Resource scheduling in a fair and efficient manner is a significant challenge in the Internet of Things. Although unequal clustering is an effective technique for alleviating the “energy holes” problem in multihop communication, resource scheduling based on unequal clustering is scarcely conducted. In the present study, a new resource scheduling based on unequal clustering in the Internet of Things (RSUC) is proposed. In RSUC, unequal clustering and multihop routing are considered, and the “energy holes” problem is alleviated effectively. RSUC includes resource scheduling of intracluster communication and intercluster communication. In resource scheduling of intracluster communication, according to the threshold of the number of cluster members, the cluster heads (CHs) recycle resources of failed nodes. In resource scheduling of intercluster communication, CHs in the different layers based on transmission chain obtain different sending and receiving time slots. In RSUC, CHs that are near the base station (BS) have fewer intracluster communication time slots and more intercluster communication time slots. Clusters that are further away from the BS end intercluster communication earlier and enter into intracluster communication instead of waiting for all CHs to complete intercluster communication. The simulation results reveal that RSUC significantly increases the network throughput and reduces the energy consumption of the Internet of Things.
{"title":"Resource Scheduling Based on Unequal Clustering in Internet of Things","authors":"Hongying Bai, Xiaotong Zhang, Yingdong Xie, Haiyan Gong, Zhuang Li, Shilong Liu","doi":"10.1155/2022/1810704","DOIUrl":"https://doi.org/10.1155/2022/1810704","url":null,"abstract":"Resource scheduling in a fair and efficient manner is a significant challenge in the Internet of Things. Although unequal clustering is an effective technique for alleviating the “energy holes” problem in multihop communication, resource scheduling based on unequal clustering is scarcely conducted. In the present study, a new resource scheduling based on unequal clustering in the Internet of Things (RSUC) is proposed. In RSUC, unequal clustering and multihop routing are considered, and the “energy holes” problem is alleviated effectively. RSUC includes resource scheduling of intracluster communication and intercluster communication. In resource scheduling of intracluster communication, according to the threshold of the number of cluster members, the cluster heads (CHs) recycle resources of failed nodes. In resource scheduling of intercluster communication, CHs in the different layers based on transmission chain obtain different sending and receiving time slots. In RSUC, CHs that are near the base station (BS) have fewer intracluster communication time slots and more intercluster communication time slots. Clusters that are further away from the BS end intercluster communication earlier and enter into intracluster communication instead of waiting for all CHs to complete intercluster communication. The simulation results reveal that RSUC significantly increases the network throughput and reduces the energy consumption of the Internet of Things.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"14 1","pages":"1810704:1-1810704:14"},"PeriodicalIF":0.0,"publicationDate":"2022-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84914249","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 whale optimization algorithm (WOA) is a popular swarm intelligence algorithm which simulates the hunting behavior of humpback whales. WOA has the deficiency of easily falling into the local optimal solutions. In order to overcome the weakness of the WOA, a modified variant of WOA called OCDWOA is proposed. There are four main operators introduced into the OCDWOA to enhance the search performance of WOA. The operators include opposition-based learning method, nonlinear parameter design, density peak clustering strategy, and differential evolution. The proposed algorithm is tested on 19 optimization benchmark functions and a seismic inversion problem. OCDWOA is compared with the classical WOA and three typical variants of WOA. The results demonstrate that OCDWOA outperforms the compared algorithms in terms of obtaining the global optimal solution.
{"title":"A Modified Whale Optimization Algorithm and Its Application in Seismic Inversion Problem","authors":"Xiaodan Liang, Siwen Xu, Yang Liu, Liling Sun","doi":"10.1155/2022/9159130","DOIUrl":"https://doi.org/10.1155/2022/9159130","url":null,"abstract":"The whale optimization algorithm (WOA) is a popular swarm intelligence algorithm which simulates the hunting behavior of humpback whales. WOA has the deficiency of easily falling into the local optimal solutions. In order to overcome the weakness of the WOA, a modified variant of WOA called OCDWOA is proposed. There are four main operators introduced into the OCDWOA to enhance the search performance of WOA. The operators include opposition-based learning method, nonlinear parameter design, density peak clustering strategy, and differential evolution. The proposed algorithm is tested on 19 optimization benchmark functions and a seismic inversion problem. OCDWOA is compared with the classical WOA and three typical variants of WOA. The results demonstrate that OCDWOA outperforms the compared algorithms in terms of obtaining the global optimal solution.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"6 1","pages":"9159130:1-9159130:18"},"PeriodicalIF":0.0,"publicationDate":"2022-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89881033","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}
Industrial Internet of Things (IIoT) has attracted much attention from global researchers and has been applied into many fields, such as medical treatment, transportation, and education. This paper pays attention to an IIoT-oriented education problem and gives the corresponding solution. Heterogeneous educational resources have multisource target data, so it is necessary to integrate the repetitive data and data with the same attributes. However, due to the poor tracking effect of the model constructed by traditional methods, the mining technology loses a part of the data characteristics and affects the multisource foreign language education data integration. So this article studies the integration mechanism of foreign language heterogeneous educational resources based on time series analysis. The mechanism adopts a data cleaning and fusion method based on the time series similarity measurement. This method uses approximate symbol aggregation, European algorithm, and similar sequences with adjusted similarity weights to complete the data cleaning of foreign language heterogeneous educational resources. After that, it uses multiple heterogeneous data fusion algorithms to complete data integration. Experiments with foreign language education resources at all levels in a certain city show that the mechanism can detect abnormal data of foreign language education resources, fill in vacant data, reduce data redundancy, and integrate heterogeneous data. After the data are cleaned by multisource heterogeneous data fusion algorithm, the credibility of the measurement data is reflected, and the mean absolute percentage error is only 6.25%. The data quality is improved as a whole, and it provides reliable basic data for the application of foreign language education resources.
工业物联网(Industrial Internet of Things, IIoT)受到全球研究人员的广泛关注，并已应用于医疗、交通、教育等诸多领域。本文关注了一个面向物联网的教育问题，并给出了相应的解决方案。异构教育资源具有多源目标数据，需要对重复数据和具有相同属性的数据进行整合。然而，由于传统方法构建的模型跟踪效果较差，挖掘技术失去了部分数据特征，影响了多源外语教育数据的集成。为此，本文基于时间序列分析对外语异质教育资源整合机制进行了研究。该机制采用了一种基于时间序列相似性度量的数据清洗和融合方法。该方法采用近似符号聚合、欧式算法和调整相似权值的相似序列来完成外语异构教育资源的数据清洗。之后，采用多种异构数据融合算法完成数据集成。对某市各级外语教育资源的实验表明，该机制可以检测外语教育资源异常数据，填补空缺数据，减少数据冗余，整合异构数据。采用多源异构数据融合算法对数据进行清洗后，体现了测量数据的可信度，平均绝对百分比误差仅为6.25%。数据质量整体提高，为外语教育资源的应用提供了可靠的基础数据。
{"title":"Integration Mechanism of Heterogeneous Foreign Language Education Resources Based on Time Series Analysis in IIoT","authors":"Hong Jin","doi":"10.1155/2022/5309556","DOIUrl":"https://doi.org/10.1155/2022/5309556","url":null,"abstract":"Industrial Internet of Things (IIoT) has attracted much attention from global researchers and has been applied into many fields, such as medical treatment, transportation, and education. This paper pays attention to an IIoT-oriented education problem and gives the corresponding solution. Heterogeneous educational resources have multisource target data, so it is necessary to integrate the repetitive data and data with the same attributes. However, due to the poor tracking effect of the model constructed by traditional methods, the mining technology loses a part of the data characteristics and affects the multisource foreign language education data integration. So this article studies the integration mechanism of foreign language heterogeneous educational resources based on time series analysis. The mechanism adopts a data cleaning and fusion method based on the time series similarity measurement. This method uses approximate symbol aggregation, European algorithm, and similar sequences with adjusted similarity weights to complete the data cleaning of foreign language heterogeneous educational resources. After that, it uses multiple heterogeneous data fusion algorithms to complete data integration. Experiments with foreign language education resources at all levels in a certain city show that the mechanism can detect abnormal data of foreign language education resources, fill in vacant data, reduce data redundancy, and integrate heterogeneous data. After the data are cleaned by multisource heterogeneous data fusion algorithm, the credibility of the measurement data is reflected, and the mean absolute percentage error is only 6.25%. The data quality is improved as a whole, and it provides reliable basic data for the application of foreign language education resources.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"17 1","pages":"5309556:1-5309556:7"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74433481","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}
Autism, a developmental disorder affecting social and communication skills, differs from most the mental handicap in showing a characteristic pattern of poor, intact, and even superior cognitive abilities. This study aims to solve the mismatch of the teaching content and mental health education for autistic children. Inspired by artificial intelligence, an improved neural network matrix factorization (NeuMF) model is designed based on the theory of collaborative filtering, and time data is added to improve the NeuMF by using the K-means clustering algorithm. Several evaluation indexes such as root mean square error (RMSE) and mean absolute error (MAE) are selected to assess the performance of the proposed model. Results show that RMSE and MAE of the improved NeuMF model are 1.251 and 0.625, respectively, which are better than collaborative filtering and traditional neural network factorization models. Moreover, the proposed model is used to recommend the activities of physical education (PE) for developing the intelligence of autistic children. This proves that the optimized model has better performance and can be used to recommend online courses for autistic users. This dynamic personalized curriculum recommendations model can help autistic children recover in a short time.
{"title":"Recommendation Optimization of Physical Education for Developing the Intelligence of Autistic Children following Intelligent Collaborative Filtering Algorithm","authors":"Hongzhong Hao, Sheng Hu","doi":"10.1155/2022/1388872","DOIUrl":"https://doi.org/10.1155/2022/1388872","url":null,"abstract":"Autism, a developmental disorder affecting social and communication skills, differs from most the mental handicap in showing a characteristic pattern of poor, intact, and even superior cognitive abilities. This study aims to solve the mismatch of the teaching content and mental health education for autistic children. Inspired by artificial intelligence, an improved neural network matrix factorization (NeuMF) model is designed based on the theory of collaborative filtering, and time data is added to improve the NeuMF by using the K-means clustering algorithm. Several evaluation indexes such as root mean square error (RMSE) and mean absolute error (MAE) are selected to assess the performance of the proposed model. Results show that RMSE and MAE of the improved NeuMF model are 1.251 and 0.625, respectively, which are better than collaborative filtering and traditional neural network factorization models. Moreover, the proposed model is used to recommend the activities of physical education (PE) for developing the intelligence of autistic children. This proves that the optimized model has better performance and can be used to recommend online courses for autistic users. This dynamic personalized curriculum recommendations model can help autistic children recover in a short time.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"34 1","pages":"1388872:1-1388872:9"},"PeriodicalIF":0.0,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85136600","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 influence of many factors such as machining and working environment, the robot kinematics model has errors, which leads to the inaccuracy of the actual position and pose. Therefore, in order to solve this problem, this paper proposes a method based on the genetic algorithm to directly modify the rotation variables of the manipulator joint to improve the positioning accuracy of the manipulator. Through the establishment of the mechanical kinematics model and the error model, the solution formula of joint correction is obtained. The actual pose of the end effector of the manipulator is detected by the NDI three-dimensional dynamic displacement measurement system, and the correction value is applied to the control of the designed 6-DOF series manipulator.
{"title":"Robust Optimization of Dynamic Characteristics of Mechanical Structure Combined with Multivariable Predictive Compensation","authors":"Li Zhang","doi":"10.1155/2022/9221522","DOIUrl":"https://doi.org/10.1155/2022/9221522","url":null,"abstract":"Due to the influence of many factors such as machining and working environment, the robot kinematics model has errors, which leads to the inaccuracy of the actual position and pose. Therefore, in order to solve this problem, this paper proposes a method based on the genetic algorithm to directly modify the rotation variables of the manipulator joint to improve the positioning accuracy of the manipulator. Through the establishment of the mechanical kinematics model and the error model, the solution formula of joint correction is obtained. The actual pose of the end effector of the manipulator is detected by the NDI three-dimensional dynamic displacement measurement system, and the correction value is applied to the control of the designed 6-DOF series manipulator.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"39 1","pages":"9221522:1-9221522:7"},"PeriodicalIF":0.0,"publicationDate":"2022-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86604664","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}
Context awareness and mobile factor ubiquity are considered key factors when it comes to mobile technology development and diffusion. Context is vital in interactive applications particularly when the context of users changes frequently and rapidly in the environment of handheld-mobile and ubiquitous technology systems. The understanding of the context and ubiquity in the development and diffusion of mobile government can influence the delivery of efficient public services. Mobile context-aware computing systems can respond to the changes in the environment in an intelligent way to provide a better consumer experience for users. This study explored the impact of context awareness and mobile factor ubiquity on the adoption of mobile government services. The framework of this study was based on the unified theory of acceptance and use of technology (UTAUT). The structural equation model (SEM) with SmartPLS 3.0 was used to conduct the data analysis. The analysis which was based on the 366 samples generated has shown that while context awareness was not significant in determining both the performance and intention to use, it was however significant in determining the effort expectancy of mobile government services. Also, mobile factor ubiquity was found to be a positive predictor of effort expectancy, intention to use, and context awareness. However, the mobile factor ubiquity does not determine the performance expectancy of mobile government services. The implications (managerial and theoretical) of these and other result findings of the study are discussed.
{"title":"The Impact of Context Awareness and Ubiquity on Mobile Government Service Adoption","authors":"Isaac Kofi Mensah, D. S. Mwakapesa","doi":"10.1155/2022/5918826","DOIUrl":"https://doi.org/10.1155/2022/5918826","url":null,"abstract":"Context awareness and mobile factor ubiquity are considered key factors when it comes to mobile technology development and diffusion. Context is vital in interactive applications particularly when the context of users changes frequently and rapidly in the environment of handheld-mobile and ubiquitous technology systems. The understanding of the context and ubiquity in the development and diffusion of mobile government can influence the delivery of efficient public services. Mobile context-aware computing systems can respond to the changes in the environment in an intelligent way to provide a better consumer experience for users. This study explored the impact of context awareness and mobile factor ubiquity on the adoption of mobile government services. The framework of this study was based on the unified theory of acceptance and use of technology (UTAUT). The structural equation model (SEM) with SmartPLS 3.0 was used to conduct the data analysis. The analysis which was based on the 366 samples generated has shown that while context awareness was not significant in determining both the performance and intention to use, it was however significant in determining the effort expectancy of mobile government services. Also, mobile factor ubiquity was found to be a positive predictor of effort expectancy, intention to use, and context awareness. However, the mobile factor ubiquity does not determine the performance expectancy of mobile government services. The implications (managerial and theoretical) of these and other result findings of the study are discussed.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"23 1","pages":"5918826:1-5918826:20"},"PeriodicalIF":0.0,"publicationDate":"2022-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77875871","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}
Venture capital has emerged as an important intermediary in financial markets, providing capital to young high-technology firms that might have otherwise gone unfunded. Venture capitalists have developed a variety of mechanisms to overcome the problems that emerge at each stage of the investment process. This study selected the China Venture (CV) source database for venture capital (VC) research in the Chinese Internet industry and extracted information on investment time, VC firms, and investment amount. Combining theoretical analysis and empirical research, the differences between the leader community and the self-organizing community in the Chinese Internet industry are analyzed and the reasons and paths leading to the change of investment performance are determined. It is found that the information dissemination of core nodes promotes the information dissemination of leaders’ communities and the two kinds of organizational learning have different effects on investment performance in the two communities. Under experimental learning and information dissemination, the investment performance of the leader community is greater than the self-organizing community. The outcomes of this research can be used as a reference for the sustainable development of the Chinese Internet industry.
{"title":"Research on Investment Performance of Venture Capital Network Community in the Internet Industry","authors":"Xiaojie Pei, Xinghua Dang","doi":"10.1155/2022/7373981","DOIUrl":"https://doi.org/10.1155/2022/7373981","url":null,"abstract":"Venture capital has emerged as an important intermediary in financial markets, providing capital to young high-technology firms that might have otherwise gone unfunded. Venture capitalists have developed a variety of mechanisms to overcome the problems that emerge at each stage of the investment process. This study selected the China Venture (CV) source database for venture capital (VC) research in the Chinese Internet industry and extracted information on investment time, VC firms, and investment amount. Combining theoretical analysis and empirical research, the differences between the leader community and the self-organizing community in the Chinese Internet industry are analyzed and the reasons and paths leading to the change of investment performance are determined. It is found that the information dissemination of core nodes promotes the information dissemination of leaders’ communities and the two kinds of organizational learning have different effects on investment performance in the two communities. Under experimental learning and information dissemination, the investment performance of the leader community is greater than the self-organizing community. The outcomes of this research can be used as a reference for the sustainable development of the Chinese Internet industry.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"156 1","pages":"7373981:1-7373981:11"},"PeriodicalIF":0.0,"publicationDate":"2022-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85495934","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 recent years, the coal industry has been expanding the scale and output of coal mining in China, yet the safety in production is faced with great challenge. Communication system in coal mines plays a significant role in production safety, and wireless narrowband data communication network technology is a new-type advantageous measure to construct wireless network security monitoring system for coal mining. Here, a coal mine monitoring signal transmission method based on bus technology and wireless data transmission technology suitable for coal mines is proposed. The corresponding monitoring system is designed, and the system is able to collect the gas concentration and mechanical operation status of the mines. Wireless sensor network nodes are used for the RF communication module. The communication performance of this system in coal and rock medium and the roadway along the goaf is simulated, and the quantitative relationship between the attenuation coefficient of different communication frequencies and the effective communication distance is obtained. Hence, the results show that the protocol has good performance in terms of route establishment, maintenance, and data transmission hop count for the positioning of coal mine employees.
{"title":"A Network Communication Frequency Routing Protocol of Coal Mine Safety Monitoring System Based on Wireless Narrowband Data Communication Network","authors":"J. Zhang, Min Chen, YaHui Liu, Pingjian Yao","doi":"10.1155/2022/4906599","DOIUrl":"https://doi.org/10.1155/2022/4906599","url":null,"abstract":"In recent years, the coal industry has been expanding the scale and output of coal mining in China, yet the safety in production is faced with great challenge. Communication system in coal mines plays a significant role in production safety, and wireless narrowband data communication network technology is a new-type advantageous measure to construct wireless network security monitoring system for coal mining. Here, a coal mine monitoring signal transmission method based on bus technology and wireless data transmission technology suitable for coal mines is proposed. The corresponding monitoring system is designed, and the system is able to collect the gas concentration and mechanical operation status of the mines. Wireless sensor network nodes are used for the RF communication module. The communication performance of this system in coal and rock medium and the roadway along the goaf is simulated, and the quantitative relationship between the attenuation coefficient of different communication frequencies and the effective communication distance is obtained. Hence, the results show that the protocol has good performance in terms of route establishment, maintenance, and data transmission hop count for the positioning of coal mine employees.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"9 1","pages":"4906599:1-4906599:8"},"PeriodicalIF":0.0,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73276553","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}
Tao Zhang, Zhipeng Li, Myung-Cheul Shin, Chunxia Wang, Wenli Song, Lei Lui
There is a lot of noise in the snowboard starting action image, which leads to the low accuracy of snowboard starting action feature extraction. We propose a snowboard starting action feature extraction using visual sensor image processing. Firstly, the overlapping images are separated by laser fringe technology. After separation, the middle point of the image is taken as the feature point, and the interference factors are filtered by laser. Secondly, the three-dimensional model is established by using visual sensing image technology, the action feature images are input in the order of recognition, and all actions are reconstructed and assembled to complete the action feature extraction of snowboard. The interference factors are filtered by laser, the middle part of the action image is extracted according to the common features of multiple images, and its definition is described. The movement change and moving distance are used to count the most features and clarity. Finally, the edge recognition effect of snowboard starting action image and the action recognition effect under multiple complex images are taken as experimental indexes. The results show that the method has a good effect on image edge extraction, the extraction effect is as high as 95%, and the accuracy is as high as 2.1%. In addition, under multiple complex images, the action feature recognition rate is also high, which can prove that the method studied has better accuracy in snowboard starting action feature extraction.
{"title":"Feature Extraction Method of Snowboard Starting Action Using Vision Sensor Image Processing","authors":"Tao Zhang, Zhipeng Li, Myung-Cheul Shin, Chunxia Wang, Wenli Song, Lei Lui","doi":"10.1155/2022/2829547","DOIUrl":"https://doi.org/10.1155/2022/2829547","url":null,"abstract":"There is a lot of noise in the snowboard starting action image, which leads to the low accuracy of snowboard starting action feature extraction. We propose a snowboard starting action feature extraction using visual sensor image processing. Firstly, the overlapping images are separated by laser fringe technology. After separation, the middle point of the image is taken as the feature point, and the interference factors are filtered by laser. Secondly, the three-dimensional model is established by using visual sensing image technology, the action feature images are input in the order of recognition, and all actions are reconstructed and assembled to complete the action feature extraction of snowboard. The interference factors are filtered by laser, the middle part of the action image is extracted according to the common features of multiple images, and its definition is described. The movement change and moving distance are used to count the most features and clarity. Finally, the edge recognition effect of snowboard starting action image and the action recognition effect under multiple complex images are taken as experimental indexes. The results show that the method has a good effect on image edge extraction, the extraction effect is as high as 95%, and the accuracy is as high as 2.1%. In addition, under multiple complex images, the action feature recognition rate is also high, which can prove that the method studied has better accuracy in snowboard starting action feature extraction.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"50 1","pages":"2829547:1-2829547:9"},"PeriodicalIF":0.0,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79422645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To better conform to the development trend of economic globalization, modern enterprises need to continuously innovate in technology, so as to provide enterprises with better products. The technological innovation level of economic innovation subjects is rising day by day, and the technological innovation level of enterprises has become more and more prominent. An excellent corporate culture will help technological innovation. The company uses corporate culture to shape its corporate image and spirit, thereby creating an atmosphere for technological innovation and bringing success to technological innovation. Corporate culture and technological innovation are two important elements to strengthen the company’s core competitiveness, which directly affect the company’s sustainable development level. Based on the previous analysis, we constructed an integrated model of corporate culture and technological innovation based on deep learning methods, analyzed the effect of corporate culture construction on corporate technological innovation capabilities, and sought measures to establish corporate culture.
{"title":"Influence of Enterprise Culture Construction on Technological Innovation Ability Based on Deep Learning","authors":"Hengshan Yang, Lu-yao Wang","doi":"10.1155/2022/7533230","DOIUrl":"https://doi.org/10.1155/2022/7533230","url":null,"abstract":"To better conform to the development trend of economic globalization, modern enterprises need to continuously innovate in technology, so as to provide enterprises with better products. The technological innovation level of economic innovation subjects is rising day by day, and the technological innovation level of enterprises has become more and more prominent. An excellent corporate culture will help technological innovation. The company uses corporate culture to shape its corporate image and spirit, thereby creating an atmosphere for technological innovation and bringing success to technological innovation. Corporate culture and technological innovation are two important elements to strengthen the company’s core competitiveness, which directly affect the company’s sustainable development level. Based on the previous analysis, we constructed an integrated model of corporate culture and technological innovation based on deep learning methods, analyzed the effect of corporate culture construction on corporate technological innovation capabilities, and sought measures to establish corporate culture.","PeriodicalId":18790,"journal":{"name":"Mob. Inf. Syst.","volume":"146 1","pages":"7533230:1-7533230:12"},"PeriodicalIF":0.0,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88638510","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：