134 Result(s)
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Article
Few-shot named entity recognition framework for forestry science metadata extraction
The effective utilization of accumulated forestry science papers is of paramount significance in enhancing our understanding of the current state of forests and the formulation of strategies for forest environ...
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Chapter and Conference Paper
Desired Impact Time Range Based on BP Neural Network
This paper focuses on the analysis of the desired impact time range under multiple constraints. In order to solve the problem that the precision of the traditional formula method is not high enough to calculat...
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Chapter and Conference Paper
Deep-Aware Network for Removing Single Haze
Some dehazing methods based on traditional statistical theory are prone to suffering from the higher complexity and resulting in some lower degeneration phenomenon such as a few halo with discontinuities and l...
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Chapter and Conference Paper
Formal Analysis of 5G EAP-TLS 1.3
As the fifth-generation mobile network communication technology, 5G supports a wider range of application scenarios with faster speed and lower latency, so the importance of its security cannot be underestimat...
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Chapter and Conference Paper
Exploration on the Evaluation Index System of E-commerce Application Talents’ Literacy for Industry Needs
The rapidly develo** e-commerce industry has a huge demand for talents, and currently, the cultivation of talents in universities cannot meet the industry’s needs in terms of quantity and quality. To help un...
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Chapter and Conference Paper
The Users’ Purchase Behavior Research of Buying Clothing of Live Streaming eCommerce on Tiktok
This paper focuses on the Tiktok platform and clothing commodity categories, and takes consumers watching live shop** with goods as the main research object to conduct research on user purchase behavior. Bas...
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Chapter and Conference Paper
Research on Cosmetics Consumer Behavior Analysis and Marketing Strategy Optimization on E-Commerce Platform “**aohongshu”
Based on consumer behavior, marketing strategies, and related theories, this article takes the “**aohongshu” e-commerce platform as the research object. Through questionnaire surveys, literature research, and ...
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Chapter and Conference Paper
Chebyshev Inequality and the Identification of Genes Associated with Alzheimer’s Disease
Alzheimer’s disease (AD) is the most common form of dementia. However, its pathogenesis is not fully understood, and one of the methods to explore the pathogenesis of AD is to search for causative genes. In th...
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Article
Improving label quality in crowdsourcing using deep co-teaching-based noise correction
In the crowdsourcing scenario, repeated labeling is employed to obtain each instance’s multiple noisy label set from different crowd workers on the Internet, and then a ground truth inference method is used to...
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Article
A novel evolutionary algorithm inspired from triangle search and its applications on parameters identification of photovoltaic models
Parameters identification of photovoltaic (PV) models is significant for forecasting power of PV system and simulating the PV models. To accurately identify the parameters of different PV models based on measu...
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Article
A blockchain-based access control protocol for secure resource sharing with mobile edge-cloud collaboration
The application scenarios of edge-cloud collaboration are very wide. In order to ensure the operational security of resource sharing among intelligent terminals in edge-cloud collaboration scenarios, and preve...
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Article
Link prediction for heterogeneous information networks based on enhanced meta-path aggregation and attention mechanism
Heterogeneous link prediction aims to reveal potential connections between two nodes in heterogeneous information networks. Most existing studies are based on meta-paths, but ignore the information contained i...
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Article
Open AccessGAN-based deep learning framework of network reconstruction
Inferring the topology of a network from network dynamics is a significant problem with both theoretical research significance and practical value. This paper considers how to reconstruct the network topology ...
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Article
Open AccessEstimation for Human Motion Posture and Health Using Improved Deep Learning and Nano Biosensor
To improve the technical level of human motion posture and health estimation, a human motion posture and health estimation algorithm based on Nano biosensor and improved deep learning is proposed. First, we us...
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Article
Fine-grained image recognition via trusted multi-granularity information fusion
Fine-grained image recognition (FGIR) is more challenging than general image recognition tasks due to the inherently subtle object variation. The existing FGIR methods are mainly based on single-granularity fe...
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Chapter and Conference Paper
Teaching Dilemma and Solution of Mathematics Courses in Applied Undergraduate Universities Under the Background of Professional Certification
Based on the conditions and requirements of engineering certification, under the background of the cultivation of applied undergraduate talents, and in view of the problems existing in the teaching process of ...
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Chapter and Conference Paper
Dynamic Computing Offloading Strategy for Multi-dimensional Resources Based on MEC
Mobile edge computing (MEC) is a technology that extends network capabilities from the core network to the edge network, which effectively solves the problems of devices in terms of computing capacity, service...
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Chapter and Conference Paper
A Cooperative Interception Allocation Method Faced on 3D Reachable Area Prediction Based on Deep Neural Network
This paper studies the problem of multi-intercept missile cooperative interception allocation faced on three-dimensional reachable area prediction. The key points of this paper are using neural network to pred...
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Chapter and Conference Paper
Experimental Flipped Classroom Teaching Mode Based on Mobile Terminal
Flipped classroom provides a new way for teaching.
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Chapter and Conference Paper
Review on the Positioning Error Causes Analysis and Methods to Improve Positioning Accuracy of Parallel Robot
Accuracy is one of the most important performance indicators of Parallel Robots, which directly affects the quality of their working performance. In this paper, the existing research results are systematically...
