in the future.


2020 ◽  
pp. 1-11
Author(s):  
Bharath Raju ◽  
Fareed Jumah ◽  
Omar Ashraf ◽  
Vinayak Narayan ◽  
Gaurav Gupta ◽  
...  

Big data has transformed into a trend phrase in healthcare and neurosurgery, becoming a pervasive and inescapable phrase in everyday life. The upsurge in big data applications is a direct consequence of the drastic boom in information technology as well as the growing number of internet-connected devices called the Internet of Things in healthcare. Compared with business, marketing, and other sectors, healthcare applications are lagging due to a lack of technical knowledge among healthcare workers, technological limitations in acquiring and analyzing the data, and improper governance of healthcare big data. Despite these limitations, the medical literature is flooded with big data–related articles, and most of these are filled with abstruse terminologies such as machine learning, artificial intelligence, artificial neural network, and algorithm. Many of the recent articles are restricted to neurosurgical registries, creating a false impression that big data is synonymous with registries. Others advocate that the utilization of big data will be the panacea to all healthcare problems and research in the future. Without a proper understanding of these principles, it becomes easy to get lost without the ability to differentiate hype from reality. To that end, the authors give a brief narrative of big data analysis in neurosurgery and review its applications, limitations, and the challenges it presents for neurosurgeons and healthcare professionals naive to this field. Awareness of these basic concepts will allow neurosurgeons to understand the literature regarding big data, enabling them to make better decisions and deliver personalized care.


2021 ◽  
pp. 009539972199868
Author(s):  
Walter Castelnovo ◽  
Maddalena Sorrentino

We must ask critical questions regarding what actors are gaining influence, and regarding why the centrality of government is to be preserved in a data-intensive society. The article recognizes that the transformative capacity of big data—and its artificial intelligence (AI)-based companion data analytics—does not deterministically result from the technologies concerned. Instead, the direction of change depends on both the technical features and the intertwining of big data applications and governmental machinery. In short, the reconfiguration of the government nodality remains an open question. Overall, government is urged to think strategically about its future role within digital ecosystems.


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