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Chinese to English: Undergraduate Agricultural Economics Education: Lessons from Japan General field: Social Sciences Detailed field: Agriculture
Source text - Chinese 日本农业经济学科本科教育的发展及启示
摘要：从学科发展和教育体系两个方面，分析了日本农业经济学科本科教育的现状及发展趋势。日本农经学科发展经验值得借鉴之处在于：（1）学科应时转型，将食品产业管理和资源环境管理作为研究和教学重点，满足市场的实际需求且保持学科吸引力；（2）重视农学知识培养，从而有助于专业知识与农业自身规律紧密联系，增强了学生在农业相关就业市场的不可替代性；（3）实施导师负责制，发挥导师在学生培养中的主导作用，培养学生的科研能力，提高了教育质量。
Translation - English Undergraduate Agricultural Economics Education: Lessons from Japan
Abstract: This paper considers Japan’s undergraduate-level education in agricultural economics, its current status and trends both as an academic subject and as part of the education system. Japan’s experience in developing the discipline of agricultural economics offers the following lessons. (1) In Japan, the subject of agricultural economics made a timely adjustment and shifted its focus, in terms of both research and teaching, to the management of food industry, resource and environment, thus meeting market demand and keeping agricultural economics attractive as a subject area. (2) Emphasis was given to the teaching of agronomic knowledge in order to strengthen the link between knowledge and practice. This ensured that students graduate with skills that are irreplaceable in agriculture-related job markets. (3) Adoption of a tutorial system places the tutor at the center of a students’ education, and therefore helps enhance the student’s research skills and the overall quality of education.
Chinese to English: Challenges Facing the Commercialization of Medical AI General field: Bus/Financial Detailed field: Journalism
Translation - English Challenges Facing the Commercialization of Medical AI
While we are pleasantly surprised by the initiatives taken by Tencent’s Medical AI Lab, we must also recognize the multiple barriers that need to be crossed before medical AI can be successfully commercialized.
The first barrier is a technological one. Great challenges still lie ahead in collecting, labelling and using data. Without solving this problem, medical AI will be as meaningless as water without its source. The “black box” problem with algorithms also requires attention. In many fields, an utterly unexplainable model will see limited use, as it fails to contribute more information that can be relied on. This is also why many still prefer using statistical models, which tend to be more explainable, even when deep learning is known to be remarkably accurate.
The second barrier has to do with metrics. To look beyond the “human-machine” rivalry and the issue of accuracy, we also ought to find a more appropriate set of metrics while also avoiding overfitting.
The last barrier lies in policy and regulation, for which China, much like the rest of the world, is still in the exploration stage.
As the saying goes, “a thousand-mile journey begins with the first step.” A giant leap has been made for both Tencent and this industry towards commercializing medical AI, as seen in the initiation of the project Research on The Solution for AI-based Clinical Decision Support Technology and Its Service Model. This progress gives us reasons to believe that any challenges and difficulties ahead can be overcome.
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Master's degree - Glendon College, York University (Canada)
Experience
Years of experience: 10. Registered at ProZ.com: Mar 2018.
Rony Gao is an experienced conference interpreter, translator and communications consultant based in Toronto and serving clients worldwide. He is a frequent speaker at regional and national conferences.
As a Chinese/English conference interpreter, Rony has provided simultaneous and consecutive interpretation for Chinese Premier and State Council Delegation to Canada, Canadian prime minister Justin Trudeau, Canada China Business Council, Mayor of Toronto, Wharton School of the University of Pennsylvania, University of Toronto, Tencent, Huawei and many other leaders in government, business, technology and education.
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