主要期刊主题：COMPUTER ARCHITECTURES AND NETWORKING并行和分布式计算理论基础软件工程知识和信息工程除了上面给出的主要主题外，编辑委员会还欢迎来自其他计算和信息学领域的论文。

This journal primarily focuses on the following topics: computer architectures and networking, parallel and distributed computing, theoretical foundations, software engineering, and knowledge and information engineering. In addition to the aforementioned topics, the editorial board also welcomes papers from other areas of computing and informatics.

本期刊主要关注以下主题：计算机体系结构与网络、并行与分布式计算、理论基础、软件工程、知识与信息工程。除了上述主题外，编辑委员会也欢迎来自其他计算和信息学领域的论文。

Computing and Informatics

How to eliminate useless information in the vast network information and retain effective information is a problem that needs to be continuously explored in the field of deep learning. This paper conducts text classification on the network evaluation frequently encountered in daily life, mainly to screen out the meaningless comments published by Internet users, to have access to more useful information. In this paper, a text filtering model was constructed based on word vector and Long Short-Term Memory (LSTM) and improved by adding Deep Averaging Networks (DAN) and convolutional neural network (CNN). The major improvement of the LSTM & DAN model was to retain the original word vector information and to improve the accuracy of the text classification model without increasing hyperparameter and model structure complexity. The LSTM & CNN model mainly combines the advantages of convolutional neural network in exploring the deep information of text, which was an improvement over the original LSTM. It was proved by experiments that this improvement is meaningful. Compared with the shallow neural network, the accuracy has been greatly improved.

Wei Dang

Ligao Cai

Mingzhe Liu

Xiaolu Li

Zhengtong Yin

Xuan Liu

Lirong Yin

Wenfeng Zheng

Increasing Text Filtering Accuracy with Improved LSTM

提高文本过滤准确性的改进LSTM方法

Wei Wu

Application and Effectiveness of IoT Edge and Fog Computing Technologies in Smart Energy Development with the Use of Encryption Algorithms and Security Systems

物联网边缘与雾计算技术在智能能源发展中的应用与效果，结合加密算法与安全系统

Ayako Ohshiro

Morikazu Nakamura

Bayesian Information Criterion Analysis for Accuracy Improvement of Multivariate Time Series Data Analysis

贝叶斯信息准则分析在多元时间序列数据分析精度提升中的应用

Shabnam Bawa

Prashant Singh Rana

Rajkumar Tekchandani

Multilevel Ensemble Model for Load Prediction on Hosts in Fog Computing Environment

雾计算环境下主机负载预测的多层次集成模型

Yun Jia

Lidan Yu

Jie Zhao

BDANet: Boosted Dense Attention Hierarchical Network for Image Denoising

BDANet：用于图像去噪的增强密集注意力分层网络

Dorcas Dachollom Datiri

Maozhen Li

Secure and Efficient Blockchain Scheme for Resource Optimization in Internet of Things (IoT) Systems

物联网系统中资源优化的安全高效区块链方案

Abbreviation	cai
Journal Impact	0.62
Quartiles(Global)	COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE(Q4)

ISSN	1335-9150, 2585-8807
h-index	31

Publication Information	Publisher: Slovak Academy of Sciences，Publishing cycle: Bimonthly，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 2000，Proportion of original research papers: 97.22%，Self Citation Rate:0.00%， Gold OA Rate: 0.00%
Average review cycle	网友分享经验：平均12.0个月
Average recruitment ratio	网友分享经验：容易

Computing and Informatics

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Increasing Text Filtering Accuracy with Improved LSTM

Application and Effectiveness of IoT Edge and Fog Computing Technologies in Smart Energy Development with the Use of Encryption Algorithms and Security Systems

Bayesian Information Criterion Analysis for Accuracy Improvement of Multivariate Time Series Data Analysis

Multilevel Ensemble Model for Load Prediction on Hosts in Fog Computing Environment

BDANet: Boosted Dense Attention Hierarchical Network for Image Denoising

Application and Effectiveness of IoT Edge and Fog Computing Technologies in Smart Energy Development with the Use of Encryption Algorithms and Security Systems

Bayesian Information Criterion Analysis for Accuracy Improvement of Multivariate Time Series Data Analysis

Multilevel Ensemble Model for Load Prediction on Hosts in Fog Computing Environment

BDANet: Boosted Dense Attention Hierarchical Network for Image Denoising

Secure and Efficient Blockchain Scheme for Resource Optimization in Internet of Things (IoT) Systems