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A deep learning approach based on graphs to detect plantation lines

Heliyon 2024年第11期10卷 e31730页

作者： Diogo Nunes Gonçalves José Marcato Junior Mauro Dos Santos de Arruda Vanessa Jordão Marcato Fernandes Ana Paula Marques Ramos Danielle Elis Garcia Furuya Lucas Prado Osco Hongjie He Lucio André de Castro Jorge Jonathan Li Farid Melgani Hemerson Pistori Wesley Nunes Gonçalves Faculty of Computer Science Federal University of Mato Grosso do Sul Av. Costa e Silva Campo Grande 79070-900 MS Brazil. Faculty of Engineering Architecture and Urbanism and Geography Federal University of Mato Grosso do Sul Av. Costa e Silva Campo Grande 79070-900 MS Brazil. Faculty of Agricultural Sciences Federal University of Grande Dourados Av. Costa e Silva Dourados 79070-900 MS Brazil. Faculty of Science and Technology São Paulo State University (UNESP) R. Roberto Simonsen 305 Presidente Prudente 19060-900 SP Brazil. Program of Environment and Regional Developement University of Western São Paulo Raposo Tavares km 572 Presidente Prudente 19067-175 SP Brazil. Department of Geography and Environmental Management University of Waterloo Waterloo ON N2L 3G1 Canada. National Research Center of Development of Agricultural Instrumentation Brazilian Agricultural Research Agency (EMBRAPA) 13560-970 R. XV de Novembro 1452 São Carlos SP Brazil. Department of Information Engineering and Computer Science University of Trento Trento 38122 Italy. INOVISAO Dom Bosco Catholic University Avenida Tamandaré 6000 Campo Grande 79117-900 MS Brazil.

Identifying plantation lines in aerial images of agricultural landscapes is re-quired for many automatic farming processes. Deep learning-based networks are among the most prominent methods to learn such patterns and extract this type of information from diverse imagery conditions. However, even state-of-the-art methods may stumble in complex plantation patterns. Here, we propose a deep learning approach based on graphs to detect plantation lines in UAV-based RGB imagery, presenting a challenging scenario containing spaced plants. The first module of our method extracts a feature map throughout the backbone, which consists of the initial layers of the VGG16. This feature map is used as an input to the knowledge Estimation Module (KEM), organized in three concatenated branches for detecting 1) the plant positions, 2) the plantation lines, and 3) the displacement vectors between the plants. A graph modeling is applied considering each plant position on the image as vertices, and edges are formed between two vertices (i.e. plants). Finally, the edge is classified as pertaining to a certain plantation line based on three probabilities (higher than 0.5): i) in visual features obtained from the backbone; ii) a chance that the edge pixels belong to a line, from the KEM step; and iii) an alignment of the displacement vectors with the edge, also from the KEM step. Experiments were conducted initially in corn plantations with different growth stages and patterns with aerial RGB imagery to present the advantages of adopting each module. We assessed the generalization capability in the other two cultures (orange and eucalyptus) datasets. The proposed method was compared against state-of-the-art deep learning methods and achieved superior performance with a significant margin considering all three datasets. This approach is useful in extracting lines with spaced plantation patterns and could be implemented in scenarios where plantation gaps occur, generating lines with few-to-no

关键词： Aerial imagery Convolutional neural networks Object detection Remote sensing UAV

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Retraction notice to "A deep learning approach based on graphs to detect plantation lines" [Heliyon Volume 10, Issue 11, 15 June 2024, e31730]

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Heliyon 2024年第23期10卷 e40689页

[This retracts the article DOI: 10.1016/***.2024.e31730.].

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Work in Progress – Establishing a Master program in Cyber Physical Systems: Basic Findings and Future Perspectives

Work in Progress – Establishing a Master Program in Cyber P...

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International Conference on Promising Electronic Technologies (ICPET)

作者： Isam Ishaq Rashid Jayousi Salaheddin Odeh Ezzaldeen Edwan Asmaa Shaheen Mohamed Elnaggar Ahmed Elagha Samy Salamah Christian Weber Hasan Abu Rasheed Raimund Kirner Martina Doolan Hamidreza Ahmadian Roman Obermaisser Dhiah el Diehn I. Abou-Tair Ala Khalifeh Sahel Alouneh Zaid Alhalhouli Khalid Alemerien Faiez Gargouri Bassem Bouaziz Nadia Aloui Mohammad Saleh Computer Engineering and Science Departments Al-Quds University Jerusalem Palestine Engineering Program and Computer Department Palestine Technical College - Deir El-Balah Deir El-Balah Palestine Institute of Knowledge Based Systems & Knowledge Management University of Siegen Siegen Germany University of Siegen Siegen Germany School of Engineering and Computer Science University of Hertfordshire Hatfield UK Chair of Embedded Systems University of Siegen Siegen Germany German Jordanian University Amman Jordan School of Electrical Engineering and Information Technology German Jordanian University Amman Jordan Computer and Information Technology Department Tafila Technical University Tafila Jordan Higher Institute of Computer Science and Multimedia University of Sfax Sfax Tunisia Higher Institute of Applied Sciences and Technology of Mateur University of Carthage Mateure Tunisia KTH Royal Institute of Technology Stockholm Sweden

This paper reports on the basic findings and future perspectives of a capacity building project funded by the European Union. The International Master of Science on Cyber Physical Systems (ms@CPS) is a collaborative project that aims to establish a master program in cyber physical systems (CPS). A consortium composed of nine partners proposed the project. Three partners are European and from Germany, UK and Sweden; while the other six partners are from the South Mediterranean region and include: Palestine, Jordan and Tunisia. The consortium is led by the University of Siegen in Germany who also manages the implementation of the work packages. CPS is an emerging engineering subject with significant economic and societal implications, which motivated the consortium to propose the establishment of a master program to offer educational and training opportunities at graduate level in the fields of CPS. In this paper, CPS as a field of study is presented with an emphasis on its importance, especially with regard to meeting local needs. A brief description of the project is presented in conjunction with the methodology for developing the courses and their learning outcomes.

关键词： Computer science Internet of Things Industries knowledge engineering Embedded systems Europe Collaboration

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Inference of pressure ulcer stage and texture on an image training set

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Pattern Recognition and Image Analysis 2016年第3期26卷 558-564页

作者： Guadagnin, R.V. Santana, L.A. Neves, R.S. MSc Program on Information Technology and Knowledge Management Catholic University of Brasília Brasília DF Brazil MSc Program on Sciences for Health at School of Health Sciences Brasília DF Brazil Head of Scientific Starting Program–PIBIC Health Sciences Graduate School Brasília DF Brazil

Health assistance depends essentially on effective information providing for professionals. Presently visual information plays an outstanding role concerning patients’ status without necessity of invading procedures. The diagnosis related to stage and texture in pressure ulcers (PU) is considered as a classification procedure, based on the image colors. As a training set this study captured 18 PU images from nine persons. RGB mean values were adopted as features to characterize the images. Classification used an ID3 similar algorithm. It achieved 83.3% accuracy concerning color and stage, as well as 88.9% concerning color and texture. So the technique was effective for automatic determination of PU stage and PU texture based on its color. © 2016, Pleiades Publishing, Ltd.

关键词： Color

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Iran in transition (vol 393, pg 1984, 2019)

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LANCET 2019年第10186期393卷 2124-2124页

作者： Danaei, G. Farzadfar, F. Kelishadi, R. [a]Department of Global Health and Population and Department of Epidemiology Harvard T H Chan School of Public Health Boston MA USA Department of Global Health and Population and Department of Epidemiology Harvard T H Chan School of Public Health Boston MA USA [b]Scientific Association for Public Health in Iran Boston MA USA Scientific Association for Public Health in Iran Boston MA USA [c]Non-Communicable Diseases Research Center Endocrinology and Metabolism Population Sciences Institute Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Center Endocrinology and Metabolism Population Sciences Institute Tehran University of Medical Sciences Tehran Iran [d]Endocrinology and Metabolism Research Center Tehran University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Center Tehran University of Medical Sciences Tehran Iran [e]Diabetes Research Center Tehran University of Medical Sciences Tehran Iran Diabetes Research Center Tehran University of Medical Sciences Tehran Iran [f]Endocrinology and Metabolism Clinical Sciences Institute Department of Health Management and Economics Tehran University of Medical Sciences Tehran Iran Endocrinology and Metabolism Clinical Sciences Institute Department of Health Management and Economics Tehran University of Medical Sciences Tehran Iran [g]Department of Global Health and Public Policy Tehran University of Medical Sciences Tehran Iran Department of Global Health and Public Policy Tehran University of Medical Sciences Tehran Iran [h]Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran [i]School of Public Health Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran [j]Faculty of Medicine Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Te

Summary Being the second-largest country in the Middle East, Iran has a long history of civilisation during which several dynasties have been overthrown and established and health-related structures have been reorganised. Iran has had the replacement of traditional practices with modern medical treatments, emergence of multiple pioneer scientists and physicians with great contributions to the advancement of science, environmental and ecological changes in addition to large-scale natural disasters, epidemics of multiple communicable diseases, and the shift towards non-communicable diseases in recent decades. Given the lessons learnt from political instabilities in the past centuries and the approaches undertaken to overcome health challenges at the time, Iran has emerged as it is today. Iran is now a country with a population exceeding 80 million, mainly inhabiting urban regions, and has an increasing burden of non-communicable diseases, including cardiovascular diseases, hypertension, diabetes, malignancies, mental disorders, substance abuse, and road injuries.

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knowledge and Awareness of Generative Artificial Intelligence Use in Medicine Among International Stakeholders: A Cross-Sectional Study

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Journal of evidence-based medicine 2025年第2期18卷 e70034页

作者： Xufei Luo Bingyi Wang Yule Li Shuang Liu Haodong Li Yaxuan Ren Wah Yang Kyle Lam Stephen R Ali Gemma Sharp Fabio Ynoe Moraes Ye Wang Di Zhu Zhenhua Yang Daher Mohammad Robert Fruscio Maged N Kamel Boulos Zhicheng Lin Kazuki Ide Xuping Song Lu Zhang Yih Chung Tham Hui Liu Long Ge Yaolong Chen Zhaoxiang Bian Evidence-Based Medicine Center School of Basic Medical Sciences Lanzhou University Lanzhou China. Research Unit of Evidence-Based Evaluation and Guidelines Chinese Academy of Medical Sciences (2021RU017) School of Basic Medical Sciences Lanzhou University Lanzhou China. World Health Organization Collaboration Center for Guideline Implementation and Knowledge Translation Lanzhou China. Institute of Health Data Science Lanzhou University Lanzhou China. Key Laboratory of Evidence Based Medicine of Gansu Province Lanzhou University Lanzhou China. Editorial Office of Medical Journal of Peking Union Medical College Hospital Peking Union Medical College Hospital Chinese Academy of Medical Sciences & Peking Union Medical College Beijing China. Chinese Journal of Hematology National Clinical Research Center for Blood Diseases Haihe Laboratory of Cell Ecosystem Institute of Hematology & Blood Diseases Hospital Chinese Academy of Medical Sciences & Peking Union Medical College Tianjin China. Tianjin Institutes of Health Science Tianjin China. School of Public Health Lanzhou University Lanzhou China. School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine Chengdu China. Department of Metabolic and Bariatric Surgery The First Affiliated Hospital of Jinan University Guangzhou China. Department of Surgery and Cancer Imperial College London London UK. Reconstructive Surgery and Regenerative Medicine Research Centre Institute of Life Sciences Swansea University Medical School Swansea UK. School of Psychology University of Queensland Brisbane Australia. Department of Oncology Queen's University Kingston Canada. School of Chinese Medicine Vincent V.C. Woo Chinese Medicine Clinical Research Institute Hong Kong Baptist University Hong Kong China. Orthopedic Department Hôtel Dieu de France Beirut Lebanon. UO Gynecology Fondazione IRCCS San Gerardo dei Tintori Monza Italy. Department of Medicine and Surgery University of Milan-Bicocca Milan Italy.

OBJECTIVE:To assess the knowledge, attitudes, and practices (KAP) of medical stakeholders regarding the use of generative artificial intelligence (GAI) tools. METHODS:A cross-sectional survey was conducted among stakeholders in medicine. Participants included researchers, clinicians, and medical journal editors with varying degrees of familiarity with GAI tools. The survey questionnaire comprised 40 questions covering four main dimensions: basic information, knowledge, attitudes, and practices related to GAI tools. Descriptive analysis, Pearson's correlation, and multivariable regression were used to analyze the data. RESULTS:The overall awareness rate of GAI tools was 93.3%. Participants demonstrated moderate knowledge (mean score 17.71 ± 5.56), positive attitudes (mean score 73.32 ± 15.83), and reasonable practices (mean score 40.70 ± 12.86). Factors influencing knowledge included education level, geographic region, and attitudes (p < 0.05). Attitudes were influenced by work experience and knowledge (p < 0.05), while practices were driven by both knowledge and attitudes (p < 0.001). Participants from outside China scored higher in all dimensions compared to those from China (p < 0.001). Additionally, 74.0% of participants emphasized the importance of reporting GAI usage in research, and 73.9% advocated for naming the specific tool used. CONCLUSION:The findings highlight a growing awareness and generally positive attitude toward GAI tools among medical stakeholders, alongside the recognition of their ethical implications and the necessity for standardized reporting practices. Targeted training and the development of clear reporting guidelines are recommended to enhance the effective use of GAI tools in medical research and practice.

关键词： ChatGPT cross‐sectional survey generative artificial intelligence knowledge and awareness

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Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026

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The Lancet Global Health 2023年第3期11卷 e385-e413页

作者： Micah, Angela E. Bhangdia, Kayleigh Cogswell, Ian E. Lasher, Dylan Lidral-Porter, Brendan Maddison, Emilie R. Nguyen, Trang Nhu Ngoc Patel, Nishali Pedroza, Paola Solorio, Juan Stutzman, Hayley Tsakalos, Golsum Wang, Yifeng Warriner, Wesley Zhao, Yingxi Zlavog, Bianca S. Abbafati, Cristiana Abbas, Jaffar Abbasi-Kangevari, Mohsen Abbasi-Kangevari, Zeinab Abdelmasseh, Michael Abdulah, Deldar Morad Abedi, Aidin Abegaz, Kedir Hussein Abhilash, E.S. Aboagye, Richard Gyan Abolhassani, Hassan Abrigo, Michael R.M. Abubaker Ali, Hiwa Abu-Gharbieh, Eman Adem, Mohammed Hussien Afzal, Muhammad Sohail Ahmadi, Ali Ahmed, Haroon Ahmed Rashid, Tarik Aji, Budi Akbarialiabad, Hossein Akelew, Yibeltal Al Hamad, Hanadi Alam, Khurshid Alanezi, Fahad Mashhour Alanzi, Turki M. Al-Hanawi, Mohammed Khaled Alhassan, Robert Kaba Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Ameyaw, Edward Kwabena Amini-Rarani, Mostafa Amu, Hubert Ancuceanu, Robert Andrei, Tudorel Anwar, Sumadi Lukman Appiah, Francis Aqeel, Muhammad Arabloo, Jalal Arab-Zozani, Morteza Aravkin, Aleksandr Y. Aremu, Olatunde Aruleba, Raphael Taiwo Athari, Seyyed Shamsadin Avila-Burgos, Leticia Ayanore, Martin Amogre Azari, Samad Baig, Atif Amin Bantie, Abere Tilahun Barrow, Amadou Baskaran, Pritish Basu, Sanjay Batiha, Abdul-Monim Mohammad Baune, Bernhard T. Berezvai, Zombor Bhardwaj, Nikha Bhardwaj, Pankaj Bhaskar, Sonu Boachie, Micheal Kofi Bodolica, Virginia Botelho, João Silva Botelho Braithwaite, Dejana Breitborde, Nicholas J.K. Busse, Reinhard Cahuana-Hurtado, Lucero Catalá-López, Ferrán Chansa, Collins Charan, Jaykaran Chattu, Vijay Kumar Chen, Simiao Chukwu, Isaac Sunday Dadras, Omid Dandona, Lalit Dandona, Rakhi Dargahi, Abdollah Debela, Sisay Abebe Denova-Gutiérrez, Edgar Desye, Belay Dharmaratne, Samath Dhamminda Diao, Nancy Doan, Linh Phuong Dodangeh, Milad dos Santos, Wendel Mombaque Doshmangir, Leila Dube, John Eini, Ebrahim El Sayed Zaki, Maysaa El Tantawi, Maha Enyew, Daniel Berhanie Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Applied Mathematics University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Nuffield Department of Medicine University of Oxford Oxford United Kingdom Department of Juridical and Economic Studies La Sapienza University Rome Italy Antai College of Economics Shanghai Jiao Tong University Shanghai China Non-communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Children’s Medical Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Tehran Heart Center Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Tehran University of Medical Sciences Tehran Iran National Institute for Health Research Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Department of Cardiology Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Center Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Department of Neurology Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Epidemiology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Health Economics and Statistics Shahid Beheshti University of Medical Sciences Tehran Iran Department of Neurosurgery Shahid Beheshti University of Medical Sciences Tehran Iran Ophthalmic R

Background: The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic;characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic;and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods: In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings: In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95% uncertainty interval [UI] 9·1–9·3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7·3 trillion (95% UI 7·2–7·4) in 2019;293·7 times the $24·8 billion (95% UI 24·3–25·3) spent by low-income countries in 2019. That same year, $43·1 billion in development assistance was provided

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Middle East and North African Health Informatics Association (MENAHIA): Building Sustainable Collaboration

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Yearbook of Medical Informatics 2018年第1期27卷 286-291页

作者： Najeeb Al-Shorbaji Mowafa Househ Adel Taweel Abdullah Alanizi Bennani Othmani Mohammed Haitham Abaza Hala Bawadi Hamayon Rasuly Khalid Alyafei Luis Fernandez-Luque Mohamed Shouman Osama El-Hassan Rada Hussein Riyad Alshammari Salah Mandil Sarah Shouman Shahrad Taheri Tamer Emara Wasmiya Dalhem Zaid Al-Hamdan Zineb Serhier eHealth and Knowledge Management Consultant Retired Director of Knowledge Ethics and Research Department WHO/HQ Amman Jordan Department of Health Informatics College of Public Health and Health Informatics King Saud Bin Abdulaziz University for Health Sciences Ministry of National Guard-Health Affairs Riyadh Saudi Arabia Department of Computer Science BirZeit University Ramallah Palestine Head of Medical Informatics Unit 20 August Hospital Ibn Rochd University Hospital Casablanca Head of Casablanca Medical Informatics Laboratory Medical Faculty of Casablanca Morocco Department of Biomedical Engineering Misr University for Science & Technology Cairo Egypt Associate Professor College of Nursing University of Jordan Amman Jordan eHealth Program Coordinator Bamyan Provincial Hospital Bamyan City Afghanistan Chief Medical Informatics Officer (CMIO) - SIDRA Assistant Professor Clinical Pediatrics at Weill Cornell Medicine Qatar Qatar Computing Research Institute Hamad Bin Khalifa University Doha Qatar Faculty of Medicine Ain Shams University Cairo Egypt Vice-Chair of Emirates Health Informatics Society Head of eHealth Section at Dubai Health Authority Dubai United Arab Emirates Founder and Former Director of the Biomedical Informatics Center of Excellence (BMICoE) Information Technology Institute (ITI) Ministry of Communications and Information Technology (MCIT) Egypt President of Saudi Association for Health Informatics Riyadh Saudi Arabia Senior Consultant on eStrategies and eHealth to WHO and ITU Geneva Switzerland Department of Medicine Weill Cornell Medical College in Qatar Qatar Foundation Doha Qatar Executive Director of Nursing Informatics Hamad Medical Corporation Qatar Associate Professor of Nursing Management Faculty of Nursing Jordan University of Science and Technology Irbid Jordan Professor at Medical Informatics Laboratory Faculty of Medicine and Pharmacy Hassan II University Casablanca Morocco

There has been a growing interest in Health Informatics applications, research, and education within the Middle East and North African Region over the past twenty years. People of this region share similar cultural and religious values, primarily speak the Arabic language, and have similar health care related issues, which are in dire need of being addressed. Health Informatics efforts, organizations, and initiatives within the region have been largely under-represented within, but not ignored by, the International Medical Informatics Association (IMIA). Attempts to create bonds and collaboration between the different organizations of the region have remained scattered, and often, resulted in failure despite the fact that the need for a united health informatics collaborative within the region has never been more crucial than today. During the 2017 MEDINFO, held in Hangzhou, China, a new organization, the Middle East and North African Health Informatics Association (MENAHIA) was conceived as a regional non-governmental organization to promote and facilitate health informatics uptake within the region endorsing health informatics research and educational initiatives of the 22 countries represented within the region. This paper provides an overview of the collaboration and efforts to date in forming MENAHIA and displays the variety of initiatives that are already occurring within the MENAHIA region, which MENAHIA will help, endorse, support, share, and improve within the international forum of health informatics.

关键词： eHealth Middle East and North Africa Health Informatics collaboration MENAHIA Universal Health Coverage Bioinformatics International Medical Informatics Association

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Abstracts

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JOURNAL OF SPINAL CORD MEDICINE 2021年第SUPPL 1期44卷 S278-S324页

作者： [Anonymous] Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto Toronto ON CA KITE - Toronto Rehabilitation Institute University Health Network Toronto ON CA Institute for Health Policy Management and Evaluation University of Toronto Toronto ON CA Rehabilitation Sciences Institute University of Toronto Toronto ON CA Institute of Medical Sciences University of Toronto Toronto ON CA. Rehabilitation Sciences Institute University of Toronto ON CA KITE Research Institute-Toronto Rehab-University Health Network Toronto ON CA Physical Therapy Department University of Toronto ON CA Praxis Spinal Cord Institute Vancouver BC Université de Montréal (École de réadaptation) Montreal QC CA Institut de réadaptation Gingras-Linsay-de-Montréal Montreal QC CA Division of Physical Medicine & Rehabilitation Department of Medicine Faculty of Medicine & Dentistry University of Alberta Edmonton AB CA University of Calgary Calgary AB CA Alberta Health Services Centre for Family Medicine Kitchener ON CA McMaster University Department of Family Medicine Hamilton ON CA Dept. of Physical Therapy University of Toronto Toronto ON CA KITE-University Health Network Toronto ON CA Praxis Spinal Cord Institute Vancouver BC CA Center for Interdisciplinary Research in Rehabilitation and Social Integration (CIRRIS) Quebec City QC CA Dept. of Rehabilitation Laval University Quebec City QC CA Institute of Health Policy Management and Evaluation University of Toronto Toronto ON CA School of Rehabilitation Science University of Saskatchewan Saskatoon SK CA Ontario Neurotrauma Foundation Toronto ON CA Canadian Spinal Research Organization Toronto ON CA CIUSSS du Centre-Sud-de-l ‘Île-de-Montréal (Installation Gingras-Lindsay) Montréal QC CA École de réadaptation Université de Montréal Montréal QC CA First Steps Wellness Centre Regina SK CA Stan Cassidy Centre for Rehabilitation Horizon Health Network Fredericton NB CA Departmen

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Getting Undergraduates Ready for China’s Belt and Road Initiative (BRI) Through an Overseas Experiential Learning Project

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China and the World 2021年第3期4卷

作者： Andrew Min Han Chin Thomas Menkhoff Hans-Dieter Evers Hoong Hui Daniel Gn Kevin Koh Chester Wey Lee Patrick H. M. Loh Linda Low Sebastian Tan Teng Seng Teo Natalie Yap Lee Kong Chian School of Business Singapore Management University (SMU) 81 Victoria Street Singapore 188065 Singapore Andrew Chin Min Han graduated from Tsinghua University in Beijing China with a Tsinghua–MIT Sloan International Master of Business Administration degree under the Singapore Government’s Asian Business Fellowship (ABF) scholarship program. He is the Program Director of Singapore Management University (SMU) Executive Certificate in China Business and of the SMU Internationalisation Series. He teaches as an Adjunct Faculty of Strategy and Organisation at the SMU Lee Kong Chian School of Business since January 2017. He teaches effectively in English and Chinese. With over 23 years of experience in education and publishing industry in Asia Andrew Chin’s multi-sector career has enabled him to experience the full spectrum of the education industry in his roles as the Singapore EDB Officer handling the World-Class University portfolio and the Specialist Information and Publishing Industry portfolio Chief Representative and Country Manager (China) at Thomson Learning (Fortune 500 company) and Co-founder and CEO for an early childhood education business. Andrew was a Business Development Director (Universities) at Sodexo Group (Fortune 500 company) for the Asia-Pacific region. After working 10 years in Beijing China Andrew returned to Singapore in 2012 to work closely with the top leadership at Singapore Management University on the SMU China & East Asia Initiatives. Thomas Menkhoff is the Professor of Organisational Behaviour & Human Resources (Education) at the Lee Kong Chian School of Business Singapore Management University (SMU). Two of his recent publications include: (i) Menkhoff Thomas Ning Kan Siew Evers Hans-Dieter and Chay Yue Wah eds. Living in Smart Cities: Innovation and Sustainability (New Jersey: World Scientific Publishing 2018) and (ii) Chay Yue Wah Menkhoff Thomas and Low Linda eds. China’s Belt and Road Initiative — Understanding the Dynamics of a Global Transfor

In this paper, we explain how an experiential learning course and study tour to Gansu Province (People’s Republic of China) enabled undergraduates at the Singapore management University (SMU) to acquire 21st-century competencies and higher-order thinking skills by analyzing and evaluating specific aspects of China’s Belt and Road Initiative (BRI) and China–Singapore (Chongqing) Connectivity Initiative — New International Land–Sea Trade Corridor (CCI-ILSTC) with emphasis on developing viable Go-To-Market (GTM) strategies aimed at selling Gansu produce in four Southeast Asian markets. We share how the course was designed to support the attainment of key learning goals and discuss how we turned pedagogical aspirations into concrete learning outcomes. We introduce key aspects of the so-called “SMU-XO” project that the students conducted in partnership with an industry partner, Pacific International Lines (PIL), and discuss how the project work helped learners to gain global competency by (i) examining critical issues related to BRI such as multi-modal infrastructure connectivity, (ii) appreciating the local perspectives of project stakeholders in Lanzhou and Shanghai and (iii) successfully interacting with people from different cultures, namely China, Indonesia, Vietnam, Malaysia and Thailand.

关键词： Experiential learning Singapore China Belt and Road Initiative (BRI)

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