Difeng Zhu, Guojiang Shen, Jingjing Chen, Wenfeng Zhou, Xiangjie Kong
Due to the incomplete coverage and failure of traffic data collectors during the collection, traffic data usually suffers from information missing. Achieving accurate imputation is critical to the operation of transportation networks. Existing approaches usually focus on the characteristic analysis of temporal variation and adjacent spatial representation, and the consideration of higher-order spatial correlations and continuous data missing attracts more attentions from the academia and industry. In this paper, by leveraging motif-based graph aggregation, we propose a spatiotemporal imputation approach to address the issue of traffic data missing. First, through motif discovery, the higher-order graph aggregation model was presented in traffic networks. It utilized graph convolution network (GCN) to polymerize the correlated segment attributes of the missing data segments. Then, the multitime dimension imputation model based on bidirectional long short-term memory (Bi-LSTM) incorporated the recent, daily-periodic, and weekly-periodic dependencies of the historical data. Finally, the spatial aggregated values and the temporal fusion values were integrated to obtain the results. We conducted comprehensive experiments based on the real-world dataset and discussed the case of random and continuous data missing by different time intervals, and the results showed that the proposed approach was feasible and accurate.
{"title":"A Higher-Order Motif-Based Spatiotemporal Graph Imputation Approach for Transportation Networks","authors":"Difeng Zhu, Guojiang Shen, Jingjing Chen, Wenfeng Zhou, Xiangjie Kong","doi":"10.1155/2022/1702170","DOIUrl":"https://doi.org/10.1155/2022/1702170","url":null,"abstract":"Due to the incomplete coverage and failure of traffic data collectors during the collection, traffic data usually suffers from information missing. Achieving accurate imputation is critical to the operation of transportation networks. Existing approaches usually focus on the characteristic analysis of temporal variation and adjacent spatial representation, and the consideration of higher-order spatial correlations and continuous data missing attracts more attentions from the academia and industry. In this paper, by leveraging motif-based graph aggregation, we propose a spatiotemporal imputation approach to address the issue of traffic data missing. First, through motif discovery, the higher-order graph aggregation model was presented in traffic networks. It utilized graph convolution network (GCN) to polymerize the correlated segment attributes of the missing data segments. Then, the multitime dimension imputation model based on bidirectional long short-term memory (Bi-LSTM) incorporated the recent, daily-periodic, and weekly-periodic dependencies of the historical data. Finally, the spatial aggregated values and the temporal fusion values were integrated to obtain the results. We conducted comprehensive experiments based on the real-world dataset and discussed the case of random and continuous data missing by different time intervals, and the results showed that the proposed approach was feasible and accurate.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"68 1","pages":"1702170:1-1702170:16"},"PeriodicalIF":0.0,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84818268","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}
Adamu Sani Yahaya, Nadeem Javaid, Sameeh Ullah, Rabiya Khalid, M. Javed, Rehan Ullah Khan, Zahid Wadud, M. Khan
A Smart Community (SC) is an essential part of the Internet of Energy (IoE), which helps to integrate Electric Vehicles (EVs) and distributed renewable energy sources in a smart grid. As a result of the potential privacy and security challenges in the distributed energy system, it is becoming a great problem to optimally schedule EVs’ charging with different energy consumption patterns and perform reliable energy trading in the SC. In this paper, a blockchain-based privacy-preserving energy trading system for 5G-deployed SC is proposed. The proposed system is divided into two components: EVs and residential prosumers. In this system, a reputation-based distributed matching algorithm for EVs and a Reward-based Starvation Free Energy Allocation Policy (RSFEAP) for residential homes are presented. A short-term load forecasting model for EVs’ charging using multiple linear regression is proposed to plan and manage the intermittent charging behavior of EVs. In the proposed system, identity-based encryption and homomorphic encryption techniques are integrated to protect the privacy of transactions and users, respectively. The performance of the proposed system for EVs’ component is evaluated using convergence duration, forecasting accuracy, and executional and transactional costs as performance metrics. For the residential prosumers’ component, the performance is evaluated using reward index, type of transactions, energy contributed, average convergence time, and the number of iterations as performance metrics. The simulation results for EVs’ charging forecasting gives an accuracy of 99.25%. For the EVs matching algorithm, the proposed privacy-preserving algorithm converges faster than the bichromatic mutual nearest neighbor algorithm. For RSFEAP, the number of iterations for 50 prosumers is 8, which is smaller than the benchmark. Its convergence duration is also 10 times less than the benchmark scheme. Moreover, security and privacy analyses are presented. Finally, we carry out security vulnerability analysis of smart contracts to ensure that the proposed smart contracts are secure and bug-free against the common vulnerabilities’ attacks. The results show that the smart contracts are secure against both internal and external attacks.
{"title":"A Secure and Efficient Energy Trading Model Using Blockchain for a 5G-Deployed Smart Community","authors":"Adamu Sani Yahaya, Nadeem Javaid, Sameeh Ullah, Rabiya Khalid, M. Javed, Rehan Ullah Khan, Zahid Wadud, M. Khan","doi":"10.1155/2022/6953125","DOIUrl":"https://doi.org/10.1155/2022/6953125","url":null,"abstract":"A Smart Community (SC) is an essential part of the Internet of Energy (IoE), which helps to integrate Electric Vehicles (EVs) and distributed renewable energy sources in a smart grid. As a result of the potential privacy and security challenges in the distributed energy system, it is becoming a great problem to optimally schedule EVs’ charging with different energy consumption patterns and perform reliable energy trading in the SC. In this paper, a blockchain-based privacy-preserving energy trading system for 5G-deployed SC is proposed. The proposed system is divided into two components: EVs and residential prosumers. In this system, a reputation-based distributed matching algorithm for EVs and a Reward-based Starvation Free Energy Allocation Policy (RSFEAP) for residential homes are presented. A short-term load forecasting model for EVs’ charging using multiple linear regression is proposed to plan and manage the intermittent charging behavior of EVs. In the proposed system, identity-based encryption and homomorphic encryption techniques are integrated to protect the privacy of transactions and users, respectively. The performance of the proposed system for EVs’ component is evaluated using convergence duration, forecasting accuracy, and executional and transactional costs as performance metrics. For the residential prosumers’ component, the performance is evaluated using reward index, type of transactions, energy contributed, average convergence time, and the number of iterations as performance metrics. The simulation results for EVs’ charging forecasting gives an accuracy of 99.25%. For the EVs matching algorithm, the proposed privacy-preserving algorithm converges faster than the bichromatic mutual nearest neighbor algorithm. For RSFEAP, the number of iterations for 50 prosumers is 8, which is smaller than the benchmark. Its convergence duration is also 10 times less than the benchmark scheme. Moreover, security and privacy analyses are presented. Finally, we carry out security vulnerability analysis of smart contracts to ensure that the proposed smart contracts are secure and bug-free against the common vulnerabilities’ attacks. The results show that the smart contracts are secure against both internal and external attacks.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"62 1","pages":"6953125:1-6953125:27"},"PeriodicalIF":0.0,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82605686","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}
Due to the development of social media, the threshold for information dissemination has become lower than ever before. As a special kind of information, rumors are usually harmful and are usually accompanied by a high degree of ambiguity that makes them difficult to immediately identify, but “rumors stop at wise men.” When someone identifies a rumor as false and begins spreading the truth instead, a confrontational relationship obtains between the rumor and the truth that leads to the stifling of the former. Given this, we developed a 2SIH2R model in this study that contains mechanisms of discernment and confrontation in a heterogeneous network to examine the dissemination of the rumor and the truth. By using mean-field equations of the 2SIH2R model, the threshold of the spreading of each can be determined separately in three cases. The results of a numerical simulation show that under the same conditions, the greater is the mechanism of discernment or confrontation, the smaller is the instantaneous maximum influence and the final range of influence of the rumor. It can be also concluded that the earlier release of the truth about the event by the government can significantly control the rumor. Secondly, it is more effective to publish the truth in advance than after the rumor has appeared. Thirdly, it is more important for the government to increase education and improve the ability of citizens to reveal the rumor than to increase the spread of the truth after the rumor occurs. These results can be used to help reduce the harmful effects of rumors.
{"title":"Dynamics of 2SIH2R Rumor-Spreading Model in a Heterogeneous Network","authors":"Yan Wang, Feng Qing, Ming Yan","doi":"10.1155/2022/7398387","DOIUrl":"https://doi.org/10.1155/2022/7398387","url":null,"abstract":"Due to the development of social media, the threshold for information dissemination has become lower than ever before. As a special kind of information, rumors are usually harmful and are usually accompanied by a high degree of ambiguity that makes them difficult to immediately identify, but “rumors stop at wise men.” When someone identifies a rumor as false and begins spreading the truth instead, a confrontational relationship obtains between the rumor and the truth that leads to the stifling of the former. Given this, we developed a 2SIH2R model in this study that contains mechanisms of discernment and confrontation in a heterogeneous network to examine the dissemination of the rumor and the truth. By using mean-field equations of the 2SIH2R model, the threshold of the spreading of each can be determined separately in three cases. The results of a numerical simulation show that under the same conditions, the greater is the mechanism of discernment or confrontation, the smaller is the instantaneous maximum influence and the final range of influence of the rumor. It can be also concluded that the earlier release of the truth about the event by the government can significantly control the rumor. Secondly, it is more effective to publish the truth in advance than after the rumor has appeared. Thirdly, it is more important for the government to increase education and improve the ability of citizens to reveal the rumor than to increase the spread of the truth after the rumor occurs. These results can be used to help reduce the harmful effects of rumors.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"19 1","pages":"7398387:1-7398387:13"},"PeriodicalIF":0.0,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88106702","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}
Jinqian Chen, Yong Yan, Shaoyong Guo, Yinlin Ren, F. Qi
With the continuous development of information technology, the Internet of Things has also been widely used. At the same time, in the power Internet of Things environment, reliable data is essential for data use and accurate analysis. Data security has become a key factor in ensuring the stable operation of the power grid. However, the power Internet of Things devices is extremely vulnerable to network attacks, leading to data tampering and deletion. Resisting tampering, preventing data loss, and reliably restoring data have become difficult to ensure data security. In order to solve this problem, this paper proposes a trusted data recovery system based on blockchain and coding technology. Data nodes of the power Internet of Things encode key data and back them up to the blockchain network through a data processing server located on the edge. The data processing server performs real-time detection of the data integrity of the data nodes. When the data is tampered with or deleted, the data processing server promptly obtains the corresponding data encoding blocks from the blockchain network, decodes them, and sends them to the data node to complete the data recovery task. According to the test result, the data backup speed of this system is increased by 15.3%, and the data recovery speed is increased by 19.8% compared with the traditional scheme. It has good security and real-time performance. Meanwhile, it reduces the network and storage resource overhead in the data backup and recovery process.
{"title":"A System for Trusted Recovery of Data Based on Blockchain and Coding Techniques","authors":"Jinqian Chen, Yong Yan, Shaoyong Guo, Yinlin Ren, F. Qi","doi":"10.1155/2022/8390241","DOIUrl":"https://doi.org/10.1155/2022/8390241","url":null,"abstract":"With the continuous development of information technology, the Internet of Things has also been widely used. At the same time, in the power Internet of Things environment, reliable data is essential for data use and accurate analysis. Data security has become a key factor in ensuring the stable operation of the power grid. However, the power Internet of Things devices is extremely vulnerable to network attacks, leading to data tampering and deletion. Resisting tampering, preventing data loss, and reliably restoring data have become difficult to ensure data security. In order to solve this problem, this paper proposes a trusted data recovery system based on blockchain and coding technology. Data nodes of the power Internet of Things encode key data and back them up to the blockchain network through a data processing server located on the edge. The data processing server performs real-time detection of the data integrity of the data nodes. When the data is tampered with or deleted, the data processing server promptly obtains the corresponding data encoding blocks from the blockchain network, decodes them, and sends them to the data node to complete the data recovery task. According to the test result, the data backup speed of this system is increased by 15.3%, and the data recovery speed is increased by 19.8% compared with the traditional scheme. It has good security and real-time performance. Meanwhile, it reduces the network and storage resource overhead in the data backup and recovery process.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"26 1","pages":"8390241:1-8390241:12"},"PeriodicalIF":0.0,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87494657","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}
Sarosh Ahmad, Bilal Manzoor, Salman Naseer, Nilton Santos-Valdivia, A. Ghaffar, M. I. Abbasi
Biomedical implantable antennas have a major role in biomedical telemetry applications. Therefore, a compact-size low-profile implantable antenna working in industrial, scientific, and medical (ISM) band at 915 MHz is presented. The presented antenna is a simple slotted patch fed with a coaxial probe of 50 Ω impedance. The patch consists of four slotted resonators printed on a flexible Roger Duroid RT5880 substrate ( ε r = 2.2 , tan δ = 0.0009 ) with the standard thickness of 0.254 mm. The complete volume of the designed antenna is 7 mm × 7 mm × 0.254 mm ( 0.08 λ g × 0.08 λ g × 0.003 λ g ). The antenna covers the bandwidth from 800 MHz to 1 GHz (200 MHz) inside skin tissue. A good agreement between the simulation and measurements of the antenna has been obtained. Finally, the specific absorption rate (SAR) values have also been analyzed through simulations as 8.17 W/kg inside skin over 1 g of mass tissue. The proposed SAR values are less than the limit of the Federal Communications Commission (FCC). This antenna is miniaturized and an ideal applicant for applications in biomedical implants.
生物医学植入式天线在生物医学遥测应用中具有重要作用。因此，提出了一种在915 MHz的工业、科学和医疗(ISM)频段工作的紧凑尺寸的低轮廓植入式天线。所提出的天线是一个简单的开槽贴片馈电同轴探头50 Ω阻抗。该贴片由四个槽谐振器组成，印刷在柔性Roger Duroid RT5880衬底上(ε r = 2.2, tan δ = 0.0009)，标准厚度为0.254 mm。设计天线的总体积为7 mm × 7 mm × 0.254 mm (0.08 λ g × 0.08 λ g × 0.003 λ g)。该天线覆盖皮肤组织内部800 - 1ghz (200mhz)的带宽。仿真结果与实测结果吻合较好。最后，通过模拟分析了比吸收率(SAR)值为8.17 W/kg / 1g质量组织的皮肤内。建议的SAR值小于美国联邦通信委员会(FCC)的限制。这种天线是小型化的，是生物医学植入物应用的理想申请人。
{"title":"X-Shaped Slotted Patch Biomedical Implantable Antenna for Wireless Communication Networks","authors":"Sarosh Ahmad, Bilal Manzoor, Salman Naseer, Nilton Santos-Valdivia, A. Ghaffar, M. I. Abbasi","doi":"10.1155/2022/7594587","DOIUrl":"https://doi.org/10.1155/2022/7594587","url":null,"abstract":"Biomedical implantable antennas have a major role in biomedical telemetry applications. Therefore, a compact-size low-profile implantable antenna working in industrial, scientific, and medical (ISM) band at 915 MHz is presented. The presented antenna is a simple slotted patch fed with a coaxial probe of 50 Ω impedance. The patch consists of four slotted resonators printed on a flexible Roger Duroid RT5880 substrate (\u0000 \u0000 \u0000 \u0000 ε\u0000 \u0000 \u0000 r\u0000 \u0000 \u0000 =\u0000 2.2\u0000 \u0000 , \u0000 \u0000 tan\u0000 δ\u0000 =\u0000 0.0009\u0000 \u0000 ) with the standard thickness of 0.254 mm. The complete volume of the designed antenna is \u0000 \u0000 7\u0000 \u0000 mm\u0000 ×\u0000 7\u0000 \u0000 mm\u0000 ×\u0000 0.254\u0000 \u0000 mm\u0000 \u0000 (\u0000 \u0000 0.08\u0000 \u0000 \u0000 λ\u0000 \u0000 \u0000 g\u0000 \u0000 \u0000 ×\u0000 0.08\u0000 \u0000 \u0000 λ\u0000 \u0000 \u0000 g\u0000 \u0000 \u0000 ×\u0000 0.003\u0000 \u0000 \u0000 λ\u0000 \u0000 \u0000 g\u0000 \u0000 \u0000 \u0000 ). The antenna covers the bandwidth from 800 MHz to 1 GHz (200 MHz) inside skin tissue. A good agreement between the simulation and measurements of the antenna has been obtained. Finally, the specific absorption rate (SAR) values have also been analyzed through simulations as 8.17 W/kg inside skin over 1 g of mass tissue. The proposed SAR values are less than the limit of the Federal Communications Commission (FCC). This antenna is miniaturized and an ideal applicant for applications in biomedical implants.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"21 1","pages":"7594587:1-7594587:11"},"PeriodicalIF":0.0,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87319887","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 development of computer technology and management science, decision support systems have emerged that can improve the quality and effects of decision-making. This study mainly examined the application of the wireless communication of an embedded microprocessor and computer vision in the decision support system of martial arts competition referees. Using the embedded microprocessor’s characteristics of a small size, high precision, high reliability, and high efficiency, a decision support system for martial arts competition referees was designed. In the experiment, the similarity between the target field and the source field could be controlled by adjusting the mean value. To better extract the target, this study used the time domain changes of the three adjacent frames, before, middle, and back, to detect the moving target to extract the change detection template. The Canny edge detection method was used to extract the edge information of the image and eliminate the nonmotion area; then, morphology was used to correct the image to complete the connection of the broken edge to obtain the final initial segmentation mask image. In the process of calculation, there were some noises and small fragments. In this study, morphology and background difference were used to optimize the segmented image. Experimental data show that the algorithm detection accuracy rate was high—between 70% and 100%—and the effect was relatively ideal. The results indicate that the proposed algorithm can effectively reduce matching noise, improve the matching accuracy of the edge area and the low-texture area, and achieve a fast matching speed.
{"title":"Influence of Embedded Microprocessor Wireless Communication and Computer Vision in Wushu Competition Referees' Decision Support","authors":"Jin-lu Ji, Feng Liang","doi":"10.1155/2022/2121573","DOIUrl":"https://doi.org/10.1155/2022/2121573","url":null,"abstract":"With the development of computer technology and management science, decision support systems have emerged that can improve the quality and effects of decision-making. This study mainly examined the application of the wireless communication of an embedded microprocessor and computer vision in the decision support system of martial arts competition referees. Using the embedded microprocessor’s characteristics of a small size, high precision, high reliability, and high efficiency, a decision support system for martial arts competition referees was designed. In the experiment, the similarity between the target field and the source field could be controlled by adjusting the mean value. To better extract the target, this study used the time domain changes of the three adjacent frames, before, middle, and back, to detect the moving target to extract the change detection template. The Canny edge detection method was used to extract the edge information of the image and eliminate the nonmotion area; then, morphology was used to correct the image to complete the connection of the broken edge to obtain the final initial segmentation mask image. In the process of calculation, there were some noises and small fragments. In this study, morphology and background difference were used to optimize the segmented image. Experimental data show that the algorithm detection accuracy rate was high—between 70% and 100%—and the effect was relatively ideal. The results indicate that the proposed algorithm can effectively reduce matching noise, improve the matching accuracy of the edge area and the low-texture area, and achieve a fast matching speed.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"10 1","pages":"2121573:1-2121573:13"},"PeriodicalIF":0.0,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82944134","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}
Vehicular ad-hoc network (VANET) is one of the most important components to realizing intelligent connected vehicles, which is a high-commercial-value vertical application of the fifth-generation (5G) mobile communication system and beyond communications. VANET requires both ultrareliable low latency and high-data rate communications. In order to evolve towards the reconfigurable wireless networks (RWNs), the 5G mobile communication system is expected to adapt the key parameters of its radio nodes rapidly. However, the current propagation prediction approaches are difficult to balance accuracy and efficiency, which makes the current network unable to perform autonomous optimization agilely. In order to break through this bottleneck, an accurate and efficient propagation prediction and optimization method empowered by artificial intelligence (AI) is proposed in this paper. Initially, a path loss model based on a multilayer perception neural network is established at 2.6 GHz for three base stations in an urban environment. Not like empirical models using environment types or deterministic models employing three-dimensional environment models, this AI-empowered model explores the environment feature by introducing interference clutters. This critical innovation makes the proposed model so accurate as ray tracing but much more efficient. Then, this validated model is utilized to realize a coverage prediction for 20 base stations only within 1 minute. Afterward, key parameters of these base stations, such as transmission power, elevation, and azimuth angles of antennas, are optimized using simulated annealing. This whole methodology paves the way for evolving the current 5G network to RWNs.
{"title":"AI-Empowered Propagation Prediction and Optimization for Reconfigurable Wireless Networks","authors":"Fusheng Zhu, Weiwen Cai, Zhigang Wang, Fang Li","doi":"10.1155/2022/9901960","DOIUrl":"https://doi.org/10.1155/2022/9901960","url":null,"abstract":"Vehicular ad-hoc network (VANET) is one of the most important components to realizing intelligent connected vehicles, which is a high-commercial-value vertical application of the fifth-generation (5G) mobile communication system and beyond communications. VANET requires both ultrareliable low latency and high-data rate communications. In order to evolve towards the reconfigurable wireless networks (RWNs), the 5G mobile communication system is expected to adapt the key parameters of its radio nodes rapidly. However, the current propagation prediction approaches are difficult to balance accuracy and efficiency, which makes the current network unable to perform autonomous optimization agilely. In order to break through this bottleneck, an accurate and efficient propagation prediction and optimization method empowered by artificial intelligence (AI) is proposed in this paper. Initially, a path loss model based on a multilayer perception neural network is established at 2.6 GHz for three base stations in an urban environment. Not like empirical models using environment types or deterministic models employing three-dimensional environment models, this AI-empowered model explores the environment feature by introducing interference clutters. This critical innovation makes the proposed model so accurate as ray tracing but much more efficient. Then, this validated model is utilized to realize a coverage prediction for 20 base stations only within 1 minute. Afterward, key parameters of these base stations, such as transmission power, elevation, and azimuth angles of antennas, are optimized using simulated annealing. This whole methodology paves the way for evolving the current 5G network to RWNs.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"61 1","pages":"9901960:1-9901960:10"},"PeriodicalIF":0.0,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78177176","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}
K. Veena, K. Meena, Yuvaraja Teekaraman, Ramya Kuppusamy, A. Radhakrishnan
In the digital age, cybercrime is spreading its root widely. Internet evolution has turned out to a boon as well as curse for those confronting the issues of privacy, national security, social decency, IP rights, child protection, fighting, detecting, and prosecuting cybercrime. Hence, there arises a need to detect the cybercriminal. Cybercrime identification utilizes dataset that is taken from CBS open dataset. For identifying the cybercriminal, support vector machine (SVM) in the C SVM classification and K -nearest neighbor (KNN) models is utilized for determining the cybercrime information. The evaluation of the performance is done taking the following metrics into consideration: true positive, false positive, true negative and false negative, false alarm rate, detection rate, accuracy, recall, precision, specificity, sensitivity, classification rate, and Fowlkes-Mallows Scores. Expectation maximization (EM) calculation is utilized for evaluating the presentation of the Gaussian mixture model. The performance of classifier’s presentation is also done. Accuracy is accomplished in the event of grouping by means of SVM classifier as 89% in the supervised method.
{"title":"C SVM Classification and KNN Techniques for Cyber Crime Detection","authors":"K. Veena, K. Meena, Yuvaraja Teekaraman, Ramya Kuppusamy, A. Radhakrishnan","doi":"10.1155/2022/3640017","DOIUrl":"https://doi.org/10.1155/2022/3640017","url":null,"abstract":"In the digital age, cybercrime is spreading its root widely. Internet evolution has turned out to a boon as well as curse for those confronting the issues of privacy, national security, social decency, IP rights, child protection, fighting, detecting, and prosecuting cybercrime. Hence, there arises a need to detect the cybercriminal. Cybercrime identification utilizes dataset that is taken from CBS open dataset. For identifying the cybercriminal, support vector machine (SVM) in the \u0000 \u0000 C\u0000 \u0000 SVM classification and \u0000 \u0000 K\u0000 \u0000 -nearest neighbor (KNN) models is utilized for determining the cybercrime information. The evaluation of the performance is done taking the following metrics into consideration: true positive, false positive, true negative and false negative, false alarm rate, detection rate, accuracy, recall, precision, specificity, sensitivity, classification rate, and Fowlkes-Mallows Scores. Expectation maximization (EM) calculation is utilized for evaluating the presentation of the Gaussian mixture model. The performance of classifier’s presentation is also done. Accuracy is accomplished in the event of grouping by means of SVM classifier as 89% in the supervised method.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"21 1","pages":"3640017:1-3640017:9"},"PeriodicalIF":0.0,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82267202","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 respect to the fuzzy boundaries of military heterogeneous entities, this paper improves the entity annotation mechanism for entity with fuzzy boundaries based on related research works. This paper applies a BERT-BiLSTM-CRF model fusing deep learning and machine learning to recognize military entities, and thus, we can construct a smart military knowledge base with these entities. Furthermore, we can explore many military AI applications with the knowledge base and military Internet of Things (MIoT). To verify the performance of the model, we design multiple types of experiments. Experimental results show that the recognition performance of the model keeps improving with the increasing size of the corpus in the multidata source scenario, with the F -score increasing from 73.56% to 84.53%. Experimental results of cross-corpus cross-validation show that the more types of entities covered in the training corpus and the richer the representation type, the stronger the generalization ability of the trained model, in which the recall rate of the model trained with the novel random type corpus reaches 74.33% and the F -score reaches 76.98%. The results of the multimodel comparison experiments show that the BERT-BiLSTM-CRF model applied in this paper performs well for the recognition of military entities. The longitudinal comparison experimental results show that the F -score of the BERT-BiLSTM-CRF model is 18.72%, 11.24%, 9.24%, and 5.07% higher than the four models CRF, LSTM-CRF, BiLSTM-CR, and BERT-CRF, respectively. The cross-sectional comparison experimental results show that the F -score of the BERT-BiLSTM-CRF model improved by 6.63%, 7.95%, 3.72%, and 1.81% compared to the Lattice-LSTM-CRF, CNN-BiLSTM-CRF, BERT-BiGRU-CRF, and BERT-IDCNN-CRF models, respectively.
{"title":"Fusion Deep Learning and Machine Learning for Heterogeneous Military Entity Recognition","authors":"Hui Li, Lin Yu, J. Zhang, Ming Lyu","doi":"10.1155/2022/1103022","DOIUrl":"https://doi.org/10.1155/2022/1103022","url":null,"abstract":"With respect to the fuzzy boundaries of military heterogeneous entities, this paper improves the entity annotation mechanism for entity with fuzzy boundaries based on related research works. This paper applies a BERT-BiLSTM-CRF model fusing deep learning and machine learning to recognize military entities, and thus, we can construct a smart military knowledge base with these entities. Furthermore, we can explore many military AI applications with the knowledge base and military Internet of Things (MIoT). To verify the performance of the model, we design multiple types of experiments. Experimental results show that the recognition performance of the model keeps improving with the increasing size of the corpus in the multidata source scenario, with the \u0000 \u0000 F\u0000 \u0000 -score increasing from 73.56% to 84.53%. Experimental results of cross-corpus cross-validation show that the more types of entities covered in the training corpus and the richer the representation type, the stronger the generalization ability of the trained model, in which the recall rate of the model trained with the novel random type corpus reaches 74.33% and the \u0000 \u0000 F\u0000 \u0000 -score reaches 76.98%. The results of the multimodel comparison experiments show that the BERT-BiLSTM-CRF model applied in this paper performs well for the recognition of military entities. The longitudinal comparison experimental results show that the \u0000 \u0000 F\u0000 \u0000 -score of the BERT-BiLSTM-CRF model is 18.72%, 11.24%, 9.24%, and 5.07% higher than the four models CRF, LSTM-CRF, BiLSTM-CR, and BERT-CRF, respectively. The cross-sectional comparison experimental results show that the \u0000 \u0000 F\u0000 \u0000 -score of the BERT-BiLSTM-CRF model improved by 6.63%, 7.95%, 3.72%, and 1.81% compared to the Lattice-LSTM-CRF, CNN-BiLSTM-CRF, BERT-BiGRU-CRF, and BERT-IDCNN-CRF models, respectively.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"2 1","pages":"1103022:1-1103022:11"},"PeriodicalIF":0.0,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82943389","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 multipath fading and Doppler effect are well-known phenomena affecting channel quality in mobile wireless communication systems. Within this context, the emergence of reconfigurable intelligence surfaces (RISs) brings a chance to achieve this goal. RISs as a potential solution are considered to be proposed in sixth generation (6G). The core idea of RISs is to change the channel characteristic from uncontrollable to controllable. This is reflected by some novel functionalities with wave absorption and abnormal reflection. In this paper, the multipath fading and Doppler effect are characterized by establishing a mathematical model from the perspective of reflectors and RISs in different mobile wireless communication processes. In addition, the solutions that improve the multipath fading and Doppler effect stemming from the movement of mobile transmitter are discussed by utilizing multiple RISs. A large number of experimental results demonstrate that the received signal strength abnormal fluctuations due to Doppler effect can be eliminated effectively by real-time control of RISs. Meanwhile, the multipath fading is also mitigated when all reflectors deployed are coated with RISs.
{"title":"Analysis of Multipath Fading and Doppler Effect with Multiple Reconfigurable Intelligent Surfaces in Mobile Wireless Networks","authors":"Guilu Wu, Fan Li, Huilin Jiang","doi":"10.1155/2022/5751316","DOIUrl":"https://doi.org/10.1155/2022/5751316","url":null,"abstract":"The multipath fading and Doppler effect are well-known phenomena affecting channel quality in mobile wireless communication systems. Within this context, the emergence of reconfigurable intelligence surfaces (RISs) brings a chance to achieve this goal. RISs as a potential solution are considered to be proposed in sixth generation (6G). The core idea of RISs is to change the channel characteristic from uncontrollable to controllable. This is reflected by some novel functionalities with wave absorption and abnormal reflection. In this paper, the multipath fading and Doppler effect are characterized by establishing a mathematical model from the perspective of reflectors and RISs in different mobile wireless communication processes. In addition, the solutions that improve the multipath fading and Doppler effect stemming from the movement of mobile transmitter are discussed by utilizing multiple RISs. A large number of experimental results demonstrate that the received signal strength abnormal fluctuations due to Doppler effect can be eliminated effectively by real-time control of RISs. Meanwhile, the multipath fading is also mitigated when all reflectors deployed are coated with RISs.","PeriodicalId":23995,"journal":{"name":"Wirel. Commun. Mob. Comput.","volume":"9 1","pages":"5751316:1-5751316:15"},"PeriodicalIF":0.0,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90243029","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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