In order to carry out a comprehensive design description of the specific architectural model of AI, the auxiliary model of AI and architectural spatial intelligence is deeply integrated, and flexible ...design is carried out according to the actual situation. AI assists in the generation of architectural intention and architectural form, mainly supporting academic and working theoretical models, promoting technological innovation, and thus improving the design efficiency of the architectural design industry. AI-aided architectural design enables every designer to achieve design freedom. At the same time, with the help of AI, architectural design can complete the corresponding work faster and more efficiently. With the help of AI technology, through the adjustment and optimization of keywords, AI automatically generates a batch of architectural space design schemes. Against this background, the auxiliary model of architectural space design is established through the literature research of the AI model, the architectural space intelligent auxiliary model, and the semantic network and the internal structure analysis of architectural space. Secondly, to ensure compliance with the three-dimensional characteristics of the architectural space from the data source, based on the analysis of the overall function and structure of space design, the intelligent design of the architectural space auxiliary by Deep Learning is carried out. Finally, it takes the 3D model selected in the UrbanScene3D data set as the research object, and the auxiliary performance of AI's architectural space intelligent model is tested. The research results show that with the increasing number of network nodes, the model fitting degree on the test data set and training data set is decreasing. The fitting curve of the comprehensive model shows that the intelligent design scheme of architectural space based on AI is superior to the traditional architectural design scheme. As the number of nodes in the network connection layer increases, the intelligent score of space temperature and humidity will continue to rise. The model can achieve the optimal intelligent auxiliary effect of architectural space. The research has practical application value for promoting the intelligent and digital transformation of architectural space design.
Aspect-based sentiment analysis (ABSA) aims to predict the sentiment expressed in a review with respect to a given aspect. The core of ABSA is to model the interaction between the context and given ...aspect to extract aspect-related information. In prior work, attention mechanisms and dependency graph networks are commonly adopted to capture the relations between the context and given aspect. And the weighted sum of context hidden states is used as the final representation fed to the classifier. However, the information related to the given aspect may be already discarded and adverse information may be retained in the context modeling processes of existing models. Such a problem cannot be solved by subsequent modules due to two reasons. First, their operations are conducted on the encoder-generated context hidden states, whose value cannot be changed after the encoder. Second, existing encoders only consider the context while not the given aspect. To address this problem, we argue the given aspect should be considered as a new clue out of context in the context modeling process. As for solutions, we design three streams of aspect-aware context encoders: an aspect-aware LSTM, an aspect-aware GCN, and three aspect-aware BERTs. They are dedicated to generating aspect-aware hidden states which are tailored for the ABSA task. In these aspect-aware context encoders, the semantics of the given aspect is used to regulate the information flow. Consequently, the aspect-related information can be retained and aspect-irrelevant information can be excluded in the generated hidden states. We conduct extensive experiments on several benchmark datasets with empirical analysis, demonstrating the efficacies and advantages of our proposed aspect-aware context encoders.
The traditional single-shot multiBox detector (SSD) for the recognition process in sea cucumbers has problems, such as an insufficient expression of features, heavy computation, and difficulty in ...application to embedded platforms. To solve these problems, we proposed an improved algorithm for sea cucumber detection based on the traditional SSD algorithm. MobileNetv1 is selected as the backbone of the SSD algorithm. We increase the feature receptive field by receptive field block (RFB) to increase feature details and location information of small targets. Combined with the attention mechanism, features at different depths are strengthened and irrelevant features are suppressed. The experimental results show that the improved algorithm has better performance than the traditional SSD algorithm. The average precision of the improved algorithm is increased by 5.1%. The improved algorithm is also more robust. Compared with YOLOv4 and the Faster R-CNN algorithm, the performance of this algorithm on the P-R curve is better, indicating that the performance of this algorithm is better. Thus, the improved algorithm can stably detect sea cucumbers in real time and provide reliable feedback information.
Currently, with the continuous improvements and advancements in artificial intelligence, wireless data transmission, and sensing technologies, increasing amounts of marine vehicles are being designed ...and applied to promote the marine economy and protect the environment ...
The direction estimation of the coherent source in a uniform circular array is an essential part of the signal processing area of the array, but the traditional uniform circular array algorithm has a ...low localization accuracy and a poor localization effect on the coherent source. To solve this problem, this paper proposes a two-dimensional direction of arrival (DOA) estimation for the coherent source in broadband. Firstly, the central frequency of the coherent sound source is estimated using the frequency estimation method of the delayed data, and a real-valued beamformer is constructed using the concept of the multiloop phase mode. Then, the cost function in the beam space is obtained. Finally, the cost function is searched in two dimensions to locate the sound source. In this paper, we simulate the DOA of the sound source at different frequencies and signal-to-noise ratios and analyze the resolution of the circular array. The simulation results show that the proposed algorithm can estimate the direction of arrival with high precision and achieve the desired results.
In this article, a capacitive angle encoder monitored and sensed by application specific integrated circuit (ASIC) with a sensitive structure fabricated by MEMS technology is proposed. The sensitive ...structure with a 27.5 mm outer diameter is designed and optimized in a limited footprint to realize higher accuracy. After being fabricated by MEMS technology, it is integrated with an ASIC, realizing high fabrication accuracy and a small footprint at the same time. The ASIC is designed in an analog-digital hybrid architecture to achieve low power consumption and a small footprint. The analog part of the ASIC consists of a charge to voltage converter with capacitance cancellation array and a sigma-delta modulator (SDM) with a 3-bit quantizer. In the digital part of ASIC, the processor based on Cortex-M3 core is designed to perform angle calculation. The measurement result of the proposed angle sensor reveals that the power consumption is 250 mW from a single 5-V supply, the bandwidth is over 130 Hz, the resolution is 0.002°, and the accuracy over the full range is 0.024°, indicating that the encoder has considerable potential for use in high-precision applications.
Abstract
Holothurians can integrate into nearby environment by changing body color which increased the difficulty of version identification. A U-Net network based visual recognition algorithm ...suitable for underwater organisms was proposed. The backbone feature extraction network adopted VGG16. In additional, upper sampling was used twice for feature fusion. Test results shown that the algorithm has high recognition accuracy and good feature extraction for holothurian with different shapes in natural environment.
This article proposes a high-precision incremental capacitive angle encoder based on microfabrication technology. Compared to traditional printed circuit board technology, the encoder manufactured by ...microfabrication technology has higher processing accuracy and better temperature characteristics. Further, the microfabrication technology makes the encoder obtain larger sensitive capacitances and achieve more electrical cycle divisions within a smaller volume. To overcome the effect of the parasitic parameters led by microfabrication technology, electric models were established and analyzed, and the solution was proposed. First, to reduce the parasitic capacitance coupling to the ground, the process materials and fabrication steps are improved and optimized. Then, a differential structure on excitation voltage wires is adopted to minimize the nonlinear error on the measurement results. In addition, the collection electrode interconnection model is optimized to reduce parasitic parameters on the collection and enhance the signal to noise ratio. Both analytical calculation and finite-element analysis results verified the feasibility of the improvement and optimization. Finally, the optimized prototype is fabricated and measured, and the result shows that the prototype can achieve 0.0002° measurement resolution and 0.0012° measurement accuracy within a 58 mm diameter.
Abstract
In order to improve and verify the application value of AIS data in fishing behavior analysis, three existing models were chosen to analyze the fishing paths of more than 200 boats around ...Zhoushan Islands. In order to confirm their operation mode, F1-score was used to evaluate related models. Experimental results shown that the Lightgbm model embodies better performance in the analysis of fishing boat behavior with higher practicality.
The path planning strategy of deep-sea mining vehicles is an important factor affecting the efficiency of deep-sea mining missions. However, the current traditional path planning algorithms suffer ...from hose entanglement problems and small coverage in the path planning of mining vehicle cluster. To improve the security and coverage of deep-sea mining systems, this paper proposes a cluster-coverage path planning strategy based on a traditional algorithm and Deep Q Network (DQN). First, we designed a deep-sea mining environment modeling and map decomposition method. Subsequently, the path planning strategy design is based on traditional algorithms and DQN. Considering the actual needs of deep-sea mining missions, the mining vehicle cluster path planning algorithm is optimized in several aspects, such as loss function, neural network structure, sample selection mechanism, constraints, and reward function. Finally, we conducted simulation experiments and analysis of the algorithm on the simulation platform. The experimental results show that the deep-sea mining cluster path planning strategy proposed in this paper performs better in terms of security, coverage, and coverage rate.
