Study on the response of IFMIF fission chambers to mixed neutron-gamma fields: PH-2 experimental tests

The engineering design of fissionchambers as on-line radiation detectors for IFMIF is being performed in the framework of the IFMIF-EVEDA works. In this paper the results of the experiments performed in the BR2 reactor during the phase-2 of the foreseen validation activities are addressed. Two detectors have been tested in a mixedneutron-gamma field with high neutron fluence and gamma absorbed dose rates, comparable with the expected values in the HFTM in IFMIF. Since the neutron spectra in all BR2 channels are dominated by the thermal neutron component, the detectors have been surrounded by a cylindrical gadolinium screen to cut the thermal neutron component, in order to get a more representative test for IFMIF conditions. The integrated gamma absorbed dose was about 4 × 1010 Gy and the fast neutron fluence (E > 0.1 MeV) 4 × 1020 n/cm2. The fissionchambers were calibrated in three BR2 channels with different neutron-to-gamma ratio, and the long-term evolution of the signals was studied and compared with theoretical calculations

Real-time image processing for crop/weed discrimination in maize fields

This paper presents a computer vision system that successfully discriminates between weed patches and crop rows under uncontrolled lighting in real-time. The system consists of two independent subsystems, a fast image processing delivering results in real-time (Fast Image Processing, FIP), and a slower and more accurate processing (Robust Crop Row Detection, RCRD) that is used to correct the first subsystem's mistakes. This combination produces a system that achieves very good results under a wide variety of conditions. Tested on several maize videos taken of different fields and during different years, the system successfully detects an average of 95% of weeds and 80% of crops under different illumination, soil humidity and weed/crop growth conditions. Moreover, the system has been shown to produce acceptable results even under very difficult conditions, such as in the presence of dramatic sowing errors or abrupt camera movements. The computer vision system has been developed for integration into a treatment system because the ideal setup for any weed sprayer system would include a tool that could provide information on the weeds and crops present at each point in real-time, while the tractor mounting the spraying bar is moving