scholarly journals Real‐Time Thermal Imaging based on the Simultaneous Rise and Decay Luminescence Lifetime Thermometry

2021 ◽  
pp. 2100208
Author(s):  
Daniel Avram ◽  
Ioana Porosnicu ◽  
Andrei Patrascu ◽  
Carmen Tiseanu
2015 ◽  
Vol 32 (11) ◽  
pp. 1369-1377 ◽  
Author(s):  
Kan Hong ◽  
Sheng Hong

2020 ◽  
Author(s):  
A. V. Arunraj ◽  
Chandan Parthasarathy ◽  
E. V. Neethu ◽  
S. Jishnu ◽  
Kartik Prakash

2020 ◽  
Vol 3 (1) ◽  
pp. 13 ◽  
Author(s):  
Tareq Khan

Whenever food in a microwave oven is heated, the user estimates the time to heat. This estimation can be incorrect, leading the food to be too hot or still cold. In this research, an intelligent microwave oven is designed. After the food is put into the microwave oven and the door is closed, it captures the image of the food, classifies the image and then suggests the food’s target temperature by learning from previous experiences, so the user does not have to recall the target food temperature each time the same food is warmed. The temperature of the food is measured using a thermal camera. The proposed microwave incorporates a display to show a real-time colored thermal image of the food. The microwave automatically stops the heating when the temperature of the food hits the target temperature using closed-loop control. The deep learning-based image classifier gradually learns the type of foods that are consumed in that household and becomes smarter in temperature recommendation. The system can classify and recommend target temperature with 93% accuracy. A prototype is developed using a microcontroller-based system and successfully tested.


Author(s):  
Quoc-Cuong Pham ◽  
Laetitia Gond ◽  
Julien Begard ◽  
Nicolas Allezard ◽  
Patrick Sayd

2018 ◽  
Vol 56 (8) ◽  
pp. 889-899 ◽  
Author(s):  
Patxi Garra ◽  
Aude-Héloïse Bonardi ◽  
Alexandre Baralle ◽  
Assi Al Mousawi ◽  
Fabien Bonardi ◽  
...  

2018 ◽  
Author(s):  
Mahendran Subramanian ◽  
Arkadiusz Miaskowski ◽  
Ajit K. Mahapatro ◽  
Ondrej Hovorka ◽  
Jon Dobson

AbstractHeat dissipation during magnetization reversal processes in magnetic nanoparticles (MNP), upon exposure to alternating magnetic fields (AMF), has been extensively studied in relation to applications in magnetic fluid hyperthermia (MFH). This current paper demonstrates the design, fabrication, and evaluation of an efficient instrument, operating on this principle, for use as (i) a non-contact, in vitro, real-time temperature monitor; (ii) a drug release analysis system (DRAS); (iii) a high flux density module for AMF-mediated MNP studies; and (iv) an in vivo coil setup for real-time, whole body thermal imaging. The proposed DRAS is demonstrated by an AMF-mediated drug release proof-of-principle experiment. Also, the technique described facilitates non-contact temperature measurements of specific absorption rate (SAR) as accurately as temperature measurements using a probe in contact with the sample. Numerical calculations estimating the absolute and root mean squared flux densities, and other MNP – AMF studies suggest that the proposed stacked planar coil module could be employed for calorimetry. Even though the proposed in vivo coil setup could be used for real-time, whole body thermal imaging (within the limitations due to issues of penetration depth), further design effort is required in order to enhance the energy transfer efficiency.


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