Augmenting Aquaculture Efficiency through Involutional Neural Networks and Self-Attention for Oplegnathus Punctatus Feeding Intensity Classification from Log Mel Spectrograms.

Understanding the feeding dynamics of aquatic animals is crucial for aquaculture optimization and ecosystem management. This paper proposes a novel framework for analyzing fish feeding behavior based on a fusion of spectrogram-extracted features and deep learning architecture. Raw audio waveforms are first transformed into Log Mel Spectrograms, and a fusion of features such as the Discrete Wavelet Transform, the Gabor filter, the Local Binary Pattern, and the Laplacian High Pass Filter, followed by a well-adapted deep model, is proposed to capture crucial spectral and spectral information that can help distinguish between the various forms of fish feeding behavior. The Involutional Neural Network (INN)-based deep learning model is used for classification, achieving an accuracy of up to 97% across various temporal segments. The proposed methodology is shown to be effective in accurately classifying the feeding intensities of Oplegnathus punctatus, enabling insights pertinent to aquaculture enhancement and ecosystem management. Future work may include additional feature extraction modalities and multi-modal data integration to further our understanding and contribute towards the sustainable management of marine resources.

Exploring Vibration Transmission Rule of an Artificial Spider Web for Potential Application in Invulnerability of Wireless Sensor Network.

Significant similarities exist between a spider web and wireless sensor network in terms of topology. Combining the unique advantages of the spider web in nature, such as invulnerability and robustness, with communication technology of a wireless sensor network presents high research value and broad development prospects. In this paper, a sort of a spiral artificial spider web based on 3D printing and its associated vibration testing device is proposed, which is used to study the transmission rule of vibration information of the spider web under given excitation conditions. It provides useful inspiration for establishment of an invulnerable communication rule of wireless sensor network. In order to investigate vibration transmission characteristics of the artificial spider web, vibration images are recorded and analyzed by a high-speed photography system, and vibration intensity is characterized by use of peak-to-peak value. Furthermore, vibration performance of the artificial spider web is studied under conditions of integrity and destruction, respectively. Our test observation reveals the vibration transmission rule of the unique structure of the spider web, providing a novel analysis method for improving invulnerability of the wireless sensor network.