In order to solve the matching algorithm problem of network e-commerce platform, a method of applying BP neural network in the network e-commerce platform matching algorithm is proposed. First of all, combined with the actual situation of the platform, select 9 factors that are most in line with the company’s actual business model to influence the selection for analysis; secondly, import 60 sets of data into MATLAB software, measure the input and output data uniformly, and divide the sample data matrix into training set and test. Finally, after multiple factor combinations and verifications, it is concluded that in the training model of the five main factors, the prediction results of the model are compared with the real values. The feasibility of establishing the selection model based on BP neural network is proved. Online e-commerce platforms can refer to this model to build a product selection model that meets the needs of the platform, helping enterprises to achieve more efficient product selection work. Since the parameter initialization of the neural network is random, although the output results are different after the program runs for many times, the R2 is still stable between 0.7 and 1.0, which proves that the predicted value made by the system is highly approximate to the real value and can achieve the predicted effect.
{"title":"Application of BP Neural Network in Matching Algorithm of Network E-Commerce Platform","authors":"Jingcheng Zhang","doi":"10.1155/2022/2045811","DOIUrl":"https://doi.org/10.1155/2022/2045811","url":null,"abstract":"In order to solve the matching algorithm problem of network e-commerce platform, a method of applying BP neural network in the network e-commerce platform matching algorithm is proposed. First of all, combined with the actual situation of the platform, select 9 factors that are most in line with the company’s actual business model to influence the selection for analysis; secondly, import 60 sets of data into MATLAB software, measure the input and output data uniformly, and divide the sample data matrix into training set and test. Finally, after multiple factor combinations and verifications, it is concluded that in the training model of the five main factors, the prediction results of the model are compared with the real values. The feasibility of establishing the selection model based on BP neural network is proved. Online e-commerce platforms can refer to this model to build a product selection model that meets the needs of the platform, helping enterprises to achieve more efficient product selection work. Since the parameter initialization of the neural network is random, although the output results are different after the program runs for many times, the R2 is still stable between 0.7 and 1.0, which proves that the predicted value made by the system is highly approximate to the real value and can achieve the predicted effect.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"140 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74669205","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}
In order to solve the intensifying problem of heavy metal pollution of soil in mining areas, a method for monitoring air quality and soil environment in mining areas based on the Internet of Things is proposed. Using meta-analysis method and health risk assessment method, the impact of mining on soil heavy metal content in Southwest China was quantitatively analyzed, and the relationship between soil heavy metal value and its potential influencing factors was discussed, as well as the heavy metal pollution, ecological risk, and health caused by soil mining activities. Risks were assessed. The results showed that artificial and oral intake were the main modes of soil heavy metal exposure, with the highest daily intakes for noncarcinogenic risk children and the highest daily intakes for carcinogenic risk adult females. The noncarcinogenic risk (HQ>1) of soil As and Pb exposure to children was 3.74 and 1.44, respectively. The carcinogenic risk values of As, Cd, Cr, and Ni in soil were all higher than 10-6, indicating that the carcinogenic risk was within the tolerance range of human body. Children were exposed to the combined noncarcinogenic risk ( HI = 3.83 ), and the risk values of the three types of recipients were 1.19 × 10 − 4 , 1.21 × 10 − 4 , and 1.06 × 10 − 4 , respectively. The correlation between heavy metal content and environmental factors was obtained. It is verified that the system in this paper can effectively monitor the meteorological environment and soil environment, and at the same time, it reveals the pollution law of heavy metals in the soil of the mining area, which provides supporting conditions for future mining and heavy metal pollution management.
{"title":"A Monitoring System for Air Quality and Soil Environment in Mining Areas Based on the Internet of Things","authors":"Hongjing Dai, Dena Huang, Haili Mao","doi":"10.1155/2022/5419167","DOIUrl":"https://doi.org/10.1155/2022/5419167","url":null,"abstract":"In order to solve the intensifying problem of heavy metal pollution of soil in mining areas, a method for monitoring air quality and soil environment in mining areas based on the Internet of Things is proposed. Using meta-analysis method and health risk assessment method, the impact of mining on soil heavy metal content in Southwest China was quantitatively analyzed, and the relationship between soil heavy metal value and its potential influencing factors was discussed, as well as the heavy metal pollution, ecological risk, and health caused by soil mining activities. Risks were assessed. The results showed that artificial and oral intake were the main modes of soil heavy metal exposure, with the highest daily intakes for noncarcinogenic risk children and the highest daily intakes for carcinogenic risk adult females. The noncarcinogenic risk (HQ>1) of soil As and Pb exposure to children was 3.74 and 1.44, respectively. The carcinogenic risk values of As, Cd, Cr, and Ni in soil were all higher than 10-6, indicating that the carcinogenic risk was within the tolerance range of human body. Children were exposed to the combined noncarcinogenic risk (\u0000 \u0000 HI\u0000 =\u0000 3.83\u0000 \u0000 ), and the risk values of the three types of recipients were \u0000 \u0000 1.19\u0000 ×\u0000 \u0000 \u0000 10\u0000 \u0000 \u0000 −\u0000 4\u0000 \u0000 \u0000 \u0000 , \u0000 \u0000 1.21\u0000 ×\u0000 \u0000 \u0000 10\u0000 \u0000 \u0000 −\u0000 4\u0000 \u0000 \u0000 \u0000 , and \u0000 \u0000 1.06\u0000 ×\u0000 \u0000 \u0000 10\u0000 \u0000 \u0000 −\u0000 4\u0000 \u0000 \u0000 \u0000 , respectively. The correlation between heavy metal content and environmental factors was obtained. It is verified that the system in this paper can effectively monitor the meteorological environment and soil environment, and at the same time, it reveals the pollution law of heavy metals in the soil of the mining area, which provides supporting conditions for future mining and heavy metal pollution management.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"58 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85484975","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}
M. Yoosuf, C. Muralidharan, S. Shitharth, Mohammed Alghamdi, Mohammed Maray, O. Rabie
The advancements in communication technologies and a rapid increase in the usage of IoT devices have resulted in an increased data generation rate. Storing, managing, and processing large quantities of unstructured data generated by IoT devices remain a huge challenge to cloud service providers (CSP). To reduce the storage overhead, CSPs implement deduplication algorithms on the cloud storage servers. It identifies and eliminates the redundant data blocks. However, implementing post-progress deduplication schemes does not address the bandwidth issues. Also, existing convergent key-based deduplication schemes are highly vulnerable to confirmation of file attacks (CFA) and can leak confidential information. To overcome these issues, FogDedupe, a fog-centric deduplication framework, is proposed. It performs source-level deduplication on the fog nodes to reduce the bandwidth usage and post-progress deduplication to improve the cloud storage efficiency. To perform source-level deduplication, a distributed index table is created and maintained in the fog nodes, and post-progress deduplication is performed using a multi-key homomorphic encryption technique. To evaluate the proposed FogDedupe framework, a testbed environment is created using the open-source Eucalyptus v.4.2.0 software and fog project v1.5.9 package. The proposed scheme tightens the security against CFA attacks and improves the storage overhead by 27% and reduces the deduplication latency by 12%.
通信技术的进步和物联网设备使用的迅速增加导致了数据生成速率的提高。存储、管理和处理物联网设备生成的大量非结构化数据仍然是云服务提供商(CSP)面临的巨大挑战。为了减少存储开销，云计算服务提供商(csp)在云存储服务器上实现重复数据删除算法。它识别并消除冗余的数据块。但是，实现进度后重复数据删除方案并不能解决带宽问题。同时，现有的基于融合密钥的重复数据删除方案极易受到文件确认攻击(confirmation of file attacks, CFA)的攻击，可能会泄露机密信息。为了克服这些问题，提出了FogDedupe，一个以雾为中心的重复数据删除框架。对雾节点进行源级重复数据删除，降低带宽占用，并进行进度重复数据删除，提高云存储效率。为了执行源级重复数据删除，在雾节点中创建和维护分布式索引表，并使用多密钥同态加密技术执行进度重复数据删除。为了评估建议的FogDedupe框架，使用开源的Eucalyptus v.4.2.0软件和fog项目v1.5.9包创建了一个测试平台环境。该方案加强了对CFA攻击的安全性，将存储开销提高了27%，将重复数据删除延迟降低了12%。
{"title":"FogDedupe: A Fog-Centric Deduplication Approach Using Multi-Key Homomorphic Encryption Technique","authors":"M. Yoosuf, C. Muralidharan, S. Shitharth, Mohammed Alghamdi, Mohammed Maray, O. Rabie","doi":"10.1155/2022/6759875","DOIUrl":"https://doi.org/10.1155/2022/6759875","url":null,"abstract":"The advancements in communication technologies and a rapid increase in the usage of IoT devices have resulted in an increased data generation rate. Storing, managing, and processing large quantities of unstructured data generated by IoT devices remain a huge challenge to cloud service providers (CSP). To reduce the storage overhead, CSPs implement deduplication algorithms on the cloud storage servers. It identifies and eliminates the redundant data blocks. However, implementing post-progress deduplication schemes does not address the bandwidth issues. Also, existing convergent key-based deduplication schemes are highly vulnerable to confirmation of file attacks (CFA) and can leak confidential information. To overcome these issues, FogDedupe, a fog-centric deduplication framework, is proposed. It performs source-level deduplication on the fog nodes to reduce the bandwidth usage and post-progress deduplication to improve the cloud storage efficiency. To perform source-level deduplication, a distributed index table is created and maintained in the fog nodes, and post-progress deduplication is performed using a multi-key homomorphic encryption technique. To evaluate the proposed FogDedupe framework, a testbed environment is created using the open-source Eucalyptus v.4.2.0 software and fog project v1.5.9 package. The proposed scheme tightens the security against CFA attacks and improves the storage overhead by 27% and reduces the deduplication latency by 12%.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"52 1","pages":"1-16"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73875678","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 vertical distribution of winter ozone in the Pearl River Delta in 2021 was analyzed using electrochemical concentration cell (ECC) ozonesonde and compared with the ozone Light detection and ranging (LiDAR) data. The transport of stratospheric ozone to the troposphere was also explored. The results show that (1) the maximum value of the stratospheric ozone layer was about 25 km. The stratospheric ozone profile is mainly unimodal, and the stratospheric ozone content was much higher than that of the troposphere. In the troposphere, the ozone content near the ground (0-2 km) was slightly higher than that between 5 and 15 km. The ozone profile in the upper and middle troposphere showed a peak structure, which was mainly divided into single peak (22%) and multipeak (77%) profiles. (2) In the middle and lower troposphere, the vertical profile of ozone detected by LiDAR is significantly different from that detected by sounding system. The difference between the two ranged from 10 ppb to 60 ppb at the same height. Ozone sounding can supplement the blind area of the near-ground layer by LiDAR ozone detection and can calibrate the inversion results of LiDAR. (3) On January 5, 2022, stratospheric ozone was transported to the troposphere. The stratospheric intrusion occurred due the high wind speed of the subtropical jet centre over Qingyuan and due to strong subsidence movement. When the stratospheric air mass moved to the troposphere, and subsidence airflow encountered, the ozone concentration near the ground was rapidly increased in a short time. It was identified as an “exceptional event.”
{"title":"Analysis of Vertical Distribution of Ozone in Winter and Its Transport from Stratosphere to Troposphere in the Pearl River Delta Region of China","authors":"Cuihua Li, Yangbin Li, Jingman Peng, Ying Chen","doi":"10.1155/2022/9771823","DOIUrl":"https://doi.org/10.1155/2022/9771823","url":null,"abstract":"The vertical distribution of winter ozone in the Pearl River Delta in 2021 was analyzed using electrochemical concentration cell (ECC) ozonesonde and compared with the ozone Light detection and ranging (LiDAR) data. The transport of stratospheric ozone to the troposphere was also explored. The results show that (1) the maximum value of the stratospheric ozone layer was about 25 km. The stratospheric ozone profile is mainly unimodal, and the stratospheric ozone content was much higher than that of the troposphere. In the troposphere, the ozone content near the ground (0-2 km) was slightly higher than that between 5 and 15 km. The ozone profile in the upper and middle troposphere showed a peak structure, which was mainly divided into single peak (22%) and multipeak (77%) profiles. (2) In the middle and lower troposphere, the vertical profile of ozone detected by LiDAR is significantly different from that detected by sounding system. The difference between the two ranged from 10 ppb to 60 ppb at the same height. Ozone sounding can supplement the blind area of the near-ground layer by LiDAR ozone detection and can calibrate the inversion results of LiDAR. (3) On January 5, 2022, stratospheric ozone was transported to the troposphere. The stratospheric intrusion occurred due the high wind speed of the subtropical jet centre over Qingyuan and due to strong subsidence movement. When the stratospheric air mass moved to the troposphere, and subsidence airflow encountered, the ozone concentration near the ground was rapidly increased in a short time. It was identified as an “exceptional event.”","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"6 1","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88840475","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}
Long Li, L. Cheng, Xiang Li, Lingping Yue, Hongbin Zhang
With the continuous progress of UAV technology and 5G technology, the safety and reliability of UAV are gradually improved. In addition, UAV has many advantages, such as light weight, small size, low cost, and fast response in view of the low economy, high labor intensity, low efficiency, and other problems of the traditional inspection of UHV intensive transmission channels. This paper proposes a multi machine collaborative autonomous inspection scheme for UHV dense transmission channels based on 5G technology. This method is to realize the intelligent detection service for UHV dense transmission channels by building a self-service inspection model under the joint cooperation of 5G technology and UAV collaborative operation technology. The research of this paper shows that the multi machine coordinated autonomous inspection scheme of UHV dense transmission channel based on 5G technology constructed in this paper is not only more efficient but also safer than the traditional inspection scheme and single UAV inspection scheme. The related technologies can not only improve the maintenance efficiency of power grid dense transmission channel but also provide theoretical and technical reference for the improvement of multi machine coordinated technology.
{"title":"Research on Multi Machine Cooperative Autonomous Inspection Strategy for UHV Dense Transmission Channel Based on 5G Technology","authors":"Long Li, L. Cheng, Xiang Li, Lingping Yue, Hongbin Zhang","doi":"10.1155/2022/8524817","DOIUrl":"https://doi.org/10.1155/2022/8524817","url":null,"abstract":"With the continuous progress of UAV technology and 5G technology, the safety and reliability of UAV are gradually improved. In addition, UAV has many advantages, such as light weight, small size, low cost, and fast response in view of the low economy, high labor intensity, low efficiency, and other problems of the traditional inspection of UHV intensive transmission channels. This paper proposes a multi machine collaborative autonomous inspection scheme for UHV dense transmission channels based on 5G technology. This method is to realize the intelligent detection service for UHV dense transmission channels by building a self-service inspection model under the joint cooperation of 5G technology and UAV collaborative operation technology. The research of this paper shows that the multi machine coordinated autonomous inspection scheme of UHV dense transmission channel based on 5G technology constructed in this paper is not only more efficient but also safer than the traditional inspection scheme and single UAV inspection scheme. The related technologies can not only improve the maintenance efficiency of power grid dense transmission channel but also provide theoretical and technical reference for the improvement of multi machine coordinated technology.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"1 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81272391","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}
Lijun Wang, Xiangchun Guo, Xiaofan Zhang, Zhanhui Gang
Industrial information security is an important part of the national security strategy that affects the economy and people’s lives. With the rapid development of automation and information technology, common protocols and common hardware and software based on information technology are increasingly used in industrial information control system products and are widely used in industries such as energy, metallurgy, water resource management, chemical, and production. Attacks on critical industrial information can not only cause accidents, losses, and local production pollution but also disrupt the balance of supply and demand of raw materials in the area covered by the system. Therefore, it is of great theoretical and practical importance to study industrial information security as an important measure to ensure the stable operation of the system. In this paper, we analyze the main industrial structure characteristics, external environment, and security requirements and propose a monitoring and warning platform architecture with cryptographic antitheft technology system based on hierarchical modeling and closed-loop control. It can prevent the spread of the attack and reduce its negative impact.
{"title":"Industrial Information Security Detection and Protection: Monitoring and Warning Platform Architecture Design and Cryptographic Antitheft Technology System Upgrade","authors":"Lijun Wang, Xiangchun Guo, Xiaofan Zhang, Zhanhui Gang","doi":"10.1155/2022/1263330","DOIUrl":"https://doi.org/10.1155/2022/1263330","url":null,"abstract":"Industrial information security is an important part of the national security strategy that affects the economy and people’s lives. With the rapid development of automation and information technology, common protocols and common hardware and software based on information technology are increasingly used in industrial information control system products and are widely used in industries such as energy, metallurgy, water resource management, chemical, and production. Attacks on critical industrial information can not only cause accidents, losses, and local production pollution but also disrupt the balance of supply and demand of raw materials in the area covered by the system. Therefore, it is of great theoretical and practical importance to study industrial information security as an important measure to ensure the stable operation of the system. In this paper, we analyze the main industrial structure characteristics, external environment, and security requirements and propose a monitoring and warning platform architecture with cryptographic antitheft technology system based on hierarchical modeling and closed-loop control. It can prevent the spread of the attack and reduce its negative impact.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"31 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90634492","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}
Mobile sink-based data collection in wireless sensor networks has become an attractive research area to mitigate hotspot issues. It further increases the efficiency of the WSN, such as throughput, lifetime, and energy efficiency, while decreasing delay and packet losses. Mobile sink algorithms developed by many researchers in recent years have only contributed to obtain efficient path planning, and only a few researchers have focused on solving the problem of network environment with obstacles. Here, constructing an obstacle-aware path for the mobile sink to collect data in WSN is a challenging issue. In this context, we present the data acquisition through mobile sink for WSNs with obstacles using support vector machine (DAOSVM). The DAOSVM algorithm works in two phases: visiting point selection and path construction. The visiting point selection uses spanning tree approach, and the path selection uses SVM. The computational complexity of the proposed DAOSVM is estimated and compared using the existing techniques, and it is lower. The DAOSVM also outperforms traditional methods concerning multiple performance metrics under various scenarios.
{"title":"Data Acquisition through Mobile Sink for WSNs with Obstacles Using Support Vector Machine","authors":"G. Sulakshana, G. Kamatam","doi":"10.1155/2022/4242740","DOIUrl":"https://doi.org/10.1155/2022/4242740","url":null,"abstract":"Mobile sink-based data collection in wireless sensor networks has become an attractive research area to mitigate hotspot issues. It further increases the efficiency of the WSN, such as throughput, lifetime, and energy efficiency, while decreasing delay and packet losses. Mobile sink algorithms developed by many researchers in recent years have only contributed to obtain efficient path planning, and only a few researchers have focused on solving the problem of network environment with obstacles. Here, constructing an obstacle-aware path for the mobile sink to collect data in WSN is a challenging issue. In this context, we present the data acquisition through mobile sink for WSNs with obstacles using support vector machine (DAOSVM). The DAOSVM algorithm works in two phases: visiting point selection and path construction. The visiting point selection uses spanning tree approach, and the path selection uses SVM. The computational complexity of the proposed DAOSVM is estimated and compared using the existing techniques, and it is lower. The DAOSVM also outperforms traditional methods concerning multiple performance metrics under various scenarios.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"10 1","pages":"1-20"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73481245","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}
Natural resource loss and environmental pollution are the focus of attention at present. Based on the analysis of the coupling relationship between natural resource loss and environmental pollution cost accounting in Chongqing, this paper makes a comprehensive analysis of the accounting results. First of all, we should define the loss of natural resources and set the direction of research and development, establish the ecosystem data model, calculate the environmental pollution cost, and display the calculation results. The results show that (1) air pollution is the focus of environmental pollution. On the premise of ensuring production quality, control the number of emissions from production and reprocess the emissions. (2) In the process of paying attention to water and soil resources, detect and protect water resources and soil, and calculate the ecological value of water resources and soil. Pay attention to the benefits between water and soil and transform and optimize the ecological value system of natural resources.
{"title":"Analysis on the Coupling Relationship between Natural Resource Loss and Environmental Pollution Cost Accounting in Chongqing","authors":"Feng Chen, Zhanxing Zhao","doi":"10.1155/2022/5223502","DOIUrl":"https://doi.org/10.1155/2022/5223502","url":null,"abstract":"Natural resource loss and environmental pollution are the focus of attention at present. Based on the analysis of the coupling relationship between natural resource loss and environmental pollution cost accounting in Chongqing, this paper makes a comprehensive analysis of the accounting results. First of all, we should define the loss of natural resources and set the direction of research and development, establish the ecosystem data model, calculate the environmental pollution cost, and display the calculation results. The results show that (1) air pollution is the focus of environmental pollution. On the premise of ensuring production quality, control the number of emissions from production and reprocess the emissions. (2) In the process of paying attention to water and soil resources, detect and protect water resources and soil, and calculate the ecological value of water resources and soil. Pay attention to the benefits between water and soil and transform and optimize the ecological value system of natural resources.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"10 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75280256","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}
In order to meet the needs of vocal feature recognition, the author proposes a system design based on the Internet of things technology. The principle of the method is that the body sensory layer of the body puts the sound sensors in different positions, records the primary sound signal, and monitors and makes the sound signal using the TMS320VC5402 light red processor. The network transport layer audio signal processes and sends the voice signal database in the process layer. The sound characteristic analysis module in the application layer uses a real-time dynamic change algorithm to obtain the best similarity between the experimental model and the design, identify the characteristics of the sound set red, and identify the content of the voice feature, the music, and the emotional results of the song. Experiments have shown that the system is capable of recognizing speech in a noisy environment, with an accuracy of approximately 95%, resulting in better sound control and the ability to switch switches and remote control. The system, developed with the Internet of things technology, has been proven to improve voice recognition.
{"title":"Design of the Vocal Music Feature Recognition System Based on the Internet of Things Technology","authors":"Haifeng Huang","doi":"10.1155/2022/1164042","DOIUrl":"https://doi.org/10.1155/2022/1164042","url":null,"abstract":"In order to meet the needs of vocal feature recognition, the author proposes a system design based on the Internet of things technology. The principle of the method is that the body sensory layer of the body puts the sound sensors in different positions, records the primary sound signal, and monitors and makes the sound signal using the TMS320VC5402 light red processor. The network transport layer audio signal processes and sends the voice signal database in the process layer. The sound characteristic analysis module in the application layer uses a real-time dynamic change algorithm to obtain the best similarity between the experimental model and the design, identify the characteristics of the sound set red, and identify the content of the voice feature, the music, and the emotional results of the song. Experiments have shown that the system is capable of recognizing speech in a noisy environment, with an accuracy of approximately 95%, resulting in better sound control and the ability to switch switches and remote control. The system, developed with the Internet of things technology, has been proven to improve voice recognition.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"21 11 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83518475","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 a rapid growth in the available resource description framework (RDF) data from disparate domains, the SPARQL query processing with graph structures has become increasingly important. In this pursuit, we designed a two-phase SPARQL query optimization method to process the SPARQL query. The structural characteristics of RDF data graphs, predicate path sequence indices (PPS-indices), were used to efficiently prune the search space, which captured the inherent features of the RDF data graphs, while the database is updated. Our storage model was based on a relational database. Compared to a baseline solution, the proposed method effectively reduced the cardinalities of the intermediate results during the query processing, and at least an order of magnitude improvement is achieved in filtering performance, thereby improving the efficiency of the query execution.
{"title":"A Two-Phase Method for Optimization of the SPARQL Query","authors":"Xiaoqing Lin, Dongyang Jiang","doi":"10.1155/2022/4624856","DOIUrl":"https://doi.org/10.1155/2022/4624856","url":null,"abstract":"With a rapid growth in the available resource description framework (RDF) data from disparate domains, the SPARQL query processing with graph structures has become increasingly important. In this pursuit, we designed a two-phase SPARQL query optimization method to process the SPARQL query. The structural characteristics of RDF data graphs, predicate path sequence indices (PPS-indices), were used to efficiently prune the search space, which captured the inherent features of the RDF data graphs, while the database is updated. Our storage model was based on a relational database. Compared to a baseline solution, the proposed method effectively reduced the cardinalities of the intermediate results during the query processing, and at least an order of magnitude improvement is achieved in filtering performance, thereby improving the efficiency of the query execution.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"14 1","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75815446","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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