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With respect to the detection and recognition of an Artificial Modulation Target (AMT) with different modulated types, the state-of-the-art methods generally suffer the deficiencies of overfitting and insufficient generalization of existing neural network solutions. To address these problems, this paper proposes a multi-scale amplitude-phase feature discrimination method for AMTs in SAR images. First, a multi-type modulated AMT Dataset is generated (AMT Detection and Modulation Type Recognition Dataset, ADMTR Dataset), wherein the factors of jamming position, jamming-to-signal ratio (JSR), and the modulated parameter are considered to enhance the generalization. Second, a Multi-Input Multi-Output Fusion Wavelet Neural Network (MIMOFWTNN) is established, which not only uses the amplitude information of the scene but also adequately makes use of the phase and high-frequency information. This empowers us to detect the AMT in a higher dimensional feature space such that the type recognition can be implemented with more certainty. Analysis and discussions conducted on comparison experiments and ablation experiments demonstrate that the proposed network can achieve an average accuracy of 96.96% on the cross-validation set and a correct rate of 99.0% on the completely independent test set, which outperforms the compared methods. [ABSTRACT FROM AUTHOR]

The study aimed to investigate the effects of temperature and dissolved oxygen on juvenile largemouth bass during transportation. The experiment involved four temperature groups: 20, 15, 10, and 5 °C. We analyzed the effects of acute and uniform cooling on fish behavior to determine the optimal approach for cooling. Then, we simulated transport under different temperature conditions while measuring the dissolved oxygen level and metabolic rate until all the fish died. The results showed that acute cooling significantly influenced the tail-beat frequency of fish compared with uniform cooling, while abnormal behaviors such as increased swimming, attempted jumping out of the water, and loss of balance were observed. As the transport temperature reduced, the oxygen consumption rate of fish significantly changed at 10 °C, being 2.6 times lower than at 15 °C, with values of 0.10 ± 0.02 and 0.47 ± 0.07 mg·g−1·h−1, respectively. The critical oxygen threshold (Pcrit) of fish were 1.90 ± 0.12, 1.61 ± 0.04, 1.15 ± 0.09, and 1.12 ± 0.25 mg·L−1 at 5, 10, 15, and 20 °C. In addition, below Pcrit, hypoxia-led behavior changes and oxygen consumption rate reduction were observed at every transport temperature. The findings suggest that the optimal low temperature can reduce metabolism and improve the hypoxia tolerance of juvenile largemouth bass. We recommend transporting largemouth bass at an optimal low temperature (15 °C), monitoring fish behavior, and maintaining oxygen levels above Pcrit during transport to prevent stress. [ABSTRACT FROM AUTHOR]

The consumption of phased array radar (PAR) resources affects the accuracy of its multi-target searching and tracking abilities. The jamming methods aimed at PAR involve deceptive jamming and comprehensive jamming strategies, but have the disadvantages of high cost and complexity. Given this context, this paper proposes a PAR resource consumption method based on phase-switched screen (PSS), and derives a relationship between the targets and the evaluation indicators. By implementing periodic modulation of PSS, a controlled number of deceptive multiple false targets can be generated, thereby enticing the radar system to engage in activities such as searching and tracking targets. When the quantity of false targets is increased, the number of beam requests becomes five times higher than compared to the scenario without false targets. This has also led the margin of time resources to exceed 50%, successfully achieving the objective of consuming radar resources. Furthermore, this method offers straightforward manipulation, flexibility, and the potential to significantly consume radar resources. The efficacy of the proposed method is confirmed with the simulation outcomes. [ABSTRACT FROM AUTHOR]

Track processing is the foundation of radar multi-target tracking, and the processing performance for jamming has particular research significance when it comes to protecting high-value targets. At present, passive jamming using a modulated metasurface exhibits a fast response and a flexible operation mode. However, most research in this area has been carried out at the radar signal processing level and less at the data processing level. In this paper, a range of false target track deception method based on a phase-switched screen (PSS) is proposed, and the relationship between the matched filtering output, radar detection, and track processing is derived. This method uses PSS to generate multiple false targets with controlled spatial distribution and magnitude, which can form high-fidelity false tracking tracks. The number of false tracking tracks can be flexibly altered by controlling the modulation parameters. The simulation results validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Marine aquaculture facilities have been working in a high salt and humidity marine environment for a long time, which makes them be inevitably affected by seawater corrosion, especially the main structures such as metal mesh and frame. Therefore, studying the corrosion behavior of net and frame steel is of great significance for the selection of materials and corrosion protection of marine aquaculture facilities. The influence of NaCl concentrations and immersion state on self-corrosion behavior and the influence of layer thickness and overlapping area on galvanic corrosion behavior of H62 copper alloy mesh/D36 steel plate was discussed in this study using weight loss and electrochemical measurements. The tensile tests were conducted to observe the influence of different corrosion conditions on maximum force and tensile strength of the net. The corrosion rate of the two materials increased rapidly with the increase of NaCl concentrations; the corrosion rate of both materials showed the decreasing trend with the extension of time, and the corrosion rate of H62 was always lower than D36 steel. When two materials were coupled, the galvanic corrosion rate would decrease with the increase of the layer thickness and overlapping area. The tensile results were consistent with the corrosion results. When these two materials work together, adding layer thickness or increasing the overlapping area is one of the ways to protect the frame steel to a certain extent. [ABSTRACT FROM AUTHOR]

Interrupted-sampling repeater modulation (ISRM) can generate multiple virtual target images by sampling and forwarding radar signals to confront the inverse synthetic aperture radar (ISAR). However, the repeating delay is unavoidable and the system is complex. Moreover, numerous works mainly discuss the ISAR image deception based on periodic modulation, and the modulation effect is relatively limited. Active frequency selective surface (AFSS) can perform intermittent amplitude modulation to the reflected signal by varying target reflectivity, thus, it can achieve the function of ISRM. In this paper, the possibility of AFSS applied in the multiple virtual target generation is discussed, and an ISAR image-modulation method is proposed. The radar signal is periodically modulated by varying target reflectivity, which is accomplished by the AFSS-loaded PIN diodes. On this basis, the AFSS modulating frequency is randomly varied in a slow time domain. When the modulation signal is processed by the ISAR system, the produced target image is unfocused and cannot be recognized by radar. Simulation results are utilized to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Time-modulated metasurfaces have attracted much attention due to their flexible manipulation of electromagnetic waves. Time-varying response leads to spread-spectrum and reallocation of energy. Thus, an amplitude-phase joint modulation (TAJM) method is proposed based on a time-modulated active polarization conversion metasurface (APCM). Taking radar high resolution range profile (HRRP) as the object, the distance transformation and multi-target phenomena are further discovered. The proposed method achieves a flexible manipulation of target amplitude and phase. The relationship between the modulation parameters and HRRP feature is studied. It is revealed that the absorption depth is the dominant factor for the energy distribution of TAJM. The method can be applied to multi-target generation and target feature manipulation. [ABSTRACT FROM AUTHOR]

In this paper, an active polarization conversion metasurface (APCM) operating in the X-band (8–12 GHz) is presented. Active unit cells consist of three metal layers and two substrate layers. Anisotropic metal patches, positive-intrinsic-negative (PIN) diodes, and bias lines are integrated into the surface layer to form a chiral structure. A simple and efficient polarization conversion function is realized in this designed structure. The operating mode is switched between linear-to-linear (LTL) polarization conversion and linear-to-circular (LTC) polarization conversion by switching the loaded PIN diode. In the LTL polarization conversion state, the polarization conversion ratio of APCM is over 90% in X-band. Reflected wave circular polarization axis ratio <3 dB in 8–12 GHz when in LTC state. The proposed structure is verified by experimental measurements. [ABSTRACT FROM AUTHOR]

In recent years, the development of China's marine aquaculture has brought serious challenges to the marine ecological environment. Therefore, it is significant to classify and extract the aquaculture zone and spatial distribution in order to provide a reference for aquaculture management. However, considering the complex marine aquaculture environment, it is difficult for traditional remote sensing technology and deep learning to achieve a breakthrough in the extraction of large-scale aquaculture zones so far. This study proposes a method based on the combination of piecewise linear stretching and R3Det to classify and extract raft aquaculture and cage aquaculture zones. The grayscale value is changed by piecewise linear stretching to reduce the influence of complex aquaculture backgrounds on the extraction accuracy, to effectively highlight the appearance characteristics of the aquaculture zone, and to improve the image contrast. On this basis, the aquaculture zone is classified and extracted by R3Det. Taking the aquaculture zone of Sansha Bay as the research object, the experimental results showed that the accuracy of R3Det in extracting the number of raft aquaculture and cage aquaculture zones was 98.91% and 97.21%, respectively, and the extraction precision of the area of the aquaculture zone reached 92.08%. The proposed method can classify and extract large-scale marine aquaculture zones more simply and efficiently than common remote sensing techniques. [ABSTRACT FROM AUTHOR]

A pile–net enclosure aquaculture facility, deployed in inshore waters, is a sustainable and ecological aquaculture pattern for rearing fish and other aquatic animals of economic value in China. It is essential to study the maximum force on and deformation of the net system of a pile–net enclosure facility to prevent its failure, since successful aquaculture is highly dependent on the longevity of the net system. In this study, a pile-net enclosure aquaculture facility with a gapped pile-net configuration was numerically investigated based on the lumped mass model. A Newton's second-law-based motion equation was solved using Euler's method. Finally, MATLAB was used to visualize the results. The results highlight that the force of a net system significantly increases with ocean loads, and the load of the entire net is mainly from the top half of the net. Moreover, the maximum force of the vertical rope occurs at the connection of the top channel steel. The maximum force of the horizontal rope and net twine occur in the rope near the still-water level and at the connection of the top channel steel, respectively. Thus, the net at those positions should be reinforced to prevent its failure. [ABSTRACT FROM AUTHOR]

The traditional corner reflector is a type of classical passive jamming equipment but with several shortcomings, such as fixed electromagnetic characteristics and a poor response to radar polarization. In this paper, an eight-quadrant corner reflector equipped with an electronically controlled miniaturized active frequency-selective surface (MAFSS) for X band is proposed to obtain better radar characteristics controllability and polarization adaptability. The scattering characteristics of the new eight-quadrant corner reflector for different switchable scattering states (penetration/reflection), frequency and polarization are simulated and analyzed. Results show that the RCS modulation depth, which is jointly affected by the electromagnetic wave frequency and incident directions, can be maintained above 10 dB in the majority of directions, and even larger than 30 dB at the resonant frequency. Moreover, the RCS adjustable bandwidth can be as wide as 1 GHz in different incident directions. [ABSTRACT FROM AUTHOR]

Netting damage limits the safe development of marine aquaculture. In order to identify and locate damaged netting accurately, we propose a detection method using an improved Mask R-CNN. We create an image dataset of different kinds of damage from a mix of conditions and enhance it by data augmentation. We then introduce the Recursive Feature Pyramid (RFP) and Deformable Convolution Network (DCN) structures into the learning framework to optimize the basic backbone for a marine environment and build a feature map with both high-level semantic and low-level localization information of the network. This modification solves the problem of poor detection performance in damaged nets with small and irregular damage. Experimental results show that these changes improve the average precision of the model significantly, to 94.48%, which is 7.86% higher than the original method. The enhanced model performs rapidly, with a missing rate of about 7.12% and a detection period of 4.74 frames per second. Compared with traditional image processing methods, the proposed netting damage detection model is robust and better balances detection precision and speed. Our method provides an effective solution for detecting netting damage in marine aquaculture environments. [ABSTRACT FROM AUTHOR]

The anchor pile is widely used in marine aquaculture, and its uplift resistance capacity determines the safety performance of the marine aquaculture structure. Cyclic loads such as wind, waves, and currents in the marine environment affect the uplift resistance capacity of anchor piles. By carrying out a cyclic loading model test of anchor piles for marine aquaculture, the influence of loading amplitude, initial tension angle, and other factors on the uplift resistance of anchor piles was investigated. The experimental results showed that with an increase in the loading amplitude, the cumulative displacement and elastic displacement of the anchor pile under vertical and oblique loading increase, and the stiffness of the soil around the anchor piles decreases. The stability of the anchor piles is reduced. When the loading amplitude is the same, with the increase in the initial loading angle, the lateral cumulative displacement of the anchor pile increases. Meanwhile, the vertical cumulative displacement decreases, the stiffness of the soil around the anchor pile decreases, and the stability decreases. [ABSTRACT FROM AUTHOR]

Road extraction is important for road network renewal, intelligent transportation systems and smart cities. This paper proposes an effective method to improve road extraction accuracy and reconstruct the broken road lines caused by ground occlusion. Firstly, an attention mechanism-based convolution neural network is established to enhance feature extraction capability. By highlighting key areas and restraining interference features, the road extraction accuracy is improved. Secondly, for the common broken road problem in the extraction results, a heuristic method based on connected domain analysis is proposed to reconstruct the road. An experiment is carried out on a benchmark dataset to prove the effectiveness of this method, and the result is compared with that of several famous deep learning models including FCN8s, SegNet, U-Net and D-Linknet. The comparison shows that this model increases the IOU value and the F1 score by 3.35–12.8% and 2.41–9.8%, respectively. Additionally, the result proves the proposed method is effective at extracting roads from occluded areas. [ABSTRACT FROM AUTHOR]

Accurately building height estimation from remote sensing imagery is an important and challenging task. However, the existing shadow-based building height estimation methods have large errors due to the complex environment in remote sensing imagery. In this paper, we propose a multi-scene building height estimation method based on shadow in high resolution imagery. First, the shadow of building is classified and described by analyzing the features of building shadow in remote sensing imagery. Second, a variety of shadow-based building height estimation models is established in different scenes. In addition, a method of shadow regularization extraction is proposed, which can solve the problem of mutual adhesion shadows in dense building areas effectively. Finally, we propose a method for shadow length calculation combines with the fish net and the pauta criterion, which means that the large error caused by the complex shape of building shadow can be avoided. Multi-scene areas are selected for experimental analysis to prove the validity of our method. The experiment results show that the accuracy rate is as high as 96% within 2 m of absolute error of our method. In addition, we compared our proposed approach with the existing methods, and the results show that the absolute error of our method are reduced by 1.24 m–3.76 m, which can achieve high-precision estimation of building height. [ABSTRACT FROM AUTHOR]