With the continuous development of informationtechnology and communication technology, the introduction of computers into everyday work has brought a lot of unexpected convenience to the work. Many units and enterpri...
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The analysis of enterprise financial status is the key to enterprise management, which has an important impact on investment decision, risk control and strategic planning of enterprises. Although traditional financial...
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Traditional research is often limited to the independent application of electronic Internet of Things (IoT) technology or cloud computing, and lacks integration research between the two, resulting in certain limitatio...
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ISBN:
(纸本)9798350363272;9798350363265
Traditional research is often limited to the independent application of electronic Internet of Things (IoT) technology or cloud computing, and lacks integration research between the two, resulting in certain limitations in collaboration and efficiency when applied in the intelligent manufacturing industry. This article combines electronic IoT technology and cloud computing, using intelligent algorithms to promote the synergy of various technologies in the intelligent manufacturing industry and improve production efficiency. Collecting large-scale intelligent manufacturing data through sensors, this article would store the collected data on cloud platforms and preprocess it. It intelligently analyzes intelligent manufacturing data through an improved Long Short Term Memory (LSTM) model. The directions for improving LSTM models include introducing attention mechanisms and Dropout regularization techniques. The results show that the average output input ratios of traditional manufacturing enterprises and intelligent manufacturing enterprises are 1.35 and 3.87, respectively. Therefore, the application of electronic IoT technology and cloud computing can effectively improve the production efficiency of intelligent manufacturing.
This paper explores the challenges inherent in the traditional model of exam data processing at universities, where the centralized cloud server encounters issues such as bandwidth limitations, prolonged sending times...
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ISBN:
(纸本)9798400716713
This paper explores the challenges inherent in the traditional model of exam data processing at universities, where the centralized cloud server encounters issues such as bandwidth limitations, prolonged sending times, and data loss due to congestion. To address these shortcomings, we propose a novel approach leveraging smart router devices equipped with storage and computing units to deploy an edge computing model. In this model, the smart routers act as temporary storage locations, optimizing data processing by sending exam data to the cloud server during periods of reduced network traffic. Through a comprehensive demonstration, we validate the effectiveness of this edge computing model, showcasing its ability to enhance the speed of exam data submissions, streamline processing efficiency, and minimize data loss. Our findings advocate for the adoption of edge computing solutions, particularly through smart router integration, as a promising strategy to modernize exam data handling in traditional university settings.
As a new type of production factor, the openness and sharing of data resources have become an important way to develop digital value. However, necessary data privacy and data security protection cannot be ignored. How...
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Augmented Reality is presented as a solution to meet the needs of people who want to design and decorate their new living spaces or restore their existing ones, since they frequently struggle to see how different furn...
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We proposed an implementation for surfactant transport simulations in gas-liquid two-phase flows. This implementation employs a tree-based interface-adapted adaptive mesh refinement (AMR) method, assigning a high-reso...
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Authentic detection of deepfakes can be vital to fighting misinformation, safeguarding security, and preventing financial and reputational damage. The more it acquires human nature, the more dangerous deepfake technol...
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This paper presents a method for generating 3D and 4D star polytopes based on the Todd-Coxeter algorithm and Wythoff construction. This method can be used to calculate most of the 3-dimensional uniform star polytopes ...
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This study embarks on an analytical journey to forecast the NEV industry, leveraging advanced time series models including the Autoregressive Integrated Moving Average (ARIMA) algorithm and Long Short-Term Memory (LST...
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