Preface

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.

An empirical analysis of human trafficking in an era of globalization

PurposeThe paper explores the dark side of economic openness by examining empirically the nexus between the globalization process and human trafficking. Specifically, it is about showing in a global perspective how the growing process of free movement of people, goods, capital, services and information technology make the globe a connected web of activity for the sale and exploitation of human beings.Design/methodology/approachAfter discussing some transmission channels through which globalization could increase this practice based on the lessons from the literature, an empirical analysis is done by employing ordinary least squares (OLS) and Probit regressions on a cross-sectional model covering 130 countries worldwide.FindingsFindings, robust to the consideration of the sub-regional specificities and controlling for social, cultural and historical factors, suggest that globalization, particularly financial and cultural, favors human trafficking. In the light of these results, some policy recommendations are discussed.Originality/valueThis study complements the extant literature by assessing dynamics of globalization in human trafficking.

Strategi Bisnis PT Crowde Membangun Bangsa dengan Pendekatan Business Model Canvas (BMC)

PT Crowde Membangun Bangsa is a financial technology company that offers capital services for agricultural activities. With the concept of peer to peer lending (P2P), the company functions as a platform are to bring investors and customers together. To continue to grow and face competition in the future, PT Crowde Membangun Bangsa requires preparation and improvement of business models. This study aims to (1) map the business model applied at PT Crowde Membangun Bangsa, (2) Identify strengths, weaknesses, opportunities, and threats of the nine elements of the Business Model Canvas based on PT Crowde Build the Nation, (3) Formulate alternative Business Model strategies The right canvas to be applied to PT Crowde Membangun Bangsa. The data collection method is carried out by direct observation and using the qualitative method. The conclusion of this study is the improvement in the new Business Model Canvas, especially in the customer segment elements by adding plantations as a new segment and beef cattle commodities as an improvement to existing segments so that the company's targets are met, improvements in these elements need to be supported by improvements in other elements. namely reactivating individual investors as additional corporate financial key resources, additional types of loan facilities to increase the value proposition, and optimizing the use of technology in customer relationship elements and key activities so that additional consumer segments are followed by maximum service and efficient key activities.

Intellectual capital in the public sector

The Intellectual Capital theory emerged mainly from analyses and observations in business sector based on the growing importance of intellectual capital as a production factor and on its contribution to create value and competitive advantages. The importance of managing intellectual capital is also recognized in public organizations although the theory reveals differences in application to the public sector and is less developed in this environment. In fact, most methodologies to manage intellectual capital were developed in the business area and research at public sector level did not verify the same attention. In literature it is possible to realize that although there are some studies that analyse the management of intellectual capital in the public sector, there are few studies that suggest methodologies specific to this sector. Thus, this article aims to discuss the main aspects about the applicability of intellectual capital theory to the public sector and to propose a taxonomy of intangible assets appropriate to this sector through critical review of main contributions of literature. The analysis allowed finding several arguments that justify the application of the theory to public sector. It also allowed suggesting a classification of intellectual capital based on the intangible assets considered relevant to public sector namely the set of the followed categories: Human capital, Structural capital, Relational capital, Services capital and Public Commitment capital.