Pub Date : 2022-06-10DOI: 10.1109/ICWOC55996.2022.9809899
Chunlong Fan, Yingyu Hao
Due to the extensive development of deep neural networks, such as strategy based neural networks, they are easy to be deceived and fooled, resulting in model failure or wrong decision. Because DRL has made great achievements in various complex tasks, it is essential to design effective attacks to build a robust DRL algorithm. So far, most of them are to separate the model from the environment and select effective disturbances through several input and output attempts to achieve the purpose of attack. Therefore, this paper proposes a way to predict the future critical state time and attack by observing each state of the environment without constantly observing the input and output of the model. It is verified in Atari game, which can effectively reduce the acquisition of cumulative rewards on the premise of high efficiency and concealment. This method is suitable for most application scenarios, and ensures the characteristics of efficient and covert attack.
{"title":"Precise Key Frames Adversarial Attack against Deep Reinforcement Learning","authors":"Chunlong Fan, Yingyu Hao","doi":"10.1109/ICWOC55996.2022.9809899","DOIUrl":"https://doi.org/10.1109/ICWOC55996.2022.9809899","url":null,"abstract":"Due to the extensive development of deep neural networks, such as strategy based neural networks, they are easy to be deceived and fooled, resulting in model failure or wrong decision. Because DRL has made great achievements in various complex tasks, it is essential to design effective attacks to build a robust DRL algorithm. So far, most of them are to separate the model from the environment and select effective disturbances through several input and output attempts to achieve the purpose of attack. Therefore, this paper proposes a way to predict the future critical state time and attack by observing each state of the environment without constantly observing the input and output of the model. It is verified in Atari game, which can effectively reduce the acquisition of cumulative rewards on the premise of high efficiency and concealment. This method is suitable for most application scenarios, and ensures the characteristics of efficient and covert attack.","PeriodicalId":402416,"journal":{"name":"2022 10th International Conference on Intelligent Computing and Wireless Optical Communications (ICWOC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129984806","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}
To provide determined network services, including high bandwidth, low data loss, low latency, and low jitter services, to transmission and computing resource integration networks, a novel routing optimization method is proposed. Based on physical-layer collision awareness and transparent packet duplication, delay and deletion, high-reliability and low-latency all-optical communication can be achieved. In addition, this method has the potential to be adapted to rapidly time-varying topologies and link lengths in wireless optical networks. In this paper, the processing and distribution of data packets in this routing optimization method are described; a structure of the all-optical switching node for supporting this routing optimization method is presented; and the influence of switching node performance, such as the maximum cache time, the maximum multicast packet number and the perception latency, on end-to-end availability are analyzed by simulation.
{"title":"A Physical-Layer Collision Awared All-Optical Time Slice Routing Optimization Method for High Reliable Low-Latency Communication in Transmission and Computing Resource Integration Networks","authors":"Chen Zhao, Nan Hua, Guanqin Pan, Jipu Li, Yanhe Li, Xiaoping Zheng","doi":"10.1109/ICWOC55996.2022.9809869","DOIUrl":"https://doi.org/10.1109/ICWOC55996.2022.9809869","url":null,"abstract":"To provide determined network services, including high bandwidth, low data loss, low latency, and low jitter services, to transmission and computing resource integration networks, a novel routing optimization method is proposed. Based on physical-layer collision awareness and transparent packet duplication, delay and deletion, high-reliability and low-latency all-optical communication can be achieved. In addition, this method has the potential to be adapted to rapidly time-varying topologies and link lengths in wireless optical networks. In this paper, the processing and distribution of data packets in this routing optimization method are described; a structure of the all-optical switching node for supporting this routing optimization method is presented; and the influence of switching node performance, such as the maximum cache time, the maximum multicast packet number and the perception latency, on end-to-end availability are analyzed by simulation.","PeriodicalId":402416,"journal":{"name":"2022 10th International Conference on Intelligent Computing and Wireless Optical Communications (ICWOC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114745365","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 : 2022-06-10DOI: 10.1109/icwoc55996.2022.9809900
Xinhai Yan, Dongyao Wang, Ziping Wei, Bin Li
Channel State Information (CSI) estimation is a very important part in the wireless communication system within the complex shipbuilding scenario. The estimation accuracy determines the rationality of the design of the precoding module in the whole communication system, and influence the spectrum efficiency and channel capacity. This paper firstly summarizes the traditional channel estimation technologies and analyzes their strengths and weaknesses. Then, with the low-rank property of channel matrix under the complicated electromagnetic environment within the shipbuilding scenario, this work proposes a fast estimation scheme for high-precision channel state information, which balances two very important but contradictory optimization objectives for channel estimation, i.e. computation complexity and accuracy. While greatly reducing the time complexity of channel estimation, the proposed method also greatly improves the estimation accuracy, which is verified by the simulation results.
{"title":"Wireless Channel Estimation in Shipbuilding Scenario Based on Reconfigurable Intelligent Surface","authors":"Xinhai Yan, Dongyao Wang, Ziping Wei, Bin Li","doi":"10.1109/icwoc55996.2022.9809900","DOIUrl":"https://doi.org/10.1109/icwoc55996.2022.9809900","url":null,"abstract":"Channel State Information (CSI) estimation is a very important part in the wireless communication system within the complex shipbuilding scenario. The estimation accuracy determines the rationality of the design of the precoding module in the whole communication system, and influence the spectrum efficiency and channel capacity. This paper firstly summarizes the traditional channel estimation technologies and analyzes their strengths and weaknesses. Then, with the low-rank property of channel matrix under the complicated electromagnetic environment within the shipbuilding scenario, this work proposes a fast estimation scheme for high-precision channel state information, which balances two very important but contradictory optimization objectives for channel estimation, i.e. computation complexity and accuracy. While greatly reducing the time complexity of channel estimation, the proposed method also greatly improves the estimation accuracy, which is verified by the simulation results.","PeriodicalId":402416,"journal":{"name":"2022 10th International Conference on Intelligent Computing and Wireless Optical Communications (ICWOC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116105825","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 : 2022-06-10DOI: 10.1109/ICWOC55996.2022.9809886
Chong Tan, Jinshan Chen, Sufang Chen, Chao Li, Hong Liu, Min Zheng
In this paper, a multi-conditional spectrum sensing combination algorithm based on random forest is proposed to address the current shortage of spectrum resources in the sensor network. The algorithm combines sensor's velocity, signal energy, the traces, and the average eigenvalue of the covariance matrix as random forest characteristic parameters, which are achieved through the strong multi-classification ability of random forest. To improve the successful rate of spectrum sensing and the utilization rate of the spectrum, we focus on analyzing the selection of parameter in theory as well as the low signal-to-noise ratio caused by channel fading and shadow effect. Meanwhile, the Doppler effective caused by car moving is also our consideration. Under low signal-to-noise ratio, the simulation results show that the proposed algorithm has better detection performance than existing spectrum sensing algorithms.
{"title":"Combination Spectrum Sensing Algorithm for Wireless Sensor Network Based on Random Forest","authors":"Chong Tan, Jinshan Chen, Sufang Chen, Chao Li, Hong Liu, Min Zheng","doi":"10.1109/ICWOC55996.2022.9809886","DOIUrl":"https://doi.org/10.1109/ICWOC55996.2022.9809886","url":null,"abstract":"In this paper, a multi-conditional spectrum sensing combination algorithm based on random forest is proposed to address the current shortage of spectrum resources in the sensor network. The algorithm combines sensor's velocity, signal energy, the traces, and the average eigenvalue of the covariance matrix as random forest characteristic parameters, which are achieved through the strong multi-classification ability of random forest. To improve the successful rate of spectrum sensing and the utilization rate of the spectrum, we focus on analyzing the selection of parameter in theory as well as the low signal-to-noise ratio caused by channel fading and shadow effect. Meanwhile, the Doppler effective caused by car moving is also our consideration. Under low signal-to-noise ratio, the simulation results show that the proposed algorithm has better detection performance than existing spectrum sensing algorithms.","PeriodicalId":402416,"journal":{"name":"2022 10th International Conference on Intelligent Computing and Wireless Optical Communications (ICWOC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128774080","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 : 2022-06-10DOI: 10.1109/ICWOC55996.2022.9809871
Jinfeng Yang, Zhangjian Qin, Qin Zhang, Tanzheng Yang
With the variety and complexity of communication signal modulation, it is more important and urgent to solve the problem of modulation identification. The modulation identification of PSK signal is studied based on the features of M-th power spectrum. The M-th power spectrum of BPSK signal, QPSK signal, OQPSK signal, DQPSK signal and π/4-DQPSK signal are simulated by Matlab. The features of M -th power spectrum of these five signals are summarized through the simulation results. Based on the results, a set of identification rules and identification process are designed, which can be used for intra-class identification of PSK signals.
{"title":"Research on Modulation Mode Identification of PSK Signal Based on M-th Power Spectrum Features","authors":"Jinfeng Yang, Zhangjian Qin, Qin Zhang, Tanzheng Yang","doi":"10.1109/ICWOC55996.2022.9809871","DOIUrl":"https://doi.org/10.1109/ICWOC55996.2022.9809871","url":null,"abstract":"With the variety and complexity of communication signal modulation, it is more important and urgent to solve the problem of modulation identification. The modulation identification of PSK signal is studied based on the features of M-th power spectrum. The M-th power spectrum of BPSK signal, QPSK signal, OQPSK signal, DQPSK signal and π/4-DQPSK signal are simulated by Matlab. The features of M -th power spectrum of these five signals are summarized through the simulation results. Based on the results, a set of identification rules and identification process are designed, which can be used for intra-class identification of PSK signals.","PeriodicalId":402416,"journal":{"name":"2022 10th International Conference on Intelligent Computing and Wireless Optical Communications (ICWOC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125584967","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 : 2022-06-10DOI: 10.1109/ICWOC55996.2022.9809884
Jing Yu, Wenhai Liu, Mingxing Zhou, Yunwen Chen, Daqi Ji, Na Sai
With the rapid development of graph neural network technology and the wide application of personalized recommender systems in the industry, how to better apply graph representation learning to recommender systems to continuously improve the recommendation effect and improve the user experience has become a hot field of the industry research. Based on hot issues such as sparse feature data, cold start, and multi-feature combination in massive data, this paper proposes a personalized recommendation ranking method that combines graph convolutional network and factorization machine. The method represents the network relationship between users and items based on the graph structure and generates the graph embeddings on the hyperparameter space through graph representation learning, uses the factorization machine to combine the learning of four categories of features of user attributes, item attributes, interaction, and context, and generates the vector representation separately, and finally predicts personalized recommendation score based on the ranking model. The comparison experiments of multiple groups of ranking methods show that the ranking learning method proposed in this paper is better than the baseline in six indicators of AUC, Logloss, UV_CTR, CVR, ATV and the exposure ratio of new items on the online e-commerce data set, which proves the effectiveness of the proposed method.
{"title":"Recommendation Ranking Method Combining Graph Convolutional Network and Factorization Machine","authors":"Jing Yu, Wenhai Liu, Mingxing Zhou, Yunwen Chen, Daqi Ji, Na Sai","doi":"10.1109/ICWOC55996.2022.9809884","DOIUrl":"https://doi.org/10.1109/ICWOC55996.2022.9809884","url":null,"abstract":"With the rapid development of graph neural network technology and the wide application of personalized recommender systems in the industry, how to better apply graph representation learning to recommender systems to continuously improve the recommendation effect and improve the user experience has become a hot field of the industry research. Based on hot issues such as sparse feature data, cold start, and multi-feature combination in massive data, this paper proposes a personalized recommendation ranking method that combines graph convolutional network and factorization machine. The method represents the network relationship between users and items based on the graph structure and generates the graph embeddings on the hyperparameter space through graph representation learning, uses the factorization machine to combine the learning of four categories of features of user attributes, item attributes, interaction, and context, and generates the vector representation separately, and finally predicts personalized recommendation score based on the ranking model. The comparison experiments of multiple groups of ranking methods show that the ranking learning method proposed in this paper is better than the baseline in six indicators of AUC, Logloss, UV_CTR, CVR, ATV and the exposure ratio of new items on the online e-commerce data set, which proves the effectiveness of the proposed method.","PeriodicalId":402416,"journal":{"name":"2022 10th International Conference on Intelligent Computing and Wireless Optical Communications (ICWOC)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127067563","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 : 2022-06-10DOI: 10.1109/ICWOC55996.2022.9809903
Zian Yan, Jianhong Zhang
Vehicular ad hoc networks (VANETs) can provide information and technical support for vehicles connected to the Internet, improving driving efficiency. However, VANETs requires drivers to disclose their specific driving paths to the server, and this measure increases the risk of leaking privacy. Honest but curious service providers may want to know customers' other private messages by collecting information about vehicle paths. Therefore, we propose an architecture based on the oblivious transport protocol to solve the above problems. In this architecture, the driver can obtain the required RSU messages without revealing the specific route information to the server. At the same time, our scheme uses the Chinese residual theorem to revoke malicious users, protecting the legitimate interests of service providers and RSU s. Finally, AES achieves fast authentication between the vehicle and the RSU, ensuring that the user can obtain real-time information while driving. Experiments show that our system can reduce computational costs compare to other methods.
{"title":"Path Privacy-Preserving Scheme Based on Oblivious Transfer Protocol","authors":"Zian Yan, Jianhong Zhang","doi":"10.1109/ICWOC55996.2022.9809903","DOIUrl":"https://doi.org/10.1109/ICWOC55996.2022.9809903","url":null,"abstract":"Vehicular ad hoc networks (VANETs) can provide information and technical support for vehicles connected to the Internet, improving driving efficiency. However, VANETs requires drivers to disclose their specific driving paths to the server, and this measure increases the risk of leaking privacy. Honest but curious service providers may want to know customers' other private messages by collecting information about vehicle paths. Therefore, we propose an architecture based on the oblivious transport protocol to solve the above problems. In this architecture, the driver can obtain the required RSU messages without revealing the specific route information to the server. At the same time, our scheme uses the Chinese residual theorem to revoke malicious users, protecting the legitimate interests of service providers and RSU s. Finally, AES achieves fast authentication between the vehicle and the RSU, ensuring that the user can obtain real-time information while driving. Experiments show that our system can reduce computational costs compare to other methods.","PeriodicalId":402416,"journal":{"name":"2022 10th International Conference on Intelligent Computing and Wireless Optical Communications (ICWOC)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124440031","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 : 2022-06-10DOI: 10.1109/icwoc55996.2022.9809879
Ayinuer Nuertai, Yasen Aizezi, Muyesaier Maerdan
Information collection is an important stage of penetration testing on the target. Only by mastering enough information of the target host or website can we attack the target host or website more effectively. Taking Baidu as the target, this paper analyzes and studies the methods used in the information collection of penetration test, and describes in detail what information needs to be collected and what tools need to be used for information collection. Information collection is of great significance in penetration test.
{"title":"Analysis and Research of Information Collection Method Based on Penetration Test","authors":"Ayinuer Nuertai, Yasen Aizezi, Muyesaier Maerdan","doi":"10.1109/icwoc55996.2022.9809879","DOIUrl":"https://doi.org/10.1109/icwoc55996.2022.9809879","url":null,"abstract":"Information collection is an important stage of penetration testing on the target. Only by mastering enough information of the target host or website can we attack the target host or website more effectively. Taking Baidu as the target, this paper analyzes and studies the methods used in the information collection of penetration test, and describes in detail what information needs to be collected and what tools need to be used for information collection. Information collection is of great significance in penetration test.","PeriodicalId":402416,"journal":{"name":"2022 10th International Conference on Intelligent Computing and Wireless Optical Communications (ICWOC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114933440","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 : 2022-06-10DOI: 10.1109/ICWOC55996.2022.9809904
Estanislao Epota Oma, J. Zhang, Ziyi Lv
Aiming at the problems of low recognition accuracy and algorithm efficiency of existing recognition methods for traffic signs, a Principal Component Analysis-Support Vector Machine (PCA-SVM) road traffic sign recognition method based on grid search was proposed. In this method, the principal component analysis (PCA) method is used to reduce the dimensionality of the traffic signs, and the principal component features of the traffic signs are extracted. The SVM classifier with optimized parameters realizes the recognition of traffic signs. Through experimental simulation and analysis and comparison with other existing traffic sign recognition algorithms, the experimental results show that the method in this paper can ensure high recognition accuracy, and the algorithm efficiency is significantly improved. The system is implemented on a Spartan-6-FPGA. For image acquisition, an off-the-shelf car camera is used. The developed system is able to reliably detect traffic signs on short distances on static images as well as on image streams.
{"title":"FPGA Based Traffic Sign Detection Using Support Vector Machine and Hybrid Filters","authors":"Estanislao Epota Oma, J. Zhang, Ziyi Lv","doi":"10.1109/ICWOC55996.2022.9809904","DOIUrl":"https://doi.org/10.1109/ICWOC55996.2022.9809904","url":null,"abstract":"Aiming at the problems of low recognition accuracy and algorithm efficiency of existing recognition methods for traffic signs, a Principal Component Analysis-Support Vector Machine (PCA-SVM) road traffic sign recognition method based on grid search was proposed. In this method, the principal component analysis (PCA) method is used to reduce the dimensionality of the traffic signs, and the principal component features of the traffic signs are extracted. The SVM classifier with optimized parameters realizes the recognition of traffic signs. Through experimental simulation and analysis and comparison with other existing traffic sign recognition algorithms, the experimental results show that the method in this paper can ensure high recognition accuracy, and the algorithm efficiency is significantly improved. The system is implemented on a Spartan-6-FPGA. For image acquisition, an off-the-shelf car camera is used. The developed system is able to reliably detect traffic signs on short distances on static images as well as on image streams.","PeriodicalId":402416,"journal":{"name":"2022 10th International Conference on Intelligent Computing and Wireless Optical Communications (ICWOC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114270103","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 : 2022-06-10DOI: 10.1109/ICWOC55996.2022.9809901
Lin Han, R. Fu, Xian Zhu, Yanyu Chen, Huiliang Ge
A new method to calculate the complex Fisher information matrix (FIM) and the Cramér-Rao bound (CRB) is proposed for line spectrum estimation (LSE) with multiple measurement vectors (MMVs), The detailed theoretic calculation process is presented in the text. Finally, numerical results are conducted not only to verify accuracy of the theoretical result by comparing against another method to calculate complex CRB, but also to demonstrate the effectiveness of CRB as the performance metric.
{"title":"A New Method to Calculate Complex Cramér-Rao Bound for Line Spectrum Estimation with Multiple Measurement Vectors","authors":"Lin Han, R. Fu, Xian Zhu, Yanyu Chen, Huiliang Ge","doi":"10.1109/ICWOC55996.2022.9809901","DOIUrl":"https://doi.org/10.1109/ICWOC55996.2022.9809901","url":null,"abstract":"A new method to calculate the complex Fisher information matrix (FIM) and the Cramér-Rao bound (CRB) is proposed for line spectrum estimation (LSE) with multiple measurement vectors (MMVs), The detailed theoretic calculation process is presented in the text. Finally, numerical results are conducted not only to verify accuracy of the theoretical result by comparing against another method to calculate complex CRB, but also to demonstrate the effectiveness of CRB as the performance metric.","PeriodicalId":402416,"journal":{"name":"2022 10th International Conference on Intelligent Computing and Wireless Optical Communications (ICWOC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132424442","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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