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"< p=""""> This book is intended for a wide range of researchers both from academia and industry interested in contributing to industries in an interdisciplinary way. The primary industries, including agriculture, fishery, and power industries, are the most fundamental infrastructure of the human societies. Traditionally, primary industries have been managed in the small family/community base, but with increase in population and development of society, the size of primary industry has grown. The efficiency, quality, and stability of these industries affect the societies significantly, so that they have become one of the major areas that mathematics could contribute to substantially. Also, primary industries are affected by the environment, where mathematical studies play an essential role. The conference was hosted by the research community in New Zealand, where such collaborative activities in mathematics between the industry and academia have been successfully established from an early stage. This enabled the conference to bring together a range of research topics- from pioneering works to cutting-edge results, from agriculture to geothermal energy and nuclear fusion, and from mathematical modeling and analysis to data analysis. ^"

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Robert McKibbin now retired from New Zealand’s Massey University, is Emeritus Professor of Applied Mathematics. An alumnus of both the University of Canterbury (M.Sc. in Mathematics), and the University of Auckland (Ph.D. in Engineering Science), he is Fellow of the NZ Mathematical Society. He was awarded the NZ Geophysics Prize 1982, the NZ Royal Society’s Hamilton Memorial Prize 1984, and the ANZIAM Medal 2012. He has been involved with Industrial Mathematics within NZ and also with the Asia Pacific Consortium (APCMfI) initiated by Kyushu University’s Institute of Mathematics for Industry; he was Member of the latter’s International Advisory Board for several years. His research interests are in mathematical modeling of heat and mass transfer processes and particularly those of geophysical phenomena associated with geothermal systems, including thermally driven underground fluid convection and atmospheric particle transport associated with volcanic and other eruptive mechanisms. Graeme Wake is now Adjunct Professor of two Auckland University campuses in New Zealand: Auckland University of Technology and Massey University (also is Emeritus Professor of the latter). He has served in four different University campuses in New Zealand, was Postdoctoral Scholar (1970), and much later Visiting Fellow at three different Oxford University Colleges. He was awarded the ANZIAM Medal for services to, and excellence in, ANZ Applied Mathematics in 2006, a Doctor of Science degree from Victoria University of Wellington in 1997, and a Fellowship of the Royal Society of New Zealand in 2004. He held two Visiting Fulbright awards, one (incoming) from the USA) and one as Visiting Fulbright Professor to USA. In 2015, he was Foundation Leader of the Group “Mathematics-in-Industry for New Zealand (MINZ)” which organizes Study Groups like those that exist now in many countries, and which started in Oxford in 1968. Graeme was the initial NZ representative of the Asia Pacific Consortium when it was formed in 2015. His research encompasses industrial mathematics, mathematical biology, applied differential, and functional differential equations. Osamu Saeki is Distinguished Professor at Kyushu University. He received his Ph.D. in Mathematics from the University of Tokyo. He was awarded the Takebe Katahiro Prize 1996 and the Geometry Prize 2015 from the Mathematical Society of Japan. He was involved in establishing the Institute of Mathematics for Industry (IMI), Kyushu University, launched in 2011. He is also engaged in the education of industrial mathematics and is Coordinator of the WISE program “Graduate Program of Mathematics for Innovation”, supported by MEXT, Japan. His current research interests concern topology, singularity theory, topology of low-dimensional manifolds, knot theory, and visualization of large scale data.

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