A Preliminary Study of Image Analysis for Parasite Detection on Honey Bees

International Conference Image Analysis and Recognition (ICIAR 2018, Póvoa de Varzim, Portugal

Photoluminescence of Eu2+ in BaF2-rich fluorohalides and photostimulation after X-ray irradiation

The luminescence of Eu2+ has been investigated in two families of BaF2-rich fluorohalides, Ba12Cl5(1−x)Br5xF19 (x≤0.8) and Ba7Cl2(1−x)Br2xF12 (x≤0.5). In the two kinds of host lattices, under UV excitation Eu2+ shows an intense blue 5d→4f band emission at 300 K. At low temperature, in addition to the latter, 4f→4f lines are present in the near UV. The efficiency of the photostimulated luminescence (PSL) after X-ray irradiation has been measured and compared with that of BaXF:Eu (X=Cl, Br). High conversion efficiencies have been obtained with compositions Ba12Cl5(1−x)Br5xF19 for stimulation at 532 nm. The presence of bromine is beneficial. For all compositions a high stimulation energy (SE) is needed to excite Eu2+ ions through colour centres

Predictive context-awareness for full-immersive multiuser virtual reality with redirected walking

Abstract: The advancement of virtual reality (VR) technology is focused on improving its immersiveness, supporting multiuser virtual experiences (VEs), and enabling the users to move freely within their VEs while remaining confined to specialized VR setups through redirected walking (RDW). To meet their extreme data-rate and latency requirements, future VR systems will require supporting wireless networking infrastructures operating in mmWave frequencies that leverage highly directional communication in both transmission and reception through beamforming and beamsteering. We propose the use of predictive context-awareness to optimize transmitter and receiver-side beam-forming and beamsteering. By predicting the users' short-term lateral movements in multiuser VR setups with RDW, transmitter-side beamforming and beamsteering can be optimized through line-of-sight (LoS) \u201ctracking\u201d in the users' directions. At the same time, predictions of short-term orientational movements can be utilized for receiver-side beam-forming for coverage flexibility enhancements. We target two open problems in predicting these two context information instances: predicting lateral movements in multiuser VR settings with RDW, and generating synthetic head rotation datasets for training orientational movements predictors. Our experimental results indicate that long short-term memory (LSTM) networks feature promising accuracy in predicting lateral movements, and context-awareness stemming from VEs further enhances this accuracy. Additionally, we show that a TimeGAN-based approach for orientational data generation can create synthetic samples that closely match experimentally obtained ones