An Ultra-Fast TSP on a CNT Heating Layer for Unsteady Temperature and Heat Flux Measurements in Subsonic Flows

In this paper, the authors demonstrate the application of a modified Ru(phen)-based temperature-sensitive paint which was originally developed for the evaluation of unsteady aero-thermodynamic phenomena in high Mach number but short duration experiments. In the present work, the modified TSP with a temperature sensitivity of up to −5.6%/K was applied in a low Mach number long-duration test case in a low-pressure environment. For the demonstration of the paint’s performance, a flat plate with a mounted cylinder was set up in the High-Speed Cascade Wind Tunnel (HGK). The test case was designed to generate vortex shedding frequencies up to 4300 Hz which were sampled using a high-speed camera at 40 kHz frame rate to resolve unsteady surface temperature fields for potential heat-transfer estimations. The experiments were carried out at reduced ambient pressure of p∞ = 13.8 kPa for three inflow Mach numbers being Ma∞=[0.3;0.5;0.7]. In order to enable the resolution of very low temperature fluctuations down to the noise floor of 10−5 K with high spatial and temporal resolution, the flat plate model was equipped with a sprayable carbon nanotube (CNT) heating layer. This constellation, together with the thermal sensors incorporated in the model, allowed for the calculation of a quasi-heat-transfer coefficient from the surface temperature fields. Besides the results of the experiments, the paper highlights the properties of the modified TSP as well as the methodology.

Green Citrus Detection and Counting in Orchards Based on YOLOv5-CS and AI Edge System

Green citrus detection in citrus orchards provides reliable support for production management chains, such as fruit thinning, sunburn prevention and yield estimation. In this paper, we proposed a lightweight object detection YOLOv5-CS (Citrus Sort) model to realize object detection and the accurate counting of green citrus in the natural environment. First, we employ image rotation codes to improve the generalization ability of the model. Second, in the backbone, a convolutional layer is replaced by a convolutional block attention module, and a detection layer is embedded to improve the detection accuracy of the little citrus. Third, both the loss function CIoU (Complete Intersection over Union) and cosine annealing algorithm are used to get the better training effect of the model. Finally, our model is migrated and deployed to the AI (Artificial Intelligence) edge system. Furthermore, we apply the scene segmentation method using the “virtual region” to achieve accurate counting of the green citrus, thereby forming an embedded system of green citrus counting by edge computing. The results show that the [email protected] of the YOLOv5-CS model for green citrus was 98.23%, and the recall is 97.66%. The inference speed of YOLOv5-CS detecting a picture on the server is 0.017 s, and the inference speed on Nvidia Jetson Xavier NX is 0.037 s. The detection and counting frame rate of the AI edge system-side counting system is 28 FPS, which meets the counting requirements of green citrus.

Comparing Online Webcam- and Laboratory-Based Eye-Tracking for the Assessment of Infants’ Audio-Visual Synchrony Perception

Online data collection with infants raises special opportunities and challenges for developmental research. One of the most prevalent methods in infancy research is eye-tracking, which has been widely applied in laboratory settings to assess cognitive development. Technological advances now allow conducting eye-tracking online with various populations, including infants. However, the accuracy and reliability of online infant eye-tracking remain to be comprehensively evaluated. No research to date has directly compared webcam-based and in-lab eye-tracking data from infants, similarly to data from adults. The present study provides a direct comparison of in-lab and webcam-based eye-tracking data from infants who completed an identical looking time paradigm in two different settings (in the laboratory or online at home). We assessed 4-6-month-old infants (n = 38) in an eye-tracking task that measured the detection of audio-visual asynchrony. Webcam-based and in-lab eye-tracking data were compared on eye-tracking and video data quality, infants’ viewing behavior, and experimental effects. Results revealed no differences between the in-lab and online setting in the frequency of technical issues and participant attrition rates. Video data quality was comparable between settings in terms of completeness and brightness, despite lower frame rate and resolution online. Eye-tracking data quality was higher in the laboratory than online, except in case of relative sample loss. Gaze data quantity recorded by eye-tracking was significantly lower than by video in both settings. In valid trials, eye-tracking and video data captured infants’ viewing behavior uniformly, irrespective of setting. Despite the common challenges of infant eye-tracking across experimental settings, our results point toward the necessity to further improve the precision of online eye-tracking with infants. Taken together, online eye-tracking is a promising tool to assess infants’ gaze behavior but requires careful data quality control. The demographic composition of both samples differed from the generic population on caregiver education: our samples comprised caregivers with higher-than-average education levels, challenging the notion that online studies will per se reach more diverse populations.

Efficient Ray Tracing of Large 3D Scenes for Mobile Distributed Computing Environments

Cluster computing has attracted much attention as an effective way of solving large-scale problems. However, only a few attempts have been made to explore mobile computing clusters that can be easily built using commodity smartphones and tablets. To investigate the possibility of mobile cluster-based rendering of large datasets, we developed a mobile GPU ray tracer that renders nontrivial 3D scenes with many millions of triangles at an interactive frame rate on a small-scale mobile cluster. To cope with the limited processing power and memory space, we first present an effective 3D scene representation scheme suitable for mobile GPU rendering. Then, to avoid performance impairment caused by the high latency and low bandwidth of mobile networks, we propose using a static load balancing strategy, which we found to be more appropriate for the vulnerable mobile clustering environment than a dynamic strategy. Our mobile distributed rendering system achieved a few frames per second when ray tracing 1024 × 1024 images, using only 16 low-end smartphones, for large 3D scenes, some with more than 10 million triangles. Through a conceptual demonstration, we also show that the presented rendering scheme can be effectively explored for augmenting real scene images, captured or perceived by augmented and mixed reality devices, with high quality ray-traced images.

Real-Time Numerical Simulation for Accurate Soft Tissues Modeling during Haptic Interaction

The simulation of fabrics physics and its interaction with the human body has been largely studied in recent years to provide realistic-looking garments and wears specifically in the entertainment business. When the purpose of the simulation is to obtain scientific measures and detailed mechanical properties of the interaction, the underlying physical models should be enhanced to obtain better simulation accuracy increasing the modeling complexity and relaxing the simulation timing constraints to properly solve the set of equations under analysis. However, in the specific field of haptic interaction, the desiderata are to have both physical consistency and high frame rate to display stable and coherent stimuli as feedback to the user requiring a tradeoff between accuracy and real-time interaction. This work introduces a haptic system for the evaluation of the fabric hand of specific garments either existing or yet to be produced in a virtual reality simulation. The modeling is based on the co-rotational Finite Element approach that allows for large displacements but the small deformation of the elements. The proposed system can be beneficial for the fabrics industry both in the design phase or in the presentation phase, where a virtual fabric portfolio can be shown to customers around the world. Results exhibit the feasibility of high-frequency real-time simulation for haptic interaction with virtual garments employing realistic mechanical properties of the fabric materials.

High-speed 3D imaging using a chaos lidar system

We characterize a new chaos lidar system configuration and demonstrate its capability for high-speed 3D imaging. Compared with a homodyned scheme employing single-element avalanche photodetectors (APDs), the proposed scheme utilizes a fiber Bragg grating and quadrant APDs to substantially increase the system throughput, frame rate, and field-of-view. By quantitatively analyzing the signal-to-noise ratio, peak-to-standard deviation of the sidelobe level, precision, and detection probability, we show that the proposed scheme has better detection performance suitable for practical applications. To show the feasibility of the chaos lidar system, while under the constrain of eye-safe regulation, we demonstrate high-speed 3D imaging with indoor and outdoor scenes at a throughput of 100 kHz, a frame rate of 10 Hz, and a FOV of 24.5$$^\circ $$ ∘ $$\times $$ × 11.5$$^\circ $$ ∘ for the first time.

Intelligent electromagnetic metasurface camera: system design and experimental results

Electromagnetic (EM) sensing is uniquely positioned among nondestructive examination options, which enables us to see clearly targets, even when they visually invisible, and thus has found many valuable applications in science, engineering and military. However, it is suffering from increasingly critical challenges from energy consumption, cost, efficiency, portability, etc., with the rapidly growing demands for the high-quality sensing with three-dimensional high-frame-rate schemes. To address these difficulties, we propose the concept of intelligent EM metasurface camera by the synergetic exploitation of inexpensive programmable metasurfaces with modern machine learning techniques, and establish a Bayesian inference framework for it. Such EM camera introduces the intelligence over the entire sensing chain of data acquisition and processing, and exhibits good performance in terms of the image quality and efficiency, even when it is deployed in highly noisy environment. Selected experimental results in real-world settings are provided to demonstrate that the developed EM metasurface camera enables us to see clearly human behaviors behind a 60 cm-thickness reinforced concrete wall with the frame rate in order of tens of Hz. We expect that the presented strategy could have considerable impacts on sensing and beyond, and open up a promising route toward smart community and beyond.

Применение неохлаждаемых микроболометров для регистрации импульсного терагерцового и инфракрасного излучения

Analytical relations for temperature response of the bolometer to periodic radiation pulses are obtained. It is theoretically shown and experimentally confirmed by the example of infrared bolometers that when detecting short radiation pulses, in contrast to the case of constant radiation, increasing the thermal conductivity of the bolometer and, accordingly, decreasing its thermal relaxation time, it is possible to significantly increase the response rate of the receiver, practically without reducing its sensitivity. The possibility of effective registration of pulsed terahertz radiation by microbolometers with a resistively coupled, thermally non-isolated antenna is considered. It is shown that such bolometers, which have increased thermal conductivity and, accordingly, reduced sensitivity to continuous-wave radiation, can be highly effective when detecting pulsed radiation with a duration shorter than the thermal relaxation time of the bolometer. On their basis, uncooled matrix detectors of pulsed terahertz radiation, characterized by a minimum detectable energy of less than 110-12 J and a frame rate of up to 1000 Hz, can be developed.

Single-shot experiments at the soft X-FEL FERMI using a back-side-illuminated scientific CMOS detector

The latest Complementary Metal Oxide Semiconductor (CMOS) 2D sensors now rival the performance of state-of-the-art photon detectors for optical application, combining a high-frame-rate speed with a wide dynamic range. While the advent of high-repetition-rate hard X-ray free-electron lasers (FELs) has boosted the development of complex large-area fast CCD detectors in the extreme ultraviolet (EUV) and soft X-ray domains, scientists lacked such high-performance 2D detectors, principally due to the very poor efficiency limited by the sensor processing. Recently, a new generation of large back-side-illuminated scientific CMOS sensors (CMOS-BSI) has been developed and commercialized. One of these cost-efficient and competitive sensors, the GSENSE400BSI, has been implemented and characterized, and the proof of concept has been carried out at a synchrotron or laser-based X-ray source. In this article, we explore the feasibility of single-shot ultra-fast experiments at FEL sources operating in the EUV/soft X-ray regime with an AXIS-SXR camera equipped with the GSENSE400BSI-TVISB sensor. We illustrate the detector capabilities by performing a soft X-ray magnetic scattering experiment at the DiProi end-station of the FERMI FEL. These measurements show the possibility of integrating this camera for collecting single-shot images at the 50 Hz operation mode of FERMI with a cropped image size of 700 × 700 pixels. The efficiency of the sensor at a working photon energy of 58 eV and the linearity over the large FEL intensity have been verified. Moreover, on-the-fly time-resolved single-shot X-ray resonant magnetic scattering imaging from prototype Co/Pt multilayer films has been carried out with a time collection gain of 30 compared to the classical start-and-stop acquisition method performed with the conventional CCD-BSI detector available at the end-station.