Abstract: We have developed an innovative framework for analyzing online public sentiment, referred to as the Online Public Opinion Situation Assessment (OPOSA) model. This model employs Deep Sparse ...
Abstract: We introduce a new convolutional autoencoder architecture for user modeling and recommendation tasks with several improvements over the state of the art. First, our model has the flexibility ...
ABSTRACT: Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction ...
Chain information management system is widely used, providing convenience for the operation and management of enterprises. However, the problem of abnormal network traffic becomes increasingly ...
ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...
Human inventions, namely engineered systems, have relied on fundamental discoveries in physics and mathematics, e.g., Maxwell’s equations, Quantum mechanics, Information theory, etc., thereby applying ...
Classification of power system event data is a growing need, particularly where non-protective relaying-based sensors are used to monitor grid performance. Given the high burden of obtaining event ...
As advancements in cryo-electron tomography (cryo-ET) continue to uncover the structure of proteins in situ, the ability to collect thousands of tomograms places significant demands on the capability ...
Big Data Innovation and Entrepreneurship Education Center of Hunan Province, Changsha University, Changsha, China Introduction: Accumulating evidence shows that human health and disease are closely ...
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