Nanostructured Organic Matrices and Intelligent Sensors

Author(s):  
Cristina Paternolli ◽  
Manuela Adami ◽  
Claudio Nicolini
Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 434
Author(s):  
Qingqi Hong ◽  
Yiwei Ding ◽  
Jinpeng Lin ◽  
Meihong Wang ◽  
Qingyang Wei ◽  
...  

With the rapid development of artificial intelligence and fifth-generation mobile network technologies, automatic instrument reading has become an increasingly important topic for intelligent sensors in smart cities. We propose a full pipeline to automatically read watermeters based on a single image, using deep learning methods to provide new technical support for an intelligent water meter reading. To handle the various challenging environments where watermeters reside, our pipeline disentangled the task into individual subtasks based on the structures of typical watermeters. These subtasks include component localization, orientation alignment, spatial layout guidance reading, and regression-based pointer reading. The devised algorithms for orientation alignment and spatial layout guidance are tailored to improve the robustness of our neural network. We also collect images of watermeters in real scenes and build a dataset for training and evaluation. Experimental results demonstrate the effectiveness of the proposed method even under challenging environments with varying lighting, occlusions, and different orientations. Thanks to the lightweight algorithms adopted in our pipeline, the system can be easily deployed and fully automated.


Agronomy ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 851
Author(s):  
Sonia Cacini ◽  
Sara Di Lonardo ◽  
Simone Orsenigo ◽  
Daniele Massa

Professional peat-free substrates for ornamental plant production are increasingly required by nursery growers. Most promising materials are green compost, coconut coir dust, and woody fibre, used alone or in mixtures. One of the major concerns is pH, usually higher than optimal. In this work, a method based on a three-step procedure was adopted to acidify three organic matrices alone or in mixtures and to individuate the most suitable product, between iron(II) sulphate 7-hydrate and elemental sulphur chips. Firstly, the determination of the buffering capacity by dilution with sulphuric acid was carried out to determine dosages. Afterwards, an incubation trial of 84 (iron(II) sulphate) or 120 days (sulphur chips) was conducted on matrices and substrate mixtures with calculated doses in a climatic chamber maintained at 21 °C. Iron(II) sulphate resulted not suitable because it caused a rapid, but not lasting, pH lowering and an excessive electrical conductivity (EC) increase. Sulphur chips could instead guarantee an adequate and lasting pH lowering. These results were then validated in the open field trial on matrices and substrates. The proposed acidification methodology could be considered in developing new substrates, but the rapidity of pH acidification and EC increase on plant and mineral nutrition should be further investigated.


Automatica ◽  
2021 ◽  
Vol 129 ◽  
pp. 109668
Author(s):  
Kemi Ding ◽  
Xiaoqiang Ren ◽  
Hongsheng Qi ◽  
Guodong Shi ◽  
Xiaofan Wang ◽  
...  

Author(s):  
Yunfeng Hu ◽  
Tieqi Huang ◽  
Hongjian Zhang ◽  
Huijuan Lin ◽  
Yao Zhang ◽  
...  

1986 ◽  
Vol 123 (1-2) ◽  
pp. 59-63 ◽  
Author(s):  
Hayao Imamura ◽  
Yasutoshi Murata ◽  
Susumu Tsuchiya
Keyword(s):  

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