This volume presents both methodologies and numerical applications for the design of non-conventional unit operations in chemical processes and plants, which are rarely studied in depth at an academic level but have w...
ISBN:
(数字)9783030345723
ISBN:
(纸本)9783030345716
This volume presents both methodologies and numerical applications for the design of non-conventional unit operations in chemical processes and plants, which are rarely studied in depth at an academic level but have wide applications in the industrial sector. The first part discusses the design, comparison and optimization of heating and cooling operations that are different from simple heat exchange. The second and larger part offers a brief but effective overview of non-conventional separation processes, mainly focusing on the heterogeneous phases. Based on sample case studies, it extrapolates the process model equations and includes the numerical solution in order to provide a straightforward application example. The end of each chapter features a C++ code implementation to solve the ODE or nonlinear equations system using the BzzMath library.
This book highlights the fundamental association between aquaculture and engineering in classifying fish hunger behaviour by means of machine learning techniques. Understanding the underlying factors that affect fish ...
ISBN:
(数字)9789811522376
ISBN:
(纸本)9789811522369
This book highlights the fundamental association between aquaculture and engineering in classifying fish hunger behaviour by means of machine learning techniques. Understanding the underlying factors that affect fish growth is essential, since they have implications for higher productivity in fish farms. Computer vision and machine learning techniques make it possible to quantify the subjective perception of hunger behaviour and so allow food to be provided as necessary. The book analyses the conceptual framework of motion tracking, feeding schedule and prediction classifiers in order to classify the hunger state, and proposes a system comprising an automated feeder system, image-processing module, as well as machine learning classifiers. Furthermore, the system substitutes conventional, complex modelling techniques with a robust, artificial intelligence approach. The findings presented are of interest to researchers, fish farmers, and aquaculture technologist wanting to gain insights into the productivity of fish and fish behaviour.
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