How to improve marketing efficiency and how to formulate scientific, effective and practical marketing strategies according to changes in the market environment are important issues facing current smart home companies. This paper adopts the analysis methods such as PEST macro model analysis method, Porter's five forces model, SWOT analysis model and STP analysis, taking Suzhou as the research object, conducts an in-depth analysis of the development environment of smart home, and clarifies the suitable smart home market. From the aspects of 6P marketing mix (product, price, channel, promotion, public relations and political rights), it proposes a Suzhou smart home marketing mix strategy based on mid-to-high-end smart home products. The research results of this paper will promote the development of the city's smart home market and have important reference value for other cities to carry out smart home marketing and can also be used as a reference for relevant government departments to formulate policies.
{"title":"Analysis of Home Furnishing Marketing Based on Internet of Things in the Intelligent Environment","authors":"Fang Wang","doi":"10.4018/ijaci.348964","DOIUrl":"https://doi.org/10.4018/ijaci.348964","url":null,"abstract":"How to improve marketing efficiency and how to formulate scientific, effective and practical marketing strategies according to changes in the market environment are important issues facing current smart home companies. This paper adopts the analysis methods such as PEST macro model analysis method, Porter's five forces model, SWOT analysis model and STP analysis, taking Suzhou as the research object, conducts an in-depth analysis of the development environment of smart home, and clarifies the suitable smart home market. From the aspects of 6P marketing mix (product, price, channel, promotion, public relations and political rights), it proposes a Suzhou smart home marketing mix strategy based on mid-to-high-end smart home products. The research results of this paper will promote the development of the city's smart home market and have important reference value for other cities to carry out smart home marketing and can also be used as a reference for relevant government departments to formulate policies.","PeriodicalId":51884,"journal":{"name":"International Journal of Ambient Computing and Intelligence","volume":"18 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141809938","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}
The technology of automatic fare collection system for urban rail transit is an important technology for achieving automatic fare collection for public transportation facilities such as urban subways. This article studies the relevant characteristics of the AFC system. Through introducing queuing models, simulation comparative experiments, and neural network debugging, it is found that the automatic fare collection system for urban rail transit not only effectively helps station staff to allocate tickets in a timely and reasonable manner, adjust station ticket supply, but also facilitates station passengers to query tickets, and passengers can freely choose whether to take the train according to their actual needs. The experiment shows that the AFC system can effectively help passengers avoid traffic congestion during peak hours, greatly improve management level, and reduce labor intensity.
{"title":"Management of New Automatic Ticket Vending Machine System in Urban Rail Transit","authors":"Yanshuo Li, Hao Zhu, Weigang Tian, Chengshun Xiao","doi":"10.4018/ijaci.344796","DOIUrl":"https://doi.org/10.4018/ijaci.344796","url":null,"abstract":"The technology of automatic fare collection system for urban rail transit is an important technology for achieving automatic fare collection for public transportation facilities such as urban subways. This article studies the relevant characteristics of the AFC system. Through introducing queuing models, simulation comparative experiments, and neural network debugging, it is found that the automatic fare collection system for urban rail transit not only effectively helps station staff to allocate tickets in a timely and reasonable manner, adjust station ticket supply, but also facilitates station passengers to query tickets, and passengers can freely choose whether to take the train according to their actual needs. The experiment shows that the AFC system can effectively help passengers avoid traffic congestion during peak hours, greatly improve management level, and reduce labor intensity.","PeriodicalId":51884,"journal":{"name":"International Journal of Ambient Computing and Intelligence","volume":"36 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141102342","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}
Shuqin Zhang, Peiyu Shi, Tianhui Du, Xinyu Su, Yunfei Han
Due to the widespread use of the industrial internet of things, the industrial control system has steadily transformed into an intelligent and informational one. To increase the industrial control system's security, based on industrial control system assets, this paper provides a method of threat modeling, attributing, and reasoning. First, this method characterizes the asset threat of an industrial control system by constructing an asset security ontology based on the asset structure. Second, this approach makes use of machine learning to identify assets and attribute the attacker's attack path. Subsequently, inference rules are devised to replicate the attacker's attack path, thereby reducing the response time of security personnel to threats and strengthening the semantic relationship between asset security within industrial control systems. Finally, the process is used in the simulation environment and real case scenario based on the power grid, where the assets and attacks are mapped. The actual attack path is deduced, and it demonstrates the approach's effectiveness.
{"title":"Threat Attribution and Reasoning for Industrial Control System Asset","authors":"Shuqin Zhang, Peiyu Shi, Tianhui Du, Xinyu Su, Yunfei Han","doi":"10.4018/ijaci.333853","DOIUrl":"https://doi.org/10.4018/ijaci.333853","url":null,"abstract":"Due to the widespread use of the industrial internet of things, the industrial control system has steadily transformed into an intelligent and informational one. To increase the industrial control system's security, based on industrial control system assets, this paper provides a method of threat modeling, attributing, and reasoning. First, this method characterizes the asset threat of an industrial control system by constructing an asset security ontology based on the asset structure. Second, this approach makes use of machine learning to identify assets and attribute the attacker's attack path. Subsequently, inference rules are devised to replicate the attacker's attack path, thereby reducing the response time of security personnel to threats and strengthening the semantic relationship between asset security within industrial control systems. Finally, the process is used in the simulation environment and real case scenario based on the power grid, where the assets and attacks are mapped. The actual attack path is deduced, and it demonstrates the approach's effectiveness.","PeriodicalId":51884,"journal":{"name":"International Journal of Ambient Computing and Intelligence","volume":"54 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139263977","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}
The popularity of cloud accounting is due to its low cost of entry, efficient data processing, and high business efficiency. However, security issues in cloud storage can affect user trust in the service. To address these security issues, a blockchain-based encryption technology model for cloud accounting data security is proposed. Firstly, the feasibility of integrating blockchain technology and cloud accounting is analyzed. Then, an elliptic curve cryptography-based cloud accounting data security solution is proposed. Blockchain and evidence chain technology are used to ensure data security and support data privacy protection for cloud service providers and third-party auditors. The proposed solution has a small computational overhead, as it does not require exponentiation or bilinear pairing. Experimental results show the proposed solution can enhance user control over cloud accounting data, ensure data transmission security, and improve trust between users and cloud accounting service providers. Moreover, it is more efficient.
{"title":"A Blockchain-Based Security Model for Cloud Accounting Data","authors":"Congcong Gou, Xiaoqing Deng","doi":"10.4018/ijaci.332860","DOIUrl":"https://doi.org/10.4018/ijaci.332860","url":null,"abstract":"The popularity of cloud accounting is due to its low cost of entry, efficient data processing, and high business efficiency. However, security issues in cloud storage can affect user trust in the service. To address these security issues, a blockchain-based encryption technology model for cloud accounting data security is proposed. Firstly, the feasibility of integrating blockchain technology and cloud accounting is analyzed. Then, an elliptic curve cryptography-based cloud accounting data security solution is proposed. Blockchain and evidence chain technology are used to ensure data security and support data privacy protection for cloud service providers and third-party auditors. The proposed solution has a small computational overhead, as it does not require exponentiation or bilinear pairing. Experimental results show the proposed solution can enhance user control over cloud accounting data, ensure data transmission security, and improve trust between users and cloud accounting service providers. Moreover, it is more efficient.","PeriodicalId":51884,"journal":{"name":"International Journal of Ambient Computing and Intelligence","volume":"64 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136235091","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}
Protecting Oroqen folk songs is not only the only way to reproduce Chinese traditional music culture, but also the only way to rebuild its national spirit and enhance national cultural confidence. In view of the modernity problems of Oroqen folk songs in the current process of inheritance and protection, this paper puts forward the management and optimization methods of music audio-visual archives resources under the background of big data. This paper analyzes and discusses the resource management path of folk music audio-visual archives in Oroqen in the era of big data and designs a set of perfect digital music audio-visual archives resource management platform, which can not only facilitate the collection, storage, management, and utilization of paper files and electronic files in archives, but also optimize the retrieval algorithm of archives. The resource allocation algorithm based on Nash equilibrium solution is used to optimize it. The simulation results show that the proposed method reduces the information resource allocation time and improves the demand satisfaction.
{"title":"Management and Optimization Methods of Music Audio-Visual Archives Resources Based on Big Data","authors":"Hongyu Liu, Chenxi Lu","doi":"10.4018/ijaci.332866","DOIUrl":"https://doi.org/10.4018/ijaci.332866","url":null,"abstract":"Protecting Oroqen folk songs is not only the only way to reproduce Chinese traditional music culture, but also the only way to rebuild its national spirit and enhance national cultural confidence. In view of the modernity problems of Oroqen folk songs in the current process of inheritance and protection, this paper puts forward the management and optimization methods of music audio-visual archives resources under the background of big data. This paper analyzes and discusses the resource management path of folk music audio-visual archives in Oroqen in the era of big data and designs a set of perfect digital music audio-visual archives resource management platform, which can not only facilitate the collection, storage, management, and utilization of paper files and electronic files in archives, but also optimize the retrieval algorithm of archives. The resource allocation algorithm based on Nash equilibrium solution is used to optimize it. The simulation results show that the proposed method reduces the information resource allocation time and improves the demand satisfaction.","PeriodicalId":51884,"journal":{"name":"International Journal of Ambient Computing and Intelligence","volume":"1 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136264184","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}
This article proposes a Weibo sentiment analysis method to improve traditional algorithms' analysis efficiency and accuracy. The proposed algorithm uses deep learning in the Spark big data environment. First, the input data are converted into dynamic word vector representations using the Chinese version of the XLNet model. Then, dual-channel feature extraction is performed on the data using TextCNN and BiLSTM. The proposed algorithm uses an attention mechanism to allocate computing resources efficiently and realizes feature fusion and data classification. Comparative experiments are conducted on two public datasets under identical experimental conditions. In the NLPCC2014 and NLPCC2015 datasets, the proposed model improves the precision and F1 metrics by at least 4.26% and 2.64%, respectively. In the weibo_senti_100k dataset, the proposed model improves the precision and F1 metrics by at least 4.66% and 2.69%, respectively. The results indicate that the proposed method has better sentiment analysis and prediction abilities than existing methods.
{"title":"Fusion of XLNet and BiLSTM-TextCNN for Weibo Sentiment Analysis in Spark Big Data Environment","authors":"Aichuan Li, Tian Li","doi":"10.4018/ijaci.331744","DOIUrl":"https://doi.org/10.4018/ijaci.331744","url":null,"abstract":"This article proposes a Weibo sentiment analysis method to improve traditional algorithms' analysis efficiency and accuracy. The proposed algorithm uses deep learning in the Spark big data environment. First, the input data are converted into dynamic word vector representations using the Chinese version of the XLNet model. Then, dual-channel feature extraction is performed on the data using TextCNN and BiLSTM. The proposed algorithm uses an attention mechanism to allocate computing resources efficiently and realizes feature fusion and data classification. Comparative experiments are conducted on two public datasets under identical experimental conditions. In the NLPCC2014 and NLPCC2015 datasets, the proposed model improves the precision and F1 metrics by at least 4.26% and 2.64%, respectively. In the weibo_senti_100k dataset, the proposed model improves the precision and F1 metrics by at least 4.66% and 2.69%, respectively. The results indicate that the proposed method has better sentiment analysis and prediction abilities than existing methods.","PeriodicalId":51884,"journal":{"name":"International Journal of Ambient Computing and Intelligence","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135046904","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}
Learning Tai Chi requires long-term practice and guidance, which is difficult for beginners. This article proposes a Tai Chi-assisted training and scoring method based on motion capture technology and a dynamic time warping (DTW) algorithm. Firstly, by using motion capture technology, the key point data of Tai Chi movements can be accurately captured. Then, using the DTW algorithm, the learner's action sequence is compared and matched with the standard Tai Chi action sequence in order to evaluate the learner's action accuracy and fluency. Learners can promptly correct incorrect actions and improve the accuracy and fluency of their actions. This method has significant advantages in accuracy and reliability. In summary, the Tai Chi-assisted training and scoring method based on motion capture technology and DTW algorithm provides an effective auxiliary tool for Tai Chi learners, which can help them better master the techniques and essence of Tai Chi. This study is of great significance for promoting the popularization of Tai Chi and improving the learning effectiveness of Tai Chi.
{"title":"Taijiquan Auxiliary Training and Scoring Based on Motion Capture Technology and DTW Algorithm","authors":"Xia Feng, Xin Lu, Xingwei Si","doi":"10.4018/ijaci.330539","DOIUrl":"https://doi.org/10.4018/ijaci.330539","url":null,"abstract":"Learning Tai Chi requires long-term practice and guidance, which is difficult for beginners. This article proposes a Tai Chi-assisted training and scoring method based on motion capture technology and a dynamic time warping (DTW) algorithm. Firstly, by using motion capture technology, the key point data of Tai Chi movements can be accurately captured. Then, using the DTW algorithm, the learner's action sequence is compared and matched with the standard Tai Chi action sequence in order to evaluate the learner's action accuracy and fluency. Learners can promptly correct incorrect actions and improve the accuracy and fluency of their actions. This method has significant advantages in accuracy and reliability. In summary, the Tai Chi-assisted training and scoring method based on motion capture technology and DTW algorithm provides an effective auxiliary tool for Tai Chi learners, which can help them better master the techniques and essence of Tai Chi. This study is of great significance for promoting the popularization of Tai Chi and improving the learning effectiveness of Tai Chi.","PeriodicalId":51884,"journal":{"name":"International Journal of Ambient Computing and Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136130942","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 deal with the problems of occurring personalized music recommendation methods, for instance, low explanation, low accuracy of recommendation, and difficulty extracting information effectively, a personalized music recommendation method combining TextCNN and attention is proposed. Firstly, TextCNN model and BERT are combined to capture local music continuous features. Secondly, self-attention is introduced to solve the remaining omitted non-continuous features that are not paid attention by TextCNN. Finally, multi-headed attention mechanism is used to get features of hotspot music and user's interest music, and cascading fusion method is used to achieve click prediction. Experimentally, the proposed model can effectively recommend personalized music, its MAE values on FMA and GTZAN datasets are 0.156 and 0.146, respectively, improving by at least 6.6% and 3.3% compared to other comparative models. And its RMSE result values on the FMA and GTZAN datasets are 0.185 and 0.164, respectively, improving by at least 12.4% and 5.2% compared to other comparative models.
{"title":"BTSAMA","authors":"S. Lv, Liliya Pan","doi":"10.4018/ijaci.327351","DOIUrl":"https://doi.org/10.4018/ijaci.327351","url":null,"abstract":"To deal with the problems of occurring personalized music recommendation methods, for instance, low explanation, low accuracy of recommendation, and difficulty extracting information effectively, a personalized music recommendation method combining TextCNN and attention is proposed. Firstly, TextCNN model and BERT are combined to capture local music continuous features. Secondly, self-attention is introduced to solve the remaining omitted non-continuous features that are not paid attention by TextCNN. Finally, multi-headed attention mechanism is used to get features of hotspot music and user's interest music, and cascading fusion method is used to achieve click prediction. Experimentally, the proposed model can effectively recommend personalized music, its MAE values on FMA and GTZAN datasets are 0.156 and 0.146, respectively, improving by at least 6.6% and 3.3% compared to other comparative models. And its RMSE result values on the FMA and GTZAN datasets are 0.185 and 0.164, respectively, improving by at least 12.4% and 5.2% compared to other comparative models.","PeriodicalId":51884,"journal":{"name":"International Journal of Ambient Computing and Intelligence","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87924730","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}
The safe and efficient authentication of users is the basis for the realization of the Internet of Things. A reliable and fast user authentication schema that combines mobile edge computing and blockchain technology is proposed. This schema adopts the polling hosting method to optimize the practical Byzantine Fault Tolerance (PBFT) algorithm, it reduces the impact of tokens in the algorithm, and ensures trusted authentication. The two-way authentication protocol between the cluster head and the base station, and the one-way authentication protocol between the base station and the sensor node are designed to effectively simplify the authentication process of sensor nodes, which further guarantees the security and speed of user authentication and effectively meets the security, reliability, and convenience requirements of the Internet of Things. Simulation experiments show that the schema can achieve efficient information verification, and the identity authentication time and protocol authentication times are only 23.58 ms and 25.06 ms, respectively, which has obvious performance advantages over the Paillier algorithm, the hybrid Paillier-blowfish algorithm, and the ElGamal algorithm.
{"title":"A User Authentication Schema Under the Integration of Mobile Edge Computing and Blockchain Technology","authors":"Feng Xue, Fangju Li","doi":"10.4018/ijaci.327027","DOIUrl":"https://doi.org/10.4018/ijaci.327027","url":null,"abstract":"The safe and efficient authentication of users is the basis for the realization of the Internet of Things. A reliable and fast user authentication schema that combines mobile edge computing and blockchain technology is proposed. This schema adopts the polling hosting method to optimize the practical Byzantine Fault Tolerance (PBFT) algorithm, it reduces the impact of tokens in the algorithm, and ensures trusted authentication. The two-way authentication protocol between the cluster head and the base station, and the one-way authentication protocol between the base station and the sensor node are designed to effectively simplify the authentication process of sensor nodes, which further guarantees the security and speed of user authentication and effectively meets the security, reliability, and convenience requirements of the Internet of Things. Simulation experiments show that the schema can achieve efficient information verification, and the identity authentication time and protocol authentication times are only 23.58 ms and 25.06 ms, respectively, which has obvious performance advantages over the Paillier algorithm, the hybrid Paillier-blowfish algorithm, and the ElGamal algorithm.","PeriodicalId":51884,"journal":{"name":"International Journal of Ambient Computing and Intelligence","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87981146","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}
Convolutional neural networks (CNNs) are deep learning methods that are utilized in image processing such as image classification and recognition. It has achieved excellent results in various sectors; however, it still lacks rotation invariant and spatial information. To establish whether two images are rotational versions of one other, one can rotate them exhaustively to see if they compare favorably at some angle. Due to the failure of current algorithms to rotate images and provide spatial information, the study proposes to transform color spaces and use the Gabor filter to address the issue. To gather spatial information, the HSV and CieLab color spaces are used, and Gabor is used to orient images at various orientation. The experiments show that HSV and CieLab color spaces and Gabor convolutional neural network (GCNN) improves image retrieval with an accuracy of 98.72% and 98.67% on the CIFAR-10 dataset.
{"title":"Rotational Invariance Using Gabor Convolution Neural Network and Color Space for Image Processing","authors":"Judy Gateri, R. Rimiru, Michael W. Kimwele","doi":"10.4018/ijaci.323798","DOIUrl":"https://doi.org/10.4018/ijaci.323798","url":null,"abstract":"Convolutional neural networks (CNNs) are deep learning methods that are utilized in image processing such as image classification and recognition. It has achieved excellent results in various sectors; however, it still lacks rotation invariant and spatial information. To establish whether two images are rotational versions of one other, one can rotate them exhaustively to see if they compare favorably at some angle. Due to the failure of current algorithms to rotate images and provide spatial information, the study proposes to transform color spaces and use the Gabor filter to address the issue. To gather spatial information, the HSV and CieLab color spaces are used, and Gabor is used to orient images at various orientation. The experiments show that HSV and CieLab color spaces and Gabor convolutional neural network (GCNN) improves image retrieval with an accuracy of 98.72% and 98.67% on the CIFAR-10 dataset.","PeriodicalId":51884,"journal":{"name":"International Journal of Ambient Computing and Intelligence","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73494388","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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