Deep learning for processing and analysis of remote sensing big data:a technical review

In recent years,the rapid development of Earth observation tech-nology has produced an increasing growth in remote sensing big data,posing serious challenges for effective and efficient proces-sing and analysis.Meanwhile,there has been a massive rise in deeplearningbased algorithms for remote sensing tasks,providing a large opportunity for remote sensing big data.In this article,we initially summarize the features of remote sensing big data.Subsequently,following the pipeline of remote sensing tasks,a detailed and technical review is conducted to discuss how deep learning has been applied to the processing and analysis of remote sensing data,including geometric and radiometric processing,cloud masking,data fusion,object detection and extraction,landuse/cover classification,change detection and multitemporal ana-lysis.Finally,we discussed technical challenges and concluded directions for future research in deep-learning-based applications for remote sensing big data.

Engineering Review Food Extrusion Technology and Its Applications

An extensive technical review of studies on food extrusion processes which involves forcing mixed food ingredients through a die to produce food snacks has been carried out in this paper. This technical review includes some historical development, food extruder types, extrusion principles and applications, flow simulation and heat transfer modeling in extruders, process parameters and product quality, extruder die and extrudate expansion among others. The research and application of extrusion in food industry was mainly based on the adaptation of plastic extrusion technology which has been in existence for over hundred years. Studies show that twin-screw extruder are more efficient than single-screw extruders because of better mixing and better handling of different combinations of food ingredients. A thorough knowledge of the flow and heat behavior inside an extruder provide an insight into the mechanism of mixing and facilitates estimation of RTD, flow rate, pressure drop, heat transfer mechanism and power consumption. Until recently, very little work has been published on the mechanism of material flow and energy transfer in intermeshing co-rotating extruder mainly due to the complexity of the geometry and the flow behavior. A more recent approach to research in modeling of food extrusion is the 2D or 3D flow modeling using finite element computer package. This research area is gaining recognition in modeling different sections of food extruder. This work also points out some of the achievements and shortcomings of the reviewed works and where necessary, possible solutions are suggested. Areas needing further research have been highlighted. This study will reveal that understanding and application of extrusion technology in developing countries of Asia and Africa are still far from being satisfactory and this work would serve as a good reference material for researchers and operators in food extrusion technology.