Target recognition and segmentation in turbid water using data from non-turbid conditions: a unified approach and experimental validation.

Semantic segmentation of targets in underwater images within turbid water environments presents significant challenges, hindered by factors such as environmental variability, difficulties in acquiring datasets, imprecise data annotation, and the poor robustness of conventional methods. This paper addresses this issue by proposing a novel joint method using deep learning to effectively perform semantic segmentation tasks in turbid environments, with the practical case of efficiently collecting polymetallic nodules in deep-sea while minimizing damage to the seabed environment. Our approach includes a novel data expansion technique and a modified U-net based model. Drawing on the underwater image formation model, we introduce noise to clear water images to simulate images captured under varying degrees of turbidity, thus providing an alternative to the required data. Furthermore, traditional U-net-based modified models have shown limitations in enhancing performance in such tasks. Based on the primary factors underlying image degradation, we propose a new model which incorporates an improved dual-channel encoder. Our method significantly advances the fine segmentation of underwater images in turbid media, and experimental validation demonstrates its effectiveness and superiority under different turbidity conditions. The study provides new technical means for deep-sea resource development, holding broad application prospects and scientific value.

Three-Stage Interpolation Method for Demosaicking Monochrome Polarization DoFP Images.

The emergence of polarization image sensors presents both opportunities and challenges for real-time full-polarization reconstruction in scene imaging. This paper presents an innovative three-stage interpolation method specifically tailored for monochrome polarization image demosaicking, emphasizing both precision and processing speed. The method introduces a novel linear interpolation model based on polarization channel difference priors in the initial two stages. To enhance results through bidirectional interpolation, a continuous adaptive edge detection method based on variance differences is employed for weighted averaging. In the third stage, a total intensity map, derived from the previous two stages, is integrated into a residual interpolation process, thereby further elevating estimation precision. The proposed method undergoes validation using publicly available advanced datasets, showcasing superior performance in both global parameter evaluations and local visual details when compared with existing state-of-the-art techniques.

Fast image visibility enhancement based on active polarization and color constancy for operation in turbid water.

Vehicles operating in a water medium sometimes encounter harsh conditions with high turbidity and low scene illumination, making it challenging to obtain reliable target information through optical devices. Although many post-processing solutions were proposed, they are not applicable to continuous vehicle operations. Inspired by the advanced polarimetric hardware technology, a joint fast algorithm was developed in this study to address the above problems. Backscatter attenuation and direct signal attenuation were solved separately by utilizing the revised underwater polarimetric image formation model. A fast local adaptive Wiener filtering method was used to improve the backscatter estimation by reducing the additive noise. Further, the image was recovered using the fast local space average color method. By using a low-pass filter guided by the color constancy theory, the problems of nonuniform illumination caused by artificial light and direct signal attenuation were both addressed. The results of testing on images from laboratory experiments showed improved visibility and realistic chromatic rendition.

Shape Deformation and Drag Variation of a Coupled Rigid-Flexible System in a Flowing Soap Film.

We experimentally study the soap film flow past a rigid plate with a trailing closed filament of a small bending modulus acting as a flexible afterbody. The complex fluid-structure interactions due to the deformable afterbody shape and corresponding dynamics are studied. We find that the shape of the afterbody is determined by filament length, filament bending modulus, and flow speed. A significant drag reduction of approximately 10.0% is achieved under specific conditions. We analyze the drag mechanism by characterizing the deformable afterbody shape. Our experiment and modeling suggest that such a flow control strategy and sizable drag reduction are expected to occur over a specific flow speed regime when a suitable flexible coating is added.

An Acquisition Method of Agricultural Equipment Roll Angle Based on Multi-Source Information Fusion.

Accurately obtaining roll angles is one of the key technologies to improve the positioning accuracy and operation quality of agricultural equipment. Given the demand for the acquisition of agricultural equipment roll angles, a roll angle monitoring model based on Kalman filtering and multi-source information fusion was established by using the MTi-300 AHRS inertial sensor (INS) and XW-GI 5630 BeiDou Navigation Satellite System (BDS), which were installed on agricultural equipment. Data of the INS and BDS were fused by MATLAB; then, Kalman filter was used to optimize the data, and the state equation and measurement equation of the integrated system were established. Then, an integrated monitoring terminal man-machine interactive interface was designed on MATLAB GUI, and a roll angle monitoring system based on the INS and BDS was designed and applied into field experiments. The mean absolute error of the integrated monitoring system based on multi-source information fusion during field experiments was 0.72°, which was smaller compared with the mean absolute errors of roll angle monitored by the INS and BDS independently (0.78° and 0.75°, respectively). Thus, the roll angle integrated model improves monitoring precision and underlies future research on navigation and independent operation of agricultural equipment.

LatinPSO: An algorithm for simultaneously inferring structure and parameters of ordinary differential equations models.

Simultaneously inferring both the structure and parameters of Ordinary Differential Equations (ODEs) for a complex dynamic system is more practical in many systems identification problems, but it remains challenging due to the complexity of the underlying search space. In this research, we propose a novel algorithm based on Particle Swarm Optimization (PSO) and Latin Hypercube Sampling (LHS) to address the above problem. The proposed algorithm is termed LatinPSO, and it can be effectively used for inferring the structure and parameters of ODE models through time course data. To start with, the real Human Immunodeficiency Virus (HIV) model and several synthetic models are used for evaluating the performance of LatinPSO. Experimental results demonstrated that LatinPSO could find satisfactory candidate ODE models with appropriate structure and parameters.

[Nummular headache: 21 new cases and therapeutic results].

OBJECTIVE: To evaluate the clinical feature of nummular headache and the efficiency of treatment in China. METHOD: The data of 21 NH patients treated from February 2006 to February 2008, were analyzed. RESULTS: They were 9 men, 12 women, aged 37 +/- 12 (18 - 63) years. Headache history ranged from 7 days to 30 years. 13 patients reported head pain confined to a circular area of 0.6 to 5 centimeter, and the other 8 patients had pain in an elliptical area of 1 - 2 centimeter x 1.5 - 3 centimeter. The symptomatic area was located in the parietal (n = 7), occipital(n = 8), temporal (n = 6), or border regions between temporal and parietal (n = 1). The right side was affected in 10 patients and the left side in the 9 patients, the middle of occipital and parietal areas were affected in 1 patient, respectively. Seven patients had mild pain, 8 patients had moderate pain and 6 patients had severe pain. The characteristics of headache included stabbing pain (n = 6), sharp pain (n = 3), pulsating apin (n = 3), grinding pain (n = 1), exploding pain (n = 5), included light-dull apin (n = 3). Three patients were treated by local nerve block with lidocaine plus dexamethasone phosphate/acetate and one of them got some 30 hours of prominent pain relief, no relief was obtained for other two patients. One patient obtained pain remission by acupuncture after amitriptyline, paroxetine had been tried ineffectively. One patient, woman, 38 years old, was treated by carbamazepine (tegretol) and amitriptyline for 3 months and pain relief was obtained gradually and the head pain disappeared finally. 8 patients were treated effectively by amitriptyline combining indomethacium, ibuprofen or carbamazepine. One patient was treated effectively by nimodipine. 2 patients were treated ineffectively by amitriptyline combining indomethacium. 4 patients were not treated. 3 patients were lost to follow-up. CONCLUSION: NH is not very rare and some of NH patients may be treated effectively by acupuncture or amitriptyline combining indomethacium, ibuprofen or carbamazepine.