Advancement in information technology has given a tremendous change in the education system. The traditional classroom education system is slowly getting transferred to the modernized system. In this conversion, the students choose to select the courses to learn in their higher education. The selection will aid the student in learning advanced technologies through theoretical and practical methods. In this research work, a data-driven educational decision-making system with the support of a course curriculum is analyzed with student’s response after the course. The educational decision-making is implemented with the help of the mobile learning technology designed and maintained by the colleges and universities. For performing the analysis, the student response dataset is given as input to the fuzzy logic system to perform the analysis. The research shows that mobile learning technology with the fuzzy logic system has provided better decision-making analysis to curriculum optimization for the student and teachers.
{"title":"Application of the Data-Driven Educational Decision-Making System to Curriculum Optimization of Higher Education","authors":"Yufan Du","doi":"10.1155/2022/5823515","DOIUrl":"https://doi.org/10.1155/2022/5823515","url":null,"abstract":"Advancement in information technology has given a tremendous change in the education system. The traditional classroom education system is slowly getting transferred to the modernized system. In this conversion, the students choose to select the courses to learn in their higher education. The selection will aid the student in learning advanced technologies through theoretical and practical methods. In this research work, a data-driven educational decision-making system with the support of a course curriculum is analyzed with student’s response after the course. The educational decision-making is implemented with the help of the mobile learning technology designed and maintained by the colleges and universities. For performing the analysis, the student response dataset is given as input to the fuzzy logic system to perform the analysis. The research shows that mobile learning technology with the fuzzy logic system has provided better decision-making analysis to curriculum optimization for the student and teachers.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"11 1","pages":"5823515:1-5823515:8"},"PeriodicalIF":0.0,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86913202","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}
With the rapid development of Internet technology, network attacks have become more frequent and complex, and intrusion detection has also played an increasingly important role in network security. Intrusion detection is real-time and proactive, and it is an indispensable technology under the diversified trend of network security issues. In terms of network security, neural networks have the characteristics of self-learning, self-adaptation, and parallel computing, which are very important in intrusion detection. This paper combines back propagation neural network (BPNN) and elite clone artificial bee colony (ECABC) to propose a new ECABC-BPNN, which updates and optimizes the settings of traditional BPNN weights and thresholds. Then, apply ECABC-BPNN to network intrusion detection. Use the attack data samples of KDD CUP 99 and water pipe for attack classification experiments using GA-BPNN, PSO-BPNN, and ECABC-BPNN. The results show that the ECABC-BPNN proposed in this paper has an accuracy rate of 98.08% on KDD 99 and 99.76% on water pipe data. ECABC-BPNN effectively improves the accuracy of network intrusion classification and reduces classification errors. In addition, the time complexity of using ECABC-BPNN to classify network attacks is relatively low. Therefore, ECABC-BPNN has superior performance in network intrusion detection and classification.
随着互联网技术的飞速发展，网络攻击变得越来越频繁和复杂，入侵检测在网络安全中也发挥着越来越重要的作用。入侵检测具有实时性和主动性，是网络安全问题多样化趋势下不可缺少的技术。在网络安全方面，神经网络具有自学习、自适应、并行计算等特点，在入侵检测中发挥着重要作用。本文将反向传播神经网络(BPNN)与精英克隆人工蜂群(ECABC)相结合，提出了一种新的ECABC-BPNN，对传统BPNN的权值和阈值设置进行了更新和优化。然后，将ECABC-BPNN应用于网络入侵检测。利用KDD CUP 99和水管的攻击数据样本，分别使用GA-BPNN、PSO-BPNN和ECABC-BPNN进行攻击分类实验。结果表明，本文提出的ECABC-BPNN在KDD 99上的准确率为98.08%，在水管数据上的准确率为99.76%。ECABC-BPNN有效地提高了网络入侵分类的准确率，减少了分类错误。此外，使用ECABC-BPNN对网络攻击进行分类的时间复杂度相对较低。因此，ECABC-BPNN在网络入侵检测和分类方面具有优越的性能。
{"title":"Intrusion Detection for Network Based on Elite Clone Artificial Bee Colony and Back Propagation Neural Network","authors":"Guohong Qi, Jie Zhou, Wenxian Jia, Menghan Liu, Shengnan Zhang, Mengying Xu","doi":"10.1155/2021/9956371","DOIUrl":"https://doi.org/10.1155/2021/9956371","url":null,"abstract":"With the rapid development of Internet technology, network attacks have become more frequent and complex, and intrusion detection has also played an increasingly important role in network security. Intrusion detection is real-time and proactive, and it is an indispensable technology under the diversified trend of network security issues. In terms of network security, neural networks have the characteristics of self-learning, self-adaptation, and parallel computing, which are very important in intrusion detection. This paper combines back propagation neural network (BPNN) and elite clone artificial bee colony (ECABC) to propose a new ECABC-BPNN, which updates and optimizes the settings of traditional BPNN weights and thresholds. Then, apply ECABC-BPNN to network intrusion detection. Use the attack data samples of KDD CUP 99 and water pipe for attack classification experiments using GA-BPNN, PSO-BPNN, and ECABC-BPNN. The results show that the ECABC-BPNN proposed in this paper has an accuracy rate of 98.08% on KDD 99 and 99.76% on water pipe data. ECABC-BPNN effectively improves the accuracy of network intrusion classification and reduces classification errors. In addition, the time complexity of using ECABC-BPNN to classify network attacks is relatively low. Therefore, ECABC-BPNN has superior performance in network intrusion detection and classification.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"157 1","pages":"9956371:1-9956371:11"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74909771","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}
Network security situation assessment (NSSA) is an important and effective active defense technology in the field of network security situation awareness. By analyzing the historical network security situation awareness data, NSSA can evaluate the network security threat and analyze the network attack stage, thus fully grasping the overall network security situation. With the rapid development of 5G, cloud computing, and Internet of things, the network environment is increasingly complex, resulting in diversity and randomness of network threats, which directly determine the accuracy and the universality of NSSA methods. Meanwhile, the indicator data is characterized by large scale and heterogeneity, which seriously affect the efficiency of the NSSA methods. In this paper, we design a new NSSA method based on the autoencoder (AE) and parsimonious memory unit (PMU). In our novel method, we first utilize an AE-based data dimensionality reduction method to process the original indicator data, thus effectively removing the redundant part of the indicator data. Subsequently, we adopt a PMU deep neural network to achieve accurate and efficient NSSA. The experimental results demonstrate that the accuracy and efficiency of our novel method are both greatly improved.
{"title":"An Efficient Network Security Situation Assessment Method Based on AE and PMU","authors":"Xiaoling Tao, Zi-yi Liu, Changsong Yang","doi":"10.1155/2021/1173065","DOIUrl":"https://doi.org/10.1155/2021/1173065","url":null,"abstract":"Network security situation assessment (NSSA) is an important and effective active defense technology in the field of network security situation awareness. By analyzing the historical network security situation awareness data, NSSA can evaluate the network security threat and analyze the network attack stage, thus fully grasping the overall network security situation. With the rapid development of 5G, cloud computing, and Internet of things, the network environment is increasingly complex, resulting in diversity and randomness of network threats, which directly determine the accuracy and the universality of NSSA methods. Meanwhile, the indicator data is characterized by large scale and heterogeneity, which seriously affect the efficiency of the NSSA methods. In this paper, we design a new NSSA method based on the autoencoder (AE) and parsimonious memory unit (PMU). In our novel method, we first utilize an AE-based data dimensionality reduction method to process the original indicator data, thus effectively removing the redundant part of the indicator data. Subsequently, we adopt a PMU deep neural network to achieve accurate and efficient NSSA. The experimental results demonstrate that the accuracy and efficiency of our novel method are both greatly improved.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"8 1","pages":"1173065:1-1173065:9"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73498022","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}
Reading and writing are the foundations of English learning as well as an important method of instruction. With the advancement of network technology and the onset of the information age, an increasing number of students have lost interest in traditional English reading and writing instruction in the classroom. Flipped classrooms have emerged as a result of this situation and have become the focus of research in one fell swoop. As a result, flipped classroom research at home and abroad has primarily focused on the theory and practical application of flipped classrooms, and flipped classroom application practice is primarily based on the overall classroom, with few separate discussions on the effects of flipped classroom students’ self-learning. As a result, we developed a recurrent neural network-based intelligent assisted learning algorithm for English flipped classrooms. There are two main characteristics of the model. First, it is a gated recurrent unit based on a variant structure of the recurrent neural network. The double-gating mechanism fully considers the context and selects memory through weight assignment, and on this basis, it integrates the novel LeakyReLU function to improve the model’s training convergence efficiency. Second, by overcoming time-consuming problems in the medium, the adoption of the connection sequence classification algorithm eliminates the need for prior alignment of speech and text data, resulting in a direct boost in model training speed. The experimental results show that in the English flipped classroom’s intelligent learning mode, students explore and discover knowledge independently, their enthusiasm and interest in learning are greatly increased, and the flipped classroom’s teaching effect is greatly improved.
{"title":"Intelligent Learning Algorithm for English Flipped Classroom Based on Recurrent Neural Network","authors":"Qifang Shan","doi":"10.1155/2021/8020461","DOIUrl":"https://doi.org/10.1155/2021/8020461","url":null,"abstract":"Reading and writing are the foundations of English learning as well as an important method of instruction. With the advancement of network technology and the onset of the information age, an increasing number of students have lost interest in traditional English reading and writing instruction in the classroom. Flipped classrooms have emerged as a result of this situation and have become the focus of research in one fell swoop. As a result, flipped classroom research at home and abroad has primarily focused on the theory and practical application of flipped classrooms, and flipped classroom application practice is primarily based on the overall classroom, with few separate discussions on the effects of flipped classroom students’ self-learning. As a result, we developed a recurrent neural network-based intelligent assisted learning algorithm for English flipped classrooms. There are two main characteristics of the model. First, it is a gated recurrent unit based on a variant structure of the recurrent neural network. The double-gating mechanism fully considers the context and selects memory through weight assignment, and on this basis, it integrates the novel LeakyReLU function to improve the model’s training convergence efficiency. Second, by overcoming time-consuming problems in the medium, the adoption of the connection sequence classification algorithm eliminates the need for prior alignment of speech and text data, resulting in a direct boost in model training speed. The experimental results show that in the English flipped classroom’s intelligent learning mode, students explore and discover knowledge independently, their enthusiasm and interest in learning are greatly increased, and the flipped classroom’s teaching effect is greatly improved.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"58 1","pages":"8020461:1-8020461:8"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86012024","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}
Zhu Zhao, Chingfang Hsu, L. Harn, Qing Yang, Lulu Ke
Internet of Medical Things (IoMT) is a kind of Internet of Things (IoT) that includes patients and medical sensors. Patients can share real-time medical data collected in IoMT with medical professionals. This enables medical professionals to provide patients with efficient medical services. Due to the high efficiency of cloud computing, patients prefer to share gathering medical information using cloud servers. However, sharing medical data on the cloud server will cause security issues, because these data involve the privacy of patients. Although recently many researchers have designed data sharing schemes in medical domain for security purpose, most of them cannot guarantee the anonymity of patients and provide access control for shared health data, and further, they are not lightweight enough for IoMT. Due to these security and efficiency issues, a novel lightweight privacy-preserving data sharing scheme is constructed in this paper for IoMT. This scheme can achieve the anonymity of patients and access control of shared medical data. At the same time, it satisfies all described security features. In addition, this scheme can achieve lightweight computations by using elliptic curve cryptography (ECC), XOR operations, and hash function. Furthermore, performance evaluation demonstrates that the proposed scheme takes less computation cost through comparison with similar solutions. Therefore, it is fairly an attractive solution for efficient and secure data sharing in IoMT.
{"title":"Lightweight Privacy-Preserving Data Sharing Scheme for Internet of Medical Things","authors":"Zhu Zhao, Chingfang Hsu, L. Harn, Qing Yang, Lulu Ke","doi":"10.1155/2021/8402138","DOIUrl":"https://doi.org/10.1155/2021/8402138","url":null,"abstract":"Internet of Medical Things (IoMT) is a kind of Internet of Things (IoT) that includes patients and medical sensors. Patients can share real-time medical data collected in IoMT with medical professionals. This enables medical professionals to provide patients with efficient medical services. Due to the high efficiency of cloud computing, patients prefer to share gathering medical information using cloud servers. However, sharing medical data on the cloud server will cause security issues, because these data involve the privacy of patients. Although recently many researchers have designed data sharing schemes in medical domain for security purpose, most of them cannot guarantee the anonymity of patients and provide access control for shared health data, and further, they are not lightweight enough for IoMT. Due to these security and efficiency issues, a novel lightweight privacy-preserving data sharing scheme is constructed in this paper for IoMT. This scheme can achieve the anonymity of patients and access control of shared medical data. At the same time, it satisfies all described security features. In addition, this scheme can achieve lightweight computations by using elliptic curve cryptography (ECC), XOR operations, and hash function. Furthermore, performance evaluation demonstrates that the proposed scheme takes less computation cost through comparison with similar solutions. Therefore, it is fairly an attractive solution for efficient and secure data sharing in IoMT.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"14 1","pages":"8402138:1-8402138:13"},"PeriodicalIF":0.0,"publicationDate":"2021-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74021403","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 paper provides an in-depth understanding and analysis of the reform of English teaching in colleges and universities by analyzing the role of big data technology for the reform through in-depth research and analysis. Based on the background of the era of education informatization, this study explores the transformative value of the integration of information technology and teaching activities and elaborates the relevant significance at the theoretical and practical levels. Based on this, the research method of this study is established. The realm of integration of information technology and teaching activities and its transformative value is taken as the focus of the study. The integration of information technology and teaching activities means that it is not only a simple superposition between information technology and teaching but also a process to explore the role and influence of information technology into teaching activities by deeply exploring the inner connection between the two, to complete the integration of information technology and teaching activities, and finally to realize the comprehensive development of student’s personality.
{"title":"Research on the Role of Big Data Technology in the Reform of English Teaching in Universities","authors":"Xiaoge Jia","doi":"10.1155/2021/9510216","DOIUrl":"https://doi.org/10.1155/2021/9510216","url":null,"abstract":"This paper provides an in-depth understanding and analysis of the reform of English teaching in colleges and universities by analyzing the role of big data technology for the reform through in-depth research and analysis. Based on the background of the era of education informatization, this study explores the transformative value of the integration of information technology and teaching activities and elaborates the relevant significance at the theoretical and practical levels. Based on this, the research method of this study is established. The realm of integration of information technology and teaching activities and its transformative value is taken as the focus of the study. The integration of information technology and teaching activities means that it is not only a simple superposition between information technology and teaching but also a process to explore the role and influence of information technology into teaching activities by deeply exploring the inner connection between the two, to complete the integration of information technology and teaching activities, and finally to realize the comprehensive development of student’s personality.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"78 1","pages":"9510216:1-9510216:13"},"PeriodicalIF":0.0,"publicationDate":"2021-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89918164","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}
As mobile networks (MNs) are advancing towards meeting mobile user requirements, the rural-urban divide still remains a major challenge. While areas within the urban space (metropolitan mobile space) are being developed, i.e., small Base Stations (BSs) empowered with computing capabilities are deployed to improve the delivery of user requirements, rural areas are left behind. Due to challenges of low population density, low income, difficult terrain, nonexistent infrastructure, and lack of power grid, remote areas have low digital penetration. This situation makes remote areas less attractive towards investments and to operate connectivity networks, thus failing to achieve universal access to the Internet. In addressing this issue, this paper proposes a new BS deployment and resource management method for remote and rural areas. Here, two MN operators share their resources towards the procurement and deployment of green energy-powered BSs equipped with computing capabilities. Then, the network infrastructure is shared between the mobile operators, with the main goal of enabling energy-efficient infrastructure sharing, i.e., BS and its colocated computing platform. Using this resource management strategy in rural communication sites guarantees a quality of service (QoS) comparable to that of urban communication sites. The performance evaluation conducted through simulations validates our analysis as the prediction variations observed show greater accuracy between the harvested energy and the traffic load. Also, the energy savings decrease as the number of mobile users (50 users in our case) connected to the remote site increases. Lastly, the proposed algorithm achieves 51% energy savings when compared with the 43% obtained by our benchmark algorithm. The proposed method demonstrates superior performance over the benchmark algorithm as it uses foresighted optimization where the harvested energy and the expected load are predicted over a given short-term horizon.
{"title":"Remote and Rural Connectivity: Infrastructure and Resource Sharing Principles","authors":"Thembelihle Dlamini, S. Vilakati","doi":"10.1155/2021/6065119","DOIUrl":"https://doi.org/10.1155/2021/6065119","url":null,"abstract":"As mobile networks (MNs) are advancing towards meeting mobile user requirements, the rural-urban divide still remains a major challenge. While areas within the urban space (metropolitan mobile space) are being developed, i.e., small Base Stations (BSs) empowered with computing capabilities are deployed to improve the delivery of user requirements, rural areas are left behind. Due to challenges of low population density, low income, difficult terrain, nonexistent infrastructure, and lack of power grid, remote areas have low digital penetration. This situation makes remote areas less attractive towards investments and to operate connectivity networks, thus failing to achieve universal access to the Internet. In addressing this issue, this paper proposes a new BS deployment and resource management method for remote and rural areas. Here, two MN operators share their resources towards the procurement and deployment of green energy-powered BSs equipped with computing capabilities. Then, the network infrastructure is shared between the mobile operators, with the main goal of enabling energy-efficient infrastructure sharing, i.e., BS and its colocated computing platform. Using this resource management strategy in rural communication sites guarantees a quality of service (QoS) comparable to that of urban communication sites. The performance evaluation conducted through simulations validates our analysis as the prediction variations observed show greater accuracy between the harvested energy and the traffic load. Also, the energy savings decrease as the number of mobile users (50 users in our case) connected to the remote site increases. Lastly, the proposed algorithm achieves 51% energy savings when compared with the 43% obtained by our benchmark algorithm. The proposed method demonstrates superior performance over the benchmark algorithm as it uses foresighted optimization where the harvested energy and the expected load are predicted over a given short-term horizon.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"6 1","pages":"6065119:1-6065119:12"},"PeriodicalIF":0.0,"publicationDate":"2021-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82528650","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 paper proposes a novel precoding-aided and efficient data transmission scheme called virtual spatial channel number and index modulation (VS-CNIM), which conveys extra data by changing both the number and index of active virtual parallel channels of multiple-input multiple-output (MIMO) channels, obtained through the singular value decomposition (SVD) in each time slot. Unlike the conventional virtual spatial modulation (VSM), where extra data bits are transmitted only using index of active virtual parallel channels, the VS-CNIM scheme, depending on incoming information bits, transmits extra bits utilizing both the number and indices of active parallel channels along the bits carried by M -ary constellation symbols. Therefore, VS-CNIM provides significantly superior spectral efficiency (SE) compared to VSM. Considering the influence of imperfect channel estimation, a closed-form upper bound is derived on average bit error probability (ABEP). The asymptotic performance is also analyzed, which gives the coding gain and diversity order and describes error floor under the consideration of perfect and imperfect channel estimation, respectively. Monte Carlo simulations exhibit that the VS-CNIM scheme achieves considerably better error performance and high SE than precoding-aided SM (PSM) and VSM schemes.
{"title":"Virtual Spatial Channel Number and Index Modulation","authors":"Zahid Iqbal, Fei Ji, Yun Liu","doi":"10.1155/2021/2982226","DOIUrl":"https://doi.org/10.1155/2021/2982226","url":null,"abstract":"This paper proposes a novel precoding-aided and efficient data transmission scheme called virtual spatial channel number and index modulation (VS-CNIM), which conveys extra data by changing both the number and index of active virtual parallel channels of multiple-input multiple-output (MIMO) channels, obtained through the singular value decomposition (SVD) in each time slot. Unlike the conventional virtual spatial modulation (VSM), where extra data bits are transmitted only using index of active virtual parallel channels, the VS-CNIM scheme, depending on incoming information bits, transmits extra bits utilizing both the number and indices of active parallel channels along the bits carried by \u0000 \u0000 M\u0000 \u0000 -ary constellation symbols. Therefore, VS-CNIM provides significantly superior spectral efficiency (SE) compared to VSM. Considering the influence of imperfect channel estimation, a closed-form upper bound is derived on average bit error probability (ABEP). The asymptotic performance is also analyzed, which gives the coding gain and diversity order and describes error floor under the consideration of perfect and imperfect channel estimation, respectively. Monte Carlo simulations exhibit that the VS-CNIM scheme achieves considerably better error performance and high SE than precoding-aided SM (PSM) and VSM schemes.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"197 2","pages":"2982226:1-2982226:10"},"PeriodicalIF":0.0,"publicationDate":"2021-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91488136","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 interconnection of all things and industrial integration is the current trend of the times. Among them, the interconnection of all things is the demand of informationization of the times, and the industrial integration is the demand of industrial development. The interconnection of all things is realized based on wireless communication technology. It is necessary to combine the development of the tourist area and the surrounding culture. The relationship between tourist attractions and culture needs to be fully and effectively developed. In order to fully explore the advantages of the cooperation between the two, it is necessary to combine modern technology to package the tour process of each characteristic culture of the scenic spot. Virtual reality is a modern technology that can combine culture and tourism. Wireless communication and VR technology are applied to the development of integration of culture and tourism. The process of tourism will promote profound changes in the tourism model. Under the demand for informatization in various industries, the tourism industry is gradually developing in this direction. The integration of culture and tourism will also be driven by informatization and technology. This paper analyzes the current situation of culture and tourism, summarizes the problems existing in the current process of integration of culture and tourism, and finally puts forward targeted solutions. Mainly in the process of the integration and development of tourism and cultural industries, the traditional culture and scenic spots are the basic factors, combined with wireless communication and virtual reality technology, to develop a tourism industry with technological characteristics of the new era.
{"title":"Research on the Integration and Development of Culture and Tourism Based on Wireless Communication and Virtual Reality Technology","authors":"HeChi Gan, Yaoguang Li, Yanan Song","doi":"10.1155/2021/8322092","DOIUrl":"https://doi.org/10.1155/2021/8322092","url":null,"abstract":"The interconnection of all things and industrial integration is the current trend of the times. Among them, the interconnection of all things is the demand of informationization of the times, and the industrial integration is the demand of industrial development. The interconnection of all things is realized based on wireless communication technology. It is necessary to combine the development of the tourist area and the surrounding culture. The relationship between tourist attractions and culture needs to be fully and effectively developed. In order to fully explore the advantages of the cooperation between the two, it is necessary to combine modern technology to package the tour process of each characteristic culture of the scenic spot. Virtual reality is a modern technology that can combine culture and tourism. Wireless communication and VR technology are applied to the development of integration of culture and tourism. The process of tourism will promote profound changes in the tourism model. Under the demand for informatization in various industries, the tourism industry is gradually developing in this direction. The integration of culture and tourism will also be driven by informatization and technology. This paper analyzes the current situation of culture and tourism, summarizes the problems existing in the current process of integration of culture and tourism, and finally puts forward targeted solutions. Mainly in the process of the integration and development of tourism and cultural industries, the traditional culture and scenic spots are the basic factors, combined with wireless communication and virtual reality technology, to develop a tourism industry with technological characteristics of the new era.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"2 3","pages":"8322092:1-8322092:6"},"PeriodicalIF":0.0,"publicationDate":"2021-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72605746","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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