Li-Fi is another term for Visible light communication (VLC) which operates by transmitting data through free space by using either Light Emitting Diodes (LEDs) or Laser Diodes (LDs). The technique finds substantial ap...
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For the application of industrial robots, positioning accuracy is a significant indicator of their performance. Aiming at the issues of low positioning accuracy, the calibration techniques are employed to obtain the r...
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Harmonic radar systems are used to interrogate, or track a location of, passive nonlinear targets in highly cluttered environments, and they are notorious for their poor power efficiency and low detection ranges. Due ...
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The charging load of electric vehicles(EVs)has a strong spatiotemporal *** the dynamic spatiotemporal distribution of the charging load of EVs is of great significance for the grid to cope with the access of large-sca...
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The charging load of electric vehicles(EVs)has a strong spatiotemporal *** the dynamic spatiotemporal distribution of the charging load of EVs is of great significance for the grid to cope with the access of large-scale *** studies lack a prediction model that can accurately describe the dual dynamic changes of EVs charging the load time and ***,a spatial-temporal dynamic load forecasting model,dilated causal convolution-2D neural network(DCC-2D),is ***,a hole factor is added to the time dimension of the three-dimensional convolutional convolution kernel to form a two-dimensional hole convolution layer so that the model can learn the spatial dimension *** entire network is then formed by stacking the layers,ensuring that the network can accept long-term historical input,enabling the model to learn time dimension *** model is simulated with the actual data of the charging pile load in a certain area and compared with the ConvLSTM *** results prove the validity of the proposed prediction model.
Policy gradient algorithms have been shown to converge to the optimal controller in a linear quadratic regulator (LQR) design problem. Calculating policy gradients using the true system such as for a robot may, howeve...
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This paper examines the use of IoT-integrated Convolutional Neural Networks (CNNs) for precise analysis of vehicle audio signals. The context highlights the growing intricacy of vehicle systems and the need for advanc...
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Automated emotion recognition and identification and its subsequent challenges have a long history. More recently, intense scientific research on computer based evaluation of human emotions has arrived at a crossroad....
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In this paper, optimization model for energy management in the prosumer power system is presented. Previous passive electricity consumers by integrating the renewable energy sources in their possession become consumer...
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We present a novel framework for learning system design with neural feature extractors. First, we introduce the feature geometry, which unifies statistical dependence and feature representations in a function space eq...
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We present a novel framework for learning system design with neural feature extractors. First, we introduce the feature geometry, which unifies statistical dependence and feature representations in a function space equipped with inner products. This connection defines function-space concepts on statistical dependence, such as norms, orthogonal projection, and spectral decomposition, exhibiting clear operational meanings. In particular, we associate each learning setting with a dependence component and formulate learning tasks as finding corresponding feature approximations. We propose a nesting technique, which provides systematic algorithm designs for learning the optimal features from data samples with off-the-shelf network architectures and optimizers. We further demonstrate multivariate learning applications, including conditional inference and multimodal learning, where we present the optimal features and reveal their connections to classical approaches.
Plant diseases affect the health and yield of the crop which can in turn impact farmers economically and pose a threat to food security across the globe. To protect crops from disease and obtain high yield, many Agric...
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