Pub Date : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00046
Han Zhang, Huo Liu, Weiguo Xiong, Jun Fang
Geological disaster monitoring can provide useful information for natural disaster early warning. In this study, the existing geological disaster monitoring sensor technology, monitoring technology is summarized. The theory, function and characteristics of the existing geological disaster monitoring sensors are introduced in detail. Several frequently used geological disaster monitoring technologies are described, and their advantages and disadvantages are compared and analyzed. Finally, the development trend of geological disaster monitoring technology is predicted.
{"title":"Review and Prospect of Geological Hazard Monitoring Methods","authors":"Han Zhang, Huo Liu, Weiguo Xiong, Jun Fang","doi":"10.1109/ICNISC57059.2022.00046","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00046","url":null,"abstract":"Geological disaster monitoring can provide useful information for natural disaster early warning. In this study, the existing geological disaster monitoring sensor technology, monitoring technology is summarized. The theory, function and characteristics of the existing geological disaster monitoring sensors are introduced in detail. Several frequently used geological disaster monitoring technologies are described, and their advantages and disadvantages are compared and analyzed. Finally, the development trend of geological disaster monitoring technology is predicted.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117351747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00030
Zuhua Fang, Jiale Wang
In this paper, a system based on the AFE4403 chip is built to acquire the Photoplethysmography signal. This study aims to explore the light intensity changes of the monochromatic light to the reflected light after entering the human tissue with the human heartbeat. The Photoplethysmography signal is acquired by the photoelectric sensor, and the signal is de-baseline drifted and eliminated. The features of the Photoplethysmography signal is extracted, and the bleeding oxygen saturation is calculated by using its features.
{"title":"Noise Filtering of Photoplethysmography Signal Based on AFE4403","authors":"Zuhua Fang, Jiale Wang","doi":"10.1109/ICNISC57059.2022.00030","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00030","url":null,"abstract":"In this paper, a system based on the AFE4403 chip is built to acquire the Photoplethysmography signal. This study aims to explore the light intensity changes of the monochromatic light to the reflected light after entering the human tissue with the human heartbeat. The Photoplethysmography signal is acquired by the photoelectric sensor, and the signal is de-baseline drifted and eliminated. The features of the Photoplethysmography signal is extracted, and the bleeding oxygen saturation is calculated by using its features.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115682324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00089
Xuebing Zhang
As the digitalization process continues to advance, the scope of application of digital technology continues to expand, especially in the fields of finance and management. In the future, enterprises will inevitably establish financial and financial resource information bases through digital technology, and rely more on mid-to-high-end talents who effectively integrate financial and data analysis. Up to now, the training methods and means of financial accounting students in most colleges and universities follow the convention, which can not make the students' practical operation ability and data analysis ability keep pace with the times, resulting in the mismatch between the students trained by the school and the talents needed by the society. In response to the above problems, this paper discusses the possibility and achievability of adjusting the direction and goals of talent training by optimizing curriculum design and content, and strengthening the transformation of teachers' teaching methods, which will improve the degree of adaptation between students and enterprises, and then provide suggestions for the connection and integration of education and industry.
{"title":"Exploration and Research on The Training Path of Accounting Professionals Under The Background of “New Mode And New Value” Digitalization","authors":"Xuebing Zhang","doi":"10.1109/ICNISC57059.2022.00089","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00089","url":null,"abstract":"As the digitalization process continues to advance, the scope of application of digital technology continues to expand, especially in the fields of finance and management. In the future, enterprises will inevitably establish financial and financial resource information bases through digital technology, and rely more on mid-to-high-end talents who effectively integrate financial and data analysis. Up to now, the training methods and means of financial accounting students in most colleges and universities follow the convention, which can not make the students' practical operation ability and data analysis ability keep pace with the times, resulting in the mismatch between the students trained by the school and the talents needed by the society. In response to the above problems, this paper discusses the possibility and achievability of adjusting the direction and goals of talent training by optimizing curriculum design and content, and strengthening the transformation of teachers' teaching methods, which will improve the degree of adaptation between students and enterprises, and then provide suggestions for the connection and integration of education and industry.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132533662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00157
Kecheng Liu, Haojun Bi, Lijun Zhang, Yingnan Wang
Construct water system structure of thermal power plant based on decentralized wastewater treatment network which is composed of water consuming units and wastewater treatment units. Based on this structure, a nonconvex optimization problem is proposed in this paper and the present mathematical method cannot guarantee the exact solution. So we propose Artificial Bee Colony (ABC) algorithm to solve this complex model. Apply this algorithm to the solution of two examples, the solving process of examples shows that ABC algorithm has the advantages of fast solving speed, high solving accuracy and has a strong adaptability to different situations without relying on an initial point.
{"title":"Optimization of Industrial Water System Based on Artificial Bee Colony Algorithm","authors":"Kecheng Liu, Haojun Bi, Lijun Zhang, Yingnan Wang","doi":"10.1109/ICNISC57059.2022.00157","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00157","url":null,"abstract":"Construct water system structure of thermal power plant based on decentralized wastewater treatment network which is composed of water consuming units and wastewater treatment units. Based on this structure, a nonconvex optimization problem is proposed in this paper and the present mathematical method cannot guarantee the exact solution. So we propose Artificial Bee Colony (ABC) algorithm to solve this complex model. Apply this algorithm to the solution of two examples, the solving process of examples shows that ABC algorithm has the advantages of fast solving speed, high solving accuracy and has a strong adaptability to different situations without relying on an initial point.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131600889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00012
Wei Wei
Based on the background of wisdom tourism with Internet and cloud computing, the author introduces the main functions of the cultural tourism big data platform from the aspects of tourist transportation, catering and accommodation and the intellectualization of tourism organization, and analyzes the design and realization path of the system. It has been proved by practice that strengthening the application of Internet and cloud computing technology can effectively improve the effect of the cultural tourism big data platform construction, which is conducive to the healthy and sustainable development of overall cultural tourism industry, so as to promote the career of rural revitalization.
{"title":"Design and Development of the Cultural Tourism Big Data Platform Based on Internet + Cloud Computing","authors":"Wei Wei","doi":"10.1109/ICNISC57059.2022.00012","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00012","url":null,"abstract":"Based on the background of wisdom tourism with Internet and cloud computing, the author introduces the main functions of the cultural tourism big data platform from the aspects of tourist transportation, catering and accommodation and the intellectualization of tourism organization, and analyzes the design and realization path of the system. It has been proved by practice that strengthening the application of Internet and cloud computing technology can effectively improve the effect of the cultural tourism big data platform construction, which is conducive to the healthy and sustainable development of overall cultural tourism industry, so as to promote the career of rural revitalization.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130822312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00143
Qi Liu, Penghao Fan, Shaoliang Ling, Yi Zhai, Chunyao Liu, Qijing Yang, Weihua Cao
To solve the problem of grid model updating in the model data center of the new generation dispatching-and-control system, a real-time model synchronization scheme based on the new generation dispatching-and-control system is proposed for incremental synchronization of model data structure transformation and operation state inspection, and the working principle of the scheme is introduced in detail. Practice shows that as a key link to ensure the consistency of heterogeneous grid models between the model data cloud platform and the new generation dispatching-and-control system, the method proposed in this paper solves the conversion requirements between heterogeneous grid models and has good social and economic benefits.
{"title":"Research on Real-time Model Synchronization Method Based on New Generation Dispatching-and-control System","authors":"Qi Liu, Penghao Fan, Shaoliang Ling, Yi Zhai, Chunyao Liu, Qijing Yang, Weihua Cao","doi":"10.1109/ICNISC57059.2022.00143","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00143","url":null,"abstract":"To solve the problem of grid model updating in the model data center of the new generation dispatching-and-control system, a real-time model synchronization scheme based on the new generation dispatching-and-control system is proposed for incremental synchronization of model data structure transformation and operation state inspection, and the working principle of the scheme is introduced in detail. Practice shows that as a key link to ensure the consistency of heterogeneous grid models between the model data cloud platform and the new generation dispatching-and-control system, the method proposed in this paper solves the conversion requirements between heterogeneous grid models and has good social and economic benefits.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130839801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00041
Xiangyuan Wang, Wozhan Li, Xiaochuan Wu, Ying Suo, Qiang Yang
High Frequency Surface Wave Radar (HFSWR) suffers seriously with the ionospheric clutter formed from ionosphere echoes. The ionospheric clutter could be extensive and exists all day long, which restricts the detection performance of HFSWR. It is necessary to eliminate the interference of ionospheric clutter which overwhelms target echoes always. However, there is not a prior knowledge about clutter each work cycle, and anti-ionospheric interference technology adapting to all kinds of situations. With the purpose of extracting the ionospheric clutter separately for clutter cancellation, image processing method is adopted to study and analyze the application of deep learning in edge extraction of ionospheric clutter existing in Range-Doppler (RD) spectrum. In this paper, holistically-nested edge detection (HED) based algorithm is adopted and Canny algorithm is used for comparison. It shows that HED algorithm is effective and efficient in edge extraction of ionospheric clutter in RD spectrum.
{"title":"HED-CNN based Ionospheric Clutter Extraction for HF Range-Doppler Spectrum","authors":"Xiangyuan Wang, Wozhan Li, Xiaochuan Wu, Ying Suo, Qiang Yang","doi":"10.1109/ICNISC57059.2022.00041","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00041","url":null,"abstract":"High Frequency Surface Wave Radar (HFSWR) suffers seriously with the ionospheric clutter formed from ionosphere echoes. The ionospheric clutter could be extensive and exists all day long, which restricts the detection performance of HFSWR. It is necessary to eliminate the interference of ionospheric clutter which overwhelms target echoes always. However, there is not a prior knowledge about clutter each work cycle, and anti-ionospheric interference technology adapting to all kinds of situations. With the purpose of extracting the ionospheric clutter separately for clutter cancellation, image processing method is adopted to study and analyze the application of deep learning in edge extraction of ionospheric clutter existing in Range-Doppler (RD) spectrum. In this paper, holistically-nested edge detection (HED) based algorithm is adopted and Canny algorithm is used for comparison. It shows that HED algorithm is effective and efficient in edge extraction of ionospheric clutter in RD spectrum.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128352959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00066
Qijia Gu, Zhen An, Lanmin Chen, Kunfu Wang
With the increasing application of the Unmanned Aerial Vehicle(UAV) technology, the path planning of UAV is becoming increasing important, However, with the increasing complexity of UAV applications, the application scenario is always complex, crowded with dense obstacles, open, and dynamic. In this paper, we dedicate to deep reinforcement learning algorithms for autonomous obstacle avoidance and navigation of UAV. The navigation problem is considered as a target-driven MDP problem, in which UAV takes its next action conditioned on both its current observation and the destination, Additionally, DRL algorithm with sparse rewards is hard to convergence, we introduce a step-wise dynamic relative goal method to extract the common feature between different navigation targets.
{"title":"Path Planning of UAV Using Step-wise Deep Q-learning Algorithm","authors":"Qijia Gu, Zhen An, Lanmin Chen, Kunfu Wang","doi":"10.1109/ICNISC57059.2022.00066","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00066","url":null,"abstract":"With the increasing application of the Unmanned Aerial Vehicle(UAV) technology, the path planning of UAV is becoming increasing important, However, with the increasing complexity of UAV applications, the application scenario is always complex, crowded with dense obstacles, open, and dynamic. In this paper, we dedicate to deep reinforcement learning algorithms for autonomous obstacle avoidance and navigation of UAV. The navigation problem is considered as a target-driven MDP problem, in which UAV takes its next action conditioned on both its current observation and the destination, Additionally, DRL algorithm with sparse rewards is hard to convergence, we introduce a step-wise dynamic relative goal method to extract the common feature between different navigation targets.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128371044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00140
Xuyang Wang, Jie Shi
Traditional text classification models mostly use the Word2vec and Glove to represent word vectors. When these traditional models classify Chinese short text data, they cannot well represent contextual semantic relationships and cannot completely extract text features. In this paper, the ERNIE (Enhanced Representation through Knowledge Integration) model is applied to the hybrid neural network model, which enhances the semantic representation of characters and generates character vectors by associating context semantic relations. Then the CNN (Convolutional Neural Network) and BiLSTM (Bidirectional Long Short Term Memory) are applied to the hybrid neural network to extract the characteristic information of the text data through CNN's different size convolution kernel and BiLSTM's bidirectional network structure. Moreover, in the training process, the weight decay mechanism of the AdamW algorithm is used to replace the traditional Adam algorithm to optimize the model performance. Finally, the obtained classification results are output by softmax classifier. By setting up comparative experiments on the THUCNews dataset and TouTiaoNews dataset, the results show that the Precision, Recall and F1-score of this model have been effectively improved over traditional neural network model and BERT-based model.
传统的文本分类模型大多使用Word2vec和Glove来表示词向量。这些传统模型在对中文短文本数据进行分类时，不能很好地表示上下文语义关系，不能完整地提取文本特征。本文将ERNIE (Enhanced Representation through Knowledge Integration)模型应用到混合神经网络模型中，通过关联上下文语义关系增强字符的语义表示，生成字符向量。然后将CNN(卷积神经网络)和BiLSTM(双向长短期记忆)应用到混合神经网络中，通过CNN不同大小的卷积核和BiLSTM的双向网络结构提取文本数据的特征信息。在训练过程中，利用AdamW算法的权值衰减机制取代传统的Adam算法，优化模型性能。最后，使用softmax分类器输出得到的分类结果。通过在THUCNews数据集和今日头条新闻数据集上进行对比实验，结果表明，该模型的Precision、Recall和F1-score都比传统的神经网络模型和基于bert的模型得到了有效的提高。
{"title":"Research on Chinese Short Text Classification Based on Pre-trained Hybrid Neural Network","authors":"Xuyang Wang, Jie Shi","doi":"10.1109/ICNISC57059.2022.00140","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00140","url":null,"abstract":"Traditional text classification models mostly use the Word2vec and Glove to represent word vectors. When these traditional models classify Chinese short text data, they cannot well represent contextual semantic relationships and cannot completely extract text features. In this paper, the ERNIE (Enhanced Representation through Knowledge Integration) model is applied to the hybrid neural network model, which enhances the semantic representation of characters and generates character vectors by associating context semantic relations. Then the CNN (Convolutional Neural Network) and BiLSTM (Bidirectional Long Short Term Memory) are applied to the hybrid neural network to extract the characteristic information of the text data through CNN's different size convolution kernel and BiLSTM's bidirectional network structure. Moreover, in the training process, the weight decay mechanism of the AdamW algorithm is used to replace the traditional Adam algorithm to optimize the model performance. Finally, the obtained classification results are output by softmax classifier. By setting up comparative experiments on the THUCNews dataset and TouTiaoNews dataset, the results show that the Precision, Recall and F1-score of this model have been effectively improved over traditional neural network model and BERT-based model.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114205644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-01DOI: 10.1109/ICNISC57059.2022.00134
Shuzheng Guo, Z. Liu, Yufeng Tan
Aiming at the research problem of weld defect type recognition based on ultrasonic signals, an automatic recognition method was proposed based on the combination of empirical mode decomposition (EMD) and BP neural network. Firstly, EMD was used to decompose the ultrasonic A-scan signals of different weld defects, and some intrinsic modal functions (IMF) of the defect signals were obtained. Then the correlation between the IMF and the original signal is carried out, and dimensionality reduction is carried out based on the eigenvalues of the parameters of the IMF. The final weld defect using BP neural network as a classifier, the intrinsic mode function of time domain and frequency domain features as input parameters to the BP neural network for training decisions, and aim to achieve the defect types automatic recognition. The experimental results show that the method can accurately classify weld internal defect information, comprehensive recognition accuracy rate reached 94%, It has good engineering application value.
{"title":"Research on Weld Defect Identification Technology Based on EMD and BP Neural Network","authors":"Shuzheng Guo, Z. Liu, Yufeng Tan","doi":"10.1109/ICNISC57059.2022.00134","DOIUrl":"https://doi.org/10.1109/ICNISC57059.2022.00134","url":null,"abstract":"Aiming at the research problem of weld defect type recognition based on ultrasonic signals, an automatic recognition method was proposed based on the combination of empirical mode decomposition (EMD) and BP neural network. Firstly, EMD was used to decompose the ultrasonic A-scan signals of different weld defects, and some intrinsic modal functions (IMF) of the defect signals were obtained. Then the correlation between the IMF and the original signal is carried out, and dimensionality reduction is carried out based on the eigenvalues of the parameters of the IMF. The final weld defect using BP neural network as a classifier, the intrinsic mode function of time domain and frequency domain features as input parameters to the BP neural network for training decisions, and aim to achieve the defect types automatic recognition. The experimental results show that the method can accurately classify weld internal defect information, comprehensive recognition accuracy rate reached 94%, It has good engineering application value.","PeriodicalId":286467,"journal":{"name":"2022 8th Annual International Conference on Network and Information Systems for Computers (ICNISC)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114711270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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