Plankton size spectra monitoring is crucial for managing and conserving aquatic ecosystems. Thus, we develop an in situ size spectra monitoring system to obtain the size spectra of plankton and the information of their living status underwater. The system consists of an imaging unit and an information processing unit. The imaging part applies a darkfield illumination to enhance the image contrast. Three lenses with different magnifications are alternated by a motor automatically to capture sizes of plankton from $3\,\mu$ m to $3\,\text{mm}$ . Moreover, the system can analyze the captured images in real time using the proposed multitask size spectra convolutional neural network, obtaining size spectra and density distribution of plankton simultaneously. Field test confirms that our system performs well both in imaging and information processing. Furthermore, the system can provide the living behavior of plankton, thereby helping biologists to study the aquatic ecosystem effectively and precisely.

The image quality might be degraded severely due to water scatterings, especially near-shore water scatterings. In addition, the degraded image reduces the accuracy of underwater 3D reconstruction. We propose an underwater imaging system based on light field camera array to obtain enhanced high-quality images and accurate three-dimensional reconstruction from harsh underwater environments. Both 2D-imaging and 3D-reconstruction using light-field imaging were studied by experiments. By refocusing and analyzing the light field images of the target through turbid water, we obtained accurate three-dimensional estimations in the underwater scene. These experiments confirm the reliability of our method, showing that the SSIM (structural similarity) value of the system in turbid water is 0.378, compared to 0.197, the SSIM value of conventional single-camera imaging in the experiments. Therefore, we verify that the light field imaging system is less affected by forward scattering of water and has a larger detective range than conventional single-camera imaging with any specific resolution.

Detection of underwater bubbles is one of the key issues of the research of ocean-atmosphere flux exchange. Digital holographic experiment is carried out based on Mach-Zehnder digital holographic system, to detect the distribution of bubbles. Holographic images of the dynamical bubble fields are recorded by the chargecoupled device (CCD) video system and the tomographic images at different depth are reproduced. The distribution of sizes and densities of the bubbles is obtained through following steps as denoising, edgedetection, and bubble-recognition using Hough transform. Through the experiments, the efficiency and applicability of the digital holographic detection of underwater bubble fields are tested and verified.

We consider a risk-aware multi-armed bandit framework with the goal of avoiding catastrophic risk. Such a framework has multiple applications in financial risk management. We introduce a new conditional value-at-risk (CVaR) estimation procedure combining extreme value theory with automated threshold selection by ordered goodness-of-fit tests, and we apply this procedure to a pure exploration best-arm identification problem under a fixed budget. We empirically compare our results with the commonly used sample average estimator of the CVaR, and we show a significant performance improvement when the underlying arm distributions are heavy-tailed.

Due to the limited processing accuracy of the platform and unevenness of the glass substrate itself, a holographic lithography system is prone to out-of-focus imaging problems; therefore, the real-time focusing components are critical for holographic lithography systems. In this paper, a real-time focus monitoring and adjusting system using an electrically tunable lens (ETL) for large-area lithography is introduced. Combined with the ETL, the limited depth of field of the microscopic objective has been effectively expanded, and the automatic focusing evaluation and adjustment are achieved. The development, including simulation using Zemax, optics system design and implementation, experiments, and evaluation are demonstrated in this paper. The results show that the out-of-focus problem in our large-area holographic lithography system has been significantly alleviated.